Search Query Qwen.ipynb

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      "execution_count": null,
      "metadata": {
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        },
        "id": "9nxCoQPaItg-",
        "outputId": "8aba8327-9760-45ed-b3c7-a1ac71319f91"
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      "outputs": [
        {
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          "name": "stdout",
          "text": [
            "\n",
            "    _|    _|  _|    _|    _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|_|_|_|    _|_|      _|_|_|  _|_|_|_|\n",
            "    _|    _|  _|    _|  _|        _|          _|    _|_|    _|  _|            _|        _|    _|  _|        _|\n",
            "    _|_|_|_|  _|    _|  _|  _|_|  _|  _|_|    _|    _|  _|  _|  _|  _|_|      _|_|_|    _|_|_|_|  _|        _|_|_|\n",
            "    _|    _|  _|    _|  _|    _|  _|    _|    _|    _|    _|_|  _|    _|      _|        _|    _|  _|        _|\n",
            "    _|    _|    _|_|      _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|        _|    _|    _|_|_|  _|_|_|_|\n",
            "\n",
            "    To login, `huggingface_hub` requires a token generated from https://huggingface.co/settings/tokens .\n",
            "Enter your token (input will not be visible): \n",
            "Add token as git credential? (Y/n) n\n",
            "Token is valid (permission: fineGrained).\n",
            "Your token has been saved to /root/.cache/huggingface/token\n",
            "Login successful\n"
          ]
        }
      ],
      "source": [
        "!huggingface-cli login"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install --upgrade transformers"
      ],
      "metadata": {
        "colab": {
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        },
        "id": "Ne-0OSaRI0GX",
        "outputId": "e788664f-6bf9-4450-d443-84434dd08093"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.44.2)\n",
            "Collecting transformers\n",
            "  Downloading transformers-4.45.2-py3-none-any.whl.metadata (44 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m44.4/44.4 kB\u001b[0m \u001b[31m2.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.16.1)\n",
            "Requirement already satisfied: huggingface-hub<1.0,>=0.23.2 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.24.7)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.26.4)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (24.1)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.2)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2024.9.11)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.32.3)\n",
            "Requirement already satisfied: safetensors>=0.4.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.4.5)\n",
            "Collecting tokenizers<0.21,>=0.20 (from transformers)\n",
            "  Downloading tokenizers-0.20.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (6.7 kB)\n",
            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.66.5)\n",
            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.23.2->transformers) (2024.6.1)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.23.2->transformers) (4.12.2)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.4.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.10)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.2.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2024.8.30)\n",
            "Downloading transformers-4.45.2-py3-none-any.whl (9.9 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m9.9/9.9 MB\u001b[0m \u001b[31m90.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading tokenizers-0.20.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.0 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.0/3.0 MB\u001b[0m \u001b[31m99.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: tokenizers, transformers\n",
            "  Attempting uninstall: tokenizers\n",
            "    Found existing installation: tokenizers 0.19.1\n",
            "    Uninstalling tokenizers-0.19.1:\n",
            "      Successfully uninstalled tokenizers-0.19.1\n",
            "  Attempting uninstall: transformers\n",
            "    Found existing installation: transformers 4.44.2\n",
            "    Uninstalling transformers-4.44.2:\n",
