RAG_Pipeline.ipynb

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      "cell_type": "markdown",
      "source": [
        "## Knowledge Base Q&A:\n",
        "\n",
        "Provide direct, dynamic answers from databases, making data access swift and user-friendly."
      ],
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    },
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      "source": [
        "## GenAI Stack Workflow for Knowledge Base Question & Answer"
      ],
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      }
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      ],
      "metadata": {
        "id": "CqWw1dqBO7WA"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Installing GenAI Stack version 2"
      ],
      "metadata": {
        "id": "c1hycpJVHos6"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TmF3lrdfLjZq",
        "outputId": "11236069-00da-4e83-d8eb-c22c0ea5bbf1"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting git+https://github.com/aiplanethub/genai-stack.git@0.2.0\n",
            "  Cloning https://github.com/aiplanethub/genai-stack.git (to revision 0.2.0) to /tmp/pip-req-build-hsmd3mo9\n",
            "  Running command git clone --filter=blob:none --quiet https://github.com/aiplanethub/genai-stack.git /tmp/pip-req-build-hsmd3mo9\n",
            "  Running command git checkout -b 0.2.0 --track origin/0.2.0\n",
            "  Switched to a new branch '0.2.0'\n",
            "  Branch '0.2.0' set up to track remote branch '0.2.0' from 'origin'.\n",
            "  Resolved https://github.com/aiplanethub/genai-stack.git to commit 4960a901d9326df683cad87a7c41843273e396c9\n",
            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
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          ]
        }
      ],
      "source": [
        "!pip install git+https://github.com/aiplanethub/genai-stack.git@0.2.0"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Componets used for implementation\n",
        "\n",
        "* **gpt-3.5-turbo** as LLM\n",
        "* **Chromadb** as Vectorstore\n",
        "* **sentence-transformers/all-mpnet-base-v2** sentence transformer for text embeddings\n",
        "* **Langchain** Framework"
      ],
      "metadata": {
        "id": "uFkGYlgRRXBd"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Import Required GenAI Stack Components"
      ],
      "metadata": {
        "id": "DdnrxAO4HScY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from genai_stack.stack.stack import Stack\n",
        "from genai_stack.etl.langchain import LangchainETL\n",
        "from genai_stack.embedding.langchain import LangchainEmbedding\n",
        "from genai_stack.vectordb.chromadb import ChromaDB\n",
        "from genai_stack.prompt_engine.engine import PromptEngine\n",
        "from genai_stack.model.gpt3_5 import OpenAIGpt35Model\n",
        "from genai_stack.retriever import LangChainRetriever\n",
        "from genai_stack.memory.langchain import ConversationBufferMemory"
      ],
      "metadata": {
        "id": "DAEFKXHoF5wh"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Instantiate ETL component by providing configuration according to source data type.\n",
        "\n",
        "* Here the input source is .pdf file\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "fSTVjT6Zpo8D"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "etl = LangchainETL.from_kwargs(name=\"PyPDFLoader\", fields={\"file_path\": \"YOUR PDF DOCUMENT PATH\"})"
      ],
      "metadata": {
        "id": "XWE464Nep9Ar"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Instantiate the LLM"
      ],
      "metadata": {
        "id": "IDS9qukTpW6G"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "llm = OpenAIGpt35Model.from_kwargs(parameters={\"openai_api_key\": \"YOUR OPENAI API KEY\"})"
      ],
      "metadata": {
        "id": "5znp5Ci-pZDZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Instantiate Embedding component using open source Huggingface Model"
      ],
      "metadata": {
        "id": "dW_X-xFeqFIX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "config = {\n",
        "    \"model_name\": \"sentence-transformers/all-mpnet-base-v2\",\n",
        "    \"model_kwargs\": {\"device\": \"cpu\"},\n",
        "    \"encode_kwargs\": {\"normalize_embeddings\": False},\n",
        "}\n",
        "embedding = LangchainEmbedding.from_kwargs(name=\"HuggingFaceEmbeddings\", fields=config)"
      ],
      "metadata": {
        "id": "WS1GRYXoqLb4"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Instantiate the Vectorstore"
      ],
      "metadata": {
        "id": "hQSmg4w4qXGU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "chromadb = ChromaDB.from_kwargs()\n",
        "chromadb\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bE4sPVOoLplm",
        "outputId": "35a41626-4af6-48dc-a14a-7d37a8927b1b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<genai_stack.vectordb.chromadb.chromadb.ChromaDB at 0x7b5e9ddc7700>"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Instantiate the Retriver"
      ],
      "metadata": {
        "id": "ckyZd6cHqlJL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "retriever = LangChainRetriever.from_kwargs()"
      ],
      "metadata": {
        "id": "Z_QfrkJlO_W7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Instantiate the Promptengine\n",
        "\n",
        "* prompt engine constructs the prompt template  for instructing the LLM"
      ],
      "metadata": {
        "id": "6eGU8It-rgCW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "promptengine = PromptEngine.from_kwargs(should_validate=False)"
      ],
      "metadata": {
        "id": "O7P_qsmFry_H"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Instantiate Memory"
