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app.py

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+from flask import Flask, request, Response, json
+import requests
+from uuid import uuid4
+import time
+
+app = Flask(__name__)
+
+MODEL_MAPPING = {
+   "deepseek": "deepseek/deepseek-chat",
+   "gpt-4o-mini": "openai/gpt-4o-mini", 
+   "gemini-flash-1.5": "google/gemini-flash-1.5",
+   "deepseek-reasoner": "deepseek-reasoner",
+   "minimax-01": "minimax/minimax-01"
+}
+
+def make_heck_request(question, session_id, messages, actual_model):
+   previous_question = previous_answer = None
+   if len(messages) >= 2:
+       for i in range(len(messages)-2, -1, -1):
+           if messages[i]["role"] == "user":
+               previous_question = messages[i]["content"]
+               if i+1 < len(messages) and messages[i+1]["role"] == "assistant":
+                   previous_answer = messages[i+1]["content"]
+               break
+
+   payload = {
+       "model": actual_model,
+       "question": question,
+       "language": "Chinese",
+       "sessionId": session_id,
+       "previousQuestion": previous_question,
+       "previousAnswer": previous_answer
+   }
+   
+   headers = {
+       "Content-Type": "application/json",
+       "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"
+   }
+
+   return requests.post(
+       "https://gateway.aiapilab.com/api/ha/v1/chat",
+       json=payload,
+       headers=headers,
+       stream=True
+   )
+
+def stream_response(question, session_id, messages, request_model, actual_model):
+   resp = make_heck_request(question, session_id, messages, actual_model)
+   is_answering = False
+   
+   for line in resp.iter_lines():
+       if line:
+           line = line.decode('utf-8')
+           if not line.startswith('data: '):
+               continue
+           
+           content = line[6:].strip()
+           
+           if content == "[ANSWER_START]":
+               is_answering = True
+               chunk = {
+                   "id": session_id,
+                   "object": "chat.completion.chunk",
+                   "created": int(time.time()),
+                   "model": request_model,
+                   "choices": [{
+                       "index": 0,
+                       "delta": {"role": "assistant"},
+                   }]
+               }
+               yield f"data: {json.dumps(chunk, ensure_ascii=False)}\n\n"
+               continue
+           
+           if content == "[ANSWER_DONE]":
+               chunk = {
+                   "id": session_id,
+                   "object": "chat.completion.chunk",
+                   "created": int(time.time()),
+                   "model": request_model,
+                   "choices": [{
+                       "index": 0,
+                       "delta": {},
+                       "finish_reason": "stop"
+                   }]
+               }
+               yield f"data: {json.dumps(chunk, ensure_ascii=False)}\n\n"
+               break
+           
+           if is_answering and content and not content.startswith("[RELATE_Q"):
+               chunk = {
+                   "id": session_id,
+                   "object": "chat.completion.chunk",
+                   "created": int(time.time()),
+                   "model": request_model,
+                   "choices": [{
+                       "index": 0,
+                       "delta": {"content": content},
+                   }]
+               }
+               yield f"data: {json.dumps(chunk, ensure_ascii=False)}\n\n"
+
+def normal_response(question, session_id, messages, request_model, actual_model):
+   resp = make_heck_request(question, session_id, messages, actual_model)
+   full_content = []
+   is_answering = False
+   
+   for line in resp.iter_lines():
+       if line:
+           line = line.decode('utf-8')
+           if line.startswith('data: '):
+               content = line[6:].strip()
+               if content == "[ANSWER_START]":
+                   is_answering = True
+               elif content == "[ANSWER_DONE]":
+                   break
+               elif is_answering:
+                   full_content.append(content)
+   
+   response = {
+       "id": session_id,
+       "object": "chat.completion",
+       "created": int(time.time()),
+       "model": request_model,
+       "choices": [{
+           "index": 0,
+           "message": {
+               "role": "assistant",
+               "content": "".join(full_content)
+           },
+           "finish_reason": "stop"
+       }]
+   }
+   return response
+
+@app.route("/v1/chat/completions", methods=["POST"])
+def chat_completions():
+   data = request.json
+   model = MODEL_MAPPING.get(data["model"])
+   if not model:
+       return {"error": "Unsupported Model"}, 400
+
+   question = next((msg["content"] for msg in reversed(data["messages"]) 
+                   if msg["role"] == "user"), None)
+   session_id = str(uuid4())
+
+   if data.get("stream"):
+       return Response(
+           stream_response(question, session_id, data["messages"], 
+                         data["model"], model),
+           mimetype="text/event-stream"
+       )
+   else:
+       return normal_response(question, session_id, data["messages"], 
+                            data["model"], model)
+
+if __name__ == "__main__":
+   app.run(host='0.0.0.0', port=8801)

requirements.txt

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+flask
+requests
+uuid