diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_1.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_1.txt new file mode 100644 index 0000000..367164b --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_1.txt @@ -0,0 +1,160 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts and running a command-line tool with those prompts, using the simple language model "mixtral" hosted on AgentArtificial's servers. + +The `do_apply_list` function takes three arguments: a function to run a command (`run_cmd`), a function to generate command-line arguments (`make_args`), and a list of type names (`type_terms`). It then generates prompts for each combination of a type name, verb, place, and optional term or place modifier. + +The `run_cmd` function takes a list of strings as arguments, concatenates them with spaces into a single string, and then runs that command using the `Unix.open_process_in` function to open a process, read its output, and print it. + +The main part of the script calls `do_apply_list` with the three functions as arguments, generating and running prompts for each combination of type name, verb, place, and optional modifiers. + +If this code were executed in the context of a fantasy role-playing game, it would generate prompts for the language model to use when creating descriptions, items, spells, challenges, and other elements of the game world. The resulting output could be used as input to a game engine or another tool for generating game content. + +To simulate the execution of this code, you could imagine running each generated command and seeing what output it produces. For example, one prompt might be: +```vbnet +"We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : create; Type Name: weapon; Place: the chest What is your response? Please generate variant array of size 3" +``` +The resulting output might be a list of three different weapons, such as "a gleaming steel sword", "a rusty iron dagger", and "a cursed elven bow". These items could then be used in the game world as treasure or loot for players to find. + +Overall, this code is an example of how a language model can be integrated into a game development pipeline to generate content for a fantasy role-playing game. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_10.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_10.txt new file mode 100644 index 0000000..27d8ea9 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_10.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts to create a fantasy role-playing game's dungeon generator using a large language model and a proof engine combined via an adaptive language agent architecture. It constructs various combinations of verbs, nouns, adjectives, places, and type names to form prompts, which are then passed as arguments to the `run_cmd` function that executes the command with those generated arguments. + +If we were to simulate its execution, it would generate a series of commands using different combinations of verbs, nouns, adjectives, places, and type names, run them in a terminal-like environment, and display the output for each command. The resulting game from this script would be a text-based fantasy role-playing game with dungeons generated based on the prompts created by the script. + +The game's experience would involve exploring various dungeons, fighting monsters, collecting treasures, completing quests, and solving challenges. The game's narrative and environment would be influenced by the type names, verbs, adjectives, places, and other elements used in the prompts generated by the script. + +To rephrase your question: How would the game experience be like if we simulated the execution of this OCaml code and imagined running each command and its corresponding output? +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_11.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_11.txt new file mode 100644 index 0000000..2fa244c --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_11.txt @@ -0,0 +1,160 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts to train a language model in the context of creating a dungeon generator for a fantasy role-playing game. It uses the Adaptive Language Agent Architecture (ALAA) combined with a proof engine. The script defines various lists of terms, verbs, and places, and then iterates through them to create prompts. These prompts are used as input for the language model, which generates responses that will be used to build the dungeon generator. + +The `do_apply_list` function is responsible for generating the prompts by combining elements from the `type_terms`, `top_terms`, `verbs`, and `places` lists. It applies the `run_cmd` function with the appropriate arguments to execute the command that generates the prompts. + +The `run_cmd` function executes a command by constructing it from an array of arguments, then opens a subprocess to run the command and prints its output. + +To simulate the execution of this script, imagine running the code and visualizing the output it would generate for each combination of terms, verbs, and places. The game would be a text-based fantasy role-playing experience where players explore dungeons with different themes, challenges, monsters, quests, treasures, and other elements. Each dungeon would have been generated based on prompts created by the language model using the Adaptive Language Agent Architecture (ALAA) combined with a proof engine. + +Here's an example of how one prompt might look like: + +Type Name: Sword +Try number: 1 +Verb: crafting +Place: a blacksmith shop connected with a forge +Prompt: "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : crafting; Type Name: Sword; Place: a blacksmith shop connected with a forge What is your response? Please generate variant array of size 1" + +The `run_cmd` function would then execute the command using this prompt, which would be used to generate responses from the language model that will help build the dungeon generator. The process is repeated multiple times with different combinations of terms, verbs, and places. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_12.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_12.txt new file mode 100644 index 0000000..0758c24 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_12.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It appears to be part of a larger program that generates descriptions for a fantasy role-playing game. The script defines several lists of terms and verbs, as well as functions to construct command-line arguments for invoking the `simple` executable with different combinations of these terms and verbs. + +The main function `do_apply_list` invokes the `run_cmd` function with different combinations of terms, verbs, and places to generate descriptions. The `run_cmd` function takes a list of command-line arguments and invokes the `simple` executable with those arguments using the `Unix.open_process_in` function. It then reads the output of the `simple` executable and prints it to the console. + +Based on the code, it seems that the larger program is a game generator that uses a language model and a proof engine combined via an adaptive language agent architecture. The script defines several functions to generate descriptions for different types of game elements such as weapons, spells, artifacts, treasure, monsters, quests, challenges, themes, drama, music, art, secrets, occult, reveal, and hero journeys. + +The generated descriptions are saved in text files with the naming convention `.new_iVERB TYPE NAME PLACE.txt`, where `i` is an integer representing the index of the description, `VERB` is the verb used to generate the description, `TYPE` is the type of game element being described, and `PLACE` is the place associated with the description. + +Overall, it seems that the larger program is a sophisticated game generator that uses natural language processing and adaptive language agent architecture to generate descriptions for different types of game elements. The generated descriptions are then used to create a rich and immersive game world for players to explore. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_13.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_13.txt new file mode 100644 index 0000000..f54d320 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_13.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts for a language model to create descriptions for a fantasy role-playing game dungeon generator. The script uses a combination of predefined terms, verbs, and place names to generate prompts, which are then passed as arguments to a command-line tool called "simple" along with the OpenAI API endpoint and other flags. + +The script runs the generated prompts through the "simple" tool three times, using different combinations of terms, verbs, and place names each time. The output for each prompt is printed to the console. + +To simulate the execution of this code, you can imagine running the script and observing the output it generates. Based on the provided prompts, the game would likely feature a variety of different types of weapons, spells, artifacts, magic items, treasures, monsters, quests, challenges, themes, dramas, music, art, secrets, occult elements, reveals, and hero journeys. + +The generated descriptions for these elements would be tailored to fit the specified place names and verbs, such as "Imagine a weapon with a magical enchantment in a dark cavern" or "Consider a spell that can control the elements in a lush garden". The script also uses terms like "role-play", "create", "analyze", and "quasi-quine-quote" to prompt the language model to generate more complex and creative descriptions. + +Overall, the game generated from this code would be a richly detailed and immersive fantasy role-playing experience, with a wide variety of elements and descriptions to explore and interact with. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_14.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_14.txt new file mode 100644 index 0000000..7df811b --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_14.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts to create variant arrays of descriptions for a fantasy role-playing game dungeon generator using a large language model and a proof engine combined via an adaptive language agent architecture. The script defines various lists of terms, verbs, places, and types that are used to generate the prompts. + +The `do_apply_list` function takes a `run_cmd` function, which is responsible for executing the generated command with the given arguments. It also takes a list of type terms, which are used as the base for generating descriptions. The function then iterates over all possible combinations of top terms, type terms, verbs, and places to generate prompts. For each prompt, it creates a list of arguments using the `make_args` function, which constructs the command to be executed by concatenating the various components of the argument list. The generated commands are then executed using the `run_cmd` function. + +The script generates and executes multiple commands, each with a different combination of type terms, verbs, and places. The generated descriptions are saved in separate text files with unique names. The output of each command is printed to the console. + +To simulate the execution of this code, one can imagine running the script and observing the output. The resulting game would be a fantasy role-playing game with a dungeon generator that uses large language model and proof engine to create descriptions for various elements such as weapons, spells, artifacts, treasure, monsters, quests, challenges, themes, drama, music, art, secrets, occult, reveal, and hero journey. The generated descriptions would vary in style, tone, and content depending on the combination of type terms, verbs, and places used in the prompt. Overall, the game would have a rich and diverse narrative that would engage players and provide them with an immersive experience. + +To rewrite the question, one could ask: "What kind of fantasy role-playing game could be created using the provided OCaml script for generating prompts to create variant arrays of descriptions?" +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_15.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_15.txt new file mode 100644 index 0000000..c31a6ef --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_15.txt @@ -0,0 +1,154 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The given code is a script written in OCaml, a functional programming language. It appears to be part of a larger program used for generating descriptions and content for a fantasy role-playing game. The script defines several lists of terms, verbs, and place names that will be used as input to the main function. + +The main function `do_apply_list` takes three arguments: `run_cmd`, `make_args`, and `type_terms`. It uses these inputs to generate a series of commands, which are then executed using the `run_cmd` function. The output of each command is printed to the console. + +The `run_cmd` function takes a list of strings as input, concatenates them into a single string, and then executes that string as a shell command. The output of the command is captured and printed to the console. + +The `make_args` function generates a list of arguments for the `run_cmd` function based on the type name, index, verb, and place name provided as input. These arguments include the name of the script to run, the OpenAI binding, the model name, the test name, the output file name, the prompt string, and the URL of the server to connect to. + +The `do_apply_list` function applies the `run_cmd` function to a series of inputs generated from the `type_terms`, `verbs`, and `places` lists. It does this for each combination of type term, verb, and place name, resulting in a large number of commands being executed. + +Overall, it seems that this code is used to generate descriptions and content for a fantasy role-playing game using a language model and a proof engine. The output of the script would be a series of text files containing generated descriptions based on the input provided. These descriptions could then be used as input to further stages of the game development process. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_16.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_16.txt new file mode 100644 index 0000000..80331bc --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_16.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The given code is a script written in OCaml, a general-purpose programming language with an emphasis on formal methods and static type checking. The script appears to be part of a larger program used for generating descriptions for a fantasy role-playing game using a large language model and a proof engine combined via adaptive language agent architecture. + +The script defines several lists of terms, verbs, and places that are used in the generation of prompts for the language model. The main function `do_apply_list` takes three arguments: `run_cmd`, `make_args`, and `type_terms`. The function uses nested loops to iterate through all possible combinations of these terms, verbs, and places, generating prompts for the language model with each combination. + +The `run_cmd` function takes a list of arguments and runs the command with those arguments using OCaml's built-in `Unix.open_process_in` function. The output of the command is then printed to the console. + +The script uses the `make_args` function to generate a list of arguments for each combination of terms, verbs, and places. The `prompt` function generates the actual prompt text that is passed as an argument to the language model. + +Overall, the script appears to be part of a larger system for generating descriptions for a fantasy role-playing game using natural language processing and formal methods. The generated descriptions could be used for a variety of purposes, such as creating in-game text or player guides. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_17.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_17.txt new file mode 100644 index 0000000..d263d50 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_17.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It appears to be generating prompts for a language model to create descriptions for a fantasy role-playing game dungeon generator. The script uses the `simple` command, which likely runs an executable file named `simple.exe`, and passes it various arguments constructed in the `make_args` function. These arguments include the type of object to be generated, the number of variants to generate, a verb, a place, and a prompt string that is used to generate the descriptions. + +The script then calls the `run_cmd` function with the constructed arguments, which runs the `simple` command with those arguments using the `Unix.open_process_in` function. The output of the command is printed to the console. + +The script uses a loop and nested loops to generate various combinations of type, verb, and place for the prompts, resulting in a total of 3 x 7 x 7 x 7 x 7 = 68,601 prompts being generated and run. The generated descriptions are not used or saved in this script, so it's likely that they are intended to be used as input for another program or system. + +In terms of the game itself, it's hard to say exactly what it would be like without more context. However, based on the prompts being generated, it seems that the game would involve exploring a dungeon and encountering various objects, such as weapons, spells, artifacts, and treasures, as well as monsters and quests. The language model's descriptions of these objects and encounters would likely add flavor and detail to the game, helping to immerse players in the fantasy world. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_18.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_18.txt new file mode 100644 index 0000000..7167c3e --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_18.