            "      Successfully uninstalled transformers-4.44.2\n",
            "Successfully installed tokenizers-0.20.1 transformers-4.45.2\n"
          ]
        }
      ]
    },
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        "# Load model directly\n",
        "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
        "\n",
        "tokenizer_qwen2 = AutoTokenizer.from_pretrained(\"Qwen/Qwen2.5-1.5B-Instruct\")\n",
        "model2 = AutoModelForCausalLM.from_pretrained(\"Qwen/Qwen2.5-1.5B-Instruct\", device_map = 0)"
      ],
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            "cb8529d946274fc89b75990160c2522d"
          ]
        },
        "id": "ex6FXJXUI2y9",
        "outputId": "606654dd-828f-443a-bc2c-acb015f387fa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: 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",
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              "version_major": 2,
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              "model_id": "87431c8d4b904e98a014d025aa62de37"
            }
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          "metadata": {}
        },
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              "version_major": 2,
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            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def main_query_answering(query, max_tokens=100):\n",
        "    \"\"\"\n",
        "    Answer the main query using Meta-Llama-3.2-3B and the retrieved documents.\n",
        "    \"\"\"\n",
        "    # Prepare the prompt using the main query and the relevant shortened documents\n",
        "    # Assuming 'body' key holds the document text in retrieved_documents\n",
        "    prompt = f\"You are an engine used to generate web search queries. Omit information you dont need, depending on what the user wants. Generate and return the correct search query. {query} \\n. The web search query is (in 5 words or less):\"\n",
        "\n",
        "    # Tokenize input for LLM\n",
        "    inputs = tokenizer_qwen2(prompt, return_tensors=\"pt\").to(\"cuda\")\n",
        "\n",
        "    # Generate answer for the main query with reduced token output\n",
        "    outputs = model2.generate(**inputs, max_new_tokens=max_tokens, temperature=0.5)\n",
        "\n",
        "    # Decode and extract answer\n",
        "    answer = tokenizer_qwen2.decode(outputs[0], skip_special_tokens=True).strip()\n",
        "\n",
        "    return answer"
      ],
      "metadata": {
        "id": "iOVGACIYI39f"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Using the open source duckduckgo API to search and return results."
      ],
      "metadata": {
        "id": "E7Q23Nn4c4Fw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install duckduckgo_search"
      ],
      "metadata": {
        "id": "7LD1HAp4I5Ny",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1dafc76d-1dde-45a0-e090-7563e5b39d11"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting duckduckgo_search\n",
            "  Downloading duckduckgo_search-6.3.0-py3-none-any.whl.metadata (25 kB)\n",
            "Requirement already satisfied: click>=8.1.7 in /usr/local/lib/python3.10/dist-packages (from duckduckgo_search) (8.1.7)\n",
            "Collecting primp>=0.6.3 (from duckduckgo_search)\n",
            "  Downloading primp-0.6.3-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (10 kB)\n",
            "Downloading duckduckgo_search-6.3.0-py3-none-any.whl (27 kB)\n",
            "Downloading primp-0.6.3-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.8/2.8 MB\u001b[0m \u001b[31m34.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: primp, duckduckgo_search\n",
            "Successfully installed duckduckgo_search-6.3.0 primp-0.6.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from duckduckgo_search import DDGS\n"
      ],
      "metadata": {
        "id": "OFOLHLN4cxnC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def websearch(query, desc):\n",
        "    response = main_query_answering(f\"The user wants: {query}. The given information is: {desc}.\")\n",
        "    search_query = response.split('\"')[1]\n",
        "\n",
        "\n",
        "    # results_text = DDGS().text(search_query, max_results=5)\n",
