Langchain_+_MongoDB_+_localEmbed_101.ipynb

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            "_model_name": "ProgressStyleModel",
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            "_view_module_version": "1.2.0",
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            "_view_module_version": "1.2.0",
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  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/prakul/MongoDB-AI-Resources/blob/main/Langchain_%2B_MongoDB_%2B_localEmbed_101.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Install prerequisites dependencies\n"
      ],
      "metadata": {
        "id": "3CaG54pnNhqM"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install langchain pypdf pymongo openai python-dotenv"
      ],
      "metadata": {
        "id": "HwQZnho4m5IY",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "dd0e8dd4-432d-41ef-f5fd-c2127211b14e"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: langchain in /usr/local/lib/python3.10/dist-packages (0.1.11)\n",
            "Requirement already satisfied: pypdf in /usr/local/lib/python3.10/dist-packages (4.1.0)\n",
            "Requirement already satisfied: pymongo in /usr/local/lib/python3.10/dist-packages (4.6.2)\n",
            "Requirement already satisfied: openai in /usr/local/lib/python3.10/dist-packages (1.13.3)\n",
            "Requirement already satisfied: python-dotenv in /usr/local/lib/python3.10/dist-packages (1.0.1)\n",
            "Requirement already satisfied: PyYAML>=5.3 in /usr/local/lib/python3.10/dist-packages (from langchain) (6.0.1)\n",
            "Requirement already satisfied: SQLAlchemy<3,>=1.4 in /usr/local/lib/python3.10/dist-packages (from langchain) (2.0.27)\n",
            "Requirement already satisfied: aiohttp<4.0.0,>=3.8.3 in /usr/local/lib/python3.10/dist-packages (from langchain) (3.9.3)\n",
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            "Requirement already satisfied: langchain-community<0.1,>=0.0.25 in /usr/local/lib/python3.10/dist-packages (from langchain) (0.0.25)\n",
            "Requirement already satisfied: langchain-core<0.2,>=0.1.29 in /usr/local/lib/python3.10/dist-packages (from langchain) (0.1.29)\n",
            "Requirement already satisfied: langchain-text-splitters<0.1,>=0.0.1 in /usr/local/lib/python3.10/dist-packages (from langchain) (0.0.1)\n",
            "Requirement already satisfied: langsmith<0.2.0,>=0.1.17 in /usr/local/lib/python3.10/dist-packages (from langchain) (0.1.21)\n",
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            "Requirement already satisfied: requests<3,>=2 in /usr/local/lib/python3.10/dist-packages (from langchain) (2.31.0)\n",
            "Requirement already satisfied: tenacity<9.0.0,>=8.1.0 in /usr/local/lib/python3.10/dist-packages (from langchain) (8.2.3)\n",
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            "Requirement already satisfied: typing-inspect<1,>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from dataclasses-json<0.7,>=0.5.7->langchain) (0.9.0)\n",
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            "Requirement already satisfied: httpcore==1.* in /usr/local/lib/python3.10/dist-packages (from httpx<1,>=0.23.0->openai) (1.0.4)\n",
            "Requirement already satisfied: h11<0.15,>=0.13 in /usr/local/lib/python3.10/dist-packages (from httpcore==1.*->httpx<1,>=0.23.0->openai) (0.14.0)\n",
            "Requirement already satisfied: jsonpointer>=1.9 in /usr/local/lib/python3.10/dist-packages (from jsonpatch<2.0,>=1.33->langchain) (2.4)\n",
            "Requirement already satisfied: packaging<24.0,>=23.2 in /usr/local/lib/python3.10/dist-packages (from langchain-core<0.2,>=0.1.29->langchain) (23.2)\n",
            "Requirement already satisfied: orjson<4.0.0,>=3.9.14 in /usr/local/lib/python3.10/dist-packages (from langsmith<0.2.0,>=0.1.17->langchain) (3.9.15)\n",
            "Requirement already satisfied: annotated-types>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1->langchain) (0.6.0)\n",
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            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain) (3.3.2)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain) (2.0.7)\n",
            "Requirement already satisfied: greenlet!=0.4.17 in /usr/local/lib/python3.10/dist-packages (from SQLAlchemy<3,>=1.4->langchain) (3.0.3)\n",
