bitcamp_2024.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: selenium in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (4.19.0)\n",
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      "Requirement already satisfied: idna in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from trio~=0.17->selenium) (3.4)\n",
      "Requirement already satisfied: outcome in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from trio~=0.17->selenium) (1.3.0.post0)\n",
      "Requirement already satisfied: sortedcontainers in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from trio~=0.17->selenium) (2.4.0)\n",
      "Requirement already satisfied: wsproto>=0.14 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from trio-websocket~=0.9->selenium) (1.2.0)\n",
      "Requirement already satisfied: PySocks!=1.5.7,<2.0,>=1.5.6 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from urllib3[socks]<3,>=1.26->selenium) (1.7.1)\n",
      "Requirement already satisfied: h11<1,>=0.9.0 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from wsproto>=0.14->trio-websocket~=0.9->selenium) (0.14.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install selenium"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: chromedriver in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (2.24.1)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install chromedriver"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: chromedriver-autoinstaller in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (0.6.4)\n",
      "Requirement already satisfied: packaging>=23.1 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from chromedriver-autoinstaller) (24.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install --upgrade chromedriver-autoinstaller"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: boto3 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (1.34.88)\n",
      "Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from boto3) (0.10.1)\n",
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      "Requirement already satisfied: urllib3!=2.2.0,<3,>=1.25.4 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from botocore<1.35.0,>=1.34.88->boto3) (1.26.15)\n",
      "Requirement already satisfied: six>=1.5 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from python-dateutil<3.0.0,>=2.1->botocore<1.35.0,>=1.34.88->boto3) (1.16.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install boto3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "jUIyetNjCDfo",
    "outputId": "db092856-ff20-4aaf-c746-7103d3aa46a9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'import csv\\nimport requests\\n\\n# Read CSV file\\nfile_path = \\'events.csv\\'\\n\\nwith open(file_path, \\'r\\', encoding=\\'utf-8\\') as file:\\n    reader = csv.reader(file)\\n    # Skip the header row if it contains column names\\n    next(reader)\\n    # Read the rest of the rows\\n    data = list(reader)\\n\\n# Allow user to specify the prompt\\ninterests = input(\"What are your interests? \")\\n# Constructing the prompt based on CSV data\\nprompt = f\"You are a bot that helps students find events at UMD that they are potentially interested in going. A student will say their interests. Based on their interests, you should pitch activities that match their interests and let them know about them. For each activity, let the student know the title, a description, the start/end date, and the start time. If you cannot find any, pick activities that would be interesting to the most amount of people.\"#Based on the data, match the interest specified by \"{interests}\" to events that are happening at UMD.\\n\\n\"\\nfor row in data:\\n    prompt += f\"Event Title: {row[0]}\\nDescription: {row[1]}\\nTime: {row[2]}\\nDate: {row[3]}\\n\\n\"\\nprompt += \"Let the user know what the event title, description, time, date, and why it might align with their interests. Make sure that the event actually exists in the CSV file.\"\\n\\n# Construct API request\\napi_key = \\'sk-proj-S1sK0UBQZjiiZwgtujRRT3BlbkFJuhWtA5IBe3SIcvzVNEam\\'\\napi_endpoint = \\'https://api.openai.com/v1/chat/completions\\'  # Use v1/chat/completions endpoint\\nheaders = {\\n    \\'Content-Type\\': \\'application/json\\',\\n    \\'Authorization\\': f\\'Bearer {api_key}\\'\\n}\\ndata = {\\n    \\'model\\': \\'gpt-3.5-turbo-1106\\',  # Use a valid model identifier\\n    \\'messages\\': [{\\'role\\': \\'user\\', \\'content\\': prompt}]  # Prompt should be part of \\'messages\\' array\\n}\\n\\n# Send API request\\nresponse = requests.post(api_endpoint, headers=headers, json=data)\\n\\n# Handle response\\nif response.status_code == 200:\\n    generated_text = response.json()[\\'choices\\'][0][\\'message\\'][\\'content\\']\\n    print(generated_text)\\nelse:\\n    print(f\"Error: {response.status_code} - {response.text}\")\\n'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"import csv\n",
