few_shots_benchmark.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Trying to see what is the most optimal number of few shot prompts to use in the agent answer generation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create some partials for the agents \n",
    "\n",
    "from chat_llm import ReflectingAgent, ChatThread, load_chat\n",
    "from llm_engines import LLMApi, ChatgptLLM\n",
    "from functools import partial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "john_partial = partial(ReflectingAgent, name=\"John\",llm=LLMApi(), interests=[\"gossip\",\"f1\", \"climate change\"], behavior=[\"smart\",\"reflective\",\"funny\"], n_last_messages=10, n_last_messages_reflection=20)\n",
    "mary_partial = partial(ReflectingAgent, name=\"Mary\",llm=LLMApi(), interests=[\"bouldering\", \"italian movies\", \"playing the arp\"], behavior=[\"kind\", \"creative\", \"friendly\"], n_last_messages=10, n_last_messages_reflection=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# a list of number of examples for each agent\n",
    "import os \n",
    "\n",
    "n_examples = [1,2,3,5,10,15,20,25]\n",
    "\n",
    "# for n in n_examples:\n",
    "#     john = john_partial(n_examples=n)\n",
    "#     mary = mary_partial(n_examples=n)\n",
    "#     # run 10 chat per configuration\n",
    "#     for i in range(10):\n",
    "#         chat = ChatThread(agent_list=[john,mary], neutral_llm=LLMApi())\n",
    "#         chat.run_chat(max_turns=75)\n",
    "        \n",
    "#         try:\n",
    "#             # find latest chat in the chat_logs folder\n",
    "#             latest_chat= max([f for f in os.listdir(\"chat_logs\") if f.startswith(\"chat\")], key=os.path.getctime)\n",
    "#             print(f\"Chat {i} with {n} examples saved as \")\n",
    "#         except:\n",
    "#             continue\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import os\n",
    "from chat_llm import load_chat\n",
    "\n",
    "\n",
    "# load the last chat\n",
    "\n",
    "\n",
    "chat_paths= [os.path.join(\"chat_logs\",f) for f in os.listdir(\"chat_logs\") if f.startswith(\"chat\")]\n",
    "chat_paths.sort(key=os.path.getctime)\n",
    "\n",
    "# get latest chat\n",
    "chat_path = chat_paths[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load chat\n",
    "chat = load_chat(chat_path)\n",
    "\n",
    "def plot_evaluation(eval):\n",
    "    import matplotlib.pyplot as plt\n",
    "    import numpy as np\n",
    "    from collections import Counter\n",
    "\n",
    "    # get the evaluation of the chat\n",
    "    evaluation = eval\n",
    "    step_eval=[  ]\n",
    "    total_eval=[  ]\n",
    "    \n",
    "    \n",
    "    \n",
    "    for key in evaluation:\n",
    "        step_eval.append((key,evaluation[key][\"step_evaluation\"]))\n",
    "        total_eval.append((key,evaluation[key][\"evaluation\"]))\n",
    "\n",
    "    \n",
    "    # plot the evaluation\n",
    "    fig, ax = plt.subplots()\n",
    "    # plot two trend lines over turn count\n",
    "    ax.plot([x[0] for x in step_eval],[x[1] for x in step_eval], label=\"Step evaluation\")\n",
    "    ax.plot([x[0] for x in total_eval],[x[1] for x in total_eval], label=\"Total evaluation\")\n",
    "    \n",
    "    print(\"Step evaluation\",step_eval)\n",
    "    print(\"Total evaluation\",total_eval)\n",
    "    \n",
    "    ax.legend()\n",
    "    \n",
    "    ax.set_xlabel('Turn count')\n",
    "    ax.set_ylabel('Evaluation')\n",
    "    ax.set_title('Evaluation of the chat')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step evaluation [('25', 10.0), ('50', 9.666666666666666)]\n",
      "Total evaluation [('25', 10.0), ('50', 10.0)]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_evaluation(chat.chat_evaluation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skipping chat chat_logs/chat_1707259742.json\n",
