feat(llm): 增强LLM错误处理和调试信息展示
在LLMError异常类中添加api_response字段存储原始错误信息 实现_extract_api_response方法从异常中提取API响应 前端增加调试信息展示面板，显示详细的错误诊断数据 后端测试接口返回完整的调试信息，包括耗时、错误类型等
This commit is contained in:
lintsinghua
parent
89ebd4d797
commit
2e11f3e1a3
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@ -292,6 +292,8 @@ class LLMTestResponse(BaseModel):
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message: str
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model: Optional[str] = None
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response: Optional[str] = None
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# 调试信息
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debug: Optional[dict] = None
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@router.post("/test-llm", response_model=LLMTestResponse)
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@ -302,7 +304,18 @@ async def test_llm_connection(
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"""测试LLM连接是否正常"""
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from app.services.llm.factory import LLMFactory, NATIVE_ONLY_PROVIDERS
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from app.services.llm.adapters import LiteLLMAdapter, BaiduAdapter, MinimaxAdapter, DoubaoAdapter
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from app.services.llm.types import LLMConfig, LLMProvider, LLMRequest, LLMMessage, DEFAULT_MODELS
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from app.services.llm.types import LLMConfig, LLMProvider, LLMRequest, LLMMessage, DEFAULT_MODELS, DEFAULT_BASE_URLS
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import traceback
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import time
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start_time = time.time()
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debug_info = {
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"provider": request.provider,
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"model_requested": request.model,
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"base_url_requested": request.baseUrl,
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"api_key_length": len(request.apiKey) if request.apiKey else 0,
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"api_key_prefix": request.apiKey[:8] + "..." if request.apiKey and len(request.apiKey) > 8 else "(empty)",
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}
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try:
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# 解析provider
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@ -322,13 +335,22 @@ async def test_llm_connection(
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provider = provider_map.get(request.provider.lower())
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if not provider:
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debug_info["error_type"] = "unsupported_provider"
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return LLMTestResponse(
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success=False,
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message=f"不支持的LLM提供商: {request.provider}"
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message=f"不支持的LLM提供商: {request.provider}",
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debug=debug_info
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)
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# 获取默认模型
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model = request.model or DEFAULT_MODELS.get(provider)
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base_url = request.baseUrl or DEFAULT_BASE_URLS.get(provider, "")
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debug_info["model_used"] = model
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debug_info["base_url_used"] = base_url
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debug_info["is_native_adapter"] = provider in NATIVE_ONLY_PROVIDERS
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print(f"[LLM Test] 开始测试: provider={provider.value}, model={model}, base_url={base_url}")
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# 创建配置
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config = LLMConfig(
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@ -348,8 +370,12 @@ async def test_llm_connection(
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LLMProvider.DOUBAO: DoubaoAdapter,
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}
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adapter = native_adapter_map[provider](config)
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debug_info["adapter_type"] = type(adapter).__name__
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else:
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adapter = LiteLLMAdapter(config)
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debug_info["adapter_type"] = "LiteLLMAdapter"
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# 获取 LiteLLM 实际使用的模型名
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debug_info["litellm_model"] = getattr(adapter, '_get_model_name', lambda: model)() if hasattr(adapter, '_get_model_name') else model
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test_request = LLMRequest(
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messages=[
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@ -358,49 +384,91 @@ async def test_llm_connection(
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max_tokens=50,
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)
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print(f"[LLM Test] 发送测试请求...")
