2_2-ChromaDB Sever mode.ipynb

{
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      "id": "7e4c9601-fcb8-49e6-ae48-4de8b6cac494",
      "metadata": {
        "id": "7e4c9601-fcb8-49e6-ae48-4de8b6cac494"
      },
      "source": [
        "<div>\n",
        "    <h1 style=\"text-align: center;\">Large Language Models Projects</a></h1>\n",
        "    <h3>Apply and Implement Strategies for Large Language Models</h3>\n",
        "    <h2>2_2-ChromaDB Server mode</h2>\n",
        "    \n",
        "</div>\n",
        "\n",
        "by [Pere Martra](https://www.linkedin.com/in/pere-martra/)\n",
        "_________\n",
        "This notebook is set up to run in a local environment. If executed in Google Colab, access to the ChromaDB server that will be created won't be possible.\n",
        "\n",
        "The code is the same as the one used in notebook 2_1_Vector_Databases_LLMs.ipynb.\n",
        "The client has been implemented in the notebook 2_3-ChromaDB Client.\n",
        "__________"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "fbdcd16f-1aca-442b-8d84-3fafdba82dd2",
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        "outputId": "15a5c4e0-ba39-41f0-f9fc-7245b1f98919"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
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            "\u001b[?25hDownloading asgiref-3.7.2-py3-none-any.whl (24 kB)\n",
            "Building wheels for collected packages: pypika\n",
            "  Building wheel for pypika (pyproject.toml) ... \u001b[?25ldone\n",
            "\u001b[?25h  Created wheel for pypika: filename=PyPika-0.48.9-py2.py3-none-any.whl size=53723 sha256=bbd24c13ce8b13ed4b60b22b80d877db0d4e9ffb31cfd6f3824f960f475fb663\n",
            "  Stored in directory: /Users/pere/Library/Caches/pip/wheels/e1/26/51/d0bffb3d2fd82256676d7ad3003faea3bd6dddc9577af665f4\n",
            "Successfully built pypika\n",
            "Installing collected packages: pypika, monotonic, mmh3, websockets, uvloop, uvicorn, urllib3, typer, python-dotenv, pulsar-client, opentelemetry-util-http, opentelemetry-semantic-conventions, opentelemetry-proto, humanfriendly, httptools, grpcio, googleapis-common-protos, deprecated, chroma-hnswlib, bcrypt, backoff, asgiref, watchfiles, starlette, opentelemetry-exporter-otlp-proto-common, opentelemetry-api, coloredlogs, posthog, opentelemetry-sdk, opentelemetry-instrumentation, onnxruntime, fastapi, opentelemetry-instrumentation-asgi, opentelemetry-exporter-otlp-proto-grpc, kubernetes, opentelemetry-instrumentation-fastapi, chromadb\n",
            "  Attempting uninstall: urllib3\n",
            "    Found existing installation: urllib3 2.0.6\n",
            "    Uninstalling urllib3-2.0.6:\n",
            "      Successfully uninstalled urllib3-2.0.6\n",
            "  Attempting uninstall: grpcio\n",
            "    Found existing installation: grpcio 1.46.3\n",
            "    Uninstalling grpcio-1.46.3:\n",
            "      Successfully uninstalled grpcio-1.46.3\n",
            "Successfully installed asgiref-3.7.2 backoff-2.2.1 bcrypt-4.1.2 chroma-hnswlib-0.7.3 chromadb-0.4.20 coloredlogs-15.0.1 deprecated-1.2.14 fastapi-0.105.0 googleapis-common-protos-1.62.0 grpcio-1.60.0 httptools-0.6.1 humanfriendly-10.0 kubernetes-28.1.0 mmh3-4.0.1 monotonic-1.6 onnxruntime-1.16.3 opentelemetry-api-1.22.0 opentelemetry-exporter-otlp-proto-common-1.22.0 opentelemetry-exporter-otlp-proto-grpc-1.22.0 opentelemetry-instrumentation-0.43b0 opentelemetry-instrumentation-asgi-0.43b0 opentelemetry-instrumentation-fastapi-0.43b0 opentelemetry-proto-1.22.0 opentelemetry-sdk-1.22.0 opentelemetry-semantic-conventions-0.43b0 opentelemetry-util-http-0.43b0 posthog-3.1.0 pulsar-client-3.3.0 pypika-0.48.9 python-dotenv-1.0.0 starlette-0.27.0 typer-0.9.0 urllib3-1.26.18 uvicorn-0.25.0 uvloop-0.19.0 watchfiles-0.21.0 websockets-12.0\n"