            "Requirement already satisfied: mypy-extensions>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from typing-inspect<1,>=0.4.0->dataclasses-json<0.7,>=0.5.7->langchain) (1.0.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install sentence-transformers"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZsT9bWykbKhQ",
        "outputId": "5b5632a6-2dfe-4cad-988e-88de191baf03"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting sentence-transformers\n",
            "  Downloading sentence_transformers-2.5.1-py3-none-any.whl (156 kB)\n",
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/156.5 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m \u001b[32m153.6/156.5 kB\u001b[0m \u001b[31m4.5 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m156.5/156.5 kB\u001b[0m \u001b[31m3.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: transformers<5.0.0,>=4.32.0 in /usr/local/lib/python3.10/dist-packages (from sentence-transformers) (4.38.1)\n",
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            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.15.1->sentence-transformers) (2024.2.2)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.11.0->sentence-transformers) (1.3.0)\n",
            "Installing collected packages: sentence-transformers\n",
            "Successfully installed sentence-transformers-2.5.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Setup the environment"
      ],
      "metadata": {
        "id": "H0zbGavtNpMJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "from dotenv import load_dotenv\n",
        "from pymongo import MongoClient\n",
        "\n",
        "load_dotenv(override=True)\n",
        "\n",
        "# Add an environment file to the notebook root directory called .env with MONGO_URI=\"xxx\" to load these envvars\n",
        "\n",
        "OPENAI_API_KEY = os.environ[\"OPENAI_API_KEY\"]\n",
        "MONGO_URI = os.environ[\"MONGO_URI\"]\n",
        "DB_NAME = \"langchain-test-3\"\n",
        "COLLECTION_NAME = \"test2\"\n",
        "ATLAS_VECTOR_SEARCH_INDEX_NAME = \"vector_search\"\n",
        "\n",
        "client = MongoClient(MONGO_URI)\n",
        "db = client[DB_NAME]\n",
        "MONGODB_COLLECTION = db[COLLECTION_NAME]"
      ],
      "metadata": {
        "id": "JWl8u9gdyBGR"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#DATA PREPARATION\n",
        "\n",
        " Create an Atlas search index via Atlas UI -> Search -> Vector Search JSON Editor with the following definition\n",
        " ```\n",
        " {\n",
        "   \"fields\":[\n",
        "      {\n",
        "         \"type\": \"vector\",\n",
        "         \"path\": \"embedding\",\n",
        "         \"numDimensions\": 1536,\n",
        "         \"similarity\": \"cosine\"\n",
        "      },\n",
        "      {\n",
        "         \"type\": \"filter\",\n",
        "         \"path\": \"page\"\n",
        "      }\n",
        "   ]\n",
        "}\n",
        "\n",
        "```"
      ],
      "metadata": {
        "id": "F7v5H-48MW18"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain.document_loaders import PyPDFLoader\n",
        "\n",
        "loader = PyPDFLoader(\"https://arxiv.org/pdf/2303.08774.pdf\")\n",
        "data = loader.load()"
      ],
      "metadata": {
        "id": "bLosUpvDmDOW"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
        "\n",
        "text_splitter = RecursiveCharacterTextSplitter(chunk_size = 500, chunk_overlap = 0)\n",
        "docs = text_splitter.split_documents(data)"
      ],
      "metadata": {
        "id": "Zot6nbm1QLUj"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "r-hmrZ-EYdw4"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain_community.embeddings import HuggingFaceEmbeddings\n",
        "\n",
        "embeddings = HuggingFaceEmbeddings(model_name=\"thenlper/gte-large\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 464,
          "referenced_widgets": [
            "0619c80b64df4bb9a74fc993659958a4",
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            "df01bb81e978469aa6fd9e6765fc4713",
            "2e95662aa8c1496f84cec9c9721d90c4",
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            "81d80103a8b64234b7c29fd1fe1a63dd",
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        },
        "id": "rfIXiACzYxcW",
        "outputId": "99c67d8e-5501-49c2-e7c7-75d1e114def5"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "modules.json:   0%|          | 0.00/385 [00:00<?, ?B/s]"
