soraapi / src /app.py.backup
anycallzhf's picture
Initial commit for Hugging Face Space deployment
b064311
import asyncio
import json
import time
import uuid
import base64
import os
import tempfile
import threading
import dotenv
import logging
from typing import List, Dict, Any, Optional, Union
from fastapi import FastAPI, HTTPException, Depends, Request, BackgroundTasks, File, UploadFile, Form
from fastapi.responses import StreamingResponse, JSONResponse, FileResponse, HTMLResponse
from fastapi.middleware.cors import CORSMiddleware
from fastapi.staticfiles import StaticFiles
from pydantic import BaseModel, Field
import uvicorn
import re
from .key_manager import KeyManager
from .sora_integration import SoraClient
from .config import Config
from .utils import localize_image_urls # 导入新增的图片本地化功能
# 日志系统配置
class LogConfig:
LEVEL = os.getenv("LOG_LEVEL", "WARNING").upper()
FORMAT = "%(asctime)s [%(levelname)s] %(message)s"
# 初始化日志
logging.basicConfig(
level=getattr(logging, LogConfig.LEVEL),
format=LogConfig.FORMAT,
datefmt="%Y-%m-%d %H:%M:%S"
)
logger = logging.getLogger("sora-api")
# 打印日志级别信息
logger.info(f"日志级别设置为: {LogConfig.LEVEL}")
logger.info(f"要调整日志级别,请设置环境变量 LOG_LEVEL=DEBUG|INFO|WARNING|ERROR")
# 创建FastAPI应用
app = FastAPI(title="OpenAI Compatible Sora API")
# 添加CORS支持
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# 确保静态文件目录存在
os.makedirs(os.path.join(Config.STATIC_DIR, "admin"), exist_ok=True)
os.makedirs(os.path.join(Config.STATIC_DIR, "admin/js"), exist_ok=True)
os.makedirs(os.path.join(Config.STATIC_DIR, "admin/css"), exist_ok=True)
os.makedirs(os.path.join(Config.STATIC_DIR, "images"), exist_ok=True) # 确保图片目录存在
# 打印配置信息
Config.print_config()
# 挂载静态文件目录
app.mount("/static", StaticFiles(directory=Config.STATIC_DIR), name="static")
# 初始化Key管理器
key_manager = KeyManager(storage_file=Config.KEYS_STORAGE_FILE)
# 初始化时保存管理员密钥
Config.save_admin_key()
# 创建Sora客户端池
sora_clients = {}
# 存储生成结果的全局字典
generation_results = {}
# 请求模型
class ContentItem(BaseModel):
type: str
text: Optional[str] = None
image_url: Optional[Dict[str, str]] = None
class ChatMessage(BaseModel):
role: str
content: Union[str, List[ContentItem]]
class ChatCompletionRequest(BaseModel):
model: str
messages: List[ChatMessage]
temperature: Optional[float] = 1.0
top_p: Optional[float] = 1.0
n: Optional[int] = 1
stream: Optional[bool] = False
max_tokens: Optional[int] = None
presence_penalty: Optional[float] = 0
frequency_penalty: Optional[float] = 0
# API密钥管理模型
class ApiKeyCreate(BaseModel):
name: str = Field(..., description="密钥名称")
key_value: str = Field(..., description="Bearer Token值")
weight: int = Field(default=1, ge=1, le=10, description="权重值")
rate_limit: int = Field(default=60, description="每分钟最大请求数")
is_enabled: bool = Field(default=True, description="是否启用")
notes: Optional[str] = Field(default=None, description="备注信息")
class ApiKeyUpdate(BaseModel):
name: Optional[str] = None
key_value: Optional[str] = None
weight: Optional[int] = None
rate_limit: Optional[int] = None
is_enabled: Optional[bool] = None
notes: Optional[str] = None
# 获取Sora客户端
def get_sora_client(auth_token: str) -> SoraClient:
if auth_token not in sora_clients:
proxy_host = Config.PROXY_HOST if Config.PROXY_HOST and Config.PROXY_HOST.strip() else None
proxy_port = Config.PROXY_PORT if Config.PROXY_PORT and Config.PROXY_PORT.strip() else None
sora_clients[auth_token] = SoraClient(
proxy_host=proxy_host,
proxy_port=proxy_port,
auth_token=auth_token
)
return sora_clients[auth_token]
# 验证API key
async def verify_api_key(request: Request):
auth_header = request.headers.get("Authorization")
if not auth_header or not auth_header.startswith("Bearer "):
raise HTTPException(status_code=401, detail="缺少或无效的API key")
api_key = auth_header.replace("Bearer ", "")
# 在实际应用中,这里应该验证key的有效性
# 这里简化处理,假设所有key都有效
return api_key
# 验证管理员权限
async def verify_admin(request: Request):
auth_header = request.headers.get("Authorization")
