File size: 5,174 Bytes
164b4eb
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
04a1b11
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
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("/ai/v1/chat/completions", methods=["POST"])
#解决v1拦截
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)