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from fastapi import FastAPI, Request, Depends, HTTPException |
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from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials |
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from fastapi.responses import StreamingResponse |
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from fastapi.background import BackgroundTasks |
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import requests |
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from curl_cffi import requests as cffi_requests |
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import uuid |
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import json |
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import time |
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from typing import Optional |
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import asyncio |
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import base64 |
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import tempfile |
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import os |
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import re |
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app = FastAPI() |
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security = HTTPBearer() |
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", None) |
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global_data = { |
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"cookie": None, |
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"cookies": None, |
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"last_update": 0 |
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} |
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def get_cookie(): |
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try: |
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response = cffi_requests.get( |
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'https://chat.akash.network/', |
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impersonate="chrome110", |
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timeout=30 |
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) |
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cookies = response.cookies.items() |
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if cookies: |
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cookie_str = '; '.join([f'{k}={v}' for k, v in cookies]) |
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global_data["cookie"] = cookie_str |
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global_data["last_update"] = time.time() |
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print(f"Got cookies: {cookie_str}") |
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return cookie_str |
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except Exception as e: |
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print(f"Error fetching cookie: {e}") |
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return None |
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async def check_and_update_cookie(background_tasks: BackgroundTasks): |
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if time.time() - global_data["last_update"] > 1800: |
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background_tasks.add_task(get_cookie) |
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@app.on_event("startup") |
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async def startup_event(): |
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get_cookie() |
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async def get_api_key(credentials: HTTPAuthorizationCredentials = Depends(security)): |
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token = credentials.credentials |
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if OPENAI_API_KEY is not None: |
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clean_token = token.replace("Bearer ", "") if token.startswith("Bearer ") else token |
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if clean_token != OPENAI_API_KEY: |
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raise HTTPException( |
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status_code=401, |
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detail="Invalid API key" |
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) |
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return token.replace("Bearer ", "") if token.startswith("Bearer ") else token |
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async def check_image_status(session: requests.Session, job_id: str, headers: dict) -> Optional[str]: |
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"""检查图片生成状态并获取生成的图片""" |
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max_retries = 30 |
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for attempt in range(max_retries): |
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try: |
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print(f"\nAttempt {attempt + 1}/{max_retries} for job {job_id}") |
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response = session.get( |
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f'https://chat.akash.network/api/image-status?ids={job_id}', |
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headers=headers |
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) |
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print(f"Status response code: {response.status_code}") |
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status_data = response.json() |
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if status_data and isinstance(status_data, list) and len(status_data) > 0: |
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job_info = status_data[0] |
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status = job_info.get('status') |
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print(f"Job status: {status}") |
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if status == "completed": |
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result = job_info.get("result") |
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if result and not result.startswith("Failed"): |
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print("Got valid result, attempting upload...") |
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image_url = await upload_to_xinyew(result, job_id) |
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if image_url: |
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print(f"Successfully uploaded image: {image_url}") |
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return image_url |
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print("Image upload failed") |
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return None |
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print("Invalid result received") |
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return None |
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elif status == "failed": |
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print(f"Job {job_id} failed") |
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return None |
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await asyncio.sleep(1) |
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continue |
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except Exception as e: |
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print(f"Error checking status: {e}") |
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return None |
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print(f"Timeout waiting for job {job_id}") |
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return None |
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@app.get("/") |
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async def health_check(): |
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"""Health check endpoint""" |
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return {"status": "ok"} |
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@app.post("/v1/chat/completions") |
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async def chat_completions( |
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request: Request, |
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api_key: str = Depends(get_api_key) |
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): |
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try: |
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data = await request.json() |
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print(f"Chat request data: {data}") |
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chat_id = str(uuid.uuid4()).replace('-', '')[:16] |
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akash_data = { |
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"id": chat_id, |
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"messages": data.get('messages', []), |
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"model": data.get('model', "DeepSeek-R1"), |
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"system": data.get('system_message', "You are a helpful assistant."), |
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"temperature": data.get('temperature', 0.6), |
