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94 lines
2.8 KiB
Python
94 lines
2.8 KiB
Python
import json
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import time
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import random
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import string
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from typing import Any
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from flask import Flask, request
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from flask_cors import CORS
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from g4f import ChatCompletion
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app = Flask(__name__)
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CORS(app)
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@app.route('/')
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def index():
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return 'interference api, url: http://127.0.0.1:1337'
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@app.route('/chat/completions', methods=['POST'])
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def chat_completions():
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model = request.get_json().get('model', 'gpt-3.5-turbo')
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stream = request.get_json().get('stream', False)
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messages = request.get_json().get('messages')
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response = ChatCompletion.create(model = model,
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stream = stream, messages = messages)
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completion_id = ''.join(random.choices(string.ascii_letters + string.digits, k=28))
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completion_timestamp = int(time.time())
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if not stream:
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return {
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'id': f'chatcmpl-{completion_id}',
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'object': 'chat.completion',
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'created': completion_timestamp,
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'model': model,
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'choices': [
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{
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'index': 0,
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'message': {
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'role': 'assistant',
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'content': response,
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},
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'finish_reason': 'stop',
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}
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],
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'usage': {
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'prompt_tokens': None,
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'completion_tokens': None,
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'total_tokens': None,
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},
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}
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def streaming():
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for chunk in response:
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completion_data = {
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'id': f'chatcmpl-{completion_id}',
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'object': 'chat.completion.chunk',
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'created': completion_timestamp,
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'model': model,
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'choices': [
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{
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'index': 0,
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'delta': {
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'content': chunk,
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},
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'finish_reason': None,
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}
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],
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}
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content = json.dumps(completion_data, separators=(',', ':'))
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yield f'data: {content}\n\n'
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time.sleep(0.1)
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end_completion_data: dict[str, Any] = {
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'id': f'chatcmpl-{completion_id}',
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'object': 'chat.completion.chunk',
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'created': completion_timestamp,
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'model': model,
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'choices': [
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{
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'index': 0,
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'delta': {},
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'finish_reason': 'stop',
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}
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],
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}
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content = json.dumps(end_completion_data, separators=(',', ':'))
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yield f'data: {content}\n\n'
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return app.response_class(streaming(), mimetype='text/event-stream')
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def run_interference():
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app.run(host='0.0.0.0', port=1337, debug=True) |