pubmed-chat.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/acdc-digital/Medex-Public-MITP/blob/main/Ingest_Playrgound.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 108,
      "metadata": {
        "id": "DXqlzn7iKi2T",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0c8bd9a0-c802-4618-b691-f63787b8332e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: datetime in /usr/local/lib/python3.10/dist-packages (5.1)\n",
            "Requirement already satisfied: zope.interface in /usr/local/lib/python3.10/dist-packages (from datetime) (6.0)\n",
            "Requirement already satisfied: pytz in /usr/local/lib/python3.10/dist-packages (from datetime) (2022.7.1)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from zope.interface->datetime) (67.7.2)\n",
            "Requirement already satisfied: IPython in /usr/local/lib/python3.10/dist-packages (7.34.0)\n",
            "Requirement already satisfied: setuptools>=18.5 in /usr/local/lib/python3.10/dist-packages (from IPython) (67.7.2)\n",
            "Requirement already satisfied: jedi>=0.16 in /usr/local/lib/python3.10/dist-packages (from IPython) (0.18.2)\n",
            "Requirement already satisfied: decorator in /usr/local/lib/python3.10/dist-packages (from IPython) (4.4.2)\n",
            "Requirement already satisfied: pickleshare in /usr/local/lib/python3.10/dist-packages (from IPython) (0.7.5)\n",
            "Requirement already satisfied: traitlets>=4.2 in /usr/local/lib/python3.10/dist-packages (from IPython) (5.7.1)\n",
            "Requirement already satisfied: prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from IPython) (3.0.39)\n",
            "Requirement already satisfied: pygments in /usr/local/lib/python3.10/dist-packages (from IPython) (2.14.0)\n",
            "Requirement already satisfied: backcall in /usr/local/lib/python3.10/dist-packages (from IPython) (0.2.0)\n",
            "Requirement already satisfied: matplotlib-inline in /usr/local/lib/python3.10/dist-packages (from IPython) (0.1.6)\n",
            "Requirement already satisfied: pexpect>4.3 in /usr/local/lib/python3.10/dist-packages (from IPython) (4.8.0)\n",
            "Requirement already satisfied: parso<0.9.0,>=0.8.0 in /usr/local/lib/python3.10/dist-packages (from jedi>=0.16->IPython) (0.8.3)\n",
            "Requirement already satisfied: ptyprocess>=0.5 in /usr/local/lib/python3.10/dist-packages (from pexpect>4.3->IPython) (0.7.0)\n",
            "Requirement already satisfied: wcwidth in /usr/local/lib/python3.10/dist-packages (from prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0->IPython) (0.2.6)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (1.22.4)\n",
            "Requirement already satisfied: openai in /usr/local/lib/python3.10/dist-packages (0.27.8)\n",
            "Requirement already satisfied: requests>=2.20 in /usr/local/lib/python3.10/dist-packages (from openai) (2.27.1)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from openai) (4.65.0)\n",
            "Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from openai) (3.8.4)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai) (1.26.16)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai) (2023.5.7)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai) (2.0.12)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai) (3.4)\n",
            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai) (23.1.0)\n",
            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai) (6.0.4)\n",
            "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai) (4.0.2)\n",
            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai) (1.9.2)\n",
            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai) (1.3.3)\n",
            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai) (1.3.1)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (2.27.1)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests) (1.26.16)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests) (2023.5.7)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests) (2.0.12)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests) (3.4)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (4.65.0)\n",
            "Requirement already satisfied: pymed in /usr/local/lib/python3.10/dist-packages (0.8.9)\n",
            "Requirement already satisfied: requests>=2.20.0 in /usr/local/lib/python3.10/dist-packages (from pymed) (2.27.1)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20.0->pymed) (1.26.16)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20.0->pymed) (2023.5.7)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20.0->pymed) (2.0.12)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20.0->pymed) (3.4)\n",
