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from fastapi import FastAPI, Request, Depends, HTTPException | |
from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials | |
from fastapi.responses import StreamingResponse | |
from fastapi.background import BackgroundTasks | |
import requests | |
from curl_cffi import requests as cffi_requests # 保留这个,用于获取cookies | |
import uuid | |
import json | |
import time | |
from typing import Optional | |
import asyncio | |
import base64 | |
import tempfile | |
import os | |
import re | |
app = FastAPI() | |
security = HTTPBearer() | |
# OpenAI API Key 配置,可以通过环境变量覆盖 | |
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", None) # 设置为 None 表示不校验,或设置具体值,如"sk-proj-1234567890" | |
# 修改全局数据存储 | |
global_data = { | |
"cookie": None, | |
"cookies": None, | |
"last_update": 0 | |
} | |
def get_cookie(): | |
try: | |
# 使用 curl_cffi 发送请求 | |
response = cffi_requests.get( | |
'https://chat.akash.network/', | |
impersonate="chrome110", | |
timeout=30 | |
) | |
# 获取所有 cookies | |
cookies = response.cookies.items() | |
if cookies: | |
cookie_str = '; '.join([f'{k}={v}' for k, v in cookies]) | |
global_data["cookie"] = cookie_str | |
global_data["last_update"] = time.time() | |
print(f"Got cookies: {cookie_str}") | |
return cookie_str | |
except Exception as e: | |
print(f"Error fetching cookie: {e}") | |
return None | |
async def check_and_update_cookie(background_tasks: BackgroundTasks): | |
# 如果cookie超过30分钟,在后台更新 | |
if time.time() - global_data["last_update"] > 1800: | |
background_tasks.add_task(get_cookie) | |
async def startup_event(): | |
get_cookie() | |
async def get_api_key(credentials: HTTPAuthorizationCredentials = Depends(security)): | |
token = credentials.credentials | |
# 如果设置了 OPENAI_API_KEY,则需要验证 | |
if OPENAI_API_KEY is not None: | |
# 去掉 Bearer 前缀后再比较 | |
clean_token = token.replace("Bearer ", "") if token.startswith("Bearer ") else token | |
if clean_token != OPENAI_API_KEY: | |
raise HTTPException( | |
status_code=401, | |
detail="Invalid API key" | |
) | |
# 返回去掉 "Bearer " 前缀的token | |
return token.replace("Bearer ", "") if token.startswith("Bearer ") else token | |
async def check_image_status(session: requests.Session, job_id: str, headers: dict) -> Optional[str]: | |
"""检查图片生成状态并获取生成的图片""" | |
max_retries = 30 | |
for attempt in range(max_retries): | |
try: | |
print(f"\nAttempt {attempt + 1}/{max_retries} for job {job_id}") | |
response = session.get( | |
f'https://chat.akash.network/api/image-status?ids={job_id}', | |
headers=headers | |
) | |
print(f"Status response code: {response.status_code}") | |
status_data = response.json() | |
if status_data and isinstance(status_data, list) and len(status_data) > 0: | |
job_info = status_data[0] | |
status = job_info.get('status') | |
print(f"Job status: {status}") | |
# 只有当状态为 completed 时才处理结果 | |
if status == "completed": | |
result = job_info.get("result") | |
if result and not result.startswith("Failed"): | |
print("Got valid result, attempting upload...") | |
image_url = await upload_to_xinyew(result, job_id) | |
if image_url: | |
print(f"Successfully uploaded image: {image_url}") | |
return image_url | |
print("Image upload failed") | |
return None | |
print("Invalid result received") | |
return None | |
elif status == "failed": | |
print(f"Job {job_id} failed") | |
return None | |
# 如果状态是其他(如 pending),继续等待 | |
await asyncio.sleep(1) | |
continue | |
except Exception as e: | |
print(f"Error checking status: {e}") | |
return None | |
print(f"Timeout waiting for job {job_id}") | |
return None | |
async def health_check(): | |
"""Health check endpoint""" | |
return {"status": "ok"} | |
async def chat_completions( | |
request: Request, | |
api_key: str = Depends(get_api_key) | |
): | |
try: | |
data = await request.json() | |
print(f"Chat request data: {data}") | |
chat_id = str(uuid.uuid4()).replace('-', '')[:16] | |