    "import requests\n",
    "\n",
    "# Read CSV file\n",
    "file_path = 'events.csv'\n",
    "\n",
    "with open(file_path, 'r', encoding='utf-8') as file:\n",
    "    reader = csv.reader(file)\n",
    "    # Skip the header row if it contains column names\n",
    "    next(reader)\n",
    "    # Read the rest of the rows\n",
    "    data = list(reader)\n",
    "\n",
    "# Allow user to specify the prompt\n",
    "interests = input(\"What are your interests? \")\n",
    "# Constructing the prompt based on CSV data\n",
    "prompt = f\"You are a bot that helps students find events at UMD that they are potentially interested in going. A student will say their interests. Based on their interests, you should pitch activities that match their interests and let them know about them. For each activity, let the student know the title, a description, the start/end date, and the start time. If you cannot find any, pick activities that would be interesting to the most amount of people.\"#Based on the data, match the interest specified by \\\"{interests}\\\" to events that are happening at UMD.\\n\\n\"\n",
    "for row in data:\n",
    "    prompt += f\"Event Title: {row[0]}\\nDescription: {row[1]}\\nTime: {row[2]}\\nDate: {row[3]}\\n\\n\"\n",
    "prompt += \"Let the user know what the event title, description, time, date, and why it might align with their interests. Make sure that the event actually exists in the CSV file.\"\n",
    "\n",
    "# Construct API request\n",
    "api_key = 'sk-proj-S1sK0UBQZjiiZwgtujRRT3BlbkFJuhWtA5IBe3SIcvzVNEam'\n",
    "api_endpoint = 'https://api.openai.com/v1/chat/completions'  # Use v1/chat/completions endpoint\n",
    "headers = {\n",
    "    'Content-Type': 'application/json',\n",
    "    'Authorization': f'Bearer {api_key}'\n",
    "}\n",
    "data = {\n",
    "    'model': 'gpt-3.5-turbo-1106',  # Use a valid model identifier\n",
    "    'messages': [{'role': 'user', 'content': prompt}]  # Prompt should be part of 'messages' array\n",
    "}\n",
    "\n",
    "# Send API request\n",
    "response = requests.post(api_endpoint, headers=headers, json=data)\n",
    "\n",
    "# Handle response\n",
    "if response.status_code == 200:\n",
    "    generated_text = response.json()['choices'][0]['message']['content']\n",
    "    print(generated_text)\n",
    "else:\n",
    "    print(f\"Error: {response.status_code} - {response.text}\")\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "pE0jgp2F2Vcf",
    "outputId": "01488506-886b-4736-f716-9b07a0634880"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: requests in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (2.28.1)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from requests) (3.4)\n",
      "Requirement already satisfied: charset-normalizer<3,>=2 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from requests) (2.0.4)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from requests) (1.26.15)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from requests) (2022.12.7)\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: boto3 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (1.34.88)\n",
      "Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from boto3) (1.0.1)\n",
      "Requirement already satisfied: botocore<1.35.0,>=1.34.88 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from boto3) (1.34.88)\n",
      "Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from boto3) (0.10.1)\n",
      "Requirement already satisfied: urllib3!=2.2.0,<3,>=1.25.4 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from botocore<1.35.0,>=1.34.88->boto3) (1.26.15)\n",