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response = await adapter.complete(test_request)
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elapsed_time = time.time() - start_time
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debug_info["elapsed_time_ms"] = round(elapsed_time * 1000, 2)
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# 验证响应内容
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if not response or not response.content:
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debug_info["error_type"] = "empty_response"
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debug_info["raw_response"] = str(response) if response else None
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print(f"[LLM Test] 空响应: {response}")
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return LLMTestResponse(
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success=False,
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message="LLM 返回空响应，请检查 API Key 和配置"
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message="LLM 返回空响应，请检查 API Key 和配置",
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debug=debug_info
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)
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debug_info["response_length"] = len(response.content)
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debug_info["usage"] = {
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"prompt_tokens": getattr(response, 'prompt_tokens', None),
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"completion_tokens": getattr(response, 'completion_tokens', None),
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"total_tokens": getattr(response, 'total_tokens', None),
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}
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print(f"[LLM Test] 成功! 响应: {response.content[:50]}... 耗时: {elapsed_time:.2f}s")
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return LLMTestResponse(
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success=True,
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message="LLM连接测试成功",
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message=f"连接成功 ({elapsed_time:.2f}s)",
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model=model,
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response=response.content[:100] if response.content else None
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response=response.content[:100] if response.content else None,
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debug=debug_info
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)
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except Exception as e:
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elapsed_time = time.time() - start_time
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error_msg = str(e)
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error_type = type(e).__name__
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debug_info["elapsed_time_ms"] = round(elapsed_time * 1000, 2)
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debug_info["error_type"] = error_type
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debug_info["error_message"] = error_msg
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debug_info["traceback"] = traceback.format_exc()
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# 提取 LLMError 中的 api_response
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if hasattr(e, 'api_response') and e.api_response:
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debug_info["api_response"] = e.api_response
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if hasattr(e, 'status_code') and e.status_code:
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debug_info["status_code"] = e.status_code
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print(f"[LLM Test] 失败: {error_type}: {error_msg}")
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print(f"[LLM Test] Traceback:\n{traceback.format_exc()}")
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# 提供更友好的错误信息
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if "401" in error_msg or "invalid_api_key" in error_msg.lower() or "incorrect api key" in error_msg.lower():
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return LLMTestResponse(
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success=False,
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message="API Key 无效或已过期，请检查后重试"
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)
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friendly_message = error_msg
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# 优先检查余额不足（因为某些 API 用 429 表示余额不足）
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if any(keyword in error_msg for keyword in ["余额不足", "资源包", "充值", "quota", "insufficient", "balance", "402"]):
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friendly_message = "账户余额不足或配额已用尽，请充值后重试"
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debug_info["error_category"] = "insufficient_balance"
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elif "401" in error_msg or "invalid_api_key" in error_msg.lower() or "incorrect api key" in error_msg.lower():
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friendly_message = "API Key 无效或已过期，请检查后重试"
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debug_info["error_category"] = "auth_invalid_key"
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elif "authentication" in error_msg.lower():
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return LLMTestResponse(
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success=False,
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message="认证失败，请检查 API Key 是否正确"
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)
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friendly_message = "认证失败，请检查 API Key 是否正确"
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debug_info["error_category"] = "auth_failed"
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elif "timeout" in error_msg.lower():
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return LLMTestResponse(
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success=False,
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message="连接超时，请检查网络或 API 地址是否正确"
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)
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elif "connection" in error_msg.lower():
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return LLMTestResponse(
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success=False,
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message="无法连接到 API 服务，请检查网络或 API 地址"
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)
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friendly_message = "连接超时，请检查网络或 API 地址是否正确"
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debug_info["error_category"] = "timeout"
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elif "connection" in error_msg.lower() or "connect" in error_msg.lower():
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friendly_message = "无法连接到 API 服务，请检查网络或 API 地址"
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debug_info["error_category"] = "connection"
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elif "rate" in error_msg.lower() and "limit" in error_msg.lower():
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friendly_message = "API 请求频率超限，请稍后重试"
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debug_info["error_category"] = "rate_limit"
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elif "model" in error_msg.lower() and ("not found" in error_msg.lower() or "does not exist" in error_msg.lower()):
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friendly_message = f"模型 '{debug_info.get('model_used', 'unknown')}' 不存在或无权访问"
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debug_info["error_category"] = "model_not_found"
