bot_with_memory_clean.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyM/ZHosGf1/+NXt6QIkFTJ5",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/satvik314/langchain/blob/main/bot_with_memory_clean.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install gpt-index langchain chromadb PyPDF2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IFG_IDw2N8YN",
        "outputId": "e9713ba4-ed21-4f44-e70d-30037086f090"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "  Downloading httptools-0.5.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (417 kB)\n",
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            "Building wheels for collected packages: hnswlib, sentence-transformers\n",
            "  Building wheel for hnswlib (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for hnswlib: filename=hnswlib-0.7.0-cp39-cp39-linux_x86_64.whl size=2118374 sha256=f5ef8a3f492ca15fc9b2295628076053ccee1bbea3ad8f41fb8688d56a1c6c19\n",
            "  Stored in directory: /root/.cache/pip/wheels/ba/26/61/fface6c407f56418b3140cd7645917f20ba6b27d4e32b2bd20\n",
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            "Successfully built hnswlib sentence-transformers\n",
            "Installing collected packages: tokenizers, sentencepiece, monotonic, duckdb, zstandard, websockets, uvloop, requests, python-dotenv, mypy-extensions, multidict, marshmallow, lz4, httptools, hnswlib, h11, frozenlist, backoff, async-timeout, yarl, watchfiles, uvicorn, typing-inspect, tiktoken, starlette, posthog, marshmallow-enum, huggingface-hub, clickhouse-connect, aiosignal, transformers, fastapi, dataclasses-json, aiohttp, openai, langchain, gpt-index, sentence-transformers, chromadb\n",
            "  Attempting uninstall: requests\n",
            "    Found existing installation: requests 2.27.1\n",
            "    Uninstalling requests-2.27.1:\n",
            "      Successfully uninstalled requests-2.27.1\n",
            "Successfully installed aiohttp-3.8.4 aiosignal-1.3.1 async-timeout-4.0.2 backoff-2.2.1 chromadb-0.3.21 clickhouse-connect-0.5.19 dataclasses-json-0.5.7 duckdb-0.7.1 fastapi-0.95.0 frozenlist-1.3.3 gpt-index-0.5.8 h11-0.14.0 hnswlib-0.7.0 httptools-0.5.0 huggingface-hub-0.13.4 langchain-0.0.132 lz4-4.3.2 marshmallow-3.19.0 marshmallow-enum-1.5.1 monotonic-1.6 multidict-6.0.4 mypy-extensions-1.0.0 openai-0.27.4 posthog-2.4.2 python-dotenv-1.0.0 requests-2.28.2 sentence-transformers-2.2.2 sentencepiece-0.1.97 starlette-0.26.1 tiktoken-0.3.3 tokenizers-0.13.3 transformers-4.27.4 typing-inspect-0.8.0 uvicorn-0.21.1 uvloop-0.17.0 watchfiles-0.19.0 websockets-11.0.1 yarl-1.8.2 zstandard-0.20.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import chromadb\n",
        "from gpt_index import GPTChromaIndex, SimpleDirectoryReader, GPTListIndex, GPTIndexMemory\n",
        "from langchain import OpenAI\n",
        "from langchain.agents import initialize_agent\n",
        "\n",
        "\n",
        "def construct_index(directory_path):\n",
        "  chroma_client = chromadb.Client()\n",
        "  chroma_collection = chroma_client.create_collection('test_data')\n",
        "  documents = SimpleDirectoryReader(directory_path).load_data()\n",
        "  index = GPTChromaIndex.from_documents(documents, chroma_collection = chroma_collection)\n",
        "  return index\n",
        "\n",
        "def ask_question(index):\n",
        "  memory = GPTIndexMemory(index = index, memory_key = 'chat_history', query_kwargs= {'response_mode': 'compact'})\n",
        "  llm = OpenAI(temperature = 0)\n",
        "  agent_chain = initialize_agent([], llm, agent = 'conversational-react-description', memory = memory)\n",
        "\n",
        "  while True:\n",
        "    user_input = input(\"Enter your question (type 'exit' to quit):\")\n",
        "    if user_input.lower() == 'exit':\n",
        "      break\n",
        "    response = agent_chain.run(input = user_input)\n",
        "    print(\"Answer:\" , response)"
      ],
      "metadata": {
        "id": "CyZqQxoHOBEv"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "from getpass import getpass\n",
        "os.environ['OPENAI_API_KEY'] = getpass()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oP_CFYrRO-78",
        "outputId": "344449af-9cbd-42b4-84a8-cdd5f4e7e9a6"
      },
      "execution_count": 8,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "··········\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "index = construct_index('/content/test_data')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hyYO-_nOOyx-",
        "outputId": "0efeb859-65f3-4770-b00a-2dcadf7bab95"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:chromadb:Using embedded DuckDB without persistence: data will be transient\n",
            "WARNING:chromadb.api.models.Collection:No embedding_function provided, using default embedding function: SentenceTransformerEmbeddingFunction\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ask_question(index)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RX7NTwLfO4zJ",
        "outputId": "d8506e9e-0efa-49f6-e8e6-6469b4924160"
      },
      "execution_count": 16,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Enter your question (type 'exit' to quit):what is the document about?\n",
            "Answer: The document is about the 2008 financial crisis, also known as the Global Financial Crisis. It discusses the underlying causes of the crisis, which can be traced back to the late 1990s, and the effects it had on the global economy. It also examines the government responses to the crisis, such as the Troubled Asset Relief Program (TARP), and the weaknesses in the global financial system that were exposed by the crisis.\n",
            "Enter your question (type 'exit' to quit):can you elaborate?\n",
            "Answer: Sure, I can elaborate. The 2008 financial crisis was caused by a combination of factors, including the deregulation of the financial sector, the proliferation of complex financial instruments, and the housing bubble in the United States. These factors created a situation where banks and other financial institutions were taking on too much risk, leading to a collapse in the global financial system. The crisis had a ripple effect, leading to a global recession and a sharp decline in stock markets around the world. In response, governments and central banks implemented a variety of measures, such as the Troubled Asset Relief Program (TARP) in the United States, to help stabilize the financial system. The crisis also highlighted weaknesses in the global financial system, such as the lack of oversight and regulation of financial institutions, and the need for better risk management practices.\n",
            "Enter your question (type 'exit' to quit):what are some personal lessons I can learn from this crisis?\n",
            "Answer: Some personal lessons you can learn from this crisis include: being aware of the risks associated with investing in the stock market and other financial instruments; having an emergency fund in place to help you weather any financial storms; being mindful of the global economy and how it can affect your personal finances; taking steps to diversify your investments and spread your risk; staying informed about the latest financial news and developments; and being prepared to make tough decisions in times of economic uncertainty.\n",
            "Enter your question (type 'exit' to quit):exit\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "Iwh-R6MNQrWP"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}