            "Requirement already satisfied: pyPDF2 in /usr/local/lib/python3.10/dist-packages (3.0.1)\n",
            "Collecting PyMuPDF\n",
            "  Downloading PyMuPDF-1.22.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (14.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m14.1/14.1 MB\u001b[0m \u001b[31m44.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: PyMuPDF\n",
            "Successfully installed PyMuPDF-1.22.5\n"
          ]
        }
      ],
      "source": [
        "!pip install datetime\n",
        "!pip install IPython\n",
        "!pip install numpy\n",
        "!pip install openai\n",
        "!pip install requests\n",
        "!pip install tqdm\n",
        "!pip install pymed\n",
        "!pip install pyPDF2\n",
        "!pip install PyMuPDF"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 109,
      "metadata": {
        "id": "YAbcCpM4KHvV"
      },
      "outputs": [],
      "source": [
        "%%capture\n",
        "%env PUBMED_API_KEY = 9ee60be0024526a2a7c631dbc41aa609b008"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 115,
      "metadata": {
        "id": "vZI9xKc7J5ex"
      },
      "outputs": [],
      "source": [
        "# Dependencies\n",
        "from datetime import date, timedelta  # date handling for fetching recent news\n",
        "from IPython import display  # for pretty printing\n",
        "import json  # for parsing the JSON api responses and model outputs\n",
        "from numpy import dot  # for cosine similarity\n",
        "import openai  # for using GPT and getting embeddings\n",
        "import os  # for loading environment variables\n",
        "import requests  # for making the API requests\n",
        "from tqdm.notebook import tqdm  # for printing progress bars\n",
        "from pymed import PubMed\n",
        "\n",
        "GPT_MODEL = \"gpt-3.5-turbo-16k\"\n",
        "\n",
        "\n",
        "# Helper functions\n",
        "def json_gpt(input: str):\n",
        "    completion = openai.ChatCompletion.create(\n",
        "        model=GPT_MODEL,\n",
        "        messages=[\n",
        "            {\"role\": \"system\", \"content\": \"Output only valid JSON\"},\n",
        "            {\"role\": \"user\", \"content\": input},\n",
        "        ],\n",
        "        temperature=0.5,\n",
        "    )\n",
        "\n",
        "    text = completion.choices[0].message.content\n",
        "    parsed = json.loads(text)\n",
        "\n",
        "    return parsed\n",
        "\n",
        "\n",
        "def embeddings(input: list[str]) -> list[list[str]]:\n",
        "    response = openai.Embedding.create(model=\"text-embedding-ada-002\", input=input)\n",
        "    return [data.embedding for data in response.data]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 116,
      "metadata": {
        "id": "LFS7rQg3KGRE"
      },
      "outputs": [],
      "source": [
        "# User asks a question\n",
        "USER_QUESTION = \"four days ago. I had cortisone injections into the cmv joint in my left hand, as well as in my tendon. its hurt even more, what now?\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 117,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SslWJ-g4KLqi",
        "outputId": "18f0ca0e-d0b5-4b57-b3ae-99d657288eb8"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['cortisone injections cmv joint left hand tendon hurt',\n",
              " 'cortisone injections cmv joint left hand tendon pain',\n",
              " 'cortisone injections cmv joint left hand tendon side effects',\n",
              " 'cortisone injections cmv joint left hand tendon complications',\n",
              " 'cortisone injections cmv joint left hand tendon recovery',\n",
              " 'cortisone injections cmv joint left hand tendon treatment',\n",
              " 'cortisone injections cmv joint left hand tendon management',\n",
              " 'cortisone injections cmv joint left hand tendon follow-up',\n",
              " 'cortisone injections cmv joint left hand tendon alternatives',\n",
              " 'cortisone injections cmv joint left hand tendon risks',\n",
              " 'cortisone injections cmv joint left hand tendon guidelines',\n",
              " 'cortisone injections cmv joint left hand tendon precautions',\n",
              " 'four days ago. I had cortisone injections into the cmv joint in my left hand, as well as in my tendon. its hurt even more, what now?']"
