diff --git a/app/handler/response_handler.py b/app/handler/response_handler.py index 95f631c..7bb2d76 100644 --- a/app/handler/response_handler.py +++ b/app/handler/response_handler.py @@ -9,6 +9,9 @@ from typing import Any, Dict, List, Optional from app.config.config import settings from app.utils.uploader import ImageUploaderFactory +from app.log.logger import get_openai_logger + +logger = get_openai_logger() class ResponseHandler(ABC): @@ -159,13 +162,16 @@ def _extract_result( gemini_format: bool = False, ) -> tuple[str, Optional[str], List[Dict[str, Any]], Optional[bool]]: text, reasoning_content, tool_calls, thought = "", "", [], None + if stream: if response.get("candidates"): candidate = response["candidates"][0] content = candidate.get("content", {}) parts = content.get("parts", []) if not parts: + logger.warning("No parts found in stream response") return "", None, [], None + if "text" in parts[0]: text = parts[0].get("text") if "thought" in parts[0]: @@ -191,24 +197,38 @@ def _extract_result( if response.get("candidates"): candidate = response["candidates"][0] text, reasoning_content = "", "" - if "parts" in candidate["content"]: - for part in candidate["content"]["parts"]: - if "text" in part: - if "thought" in part and settings.SHOW_THINKING_PROCESS: - reasoning_content += part["text"] - else: - text += part["text"] - if "thought" in part and thought is None: - thought = part.get("thought") - elif "inlineData" in part: - text += _extract_image_data(part) + + # 使用安全的访问方式 + content = candidate.get("content", {}) + + if content and isinstance(content, dict): + parts = content.get("parts", []) + + if parts: + for part in parts: + if "text" in part: + if "thought" in part and settings.SHOW_THINKING_PROCESS: + reasoning_content += part["text"] + else: + text += part["text"] + if "thought" in part and thought is None: + thought = part.get("thought") + elif "inlineData" in part: + text += _extract_image_data(part) + else: + logger.warning(f"No parts found in content for model: {model}") + else: + logger.error(f"Invalid content structure for model: {model}") text = _add_search_link_text(model, candidate, text) - tool_calls = _extract_tool_calls( - candidate["content"]["parts"], gemini_format - ) + + # 安全地获取 parts 用于工具调用提取 + parts = candidate.get("content", {}).get("parts", []) + tool_calls = _extract_tool_calls(parts, gemini_format) else: + logger.warning(f"No candidates found in response for model: {model}") text = "暂无返回" + return text, reasoning_content, tool_calls, thought @@ -250,8 +270,8 @@ def _extract_tool_calls( return [] letters = string.ascii_lowercase + string.digits - tool_calls = list() + for i in range(len(parts)): part = parts[i] if not part or not isinstance(part, dict): @@ -260,7 +280,7 @@ def _extract_tool_calls( item = part.get("functionCall", {}) if not item or not isinstance(item, dict): continue - + if gemini_format: tool_calls.append(part) else: diff --git a/app/service/chat/openai_chat_service.py b/app/service/chat/openai_chat_service.py index 2a7a067..a86756b 100644 --- a/app/service/chat/openai_chat_service.py +++ b/app/service/chat/openai_chat_service.py @@ -142,6 +142,23 @@ def _get_safety_settings(model: str) -> List[Dict[str, str]]: return settings.SAFETY_SETTINGS +def _validate_and_set_max_tokens( + payload: Dict[str, Any], + max_tokens: Optional[int], + logger_instance +) -> None: + """验证并设置 max_tokens 参数""" + if max_tokens is None: + return + + # 参数验证和处理 + if max_tokens <= 0: + logger_instance.warning(f"Invalid max_tokens value: {max_tokens}, will not set maxOutputTokens") + # 不设置 maxOutputTokens，让 Gemini API 使用默认值 + else: + payload["generationConfig"]["maxOutputTokens"] = max_tokens + + def _build_payload( request: ChatRequest, messages: List[Dict[str, Any]], @@ -159,12 +176,16 @@ def _build_payload( "tools": _build_tools(request, messages), "safetySettings": _get_safety_settings(request.model), } - if request.max_tokens is not None: - payload["generationConfig"]["maxOutputTokens"] = request.max_tokens + + # 处理 max_tokens 参数 + _validate_and_set_max_tokens(payload, request.max_tokens, logger) + if request.model.endswith("-image") or request.model.endswith("-image-generation"): payload["generationConfig"]["responseModalities"] = ["Text", "Image"] + if request.model.endswith("-non-thinking"): payload["generationConfig"]["thinkingConfig"] = {"thinkingBudget": 0} + if request.model in settings.THINKING_BUDGET_MAP: if settings.SHOW_THINKING_PROCESS: payload["generationConfig"]["thinkingConfig"] = { @@ -239,27 +260,53 @@ class OpenAIChatService: is_success = False status_code = None response = None + try: response = await self.api_client.generate_content(payload, model, api_key) usage_metadata = response.get("usageMetadata", {}) is_success = True status_code = 200 - return self.response_handler.handle_response( - response, - model, - stream=False, - finish_reason="stop", - usage_metadata=usage_metadata, - ) + + # 尝试处理响应，捕获可能的响应处理异常 + try: + result = self.response_handler.handle_response( + response, + model, + stream=False, + finish_reason="stop", + usage_metadata=usage_metadata, + ) + return result + except Exception as response_error: + logger.error(f"Response processing failed for model {model}: {str(response_error)}") + + # 记录详细的错误信息 + if "parts" in str(response_error): + logger.error("Response structure issue - missing or invalid parts") + if response.get("candidates"): + candidate = response["candidates"][0] + content = candidate.get("content", {}) + logger.error(f"Content structure: {content}") + + # 重新抛出异常 + raise response_error + except Exception as e: is_success = False error_log_msg = str(e) - logger.error(f"Normal API call failed with error: {error_log_msg}") + logger.error(f"API call failed for model {model}: {error_log_msg}") + + # 特别记录 max_tokens 相关的错误 + gen_config = payload.get('generationConfig', {}) + if "maxOutputTokens" in gen_config: + logger.error(f"Request had maxOutputTokens: {gen_config['maxOutputTokens']}") + + # 如果是响应处理错误，记录更多信息 + if "parts" in error_log_msg: + logger.error("This is likely a response processing error") + match = re.search(r"status code (\d+)", error_log_msg) - if match: - status_code = int(match.group(1)) - else: - status_code = 500 + status_code = int(match.group(1)) if match else 500 await add_error_log( gemini_key=api_key, @@ -273,6 +320,8 @@ class OpenAIChatService: finally: end_time = time.perf_counter() latency_ms = int((end_time - start_time) * 1000) + logger.info(f"Normal completion finished - Success: {is_success}, Latency: {latency_ms}ms") + await add_request_log( model_name=model, api_key=api_key, diff --git a/app/service/client/api_client.py b/app/service/client/api_client.py index dd297a5..d92d661 100644 --- a/app/service/client/api_client.py +++ b/app/service/client/api_client.py @@ -7,6 +7,7 @@ from abc import ABC, abstractmethod from app.config.config import settings from app.log.logger import get_api_client_logger from app.core.constants import DEFAULT_TIMEOUT +import json logger = get_api_client_logger() @@ -77,7 +78,7 @@ class GeminiApiClient(ApiClient): async def generate_content(self, payload: Dict[str, Any], model: str, api_key: str) -> Dict[str, Any]: timeout = httpx.Timeout(self.timeout, read=self.timeout) model = self._get_real_model(model) - + proxy_to_use = None if settings.PROXIES: if settings.PROXIES_USE_CONSISTENCY_HASH_BY_API_KEY: @@ -87,13 +88,35 @@ class GeminiApiClient(ApiClient): logger.info(f"Using proxy for getting models: {proxy_to_use}") headers = self._prepare_headers() + async with httpx.AsyncClient(timeout=timeout, proxy=proxy_to_use) as client: url = f"{self.base_url}/models/{model}:generateContent?key={api_key}" - response = await client.post(url, json=payload, headers=headers) - if response.status_code != 200: - error_content = response.text - raise Exception(f"API call failed with status code {response.status_code}, {error_content}") - return response.json() + + try: + response = await client.post(url, json=payload, headers=headers) + + if response.status_code != 200: + error_content = response.text + logger.error(f"API call failed - Status: {response.status_code}, Content: {error_content}") + raise Exception(f"API call failed with status code {response.status_code}, {error_content}") + + response_data = response.json() + + # 检查响应结构的基本信息 + if not response_data.get("candidates"): + logger.warning("No candidates found in API response") + + return response_data + + except httpx.TimeoutException as e: + logger.error(f"Request timeout: {e}") + raise Exception(f"Request timeout: {e}") + except httpx.RequestError as e: + logger.error(f"Request error: {e}") + raise Exception(f"Request error: {e}") + except Exception as e: + logger.error(f"Unexpected error: {e}") + raise async def stream_generate_content(self, payload: Dict[str, Any], model: str, api_key: str) -> AsyncGenerator[str, None]: timeout = httpx.Timeout(self.timeout, read=self.timeout)