if not auth_header or not auth_header.startswith("Bearer "):
raise HTTPException(status_code=401, detail="未授权")
admin_key = auth_header.replace("Bearer ", "")
# 这里应该检查是否为管理员密钥
# 简化处理,假设admin_key是预设的管理员密钥
if admin_key != Config.ADMIN_KEY:
raise HTTPException(status_code=403, detail="没有管理员权限")
return admin_key
# 将处理中状态消息格式化为think代码块
def format_think_block(message):
"""将消息放入```think代码块中"""
return f"```think\n{message}\n```"
# 后台任务处理函数 - 文本生成图像
async def process_image_generation(
request_id: str,
sora_client: SoraClient,
prompt: str,
num_images: int = 1,
width: int = 720,
height: int = 480
):
try:
# 更新状态为生成中
generation_results[request_id] = {
"status": "processing",
"message": format_think_block("正在生成图像中,请耐心等待..."),
"timestamp": int(time.time())
}
# 生成图像
logger.info(f"[{request_id}] 开始生成图像, 提示词: {prompt}")
image_urls = await sora_client.generate_image(
prompt=prompt,
num_images=num_images,
width=width,
height=height
)
# 验证生成结果
if isinstance(image_urls, str):
logger.warning(f"[{request_id}] 图像生成失败或返回了错误信息: {image_urls}")
generation_results[request_id] = {
"status": "failed",
"error": image_urls,
"message": format_think_block(f"图像生成失败: {image_urls}"),
"timestamp": int(time.time())
}
return
if not image_urls:
logger.warning(f"[{request_id}] 图像生成返回了空列表")
generation_results[request_id] = {
"status": "failed",
"error": "图像生成返回了空结果",
"message": format_think_block("图像生成失败: 服务器返回了空结果"),
"timestamp": int(time.time())
}
return
logger.info(f"[{request_id}] 成功生成 {len(image_urls)} 张图片")
if logger.isEnabledFor(logging.DEBUG):
for i, url in enumerate(image_urls):
logger.debug(f"[{request_id}] 图片 {i+1}: {url}")
# 本地化图片URL
if Config.IMAGE_LOCALIZATION:
logger.info(f"[{request_id}] 准备进行图片本地化处理")
logger.debug(f"[{request_id}] 图片本地化配置: 启用={Config.IMAGE_LOCALIZATION}, 保存目录={Config.IMAGE_SAVE_DIR}")
try:
localized_urls = await localize_image_urls(image_urls)
logger.info(f"[{request_id}] 图片本地化处理完成")
# 检查本地化结果
if not localized_urls:
logger.warning(f"[{request_id}] 本地化处理返回了空列表,将使用原始URL")
localized_urls = image_urls
# 检查是否所有URL都被正确本地化
local_count = sum(1 for url in localized_urls if url.startswith("/static/") or "/static/" in url)
logger.info(f"[{request_id}] 本地化结果: 总计 {len(localized_urls)} 张图片,成功本地化 {local_count} 张")
if local_count == 0:
logger.warning(f"[{request_id}] 警告:没有一个URL被成功本地化,将使用原始URL")
localized_urls = image_urls
# 打印结果对比
if logger.isEnabledFor(logging.DEBUG):
for i, (orig, local) in enumerate(zip(image_urls, localized_urls)):
logger.debug(f"[{request_id}] 图片 {i+1} 本地化结果: {orig} -> {local}")
image_urls = localized_urls
except Exception as e:
logger.error(f"[{request_id}] 图片本地化过程中发生错误: {str(e)}")
if logger.isEnabledFor(logging.DEBUG):
import traceback
logger.debug(traceback.format_exc())
logger.info(f"[{request_id}] 由于错误,将使用原始URL")
else:
logger.info(f"[{request_id}] 图片本地化功能未启用,使用原始URL")
# 存储结果
generation_results[request_id] = {
"status": "completed",
"image_urls": image_urls,
"timestamp": int(time.time())
}
# 30分钟后自动清理结果
threading.Timer(1800, lambda: generation_results.pop(request_id, None)).start()
except Exception as e:
error_message = f"图像生成失败: {str(e)}"
generation_results[request_id] = {
"status": "failed",
"error": error_message,
"message": format_think_block(error_message),
"timestamp": int(time.time())
}
logger.error(f"图像生成失败 (ID: {request_id}): {str(e)}")
if logger.isEnabledFor(logging.DEBUG):
import traceback
logger.debug(traceback.format_exc())
# 后台任务处理函数 - 带图片的remix
async def process_image_remix(
request_id: str,
sora_client: SoraClient,
prompt: str,
image_data: str,
num_images: int = 1
):
try:
# 更新状态为处理中
generation_results[request_id] = {
"status": "processing",
"message": format_think_block("正在处理上传的图片..."),
"timestamp": int(time.time())
}
# 保存base64图片到临时文件
temp_dir = tempfile.mkdtemp()
temp_image_path = os.path.join(temp_dir, f"upload_{uuid.uuid4()}.png")
try:
# 解码并保存图片
with open(temp_image_path, "wb") as f:
f.write(base64.b64decode(image_data))
# 更新状态为上传中
generation_results[request_id] = {
"status": "processing",
"message": format_think_block("正在上传图片到Sora服务..."),
"timestamp": int(time.time())
}
# 上传图片
upload_result = await sora_client.upload_image(temp_image_path)
media_id = upload_result['id']
# 更新状态为生成中
generation_results[request_id] = {
"status": "processing",
"message": format_think_block("正在基于图片生成新图像..."),
"timestamp": int(time.time())
}
# 执行remix生成
logger.info(f"[{request_id}] 开始生成Remix图像, 提示词: {prompt}")
image_urls = await sora_client.generate_image_remix(
prompt=prompt,
media_id=media_id,
num_images=num_images
)
# 本地化图片URL
if Config.IMAGE_LOCALIZATION:
logger.info(f"[{request_id}] 准备进行图片本地化处理")
localized_urls = await localize_image_urls(image_urls)
image_urls = localized_urls
logger.info(f"[{request_id}] Remix图片本地化处理完成")
# 存储结果
generation_results[request_id] = {
"status": "completed",
"image_urls": image_urls,
"timestamp": int(time.time())
}
# 30分钟后自动清理结果
threading.Timer(1800, lambda: generation_results.pop(request_id, None)).start()
finally:
# 清理临时文件
if os.path.exists(temp_image_path):
os.remove(temp_image_path)
if os.path.exists(temp_dir):
os.rmdir(temp_dir)
except Exception as e:
error_message = f"图像Remix失败: {str(e)}"
generation_results[request_id] = {
"status": "failed",
"error": error_message,
"message": format_think_block(error_message),
"timestamp": int(time.time())
}
logger.error(f"图像Remix失败 (ID: {request_id}): {str(e)}")
# 添加一个新端点用于检查生成状态
@app.get("/v1/generation/{request_id}")
async def check_generation_status(request_id: str, api_key: str = Depends(verify_api_key)):
"""
检查图像生成任务的状态
"""
# 获取一个可用的key并记录开始时间
sora_auth_token = key_manager.get_key()
if not sora_auth_token:
raise HTTPException(status_code=429, detail="所有API key都已达到速率限制")
start_time = time.time()
success = False
try:
if request_id not in generation_results:
raise HTTPException(status_code=404, detail=f"找不到生成任务: {request_id}")
result = generation_results[request_id]
if result["status"] == "completed":
image_urls = result["image_urls"]
# 构建OpenAI兼容的响应
response = {
"id": request_id,
"object": "chat.completion",
"created": result["timestamp"],
"model": "sora-1.0",
"choices": [
{
"index": i,
"message": {
"role": "assistant",
"content": f"![Generated Image]({url})"
},
"finish_reason": "stop"
}
for i, url in enumerate(image_urls)
],
"usage": {
"prompt_tokens": 0, # 简化的令牌计算
"completion_tokens": 20,
"total_tokens": 20
}
}
success = True
return JSONResponse(content=response)
elif result["status"] == "failed":
if "message" in result:
# 返回带有格式化错误消息的响应
response = {
"id": request_id,
"object": "chat.completion",
"created": result["timestamp"],
"model": "sora-1.0",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": result["message"]
},
"finish_reason": "error"
}
],
"usage": {
"prompt_tokens": 0,
"completion_tokens": 10,
"total_tokens": 10
}
}
success = False
return JSONResponse(content=response)
else:
# 向后兼容,使用老的方式
raise HTTPException(status_code=500, detail=f"生成失败: {result['error']}")
else: # 处理中
message = result.get("message", "```think\n正在生成图像,请稍候...\n```")
response = {
"id": request_id,
"object": "chat.completion",
"created": result["timestamp"],
"model": "sora-1.0",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": message
},
"finish_reason": "processing"
}
],
"usage": {
"prompt_tokens": 0,
"completion_tokens": 10,
"total_tokens": 10
}
}
success = True
return JSONResponse(content=response)
except Exception as e:
success = False
raise HTTPException(status_code=500, detail=f"检查任务状态失败: {str(e)}")
finally:
# 记录请求结果
response_time = time.time() - start_time
key_manager.record_request_result(sora_auth_token, success, response_time)
# 聊天完成端点
@app.post("/v1/chat/completions")
async def chat_completions(
request: ChatCompletionRequest,
api_key: str = Depends(verify_api_key),
background_tasks: BackgroundTasks = None
):
# 获取一个可用的key
sora_auth_token = key_manager.get_key()