          ]
        }
      ],
      "source": [
        "!pip install -q chromadb==0.4.20"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "d6c765af-dc87-41e3-891d-a6e934a53259",
      "metadata": {
        "id": "d6c765af-dc87-41e3-891d-a6e934a53259"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "8be6c63a-5077-4550-98f7-6e3e118872a5",
      "metadata": {
        "id": "8be6c63a-5077-4550-98f7-6e3e118872a5"
      },
      "outputs": [],
      "source": [
        "#download and unzip  the dataset from kaggle:\n",
        "#https://www.kaggle.com/datasets/kotartemiy/topic-labeled-news-dataset\n",
        "\n",
        "#Pass the directory where the .csv file is stored to read_csv\n",
        "news = pd.read_csv('./kaggle/labelled_newscatcher_dataset.csv', sep=';')\n",
        "MAX_NEWS = 1000\n",
        "DOCUMENT=\"title\"\n",
        "TOPIC=\"topic\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "6a2fd5a3-29a4-4d5b-9527-fd431671ed93",
      "metadata": {
        "id": "6a2fd5a3-29a4-4d5b-9527-fd431671ed93"
      },
      "outputs": [],
      "source": [
        "#Because it is just a example we select a small portion of News.\n",
        "subset_news = news.head(MAX_NEWS)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "5e7fc76a-c828-4db4-bada-b1e14c2eefea",
      "metadata": {
        "id": "5e7fc76a-c828-4db4-bada-b1e14c2eefea"
      },
      "outputs": [],
      "source": [
        "import chromadb"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "04b25934-62bd-4720-871a-7e516807c3e7",
      "metadata": {
        "id": "04b25934-62bd-4720-871a-7e516807c3e7"
      },
      "outputs": [],
      "source": [
        "chroma_client = chromadb.PersistentClient(path=\"./chromadb\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "06549d87-b66f-44b7-a1dc-b6c122685602",
      "metadata": {
        "id": "06549d87-b66f-44b7-a1dc-b6c122685602"
      },
      "outputs": [],
      "source": [
        "collection_name = \"local_news_collection\"\n",
        "if len(chroma_client.list_collections()) > 0 and collection_name in [chroma_client.list_collections()[0].name]:\n",
        "        chroma_client.delete_collection(name=collection_name)\n",
        "\n",
        "collection = chroma_client.create_collection(name=collection_name)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "f8b6d5c4-0f6c-4bfd-9bab-6f0df0fa2469",
      "metadata": {
        "id": "f8b6d5c4-0f6c-4bfd-9bab-6f0df0fa2469",
        "outputId": "a281dc8b-4d31-4ecf-a50a-95cec127d7d6"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/Users/pere/.cache/chroma/onnx_models/all-MiniLM-L6-v2/onnx.tar.gz: 100%|█| 79.3\n"
          ]
        }
      ],
      "source": [
        "collection.add(\n",
        "    documents=subset_news[DOCUMENT].tolist(),\n",
        "    metadatas=[{TOPIC: topic} for topic in subset_news[TOPIC].tolist()],\n",
        "    ids=[f\"id{x}\" for x in range(MAX_NEWS)],\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "9c9211e7-bd14-4cd0-b617-6b520de23e1b",
      "metadata": {
        "id": "9c9211e7-bd14-4cd0-b617-6b520de23e1b",
