work in progress

README.md

@@ -48,3 +48,15 @@ Run the following commands from the agents directory to run an ephemeral docker
 ./scripts/bash/build-docker.sh
 ./scripts/bash/run-docker-dev.sh
 ```
+
+# Future
+
+This repo is intended to be an experimental developer toolkit. In order to productionize the system with capital, we recommend the following major projects begin to be developed:
+
+[ ] Backtesting
+[ ] Papertrading
+
+Other major development endeavors that would support the current state of the system include:
+
+[ ] External embeddings
+[ ] More news api sources

ai/llm/executor.py

@@ -1,15 +1,20 @@
 import os
+import time
+import json
 
 from dotenv import load_dotenv
 from langchain_core.messages import HumanMessage, SystemMessage
 from langchain_openai import ChatOpenAI
+from langchain_openai import OpenAIEmbeddings
 
 from ai.llm import prompts
 from api.gamma import GammaMarketClient
-from polymarket.agents.ai.llm.prompts import Prompter
+from ai.llm.prompts import Prompter
+from ai.rag.chroma import Chroma
 
 
 class Executor:
+
     def __init__(self):
         load_dotenv()
         self.prompter = Prompter()
@@ -18,7 +23,13 @@ def __init__(self):
             model="gpt-3.5-turbo",
             temperature=0,
         )
+        self.llm_embedding_function = OpenAIEmbeddings(model="text-embedding-3-small")
         self.client = GammaMarketClient()
+        self.chroma = Chroma()
+
+        self.local_data_directory = "./localDb"
+        if not os.path.isdir(self.local_data_directory):
+            os.mkdir(self.local_data_directory)
 
     def get_llm_response(self, user_input: str) -> str:
         system_message = SystemMessage(content=str(prompts.market_analyst))
@@ -47,8 +58,32 @@ def get_polymarket_llm(self, user_input: str) -> str:
         result = self.llm.invoke(messages)
         return result.content
 
-    def filter_events(self):
-        pass
+    def filter_events(self, events):
+        if not self.chroma:
+            # create local embedding for events
+            local_events_embedding_path = f"{self.local_data_directory}/events.json"
+            if os.path.isfile(self.local_data_directory):
+                os.remove(local_events_embedding_path)
+            with open(local_events_embedding_path, "w+") as output_file:
+                json.dump(events, output_file)
+
+            # load embedding into chroma
+            local_db = Chroma(
+                persist_directory=self.local_data_directory,
+                embedding_function=self.llm_embedding_function,
+            )
+
+            # query using a prompt
+            prompt = self.prompter.filter_events()
+            print(prompt)
+            response_docs = local_db.similarity_search_with_score(query=prompt)
+            print(response_docs)
+            return response_docs
+
+        else:
+            self.chroma.create_local_markets_rag()
+            prompt = self.prompter.filter_events()
+            return self.chroma.query_local_markets_rag(prompt)
 
     def filter_markets(self):
         pass

ai/llm/prompts.py

@@ -121,7 +121,7 @@ def polymarket_analyst_api(self) -> str:
 
     def filter_events(self) -> str:
         return (
-            self.polymarket_analyst_api(self)
+            self.polymarket_analyst_api()
             + """
         
         Filter events for the ones you will be best at trading on profitably.

ai/rag/chroma.py

@@ -8,14 +8,14 @@
 from api.gamma import GammaMarketClient
 
 
-class PolymarketRAG:
+class Chroma:
     def __init__(self, local_db_directory=None, embedding_function=None) -> None:
         self.gamma_client = GammaMarketClient()
         self.local_db_directory = local_db_directory
         self.embedding_function = embedding_function
 
     def load_json_from_local(
-        self, json_file_path=None, vector_db_directory="./local_db"
+        self, json_file_path=None, vector_db_directory="./localDb"
     ):
         loader = JSONLoader(
             file_path=json_file_path, jq_schema=".[].description", text_content=False
@@ -29,7 +29,7 @@ def load_json_from_local(
 
         return db2
 
-    def create_local_markets_rag(self, local_directory="./local_db"):
+    def create_local_markets_rag(self, local_directory="./localDb"):
         all_markets = self.gamma_client.get_all_current_markets()
 
         if not os.path.isdir(local_directory):
@@ -44,7 +44,7 @@ def create_local_markets_rag(self, local_directory="./local_db"):
             json_file_path=local_file_path, vector_db_directory=local_directory
         )
 
-    def query_local_markets_rag(self, local_directory=None, query=None):
+    def query_local_markets_rag(self, query=None, local_directory="./local_db"):
         embedding_function = OpenAIEmbeddings(model="text-embedding-3-small")
         local_db = Chroma(
             persist_directory=local_directory, embedding_function=embedding_function

api/polymarket.py

@@ -22,8 +22,8 @@
 from py_clob_client.clob_types import OrderArgs
 from py_clob_client.order_builder.constants import BUY
 
-from api.polymarket.types import SimpleMarket
-from api.polymarket.types import SimpleEvent
+from api.types import SimpleMarket
+from api.types import SimpleEvent
 
 load_dotenv()
 
@@ -45,8 +45,8 @@ def __init__(self):