            ]
          },
          "metadata": {},
          "execution_count": 117
        }
      ],
      "source": [
        "import openai\n",
        "openai.api_key = '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'\n",
        "\n",
        "QUERIES_INPUT = f\"\"\"\n",
        "You have access to a search API that returns recent PubMed articles.\n",
        "Generate an array of search queries that are relevant to this question.\n",
        "Use a variation of related keywords for the queries, trying to be as general as possible.\n",
        "Include as many queries as you can think of, including and excluding terms.\n",
        "For example, include queries like ['keyword_1 keyword_2', 'keyword_1', 'keyword_2'].\n",
        "Be creative. The more queries you include, the more likely you are to find relevant results.\n",
        "\n",
        "User question: {USER_QUESTION}\n",
        "\n",
        "Format: {{\"queries\": [\"query_1\", \"query_2\", \"query_3\"]}}\n",
        "\"\"\"\n",
        "\n",
        "queries = json_gpt(QUERIES_INPUT)[\"queries\"]\n",
        "\n",
        "# Let's include the original question as well for good measure\n",
        "queries.append(USER_QUESTION)\n",
        "\n",
        "queries"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 103,
          "referenced_widgets": [
            "b784dff6238a47b0b33726ce7a761719",
            "3a2597c0bb254909b7adf11bd9dceb81",
            "16074aa907de4b4ebbe49ad9df89b8a9",
            "d36a0b9e3e1b4e32a5c0d47abefaded6",
            "56d1acb30ae444ffae994dcc4f3891c6",
            "1034a4817a3640b9959d6f60312c9ad1",
            "46595ee2a8424d73b61f42fd358a7a0c",
            "d8c6f83cfcb0443082f0fd6a3ef889d6",
            "8da1656b5e8748ab9753cfc24225278c",
            "8a1a63069e9346c3b69c5fca5e896c3f",
            "8d240fa36f3d4148ac8119e768dbca50"
          ]
        },
        "id": "AWUtCb_eKOQG",
        "outputId": "734ae275-8727-48ab-d4d5-59bff42d9e2c"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/17 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "b784dff6238a47b0b33726ce7a761719"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Total number of articles: 0\n",
            "Top 5 articles of query 1: \n",
            "\n"
          ]
        }
      ],
      "source": [
        "import requests\n",
        "import xml.etree.ElementTree as ET\n",
        "\n",
        "def search_pubmed(\n",
        "    query: str,\n",
        "    pubmed_api_key: str = \"9ee60be0024526a2a7c631dbc41aa609b008\",\n",
        "    num_articles: int = 5,\n",
        "    from_date: str = \"2023-4-10\",\n",
        "    to_date: str = \"2023-7-10\",\n",
        ") -> dict:\n",
        "    response = requests.get(\n",
        "        \"https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi\",\n",
        "        params={\n",
        "            \"db\": \"pubmed\",\n",
        "            \"term\": query,\n",
        "            \"api_key\": pubmed_api_key,\n",
        "            \"retmax\": num_articles,\n",
        "            \"datetype\": \"pdat\",\n",
        "            \"mindate\": from_date,\n",
        "            \"maxdate\": to_date,\n",
        "        },\n",
        "    )\n",
        "\n",
        "    if response.status_code != 200:\n",
        "        raise Exception(f\"Request failed with status code {response.status_code}\")\n",
        "\n",
        "    root = ET.fromstring(response.content)\n",
        "    error = root.find(\".//ErrorList/PhraseNotFound\")\n",
        "    if error is not None:\n",
        "        raise Exception(\"Phrase not found\")\n",
        "\n",
        "    article_ids = [id_elem.text for id_elem in root.findall(\".//IdList/Id\")]\n",
        "    return article_ids\n",
        "\n",
        "\n",
        "def search_pubmed_summary(pubmed_id: str, pubmed_api_key: str = \"9ee60be0024526a2a7c631dbc41aa609b008\") -> dict:\n",
        "    response = requests.get(\n",
        "        \"https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi\",\n",
        "        params={\n",
        "            \"db\": \"pubmed\",\n",
        "            \"id\": pubmed_id,\n",
        "            \"api_key\": pubmed_api_key,\n",
        "        },\n",
        "    )\n",
        "\n",
        "    if response.status_code != 200:\n",
        "        raise Exception(f\"Request failed with status code {response.status_code}\")\n",
        "\n",
        "    root = ET.fromstring(response.content)\n",
        "    error = root.find(\".//Error\")\n",
        "    if error is not None:\n",
        "        raise Exception(f\"Error retrieving summary for PubMed ID: {pubmed_id}\")\n",
        "\n",
        "    article = {}\n",
        "    article[\"title\"] = root.findtext(\".//Item[@Name='Title']\")\n",
        "    article[\"abstract\"] = root.findtext(\".//Item[@Name='Abstract']\")\n",
        "    article[\"score\"] = root.findtext(\".//Item[@Name='Score']\")\n",
        "\n",
        "    return article\n",
        "\n",
        "# Set the desired maximum number of articles\n",
        "max_num_articles = 10\n",
        "\n",
        "\n",
        "articles = []\n",
        "\n",
        "for query in tqdm(queries):\n",
        "    result = search_pubmed(query)\n",
        "\n",
        "    for article_id in result:\n",
        "        article_summary = search_pubmed_summary(article_id)\n",
        "        articles.append(article_summary)\n",
        "\n",
        "print(\"Total number of articles:\", len(articles))\n",
        "print(\"Top 5 articles of query 1:\", \"\\n\")\n",
        "\n",
        "for article in articles[0:2]:\n",
        "    print(\"Title:\", article[\"title\"])\n",
        "    print(\"Abstract:\", article[\"abstract\"])\n",
        "    print(\"Score:\", article[\"score\"])\n",
        "    print()\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 71
        },
        "id": "ULgoZnVFKTQK",