            ],
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "README.md:   0%|          | 0.00/67.9k [00:00<?, ?B/s]"
            ],
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "sentence_bert_config.json:   0%|          | 0.00/57.0 [00:00<?, ?B/s]"
            ],
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
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          "metadata": {}
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        {
          "output_type": "display_data",
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          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "1887721c7b1f40d6917ede161c806d2e"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain.embeddings import OpenAIEmbeddings\n",
        "from langchain.vectorstores import MongoDBAtlasVectorSearch\n",
        "\n",
        "# insert the documents in MongoDB Atlas Vector Search\n",
        "x = MongoDBAtlasVectorSearch.from_documents(\n",
        "     documents=docs, embedding=embeddings, collection=MONGODB_COLLECTION, index_name=ATLAS_VECTOR_SEARCH_INDEX_NAME\n",
        " )\n"
      ],
      "metadata": {
        "id": "NUrRHjYumSh_"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#DATA QUERY"
      ],
      "metadata": {
        "id": "I0yiKlx9MRXi"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# initialize a connection to MongoDB Vector Search if not done in previous Steps\n",
        "\n",
        "from langchain.vectorstores import MongoDBAtlasVectorSearch\n",
        "\n",
        "vector_search = MongoDBAtlasVectorSearch.from_connection_string(\n",
        "    MONGO_URI,\n",
        "    DB_NAME + \".\" + COLLECTION_NAME,\n",
        "    embeddings,\n",
        "    index_name=ATLAS_VECTOR_SEARCH_INDEX_NAME\n",
        ")\n"
      ],
      "metadata": {
        "id": "TZp7_CBfxTOB"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## SEMANTIC SEARCH"
      ],
      "metadata": {
        "id": "rJ6O9OL65HnF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "question = \"How much better is GPT-4 in reducing hallucinations over GPT-3.5\"\n",
        "\n",
        "results = vector_search.similarity_search(question)\n"
      ],
      "metadata": {
        "id": "cIt7Qnh5GvrS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## RAG (WIP)"
      ],
      "metadata": {
        "id": "pjfXnCnm5FWb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain_community.llms import HuggingFaceHub\n",
        "\n",
        "llm = HuggingFaceHub(\n",
        "    repo_id=\"HuggingFaceH4/zephyr-7b-beta\",\n",
        "    task=\"text-generation\",\n",
        "    model_kwargs={\n",
        "        \"max_new_tokens\": 512,\n",
        "        \"top_k\": 30,\n",
        "        \"temperature\": 0.1,\n",
        "        \"repetition_penalty\": 1.03,\n",
        "    },\n",
        ")\n",
        "\n"
      ],
      "metadata": {
        "id": "4HH_BCsBZZtx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain.chains import RetrievalQA\n",
        "from langchain.chat_models import ChatOpenAI\n",
        "llm = ChatOpenAI(model_name=\"gpt-3.5-turbo\", temperature=0)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IHZQfWaXmV3N",
        "outputId": "8c28a53c-c1e7-42e3-e912-b17030d0cf6c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'query': 'How much better is GPT-4 in reducing hallucinations over GPT-3.5',\n",
              " 'result': \"I'm sorry, but I don't have access to information about the specific capabilities or improvements of GPT-4 over GPT-3.5. My knowledge is based on GPT-3, and I don't have real-time updates on subsequent versions.\"}"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "question = \"How much better is GPT-4 in reducing hallucinations over GPT-3.5\"\n"
      ],
      "metadata": {
        "id": "Dg7dL2drZdP4"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "qa_chain = RetrievalQA.from_chain_type(llm, retriever=vector_search.as_retriever())\n",
        "qa_chain({\"query\": question})\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BZLYniCQmYhi",
        "outputId": "af7518bd-222e-4cde-eaef-db29310f6969"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'query': 'How much better is GPT-4 in reducing hallucinations over GPT-3.5',\n",
              " 'result': 'GPT-4 scores 19 percentage points higher than GPT-3.5 in reducing hallucinations.'}"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    }
  ]
}