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import gevent.pywsgi |
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from gevent import monkey;monkey.patch_all() |
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from flask import Flask, request, Response, jsonify |
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import argparse |
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import requests |
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import random |
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import string |
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import time |
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import json |
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import os |
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app = Flask(__name__) |
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app.json.sort_keys = False |
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parser = argparse.ArgumentParser(description="An example of Qwen demo with a similar API to OAI.") |
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parser.add_argument("--host", type=str, help="Set the ip address.(default: 0.0.0.0)", default='0.0.0.0') |
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parser.add_argument("--port", type=int, help="Set the port.(default: 7860)", default=7860) |
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args = parser.parse_args() |
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base_url = os.getenv('MODEL_BASE_URL') |
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print(base_url) |
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@app.route('/api/v1/models', methods=["GET", "POST"]) |
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@app.route('/v1/models', methods=["GET", "POST"]) |
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def model_list(): |
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time_now = int(time.time()) |
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model_list = { |
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"object": "list", |
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"data": [ |
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{ |
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"id": "qwen", |
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"object": "model", |
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"created": time_now, |
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"owned_by": "tastypear" |
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}, |
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{ |
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"id": "gpt-3.5-turbo", |
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"object": "model", |
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"created": time_now, |
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"owned_by": "tastypear" |
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} |
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] |
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} |
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return jsonify(model_list) |
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@app.route("/", methods=["GET"]) |
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def index(): |
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return Response(f"Hunyuan-Large OpenAI Compatible API<br><br>"+ |
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f'Set "{os.getenv("SPACE_URL")}/api" as proxy (or API Domain) in your Chatbot.<br><br>'+ |
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f"The complete API is: {os.getenv("SPACE_URL")}/api/v1/chat/completions<br><br>"+ |
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f"Don't set the Syetem Prompt. It will be ignored.") |
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@app.route("/api/v1/chat/completions", methods=["POST", "OPTIONS"]) |
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@app.route("/v1/chat/completions", methods=["POST", "OPTIONS"]) |
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def chat_completions(): |
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if request.method == "OPTIONS": |
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return Response( |
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headers={ |
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"Access-Control-Allow-Origin": "*", |
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"Access-Control-Allow-Headers": "*", |
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} |
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) |
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data = request.get_json() |
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system = "You are a helpful assistant." |
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chat_history = [] |
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prompt = "" |
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if "messages" in data: |
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messages = data["messages"] |
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message_size = len(messages) |
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prompt = messages[-1].get("content") |
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for i in range(message_size - 1): |
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role_this = messages[i].get("role") |
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role_next = messages[i + 1].get("role") |
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if role_this == "system": |
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system = messages[i].get("content") |
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elif role_this == "user": |
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if role_next == "assistant": |
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chat_history.append( |
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[messages[i].get("content"), messages[i + 1].get("content")] |
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) |
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else: |
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chat_history.append([messages[i].get("content"), " "]) |
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fn_index = 3 |
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chars = string.ascii_lowercase + string.digits |
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session_hash = "".join(random.choice(chars) for _ in range(10)) |
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single_prompt_data = { |
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'data': [ |
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prompt, |
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[], |
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], |
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'event_data': None, |
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'fn_index': 1, |
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'trigger_id': 5, |
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'session_hash': session_hash, |
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} |
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response = requests.post(f'{base_url}/gradio_api/run/predict', json=single_prompt_data) |
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context_data = { |
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'data': [ |
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None, |
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chat_history+[[prompt,None]] |
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], |
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'event_data': None, |
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'fn_index': fn_index, |
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'trigger_id': 5, |
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'session_hash': session_hash, |
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} |
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response = requests.post(f"{base_url}/gradio_api/queue/join", json=context_data) |
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def generate(): |
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url = f"{base_url}/gradio_api/queue/data?session_hash={session_hash}" |
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data = requests.get(url, stream=True) |
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time_now = int(time.time()) |
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for line in data.iter_lines(): |
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if line: |
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decoded_line = line.decode("utf-8") |
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json_line = json.loads(decoded_line[6:]) |
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if json_line["msg"] == "process_starts": |
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res_data = gen_res_data({}, time_now=time_now, start=True) |
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yield f"data: {json.dumps(res_data)}\n\n" |
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elif json_line["msg"] == "process_generating": |
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res_data = gen_res_data(json_line, time_now=time_now) |
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yield f"data: {json.dumps(res_data)}\n\n" |
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elif json_line["msg"] == "process_completed": |
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yield "data: [DONE]" |
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return Response( |
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generate(), |
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mimetype="text/event-stream", |
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headers={ |
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"Access-Control-Allow-Origin": "*", |
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"Access-Control-Allow-Headers": "*", |
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}, |
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) |
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def gen_res_data(data, time_now=0, start=False): |
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res_data = { |
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"id": "chatcmpl", |
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"object": "chat.completion.chunk", |
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"created": time_now, |
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"model": "qwen2_5", |
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"choices": [{"index": 0, "finish_reason": None}], |
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} |
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if start: |
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res_data["choices"][0]["delta"] = {"role": "assistant", "content": ""} |
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else: |
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chat_pair = data["output"]["data"][0] |
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if chat_pair == []: |
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res_data["choices"][0]["finish_reason"] = "stop" |
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else: |
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res_data["choices"][0]["delta"] = {"content": chat_pair[-1][-1]} |
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return res_data |
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if __name__ == "__main__": |
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gevent.pywsgi.WSGIServer((args.host, args.port), app).serve_forever() |