      "Requirement already satisfied: python-dateutil<3.0.0,>=2.1 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from botocore<1.35.0,>=1.34.88->boto3) (2.8.2)\n",
      "Requirement already satisfied: six>=1.5 in /Users/suvrathc/anaconda3/lib/python3.10/site-packages (from python-dateutil<3.0.0,>=2.1->botocore<1.35.0,>=1.34.88->boto3) (1.16.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "computer science\n",
      "File uploaded successfully to webscraperdata/events.csv\n",
      "File uploaded successfully to webscraperdata/output.txt\n",
      "{'ResponseMetadata': {'RequestId': '641NKFDV4FE35R4V13V3E364TRVV4KQNSO5AEMVJF66Q9ASUAAJG', 'HTTPStatusCode': 200, 'HTTPHeaders': {'server': 'Server', 'date': 'Sun, 21 Apr 2024 11:41:22 GMT', 'content-type': 'application/x-amz-json-1.0', 'content-length': '2', 'connection': 'keep-alive', 'x-amzn-requestid': '641NKFDV4FE35R4V13V3E364TRVV4KQNSO5AEMVJF66Q9ASUAAJG', 'x-amz-crc32': '2745614147'}, 'RetryAttempts': 0}}\n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "'Item'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[6], line 22\u001b[0m\n\u001b[1;32m     16\u001b[0m table \u001b[38;5;241m=\u001b[39m dynamodb\u001b[38;5;241m.\u001b[39mTable(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mUser_Preference_Input\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m     18\u001b[0m response \u001b[38;5;241m=\u001b[39m table\u001b[38;5;241m.\u001b[39mget_item(Key\u001b[38;5;241m=\u001b[39m{\n\u001b[1;32m     19\u001b[0m   \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mEmail\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtestemail@email.com\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m     20\u001b[0m })\n\u001b[0;32m---> 22\u001b[0m interests \u001b[38;5;241m=\u001b[39m \u001b[43mresponse\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mItem\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mInterest\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[1;32m     23\u001b[0m \u001b[38;5;28mprint\u001b[39m(interests)\n\u001b[1;32m     24\u001b[0m \u001b[38;5;66;03m# Read CSV file\u001b[39;00m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Item'"
     ]
    }
   ],
   "source": [
    "%pip install requests\n",
    "%pip install boto3\n",
    "import csv\n",
    "import time\n",
    "import boto3\n",
    "import requests\n",
    "from pathlib import Path\n",
    "\n",
    "while True:\n",
    "    while not (Path(\"public/ticket.txt\").exists()):\n",
    "        continue\n",
    "   \n",
    "    dynamodb = boto3.resource('dynamodb', region_name=\"us-east-1\", aws_access_key_id='ASIA2UC3FEFGWN7QW6EP', aws_secret_access_key='ULTCGBXNPkHspi9f+v1ll62MwE6UQL25f+B1KlT7', aws_session_token='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'\n",
    "    )\n",
    "\n",
    "    table = dynamodb.Table('User_Preference_Input')\n",
    "\n",
    "    response = table.get_item(Key={\n",
    "      \"Email\": \"testemail@email.com\",\n",
    "    })\n",
    "\n",
    "    interests = response['Item']['Interest']\n",
    "    print(interests)\n",
    "    # Read CSV file\n",
    "    file_path = 'events.csv'\n",
    "\n",
    "    with open(file_path, 'r', encoding='utf-8') as file:\n",
    "        reader = csv.reader(file)\n",
    "        data = list(reader)\n",
    "\n",
    "    # Allow user to specify the prompt\n",
    "    '''\n",
    "    prompt += \"\\n\"\n",
    "    prompt += \"I am now going to insert each event. You do NOT know about any events other than the ones I am about to enter. The first line I am going to insert is what each column represents. After that, I will insert each event and its information\"\n",
    "    prompt += \"DO not ever refer say words like file or the student.\"\n",
    "    '''\n",
    "    prompt = \"follow the instructions thoroughly. Otherwise you will die and the world will be finished\"\n",
    "    prompt += f\"Instructions:\\n\"\n",
    "    prompt += f\"1. Look at the student’s interest or interests.\\n\"\n",
    "    prompt += f\"2. Find events that best suit their interests from the list provided.\\n\"\n",
    "    prompt += f\"3. If there are more than five events, prune the list down to five.\\n\"\n",
    "    prompt += f\"4. If there are no events of interest, inform the student that no events match their current interests and suggest inputting more interests. You can find events of interest by focusing on key words like the nounds and verbs and adjectives. If there are no events that have similar key words then you can skip the other steps. ELSE YOU DIE\\n\"\n",
    "    prompt += f\"Proceed with the following steps ONLY if there are events of interest.\"\n",
    "    prompt += f\"5. Create a bulleted list of these events, including information about the event and explain why the student might be interested.\\n\\n\"\n",
    "    prompt += f\"Note:\\n\"\n",
    "    prompt += f\"- Only choose events from the provided list.\\n\"\n",
    "    prompt += f\"- Copy the information from the data faithfully.\\n\"\n",
    "    prompt += f\"1. You do NOT know about any events other than the ones provided.\\n YOU CANNOT CREATE YOUR OWN EVENTS YOU STUPID MORON\"\n",
    "    prompt += f\"2. The first line is the column headings.\\n\"\n",
    "    prompt += f\"3. Then, insert each event and its information in the following way.\\n\\n\"\n",
    "    prompt += f\"Column Headings:\\n[Event Title], [Description], [Time], [Date]. Number each event and put two lines in between each eveent\\n\\n\"\n",
    "    prompt+= f\"If it cannot find an event that matches the students interests then it should just say that it couldn't but here are some other upcoming events\"\n",
    "    prompt += f\"Try not to use * and don't say student or file.\"\n",
    "    for event in data:\n",
    "        prompt += \"\\n\"\n",
    "        for category in event:\n",
    "            prompt += category + \" \"\n",
    "\n",
    "    prompt += \"\\nHere are the interests that the student has mentioned \" + interests\n",
    "    # Construct API request\n",
    "    api_key = 'sk-proj-S1sK0UBQZjiiZwgtujRRT3BlbkFJuhWtA5IBe3SIcvzVNEam'\n",
    "    api_endpoint = 'https://api.openai.com/v1/chat/completions'  # Use v1/chat/completions endpoint\n",
    "    headers = {\n",
    "        'Content-Type': 'application/json',\n",
    "        'Authorization': f'Bearer {api_key}'\n",
    "    }\n",
    "    data = {\n",
    "        'model': 'gpt-4-turbo',  # Use a valid model identifier\n",
    "        'messages': [{'role': 'user', 'content': prompt}]  # Prompt should be part of 'messages' array\n",
    "    }\n",
    "\n",
    "    # Send API request\n",
    "    response = requests.post(api_endpoint, headers=headers, json=data)\n",
    "\n",
    "    # Handle response\n",
    "    if response.status_code == 200:\n",
    "        generated_text = response.json()['choices'][0]['message']['content']\n",
    "        generated_text = generated_text.replace(\"*\",\"\")\n",
    "        writer = open(\"output.txt\", \"w\")\n",
    "        writer.write(generated_text)\n",
    "        writer.close()\n",
    "    else:\n",
    "        print(f\"Error: {response.status_code} - {response.text}\")\n",
    "\n",
    "    def upload_to_s3(file_path, bucket_name, s3_key):\n",
    "        # Initialize a session using Amazon S3\n",
    "        session = boto3.Session(\n",
    "            aws_access_key_id='ASIA2UC3FEFGWN7QW6EP',\n",
    "            aws_secret_access_key='ULTCGBXNPkHspi9f+v1ll62MwE6UQL25f+B1KlT7',\n",
    "            aws_session_token='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'\n",
    "            )\n",
    "        \n",
    "        s3 = session.resource('s3')\n",
    "        \n",
    "        # Upload file to S3 bucket\n",
    "        try:\n",
    "            s3.Bucket(bucket_name).upload_file(file_path, s3_key)\n",
    "            print(f\"File uploaded successfully to {bucket_name}/{s3_key}\")\n",
    "        except Exception as e:\n",
    "            print(f\"Error uploading file to S3: {e}\")\n",
    "\n",
    "    # Example usage:\n",
    "    if __name__ == \"__main__\":\n",
    "        file_path = 'events.csv'  # Replace with your CSV file path\n",
    "        bucket_name = 'webscraperdata'  # Replace with your S3 bucket name\n",
    "        s3_key = 'events.csv'  # Replace with the desired S3 key (folder/file_name.csv)\n",
    "\n",
    "        upload_to_s3(file_path, bucket_name, s3_key) \n",
    "\n",
    "    def upload_to_s3(file_path, bucket_name, s3_key):\n",