      "Skipping chat chat_logs/chat_1707262865.json\n",
      "Skipping chat chat_logs/chat_1707265926.json\n",
      "Skipping chat chat_logs/chat_1707268588.json\n",
      "Skipping chat chat_logs/chat_1707271188.json\n",
      "Skipping chat chat_logs/chat_1707273897.json\n",
      "Skipping chat chat_logs/chat_1707276892.json\n",
      "Skipping chat chat_logs/chat_1707279637.json\n",
      "Skipping chat chat_logs/chat_1707282819.json\n",
      "Skipping chat chat_logs/chat_1707285653.json\n",
      "Skipping chat chat_logs/chat_1707288571.json\n",
      "Skipping chat chat_logs/chat_1707291427.json\n",
      "Skipping chat chat_logs/chat_1707295461.json\n",
      "Skipping chat chat_logs/chat_1707298112.json\n",
      "Skipping chat chat_logs/chat_1707300718.json\n",
      "Skipping chat chat_logs/chat_1707303473.json\n",
      "Skipping chat chat_logs/chat_1707306340.json\n",
      "Skipping chat chat_logs/chat_1707308935.json\n",
      "Skipping chat chat_logs/chat_1707311862.json\n",
      "Skipping chat chat_logs/chat_1707314206.json\n",
      "Skipping chat chat_logs/chat_1707316441.json\n",
      "Skipping chat chat_logs/chat_1707319814.json\n",
      "Skipping chat chat_logs/chat_1707323501.json\n",
      "Skipping chat chat_logs/chat_1707325834.json\n",
      "Skipping chat chat_logs/chat_1707329158.json\n",
      "Skipping chat chat_logs/chat_1707332357.json\n",
      "Skipping chat chat_logs/chat_1707335077.json\n",
      "Skipping chat chat_logs/chat_1707337760.json\n",
      "Skipping chat chat_logs/chat_1707340260.json\n",
      "Skipping chat chat_logs/chat_1707343318.json\n",
      "Skipping chat chat_logs/chat_1707346281.json\n",
      "Skipping chat chat_logs/chat_1707351503.json\n",
      "Skipping chat chat_logs/chat_1707354030.json\n",
      "Skipping chat chat_logs/chat_1707357429.json\n",
      "Skipping chat chat_logs/chat_1707360088.json\n",
      "Skipping chat chat_logs/chat_1707363454.json\n",
      "Skipping chat chat_logs/chat_1707366099.json\n",
      "Skipping chat chat_logs/chat_1707370126.json\n",
      "Skipping chat chat_logs/chat_1707372179.json\n",
      "Skipping chat chat_logs/chat_1707374650.json\n",
      "Skipping chat chat_logs/chat_1707377396.json\n",
      "Skipping chat chat_logs/chat_1707382384.json\n",
      "Skipping chat chat_logs/chat_1707386622.json\n",
      "Skipping chat chat_logs/chat_1707391453.json\n",
      "Skipping chat chat_logs/chat_1707395142.json\n",
      "Skipping chat chat_logs/chat_1707399291.json\n",
      "Skipping chat chat_logs/chat_1707402449.json\n",
      "Skipping chat chat_logs/chat_1707408005.json\n",
      "Skipping chat chat_logs/chat_1707411425.json\n",
      "Skipping chat chat_logs/chat_1707420029.json\n",
      "Skipping chat chat_logs/chat_1707424211.json\n",
      "Skipping chat chat_logs/chat_1707430853.json\n",
      "Skipping chat chat_logs/chat_1707434287.json\n",
      "Skipping chat chat_logs/chat_1707439176.json\n",
      "Skipping chat chat_logs/chat_1707443972.json\n",
      "Skipping chat chat_logs/chat_1707452544.json\n",
      "Skipping chat chat_logs/chat_1707457519.json\n",
      "Skipping chat chat_logs/chat_1707463978.json\n",
      "Skipping chat chat_logs/chat_1707471671.json\n",
      "Skipping chat chat_logs/chat_1707475483.json\n",
      "Skipping chat chat_logs/chat_1707480158.json\n",
      "Skipping chat chat_logs/chat_1707484888.json\n",
      "Skipping chat chat_logs/chat_1707488441.json\n",
      "Skipping chat chat_logs/chat_1707492353.json\n",
      "Skipping chat chat_logs/chat_1707497085.json\n",
      "Skipping chat chat_logs/chat_1707502471.json\n",
      "Skipping chat chat_logs/chat_1707507082.json\n",
      "Skipping chat chat_logs/chat_1707514978.json\n",