        "outputId": "2358d16f-6269-4aa9-de1a-5f6f4c15134d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "{'ids': [['id173', 'id829', 'id117', 'id535', 'id141', 'id218', 'id390', 'id273', 'id56', 'id900']], 'distances': [[0.8593592047691345, 1.0294400453567505, 1.0793328285217285, 1.093001365661621, 1.1329681873321533, 1.2130439281463623, 1.2143322229385376, 1.2164145708084106, 1.222063660621643, 1.275417447090149]], 'metadatas': [[{'topic': 'TECHNOLOGY'}, {'topic': 'TECHNOLOGY'}, {'topic': 'TECHNOLOGY'}, {'topic': 'TECHNOLOGY'}, {'topic': 'TECHNOLOGY'}, {'topic': 'TECHNOLOGY'}, {'topic': 'TECHNOLOGY'}, {'topic': 'TECHNOLOGY'}, {'topic': 'TECHNOLOGY'}, {'topic': 'TECHNOLOGY'}]], 'embeddings': None, 'documents': [['The Legendary Toshiba is Officially Done With Making Laptops', '3 gaming laptop deals you can’t afford to miss today', 'Lenovo and HP control half of the global laptop market', 'Asus ROG Zephyrus G14 gaming laptop announced in India', 'Acer Swift 3 featuring a 10th-generation Intel Ice Lake CPU, 2K screen, and more launched in India for INR 64999 (US$865)', \"Apple's Next MacBook Could Be the Cheapest in Company's History\", \"Features of Huawei's Desktop Computer Revealed\", 'Redmi to launch its first gaming laptop on August 14: Here are all the details', 'Toshiba shuts the lid on laptops after 35 years', 'This is the cheapest Windows PC by a mile and it even has a spare SSD slot']], 'uris': None, 'data': None}\n"
          ]
        }
      ],
      "source": [
        "results = collection.query(query_texts=[\"laptop\"], n_results=10 )\n",
        "\n",
        "print(results)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "65a107f7-efbb-4a4a-8fe4-4137f00d925f",
      "metadata": {
        "id": "65a107f7-efbb-4a4a-8fe4-4137f00d925f",
        "outputId": "fdc6fa12-0122-45a1-e3d6-07c23e8f994d"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
            "To disable this warning, you can either:\n",
            "\t- Avoid using `tokenizers` before the fork if possible\n",
            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[1m\n",
            "\n",
            "                \u001b[38;5;069m(((((((((    \u001b[38;5;203m(((((\u001b[38;5;220m####\n",
            "             \u001b[38;5;069m(((((((((((((\u001b[38;5;203m(((((((((\u001b[38;5;220m#########\n",
            "           \u001b[38;5;069m(((((((((((((\u001b[38;5;203m(((((((((((\u001b[38;5;220m###########\n",
            "         \u001b[38;5;069m((((((((((((((\u001b[38;5;203m((((((((((((\u001b[38;5;220m############\n",
            "        \u001b[38;5;069m(((((((((((((\u001b[38;5;203m((((((((((((((\u001b[38;5;220m#############\n",
            "        \u001b[38;5;069m(((((((((((((\u001b[38;5;203m((((((((((((((\u001b[38;5;220m#############\n",
            "         \u001b[38;5;069m((((((((((((\u001b[38;5;203m(((((((((((((\u001b[38;5;220m##############\n",
            "         \u001b[38;5;069m((((((((((((\u001b[38;5;203m((((((((((((\u001b[38;5;220m##############\n",
            "           \u001b[38;5;069m((((((((((\u001b[38;5;203m(((((((((((\u001b[38;5;220m#############\n",
            "             \u001b[38;5;069m((((((((\u001b[38;5;203m((((((((\u001b[38;5;220m##############\n",
            "                \u001b[38;5;069m(((((\u001b[38;5;203m((((    \u001b[38;5;220m#########\u001b[0m\n",
            "\n",
            "    \n",
            "\u001b[1m\n",
            "Running Chroma\n",
            "\u001b[0m\n",
            "\u001b[1mSaving data to\u001b[0m: \u001b[32m./chromadb\u001b[0m\n",
            "\u001b[1mConnect to chroma at\u001b[0m: \u001b[32mhttp://localhost:8000\u001b[0m\n",