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"topP": data.get('top_p', 0.95) |
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} |
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headers = { |
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"Content-Type": "application/json", |
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"Cookie": f"session_token={api_key}", |
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"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", |
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"Accept": "*/*", |
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"Accept-Language": "zh-CN,zh;q=0.9,en-US;q=0.8,en;q=0.7", |
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"Accept-Encoding": "gzip, deflate, br", |
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"Origin": "https://chat.akash.network", |
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"Referer": "https://chat.akash.network/", |
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"Sec-Fetch-Dest": "empty", |
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"Sec-Fetch-Mode": "cors", |
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"Sec-Fetch-Site": "same-origin", |
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"Connection": "keep-alive", |
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"Priority": "u=1, i" |
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} |
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print(f"Sending request to Akash with headers: {headers}") |
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print(f"Request data: {akash_data}") |
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with requests.Session() as session: |
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response = session.post( |
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'https://chat.akash.network/api/chat', |
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json=akash_data, |
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headers=headers, |
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stream=True |
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) |
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def generate(): |
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content_buffer = "" |
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for line in response.iter_lines(): |
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if not line: |
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continue |
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try: |
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line_str = line.decode('utf-8') |
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msg_type, msg_data = line_str.split(':', 1) |
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if msg_type == '0': |
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if msg_data.startswith('"') and msg_data.endswith('"'): |
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msg_data = msg_data.replace('\\"', '"') |
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msg_data = msg_data[1:-1] |
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msg_data = msg_data.replace("\\n", "\n") |
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if data.get('model') == 'AkashGen' and "<image_generation>" in msg_data: |
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async def process_and_send(): |
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end_msg = await process_image_generation(msg_data, session, headers, chat_id) |
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if end_msg: |
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chunk = { |
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"id": f"chatcmpl-{chat_id}", |
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"object": "chat.completion.chunk", |
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"created": int(time.time()), |
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"model": data.get('model'), |
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"choices": [{ |
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"delta": {"content": end_msg}, |
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"index": 0, |
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"finish_reason": None |
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}] |
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} |
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return f"data: {json.dumps(chunk)}\n\n" |
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return None |
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loop = asyncio.new_event_loop() |
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asyncio.set_event_loop(loop) |
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try: |
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result = loop.run_until_complete(process_and_send()) |
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finally: |
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loop.close() |
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if result: |
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yield result |
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continue |
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content_buffer += msg_data |
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chunk = { |
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"id": f"chatcmpl-{chat_id}", |
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"object": "chat.completion.chunk", |
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"created": int(time.time()), |
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"model": data.get('model'), |
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"choices": [{ |
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"delta": {"content": msg_data}, |
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"index": 0, |
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"finish_reason": None |
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}] |
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} |
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yield f"data: {json.dumps(chunk)}\n\n" |
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elif msg_type in ['e', 'd']: |
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chunk = { |
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"id": f"chatcmpl-{chat_id}", |
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"object": "chat.completion.chunk", |
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"created": int(time.time()), |
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"model": data.get('model'), |
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"choices": [{ |
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"delta": {}, |
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"index": 0, |
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"finish_reason": "stop" |
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}] |
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} |
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yield f"data: {json.dumps(chunk)}\n\n" |
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yield "data: [DONE]\n\n" |
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break |
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except Exception as e: |
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print(f"Error processing line: {e}") |
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continue |
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return StreamingResponse( |
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generate(), |
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media_type='text/event-stream', |
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headers={ |
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'Cache-Control': 'no-cache', |
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'Connection': 'keep-alive', |
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'Content-Type': 'text/event-stream' |
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} |
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) |
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except Exception as e: |
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return {"error": str(e)} |
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@app.get("/v1/models") |
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async def list_models(api_key: str = Depends(get_api_key)): |
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try: |
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headers = { |
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"Content-Type": "application/json", |
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"Cookie": f"session_token={api_key}", |
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"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", |
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"Accept": "*/*", |
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"Accept-Language": "zh-CN,zh;q=0.9,en-US;q=0.8,en;q=0.7", |
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"Accept-Encoding": "gzip, deflate, br", |
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"Origin": "https://chat.akash.network", |
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"Referer": "https://chat.akash.network/", |