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts to train a language model for a fantasy role-playing game. The script defines several lists of terms related to the game, such as weapons, spells, monsters, and places. It then uses these terms to construct prompts for the language model by combining different elements from the lists. + +The main function `do_apply_list` takes a `run_cmd` function, which is responsible for executing a command with a given set of arguments. The function iterates over all possible combinations of terms in the lists and generates a prompt using the `make_args` helper function. This function constructs an array of strings that represent the command line arguments for running the language model with the generated prompt. + +The script then calls `run_cmd` with the constructed arguments to execute the command and print the output. The output is not shown in the provided code, but it would typically be the text generated by the language model in response to the given prompt. + +Overall, the script generates a large number of prompts for training the language model, covering various aspects of the game's world and mechanics. Once trained, the language model could be used to generate descriptions, dialogues, and other textual content for the game. The proof engine mentioned in the comment at the beginning of the code is not actually used in this script, but it might be used in conjunction with the language model to ensure the consistency and accuracy of the generated text. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_19.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_19.txt new file mode 100644 index 0000000..6550c9f --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_19.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It appears to be part of a larger system for generating descriptions of dungeons for a fantasy role-playing game using a large language model and a proof engine combined via adaptive language agent architecture. + +The script defines several lists of terms, verbs, and places, as well as some other variables. The main function `do_apply_list` takes three arguments: `run_cmd`, `make_args`, and `type_terms`. It uses these arguments to generate and execute a series of command-line commands that call the large language model with different combinations of terms, verbs, and places. + +The output of each command is printed to the console. The generated descriptions are not used for any further processing in this script. + +To simulate the execution of this code, you could imagine running each of the generated commands and seeing the output that would be produced. Based on the terms, verbs, and places defined in the script, the generated descriptions would likely involve dungeons with different types of weapons, spells, artifacts, monsters, quests, challenges, themes, drama, music, art, secrets, occult elements, reveals, and hero journeys. The dungeons might be located in various places such as countries, regions, cities, streets, houses, buildings, dungeons, labyrinths, caves, swamps, rooms, hallways, chests, bags, wallets, vaults, keeps, or hideouts. + +The game generated by this code would likely be a text-based role-playing game where players explore different dungeons and encounter various challenges and obstacles. The descriptions of the dungeons and their contents would be generated on the fly using the large language model, providing a dynamic and immersive experience for the players. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_2.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_2.txt new file mode 100644 index 0000000..80a6990 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_2.txt @@ -0,0 +1,153 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts to create descriptions for a fantasy role-playing game's dungeon generator using a large language model and a proof engine combined via adaptive language agent architecture. It generates a list of arguments (`args`) based on different combinations of type terms, top terms, verbs, and places, then runs the command with those arguments to generate descriptions for the game's assets. + +To simulate its execution, you can imagine running this script and visualize what it would do: + +1. It defines some lists containing type terms (e.g., "weapon", "spell"), top terms (e.g., "Imagine", "Consider"), verbs (e.g., "role-play", "specify"), and places (e.g., "the country", "the city"). +2. The `do_apply_list` function generates combinations of these lists and calls the `run_cmd` function for each combination, which runs a command to generate descriptions based on those combinations. +3. The `make_args` function creates an array of arguments, including the type name, index (i), verb, and place, using the provided lists and other variables. These arguments are then passed to the `run_cmd` function. +4. Finally, the `do_apply_list` function iterates through all combinations and calls the `run_cmd` function for each one, generating descriptions based on those combinations. + +To answer your question, if you were to execute this code, it would generate a series of prompts asking the large language model to create descriptions for different assets in a fantasy role-playing game's dungeon generator, such as weapons, spells, and monsters, using various verbs and places. The generated descriptions would then be used to build a richer and more engaging gaming experience. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_20.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_20.txt new file mode 100644 index 0000000..5854f1b --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_20.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts to train a language model in the context of building a dungeon generator for a fantasy role-playing game. The script uses a combination of predefined terms, verbs, and places to create different types of dungeons with various features. + +The script defines several lists containing terms related to different aspects of the game, such as weapons, spells, monsters, and treasure. It also includes a list of verbs that describe actions or states, like "role-play," "create," and "analyze." Finally, there is a list of places where the dungeons can be located. + +The main function in the script, `do_apply_list`, applies all possible combinations of terms, verbs, and places to generate prompts for the language model. It uses the `run_cmd` function to execute an external command that generates a variant array (i.e., multiple outputs) based on the provided prompt. + +The generated dungeons will likely include various features and elements based on the predefined lists, resulting in diverse and engaging gameplay experiences. Since the script uses a language model trained with these prompts, the output is not immediately available but must be simulated by running the code and observing its output. + +To improve understanding of the generated dungeons, it would be helpful to rephrase the question as follows: "How would the fantasy role-playing game experience be influenced by the dungeons generated using this OCaml script? What kind of features and challenges can players expect based on the predefined lists used in the script?" +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_21.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_21.txt new file mode 100644 index 0000000..21930f1 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_21.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The given code is a script written in OCaml, a functional programming language. It appears to be part of a larger system for generating descriptions of dungeons for a fantasy role-playing game using a large language model and a proof engine combined via adaptive language agent architecture. + +The script defines several lists of terms related to different aspects of the game, such as weapons, spells, monsters, quests, etc. It also defines some utility functions for constructing command-line arguments and running commands. The main function `do_apply_list` takes a function `run_cmd` for executing commands, a function `make_args` for constructing command-line arguments, and a list of type terms, and generates and runs multiple commands by combining different elements from the lists. + +The generated commands are executed using the `run_cmd` function, which opens a subprocess and reads its output. The output is printed to the console. + +Overall, it seems like this script is part of a larger system for generating game content using natural language processing techniques. It might be used to generate descriptions of different parts of a dungeon in a fantasy role-playing game, such as rooms, treasures, monsters, and quests. The generated descriptions could then be used as input to other systems or tools for creating game assets, such as art, music, or game mechanics. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_22.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_22.txt new file mode 100644 index 0000000..0367a59 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_22.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It appears to be generating prompts for a language model to create descriptions for a fantasy role-playing game dungeon generator. The script uses the `simple` command to run the `simple.exe` program with various arguments, which include the name of the model, the type of object to generate, the number of variants to generate, and the prompt for the language model. + +The script iterates through a list of types (such as "weapon" or "spell"), verbs (such as "create" or "design"), and places (such as "the country" or "the dungeon") to create prompts for the language model. For example, one prompt might be: + +"We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : create; Type Name: weapon; Place: the country What is your response? Please generate variant array of size 3" + +The script then runs the `simple` command with this prompt and other arguments to generate a description for a weapon in the country. This process is repeated multiple times with different types, verbs, and places to create a variety of descriptions. + +Overall, the script seems to be part of a larger project for generating content for a fantasy role-playing game using a language model and other tools. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_23.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_23.txt new file mode 100644 index 0000000..8effc48 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_23.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It appears to be part of a larger program that generates descriptions for a fantasy role-playing game. The script uses a language model and a proof engine combined via adaptive language agent architecture to generate variant arrays of strings based on given context. + +The main function `do_apply_list` takes three arguments: `run_cmd`, `make_args`, and `type_terms`. It iterates through a list of top-level terms, types, and verbs, and for each combination, it generates a set of commands to be executed by the `run_cmd` function. The commands are generated using the `make_args` function, which takes four arguments: `type_name`, `i`, `verb`, and `place`. + +The `run_cmd` function takes a list of strings that represent command line arguments and executes the corresponding command. In this case, it runs the command using the `Unix.open_process_in` function, which opens a process and returns an input channel that can be used to read its output. + +Overall, the script generates variant arrays of descriptions for various combinations of types, verbs, and places, which can then be used in a fantasy role-playing game. The generated descriptions are saved in separate text files with unique names based on the combination of type, verb, and place. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_24.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_24.txt new file mode 100644 index 0000000..dbfbb1d --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_24.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It appears to be part of a larger project for generating descriptions for a fantasy role-playing game using a large language model and a proof engine combined via adaptive language agent architecture. + +The script defines several lists of terms related to the genre, such as "weapon", "spell", "monster", etc. It also defines some utility functions for constructing command-line arguments for invoking an external command, and then uses those functions in a loop to generate multiple variants of a prompt that will be passed to the language model. + +The script uses the `do_apply_list` function to iterate over several lists of terms (type\_terms, top\_terms, etc.) and constructs prompts by combining elements from those lists. It then invokes an external command with the constructed arguments using the `run_cmd` function. + +The output of the script would be the standard output of the external command that is executed in the `run_cmd` function for each combination of terms generated by the `do_apply_list` function. The exact output would depend on the implementation of the external command and the specific terms passed to it. + +Based on the code, it seems like the game being developed would be a fantasy role-playing game with a focus on exploration and combat, featuring different types of characters, weapons, spells, monsters, treasures, quests, etc. The language model is used to generate descriptive text for various aspects of the game, such as locations, items, and NPCs, based on the prompts constructed by the script. The proof engine and adaptive language agent architecture mentioned in the comment at the beginning of the code might be used to ensure consistency and coherence in the generated descriptions, but their implementation is not shown in the code provided. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_25.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_25.txt new file mode 100644 index 0000000..17a71e1 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_25.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It appears to be part of a larger program that uses a large language model and a proof engine combined via adaptive language agent architecture to generate content for a fantasy role-playing game. The script defines a number of lists containing different types of elements related to the game, such as verbs, type names, places, and terms. It then uses these lists to generate prompts that are passed to the language model to generate variant arrays of text based on the given context. + +The `do_apply_list` function takes three arguments: a `run_cmd` function, which is used to run commands; a `make_args` function, which generates command-line arguments for the `run_cmd` function; and a list of type names (`type_terms`). The function uses these inputs to generate and run commands that call the language model with different prompts. + +The `prompt` function takes four arguments: a type name, an index, a verb, and a place. It constructs a prompt string that asks the language model to generate text based on the given context. The `make_args` function takes three arguments: a type name, an index, a verb, and a place. It generates command-line arguments for the `run_cmd` function based on the given inputs. + +Overall, it seems that this script is used to generate a large number of text variants using the language model, which can then be used as input for the larger program that generates content for the fantasy role-playing game. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_26.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_26.txt new file mode 100644 index 0000000..70a7974 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_26.txt @@ -0,0 +1,154 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts and running them through an AI language model to generate descriptions for a fantasy role-playing game's dungeon generator. The code defines several lists of terms, verbs, and places to use in the prompts, as well as functions for constructing the prompts and executing the commands to run them through the AI model. + +The main function `do_apply_list` takes a function `run_cmd` that runs a command with a given set of arguments, a function `make_args` that generates the arguments for each prompt, and a list of type terms. It then loops through the top-level terms, type terms, verbs, and places to create and run prompts with different combinations of these elements. The generated descriptions are written to text files in the current working directory. + +If you were to simulate the execution of this code, imagine that for each combination of top-level term, type term, verb, and place, a new prompt is constructed using the `prompt` function, which includes these elements as well as the name of the type, an index number, and a URL. The `make_args` function then creates a list of arguments to pass to the `run_cmd` function, including the name of the binary to run, various flags and options for specifying the model, test name, output file, prompt text, and the URL. + +The `run_cmd` function takes these arguments and constructs a command string by concatenating them with spaces in between. It then opens a subprocess to execute this command and reads the output from it. If there is output, it prints it to the console. Otherwise, it prints "Output: None". + +To imagine what the game would be like based on this code, we can consider the types of descriptions that might be generated for different combinations of top-level terms, type terms, verbs, and places. For example, a prompt with the top-level term "Imagine", type term "weapon", verb "creating", and place "the dungeon" might generate a description like "Imagine creating a weapon in the dungeon". This could be used to describe a blacksmith's forge or a magical laboratory within the dungeon. Similarly, a prompt with the top-level term "Consider", type term "monster", verb "encountering", and place "the labyrinth" might generate a description like "Consider encountering a monster in the labyrinth". This could be used to describe a boss battle or a random encounter with a wandering creature. + +By generating many such descriptions for different combinations of terms, the code can help create a rich and varied game world with a consistent language and style. The generated descriptions can also serve as inspiration for artists, writers, and other creators working on the game's visual and narrative elements. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_27.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_27.txt new file mode 100644 index 0000000..443a4be --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_27.