mirror of
https://github.com/xtekky/gpt4free.git
synced 2024-12-19 00:22:26 +03:00
91 lines
2.6 KiB
Python
91 lines
2.6 KiB
Python
import json
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import random
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import string
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import time
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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("/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, 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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if __name__ == "__main__":
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app.run(host="0.0.0.0", port=1337, debug=True) |