            "\u001b[1mGetting started guide\u001b[0m: https://docs.trychroma.com/getting-started\n",
            "\n",
            "\n",
            "\u001b[32mINFO\u001b[0m:     [24-12-2023 16:53:25] Set chroma_server_nofile to 65535\n",
            "\u001b[32mINFO\u001b[0m:     [24-12-2023 16:53:25] Anonymized telemetry enabled. See                     https://docs.trychroma.com/telemetry for more information.\n",
            "\u001b[36mDEBUG\u001b[0m:    [24-12-2023 16:53:25] Starting component System\n",
            "\u001b[36mDEBUG\u001b[0m:    [24-12-2023 16:53:25] Starting component OpenTelemetryClient\n",
            "\u001b[36mDEBUG\u001b[0m:    [24-12-2023 16:53:25] Starting component SimpleAssignmentPolicy\n",
            "\u001b[36mDEBUG\u001b[0m:    [24-12-2023 16:53:25] Starting component SqliteDB\n",
            "\u001b[36mDEBUG\u001b[0m:    [24-12-2023 16:53:25] Starting component Posthog\n",
            "\u001b[36mDEBUG\u001b[0m:    [24-12-2023 16:53:25] Starting component LocalSegmentManager\n",
            "\u001b[36mDEBUG\u001b[0m:    [24-12-2023 16:53:25] Starting component SegmentAPI\n",
            "\u001b[32mINFO\u001b[0m:     [24-12-2023 16:53:25] Started server process [\u001b[36m7527\u001b[0m]\n",
            "\u001b[32mINFO\u001b[0m:     [24-12-2023 16:53:25] Waiting for application startup.\n",
            "\u001b[32mINFO\u001b[0m:     [24-12-2023 16:53:25] Application startup complete.\n",
            "\u001b[32mINFO\u001b[0m:     [24-12-2023 16:53:25] Uvicorn running on \u001b[1mhttp://localhost:8000\u001b[0m (Press CTRL+C to quit)\n",
            "\u001b[32mINFO\u001b[0m:     [24-12-2023 16:57:57] ::1:52448 - \"GET /api/v1/tenants/default_tenant HTTP/1.1\" 200\n",
            "\u001b[32mINFO\u001b[0m:     [24-12-2023 16:57:57] ::1:52448 - \"GET /api/v1/databases/default_database?tenant=default_tenant HTTP/1.1\" 200\n",
            "\u001b[32mINFO\u001b[0m:     [24-12-2023 17:06:21] ::1:52463 - \"GET /api/v1/collections/local_news_collection?tenant=default_tenant&database=default_database HTTP/1.1\" 200\n",
            "\u001b[36mDEBUG\u001b[0m:    [24-12-2023 17:06:22] Starting component PersistentLocalHnswSegment\n",
            "\u001b[32mINFO\u001b[0m:     [24-12-2023 17:06:22] ::1:52463 - \"POST /api/v1/collections/a37539aa-239b-44f5-8079-c36926d21419/query HTTP/1.1\" 200\n",
            "^C\n",
            "\u001b[32mINFO\u001b[0m:     [24-12-2023 17:56:12] Shutting down\n",
            "\u001b[32mINFO\u001b[0m:     [24-12-2023 17:56:12] Waiting for application shutdown.\n",
            "\u001b[32mINFO\u001b[0m:     [24-12-2023 17:56:12] Application shutdown complete.\n",
            "\u001b[32mINFO\u001b[0m:     [24-12-2023 17:56:12] Finished server process [\u001b[36m7527\u001b[0m]\n"
          ]
        }
      ],
      "source": [
        "#Running Chroma in Server Mode\n",
        "!chroma run --path ./chromadb"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "bcb943bf-a5b2-4bb3-a265-72e2633ab98a",
      "metadata": {
        "id": "bcb943bf-a5b2-4bb3-a265-72e2633ab98a"
      },
      "source": [
        "You have the code to test this server in the notebook 2_3-ChromaDB Client.ipynb"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "a9428dd9-39dd-4d96-9bdb-05b6c00cfe67",
      "metadata": {
        "id": "a9428dd9-39dd-4d96-9bdb-05b6c00cfe67"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.10.12"
    },
    "colab": {
      "provenance": []
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  "nbformat": 4,
  "nbformat_minor": 5
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