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else:
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debug_info["error_category"] = "unknown"
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return LLMTestResponse(
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success=False,
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message=f"LLM连接测试失败: {error_msg}"
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message=friendly_message,
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debug=debug_info
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)
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@ -109,6 +109,45 @@ class LiteLLMAdapter(BaseLLMAdapter):
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return f"{prefix}/{model}"
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def _extract_api_response(self, error: Exception) -> Optional[str]:
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"""从异常中提取 API 服务器返回的原始响应信息"""
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error_str = str(error)
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# 尝试提取 JSON 格式的错误信息
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import re
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import json
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# 匹配 {'error': {...}} 或 {"error": {...}} 格式
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json_pattern = r"\{['\"]error['\"]:\s*\{[^}]+\}\}"
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match = re.search(json_pattern, error_str)
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if match:
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try:
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# 将单引号替换为双引号以便 JSON 解析
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json_str = match.group().replace("'", '"')
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error_obj = json.loads(json_str)
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if 'error' in error_obj:
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err = error_obj['error']
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code = err.get('code', '')
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message = err.get('message', '')
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return f"[{code}] {message}" if code else message
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except:
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pass
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# 尝试提取 message 字段
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message_pattern = r"['\"]message['\"]:\s*['\"]([^'\"]+)['\"]"
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match = re.search(message_pattern, error_str)
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if match:
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return match.group(1)
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# 尝试从 litellm 异常中获取原始消息
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if hasattr(error, 'message'):
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return error.message
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if hasattr(error, 'llm_provider'):
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# litellm 异常通常包含原始错误信息
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return error_str.split(' - ')[-1] if ' - ' in error_str else None
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return None
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def _get_api_base(self) -> Optional[str]:
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"""获取 API 基础 URL"""
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# 优先使用用户配置的 base_url
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@ -200,20 +239,31 @@ class LiteLLMAdapter(BaseLLMAdapter):
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# 调用 LiteLLM
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response = await litellm.acompletion(**kwargs)
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except litellm.exceptions.AuthenticationError as e:
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raise LLMError(f"API Key 无效或已过期: {str(e)}", self.config.provider, 401)
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api_response = self._extract_api_response(e)
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raise LLMError(f"API Key 无效或已过期", self.config.provider, 401, api_response=api_response)
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except litellm.exceptions.RateLimitError as e:
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raise LLMError(f"API 调用频率超限: {str(e)}", self.config.provider, 429)
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error_msg = str(e)
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api_response = self._extract_api_response(e)
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# 区分"余额不足"和"频率超限"
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if any(keyword in error_msg for keyword in ["余额不足", "资源包", "充值", "quota", "insufficient", "balance"]):
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raise LLMError(f"账户余额不足或配额已用尽，请充值后重试", self.config.provider, 402, api_response=api_response)
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raise LLMError(f"API 调用频率超限，请稍后重试", self.config.provider, 429, api_response=api_response)
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except litellm.exceptions.APIConnectionError as e:
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raise LLMError(f"无法连接到 API 服务: {str(e)}", self.config.provider)
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api_response = self._extract_api_response(e)
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raise LLMError(f"无法连接到 API 服务", self.config.provider, api_response=api_response)
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except litellm.exceptions.APIError as e:
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raise LLMError(f"API 错误: {str(e)}", self.config.provider, getattr(e, 'status_code', None))
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api_response = self._extract_api_response(e)
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raise LLMError(f"API 错误", self.config.provider, getattr(e, 'status_code', None), api_response=api_response)
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except Exception as e:
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# 捕获其他异常并重新抛出
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error_msg = str(e)
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api_response = self._extract_api_response(e)
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if "invalid_api_key" in error_msg.lower() or "incorrect api key" in error_msg.lower():
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raise LLMError(f"API Key 无效: {error_msg}", self.config.provider, 401)
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raise LLMError(f"API Key 无效", self.config.provider, 401, api_response=api_response)
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elif "authentication" in error_msg.lower():
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raise LLMError(f"认证失败: {error_msg}", self.config.provider, 401)
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raise LLMError(f"认证失败", self.config.provider, 401, api_response=api_response)
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elif any(keyword in error_msg for keyword in ["余额不足", "资源包", "充值", "quota", "insufficient", "balance"]):
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raise LLMError(f"账户余额不足或配额已用尽", self.config.provider, 402, api_response=api_response)
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raise
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# 解析响应
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@ -79,12 +79,14 @@ class LLMError(Exception):
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message: str,
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provider: Optional[LLMProvider] = None,