        "outputId": "8882b364-e20d-4698-c45a-fa2c00b5aa89"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Based on the information provided, it is possible that the cortisone injections into the cmv joint in your left hand and tendon have not provided the expected relief. It is recommended to consult with your healthcare provider for further evaluation and to discuss alternative treatment options.'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 84
        }
      ],
      "source": [
        "HA_INPUT = f\"\"\"\n",
        "Generate a hypothetical answer to the user's question. This answer will be used to rank search results.\n",
        "Pretend you have all the information you need to answer, but don't use any actual facts. Instead, use placeholders\n",
        "like NAME did something, or NAME said something at PLACE.\n",
        "\n",
        "User question: {USER_QUESTION}\n",
        "\n",
        "Format: {{\"hypotheticalAnswer\": \"hypothetical answer text\"}}\n",
        "\"\"\"\n",
        "\n",
        "hypothetical_answer = json_gpt(HA_INPUT)[\"hypotheticalAnswer\"]\n",
        "\n",
        "hypothetical_answer"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y4rx-buvKWOE",
        "outputId": "3ec8c29a-b5f4-47d4-8555-b8cf3aa78b30"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[]\n"
          ]
        }
      ],
      "source": [
        "import concurrent.futures\n",
        "\n",
        "article_embeddings = []\n",
        "cosine_similarities = []\n",
        "\n",
        "def process_article(article):\n",
        "    article_text = f\"{article.get('title', '')} {article.get('abstract', '')} {article.get('content', '')[:50]}\"\n",
        "    if article_text.strip() != \"\":\n",
        "        response = openai.ChatCompletion.create(\n",
        "            model=\"gpt-3.5-turbo-16k\",\n",
        "            messages=[\n",
        "                {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n",
        "                {\"role\": \"user\", \"content\": article_text}\n",
        "            ]\n",
        "        )\n",
        "        article_embedding = response.choices[0].message.get(\"embedding\")\n",
        "        article_embeddings.append(article_embedding)\n",
        "\n",
        "        similarity = openai.ChatCompletion.create(\n",
        "            model=\"gpt-3.5-turbo-16k\",\n",
        "            messages=[\n",
        "                {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n",
        "                {\"role\": \"user\", \"content\": hypothetical_answer},\n",
        "                {\"role\": \"assistant\", \"content\": article_embedding}\n",
        "            ]\n",
        "        )\n",
        "        cosine_similarity = similarity.choices[0].score\n",
        "        cosine_similarities.append(cosine_similarity)\n",
        "\n",
        "# Adjust the batch size based on your available resources and performance requirements\n",
        "batch_size = 5\n",
        "\n",
        "# Create a ThreadPoolExecutor with the desired number of threads (adjust as needed)\n",
        "with concurrent.futures.ThreadPoolExecutor() as executor:\n",
        "    # Submit the tasks for processing in parallel\n",
        "    futures = []\n",
        "    for article in articles:\n",
        "        future = executor.submit(process_article, article)\n",
        "        futures.append(future)\n",
        "\n",
        "    # Wait for all tasks to complete\n",
        "    concurrent.futures.wait(futures)\n",
        "\n",
        "# Print the first 5 cosine similarities\n",
        "print(cosine_similarities[:5])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "h2YbsnlHKY_M",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f0c0390f-32cb-487b-e889-877bb1ae09e0"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Top 5 articles: \n",
            "\n"
          ]
        }
      ],
      "source": [
        "scored_articles = zip(articles, cosine_similarities)\n",
        "\n",
        "# Sort articles by cosine similarity\n",
        "sorted_articles = sorted(scored_articles, key=lambda x: x[1], reverse=True)\n",
        "\n",
        "# Print top 5 articles\n",
        "print(\"Top 5 articles:\", \"\\n\")\n",
        "\n",
        "for article, score in sorted_articles[0:5]:\n",
        "    print(\"Title:\", article[\"title\"])\n",
        "    print(\"Description:\", article[\"description\"])\n",
        "    print(\"Content:\", article[\"content\"][0:100] + \"...\")\n",
        "    print(\"Score:\", score)\n",
        "    print()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BEcP_WqiKbvD",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 209
        },
        "outputId": "2e9a71aa-af4c-4fd0-f103-d9d54c068923"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Markdown object>"
            ],
            "text/markdown": "I'm sorry to hear that you're experiencing increased pain after cortisone injections in your left hand. It's important to note that I'm an AI language model and cannot provide medical advice. However, I can offer some general information.\n\nIncreased pain after cortisone injections can sometimes occur, and it's advisable to consult with your healthcare provider for an evaluation. They will be able to assess your specific situation and provide appropriate guidance.\n\nIn the meantime, you may find it helpful to apply ice to the affected area for 15-20 minutes several times a day to help reduce inflammation and pain. Avoiding activities that aggravate the pain and keeping the hand elevated when possible may also provide some relief.\n\nIf you have any concerns or questions, it's best to reach out to your healthcare provider for further assistance. They are the most qualified to provide personalized advice based on your medical history and current condition.\n\nPlease remember that the information provided here is not a substitute for professional medical advice."
          },
          "metadata": {}
        }
      ],
      "source": [
        "formatted_top_results = [\n",
        "    {\n",
        "        \"title\": article[\"title\"],\n",
        "        \"description\": article[\"description\"],\n",
        "        \"url\": article[\"url\"],\n",
        "    }\n",
        "    for article, _score in sorted_articles[0:5]\n",
        "]\n",
        "\n",
        "ANSWER_INPUT = f\"\"\"\n",
        "Generate an answer to the user's question based on the given search results.\n",
        "TOP_RESULTS: {formatted_top_results}\n",
        "USER_QUESTION: {USER_QUESTION}\n",
        "\n",
        "Include as much information as possible in the answer. Reference the relevant search result urls as markdown links.\n",
        "\"\"\"\n",
        "\n",
        "completion = openai.ChatCompletion.create(\n",
        "    model=GPT_MODEL,\n",
        "    messages=[{\"role\": \"user\", \"content\": ANSWER_INPUT}],\n",
        "    temperature=0.5,\n",
        "    stream=True,\n",
        ")\n",
        "\n",
        "text = \"\"\n",
        "for chunk in completion:\n",
        "    text += chunk.choices[0].delta.get(\"content\", \"\")\n",
        "    display.clear_output(wait=True)\n",
        "    display.display(display.Markdown(text))"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyPg1iuSRC+RBFhb0QH/Xe5x",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    },
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "b784dff6238a47b0b33726ce7a761719": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_3a2597c0bb254909b7adf11bd9dceb81",
              "IPY_MODEL_16074aa907de4b4ebbe49ad9df89b8a9",
              "IPY_MODEL_d36a0b9e3e1b4e32a5c0d47abefaded6"
            ],
            "layout": "IPY_MODEL_56d1acb30ae444ffae994dcc4f3891c6"
          }
        },
        "3a2597c0bb254909b7adf11bd9dceb81": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_1034a4817a3640b9959d6f60312c9ad1",
            "placeholder": "​",
            "style": "IPY_MODEL_46595ee2a8424d73b61f42fd358a7a0c",
            "value": "100%"
          }
        },
        "16074aa907de4b4ebbe49ad9df89b8a9": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_d8c6f83cfcb0443082f0fd6a3ef889d6",
            "max": 17,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_8da1656b5e8748ab9753cfc24225278c",
            "value": 17
          }
        },
        "d36a0b9e3e1b4e32a5c0d47abefaded6": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_8a1a63069e9346c3b69c5fca5e896c3f",
            "placeholder": "​",
            "style": "IPY_MODEL_8d240fa36f3d4148ac8119e768dbca50",
            "value": " 17/17 [00:14&lt;00:00,  1.11it/s]"
          }
        },
        "56d1acb30ae444ffae994dcc4f3891c6": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "1034a4817a3640b9959d6f60312c9ad1": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "46595ee2a8424d73b61f42fd358a7a0c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "d8c6f83cfcb0443082f0fd6a3ef889d6": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "8da1656b5e8748ab9753cfc24225278c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "8a1a63069e9346c3b69c5fca5e896c3f": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "8d240fa36f3d4148ac8119e768dbca50": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        }
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}