akash_data = { | |
"id": chat_id, | |
"messages": data.get('messages', []), | |
"model": data.get('model', "DeepSeek-R1"), | |
"system": data.get('system_message', "You are a helpful assistant."), | |
"temperature": data.get('temperature', 0.6), | |
"topP": data.get('top_p', 0.95) | |
} | |
headers = { | |
"Content-Type": "application/json", | |
"Cookie": f"session_token={api_key}", | |
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36", | |
"Accept": "*/*", | |
"Accept-Language": "zh-CN,zh;q=0.9,en-US;q=0.8,en;q=0.7", | |
"Accept-Encoding": "gzip, deflate, br", | |
"Origin": "https://chat.akash.network", | |
"Referer": "https://chat.akash.network/", | |
"Sec-Fetch-Dest": "empty", | |
"Sec-Fetch-Mode": "cors", | |
"Sec-Fetch-Site": "same-origin", | |
"Connection": "keep-alive", | |
"Priority": "u=1, i" | |
} | |
print(f"Sending request to Akash with headers: {headers}") | |
print(f"Request data: {akash_data}") | |
with requests.Session() as session: | |
response = session.post( | |
'https://chat.akash.network/api/chat', | |
json=akash_data, | |
headers=headers, | |
stream=True | |
) | |
def generate(): | |
content_buffer = "" | |
for line in response.iter_lines(): | |
if not line: | |
continue | |
try: | |
line_str = line.decode('utf-8') | |
msg_type, msg_data = line_str.split(':', 1) | |
if msg_type == '0': | |
if msg_data.startswith('"') and msg_data.endswith('"'): | |
msg_data = msg_data.replace('\\"', '"') | |
msg_data = msg_data[1:-1] | |
msg_data = msg_data.replace("\\n", "\n") | |
# 在处理消息时先判断模型类型 | |
if data.get('model') == 'AkashGen' and "<image_generation>" in msg_data: | |
# 图片生成模型的特殊处理 | |
async def process_and_send(): | |
end_msg = await process_image_generation(msg_data, session, headers, chat_id) | |
if end_msg: | |
chunk = { | |
"id": f"chatcmpl-{chat_id}", | |
"object": "chat.completion.chunk", | |
"created": int(time.time()), | |
"model": data.get('model'), | |
"choices": [{ | |
"delta": {"content": end_msg}, | |
"index": 0, | |
"finish_reason": None | |
}] | |
} | |
return f"data: {json.dumps(chunk)}\n\n" | |
return None | |
# 创建新的事件循环 | |
loop = asyncio.new_event_loop() | |
asyncio.set_event_loop(loop) | |
try: | |
result = loop.run_until_complete(process_and_send()) | |
finally: | |
loop.close() | |
if result: | |
yield result | |
continue | |
content_buffer += msg_data | |
chunk = { | |
"id": f"chatcmpl-{chat_id}", | |
"object": "chat.completion.chunk", | |
"created": int(time.time()), | |
"model": data.get('model'), | |
"choices": [{ | |
"delta": {"content": msg_data}, | |
"index": 0, | |
"finish_reason": None | |
}] | |
} | |
yield f"data: {json.dumps(chunk)}\n\n" | |
elif msg_type in ['e', 'd']: | |
chunk = { | |
"id": f"chatcmpl-{chat_id}", | |
"object": "chat.completion.chunk", | |
"created": int(time.time()), | |
"model": data.get('model'), # 使用请求中指定的模型 | |
"choices": [{ | |
"delta": {}, | |
"index": 0, | |
"finish_reason": "stop" | |
}] | |
} | |
yield f"data: {json.dumps(chunk)}\n\n" | |
yield "data: [DONE]\n\n" | |
break | |
except Exception as e: | |
print(f"Error processing line: {e}") | |
continue | |
return StreamingResponse( | |
generate(), | |
media_type='text/event-stream', | |
headers={ | |
'Cache-Control': 'no-cache', | |
'Connection': 'keep-alive', | |
'Content-Type': 'text/event-stream' | |
} | |
) | |
except Exception as e: | |
return {"error": str(e)} | |
async def list_models(api_key: str = Depends(get_api_key)): | |
try: | |
headers = { | |
"Content-Type": "application/json", | |
"Cookie": f"session_token={api_key}", | |
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36", | |
"Accept": "*/*", | |
"Accept-Language": "zh-CN,zh;q=0.9,en-US;q=0.8,en;q=0.7", | |
"Accept-Encoding": "gzip, deflate, br", | |
"Origin": "https://chat.akash.network", | |
"Referer": "https://chat.akash.network/", | |
"Sec-Fetch-Dest": "empty", | |
