| 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 |
| 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 = os.getenv("OPENAI_API_KEY", None) |
|
|
| |
| global_data = { |
| "cookie": None, |
| "cookies": None, |
| "last_update": 0 |
| } |
|
|
| def get_cookie(): |
| try: |
| |
| response = cffi_requests.get( |
| 'https://chat.akash.network/', |
| impersonate="chrome110", |
| timeout=30 |
| ) |
| |
| |
| 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): |
| |
| if time.time() - global_data["last_update"] > 1800: |
| background_tasks.add_task(get_cookie) |
|
|
| @app.on_event("startup") |
| async def startup_event(): |
| get_cookie() |
|
|
| async def get_api_key(credentials: HTTPAuthorizationCredentials = Depends(security)): |
| token = credentials.credentials |
| |
| |
| if OPENAI_API_KEY is not None: |
| |
| 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" |
| ) |
| |
| |
| 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}") |
| |
| |
| 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 |
| |
| |
| 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 |
|
|
| @app.get("/") |
| async def health_check(): |
| """Health check endpoint""" |
| return {"status": "ok"} |
|
|
| @app.post("/v1/chat/completions") |
| 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") |
| |
| |
| if data.get('model') == 'AkashGen' and "<image_generation>" in msg_data: |
| |
| async def process_and_send(): |
| messages = await process_image_generation(msg_data, session, headers, chat_id) |
| if messages: |
| return messages |
| return None |
|
|
| |
| loop = asyncio.new_event_loop() |
| asyncio.set_event_loop(loop) |
| try: |
| result_messages = loop.run_until_complete(process_and_send()) |
| finally: |
| loop.close() |
| |
| if result_messages: |
| for message in result_messages: |
| yield f"data: {json.dumps(message)}\n\n" |
| 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'), |
| "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)} |
|
|
| @app.get("/v1/models") |
| 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() |
| |
| |
| print(f"Akash API response: {akash_response}") |
| |
| |
| models_list = [] |
| if isinstance(akash_response, list): |
| |
| models_list = akash_response |
| elif isinstance(akash_response, dict): |
| |
| models_list = akash_response.get("models", []) |
| else: |
| print(f"Unexpected response format: {type(akash_response)}") |
| models_list = [] |
| |
| |
| openai_models = { |
| "object": "list", |
| "data": [ |
| { |
| "id": model["id"] if isinstance(model, dict) else model, |
| "object": "model", |
| "created": int(time.time()), |
| "owned_by": "akash", |
| "permission": [{ |
| "id": f"modelperm-{model['id'] if isinstance(model, dict) else model}", |
| "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 models_list |
| ] |
| } |
| |
| return openai_models |
| |
| except Exception as e: |
| print(f"Error in list_models: {e}") |
| import traceback |
| print(traceback.format_exc()) |
| 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)}") |
| |
| |
| 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 |
| |
| |
| 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}") |
| |
| |
| 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: |
| |
| 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) -> Optional[list]: |
| """处理图片生成的逻辑,返回多个消息块""" |
| 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}") |
| |
| |
| start_time = time.time() |
| |
| |
| think_msg = "<think>\n" |
| think_msg += "🎨 Generating image...\n\n" |
| think_msg += f"Prompt: {prompt}\n" |
| |
| |
| result = await check_image_status(session, job_id, headers) |
| |
| |
| elapsed_time = time.time() - start_time |
| |
| |
| think_msg += f"\n🤔 Thinking for {elapsed_time:.1f}s...\n" |
| think_msg += "</think>" |
| |
| |
| messages = [] |
| |
| |
| messages.append({ |
| "id": f"chatcmpl-{chat_id}-think", |
| "object": "chat.completion.chunk", |
| "created": int(time.time()), |
| "model": "AkashGen", |
| "choices": [{ |
| "delta": {"content": think_msg}, |
| "index": 0, |
| "finish_reason": None |
| }] |
| }) |
| |
| |
| if result: |
| image_msg = f"\n\n" |
| messages.append({ |
| "id": f"chatcmpl-{chat_id}-image", |
| "object": "chat.completion.chunk", |
| "created": int(time.time()), |
| "model": "AkashGen", |
| "choices": [{ |
| "delta": {"content": image_msg}, |
| "index": 0, |
| "finish_reason": None |
| }] |
| }) |
| else: |
| fail_msg = "\n\n*Image generation or upload failed.*" |
| messages.append({ |
| "id": f"chatcmpl-{chat_id}-fail", |
| "object": "chat.completion.chunk", |
| "created": int(time.time()), |
| "model": "AkashGen", |
| "choices": [{ |
| "delta": {"content": fail_msg}, |
| "index": 0, |
| "finish_reason": None |
| }] |
| }) |
| |
| return messages |
| return None |
|
|
| if __name__ == '__main__': |
| import uvicorn |
| uvicorn.run(app, host='0.0.0.0', port=9000) |