if not sora_auth_token:
raise HTTPException(status_code=429, detail="所有API key都已达到速率限制")
# 获取Sora客户端
sora_client = get_sora_client(sora_auth_token)
# 分析最后一条用户消息以提取内容
user_messages = [m for m in request.messages if m.role == "user"]
if not user_messages:
raise HTTPException(status_code=400, detail="至少需要一条用户消息")
last_user_message = user_messages[-1]
prompt = ""
image_data = None
# 提取提示词和图片数据
if isinstance(last_user_message.content, str):
# 简单的字符串内容
prompt = last_user_message.content
# 检查是否包含内嵌的base64图片
pattern = r'data:image\/[^;]+;base64,([^"]+)'
match = re.search(pattern, prompt)
if match:
image_data = match.group(1)
# 从提示词中删除base64数据,以保持提示词的可读性
prompt = re.sub(pattern, "[已上传图片]", prompt)
else:
# 多模态内容,提取文本和图片
content_items = last_user_message.content
text_parts = []
for item in content_items:
if item.type == "text" and item.text:
text_parts.append(item.text)
elif item.type == "image_url" and item.image_url:
# 如果有图片URL包含base64数据
url = item.image_url.get("url", "")
if url.startswith("data:image/"):
pattern = r'data:image\/[^;]+;base64,([^"]+)'
match = re.search(pattern, url)
if match:
image_data = match.group(1)
text_parts.append("[已上传图片]")
prompt = " ".join(text_parts)
# 记录开始时间
start_time = time.time()
success = False
# 处理图片生成
try:
# 检查是否为流式响应
if request.stream:
# 流式响应特殊处理文本+图片的情况
if image_data:
response = StreamingResponse(
generate_streaming_remix_response(sora_client, prompt, image_data, request.n),
media_type="text/event-stream"
)
else:
response = StreamingResponse(
generate_streaming_response(sora_client, prompt, request.n),
media_type="text/event-stream"
)
success = True
# 记录请求结果(流式响应立即记录)
response_time = time.time() - start_time
key_manager.record_request_result(sora_auth_token, success, response_time)
return response
else:
# 对于非流式响应,返回一个即时响应,表示任务已接收
# 创建一个唯一ID
request_id = f"chatcmpl-{uuid.uuid4().hex}"
# 在结果字典中创建初始状态
processing_message = "正在准备生成任务,请稍候..."
generation_results[request_id] = {
"status": "processing",
"message": format_think_block(processing_message),
"timestamp": int(time.time())
}
# 添加后台任务
if image_data:
background_tasks.add_task(
process_image_remix,
request_id,
sora_client,
prompt,
image_data,
request.n
)
else:
background_tasks.add_task(
process_image_generation,
request_id,
sora_client,
prompt,
request.n,
720, # width
480 # height
)
# 立即返回一个"正在处理中"的响应
response = {
"id": request_id,
"object": "chat.completion",
"created": int(time.time()),
"model": "sora-1.0",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": format_think_block(processing_message)
},
"finish_reason": "processing"
}
],
"usage": {
"prompt_tokens": len(prompt) // 4,
"completion_tokens": 10,
"total_tokens": len(prompt) // 4 + 10
}
}
success = True
# 记录请求结果(非流式响应立即记录)
response_time = time.time() - start_time
key_manager.record_request_result(sora_auth_token, success, response_time)
return JSONResponse(content=response)
except Exception as e:
success = False
# 记录请求结果(异常情况也记录)
response_time = time.time() - start_time
key_manager.record_request_result(sora_auth_token, success, response_time)
raise HTTPException(status_code=500, detail=f"图像生成失败: {str(e)}")
# 流式响应生成器 - 普通文本到图像
async def generate_streaming_response(
sora_client: SoraClient,
prompt: str,
n_images: int = 1
):
request_id = f"chatcmpl-{uuid.uuid4().hex}"
# 发送开始事件
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'role': 'assistant'}, 'finish_reason': None}]})}\n\n"
# 发送处理中的消息(放在代码块中)
start_msg = "```think\n正在生成图像,请稍候...\n"
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'content': start_msg}, 'finish_reason': None}]})}\n\n"
# 创建一个后台任务来生成图像
logger.info(f"[流式响应 {request_id}] 开始生成图像, 提示词: {prompt}")
generation_task = asyncio.create_task(sora_client.generate_image(
prompt=prompt,
num_images=n_images,
width=720,
height=480
))
# 每5秒发送一条"仍在生成中"的消息,防止连接超时
progress_messages = [
"正在处理您的请求...",
"仍在生成图像中,请继续等待...",
"Sora正在创作您的图像作品...",
"图像生成需要一点时间,感谢您的耐心等待...",
"我们正在努力为您创作高质量图像..."