"Sec-Fetch-Mode": "cors", | |
"Sec-Fetch-Site": "same-origin", | |
"Connection": "keep-alive" | |
} | |
response = requests.get( | |
'https://chat.akash.network/api/models', | |
headers=headers | |
) | |
akash_response = response.json() | |
# 转换为标准 OpenAI 格式 | |
openai_models = { | |
"object": "list", | |
"data": [ | |
{ | |
"id": model["id"], | |
"object": "model", | |
"created": int(time.time()), | |
"owned_by": "akash", | |
"permission": [{ | |
"id": "modelperm-" + model["id"], | |
"object": "model_permission", | |
"created": int(time.time()), | |
"allow_create_engine": False, | |
"allow_sampling": True, | |
"allow_logprobs": True, | |
"allow_search_indices": False, | |
"allow_view": True, | |
"allow_fine_tuning": False, | |
"organization": "*", | |
"group": None, | |
"is_blocking": False | |
}] | |
} for model in akash_response.get("models", []) | |
] | |
} | |
return openai_models | |
except Exception as e: | |
print(f"Error in list_models: {e}") | |
return {"error": str(e)} | |
async def upload_to_xinyew(image_base64: str, job_id: str) -> Optional[str]: | |
"""上传图片到新野图床并返回URL""" | |
try: | |
print(f"\n=== Starting image upload for job {job_id} ===") | |
print(f"Base64 data length: {len(image_base64)}") | |
# 解码base64图片数据 | |
try: | |
image_data = base64.b64decode(image_base64.split(',')[1] if ',' in image_base64 else image_base64) | |
print(f"Decoded image data length: {len(image_data)} bytes") | |
except Exception as e: | |
print(f"Error decoding base64: {e}") | |
print(f"First 100 chars of base64: {image_base64[:100]}...") | |
return None | |
# 创建临时文件 | |
with tempfile.NamedTemporaryFile(suffix='.jpeg', delete=False) as temp_file: | |
temp_file.write(image_data) | |
temp_file_path = temp_file.name | |
try: | |
filename = f"{job_id}.jpeg" | |
print(f"Using filename: {filename}") | |
# 准备文件上传 | |
files = { | |
'file': (filename, open(temp_file_path, 'rb'), 'image/jpeg') | |
} | |
print("Sending request to xinyew.cn...") | |
response = requests.post( | |
'https://api.xinyew.cn/api/jdtc', | |
files=files, | |
timeout=30 | |
) | |
print(f"Upload response status: {response.status_code}") | |
if response.status_code == 200: | |
result = response.json() | |
print(f"Upload response: {result}") | |
if result.get('errno') == 0: | |
url = result.get('data', {}).get('url') | |
if url: | |
print(f"Successfully got image URL: {url}") | |
return url | |
print("No URL in response data") | |
else: | |
print(f"Upload failed: {result.get('message')}") | |
else: | |
print(f"Upload failed with status {response.status_code}") | |
print(f"Response content: {response.text}") | |
return None | |
finally: | |
# 清理临时文件 | |
try: | |
os.unlink(temp_file_path) | |
except Exception as e: | |
print(f"Error removing temp file: {e}") | |
except Exception as e: | |
print(f"Error in upload_to_xinyew: {e}") | |
import traceback | |
print(traceback.format_exc()) | |
return None | |
async def process_image_generation(msg_data: str, session: requests.Session, headers: dict, chat_id: str) -> str: | |
"""处理图片生成的逻辑""" | |
match = re.search(r"jobId='([^']+)' prompt='([^']+)' negative='([^']*)'", msg_data) | |
if match: | |
job_id, prompt, negative = match.groups() | |
print(f"Starting image generation process for job_id: {job_id}") | |
# 发送思考开始的消息 | |
start_time = time.time() | |
end_msg = "<think>\n" | |
end_msg += "🎨 Generating image...\n\n" | |
end_msg += f"Prompt: {prompt}\n" | |
# 检查图片状态和上传 | |
result = await check_image_status(session, job_id, headers) | |
# 发送结束消息 | |
elapsed_time = time.time() - start_time | |
end_msg += f"\n🤔 Thinking for {elapsed_time:.1f}s...\n" | |
end_msg += "</think>\n\n" | |
if result: # result 现在是上传后的图片URL | |
end_msg += f"" | |
else: | |
end_msg += "*Image generation or upload failed.*\n" | |
return end_msg | |
return "" | |
if __name__ == '__main__': | |
import uvicorn | |
uvicorn.run(app, host='0.0.0.0', port=9000) |