| | 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(): |
| | 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 |
| |
|
| | |
| | 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'), |
| | "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) -> 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}") |
| | |
| | |
| | start_time = time.time() |
| | end_msg = "<think>\n" |
| | end_msg += "🎨 Generating image...\n\n" |
| | end_msg += f"Prompt: {prompt}\n" |
| | |
| | |
| | result = await check_image_status(session, job_id, headers) |
| | |
| | |
| | elapsed_time = time.time() - start_time |
| | end_msg += f"\n🤔 Thinking for {elapsed_time:.1f}s...\n" |
| | end_msg += "</think>\n\n" |
| | |
| | if result: |
| | 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) |