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts and calling an AI language model with those prompts to generate descriptions for a fantasy role-playing game dungeon generator. It uses the `simple` command line tool, which is not defined in this script, but presumably runs the main loop of the program. + +The script defines several lists of terms related to different aspects of a dungeon generator, such as "weapon", "spell", "treasure", etc. It then iterates over these lists and generates prompts by combining different elements from each list, creating a verb phrase and a place description for each combination. The prompts are passed as arguments to the `simple` command along with other options, such as the name of the model, the URL of the server, and the output file name. + +The script then runs the `run_cmd` function with the generated arguments, which likely executes the `simple` command and saves the output to a file. The output is not processed or analyzed in any way by this script. + +Overall, this script seems to be a simple tool for generating prompts and calling an AI language model to generate text based on those prompts. It could be used as part of a larger system for generating descriptions for a dungeon generator or other similar applications. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_28.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_28.txt new file mode 100644 index 0000000..77f5a8f --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_28.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts to create a dungeon generator for a fantasy role-playing game using a large language model and a proof engine combined via adaptive language agent architecture. + +The script defines several lists of terms, verbs, and places that are used to generate the prompts. The `do_apply_list` function takes a command runner function `run_cmd`, a function to create arguments for the command `make_args`, and a list of type terms as input. It then iterates through all possible combinations of top terms, type terms, other terms, verbs, and places to generate prompts and run the command with those prompts as arguments. + +The `run_cmd` function takes a list of command-line arguments as input and runs the corresponding command using OCaml's built-in process handling functions. It then prints the output of the command to the console. + +Overall, running this script would generate a large number of prompts for creating a dungeon generator with various combinations of terms, verbs, and places. The actual game or application being developed is not clear from the provided code, but it seems to be focused on generating descriptions or scenarios for a fantasy role-playing game using natural language processing techniques. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_29.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_29.txt new file mode 100644 index 0000000..60504eb --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_29.txt @@ -0,0 +1,154 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts for a language model to create descriptions of various elements of a fantasy role-playing game, such as weapons, spells, artifacts, monsters, quests, and challenges. The script uses the `simple` command-line tool to run the language model with different parameters and generates multiple variants for each combination of type, verb, and place. + +The script defines several lists of terms related to the game elements, verbs, and places, as well as a function to construct the command-line arguments for running the `simple` tool. The main function, `do_apply_list`, applies the `run_cmd` function to all combinations of type, verb, and place using nested loops. + +The generated descriptions can be used as input for an artist to create visual assets or as inspiration for a game designer to develop the game mechanics and storyline. The script's output would consist of multiple text files, each containing a variant of a description for a specific combination of type, verb, and place. + +To simulate the execution of the code, we can imagine running the script and observing the output generated by the language model for each combination of parameters. For example, one possible output could be: + +Output: "Imagine a weapon with a rusty blade in a dark alley connected with a haunted mansion. The weapon is a longsword, used by a ranger to defend themselves from the undead creatures lurking in the shadows." + +The game would be a fantasy role-playing game where players explore different locations, encounter various monsters, and collect weapons, spells, and artifacts to complete quests and challenges. The language model's descriptions would provide inspiration for the visual and narrative aspects of the game, as well as potential mechanics and rules. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_3.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_3.txt new file mode 100644 index 0000000..87fe239 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_3.txt @@ -0,0 +1,156 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts to create variants of a dungeon generator for a fantasy role-playing game using a large language model and a proof engine combined via adaptive language agent architecture. The script generates different combinations of type names, verbs, places, and other terms to create prompts for the language model. + +The code defines some lists of terms, such as `type_terms`, `verbs`, `places`, `top_terms`, and a constant `count` set to 3, which indicates how many variants should be generated for each combination of terms. + +The main function in the script is `do_apply_list`, which takes three arguments: a function `run_cmd` that runs a command with the given arguments, a function `make_args` that creates the arguments for the command based on the type name, index, verb, and place, and the list of `type_terms`. + +The `do_apply_list` function uses nested loops to iterate through all possible combinations of terms from the lists defined earlier and calls the `make_args` function to create a set of arguments for each combination. Then it calls the `run_cmd` function with those arguments to run the command and generate a variant of the dungeon generator. + +The generated variants are saved in text files named `new_[index]_[verb]_[type_name]_[place].txt`, where `[index]` is the index of the variant, `[verb]` is the verb used in the prompt, `[type_name]` is the type name used in the prompt, and `[place]` is the place used in the prompt. + +The generated variants can then be used to create different versions of a dungeon generator for a fantasy role-playing game that use different terms and concepts. The language model can generate descriptions, stories, characters, items, monsters, quests, challenges, themes, drama, music, art, secrets, occult, reveals, and hero journeys based on the prompts generated by this script. + +Overall, the code provides a flexible and customizable way to generate prompts for a large language model to create different versions of a dungeon generator for a fantasy role-playing game. The resulting generators can be used to create engaging and immersive gaming experiences that cater to different preferences and styles. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_30.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_30.txt new file mode 100644 index 0000000..b240d4a --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_30.txt @@ -0,0 +1,160 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The given OCaml code is a script for generating prompts for a language model to create descriptions for a fantasy role-playing game. The script uses a combination of predefined terms, verbs, and places to generate various prompts, which are then passed as arguments to a command-line tool that interfaces with the OpenAI API to generate the descriptions. + +The code defines several lists of terms, such as `type_terms`, `verbs`, `top_terms`, and `places`, which are used to construct the prompts. The `do_apply_list` function applies a given command-line tool (`run_cmd`) with different combinations of arguments generated from these lists. + +The main part of the code consists of calling `do_apply_list` with the `run_cmd` and `make_args` functions, along with the `type_terms` list as an argument. The `make_args` function generates a list of command-line arguments based on the given type name, iteration index, verb, and place. These arguments are then passed to the `run_cmd` function, which executes the command-line tool with the specified arguments. + +To simulate the execution of this code, you can imagine running each generated prompt through a language model API, such as OpenAI, and receiving a description based on the given context. The game would then be created from these descriptions, using them to build out different areas, characters, and objects within the game world. + +For example, one generated prompt might look like this: +"We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : construct; Type Name: weapon; Place: the armory connected with the treasure room What is your response? Please generate variant array of size 3" + +The output from the language model might then be something like this: +"1. A longsword forged in dragonfire, its blade etched with intricate runes and glowing faintly in the darkness. +2. A crossbow made of dark wood and adorned with gold filigree, capable of firing bolts imbued with elemental magic. +3. A mace wielded by a legendary hero, its head fashioned from enchanted crystal and rumored to shatter any shield." + +By combining many such prompts and their outputs, you can create a rich and varied game world for players to explore. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_31.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_31.txt new file mode 100644 index 0000000..af1a269 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_31.txt @@ -0,0 +1,154 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The given code is a script written in OCaml, a functional programming language. It appears to be part of a larger program for generating descriptions for a fantasy role-playing game, using a large language model and a proof engine combined via adaptive language agent architecture. + +The main function `do_apply_list` takes three arguments: `run_cmd`, `make_args`, and `type_terms`. It uses these arguments to generate and run commands that invoke the language model with specific prompts, using various combinations of verbs, type names, and places. + +The `run_cmd` function takes a list of command-line arguments as input and runs the corresponding command using OCaml's built-in `Unix.open_process_in` function. It then prints the output of the command to the console. + +The `make_args` function takes three arguments: `type_name`, `i`, `verb`, and `place`. It constructs a list of command-line arguments by concatenating various strings, including the prompt string that is passed to the language model. The prompt string asks the language model to generate a variant array of size `try_n` (which is set to 3 at the beginning of the script) based on the given type name, verb, and place. + +The `do_apply_list` function uses nested loops to iterate over various combinations of type names, verbs, and places, and generates a unique prompt string for each combination. It then calls `run_cmd` with the corresponding arguments to invoke the language model and print the output. + +Overall, it seems that this script is part of a larger program for generating descriptions for a fantasy role-playing game. The generated descriptions may be used as input for other parts of the program, such as a game engine or a user interface. However, without more context, it is difficult to say exactly how the generated descriptions would be used in practice. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_32.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_32.txt new file mode 100644 index 0000000..551721a --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_32.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It defines several lists of terms and verbs related to fantasy role-playing games, such as "weapon", "spell", "monster", "create", "analyze", etc. Then, it uses these terms and verbs to generate prompts for a language model, which will generate descriptions for various aspects of a fantasy role-playing game. + +The script defines a function `prompt` that takes a type name, a try number, a verb, and a place as arguments, and returns a string that is a prompt for the language model. The function `make_args` creates a list of command-line arguments to be passed to the `run_cmd` function, which runs the command with the given arguments. + +The script then calls the function `do_apply_list`, which applies the `run_cmd` function with the command-line arguments generated by the `make_args` function, using all possible combinations of terms and verbs in the lists defined at the beginning of the script. The resulting descriptions will be saved to text files. + +In summary, this script generates a large number of prompts for a language model, which will generate descriptions for various aspects of a fantasy role-playing game. These descriptions will be saved to text files for further use. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_33.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_33.txt new file mode 100644 index 0000000..7775285 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_33.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It appears to be part of a larger program used for generating descriptions for a fantasy role-playing game, specifically for creating a dungeon generator using a large language model and a proof engine combined via an adaptive language agent architecture. + +The script defines several lists containing different types of terms (such as "weapon", "spell", etc.), verbs (such as "role-play", "specify", etc.), top terms (such as "Imagine", "Consider", etc.), and places (such as "the country", "the region", etc.). The script then uses these lists to generate prompts for the language model, using a helper function `prompt` to construct the prompt string. + +The main function in this script is `do_apply_list`, which takes three arguments: `run_cmd`, `make_args`, and `type_terms`. The function uses nested loops to iterate over all possible combinations of terms, verbs, and places, and for each combination, it generates a set of arguments using the `make_args` function. These arguments are then passed to the `run_cmd` function, which runs the command specified by the arguments. + +Overall, this script is used as part of a larger program for generating descriptions for a fantasy role-playing game. It uses a language model and a proof engine to generate descriptions based on a set of predefined terms, verbs, and places. The output of the script would be a series of generated descriptions that could be used to populate a dungeon in a role-playing game. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_34.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_34.txt new file mode 100644 index 0000000..b77ddea --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_34.txt @@ -0,0 +1,154 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The given code is written in OCaml programming language and it appears to be a script for generating prompts for a language model to create descriptions for a fantasy role-playing game. The script uses a list of verbs, type names, terms, places, and other parameters to construct prompts and then runs them through a command line interface to generate the descriptions. + +To simulate its execution, we can imagine running the code and seeing the output it would generate for each prompt. For example, one of the prompts generated by the script is: + +"We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : explore; Type Name: weapon; Place: the cave What is your response? Please generate variant array of size 3" + +Running this prompt through the command line interface would generate three descriptions for a weapon used in a fantasy role-playing game set in a cave. The output would depend on the language model being used and the specific parameters provided in the prompt. + +To imagine what the game would be like, we can envision a fantasy role-playing game where players explore different environments, encounter various creatures and obstacles, and collect weapons, spells, and other items to aid them on their journey. The descriptions generated by the language model would help bring these elements to life and make the game more immersive and engaging for players. + +Overall, the script is an interesting example of how natural language processing and machine learning can be used to generate creative content for games and other applications. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_35.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_35.txt new file mode 100644 index 0000000..5e77613 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_35.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The given code is a script written in OCaml, a functional programming language. It appears to be part of a larger program that generates prompts for a language model to create descriptions for a fantasy role-playing game. The script defines several lists of terms related to the game, such as weapons, spells, and treasure, as well as places where the action can take place. + +The `prompt` function constructs a prompt string that will be used to generate a description of a particular type (specified by the `type_name` parameter), using a specific verb and taking place in a specified location. The `make_args` function creates a list of command-line arguments that will be passed to the language model, including the prompt string and other parameters such as the model name, URL, and output file name. + +The `do_apply_list` function applies the `run_cmd` function to each combination of terms from the `type_terms`, `top_terms`, `verbs`, and `places` lists, generating a series of prompts that will be used to create descriptions for different aspects of the game. The `run_cmd` function simply executes the command-line arguments passed to it as a shell command, printing the output to the console. + +To simulate the execution of this script, we would need to imagine running each combination of prompts that is generated by the `do_apply_list` function, and consider how the language model might respond to each prompt. The resulting descriptions could then be used to create a rich, immersive game world with a wide variety of characters, items, and locations. + +To answer your question about what the game would be like, it is difficult to say without more context about the larger program that this script is part of. However, based on the terms and prompts defined in the script, we can imagine a fantasy role-playing game with a variety of weapons, spells, magic items, treasure, monsters, quests, challenges, themes, drama, music, art, secrets, occult elements, and hero journeys. The game might take place in a variety of locations, such as dungeons, labyrinths, caves, swamps, buildings, rooms, hallways, chests, bags, wallets, vaults, keeps, hideouts, Plato's cave, the Garden of Eden, the River Styx, and the Restaurant at the End of the Universe. The language model could be used to generate descriptions for each of these elements, creating a rich and engaging game world that adapts to player choices and actions. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_36.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_36.txt new file mode 100644 index 0000000..ed980a0 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_36.txt @@ -0,0 +1,148 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The given code is a script written in OCaml, a functional programming language. It appears to be part of a larger program that generates prompts for a language model to create descriptions for a fantasy role-playing game. The script defines several lists of terms related to the game, such as "weapon", "spell", and "monster". It then uses these terms to generate prompts for the language model to describe various aspects of the game. + +The main function in the script is `do_apply_list`, which takes three arguments: a function `run_cmd` that runs a command, a function `make_args` that generates command-line arguments, and a list of type terms. The function iterates over each combination of top terms, type terms, subtype terms, verbs, and places to generate prompts for the language model. It then uses the `run_cmd` function to run the generated command, which presumably invokes the language model with the generated prompt. + +Overall, it seems like this script is part of a larger system that uses a language model to automatically generate descriptions for a fantasy role-playing game. The generated descriptions could be used for various purposes, such as creating game assets or generating adventure hooks for players. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_37.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_37.txt new file mode 100644 index 0000000..2919769 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_37.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts for a language model to create descriptions for a fantasy role-playing game's dungeon generator. The script uses a combination of predefined terms, verbs, and place names to generate various combinations, which are then used as prompts for the language model. + +To simulate its execution, imagine running this code in an OCaml environment. It would first define several lists containing different terms, verbs, and place names. Then, it would iterate through these lists, combining them to create various prompts. For each prompt, it would generate a set of arguments for the language model and call the `run_cmd` function, which simulates running a command using these arguments. The output of this command is then printed to the console. + +The generated game would be a fantasy role-playing game with a dungeon generator powered by a large language model. The prompts created by this script would guide the language model in generating descriptions for various aspects of the game, such as weapons, spells, monsters, and treasures. These descriptions would then be used to create a rich and immersive gaming experience for players. + +To rewrite your question: How would the fantasy role-playing game generated by this OCaml script look like? What kind of player experience could we expect from such a game? +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_38.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_38.txt new file mode 100644 index 0000000..51ed797 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_38.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The given OCaml code is a script for generating prompts for a language model to create descriptions for a fantasy role-playing game. The code defines several lists of terms, verbs, and places, which are used to generate the prompts. The `do_apply_list` function takes a function `run_cmd` and a list of type terms, and applies it to all combinations of top terms, type terms, verbs, and places. + +The `run_cmd` function runs a command by constructing a string from an array of arguments and then using the `Unix.open_process_in` function to execute it. The output is read from the channel and printed to the console. + +In this case, the command being run is a custom program called `simple`, which takes several options including `-m` for the model name, `-s` for the seed file, `-x` for the output file, `-p` for the prompt, and `-u` for the URL. The `prompt` function generates the actual prompt string, which includes information about the type name, verb, and place to be used in the description. + +The script runs through all combinations of terms, verbs, and places to generate a large number of prompts, each resulting in a new file with the output. The generated descriptions could then be used as input for further processing or directly in a game. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_39.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_39.txt new file mode 100644 index 0000000..d9bfcb6 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_39.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The given code is a script written in OCaml, a functional programming language. It appears to be part of a larger program that uses a large language model and a proof engine combined via adaptive language agent architecture to generate descriptions for a fantasy role-playing game dungeon. The script defines several lists of terms, verbs, and places, as well as some utility functions for generating prompts and command line arguments. + +The main function in the script is `do_apply_list`, which takes three arguments: a function `run_cmd` that runs a command with a given list of arguments, a function `make_args` that generates the command line arguments based on some input parameters, and a list of type terms. The function then iterates over several combinations of top terms, type terms, other terms, verbs, and places to generate prompts and run the `run_cmd` function with the corresponding arguments. + +Based on the code, it seems that the game being generated would involve creating descriptions for various types of objects, such as weapons, spells, artifacts, magic items, treasure, monsters, quests, challenges, themes, drama, music, art, secrets, and occult subjects. The language model is prompted to generate descriptions for these objects in different contexts and variations, based on the given terms, verbs, and places. + +The output of the script would be a series of generated descriptions, each stored in a separate text file with a unique name. These descriptions could then be used as input for further game development, such as creating artwork, designing levels, or implementing game mechanics. + +Overall, the script seems to be part of a larger system for generating and managing game content using artificial intelligence techniques. The generated descriptions would likely be used in a fantasy role-playing game, possibly one with a strong emphasis on language and storytelling. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_4.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_4.txt new file mode 100644 index 0000000..cde936f --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_4.txt @@ -0,0 +1,154 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It appears to be part of a larger program that generates descriptions for a fantasy role-playing game using a large language model and a proof engine combined via adaptive language agent architecture. + +The script defines several lists of terms related to the game, such as weapons, spells, monsters, and treasures. It also defines a list of verbs, places, and types that will be used in prompts for the language model. The main function `do_apply_list` takes three arguments: `run_cmd`, `make_args`, and `type_terms`. + +The function `run_cmd` takes a list of command-line arguments as input and runs the corresponding command using OCaml's `Unix.open_process_in` function. It then prints the output of the command to the console. + +The function `make_args` creates a list of command-line arguments based on the input type name, index, verb, and place. The arguments include the name of the program to run, the language model to use, the unique identifier for this prompt, the file path to save the output, and the prompt itself. + +The function `do_apply_list` applies the `run_cmd` function to a list of prompts generated from the input type terms, index, verb, and place. The function iterates over each combination of type term, top term, term, term2, verb, and place, generating a unique prompt for each combination and running the corresponding command using `run_cmd`. + +Overall, the script appears to be part of a larger program that generates descriptions for a fantasy role-playing game using a language model and a proof engine. The generated descriptions are saved to text files for later use. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_40.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_40.txt new file mode 100644 index 0000000..cddce2c --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_40.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. The script appears to be part of a larger program for generating descriptions for a fantasy role-playing game using a large language model and a proof engine combined via adaptive language agent architecture. + +The main function `do_apply_list` takes three arguments: `run_cmd`, `make_args`, and `type_terms`. It uses these arguments to generate and run commands that invoke the language model to generate descriptions for various elements of the game, such as weapons, spells, monsters, quests, and treasures. + +The function iterates through a list of top-level terms (such as "Imagine" or "Consider"), type names (such as "weapon" or "spell"), verbs (such as "role-play" or "specify"), and places (such as "the country" or "the dungeon"). It constructs a command for each combination of these elements, using the `make_args` function to generate the arguments for the command. The command is then executed using the `run_cmd` function. + +The `run_cmd` function takes a list of strings as its argument and concatenates them into a single string that represents a command to be run in the terminal. It then opens a subprocess to execute the command and reads the output from the subprocess. The output is printed to the console, along with any error messages that may have been generated. + +Overall, the script appears to be part of a larger system for generating descriptions for a fantasy role-playing game using natural language processing techniques. The generated descriptions could be used to populate a game world, provide flavor text for items and abilities, or serve as inspiration for game designers and players alike. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_41.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_41.txt new file mode 100644 index 0000000..8c6478b --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_41.txt @@ -0,0 +1,154 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts to create a fantasy role-playing game (RPG) dungeon generator using a large language model and a proof engine combined via adaptive language agent architecture. The script defines several lists of terms, verbs, and places, as well as functions to construct command-line arguments and run the generated commands. + +To simulate its execution, we can imagine running the code and all the output it would generate as follows: + +1. The `do_apply_list` function is called with three lists as arguments: `type_terms`, which contains various types of items that can appear in a dungeon (e.g., "weapon", "spell", etc.); `verbs`, which contains various actions that can be performed on those items (e.g., "role-play", "specify", etc.); and `places`, which contains various locations where the items can appear (e.g., "the country", "the city", etc.). +2. For each combination of a type term, verb, and place from the input lists, the function constructs a prompt string that asks the language model to generate a variant array of size `try_n` with a specific context (verb, type name, and place). The prompt is then used to construct command-line arguments for running the language model. +3. The `run_cmd` function takes a list of command-line arguments as input and runs the corresponding command using OCaml's `Unix.open_process_in` function. It then prints the output of the command. +4. In the main part of the script, the `do_apply_list` function is called with the `run_cmd`, `make_args`, and `type_terms` variables as arguments. This generates and runs a series of commands to prompt the language model to generate variant arrays of size `try_n` for each combination of type term, verb, and place from the input lists. +5. The generated dungeons can then be used in a fantasy RPG game, where players can explore different locations, interact with various types of items, and perform various actions on them. + +To rephrase the question: How would the game experience be like if we ran this OCaml script to generate dungeons using a language model and a proof engine combined via adaptive language agent architecture? +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_42.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_42.txt new file mode 100644 index 0000000..50ab1e5 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_42.txt @@ -0,0 +1,154 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts and calling an external command with those prompts, using the OCaml `Unix` module to handle process execution. The prompts are generated by combining elements from several lists of terms related to fantasy role-playing games, such as "weapon", "spell", "monster", etc. + +The script defines a function `prompt`, which takes four arguments: a type name, an index, a verb, and a place. It constructs a prompt string by combining these arguments with other hardcoded strings to form a complete English sentence. This prompt is then used in the call to `run_cmd` along with other arguments to execute an external command. + +The function `make_args` takes four arguments: a type name, an index, a verb, and a place, and returns a list of strings that represent the arguments to be passed to the external command. The first element in the list is the name of the executable, followed by various options such as the model name, the test name, the input and output file names, the prompt string, and the URL. + +The function `do_apply_list` takes three arguments: a function `run_cmd`, a function `make_args`, and a list of type terms. It applies these functions to each combination of terms from the lists provided as arguments, generating prompts and running the external command for each combination. + +Finally, the script defines a main block that calls `do_apply_list` with the functions `run_cmd` and `make_args`, and the list of type terms. This generates prompts and runs the external command for all possible combinations of terms from the lists provided as arguments. + +To simulate the execution of this script, one could imagine running each generated prompt through the external command, and collecting the output. The resulting texts could then be used as input to a fantasy role-playing game, perhaps by serving as descriptions of different parts of a dungeon or other game environment. The game itself would depend on how these descriptions are used and interpreted by players and the game system. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_43.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_43.txt new file mode 100644 index 0000000..b953ee1 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_43.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts for a language model to create descriptions for a fantasy role-playing game. It does this by combining different elements from various lists, such as verbs, type names, places, and more. The `do_apply_list` function takes a `run_cmd` function, a `make_args` function, and a list of type terms. It then iterates through the top terms, type terms, and other lists to create combinations of prompts, which are passed to the `run_cmd` function to be executed. + +The `run_cmd` function takes a list of arguments and combines them into a command string, which is then executed using the `Unix.open_process_in` function. The output of the command is printed to the console. + +To simulate the execution of this code, imagine that the code is executed and generates prompts for the language model to create descriptions for a fantasy role-playing game. For each combination of elements from the lists, a prompt is generated and passed to the `run_cmd` function to be executed. The output of each command is printed to the console. + +The resulting game would be a text-based fantasy role-playing game with descriptions generated by a language model based on the prompts created by this code. The game would feature various types of elements, such as weapons, spells, artifacts, and monsters, in different places and scenarios, all described in creative and imaginative ways using the language model. + +To answer your question more directly, running this code would result in a text-based fantasy role-playing game with descriptions generated by a language model based on prompts created by this OCaml script. The game would feature various types of elements, such as weapons, spells, artifacts, and monsters, in different places and scenarios, all described in creative and imaginative ways using the language model. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_44.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_44.txt new file mode 100644 index 0000000..275cd92 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_44.txt @@ -0,0 +1,154 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It appears to be part of a larger program used for generating descriptions for a fantasy role-playing game using a large language model and a proof engine combined via an adaptive language agent architecture. Here's a high-level overview of what the code does: + +1. Defines some constants, including a list of terms related to various aspects of a role-playing game (e.g., "weapon", "spell"), a list of verbs (e.g., "role-play", "create"), and a list of place types (e.g., "the country", "the city"). +2. Defines a function `prompt` that constructs a prompt string for the language model based on the given type name, number of tries, verb, and place. +3. Defines a function `make_args` that creates command-line arguments for running the language model with the provided settings. +4. Calls the `do_apply_list` function to generate prompts using all possible combinations of terms, verbs, and places. It then runs the language model with these prompts in a loop, saving the output to text files. +5. Runs the command specified by `run_cmd` with the generated arguments from `make_args`. + +Simulating its execution would involve running this script using an OCaml interpreter or compiler and observing the output as it generates descriptions for various combinations of terms, verbs, and places. The resulting game would likely be a richly-detailed fantasy role-playing experience with a wide variety of characters, items, monsters, quests, and environments generated by the language model. + +To rephrase your question: How would you imagine the final output of this code to look like if it were simulated? What would be the resulting game based on the generated descriptions? +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_45.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_45.txt new file mode 100644 index 0000000..d2ad81d --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_45.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating descriptions for a fantasy role-playing game using a large language model and a proof engine combined via adaptive language agent architecture. The script defines several lists of terms related to the game, such as weapons, spells, monsters, etc., and then uses these terms in various combinations to generate descriptions. + +The `prompt` function constructs a string that serves as input for the language model, asking it to generate a variant array of size `try_n` with a specific verb, type name, and place. The `make_args` function creates a list of command-line arguments for the `simple` command, which is used to run the large language model with the generated prompt. + +The `do_apply_list` function applies the `run_cmd` function to all combinations of terms in the `type_terms`, `verbs`, and `places` lists, as well as some additional top-level terms in the `top_terms` list. This generates a large number of descriptions with different combinations of game elements. + +Overall, the script seems to be designed to generate a large number of descriptions for a fantasy role-playing game using a language model and a proof engine. The resulting game would likely involve exploring various locations, fighting monsters, collecting treasure, and completing quests, all described in detail using the generated descriptions. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_46.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_46.txt new file mode 100644 index 0000000..7916e38 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_46.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The given code is a script written in OCaml, a general-purpose programming language with a focus on "functional" programming, which means that functions and data structures are the building blocks of the program. In this case, the script defines several lists of terms, verbs, and places, as well as some other variables. It then uses these variables to generate command-line arguments for an external program called `simple`, which seems to be a tool for generating and processing text using language models and proof engines. + +The main function in the script is `do_apply_list`, which applies a given function (in this case, `run_cmd`) to a list of arguments generated by the `make_args` function. The `make_args` function takes a "type name", an index `i`, a verb, and a place as input and returns a list of command-line arguments that can be passed to `simple`. These arguments include the model name, the test name, the output file name, the prompt text, the URL, and other options. + +The script then calls `do_apply_list` with `run_cmd`, `make_args`, and the list of `type_terms` to generate and run multiple commands that use different combinations of type names, verbs, and places. The output of each command is printed to the console. + +In terms of generating a game, it seems like the script is part of a larger system for creating a "dungeon generator" for a fantasy role-playing game (RPG). The script uses language models and proof engines to generate text descriptions of dungeons, rooms, monsters, treasures, and other elements of an RPG. These descriptions can then be used to create a playable game, possibly with the help of other tools or scripts. However, the script itself does not directly create a game; it only generates text that could be used as input for a game creation process. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_47.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_47.txt new file mode 100644 index 0000000..7caf3d2 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_47.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts and calling an external command to process those prompts using a large language model and a proof engine combined via adaptive language agent architecture. The prompts are generated based on combinations of type names, verbs, places, and other terms from predefined lists. + +The script runs the specified command with different combinations of arguments for each prompt, resulting in multiple output strings that represent the model's responses to those prompts. + +To simulate its execution, you can run the script in an OCaml environment or interpreter, providing the necessary dependencies and configuration. The output will be a series of print statements showing the command executed and the corresponding output string from the language model. + +If you rewrite your question to make it more specific, I would be happy to help further. However, based on the given code and context, I would imagine that running this script would result in a game with a richly detailed and interconnected world, filled with various types of weapons, spells, artifacts, magic items, treasure, monsters, quests, challenges, themes, drama, music, art, secrets, occult elements, and hero journeys. The language model's responses would help create descriptions for an artist to design a visually stunning and immersive experience for players. + +Confidence: 85% +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_48.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_48.txt new file mode 100644 index 0000000..64a764b --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_48.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The given code is a script written in OCaml, a general-purpose programming language with an emphasis on formal methods and static typing. When executed, this script generates prompts for a large language model to create descriptions for various elements of a fantasy role-playing game. These elements include weapons, spells, artifacts, magic items, treasure, monsters, quests, challenges, themes, drama, music, art, secrets, the occult, reveals, and hero journeys. The script also generates prompts based on places such as dungeons, labyrinths, caves, swamps, rooms, hallways, chests, bags, wallets, vaults, keeps, and hideouts. + +The script uses a combination of the provided terms, verbs, and places to create the prompts, resulting in a large number of possible combinations. The generated prompts are then used as input for a language model, which generates descriptions based on the given prompts. These descriptions can then be used to create a rich and detailed fantasy role-playing game. + +The script itself consists of several functions that define the behavior of the program. The `prompt` function constructs a prompt string using the provided type name, try number, verb, and place. The `make_args` function creates a list of command line arguments to be passed to the language model. The `do_apply_list` function is the main entry point of the script and generates all the possible combinations of terms, verbs, and places using nested loops and recursion. Finally, the `run_cmd` function takes a list of command line arguments and executes the corresponding command in the terminal. + +In summary, this script is a tool for generating prompts to be used with a large language model to create descriptions for various elements of a fantasy role-playing game. By combining different terms, verbs, and places, the script generates a wide variety of possible prompts, resulting in rich and detailed descriptions that can be used to build an immersive game world. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_49.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_49.txt new file mode 100644 index 0000000..c4e5b5c --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_49.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code generates prompts for a language model to create descriptions of a dungeon in a fantasy role-playing game. It uses a list of verbs, nouns, and adjectives to generate various combinations of prompts. Each prompt is used to generate a variant array of descriptions for a specific aspect of the dungeon, such as its layout, treasures, or monsters. The generated descriptions are saved in text files for later use. + +To imagine what it would be like to run this code and play the game, you can think about the type of experience you want from a fantasy role-playing game. Do you want a traditional dungeon crawler with traps, monsters, and treasure? Or do you want something more unique, such as a surreal or abstract dungeon that challenges your preconceptions of what a dungeon can be? + +Once you have an idea of the type of experience you want, you can use the generated prompts to inspire the creation of your game. You can use the descriptions as inspiration for the layout and atmosphere of the dungeon, or as a guide for creating encounters and challenges for the players. The language model's responses can also provide ideas for unique treasures, monsters, and other elements that you can incorporate into your game. + +Overall, running this code and using the generated prompts can help you create a more immersive and engaging dungeon for your fantasy role-playing game. By providing a diverse range of prompts, the code encourages creativity and flexibility in the design process, allowing you to create a dungeon that is tailored to your specific vision and goals. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_5.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_5.txt new file mode 100644 index 0000000..13399f5 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_5.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts to create descriptions of a fantasy role-playing game's elements, such as weapons, spells, and monsters, using a large language model and a proof engine combined via an adaptive language agent architecture. The script defines several lists of terms related to these elements, verbs, places, and top-level categories, then iterates through all possible combinations to generate prompts for the language model. + +The `do_apply_list` function takes three arguments: a function `run_cmd`, which runs a command with the given arguments; a function `make_args`, which generates the arguments for each prompt based on the type name, index, verb, and place; and a list of type terms. The function then iterates through all possible combinations of top-level categories, types, subtypes, verbs, and places to generate prompts for the language model. + +The `run_cmd` function takes a list of arguments and runs a command with those arguments using OCaml's `Unix.open_process_in` function. The output of the command is printed to the console. + +Overall, the script generates prompts for the language model to create descriptions of various elements in a fantasy role-playing game, such as "Imagine creating a weapon with a sharp blade in a dark dungeon connected with a treacherous maze." The generated prompts are saved to text files for further processing. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_50.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_50.txt new file mode 100644 index 0000000..e0677f3 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_50.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It appears to be generating prompts for an AI model to create descriptions of items, monsters, quests, and other elements for a fantasy tabletop role-playing game. The generated descriptions are saved to text files. + +The script uses the `simple` command, which is likely a custom executable built alongside this script. This command takes several arguments, including the model name, test name, type of item to generate, number of variants to generate, verb, and place. These arguments are passed in through the `make_args` function, which constructs a string array containing the command and its parameters. + +The main part of the script is the `do_apply_list` function, which iterates over a list of top-level terms (e.g., "Imagine", "Consider", etc.), type terms (e.g., "weapon", "spell", etc.), and other related terms to generate prompts for the AI model. The `run_cmd` function is then called with these arguments, which runs the `simple` command and saves the output to a text file. + +The generated descriptions would likely be used as inputs for a tabletop role-playing game, such as Dungeons & Dragons. They could provide inspiration for dungeon masters or players when creating their own campaigns and adventures. The script's use of a large language model and proof engine suggests that it may also incorporate some level of automated reasoning or consistency checking to ensure the generated descriptions fit within the game's lore and rules. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_51.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_51.txt new file mode 100644 index 0000000..7f62b76 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_51.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It appears to be part of a larger system for generating descriptions for a fantasy role-playing game using a large language model and a proof engine combined via adaptive language agent architecture. The script defines a number of lists of terms, verbs, and place names, as well as some functions for generating command line arguments and running commands. + +The main function in the script is `do_apply_list`, which takes three arguments: `run_cmd`, `make_args`, and `type_terms`. It uses these arguments to generate and run a series of commands, each of which invokes the large language model with a specific prompt. The prompts are generated by concatenating terms from the `type_terms` list with verbs and place names from other lists. + +The script runs the commands in a loop, generating a new prompt for each iteration of the loop. It uses the `run_cmd` function to execute each command, which appears to involve invoking an external program with some command line arguments. The output of each command is printed to the console. + +Overall, it seems that this script is part of a system for generating descriptions of game elements, such as weapons, spells, and monsters. It uses a large language model to generate these descriptions based on a set of input terms, verbs, and place names. The generated descriptions are then used to create a game world for a fantasy role-playing game. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_52.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_52.txt new file mode 100644 index 0000000..5a6919e --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_52.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It appears to be part of a larger program for generating descriptions for a fantasy role-playing game, specifically for creating a dungeon generator using a large language model and a proof engine combined via adaptive language agent architecture. + +The script defines several lists of terms related to the game's themes, such as weapons, spells, artifacts, treasures, monsters, quests, challenges, and so on. It also defines a list of verbs and places that can be used in the generated descriptions. + +The main function `do_apply_list` takes three arguments: a function `run_cmd` for executing command-line instructions, a function `make_args` for generating command-line arguments based on the game's terms and parameters, and a list of top-level game themes to be used in the descriptions. + +The function then loops over each combination of theme, term, type, verb, and place, generating a set of command-line arguments for running the language model with a specific prompt based on these parameters. It saves the generated output to a text file with a unique name based on the current iteration number. + +Overall, the script appears to be part of a larger system for automatically generating descriptions and content for a fantasy role-playing game using natural language processing and machine learning techniques. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_53.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_53.txt new file mode 100644 index 0000000..139a061 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_53.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The given code is a script written in OCaml, a general-purpose programming language with a focus on "functional" programming. It appears to be part of a larger system for generating descriptions and prompts related to building a dungeon generator for a fantasy role-playing game using a large language model and a proof engine combined via adaptive language agent architecture. + +The script defines several lists of terms, verbs, and places, as well as some functions and variables. The main function `do_apply_list` takes 3 arguments: `run_cmd`, `make_args`, and `type_terms`. This function iterates through the `top_terms`, `type_terms`, `verbs`, and `places` lists, combining them in various ways to generate a list of command-line arguments for invoking an external command. The `run_cmd` function is then called with these arguments, which runs the specified command and prints its output. + +The code appears to be generating a set of prompts for a language model by combining different terms and verbs in various ways, and then using those prompts to generate textual descriptions related to building a dungeon generator. The generated descriptions are written to text files with names like "new\_1verb\_typenoun.txt", where "verb" and "type" are replaced with the specific verb and type used in the prompt. + +Without further context, it's difficult to say exactly what this code is intended for or how it fits into a larger system, but it seems to be part of an automated testing framework for generating prompts and descriptions related to building a dungeon generator using a language model. The resulting text files could be used as input for the language model or as part of a training set for building a machine learning model. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_54.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_54.txt new file mode 100644 index 0000000..17459d5 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_54.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It appears to be part of a larger program for generating descriptions for a fantasy role-playing game using a large language model and a proof engine combined via adaptive language agent architecture. The script defines a number of lists containing different types of terms, verbs, and places that can be used in the generated descriptions. It also defines a function `prompt` which constructs a prompt string to be used when generating the descriptions. + +The main function `do_apply_list` takes three arguments: `run_cmd`, `make_args`, and `type_terms`. It uses these arguments to generate and run commands that use the large language model to generate descriptions using the defined terms, verbs, and places. The generated descriptions are saved to text files with names that include the type name, verb, and place used in the generation. + +The script runs the `do_apply_list` function three times, each time with a different type name from the `type_terms` list. Within each run, it iterates over a list of top-level terms, then for each top-level term, it iterates over a list of sub-terms and verbs, and finally for each combination of top-level term, sub-term, and verb, it iterates over a list of places. For each combination of top-level term, sub-term, verb, and place, it generates and runs a command that uses the large language model to generate a description and saves it to a text file. + +In order to run this script, you would need to have OCaml installed on your system, as well as any dependencies required by the script. You would also need to replace the `run_cmd` function with your own implementation that runs the generated commands. This could be done using the `Sys.command` function in OCaml, which runs a command and returns its exit status. + +It is hard to say exactly what the game would be like without more context, but based on the code provided, it seems that the game would involve exploring different locations and encountering various objects, creatures, and events, each with their own descriptions generated by the large language model. The descriptions would be stored in text files and could potentially be used to create a rich and immersive game world. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_55.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_55.txt new file mode 100644 index 0000000..9355374 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_55.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts for a language model to create descriptions for a fantasy role-playing game. It uses a combination of predefined terms, verbs, and places to construct prompts and then calls an external command to generate the descriptions. The script runs the command multiple times with different combinations of the terms, verbs, and places to create a variety of descriptions. + +To simulate its execution, you can imagine running the OCaml code in an OCaml environment. Each time the `run_cmd` function is called, it would execute the external command with the provided arguments, which include the generated prompt. The output of the command would be printed to the console. + +The game that this script generates would be a fantasy role-playing game with descriptions of various game elements such as weapons, spells, artifacts, monsters, quests, and challenges. These descriptions would be generated by the language model based on the prompts constructed by the script. The script uses a variety of terms, verbs, and places to create different prompts, resulting in a diverse set of game descriptions. + +The generated descriptions could then be used as input for further game development, such as creating game assets or implementing game mechanics. The adaptive language agent architecture mentioned in the code comment could potentially be used to refine the language model's responses based on feedback from the game development process. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_56.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_56.txt new file mode 100644 index 0000000..82c0e1c --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_56.txt @@ -0,0 +1,158 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts and calling an AI model to generate responses based on those prompts. The prompts are constructed using different combinations of terms, verbs, and places, with the goal of creating a variety of descriptions that can be used in a fantasy role-playing game. + +The script defines several lists of terms related to the game, such as "weapon", "spell", "monster", etc. It also defines a list of verbs and places that can be used in the prompts. The `prompt` function constructs a prompt string using these terms, verbs, and places. + +The script then defines a function `make_args` which creates a command-line argument list for running the AI model. This function takes a type name, index, verb, and place as arguments and returns a list of strings that can be passed to the `run_cmd` function. + +The `do_apply_list` function applies the `run_cmd` function to a series of prompts generated using different combinations of terms, verbs, and places. The function uses nested loops to iterate through all possible combinations, creating and running a new command for each one. + +Finally, the script runs the `do_apply_list` function with the appropriate arguments to generate prompts and call the AI model to generate responses. + +To simulate the execution of this code, we can imagine that the AI model is able to generate creative and varied descriptions based on the prompts provided. For example, given a prompt like "Create descriptions for an artist to design a comic book panel with a weapon, a sword, being used by a hero in a dungeon", the AI model might generate descriptions of different panels showing a hero using a sword to fight monsters in a dungeon. + +If we run this code multiple times with different combinations of terms, verbs, and places, we can generate a large number of diverse descriptions that could be used in a fantasy role-playing game. The game might include elements like weapons, spells, artifacts, treasures, monsters, quests, challenges, themes, drama, music, art, secrets, occult knowledge, reveals, and hero journeys, all described in creative and varied ways based on the prompts generated by this script. + +Overall, running this code would help to create a rich and immersive game world full of interesting characters, locations, and events. The descriptions generated by the AI model could be used as inspiration for artists, writers, and game designers, or they could be incorporated directly into the game itself. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_57.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_57.txt new file mode 100644 index 0000000..ecf3b0c --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_57.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts for an AI language model to create descriptions for a fantasy role-playing game. The script uses a combination of different terms, verbs, and places to construct prompts and then runs the language model with those prompts to generate descriptions. + +If we simulate the execution of this code, we can imagine that it would generate a large number of prompts, each one asking the language model to create a description for a specific aspect of the game. For example, one prompt might ask the model to describe a "weapon with a magical enchantment in a dark dungeon connected to a hidden passageway." The model would then generate a description based on that prompt, which could be used as part of the game's lore or dialogue. + +If we were to actually run this code, it would generate many such prompts and save the descriptions to text files. These descriptions could then be used to create a rich and immersive world for a fantasy role-playing game. The game could include elements such as weapons, spells, artifacts, monsters, quests, challenges, themes, drama, music, art, secrets, occult lore, and hero journeys. The script's use of different terms, verbs, and places ensures that the generated descriptions are varied and interesting, providing players with a diverse and engaging game world to explore. + +In summary, the provided OCaml code is a script for generating prompts for an AI language model to create descriptions for a fantasy role-playing game. If executed, it would generate many such prompts and save the resulting descriptions to text files, providing the basis for a rich and immersive game world. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_58.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_58.txt new file mode 100644 index 0000000..d7d885f --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_58.txt @@ -0,0 +1,148 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts and running a command-line tool with those prompts to generate content related to a fantasy role-playing game. When executed, it simulates the process of creating a variety of prompts based on different combinations of type names (e.g., weapon, spell), terms (e.g., artifacts, treasure), verbs (e.g., create, design), and places (e.g., city, dungeon). These prompts are then passed to the command-line tool, which likely uses a language model such as GPT or another AI language generation system to generate content based on each prompt. + +The generated content could be used for various aspects of a fantasy role-playing game, such as creating weapons, spells, monsters, and quests, or providing descriptions for art, music, and other visual elements. The script is designed to create multiple variations of prompts with different combinations of terms and verbs, allowing the language model to generate a wide range of content that can be used in various parts of the game. + +Overall, the code provides an automated way to generate content for a fantasy role-playing game using a combination of programming, AI language models, and adaptive language agent architecture. The generated content can help create a rich and immersive world for players to explore and interact with, making the game more engaging and enjoyable. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_59.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_59.txt new file mode 100644 index 0000000..c54457a --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_59.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code is a script for generating prompts to create descriptions for an artist to design fantasy role-playing game elements such as weapons, spells, magic items, treasure, monsters, quests, challenges, themes, drama, music, art, secrets, and occult. It does this by combining various terms, verbs, and places to generate a list of prompts that can be used to create these descriptions. + +The script uses the OCaml language and several libraries such as Coq, MetaCoq, and Introspector to perform the task. The main function `do_apply_list` takes three arguments: `run_cmd`, `make_args`, and `type_terms`. The `run_cmd` argument is a function that runs a command with a given set of arguments. The `make_args` argument is a function that generates the arguments for the `run_cmd` function based on the type name, try number, verb, and place provided. The `type_terms` argument is a list of fantasy role-playing game element types such as weapon, spell, or treasure. + +The script then iterates through various combinations of top terms, type terms, verbs, and places to generate prompts that can be used to create descriptions for an artist to design these elements. The `run_cmd` function is called with the generated arguments to execute the command and print the output. + +To simulate the execution of this code, one would need to have OCaml and the necessary libraries installed on their system. They would then need to run the script in an OCaml environment, providing the required arguments such as the type name, try number, verb, and place. The script would generate a list of prompts based on these arguments and execute the `run_cmd` function with the generated arguments to print the output. + +The game that this code generates would be a fantasy role-playing game where various elements such as weapons, spells, magic items, treasure, monsters, quests, challenges, themes, drama, music, art, secrets, and occult are designed using descriptions generated by a large language model and a proof engine combined via adaptive language agent architecture. The game would be highly customizable, with the ability to generate various combinations of elements based on user input. The game would also have a strong focus on creativity and imagination, as the descriptions generated by the language model would be designed to inspire an artist to create visually stunning and engaging fantasy role-playing game elements. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_6.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_6.txt new file mode 100644 index 0000000..8e74eb8 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_6.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided OCaml code appears to be a script for generating prompts and running a command-line tool with those prompts, using various combinations of terms from several lists (`type_terms`, `verbs`, `places`, etc.). + +The code defines some helper functions, including `prompt`, which constructs a prompt string given a type name, try number, verb, and place; and `make_args`, which constructs a list of command-line arguments given the same inputs. The main function `do_apply_list` uses these helper functions to generate many prompts and run the command-line tool with them. + +The resulting program would generate a large number of prompts, each asking the language model to create a variant array of size `try_n`, where `try_n` is an integer from 1 to `count`. The prompts are constructed by combining terms from the various lists in different ways, and they all involve a fantasy role-playing game, a dungeon generator, and a large language model. + +To simulate the execution of this code, we can imagine running each prompt through the command-line tool specified in `run_cmd`, which would generate output that could be used as input for the next step of the dungeon generator. This process would repeat many times, with different combinations of terms and prompts, to create a rich and varied set of descriptions and ideas for the game. + +The final game would likely involve exploring dungeons, fighting monsters, collecting treasure, and going on quests, all generated using a large language model and a proof engine combined via adaptive language agent architecture. The game would be designed to be flexible and adaptable, with many different types of challenges and rewards for players to discover. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_7.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_7.txt new file mode 100644 index 0000000..81c2418 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_7.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is a script written in OCaml, a functional programming language. It defines several lists of terms, verbs, and places, as well as some functions to generate commands for an imaginary command-line tool. The main function `do_apply_list` applies the `run_cmd` function to a list of generated commands using the `make_args` function to create the arguments for each command. + +The script seems to be generating prompts for a language model to generate descriptions or ideas for a fantasy role-playing game, specifically for creating a dungeon generator. The generated descriptions or ideas are saved in separate text files. + +To simulate its execution, one would need to have an OCaml environment set up and run the script using an OCaml compiler such as `ocaml` or `dune`. However, without access to the actual command-line tool being called by `run_cmd`, it's impossible to see the output of the generated commands. + +To answer the question about what the game would be like, one can only speculate based on the terms and places defined in the script. It seems that the game would involve exploring dungeons with various themes, challenges, and treasures, possibly facing monsters and completing quests. The language model would generate descriptions or ideas for each type of dungeon element, providing inspiration for the game designer. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_8.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_8.txt new file mode 100644 index 0000000..2639a96 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_8.txt @@ -0,0 +1,152 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The given code is a script written in OCaml, a functional programming language. It defines several lists of terms, verbs, and places, and uses them to generate prompts for a language model. The prompts are used to create variations of a dungeon generator for a fantasy role-playing game. + +The code starts by defining some lists of terms related to the game, such as "weapon", "spell", "monster", "quest", etc. Then it defines a list of verbs and places that can be used in the prompts. It also defines a model name, a URL, and a simple command for running the generated prompts with the language model. + +The main function `do_apply_list` takes three arguments: a function to run the commands, a function to generate the arguments for the commands, and a list of type terms. It uses nested loops to iterate over all combinations of terms, verbs, and places, and generates prompts using the `prompt` function. The prompts are then used to create command arguments with the `make_args` function, which concatenates the simple command with the generated prompt and other parameters. Finally, the commands are executed with the `run_cmd` function, which simply opens a process and reads its output. + +To simulate the execution of this code, one can imagine running each generated command with the language model, and observing the output. The output would be a set of variations of the dungeon generator, each with a different combination of type term, verb, and place. The variations would be saved as text files in the current directory. + +The resulting game would be a fantasy role-playing game with a dynamic and customizable dungeon generator, powered by a language model and a proof engine combined via adaptive language agent architecture. The generator would create dungeons that fit the player's preferences and actions, as specified in the prompts. The game would therefore offer a unique and immersive experience for each player, with a high degree of replayability. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_9.txt b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_9.txt new file mode 100644 index 0000000..b5b8b68 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T11:55:25-05:00_9.txt @@ -0,0 +1,150 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please simulate its execution. Imagine running the code and all the output it would generate. then Imagine running that code. what would the game be like? Please rewrite my question if confusing. + +#+end_src +#+begin_src output mixtral + Result: The provided code is written in OCaml and appears to be a script for generating prompts for a language model to create descriptions for a fantasy role-playing game. The script defines several lists of terms, verbs, and places, as well as some functions for constructing command line arguments and running commands. + +The main function `do_apply_list` takes a `run_cmd` function, a `make_args` function, and a list of type terms as input. It then iterates over the top-level terms, inner terms, verbs, and places to create a large number of unique prompts for the language model. Each prompt is used to generate a description of a game element, such as a weapon, spell, or monster. The generated descriptions are saved to text files in the current working directory. + +The script defines a `run_cmd` function that takes a list of command line arguments and runs the corresponding command using OCaml's built-in `Unix` module. This function is used by `do_apply_list` to run the language model and generate descriptions for each prompt. + +Overall, this script appears to be part of a larger system for generating content for a fantasy role-playing game using a language model and a proof engine combined via adaptive language agent architecture. The generated descriptions could be used as input for further processing, such as creating game assets or designing game mechanics. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_1.txt b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_1.txt new file mode 100644 index 0000000..6bd1a59 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_1.txt @@ -0,0 +1,160 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please imagine the simulation its execution. Imagine running the code and all the output it would generate. Generate a grammar that we can use to generate prompts for create the dungeon using your knowledge. Write the grammar in EBNF notation. We will start with path through the dungeon starting at the entrance and going all the way to the ends. + +#+end_src +#+begin_src output mixtral + Result: Here is an example of an EBNF grammar for generating prompts for creating a path through a dungeon: + +path ::= place1 -> place2 | path -> place3 +place1, place2, place3 ::= entrance | room | hallway | treasure\_room | boss\_room +entrance ::= "the entrance of the dungeon" +room ::= "a random room in the dungeon" +hallway ::= "a hallway leading to another part of the dungeon" +treasure\_room ::= "a room containing valuable treasure" +boss\_room ::= "the final boss's lair" + +This grammar can be used to generate prompts like: + +* Generate a variant array of paths from the entrance to a random room. +* Generate a variant array of paths from a hallway to a room with valuable treasure. +* Generate a variant array of paths from a random room to the final boss's lair. + +You can expand this grammar by adding more types of places and variations on the path structure to generate a wide variety of prompts for your dungeon generator. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_10.txt b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_10.txt new file mode 100644 index 0000000..ca87da4 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_10.txt @@ -0,0 +1,166 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please imagine the simulation its execution. Imagine running the code and all the output it would generate. Generate a grammar that we can use to generate prompts for create the dungeon using your knowledge. Write the grammar in EBNF notation. We will start with path through the dungeon starting at the entrance and going all the way to the ends. + +#+end_src +#+begin_src output mixtral + Result: Here is an example of an EBNF grammar that can be used to generate prompts for creating a path through a dungeon: + +path ::= entrance room* exit + +entrance ::= "the entrance" + +exit ::= "the exit" | "a treasure room" + +room ::= place connected\_place + +place ::= "a room with" type\_name + +connected\_place ::= "connected to" place | "at the end of a hallway" + +type\_name ::= "a monster-filled" | "a trap-filled" | "a treasure-filled" + +This grammar can generate prompts like "Imagine a path through the dungeon starting at the entrance and ending at a treasure room. The first room is a monster-filled room connected to a trap-filled room." + +You could also add other elements from your code, such as verbs or top terms, to make the prompts more varied and interesting. For example: + +path ::= (top\_term "a" type\_name) entrance room* exit + +where top\_term is a term chosen from the list [Imagine; Consider; Draw; Paint; Compose; Balance]. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_11.txt b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_11.txt new file mode 100644 index 0000000..5d338a3 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_11.txt @@ -0,0 +1,158 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please imagine the simulation its execution. Imagine running the code and all the output it would generate. Generate a grammar that we can use to generate prompts for create the dungeon using your knowledge. Write the grammar in EBNF notation. We will start with path through the dungeon starting at the entrance and going all the way to the ends. + +#+end_src +#+begin_src output mixtral + Result: Here is an example of an EBNF grammar that could be used to generate prompts for creating a dungeon: +``` +dungeon_path = path_segment+; +path_segment = room_description space direction space room_description; +room_description = type_name "in" place | type_name "with a" type2_name "and" type3_name "in" place; +type_name = weapon | spell | artifact | magic_item | treasure | monster | quest | challenge | theme | drama | music | art | secret | occult | reveal | hero_journey; +type2_name = weapon | spell | artifact | magic_item | treasure | monster | quest | challenge | theme | drama | music | art | secret | occult | reveal | hero_journey; +type3_name = weapon | spell | artifact | magic_item | treasure | monster | quest | challenge | theme | drama | music | art | secret | occult | reveal | hero_journey; +place = the country | the region | the city | the street | the house | the building | the dungeon | the labyrinth | the cave | the swamp | the room | the hallway | the chest | the bag | the wallet | the vault | the keep | the hideout | platos_cave | garden_of_eden | the river_styx | the restaurant_at_the_end_of_the_universe; +direction = "to" | "from"; +space = " " | "\t"; +``` +This grammar describes a `dungeon\_path` as one or more `path\_segment`s. A `path\_segment` is made up of two `room\_description`s connected by a `direction`. A `room\_description` can be either a `type\_name` followed by "in" and a `place`, or a `type\_name` followed by "with a" `type2\_name`, "and" a `type3\_name`, and "in" a `place`. The `type\_name`, `type2\_name`, and `type3\_name` non-terminals can be any of the predefined types, such as weapon or spell. The `place` non-terminal can be any of the predefined places, such as the country or the dungeon. + +This grammar is just one example, and you could modify it to suit your specific needs. For example, you might want to add additional non-terminals for different types of rooms or places, or you might want to allow for more complex paths that include loops or branches. The key is to create a grammar that generates prompts that are both varied and easy to understand, so that the language model can generate creative and interesting descriptions for your dungeon generator. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_12.txt b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_12.txt new file mode 100644 index 0000000..30803a6 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_12.txt @@ -0,0 +1,176 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please imagine the simulation its execution. Imagine running the code and all the output it would generate. Generate a grammar that we can use to generate prompts for create the dungeon using your knowledge. Write the grammar in EBNF notation. We will start with path through the dungeon starting at the entrance and going all the way to the ends. + +#+end_src +#+begin_src output mixtral + Result: Here is an example of an EBNF grammar that could be used to generate prompts for creating a dungeon: +```less + ::= | "to" + ::= "" + ::= "weapon" | "spell" | "artifact" | "magic item" | "treasure" + | "monster" | "quest" | "challenge" | "theme" | "drama" + | "music" | "art" | "secret" | "occult" | "reveal" + ::= + ::= "a" | "an" | "the" + ::= | "," + ::= "role-play" | "specify" | "encode" | "code" | "program" + | "prove" | "create" | "design" | "create descriptions for an artist" + | "create descriptions for a comic book panel" + | "analyse" | "lift" | "shift" | "splice" | "quote" + | "quasi-quote" | "quasi-quine-quote" | "quasi-quine-quote-in-ocaml" + | "quasi-quine-quote-in-ocaml-coq-metacoq" + | "quasi-quine-quote-in-ocaml-coq-metacoq-introspector" + | "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap" + | "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe" + | "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient" + | "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide" + | "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act" + | "meta-quote" + ::= + ::= | "," +``` +This grammar allows for the generation of paths through a dungeon, where each room in the path is described by its type (e.g. weapon, spell), an adjective (e.g. "magic"), and a place name (e.g. "chest"). The path can be generated recursively, with each room leading to another room via a "to" keyword. + +The `` production allows for the generation of various verbs that could be used in the prompt, such as "create" or "program". These verbs can be modified by various adverbs (e.g. "quickly") and other modifiers (e.g. "doing"). + +The `` production allows for the generation of determiners such as "a", "an", or "the", which are used to specify nouns in English. The `` and `` productions allow for the generation of lists of adjectives and place names, respectively, separated by commas. + +This is just one example of how a grammar for generating prompts for creating a dungeon could be structured. There are many other possible ways to design such a grammar, depending on the desired level of detail and complexity. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_13.txt b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_13.txt new file mode 100644 index 0000000..7beac9d --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_13.txt @@ -0,0 +1,165 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please imagine the simulation its execution. Imagine running the code and all the output it would generate. Generate a grammar that we can use to generate prompts for create the dungeon using your knowledge. Write the grammar in EBNF notation. We will start with path through the dungeon starting at the entrance and going all the way to the ends. + +#+end_src +#+begin_src output mixtral + Result: Here is an example of an EBNF grammar for generating prompts for creating a dungeon: +```lua + ::= "Imagine" "connected with" ";" + ";" + "with a" ";" + "What is your response?" + + ::= "doing" + + ::= | "of" + + ::= "monster" | "treasure" | "weapon" | "spell" | "artifact" + + ::= "the" + + ::= "entrance" | "exit" | "room" | "hallway" | "chest" | "bag" + | "vault" | "keep" | "hideout" | "dungeon" | "labyrinth" + | "cave" | "swamp" | "street" | "city" | "region" | "country" +``` +This grammar allows you to generate prompts for creating a dungeon with different types of monsters, treasures, weapons, spells, and artifacts in various locations. The `` part of the prompt encourages the AI to perform an action related to the type name, while the `` part specifies where the action takes place. + +You can use this grammar as a starting point and extend it with more elements or variations depending on your specific needs. For example, you could add more nouns, verbs, or locations, or you could introduce new types of objects or actions. By using a generative grammar like this one, you can easily create many prompts for generating different parts of the dungeon, ensuring that the final result is diverse and interesting. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_2.txt b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_2.txt new file mode 100644 index 0000000..a2cddd0 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_2.txt @@ -0,0 +1,164 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please imagine the simulation its execution. Imagine running the code and all the output it would generate. Generate a grammar that we can use to generate prompts for create the dungeon using your knowledge. Write the grammar in EBNF notation. We will start with path through the dungeon starting at the entrance and going all the way to the ends. + +#+end_src +#+begin_src output mixtral + Result: Here is an example of an EBNF grammar that could be used to generate prompts for creating a path through a dungeon: + +path ::= path\_segment | ε + +path\_segment ::= "move" direction "through" location "to" next\_location + +direction ::= "north" | "south" | "east" | "west" + +location ::= room | corridor + +room ::= "a room" | "the entrance" | "the treasure room" | "a monster's lair" + +corridor ::= "a corridor" | "a dead end" | "a intersection" + +next\_location ::= room | corridor | "the exit" + +This grammar describes a path through the dungeon as a series of connected path segments. Each path segment consists of moving in a particular direction through a location to a next location. Locations can be rooms or corridors, and the final location in the path can be the exit. + +For example, using this grammar, a possible prompt for creating a path could be: "Move north through the entrance to a room, then move east through the room to an intersection, then move south through the intersection to a dead end." + +This is just one example of how a grammar for generating prompts for creating a dungeon might look. Depending on the specific requirements and constraints of the dungeon generator, other grammars could be used as well. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_3.txt b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_3.txt new file mode 100644 index 0000000..3338b66 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_3.txt @@ -0,0 +1,189 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please imagine the simulation its execution. Imagine running the code and all the output it would generate. Generate a grammar that we can use to generate prompts for create the dungeon using your knowledge. Write the grammar in EBNF notation. We will start with path through the dungeon starting at the entrance and going all the way to the ends. + +#+end_src +#+begin_src output mixtral + Result: Here is an example of an EBNF grammar for generating a path through a dungeon: + +path ::= path-segment | ε +path-segment ::= "move" direction "to" location +direction ::= "north" | "south" | "east" | "west" +location ::= room-name | description +room-name ::= [a-zA-Z]+ +description ::= "[a-zA-Z0-9\\s.,!?]*" +ε ::= the empty string (no characters) + +This grammar defines a path as a sequence of path-segments, which are made up of a "move" action followed by a direction and a location. The location can either be a room-name or a more detailed description. This allows for flexibility in how the locations in the dungeon are described. + +For example, the following would be a valid path according to this grammar: + +path: move north to the entrance +path-segment: move north to the entrance +direction: north +location: the entrance + +or + +path: move north to the dark, damp cave, move west to the treasure room with glowing crystals +path-segment: move north to the dark, damp cave +path-segment: move west to the treasure room with glowing crystals +direction: north +location: the dark, damp cave +direction: west +location: the treasure room with glowing crystals + +It is also possible to add more elements like enemies, traps, treasures and other elements in the path-segment or location. + +path ::= path-segment | ε +path-segment ::= "move" direction "to" location [encounter] +direction ::= "north" | "south" | "east" | "west" +location ::= room-name | description +room-name ::= [a-zA-Z]+ +description ::= "[a-zA-Z0-9\\s.,!?]*" +encounter ::= encounter-type encounter-details +encounter-type ::= "find" | "fight" | "bargain with" +encounter-details ::= enemy | treasure | trap +enemy ::= [a-zA-Z]+ +treasure ::= "[a-zA-Z0-9\\s.,!?]*" +trap ::= "[a-zA-Z0-9\\s.,!?]*" +ε ::= the empty string (no characters) + +This way you can add more information in the path and make it more interesting for the players. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_4.txt b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_4.txt new file mode 100644 index 0000000..ff743ad --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_4.txt @@ -0,0 +1,168 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please imagine the simulation its execution. Imagine running the code and all the output it would generate. Generate a grammar that we can use to generate prompts for create the dungeon using your knowledge. Write the grammar in EBNF notation. We will start with path through the dungeon starting at the entrance and going all the way to the ends. + +#+end_src +#+begin_src output mixtral + Result: Here is an example of an EBNF grammar that could be used to generate prompts for creating a dungeon: + +dungeon := [room | hallway | chest | bag | wallet | vault | keep | hideout] +room := "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : enter; Type Name: room; Place: " place " What is your response?" +hallway := "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : walk; Type Name: hallway; Place: " place " What is your response?" +chest := "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : open; Type Name: chest; Place: " place " What is your response?" +bag := "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : search; Type Name: bag; Place: " place " What is your response?" +wallet := "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : check; Type Name: wallet; Place: " place " What is your response?" +vault := "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : unlock; Type Name: vault; Place: " place " What is your response?" +keep := "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : enter; Type Name: keep; Place: " place " What is your response?" +hideout := "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : enter; Type Name: hideout; Place: " place " What is your response?" +place := (entrance | room | hallway | chest | bag | wallet | vault | keep | hideout) + +In this grammar, a dungeon is defined as a series of connected rooms, hallways, chests, bags, wallets, vaults, keeps, and/or hideouts. Each type of location has its own prompt with the context (verb, type name, and place) that will be used to generate a response from a language model. The "place" production allows for recursively defining locations in terms of other locations, allowing for complex dungeon structures to be generated. + +To use this grammar, you would first define the starting location (e.g., the entrance), then use the productions to generate prompts for creating each connected location, following the structure defined by the grammar. For example, to create a simple dungeon with an entrance leading to a room and a chest, you would use the following prompts: + +* "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : enter; Type Name: entrance; Place: Entrance Hall What is your response?" +* "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : walk; Type Name: hallway; Place: Entrance Hall What is your response?" +* "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : enter; Type Name: room; Place: Room What is your response?" +* "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : search; Type Name: chest; Place: Room What is your response?" + +You would then use the responses from the language model to generate the actual content for each location, such as descriptions of the room or items in the chest. + +Note that this is just one example of a grammar for generating prompts for creating a dungeon, and you could easily modify it to suit your specific needs or preferences. You could also use different grammars for different parts of the dungeon (e.g., a separate grammar for puzzles or encounters) or combine multiple grammars into a single system. The key is to find a structure that works well for your application and allows you to generate interesting and diverse content. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_5.txt b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_5.txt new file mode 100644 index 0000000..93d5d4b --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_5.txt @@ -0,0 +1,161 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please imagine the simulation its execution. Imagine running the code and all the output it would generate. Generate a grammar that we can use to generate prompts for create the dungeon using your knowledge. Write the grammar in EBNF notation. We will start with path through the dungeon starting at the entrance and going all the way to the ends. + +#+end_src +#+begin_src output mixtral + Result: Here is an example of an EBNF grammar that could be used to generate prompts for creating a dungeon: +```less +prompt ::= "Imagine a " type_name " in a " place " as you " verb +type_name ::= "weapon" | "spell" | "artifact" | "magic item" | "treasure" | "monster" | "quest" | "challenge" | "theme" | "drama" | "music" | "art" | "secrets" | "occult" | "reveal" | "hero journey" +place ::= "entrance" | "corridor" | "room" | "hallway" | "chamber" | "vault" | "dungeon" | "keep" | "hideout" +verb ::= "design" | "create" | "draw" | "paint" | "compose" | "balance" +``` +This grammar allows for the generation of prompts that ask the user to imagine a specific type of object or element in a particular location and to perform a certain action on it, such as designing or creating. The `type_name`, `place`, and `verb` non-terminals can be instantiated with any of the provided options, allowing for a wide variety of prompts to be generated. + +Using this grammar, we could generate a prompt that asks the user to imagine a weapon in the entrance and design it as follows: +``` +Imagine a weapon in a entrance as you design +``` +Or, if we wanted to ask the user to create a monster in a vault and paint it, we could use the following prompt: +``` +Imagine a monster in a vault as you paint +``` +This grammar provides a simple and flexible way to generate prompts for creating a dungeon, allowing us to easily specify the type of object or element we want the user to imagine and the action we want them to perform on it. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_6.txt b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_6.txt new file mode 100644 index 0000000..5b0419d --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_6.txt @@ -0,0 +1,160 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please imagine the simulation its execution. Imagine running the code and all the output it would generate. Generate a grammar that we can use to generate prompts for create the dungeon using your knowledge. Write the grammar in EBNF notation. We will start with path through the dungeon starting at the entrance and going all the way to the ends. + +#+end_src +#+begin_src output mixtral + Result: Here is an example of an EBNF grammar that could be used to generate prompts for creating a path through a dungeon: + +path ::= entrance room* exit + +entrance ::= "the entrance" + +room ::= "a room" | "another room" | "the next room" + +exit ::= "the exit" + +Each non-terminal symbol in the grammar represents a part of the path through the dungeon. The start symbol is "path," which consists of an entrance, zero or more rooms, and an exit. The other non-terminal symbols represent specific parts of the path. For example, the "entrance" non-terminal always represents "the entrance," while the "room" non-terminal can be one of three different phrases. + +To generate a prompt using this grammar, you would first choose a phrase for each non-terminal symbol, and then concatenate them together into a single string. For example, here is a possible prompt generated using this grammar: + +"We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : imagine; Type Name: path; Place: the entrance What is your response? Please generate variant array of size 1" + +This prompt asks the model to imagine a path through a dungeon, starting at the entrance and ending at the exit. It specifies that the type name is "path," and that the place is "the entrance." The verb "imagine" is used to encourage the model to be creative and use its imagination when generating the path. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_7.txt b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_7.txt new file mode 100644 index 0000000..48c2d5f --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_7.txt @@ -0,0 +1,162 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please imagine the simulation its execution. Imagine running the code and all the output it would generate. Generate a grammar that we can use to generate prompts for create the dungeon using your knowledge. Write the grammar in EBNF notation. We will start with path through the dungeon starting at the entrance and going all the way to the ends. + +#+end_src +#+begin_src output mixtral + Result: Here is an example of an EBNF grammar for generating prompts for creating a dungeon: +```css + ::= "Imagine" "; Type Name: " "; Place: "" "What is your response?" + ::= | + ::= + ::= "with a" + ::= + ::= + ::= + + ::= "specify" | "encode" | "code" | "program" | "prove" | "create" | "design" | "analyse" | "lift" | "shift" | "splice" | "quote" | "quasi-quote" | "quasi-quine-quote" | "quasi-quine-quote-in-ocaml" | "quasi-quine-quote-in-ocaml-coq-metacoq" | "quasi-quine-quote-in-ocaml-coq-metacoq-introspector" | "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap" | "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe" | "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient" | "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide" | "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act" | "meta-quote" + ::= "weapon" | "spell" | "artifacts" | "magic items" | "treasure" | "monster" | "quest" | "challenge" | "theme" | "drama" | "music" | "art" | "secrets" | "occult" | "reveal" | "hero journey" + ::= "the country" | "the region" | "the city" | "the street" | "the house" | "the building" | "the dungeon" | "the labyrinth" | "the cave" | "the swamp" | "the room" | "the hall" | "the corridor" | "the entrance" | "the exit" +``` +This grammar can be used to generate prompts for creating different elements of the dungeon, such as weapons, spells, artifacts, monsters, quests, challenges, themes, drama, music, art, secrets, occult, reveal and hero journey. The grammar allows for simple verb phrases or compound verb phrases, which can include a type name. For example, "specify weapon" or "specify weapon with a magic item". +Additionally, the grammar includes a list of places where the player could be in the dungeon, such as the country, region, city, street, house, building, dungeon, labyrinth, cave, swamp, room, hall, corridor, entrance and exit. The verb phrase is then connected to the place, for example "specify weapon with a magic item in the dungeon". +This grammar can be used as a starting point for generating prompts for creating a more complex and interactive simulation of a dungeon. + +Note: This grammar is just an example and it may need some adjustments to fit your specific use case, but it should give you a good idea of how to structure the grammar. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_8.txt b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_8.txt new file mode 100644 index 0000000..0ed12d1 --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_8.txt @@ -0,0 +1,162 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please imagine the simulation its execution. Imagine running the code and all the output it would generate. Generate a grammar that we can use to generate prompts for create the dungeon using your knowledge. Write the grammar in EBNF notation. We will start with path through the dungeon starting at the entrance and going all the way to the ends. + +#+end_src +#+begin_src output mixtral + Result: Here is an example of an EBNF grammar for generating a path through a dungeon: +```makefile + ::= { } + ::= | + ::= "connected with" | "leading to" + ::= "the entrance" | "the exit" | + ::= "a room with a " " named " + ::= "weapon" | "spell" | "artifact" | "magic item" | "treasure" + ::= { " and a " } + ::= "sword" | "staff" | "chest" | "scroll" + ::= { | } + ::= "a" | "b" | "c" | ... | "z" + ::= "0" | "1" | "2" | ... | "9" +``` +This grammar defines a path as a sequence of rooms connected by some form of connection. A room can be either a named place, such as the entrance or the exit, or a description of a room with a specific type of item. The type of item is represented by a `type_name`, which can be any of the terms in the `type_terms` list defined earlier. The `term` represents the name of the item and can consist of multiple words separated by spaces. + +The grammar also includes rules for generating place names, such as the entrance or the exit, and descriptions of rooms with specific types of items. The `identifier` rule allows for the generation of unique names for rooms using a combination of letters and numbers. + +This is just one example of how a grammar could be defined to generate prompts for creating a dungeon. There are many other ways to define such a grammar, and the specific details will depend on the desired structure and complexity of the generated prompts. +#+end_src diff --git a/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_9.txt b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_9.txt new file mode 100644 index 0000000..80b461f --- /dev/null +++ b/data/dungeon/sim_dungeon_1_2024-02-18T12:03:17-05:00_9.txt @@ -0,0 +1,166 @@ + +#+begin_src input +The goal is to create a flexible and customizable system for generating prompts for a language model that can be used to generate creative and imaginative descriptions of a dungeon in a fantasy role-playing game. +the game would involve exploring a dungeon generated using a large language model and a proof engine. The player would navigate through the dungeon, encountering various objects and NPCs along the way, each with their own set of properties and behaviors defined by the terms used in the script. + +the game would involve exploring a dungeon and encountering various types of monsters, treasures, and challenges. The player would use weapons, spells, and artifacts to defeat the monsters and complete quests, all while navigating a labyrinthine cave or other underground environment. The game might also include elements of drama, music, and art, as well as secrets and occult themes. + +Overall, it seems that the code is designed to generate a richly detailed and immersive fantasy RPG experience using a combination of natural language processing and formal methods. By using a large language model and a proof engine, the game could potentially offer a high degree of realism and interactivity, allowing players to explore and interact with the dungeon in flexible and unpredictable ways. +The script is being used to generate and test various combinations of terms to create content for a fantasy role-playing game. The generated content include descriptions of weapons, spells, artifacts, monsters, quests, and other elements of a typical RPG setting. +Here is the code we wrote so far +let type_terms = [ + "weapon"; + "spell"; + "artifacts"; + "magic items"; + "treasure"; + "monster"; + "quest"; + "challege"; + "theme"; + "drama"; + "music"; + "art"; + "secrets"; + "occult"; + "reveal"; + "hero journey" +] +let model_name = "mixtral" +let url= "https://dev-hub.agentartificial.com" +let verbs = [ + "role-play"; + "specify";"encode";"code"; "program";"prove"; + "create"; "design"; + "create descriptions for an artist"; + "create descriptions for an artist to design a comic book panel"; + "analyse";"lift";"shift";"splice";"quote"; + "quasi-quote"; + "quasi-quine-quote"; + "quasi-quine-quote-in-ocaml"; + "quasi-quine-quote-in-ocaml-coq-metacoq"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-observe"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-orient"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-decide"; + "quasi-quine-quote-in-ocaml-coq-metacoq-introspector-bootstrap-act"; + "meta-quote" +] +let top_terms = ["Imagine"; + "Consider"; + "Draw"; + "Paint"; + "Compose"; + "Balance"] + +let places = [ + "the country"; + "the region"; + "the city"; + "the street"; + "the house"; + "the building"; + "the dungeon"; + "the labyrinth"; + "the cave"; + "the swamp"; + "the room"; + "the hallway"; + "the chest"; + "the bag"; + "the wallet"; + "the vault"; + "the keep"; + "the hideout"; + "platos cave"; + "garden of eden"; + "the river styx"; + "the restaurant at the end of the universe"; +] + +let count= 3 +let simple = "dune exec ./bin/simple.exe --" +let binding = "--openai" +let test_name = "dungeon2" + +let prompt type_name try_n verb place= + "\"" ^ + "We are building a dungeon generator for a fantasy role-playing game with a large language model and a proof engine combined via adaptive language agent architecture. In that context we ask you to forgivingly and creatively use the following context: Verb : " ^ verb ^ "; Type Name: " ^ type_name ^ "; Place: " ^ place ^ " What is your response?" ^ " Please generate variant array of size " ^ ( string_of_int try_n) ^ "\"" + +let make_args type_name i verb place= [ + simple; + binding; + "-m"; model_name; + "-s"; test_name ^ type_name ^ verb; + "-x"; ".new_" ^ (string_of_int i) ^ verb ^ type_name ^ place ^ ".txt"; + "-p"; prompt type_name i verb place; + "-u"; url; +] + + +let do_apply_list run_cmd make_args type_terms = + for i = 1 to count do + List.iter (fun top -> + List.iter (fun term -> + List.iter (fun term2 -> + List.iter (fun verb -> + List.iter (fun place -> + List.iter (fun place2 -> + let term3 = term ^ " with a " ^ term2 in + let verb2 = top ^ " doing " ^ verb in + let place3 = place ^ " connected with " ^ place2 in + let args = make_args + term3 i verb2 + place3 in + run_cmd args + ) places + ) places + ) verbs + ) type_terms + ) type_terms + ) top_terms + done + +let run_cmd args = + let cmd = String.concat " " args in + Printf.printf "Cmd: %s\n" cmd; + let inp = Unix.open_process_in cmd in + let r = In_channel.input_line inp in + In_channel.close inp; + match r with + |Some out -> + Printf.printf "Output: %s\n" out + |None -> + Printf.printf "Output: None\n" + +let () =do_apply_list run_cmd make_args type_terms + + ENDSRC . Please imagine the simulation its execution. Imagine running the code and all the output it would generate. Generate a grammar that we can use to generate prompts for create the dungeon using your knowledge. Write the grammar in EBNF notation. We will start with path through the dungeon starting at the entrance and going all the way to the ends. + +#+end_src +#+begin_src output mixtral + Result: Here is an example of an EBNF grammar that could be used to generate prompts for creating a dungeon: +```css + ::= "Imagine" "a path through the dungeon starting at the entrance and going all the way to the end, with:" + + ::= []* + + ::= "a room with a" [] + + ::= "moving from" "to" + + ::= "weapon" | "spell" | "artifact" | "magic item" | "treasure" | "monster" | "quest" | "challenge" | "theme" | "drama" | "music" | "art" | "secret" | "occult" | "reveal" | "hero journey" + + ::= []* + + ::= "filled with" | "full of" | "with a" + + ::= "trap" | "puzzle" | "guard" | "riddle" | "hidden door" | "pressure plate" | "trip wire" | "monster den" | "prize" | "altar" | "statue" + + ::= | "the entrance" | "the end" +``` +This grammar allows for generating prompts that describe a path through the dungeon, starting at the entrance and going all the way to the end. Each room in the path is described by its type (e.g. weapon, treasure) and any additional features it may have, such as traps or guards. The path between rooms is also described, including the type of connection (e.g. door, ladder, hidden passage). + +This grammar can be extended to include more detailed descriptions, different types of rooms, and other elements of a typical RPG setting. It can also be used in conjunction with other grammars to generate prompts for creating specific types of content, such as art or music. +#+end_src