]
i = 0
while not generation_task.done():
# 每5秒发送一次进度消息
await asyncio.sleep(5)
progress_msg = progress_messages[i % len(progress_messages)]
i += 1
content = "\n" + progress_msg + "\n"
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'content': content}, 'finish_reason': None}]})}\n\n"
try:
# 获取生成结果
image_urls = await generation_task
logger.info(f"[流式响应 {request_id}] 图像生成完成,获取到 {len(image_urls) if isinstance(image_urls, list) else '非列表'} 个URL")
# 本地化图片URL
if Config.IMAGE_LOCALIZATION and isinstance(image_urls, list) and image_urls:
logger.info(f"[流式响应 {request_id}] 准备进行图片本地化处理")
try:
localized_urls = await localize_image_urls(image_urls)
logger.info(f"[流式响应 {request_id}] 图片本地化处理完成")
# 检查本地化结果
if not localized_urls:
logger.warning(f"[流式响应 {request_id}] 本地化处理返回了空列表,将使用原始URL")
localized_urls = image_urls
# 检查是否所有URL都被正确本地化
local_count = sum(1 for url in localized_urls if url.startswith("/static/") or "/static/" in url)
if local_count == 0:
logger.warning(f"[流式响应 {request_id}] 警告:没有一个URL被成功本地化,将使用原始URL")
localized_urls = image_urls
else:
logger.info(f"[流式响应 {request_id}] 成功本地化 {local_count}/{len(localized_urls)} 张图片")
# 打印本地化对比结果
if logger.isEnabledFor(logging.DEBUG):
for i, (orig, local) in enumerate(zip(image_urls, localized_urls)):
logger.debug(f"[流式响应 {request_id}] 图片 {i+1}: {orig} -> {local}")
image_urls = localized_urls
except Exception as e:
logger.error(f"[流式响应 {request_id}] 图片本地化过程中发生错误: {str(e)}")
if logger.isEnabledFor(logging.DEBUG):
import traceback
logger.debug(traceback.format_exc())
logger.info(f"[流式响应 {request_id}] 由于错误,将使用原始URL")
elif not Config.IMAGE_LOCALIZATION:
logger.info(f"[流式响应 {request_id}] 图片本地化功能未启用")
elif not isinstance(image_urls, list) or not image_urls:
logger.warning(f"[流式响应 {request_id}] 无法进行本地化: 图像结果不是有效的URL列表")
# 结束代码块
content_str = "\n```\n\n"
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'content': content_str}, 'finish_reason': None}]})}\n\n"
# 添加生成的图片URLs
for i, url in enumerate(image_urls):
if i > 0:
content_str = "\n\n"
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'content': content_str}, 'finish_reason': None}]})}\n\n"
image_markdown = f"![Generated Image]({url})"
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'content': image_markdown}, 'finish_reason': None}]})}\n\n"
# 发送完成事件
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {}, 'finish_reason': 'stop'}]})}\n\n"
# 发送结束标志
yield "data: [DONE]\n\n"
except Exception as e:
error_msg = f"图像生成失败: {str(e)}"
logger.error(f"[流式响应 {request_id}] 错误: {error_msg}")
if logger.isEnabledFor(logging.DEBUG):
import traceback
logger.debug(traceback.format_exc())
error_content = f"\n{error_msg}\n```"
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'content': error_content}, 'finish_reason': 'error'}]})}\n\n"
yield "data: [DONE]\n\n"
# 流式响应生成器 - 带图片的remix
async def generate_streaming_remix_response(
sora_client: SoraClient,
prompt: str,
image_data: str,
n_images: int = 1
):
request_id = f"chatcmpl-{uuid.uuid4().hex}"
# 发送开始事件
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'role': 'assistant'}, 'finish_reason': None}]})}\n\n"
try:
# 保存base64图片到临时文件
temp_dir = tempfile.mkdtemp()
temp_image_path = os.path.join(temp_dir, f"upload_{uuid.uuid4()}.png")
try:
# 解码并保存图片
with open(temp_image_path, "wb") as f:
f.write(base64.b64decode(image_data))
# 上传图片
upload_msg = "```think\n上传图片中...\n"
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'content': upload_msg}, 'finish_reason': None}]})}\n\n"
logger.info(f"[流式响应Remix {request_id}] 上传图片中")
upload_result = await sora_client.upload_image(temp_image_path)
media_id = upload_result['id']
# 发送生成中消息
generate_msg = "\n基于图片生成新图像中...\n"
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'content': generate_msg}, 'finish_reason': None}]})}\n\n"
# 创建一个后台任务来生成图像
logger.info(f"[流式响应Remix {request_id}] 开始生成图像,提示词: {prompt}")
generation_task = asyncio.create_task(sora_client.generate_image_remix(
prompt=prompt,
media_id=media_id,
num_images=n_images
))
# 每5秒发送一条"仍在生成中"的消息,防止连接超时
progress_messages = [
"正在处理您的请求...",
"仍在生成图像中,请继续等待...",
"Sora正在基于您的图片创作新作品...",
"图像生成需要一点时间,感谢您的耐心等待...",
"正在努力融合您的风格和提示词,打造专属图像..."
