File size: 9,689 Bytes
0731c95
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
17808c5
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
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
import os
import json
import time
import uuid
import httpx
from fastapi import FastAPI, HTTPException, Request
from fastapi.responses import StreamingResponse
from pydantic import BaseModel, Field
from typing import List, Optional, Dict, Any
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

# Initialize FastAPI app
app = FastAPI(
    title="Ki2API - Claude Sonnet 4 OpenAI Compatible API",
    description="Simple Docker-ready OpenAI-compatible API for Claude Sonnet 4",
    version="1.0.0"
)

# Configuration
API_KEY = os.getenv("API_KEY", "ki2api-key-2024")
KIRO_ACCESS_TOKEN = os.getenv("KIRO_ACCESS_TOKEN")
KIRO_REFRESH_TOKEN = os.getenv("KIRO_REFRESH_TOKEN")
KIRO_BASE_URL = "https://codewhisperer.us-east-1.amazonaws.com/generateAssistantResponse"
PROFILE_ARN = "arn:aws:codewhisperer:us-east-1:699475941385:profile/EHGA3GRVQMUK"

# Model mapping
MODEL_NAME = "claude-sonnet-4-20250514"
CODEWHISPERER_MODEL = "CLAUDE_SONNET_4_20250514_V1_0"

# Pydantic models
class ChatMessage(BaseModel):
    role: str
    content: str

class ChatCompletionRequest(BaseModel):
    model: str
    messages: List[ChatMessage]
    temperature: Optional[float] = 0.7
    max_tokens: Optional[int] = 4000
    stream: Optional[bool] = False

class ChatCompletionResponse(BaseModel):
    id: str = Field(default_factory=lambda: f"chatcmpl-{uuid.uuid4()}")
    object: str = "chat.completion"
    created: int = Field(default_factory=lambda: int(time.time()))
    model: str
    choices: List[Dict[str, Any]]
    usage: Dict[str, int]

class ChatCompletionStreamResponse(BaseModel):
    id: str = Field(default_factory=lambda: f"chatcmpl-{uuid.uuid4()}")
    object: str = "chat.completion.chunk"
    created: int = Field(default_factory=lambda: int(time.time()))
    model: str
    choices: List[Dict[str, Any]]

# Token management
class TokenManager:
    def __init__(self):
        self.access_token = KIRO_ACCESS_TOKEN
        self.refresh_token = KIRO_REFRESH_TOKEN
        self.refresh_url = "https://prod.us-east-1.auth.desktop.kiro.dev/refreshToken"

    async def refresh_tokens(self):
        if not self.refresh_token:
            return None
        
        try:
            async with httpx.AsyncClient() as client:
                response = await client.post(
                    self.refresh_url,
                    json={"refreshToken": self.refresh_token},
                    timeout=30
                )
                response.raise_for_status()
                
                data = response.json()
                self.access_token = data.get("accessToken")
                return self.access_token
        except Exception as e:
            print(f"Token refresh failed: {e}")
            return None

    def get_token(self):
        return self.access_token

token_manager = TokenManager()

# Build CodeWhisperer request
def build_codewhisperer_request(messages: List[ChatMessage]):
    conversation_id = str(uuid.uuid4())
    
    # Extract system prompt and user messages
    system_prompt = ""
    user_messages = []
    
    for msg in messages:
        if msg.role == "system":
            system_prompt = msg.content
        else:
            user_messages.append(msg)
    
    if not user_messages:
        raise HTTPException(status_code=400, detail="No user messages found")
    
    # Build history
    history = []
    for i in range(0, len(user_messages) - 1, 2):
        if i + 1 < len(user_messages):
            history.append({
                "userInputMessage": {
                    "content": user_messages[i].content,
                    "modelId": CODEWHISPERER_MODEL,
                    "origin": "AI_EDITOR"
                }
            })
            history.append({
                "assistantResponseMessage": {
                    "content": user_messages[i + 1].content,
                    "toolUses": []
                }
            })
    
    # Build current message
    current_message = user_messages[-1]
    content = current_message.content
    if system_prompt:
        content = f"{system_prompt}\n\n{content}"
    
    return {
        "profileArn": PROFILE_ARN,
        "conversationState": {
            "chatTriggerType": "MANUAL",
            "conversationId": conversation_id,
            "currentMessage": {
                "userInputMessage": {
                    "content": content,
                    "modelId": CODEWHISPERER_MODEL,
                    "origin": "AI_EDITOR",
                    "userInputMessageContext": {}
                }
            },
            "history": history
        }
    }