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"Sec-Fetch-Dest": "empty", |
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"Sec-Fetch-Mode": "cors", |
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"Sec-Fetch-Site": "same-origin", |
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"Connection": "keep-alive" |
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} |
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response = requests.get( |
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'https://chat.akash.network/api/models', |
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headers=headers |
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) |
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akash_response = response.json() |
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openai_models = { |
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"object": "list", |
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"data": [ |
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{ |
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"id": model["id"], |
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"object": "model", |
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"created": int(time.time()), |
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"owned_by": "akash", |
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"permission": [{ |
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"id": "modelperm-" + model["id"], |
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"object": "model_permission", |
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"created": int(time.time()), |
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"allow_create_engine": False, |
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"allow_sampling": True, |
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"allow_logprobs": True, |
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"allow_search_indices": False, |
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"allow_view": True, |
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"allow_fine_tuning": False, |
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"organization": "*", |
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"group": None, |
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"is_blocking": False |
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}] |
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} for model in akash_response.get("models", []) |
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] |
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} |
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return openai_models |
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except Exception as e: |
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print(f"Error in list_models: {e}") |
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return {"error": str(e)} |
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async def upload_to_xinyew(image_base64: str, job_id: str) -> Optional[str]: |
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"""上传图片到新野图床并返回URL""" |
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try: |
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print(f"\n=== Starting image upload for job {job_id} ===") |
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print(f"Base64 data length: {len(image_base64)}") |
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try: |
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image_data = base64.b64decode(image_base64.split(',')[1] if ',' in image_base64 else image_base64) |
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print(f"Decoded image data length: {len(image_data)} bytes") |
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except Exception as e: |
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print(f"Error decoding base64: {e}") |
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print(f"First 100 chars of base64: {image_base64[:100]}...") |
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return None |
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with tempfile.NamedTemporaryFile(suffix='.jpeg', delete=False) as temp_file: |
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temp_file.write(image_data) |
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temp_file_path = temp_file.name |
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try: |
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filename = f"{job_id}.jpeg" |
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print(f"Using filename: {filename}") |
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files = { |
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'file': (filename, open(temp_file_path, 'rb'), 'image/jpeg') |
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} |
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print("Sending request to xinyew.cn...") |
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response = requests.post( |
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'https://api.xinyew.cn/api/jdtc', |
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files=files, |
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timeout=30 |
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) |
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print(f"Upload response status: {response.status_code}") |
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if response.status_code == 200: |
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result = response.json() |
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print(f"Upload response: {result}") |
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if result.get('errno') == 0: |
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url = result.get('data', {}).get('url') |
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if url: |
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print(f"Successfully got image URL: {url}") |
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return url |
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print("No URL in response data") |
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else: |
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print(f"Upload failed: {result.get('message')}") |
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else: |
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print(f"Upload failed with status {response.status_code}") |
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print(f"Response content: {response.text}") |
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return None |
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finally: |
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try: |
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os.unlink(temp_file_path) |
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except Exception as e: |
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print(f"Error removing temp file: {e}") |
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except Exception as e: |
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print(f"Error in upload_to_xinyew: {e}") |
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import traceback |
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print(traceback.format_exc()) |
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return None |
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async def process_image_generation(msg_data: str, session: requests.Session, headers: dict, chat_id: str) -> str: |
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"""处理图片生成的逻辑""" |
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match = re.search(r"jobId='([^']+)' prompt='([^']+)' negative='([^']*)'", msg_data) |
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if match: |
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job_id, prompt, negative = match.groups() |
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print(f"Starting image generation process for job_id: {job_id}") |
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start_time = time.time() |
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end_msg = "<think>\n" |
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end_msg += "🎨 Generating image...\n\n" |
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end_msg += f"Prompt: {prompt}\n" |
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result = await check_image_status(session, job_id, headers) |
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elapsed_time = time.time() - start_time |
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end_msg += f"\n🤔 Thinking for {elapsed_time:.1f}s...\n" |
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end_msg += "</think>\n\n" |
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if result: |
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end_msg += f"" |
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else: |
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end_msg += "*Image generation or upload failed.*\n" |
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return end_msg |
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return "" |
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if __name__ == '__main__': |
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import uvicorn |
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uvicorn.run(app, host='0.0.0.0', port=9000) |