      "Skipping chat chat_logs/chat_1707529853.json\n",
      "Skipping chat chat_logs/chat_1707533501.json\n",
      "Skipping chat chat_logs/chat_1707538833.json\n",
      "Skipping chat chat_logs/chat_1707549032.json\n",
      "Skipping chat chat_logs/chat_1707553244.json\n",
      "Skipping chat chat_logs/chat_1707558176.json\n",
      "Skipping chat chat_logs/chat_1707562316.json\n",
      "Skipping chat chat_logs/chat_1707568022.json\n",
      "Skipping chat chat_logs/chat_1707572630.json\n",
      "Skipping chat chat_logs/chat_1707581311.json\n",
      "Skipping chat chat_logs/chat_1707585517.json\n",
      "Skipping chat chat_logs/chat_1707591035.json\n",
      "Skipping chat chat_logs/chat_1707607684.json\n",
      "Skipping chat chat_logs/chat_1707680564.json\n"
     ]
    }
   ],
   "source": [
    "# for each chat path, find the n_examples and put the chat eval in a dict\n",
    "\n",
    "chat_evals = {}\n",
    "for chat_path in chat_paths:\n",
    "    # load chat\n",
    "    chat = load_chat(chat_path)\n",
    "    # check if llm is chatgpt\n",
    "    if chat.neutral_llm.__class__ == ChatgptLLM:\n",
    "        # check for react \n",
    "        if chat.agent_list[0].react:\n",
    "            n_examples = chat.agent_list[0].n_examples\n",
    "            chat_evals[(n_examples,\"react\")] = chat.chat_evaluation\n",
    "        else:\n",
    "            n_examples = chat.agent_list[0].n_examples\n",
    "            chat_evals[(n_examples,\"no_react\")] = chat.chat_evaluation\n",
    "    else:\n",
    "        # print(\"Chat is not chatgpt\")\n",
    "        print(f\"Skipping chat {chat_path}\")\n",
    "        continue\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{(1, 'react'): {'25': {'evaluation': 10.0, 'step_evaluation': 10.0},\n",
       "  '50': {'evaluation': 10.0, 'step_evaluation': 9.666666666666666}}}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat_evals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of chat with 1 examples and react: 2\n"
     ]
    }
   ],
   "source": [
    "# get number of chat per n_examples\n",
    "for key in chat_evals:print(f\"Number of chat with {key[0]} examples and {key[1]}: {len(chat_evals[key])}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "string indices must be integers, not 'str'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[10], line 10\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 10\u001b[0m     average_evals[key][turn][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstep_evaluation\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mappend(chat_eval[turn][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstep_evaluation\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[1;32m     11\u001b[0m     average_evals[key][turn][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mevaluation\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mappend(chat_eval[turn][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mevaluation\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n",
      "\u001b[0;31mKeyError\u001b[0m: '2'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[10], line 13\u001b[0m\n\u001b[1;32m     11\u001b[0m             average_evals[key][turn][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mevaluation\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mappend(chat_eval[turn][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mevaluation\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[1;32m     12\u001b[0m         \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[0;32m---> 13\u001b[0m             average_evals[key][turn] \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstep_evaluation\u001b[39m\u001b[38;5;124m\"\u001b[39m:[chat_eval[turn][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstep_evaluation\u001b[39m\u001b[38;5;124m\"\u001b[39m]], \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mevaluation\u001b[39m\u001b[38;5;124m\"\u001b[39m:[chat_eval[turn][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mevaluation\u001b[39m\u001b[38;5;124m\"\u001b[39m]]}\n\u001b[1;32m     14\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m turn \u001b[38;5;129;01min\u001b[39;00m average_evals[key]:\n\u001b[1;32m     15\u001b[0m     average_evals[key][turn][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstep_evaluation\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mmean(average_evals[key][turn][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstep_evaluation\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n",
      "\u001b[0;31mTypeError\u001b[0m: string indices must be integers, not 'str'"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "# take the average eval per n_examples per turn\n",
    "average_evals = {}\n",
    "for key in chat_evals:\n",
    "    average_evals[key] = {}\n",
    "    for chat_eval in chat_evals[key]:\n",
    "        for turn in chat_eval:\n",
    "            try:\n",
    "                average_evals[key][turn][\"step_evaluation\"].append(chat_eval[turn][\"step_evaluation\"])\n",
    "                average_evals[key][turn][\"evaluation\"].append(chat_eval[turn][\"evaluation\"])\n",
    "            except:\n",
    "                average_evals[key][turn] = {\"step_evaluation\":[chat_eval[turn][\"step_evaluation\"]], \"evaluation\":[chat_eval[turn][\"evaluation\"]]}\n",
    "    for turn in average_evals[key]:\n",
    "        average_evals[key][turn][\"step_evaluation\"] = np.mean(average_evals[key][turn][\"step_evaluation\"])\n",
    "        average_evals[key][turn][\"evaluation\"] = np.mean(average_evals[key][turn][\"evaluation\"])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_782657/3697121418.py:10: MatplotlibDeprecationWarning: Auto-removal of overlapping axes is deprecated since 3.6 and will be removed two minor releases later; explicitly call ax.remove() as needed.\n",
      "  ax = plt.subplot(4, 2, i + 1, sharey=fig.axes[0])\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x1500 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# plot everything in subplots title with n_examples\n",
    "fig, ax = plt.subplots(3, 2, figsize=(15, 15), sharex=True, sharey=True)\n",
    "fig.suptitle(\"Average evaluation of the chat per turn with different number of examples\")\n",
    "\n",
    "# order average evals by n_examples\n",
    "average_evals = dict(sorted(average_evals.items()))\n",
    "for i, key in enumerate(average_evals):\n",
    "    ax = plt.subplot(4, 2, i + 1, sharey=fig.axes[0])\n",
    "    ax.set_title(f\"n_examples: {key}\")\n",
    "\n",
    "    step_eval = []\n",
    "    total_eval = []\n",
    "\n",
    "    for turn in average_evals[key]:\n",
    "        step_eval.append((turn, average_evals[key][turn][\"step_evaluation\"]))\n",
    "        total_eval.append((turn, average_evals[key][turn][\"evaluation\"]))\n",
    "\n",
    "    ax.plot([x[0] for x in step_eval], [x[1] for x in step_eval], label=\"Step evaluation\")\n",
    "    ax.plot([x[0] for x in total_eval], [x[1] for x in total_eval], label=\"Total evaluation\")\n",
    "    ax.legend()\n",
    "    ax.set_xlabel('Turn count')\n",
    "    ax.set_ylabel('Evaluation')\n",
    "    ax.set_title(f'Evaluation of the chat with {key} examples')\n",
    "\n",
    "\n",
    "\n",
    "plt.subplots_adjust(hspace=0.5)  # Adjust the vertical spacing between subplots\n",
    "# diminish the space between the title and the plots\n",
    "plt.tight_layout(rect=[0, 0.03, 1, 0.95])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat_evals"
   ]
  }
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