]
i = 0
while not generation_task.done():
# 每5秒发送一次进度消息
await asyncio.sleep(5)
progress_msg = progress_messages[i % len(progress_messages)]
i += 1
content = "\n" + progress_msg + "\n"
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'content': content}, 'finish_reason': None}]})}\n\n"
# 获取生成结果
image_urls = await generation_task
logger.info(f"[流式响应Remix {request_id}] 图像生成完成")
# 本地化图片URL
if Config.IMAGE_LOCALIZATION:
logger.info(f"[流式响应Remix {request_id}] 进行图片本地化处理")
localized_urls = await localize_image_urls(image_urls)
image_urls = localized_urls
logger.info(f"[流式响应Remix {request_id}] 图片本地化处理完成")
else:
logger.info(f"[流式响应Remix {request_id}] 图片本地化功能未启用")
# 结束代码块
content_str = "\n```\n\n"
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'content': content_str}, 'finish_reason': None}]})}\n\n"
# 发送图片URL作为Markdown
for i, url in enumerate(image_urls):
if i > 0:
newline_str = "\n\n"
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'content': newline_str}, 'finish_reason': None}]})}\n\n"
image_markdown = f"![Generated Image]({url})"
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'content': image_markdown}, 'finish_reason': None}]})}\n\n"
# 发送完成事件
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {}, 'finish_reason': 'stop'}]})}\n\n"
# 发送结束标志
yield "data: [DONE]\n\n"
finally:
# 清理临时文件
if os.path.exists(temp_image_path):
os.remove(temp_image_path)
if os.path.exists(temp_dir):
os.rmdir(temp_dir)
except Exception as e:
error_msg = f"图像Remix失败: {str(e)}"
logger.error(f"[流式响应Remix {request_id}] 错误: {error_msg}")
if logger.isEnabledFor(logging.DEBUG):
import traceback
logger.debug(traceback.format_exc())
error_content = f"\n{error_msg}\n```"
yield f"data: {json.dumps({'id': request_id, 'object': 'chat.completion.chunk', 'created': int(time.time()), 'model': 'sora-1.0', 'choices': [{'index': 0, 'delta': {'content': error_content}, 'finish_reason': 'error'}]})}\n\n"
# 结束流
yield "data: [DONE]\n\n"
# API密钥管理端点
@app.get("/api/keys")
async def get_all_keys(admin_key: str = Depends(verify_admin)):
"""获取所有API密钥"""
return key_manager.get_all_keys()
@app.get("/api/keys/{key_id}")
async def get_key(key_id: str, admin_key: str = Depends(verify_admin)):
"""获取单个API密钥详情"""
key = key_manager.get_key_by_id(key_id)
if not key:
raise HTTPException(status_code=404, detail="密钥不存在")
return key
@app.post("/api/keys")
async def create_key(key_data: ApiKeyCreate, admin_key: str = Depends(verify_admin)):
"""创建新API密钥"""
try:
# 确保密钥值包含 Bearer 前缀
key_value = key_data.key_value
if not key_value.startswith("Bearer "):
key_value = f"Bearer {key_value}"
new_key = key_manager.add_key(
key_value,
name=key_data.name,
weight=key_data.weight,
rate_limit=key_data.rate_limit,
is_enabled=key_data.is_enabled,
notes=key_data.notes
)
# 通过Config永久保存所有密钥
Config.save_api_keys(key_manager.keys)
return new_key
except Exception as e:
raise HTTPException(status_code=400, detail=str(e))
@app.put("/api/keys/{key_id}")
async def update_key(key_id: str, key_data: ApiKeyUpdate, admin_key: str = Depends(verify_admin)):
"""更新API密钥信息"""
try:
# 如果提供了新的密钥值,确保包含Bearer前缀
key_value = key_data.key_value
if key_value and not key_value.startswith("Bearer "):
key_value = f"Bearer {key_value}"
key_data.key_value = key_value
updated_key = key_manager.update_key(
key_id,
key_value=key_data.key_value,
name=key_data.name,
weight=key_data.weight,
rate_limit=key_data.rate_limit,
is_enabled=key_data.is_enabled,
notes=key_data.notes
)
if not updated_key:
raise HTTPException(status_code=404, detail="密钥不存在")
# 通过Config永久保存所有密钥
Config.save_api_keys(key_manager.keys)
return updated_key
except Exception as e:
raise HTTPException(status_code=400, detail=str(e))
@app.delete("/api/keys/{key_id}")
async def delete_key(key_id: str, admin_key: str = Depends(verify_admin)):
"""删除API密钥"""
success = key_manager.delete_key(key_id)
if not success:
raise HTTPException(status_code=404, detail="密钥不存在")
# 通过Config永久保存所有密钥
Config.save_api_keys(key_manager.keys)
return {"status": "success", "message": "密钥已删除"}
@app.get("/api/stats")
async def get_usage_stats(admin_key: str = Depends(verify_admin)):
"""获取API使用统计"""
return key_manager.get_usage_stats()
@app.post("/api/keys/test")
async def test_key(key_data: ApiKeyCreate, admin_key: str = Depends(verify_admin)):
"""测试API密钥是否有效"""
try:
# 确保密钥值包含 Bearer 前缀
key_value = key_data.key_value
if not key_value.startswith("Bearer "):
key_value = f"Bearer {key_value}"
# 获取代理配置
proxy_host = Config.PROXY_HOST if Config.PROXY_HOST and Config.PROXY_HOST.strip() else None
proxy_port = Config.PROXY_PORT if Config.PROXY_PORT and Config.PROXY_PORT.strip() else None
# 创建临时客户端测试连接
test_client = SoraClient(
proxy_host=proxy_host,
proxy_port=proxy_port,
auth_token=key_value
)
# 执行简单API调用测试连接
test_result = await test_client.test_connection()
return {"status": "success", "message": "API密钥测试成功", "details": test_result}
except Exception as e:
return {"status": "error", "message": f"API密钥测试失败: {str(e)}"}
@app.post("/api/keys/batch")
async def batch_operation(operation: Dict[str, Any], admin_key: str = Depends(verify_admin)):
"""批量操作API密钥"""
action = operation.get("action")
key_ids = operation.get("key_ids", [])
if not action or not key_ids:
raise HTTPException(status_code=400, detail="无效的请求参数")
# 确保key_ids是一个列表
if isinstance(key_ids, str):
key_ids = [key_ids]
results = {}
if action == "enable":
for key_id in key_ids:
success = key_manager.update_key(key_id, is_enabled=True)
results[key_id] = "success" if success else "failed"
elif action == "disable":
for key_id in key_ids:
success = key_manager.update_key(key_id, is_enabled=False)
results[key_id] = "success" if success else "failed"
elif action == "delete":
for key_id in key_ids:
success = key_manager.delete_key(key_id)
results[key_id] = "success" if success else "failed"
else:
raise HTTPException(status_code=400, detail="不支持的操作类型")
# 通过Config永久保存所有密钥
Config.save_api_keys(key_manager.keys)
return {"status": "success", "results": results}
# 健康检查端点
@app.get("/health")
async def health_check():
return {"status": "ok", "timestamp": time.time()}
# 管理界面路由
@app.get("/admin")
async def admin_panel():
return FileResponse(os.path.join(Config.STATIC_DIR, "admin/index.html"))
# 管理员密钥API
@app.get("/admin/key")
async def admin_key():
return {"admin_key": Config.ADMIN_KEY}
# 挂载静态文件
app.mount("/admin", StaticFiles(directory=os.path.join(Config.STATIC_DIR, "admin"), html=True), name="admin")
# 配置管理模型
class ConfigUpdate(BaseModel):
IMAGE_LOCALIZATION: Optional[bool] = None
IMAGE_SAVE_DIR: Optional[str] = None
LOG_LEVEL: Optional[str] = None
# 配置管理页面
@app.get("/admin/config")
async def config_panel():
return FileResponse("src/static/admin/config.html")
# 获取当前配置
@app.get("/api/config")
async def get_config(admin_key: str = Depends(verify_admin)):
"""获取当前系统配置"""
return {
"IMAGE_LOCALIZATION": Config.IMAGE_LOCALIZATION,
"IMAGE_SAVE_DIR": Config.IMAGE_SAVE_DIR,
"LOG_LEVEL": LogConfig.LEVEL
}
# 更新配置
@app.post("/api/config")
async def update_config(config_data: ConfigUpdate, admin_key: str = Depends(verify_admin)):
"""更新系统配置"""
changes = {}
if config_data.IMAGE_LOCALIZATION is not None:
old_value = Config.IMAGE_LOCALIZATION
Config.IMAGE_LOCALIZATION = config_data.IMAGE_LOCALIZATION
os.environ["IMAGE_LOCALIZATION"] = str(config_data.IMAGE_LOCALIZATION)
changes["IMAGE_LOCALIZATION"] = {
"old": old_value,
"new": Config.IMAGE_LOCALIZATION
}
if config_data.IMAGE_SAVE_DIR is not None:
old_value = Config.IMAGE_SAVE_DIR
Config.IMAGE_SAVE_DIR = config_data.IMAGE_SAVE_DIR
os.environ["IMAGE_SAVE_DIR"] = config_data.IMAGE_SAVE_DIR
# 确保目录存在
os.makedirs(Config.IMAGE_SAVE_DIR, exist_ok=True)
changes["IMAGE_SAVE_DIR"] = {
"old": old_value,
"new": Config.IMAGE_SAVE_DIR
}
if config_data.LOG_LEVEL is not None:
old_value = LogConfig.LEVEL
level = config_data.LOG_LEVEL.upper()
# 验证日志级别是否有效
valid_levels = ["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]
if level not in valid_levels:
raise HTTPException(status_code=400, detail=f"无效的日志级别,有效值:{', '.join(valid_levels)}")
# 更新日志级别
LogConfig.LEVEL = level
logging.getLogger("sora-api").setLevel(getattr(logging, level))
os.environ["LOG_LEVEL"] = level
changes["LOG_LEVEL"] = {
"old": old_value,
"new": level
}
logger.info(f"日志级别已更改为: {level}")
# 保存到.env文件以持久化配置
try:
dotenv_file = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), ".env")
# 读取现有.env文件
env_vars = {}
if os.path.exists(dotenv_file):
with open(dotenv_file, "r") as f:
for line in f:
if line.strip() and not line.startswith("#"):
key, value = line.strip().split("=", 1)
env_vars[key] = value
# 更新值
if config_data.IMAGE_LOCALIZATION is not None:
env_vars["IMAGE_LOCALIZATION"] = str(config_data.IMAGE_LOCALIZATION)
if config_data.IMAGE_SAVE_DIR is not None:
env_vars["IMAGE_SAVE_DIR"] = config_data.IMAGE_SAVE_DIR
if config_data.LOG_LEVEL is not None:
env_vars["LOG_LEVEL"] = config_data.LOG_LEVEL.upper()
# 写回文件
with open(dotenv_file, "w") as f:
for key, value in env_vars.items():
f.write(f"{key}={value}\n")
except Exception as e:
logger.error(f"保存配置到.env文件失败: {str(e)}")
return {
"success": True,
"message": "配置已更新",
"changes": changes
}
# 日志级别控制
class LogLevelUpdate(BaseModel):
level: str = Field(..., description="日志级别")
@app.post("/api/logs/level")
async def update_log_level(data: LogLevelUpdate, admin_key: str = Depends(verify_admin)):
"""更新系统日志级别"""
level = data.level.upper()
# 验证日志级别是否有效
valid_levels = ["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]
if level not in valid_levels:
raise HTTPException(status_code=400, detail=f"无效的日志级别,有效值:{', '.join(valid_levels)}")
# 更新日志级别
old_level = LogConfig.LEVEL
LogConfig.LEVEL = level
logging.getLogger("sora-api").setLevel(getattr(logging, level))
os.environ["LOG_LEVEL"] = level
# 记录变更
logger.info(f"日志级别已更改为: {level}")
# 更新.env文件
try:
dotenv_file = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), ".env")
# 读取现有.env文件
env_vars = {}
if os.path.exists(dotenv_file):
with open(dotenv_file, "r") as f:
for line in f:
if line.strip() and not line.startswith("#"):
key, value = line.strip().split("=", 1)
env_vars[key] = value
# 更新日志级别
env_vars["LOG_LEVEL"] = level
# 写回文件
with open(dotenv_file, "w") as f:
for key, value in env_vars.items():
f.write(f"{key}={value}\n")
except Exception as e:
logger.warning(f"保存日志级别到.env文件失败: {str(e)}")
return {
"success": True,
"message": f"日志级别已更改: {old_level} -> {level}"
}