      ],
      "metadata": {
        "id": "O1ZbaAeNs1_S"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "memory = ConversationBufferMemory.from_kwargs()"
      ],
      "metadata": {
        "id": "rBQjWE3ws4oD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Setup the GenAI Stack"
      ],
      "metadata": {
        "id": "i1LXqz6RtBf3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "stack = Stack(\n",
        "    etl=etl,\n",
        "    embedding=embedding,\n",
        "    vectordb=chromadb,\n",
        "    model=llm,\n",
        "    prompt_engine=promptengine,\n",
        "    retriever=retriever,\n",
        "    memory=memory\n",
        ")"
      ],
      "metadata": {
        "id": "H0UpnsUNPbG7",
        "colab": {
          "base_uri": "https://localhost:8080/",
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        },
        "outputId": "7cb43a86-822d-4bbd-de31-f862437f93d6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
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      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Performing the ETL operations\n",
        "1. extracting the content\n",
        "2. transforrmation(creating embeddings),\n",
        "3. load(storing the knowledge base in  the vectordb)"
      ],
      "metadata": {
        "id": "OJ4ZJMG1uEgi"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "etl.run()"
      ],
      "metadata": {
        "id": "6mQe6U08Psn1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Ask a question"
      ],
      "metadata": {
        "id": "1pzs7iq7y5Wu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "question = input(\"Ask a question: \")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kjgFOiWN2NTV",
        "outputId": "4787f295-0e6d-4204-8ecd-833296ee3fdd"
      },
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Ask a question: What has been mentioned about Mental health literacy?\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Response formulated by the GenAI stack"
      ],
      "metadata": {
        "id": "UiWN1Di73A3M"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "response = retriever.retrieve(question)\n",
        "print(response['output'])"
      ],
      "metadata": {
        "id": "d470nLozP0Sn",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8cbb144a-8903-4741-a15e-7f2ca3f9da72"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "In the context, it is mentioned that there is conceptual confusion regarding mental health literacy among adults and children in the general population. The focus group participants did not find the single continuum model suggested by the WHO helpful. There is also confusion among young people regarding the terms \"mental health,\" \"mental illness,\" and \"learning disability.\" Additionally, it is stated that less than a fifth of young people who need mental health care actually receive any services, and of those who do receive services, less than half obtain services appropriate to their need.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Helper Function to generate response"
      ],
      "metadata": {
        "id": "gNxONF2_3r_C"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "process = \"y\"\n",
        "while process == 'y':\n",
        "  question = input(\"Ask a question: \")\n",
        "  print(f\"Question : {question}\")\n",
        "  response = retriever.retrieve(question)\n",
        "  print(f\"Response : {response}\")\n",
        "  print(\"\\n\\n\")\n",
        "  process =  input(\"Do you want to continue : y -to continue, n - to exit :\")\n",
        "  print(\"\\n\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "52Zm683H3vzt",
        "outputId": "51f4e110-651a-44ca-e142-eb4c2d769432"
      },
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Ask a question: What is the stigma related to mental illness ?\n",
            "Question : What is the stigma related to mental illness ?\n",
            "Response : {'output': 'The stigma related to mental illness refers to the negative attitudes, beliefs, and stereotypes that society holds towards individuals with mental health conditions. This stigma can lead to discrimination, social exclusion, and the devaluation of individuals with mental illness. It is often based on misconceptions and fear, and can result in individuals being labeled as dangerous, unpredictable, or responsible for their own condition. Stigma can have significant negative impacts on individuals with mental illness, including barriers to seeking help, reduced access to treatment, and decreased quality of life.'}\n",
            "\n",
            "\n",
            "\n",
            "Do you want to continue : y -to continue, n - to exit :y\n",
            "Ask a question: What has been mentioned about Mental health literacy?\n",
            "Question : What has been mentioned about Mental health literacy?\n",
            "Response : {'output': 'In the context, it is mentioned that there is conceptual confusion regarding mental health literacy among adults and children in the general population. The focus group participants did not find the single continuum model suggested by the WHO helpful. There is also confusion among young people regarding the terms \"mental health,\" \"mental illness,\" and \"learning disability.\" Additionally, it is stated that less than a fifth of young people who need mental health care actually receive any services, and of those who do receive services, less than half obtain services appropriate to their need.'}\n",
            "\n",
            "\n",
            "\n",
            "Do you want to continue : y -to continue, n - to exit :n\n"
          ]
        }
      ]
    }
  ]
}