mirror of
https://github.com/wassname/stampy-chat.git
synced 2026-09-24 14:00:40 +08:00
64 lines
1.6 KiB
Python
64 lines
1.6 KiB
Python
from flask import Flask, jsonify, request
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from flask_cors import CORS, cross_origin
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from get_blocks import get_top_k_blocks
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from chat import talk_to_robot
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import dataclasses
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import os
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import openai
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import pickle
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import requests
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if os.path.exists('.env'):
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from dotenv import load_dotenv
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load_dotenv()
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app = Flask(__name__)
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cors = CORS(app)
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app.config['CORS_HEADERS'] = 'Content-Type'
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# -------------------------------- general setup -------------------------------
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OPENAI_API_KEY = os.environ.get('OPENAI_API_KEY')
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openai.api_key = OPENAI_API_KEY
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print('Downloading dataset...')
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url = os.environ.get('DATASET_URL')
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if url is None:
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print('No dataset url provided.')
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exit()
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dataset_dict_bytes = requests.get(url).content
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print('Unpacking dataset...')
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dataset_dict = pickle.loads(dataset_dict_bytes)
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print('Done!')
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# ------------------------------- semantic search ------------------------------
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@app.route('/semantic', methods=['POST'])
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@cross_origin()
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def semantic():
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query = request.json['query']
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return jsonify([dataclasses.asdict(block) for block in get_top_k_blocks(dataset_dict, query)])
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# ------------------------------------ chat ------------------------------------
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@app.route('/chat', methods=['POST'])
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@cross_origin()
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def chat():
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query = request.json['query']
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response, context = talk_to_robot(dataset_dict, query)
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return jsonify({'response': response, 'citations': [{'title': block.title, 'author': block.author, 'date': block.date, 'url': block.url} for block in context]})
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# ------------------------------------------------------------------------------
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if __name__ == '__main__': app.run(debug=True, port=3000)
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