        "\n",
        "    # results_img = DDGS().images(search_query, max_results=5)\n",
        "\n",
        "    return search_query"
      ],
      "metadata": {
        "id": "Np4oq_tOspev"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install fastapi uvicorn\n",
        "!pip install fastapi uvicorn nest_asyncio pyngrok\n",
        "!npm install -g localtunnel"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BXaPMjxgxFYO",
        "outputId": "aa3628bf-3975-43c8-8306-84d86e04c493"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting fastapi\n",
            "  Downloading fastapi-0.115.2-py3-none-any.whl.metadata (27 kB)\n",
            "Collecting uvicorn\n",
            "  Downloading uvicorn-0.31.1-py3-none-any.whl.metadata (6.6 kB)\n",
            "Collecting starlette<0.41.0,>=0.37.2 (from fastapi)\n",
            "  Downloading starlette-0.39.2-py3-none-any.whl.metadata (6.0 kB)\n",
            "Requirement already satisfied: pydantic!=1.8,!=1.8.1,!=2.0.0,!=2.0.1,!=2.1.0,<3.0.0,>=1.7.4 in /usr/local/lib/python3.10/dist-packages (from fastapi) (2.9.2)\n",
            "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from fastapi) (4.12.2)\n",
            "Requirement already satisfied: click>=7.0 in /usr/local/lib/python3.10/dist-packages (from uvicorn) (8.1.7)\n",
            "Collecting h11>=0.8 (from uvicorn)\n",
            "  Downloading h11-0.14.0-py3-none-any.whl.metadata (8.2 kB)\n",
            "Requirement already satisfied: annotated-types>=0.6.0 in /usr/local/lib/python3.10/dist-packages (from pydantic!=1.8,!=1.8.1,!=2.0.0,!=2.0.1,!=2.1.0,<3.0.0,>=1.7.4->fastapi) (0.7.0)\n",
            "Requirement already satisfied: pydantic-core==2.23.4 in /usr/local/lib/python3.10/dist-packages (from pydantic!=1.8,!=1.8.1,!=2.0.0,!=2.0.1,!=2.1.0,<3.0.0,>=1.7.4->fastapi) (2.23.4)\n",
            "Requirement already satisfied: anyio<5,>=3.4.0 in /usr/local/lib/python3.10/dist-packages (from starlette<0.41.0,>=0.37.2->fastapi) (3.7.1)\n",
            "Requirement already satisfied: idna>=2.8 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<0.41.0,>=0.37.2->fastapi) (3.10)\n",
            "Requirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<0.41.0,>=0.37.2->fastapi) (1.3.1)\n",
            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<0.41.0,>=0.37.2->fastapi) (1.2.2)\n",
            "Downloading fastapi-0.115.2-py3-none-any.whl (94 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m94.7/94.7 kB\u001b[0m \u001b[31m7.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading uvicorn-0.31.1-py3-none-any.whl (63 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m63.7/63.7 kB\u001b[0m \u001b[31m6.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading h11-0.14.0-py3-none-any.whl (58 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m6.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading starlette-0.39.2-py3-none-any.whl (73 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m73.2/73.2 kB\u001b[0m \u001b[31m7.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: h11, uvicorn, starlette, fastapi\n",
            "Successfully installed fastapi-0.115.2 h11-0.14.0 starlette-0.39.2 uvicorn-0.31.1\n",
            "Requirement already satisfied: fastapi in /usr/local/lib/python3.10/dist-packages (0.115.2)\n",
            "Requirement already satisfied: uvicorn in /usr/local/lib/python3.10/dist-packages (0.31.1)\n",
            "Requirement already satisfied: nest_asyncio in /usr/local/lib/python3.10/dist-packages (1.6.0)\n",
            "Collecting pyngrok\n",
            "  Downloading pyngrok-7.2.0-py3-none-any.whl.metadata (7.4 kB)\n",
            "Requirement already satisfied: starlette<0.41.0,>=0.37.2 in /usr/local/lib/python3.10/dist-packages (from fastapi) (0.39.2)\n",
            "Requirement already satisfied: pydantic!=1.8,!=1.8.1,!=2.0.0,!=2.0.1,!=2.1.0,<3.0.0,>=1.7.4 in /usr/local/lib/python3.10/dist-packages (from fastapi) (2.9.2)\n",
            "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from fastapi) (4.12.2)\n",
            "Requirement already satisfied: click>=7.0 in /usr/local/lib/python3.10/dist-packages (from uvicorn) (8.1.7)\n",
            "Requirement already satisfied: h11>=0.8 in /usr/local/lib/python3.10/dist-packages (from uvicorn) (0.14.0)\n",
