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| from fastapi import Request | |
| from starlette.middleware.base import BaseHTTPMiddleware | |
| from app.config.config import settings | |
| from app.log.logger import get_main_logger | |
| import re | |
| logger = get_main_logger() | |
| class SmartRoutingMiddleware(BaseHTTPMiddleware): | |
| def __init__(self, app): | |
| super().__init__(app) | |
| # 简化的路由规则 - 直接根据检测结果路由 | |
| pass | |
| async def dispatch(self, request: Request, call_next): | |
| if not settings.URL_NORMALIZATION_ENABLED: | |
| return await call_next(request) | |
| logger.debug(f"request: {request}") | |
| original_path = str(request.url.path) | |
| method = request.method | |
| # 尝试修复URL | |
| fixed_path, fix_info = self.fix_request_url(original_path, method, request) | |
| if fixed_path != original_path: | |
| logger.info(f"URL fixed: {method} {original_path} → {fixed_path}") | |
| if fix_info: | |
| logger.debug(f"Fix details: {fix_info}") | |
| # 重写请求路径 | |
| request.scope["path"] = fixed_path | |
| request.scope["raw_path"] = fixed_path.encode() | |
| return await call_next(request) | |
| def fix_request_url(self, path: str, method: str, request: Request) -> tuple: | |
| """简化的URL修复逻辑""" | |
| # 首先检查是否已经是正确的格式，如果是则不处理 | |
| if self.is_already_correct_format(path): | |
| return path, None | |
| # 1. 最高优先级：包含generateContent → Gemini格式 | |
| if "generatecontent" in path.lower() or "v1beta/models" in path.lower(): | |
| return self.fix_gemini_by_operation(path, method, request) | |
| # 2. 第二优先级：包含/openai/ → OpenAI格式 | |
| if "/openai/" in path.lower(): | |
| return self.fix_openai_by_operation(path, method) | |
| # 3. 第三优先级：包含/v1/ → v1格式 | |
| if "/v1/" in path.lower(): | |
| return self.fix_v1_by_operation(path, method) | |
| # 4. 第四优先级：包含/chat/completions → chat功能 | |
| if "/chat/completions" in path.lower(): | |
| return "/v1/chat/completions", {"type": "v1_chat"} | |
| # 5. 默认：原样传递 | |
| return path, None | |
| def is_already_correct_format(self, path: str) -> bool: | |
| """检查是否已经是正确的API格式""" | |
| # 检查是否已经是正确的端点格式 | |
| correct_patterns = [ | |
| r"^/v1beta/models/[^/:]+:(generate|streamGenerate)Content$", # Gemini原生 | |
| r"^/gemini/v1beta/models/[^/:]+:(generate|streamGenerate)Content$", # Gemini带前缀 | |
| r"^/v1beta/models$", # Gemini模型列表 | |
| r"^/gemini/v1beta/models$", # Gemini带前缀的模型列表 | |
| r"^/v1/(chat/completions|models|embeddings|images/generations|audio/speech)$", # v1格式 | |
| r"^/openai/v1/(chat/completions|models|embeddings|images/generations|audio/speech)$", # OpenAI格式 | |
| r"^/hf/v1/(chat/completions|models|embeddings|images/generations|audio/speech)$", # HF格式 | |
| r"^/vertex-express/v1beta/models/[^/:]+:(generate|streamGenerate)Content$", # Vertex Express Gemini格式 | |
| r"^/vertex-express/v1beta/models$", # Vertex Express模型列表 | |
| r"^/vertex-express/v1/(chat/completions|models|embeddings|images/generations)$", # Vertex Express OpenAI格式 | |
| ] | |
| for pattern in correct_patterns: | |
| if re.match(pattern, path): | |
| return True | |
| return False | |
| def fix_gemini_by_operation( | |
| self, path: str, method: str, request: Request | |
| ) -> tuple: | |
| """根据Gemini操作修复，考虑端点偏好""" | |
| if method == "GET": | |
| return "/v1beta/models", { | |
| "role": "gemini_models", | |
| } | |
| # 提取模型名称 | |
| try: | |
| model_name = self.extract_model_name(path, request) | |
| except ValueError: | |
| # 无法提取模型名称，返回原路径不做处理 | |
| return path, None | |
| # 检测是否为流式请求 | |
| is_stream = self.detect_stream_request(path, request) | |
| # 检查是否有vertex-express偏好 | |
| if "/vertex-express/" in path.lower(): | |
| if is_stream: | |
| target_url = ( | |
| f"/vertex-express/v1beta/models/{model_name}:streamGenerateContent" | |
| ) | |
| else: | |
| target_url = ( | |
| f"/vertex-express/v1beta/models/{model_name}:generateContent" | |
| ) | |
| fix_info = { | |
| "rule": ( | |
| "vertex_express_generate" | |
| if not is_stream | |
| else "vertex_express_stream" | |
| ), | |
| "preference": "vertex_express_format", | |
| "is_stream": is_stream, | |
| "model": model_name, | |
| } | |
| else: | |
| # 标准Gemini端点 | |
| if is_stream: | |
| target_url = f"/v1beta/models/{model_name}:streamGenerateContent" | |
| else: | |
| target_url = f"/v1beta/models/{model_name}:generateContent" | |
| fix_info = { | |
| "rule": "gemini_generate" if not is_stream else "gemini_stream", | |
| "preference": "gemini_format", | |
| "is_stream": is_stream, | |
| "model": model_name, | |
| } | |
| return target_url, fix_info | |
| def fix_openai_by_operation(self, path: str, method: str) -> tuple: | |
| """根据操作类型修复OpenAI格式""" | |
| if method == "POST": | |
| if "chat" in path.lower() or "completion" in path.lower(): | |
| return "/openai/v1/chat/completions", {"type": "openai_chat"} | |
| elif "embedding" in path.lower(): | |
| return "/openai/v1/embeddings", {"type": "openai_embeddings"} | |
| elif "image" in path.lower(): | |
| return "/openai/v1/images/generations", {"type": "openai_images"} | |
| elif "audio" in path.lower(): | |
| return "/openai/v1/audio/speech", {"type": "openai_audio"} | |
| elif method == "GET": | |
| if "model" in path.lower(): | |
| return "/openai/v1/models", {"type": "openai_models"} | |
| return path, None | |
| def fix_v1_by_operation(self, path: str, method: str) -> tuple: | |
| """根据操作类型修复v1格式""" | |
| if method == "POST": | |
| if "chat" in path.lower() or "completion" in path.lower(): | |
| return "/v1/chat/completions", {"type": "v1_chat"} | |
| elif "embedding" in path.lower(): | |
| return "/v1/embeddings", {"type": "v1_embeddings"} | |
| elif "image" in path.lower(): | |
| return "/v1/images/generations", {"type": "v1_images"} | |
| elif "audio" in path.lower(): | |
| return "/v1/audio/speech", {"type": "v1_audio"} | |
| elif method == "GET": | |
| if "model" in path.lower(): | |
| return "/v1/models", {"type": "v1_models"} | |
| return path, None | |
| def detect_stream_request(self, path: str, request: Request) -> bool: | |
| """检测是否为流式请求""" | |
| # 1. 路径中包含stream关键词 | |
| if "stream" in path.lower(): | |
| return True | |
| # 2. 查询参数 | |
| if request.query_params.get("stream") == "true": | |
| return True | |
| return False | |
| def extract_model_name(self, path: str, request: Request) -> str: | |
| """从请求中提取模型名称，用于构建Gemini API URL""" | |
| # 1. 从请求体中提取 | |
| try: | |
| if hasattr(request, "_body") and request._body: | |
| import json | |
| body = json.loads(request._body.decode()) | |
| if "model" in body and body["model"]: | |
| return body["model"] | |
| except Exception: | |
| pass | |
| # 2. 从查询参数中提取 | |
| model_param = request.query_params.get("model") | |
| if model_param: | |
| return model_param | |
| # 3. 从路径中提取（用于已包含模型名称的路径） | |
| match = re.search(r"/models/([^/:]+)", path, re.IGNORECASE) | |
| if match: | |
| return match.group(1) | |
| # 4. 如果无法提取模型名称，抛出异常 | |
| raise ValueError("Unable to extract model name from request") | |