# Make API call to Kiro/CodeWhisperer
async def call_kiro_api(messages: List[ChatMessage], stream: bool = False):
    token = token_manager.get_token()
    if not token:
        raise HTTPException(status_code=401, detail="No access token available")
    
    request_data = build_codewhisperer_request(messages)
    
    headers = {
        "Authorization": f"Bearer {token}",
        "Content-Type": "application/json",
        "Accept": "text/event-stream" if stream else "application/json"
    }
    
    try:
        async with httpx.AsyncClient() as client:
            response = await client.post(
                KIRO_BASE_URL,
                headers=headers,
                json=request_data,
                timeout=120
            )
            
            if response.status_code == 403:
                # Try to refresh token
                new_token = await token_manager.refresh_tokens()
                if new_token:
                    headers["Authorization"] = f"Bearer {new_token}"
                    response = await client.post(
                        KIRO_BASE_URL,
                        headers=headers,
                        json=request_data,
                        timeout=120
                    )
            
            response.raise_for_status()
            return response
            
    except Exception as e:
        raise HTTPException(status_code=503, detail=f"API call failed: {str(e)}")

# API endpoints
@app.get("/v1/models")
async def list_models():
    return {
        "object": "list",
        "data": [
            {
                "id": MODEL_NAME,
                "object": "model",
                "created": int(time.time()),
                "owned_by": "ki2api"
            }
        ]
    }

@app.post("/v1/chat/completions")
async def create_chat_completion(request: ChatCompletionRequest):
    if request.model != MODEL_NAME:
        raise HTTPException(status_code=400, detail=f"Only {MODEL_NAME} is supported")
    
    if request.stream:
        return await create_streaming_response(request)
    else:
        return await create_non_streaming_response(request)

async def create_non_streaming_response(request: ChatCompletionRequest):
    response = await call_kiro_api(request.messages, stream=False)
    
    # Parse response
    response_text = response.text
    
    return ChatCompletionResponse(
        model=MODEL_NAME,
        choices=[{
            "index": 0,
            "message": {
                "role": "assistant",
                "content": response_text
            },
            "finish_reason": "stop"
        }],
        usage={
            "prompt_tokens": 0,
            "completion_tokens": 0,
            "total_tokens": 0
        }
    )

async def create_streaming_response(request: ChatCompletionRequest):
    response = await call_kiro_api(request.messages, stream=True)
    
    async def generate():
        # Send initial response
        initial_chunk = {
            'id': f'chatcmpl-{uuid.uuid4()}',
            'object': 'chat.completion.chunk',
            'created': int(time.time()),
            'model': MODEL_NAME,
            'choices': [{
                'index': 0,
                'delta': {'role': 'assistant'},
                'finish_reason': None
            }]
        }
        yield f"data: {json.dumps(initial_chunk)}\n\n"
        
        # Read response and stream content
        content = ""
        async for line in response.aiter_lines():
            if line.startswith('data: '):
                try:
                    data = json.loads(line[6:])
                    if 'content' in data:
                        content += data['content']
                        chunk = {
                            'id': f'chatcmpl-{uuid.uuid4()}',
                            'object': 'chat.completion.chunk',
                            'created': int(time.time()),
                            'model': MODEL_NAME,
                            'choices': [{
                                'index': 0,
                                'delta': {'content': data['content']},
                                'finish_reason': None
                            }]
                        }
                        yield f"data: {json.dumps(chunk)}\n\n"
                except:
                    continue
        
        # Send final response
        final_chunk = {
            'id': f'chatcmpl-{uuid.uuid4()}',
            'object': 'chat.completion.chunk',
            'created': int(time.time()),
            'model': MODEL_NAME,
            'choices': [{
                'index': 0,
                'delta': {},
                'finish_reason': 'stop'
            }]
        }
        yield f"data: {json.dumps(final_chunk)}\n\n"
        
        yield "data: [DONE]\n\n"
    
    return StreamingResponse(generate(), media_type="text/event-stream")

# Health check
@app.get("/health")
async def health_check():
    return {"status": "ok", "service": "ki2api"}

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=7860)