            "Requirement already satisfied: PyYAML>=5.1 in /usr/local/lib/python3.10/dist-packages (from pyngrok) (6.0.2)\n",
            "Requirement already satisfied: annotated-types>=0.6.0 in /usr/local/lib/python3.10/dist-packages (from pydantic!=1.8,!=1.8.1,!=2.0.0,!=2.0.1,!=2.1.0,<3.0.0,>=1.7.4->fastapi) (0.7.0)\n",
            "Requirement already satisfied: pydantic-core==2.23.4 in /usr/local/lib/python3.10/dist-packages (from pydantic!=1.8,!=1.8.1,!=2.0.0,!=2.0.1,!=2.1.0,<3.0.0,>=1.7.4->fastapi) (2.23.4)\n",
            "Requirement already satisfied: anyio<5,>=3.4.0 in /usr/local/lib/python3.10/dist-packages (from starlette<0.41.0,>=0.37.2->fastapi) (3.7.1)\n",
            "Requirement already satisfied: idna>=2.8 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<0.41.0,>=0.37.2->fastapi) (3.10)\n",
            "Requirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<0.41.0,>=0.37.2->fastapi) (1.3.1)\n",
            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.4.0->starlette<0.41.0,>=0.37.2->fastapi) (1.2.2)\n",
            "Downloading pyngrok-7.2.0-py3-none-any.whl (22 kB)\n",
            "Installing collected packages: pyngrok\n",
            "Successfully installed pyngrok-7.2.0\n",
            "\u001b[K\u001b[?25h\n",
            "added 22 packages, and audited 23 packages in 2s\n",
            "\n",
            "3 packages are looking for funding\n",
            "  run `npm fund` for details\n",
            "\n",
            "1 \u001b[33m\u001b[1mmoderate\u001b[22m\u001b[39m severity vulnerability\n",
            "\n",
            "To address all issues (including breaking changes), run:\n",
            "  npm audit fix --force\n",
            "\n",
            "Run `npm audit` for details.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "from pyngrok import ngrok\n",
        "\n",
        "# Set the Ngrok authentication token\n",
        "ngrok.set_auth_token(\"2nRYGlbanqTVP1JoOsPlk8MKAWj_7hc88mo63ZNm1gCEosmh9\")\n",
        "\n",
        "# Open a tunnel to the FastAPI app running on port 8000\n",
        "public_url = ngrok.connect(8000)\n",
        "\n",
        "print(f\"FastAPI is publicly available at: {public_url}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oIXVGZ53sZtE",
        "outputId": "67888f50-7af3-4c7b-9dae-06f9ca88d7d9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "FastAPI is publicly available at: NgrokTunnel: \"https://e450-34-125-122-228.ngrok-free.app\" -> \"http://localhost:8000\"\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import nest_asyncio\n",
        "import uvicorn\n",
        "from fastapi import FastAPI\n",
        "from pydantic import BaseModel\n",
        "\n",
        "# Apply nest_asyncio to allow running uvicorn inside the notebook\n",
        "nest_asyncio.apply()\n",
        "\n",
        "# Define the FastAPI app\n",
        "app = FastAPI()\n",
        "\n",
        "# Define a Pydantic model for the input query\n",
        "class QueryRequest(BaseModel):\n",
        "    query: str\n",
        "\n",
        "@app.post(\"/web_search\")\n",
        "async def web_search_endpoint(request: QueryRequest):\n",
        "    query = request.query\n",
        "    desc, final_query = query.split('||')\n",
        "    final_answer = websearch(final_query, desc)  # Assuming rag_pipeline function is defined elsewhere\n",
        "    return {\"final_answer\": final_answer}\n",
        "\n",
        "# Run the FastAPI app\n",
        "uvicorn.run(app, host=\"0.0.0.0\", port=8000)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AEEF1Ptbsdjh",
        "outputId": "60cf644e-339b-410b-80de-d398bfcab034"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:     Started server process [1735]\n",
            "INFO:     Waiting for application startup.\n",
            "INFO:     Application startup complete.\n",
            "INFO:     Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "INFO:     2401:4900:5f30:64ed:4082:8723:6974:59da:0 - \"POST /web_search HTTP/1.1\" 200 OK\n",
            "INFO:     2401:4900:5f30:64ed:4082:8723:6974:59da:0 - \"POST /web_search HTTP/1.1\" 200 OK\n",
            "INFO:     2401:4900:5f30:64ed:4082:8723:6974:59da:0 - \"POST /web_search HTTP/1.1\" 200 OK\n",
            "INFO:     2401:4900:5f30:64ed:4082:8723:6974:59da:0 - \"POST /web_search HTTP/1.1\" 200 OK\n"
          ]
        }
      ]
    }
  ]
}