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data preprocessing
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Paul Lin authored and Paul Lin committed Mar 28, 2024
1 parent dc17f99 commit c9491d3
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89 changes: 89 additions & 0 deletions backend/process_data.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"from openai import OpenAI\n",
"import json\n",
"from tqdm import tqdm\n",
"import os\n",
"from dotenv import load_dotenv\n",
"load_dotenv()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"OPENAI_API_KEY = os.getenv(\"OPENAI_API_KEY\")\n",
"client = OpenAI(api_key=OPENAI_API_KEY)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"def get_embedding(text):\n",
" response = client.embeddings.create(\n",
" model=\"text-embedding-3-small\",\n",
" input=text\n",
" )\n",
" return response.data[0].embedding"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 1206/1206 [04:05<00:00, 4.91it/s]\n"
]
}
],
"source": [
"with open('202501.json', 'r') as file:\n",
" courses = json.load(file)\n",
"\n",
"for course in tqdm(courses):\n",
" text_to_embed = f\"{course['short_title']}: {course['description']}\"\n",
" embedding = get_embedding(text_to_embed) \n",
" course['embedding'] = embedding\n",
"\n",
"with open('courses_with_embeddings.json', 'w') as file:\n",
" json.dump(courses, file, indent=4)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.12.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

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