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status_code: Optional[int] = None,
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original_error: Optional[Any] = None
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original_error: Optional[Any] = None,
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api_response: Optional[str] = None
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):
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super().__init__(message)
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self.provider = provider
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self.status_code = status_code
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self.original_error = original_error
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self.api_response = api_response # API 服务器返回的原始错误信息
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# 各平台默认模型 (2025年最新推荐)
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@ -51,7 +51,8 @@ export function SystemConfig() {
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const [showApiKey, setShowApiKey] = useState(false);
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const [hasChanges, setHasChanges] = useState(false);
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const [testingLLM, setTestingLLM] = useState(false);
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const [llmTestResult, setLlmTestResult] = useState<{ success: boolean; message: string } | null>(null);
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const [llmTestResult, setLlmTestResult] = useState<{ success: boolean; message: string; debug?: Record<string, unknown> } | null>(null);
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const [showDebugInfo, setShowDebugInfo] = useState(false);
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useEffect(() => { loadConfig(); }, []);
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@ -372,6 +373,7 @@ export function SystemConfig() {
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</div>
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{llmTestResult && (
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<div className={`p-3 rounded-lg ${llmTestResult.success ? 'bg-emerald-500/10 border border-emerald-500/30' : 'bg-rose-500/10 border border-rose-500/30'}`}>
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<div className="flex items-center justify-between">
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<div className="flex items-center gap-2 text-sm">
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{llmTestResult.success ? (
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<CheckCircle2 className="h-4 w-4 text-emerald-400" />
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@ -382,6 +384,61 @@ export function SystemConfig() {
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{llmTestResult.message}
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</span>
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</div>
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{llmTestResult.debug && (
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<button
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onClick={() => setShowDebugInfo(!showDebugInfo)}
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className="text-xs text-muted-foreground hover:text-foreground underline"
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>
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{showDebugInfo ? '隐藏调试信息' : '显示调试信息'}
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</button>
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)}
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</div>
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{showDebugInfo && llmTestResult.debug && (
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<div className="mt-3 pt-3 border-t border-border/50">
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<div className="text-xs font-mono space-y-1 text-muted-foreground">
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<div className="font-bold text-foreground mb-2">调试信息:</div>
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<div>Provider: <span className="text-foreground">{String(llmTestResult.debug.provider)}</span></div>
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<div>Model: <span className="text-foreground">{String(llmTestResult.debug.model_used || llmTestResult.debug.model_requested || 'N/A')}</span></div>
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<div>Base URL: <span className="text-foreground">{String(llmTestResult.debug.base_url_used || llmTestResult.debug.base_url_requested || '(default)')}</span></div>
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<div>Adapter: <span className="text-foreground">{String(llmTestResult.debug.adapter_type || 'N/A')}</span></div>
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<div>API Key: <span className="text-foreground">{String(llmTestResult.debug.api_key_prefix)} (长度: {String(llmTestResult.debug.api_key_length)})</span></div>
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<div>耗时: <span className="text-foreground">{String(llmTestResult.debug.elapsed_time_ms || 'N/A')} ms</span></div>
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{llmTestResult.debug.error_category && (
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<div>错误类型: <span className="text-rose-400">{String(llmTestResult.debug.error_category)}</span></div>
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)}
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{llmTestResult.debug.error_type && (
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<div>异常类型: <span className="text-rose-400">{String(llmTestResult.debug.error_type)}</span></div>
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)}
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{llmTestResult.debug.status_code && (
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<div>HTTP 状态码: <span className="text-rose-400">{String(llmTestResult.debug.status_code)}</span></div>
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)}
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{llmTestResult.debug.api_response && (
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<div className="mt-2">
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<div className="font-bold text-amber-400">API 服务器返回:</div>
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<pre className="mt-1 p-2 bg-amber-500/10 border border-amber-500/30 rounded text-xs overflow-x-auto">
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{String(llmTestResult.debug.api_response)}
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</pre>
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</div>
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)}
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{llmTestResult.debug.error_message && (
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<div className="mt-2">
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<div className="font-bold text-foreground">完整错误信息:</div>
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<pre className="mt-1 p-2 bg-background/50 rounded text-xs overflow-x-auto max-h-32 overflow-y-auto">
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{String(llmTestResult.debug.error_message)}
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</pre>
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</div>
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)}
|
||||
{llmTestResult.debug.traceback && (
|
||||
<details className="mt-2">
|
||||
<summary className="cursor-pointer text-muted-foreground hover:text-foreground">完整堆栈跟踪</summary>
|
||||
<pre className="mt-1 p-2 bg-background/50 rounded text-xs overflow-x-auto max-h-48 overflow-y-auto whitespace-pre-wrap">
|
||||
{String(llmTestResult.debug.traceback)}
|
||||
</pre>
|
||||
</details>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue