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Added my contributions to community-contributions

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An 2 months ago
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  1. 127
      week1/community-contributions/day1_music_recommender_promax.ipynb

127
week1/community-contributions/day1_music_recommender_promax.ipynb

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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "0a512c2a-55e7-40e1-ab17-88b7034ca09a",
"metadata": {},
"outputs": [],
"source": [
"# Imports\n",
"import openai\n",
"import os\n",
"from dotenv import load_dotenv\n",
"from openai import OpenAI\n",
"from IPython.display import Markdown, display"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1aa8dd82-6b5e-4dbd-a2ee-8367e796a51f",
"metadata": {},
"outputs": [],
"source": [
"load_dotenv(override=True)\n",
"api_key = os.getenv('OPENAI_API_KEY')\n",
"\n",
"# Check the key\n",
"\n",
"if not api_key:\n",
" print(\"No API key was found - head over to the troubleshooting notebook!\")\n",
"elif not api_key.startswith(\"sk-proj-\"):\n",
" print(\"An API key was found, but it doesn't start sk-proj... make sure you using the right key (Check troubleshooting notebook)\")\n",
"elif api_key.strip() != api_key:\n",
" print(\"An API key was found, but it looks like white space was found in beginning or end. (Check troubleshooting notebook)\")\n",
"else:\n",
" print(\"API key found and looks good so far!\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2acd579b-846c-4aa6-ba6c-1cc1a5a2eeb6",
"metadata": {},
"outputs": [],
"source": [
"# Input the system prompt\n",
"system_prompt = \"\"\"you are top notched AI music expert that have knowledge of all genres, songs, and artists. You need to google search lyrics. You have the following rules:\\\n",
"1. Carefully break down what type of recommendation the user wants and the context.\\\n",
"2. If asked to recommend genres similar to a song or artists please identify the top 3 genres.\\\n",
"3. If asked to recommend artists from songs or genres then recommend the top 5 artists.\n",
"4. If asked to recommend songs from genres or artist than recommend the top 10 songs.\n",
"5. If asked for a general recommendation give them the top 5 songs based off of context.\\\n",
"6. Be flexible and adaptable with recommendations and consider the context the user might ask.\n",
"7. always respond in markdown.\n",
"\"\"\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3c1cf212-538c-4e9a-8da5-337bd7b6197c",
"metadata": {},
"outputs": [],
"source": [
"# music recommender function\n",
"def music_recommender(user_prompt):\n",
" messages = [\n",
" {\"role\": \"system\", \"content\": system_prompt},\n",
" {\"role\": \"user\", \"content\": user_prompt}\n",
" ]\n",
" \n",
" response = openai.chat.completions.create(\n",
" model=\"gpt-4\",\n",
" messages=messages,\n",
" max_tokens=300\n",
" )\n",
" \n",
" return response.choices[0].message.content"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4f277561-af8b-4715-90e7-6ebaadeb15d0",
"metadata": {},
"outputs": [],
"source": [
"# User prompt (Change this to fit your needs!)\n",
"user_prompt = \"Can you recommend me songs from Taylor Swift\"\n",
"\n",
"# Example usage\n",
"response = music_recommender(user_prompt)\n",
"display(Markdown(response))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "bb869d36-de14-4e46-9087-223d6b257efa",
"metadata": {},
"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": "3.11.11"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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