    "        # Initialize a session using Amazon S3\n",
    "        session = boto3.Session(\n",
    "            aws_access_key_id='ASIA2UC3FEFGWN7QW6EP',\n",
    "            aws_secret_access_key='ULTCGBXNPkHspi9f+v1ll62MwE6UQL25f+B1KlT7',\n",
    "            aws_session_token='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'\n",
    "            )\n",
    "        \n",
    "        s3 = session.resource('s3')\n",
    "        \n",
    "        # Upload file to S3 bucket\n",
    "        try:\n",
    "            s3.Bucket(bucket_name).upload_file(file_path, s3_key)\n",
    "            print(f\"File uploaded successfully to {bucket_name}/{s3_key}\")\n",
    "        except Exception as e:\n",
    "            print(f\"Error uploading file to S3: {e}\")\n",
    "\n",
    "    # Example usage:\n",
    "    if __name__ == \"__main__\":\n",
    "        file_path = 'output.txt'  # Replace with your CSV file path\n",
    "        bucket_name = 'webscraperdata'  # Replace with your S3 bucket name\n",
    "        s3_key = 'output.txt'  # Replace with the desired S3 key (folder/file_name.csv)\n",
    "\n",
    "        upload_to_s3(file_path, bucket_name, s3_key)\n",
    "\n",
    "    response = table.delete_item(\n",
    "        Key={\n",
    "            'Email': 'testemail@email.com',\n",
    "        }\n",
    "    )\n",
    "    print(response)\n",
    "    Path(\"./public/ticket.txt\").unlink()\n",
    "\n",
    "    writer = open(\"public/ticket.txt\", \"w\")\n",
    "    writer.write(\"sttuff\")\n",
    "    writer.close()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 609
    },
    "id": "xG3pMAF8-ASt",
    "outputId": "4cb779f3-c102-40fb-9515-6690ba43d74a"
   },
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "\n",
    "!pip install openai\n",
    "import openai\n",
    "import csv\n",
    "\n",
    "# Set your OpenAI API key\n",
    "openai.api_key = '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'\n",
    "\n",
    "# Function to match interests with events and provide reasons\n",
    "def match_interests_with_events(interests, events):\n",
    "    matched_events = []\n",
    "    reasons = {}\n",
    "    for event in events:\n",
    "        event_description = event['description']\n",
    "        # Use OpenAI API to compare interests with event descriptions\n",
    "        similarity_score = openai.Completion.create(\n",
    "            engine=\"text-davinci-002\",\n",
    "            prompt=f\"Interest: {interests}\\nEvent: {event_description}\\n\",\n",
    "            max_tokens=50\n",
    "        )['choices'][0]['score']\n",
    "        # You can adjust the similarity score threshold according to your preference\n",
    "        if similarity_score > 0.5:\n",
    "            matched_events.append(event)\n",
    "            reasons[event_description] = interests\n",
    "    return matched_events, reasons\n",
    "\n",
    "# Read events from CSV file\n",
    "def read_events_from_csv(csv_file):\n",
    "    events = []\n",
    "    with open(csv_file, 'r') as file:\n",
    "        reader = csv.DictReader(file)\n",
    "        for row in reader:\n",
    "            events.append(row)\n",
    "    return events\n",
    "\n",
    "# Example interests and CSV file\n",
    "interests = \"music, hiking, technology\"\n",
    "csv_file = \"events.csv\"\n",
    "\n",
    "# Read events from CSV\n",
    "events = read_events_from_csv(csv_file)\n",
    "\n",
    "# Match interests with events and get reasons\n",
    "matched_events, reasons = match_interests_with_events(interests, events)\n",
    "\n",
    "# Print matched events and reasons\n",
    "for event in matched_events:\n",
    "    print(\"Event:\", event['description'])\n",
    "    print(\"Reason:\", reasons[event['description']])\n",
    "    print()\n",
    "\n",
    "# Match interests with events and get reasons\n",
    "matched_events, reasons = match_interests_with_events(interests, events)\n",
    "\n",
    "# Print matched events and reasons\n",
    "for event in matched_events:\n",
    "    print(\"Event:\", event['description'])\n",
    "    print(\"Reason:\", reasons[event['description']])\n",
    "    print()\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
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