         self.exchange_address = "0x4bfb41d5b3570defd03c39a9a4d8de6bd8b8982e"
         self.neg_risk_exchange_address = "0xC5d563A36AE78145C45a50134d48A1215220f80a"
 
-        self._init_api_keys()
-        self._init_approvals(True)
+        # self._init_api_keys()
+        # self._init_approvals(True)
 
     def _init_api_keys(self):
         self.client = ClobClient(

jobs/scheduler.py

@@ -1,15 +1,15 @@
 import datetime as dt
 import time
-from polymarket.agents.lib.trade import Trader
+from lib.trade import Trader
 
-from polymarket.agents.lib.history import record_history
-from polymarket.agents.lib.refresh import refresh_trades
+from lib.history import record_history
+from lib.refresh import refresh_trades
 
 from scheduler import Scheduler
 from scheduler.trigger import Monday
 
 
-class Scheduler:
+class MetaScheduler:
     def __init__(self):
         self.trader = Trader()
         self.schedule = Scheduler()
@@ -22,11 +22,14 @@ def start(self):
 
 class TradingAgent(Scheduler):
     def __init__(self):
-        super()
         self.trader = Trader()
-        self.weekly(Monday(), self.trader.one_best_trade)
-        self.daily(dt.time(hour=12), refresh_trades)
-        self.hourly(dt.time(minute=30), record_history)
+        self.schedule = Scheduler()
+        self.schedule.weekly(Monday(), self.trader.one_best_trade)
+        self.schedule.daily(dt.time(hour=12), refresh_trades)
+        self.schedule.hourly(dt.time(minute=30), record_history)
+
+    def trade(self):
+        self.trader.one_best_trade()
 
 
 # TODO: add task objects for generalized schedule management infrastructure

lib/creator.py

@@ -1,6 +1,6 @@
-from polymarket.agents.ai.llm.executor import Executor as Agent
-from polymarket.agents.api.polymarket import Polymarket
-from polymarket.agents.data.newspaper import Newspaper
+from ai.llm.executor import Executor as Agent
+from api.polymarket import Polymarket
+from data.newspaper import Newspaper
 
 
 class Creator:

lib/trade.py

@@ -1,6 +1,8 @@
-from polymarket.agents.ai.llm.executor import Executor as Agent
-from polymarket.agents.api.polymarket import Polymarket
-from polymarket.agents.data.newspaper import Newspaper
+from ai.llm.executor import Executor as Agent
+from api.polymarket import Polymarket
+from data.newspaper import Newspaper
+
+import pdb
 
 
 class Trader:
@@ -19,17 +21,23 @@ def one_best_trade(self):
         then executes that trade without any human intervention
 
         """
+
+        print("1. GETTING ALL EVENTS polymarket.get_all_events()")
         events = self.polymarket.get_all_events()
-        events = self.agent.filter_events()
-        markets = [self.polymarket.get_market(e) for e in events]
-        markets = self.agent.filter_markets()
-        orderbooks = [self.polymarket.get_orderbooks(m) for m in markets]
-        orderbooks = self.agent.filter_orderbooks()
-        best_trade = self.agent.source_best_trade(
-            events, markets, orderbooks, self.newspaper
-        )
-        formatted_best_trade = self.agent.format_trade_prompt_for_execution(best_trade)
-        return self.polymarket.execute_order(**formatted_best_trade)
+        print("2. GOT EVENTS. len(events) = ", len(events))
+        print("3. FILTERING EVENTS ...")
+        pdb.set_trace()
+        events = self.agent.filter_events([x.json() for x in events])
+        print("4. GOT BEST EVENTS: ", events)
+        # markets = [self.polymarket.get_market(e) for e in events]
+        # markets = self.agent.filter_markets()
+        # orderbooks = [self.polymarket.get_orderbooks(m) for m in markets]
+        # orderbooks = self.agent.filter_orderbooks()
+        # best_trade = self.agent.source_best_trade(
+        #     events, markets, orderbooks, self.newspaper
+        # )
+        # formatted_best_trade = self.agent.format_trade_prompt_for_execution(best_trade)
+        # return self.polymarket.execute_order(**formatted_best_trade)
 
     def maintain_positions(self):
         pass

scripts/python/cli.py

@@ -3,14 +3,14 @@
 
 from api.polymarket import Polymarket
 from ai.llm import executor, prompts
-from ai.rag.chroma import PolymarketRAG
+from ai.rag.chroma import Chroma
 from data.news.newsapiorg.api import API as NewsApiCaller
 from jobs.scheduler import TradingAgent
 
 app = typer.Typer()
 polymarket = Polymarket()
 newsapi_client = NewsApiCaller()
-polymarket_rag = PolymarketRAG()
+polymarket_rag = Chroma()
 
 
 @app.command()
@@ -118,12 +118,12 @@ def ask_polymarket_llm(user_input: str):
 
 
 @app.command()
-def run_autonomous_trader(user_input: str):
+def run_autonomous_trader():
     """
     Let an autonomous system trade for you.
     """
     trader = TradingAgent()
-    trader.start()
+    trader.trade()
 
 
 if __name__ == "__main__":

scripts/python/server.py

@@ -1,3 +1,13 @@
+"""
+
+We envision decentralized agents being able to 
+communicate with one another as they decide trades.
+
+This server could also be used for observability of
+decentralized agents trading performance.
+
+"""
+
 from typing import Union
 from fastapi import FastAPI
 
@@ -22,6 +32,3 @@ def read_trade(trade_id: int, q: Union[str, None] = None):
 @app.get("/markets/{market_id}")
 def read_market(market_id: int, q: Union[str, None] = None):
     return {"market_id": market_id, "q": q}
-
-
-# post new prompt