优化代码格式和异常处理
- 修复异常处理链，使用from语法保留原始异常 - 格式化代码以符合项目规范 - 优化导入模块的顺序 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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春河晴
@@ -26,11 +26,11 @@ class LLM_request:
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"o1-mini",
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"o1-preview",
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"o1-2024-12-17",
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"o1-preview-2024-09-12",
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"o1-preview-2024-09-12",
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"o3-mini-2025-01-31",
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"o1-mini-2024-09-12",
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]
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def __init__(self, model, **kwargs):
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# 将大写的配置键转换为小写并从config中获取实际值
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try:
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@@ -52,9 +52,6 @@ class LLM_request:
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# 从 kwargs 中提取 request_type，如果没有提供则默认为 "default"
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self.request_type = kwargs.pop("request_type", "default")
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@staticmethod
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def _init_database():
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"""初始化数据库集合"""
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@@ -180,7 +177,7 @@ class LLM_request:
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api_url = f"{self.base_url.rstrip('/')}/{endpoint.lstrip('/')}"
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# 判断是否为流式
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stream_mode = self.params.get("stream", False)
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logger_msg = "进入流式输出模式，" if stream_mode else ""
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# logger_msg = "进入流式输出模式，" if stream_mode else ""
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# logger.debug(f"{logger_msg}发送请求到URL: {api_url}")
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# logger.info(f"使用模型: {self.model_name}")
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@@ -229,7 +226,8 @@ class LLM_request:
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error_message = error_obj.get("message")
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error_status = error_obj.get("status")
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logger.error(
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f"服务器错误详情: 代码={error_code}, 状态={error_status}, 消息={error_message}"
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f"服务器错误详情: 代码={error_code}, 状态={error_status}, "
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f"消息={error_message}"
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)
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elif isinstance(error_json, dict) and "error" in error_json:
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# 处理单个错误对象的情况
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@@ -282,7 +280,7 @@ class LLM_request:
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flag_delta_content_finished = False
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accumulated_content = ""
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usage = None # 初始化usage变量，避免未定义错误
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async for line_bytes in response.content:
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line = line_bytes.decode("utf-8").strip()
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if not line:
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@@ -294,7 +292,7 @@ class LLM_request:
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try:
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chunk = json.loads(data_str)
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if flag_delta_content_finished:
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chunk_usage = chunk.get("usage",None)
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chunk_usage = chunk.get("usage", None)
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if chunk_usage:
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usage = chunk_usage # 获取token用量
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else:
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@@ -306,7 +304,7 @@ class LLM_request:
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# 检测流式输出文本是否结束
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finish_reason = chunk["choices"][0].get("finish_reason")
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if finish_reason == "stop":
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chunk_usage = chunk.get("usage",None)
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chunk_usage = chunk.get("usage", None)
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if chunk_usage:
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usage = chunk_usage
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break
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@@ -355,12 +353,16 @@ class LLM_request:
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if "error" in error_item and isinstance(error_item["error"], dict):
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error_obj = error_item["error"]
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logger.error(
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f"服务器错误详情: 代码={error_obj.get('code')}, 状态={error_obj.get('status')}, 消息={error_obj.get('message')}"
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f"服务器错误详情: 代码={error_obj.get('code')}, "
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f"状态={error_obj.get('status')}, "
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f"消息={error_obj.get('message')}"
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)
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elif isinstance(error_json, dict) and "error" in error_json:
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error_obj = error_json.get("error", {})
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logger.error(
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f"服务器错误详情: 代码={error_obj.get('code')}, 状态={error_obj.get('status')}, 消息={error_obj.get('message')}"
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f"服务器错误详情: 代码={error_obj.get('code')}, "
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f"状态={error_obj.get('status')}, "
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f"消息={error_obj.get('message')}"
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)
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else:
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logger.error(f"服务器错误响应: {error_json}")
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@@ -373,15 +375,22 @@ class LLM_request:
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else:
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logger.critical(f"HTTP响应错误达到最大重试次数: 状态码: {e.status}, 错误: {e.message}")
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# 安全地检查和记录请求详情
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if image_base64 and payload and isinstance(payload, dict) and "messages" in payload and len(payload["messages"]) > 0:
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if (
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image_base64
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and payload
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and isinstance(payload, dict)
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and "messages" in payload
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and len(payload["messages"]) > 0
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):
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if isinstance(payload["messages"][0], dict) and "content" in payload["messages"][0]:
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content = payload["messages"][0]["content"]
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if isinstance(content, list) and len(content) > 1 and "image_url" in content[1]:
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payload["messages"][0]["content"][1]["image_url"]["url"] = (
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f"data:image/{image_format.lower() if image_format else 'jpeg'};base64,{image_base64[:10]}...{image_base64[-10:]}"
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f"data:image/{image_format.lower() if image_format else 'jpeg'};base64,"
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f"{image_base64[:10]}...{image_base64[-10:]}"
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)
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logger.critical(f"请求头: {await self._build_headers(no_key=True)} 请求体: {payload}")
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raise RuntimeError(f"API请求失败: 状态码 {e.status}, {e.message}")
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raise RuntimeError(f"API请求失败: 状态码 {e.status}, {e.message}") from e
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except Exception as e:
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if retry < policy["max_retries"] - 1:
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wait_time = policy["base_wait"] * (2**retry)
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@@ -390,15 +399,22 @@ class LLM_request:
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else:
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logger.critical(f"请求失败: {str(e)}")
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# 安全地检查和记录请求详情
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if image_base64 and payload and isinstance(payload, dict) and "messages" in payload and len(payload["messages"]) > 0:
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if (
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image_base64
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and payload
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and isinstance(payload, dict)
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and "messages" in payload
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and len(payload["messages"]) > 0
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):
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if isinstance(payload["messages"][0], dict) and "content" in payload["messages"][0]:
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content = payload["messages"][0]["content"]
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if isinstance(content, list) and len(content) > 1 and "image_url" in content[1]:
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payload["messages"][0]["content"][1]["image_url"]["url"] = (
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f"data:image/{image_format.lower() if image_format else 'jpeg'};base64,{image_base64[:10]}...{image_base64[-10:]}"
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f"data:image/{image_format.lower() if image_format else 'jpeg'};base64,"
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f"{image_base64[:10]}...{image_base64[-10:]}"
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)
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logger.critical(f"请求头: {await self._build_headers(no_key=True)} 请求体: {payload}")
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raise RuntimeError(f"API请求失败: {str(e)}")
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raise RuntimeError(f"API请求失败: {str(e)}") from e
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logger.error("达到最大重试次数，请求仍然失败")
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raise RuntimeError("达到最大重试次数，API请求仍然失败")
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@@ -411,7 +427,7 @@ class LLM_request:
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"""
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# 复制一份参数，避免直接修改原始数据
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new_params = dict(params)
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if self.model_name.lower() in self.MODELS_NEEDING_TRANSFORMATION:
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# 删除 'temperature' 参数（如果存在）
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new_params.pop("temperature", None)
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@@ -479,7 +495,7 @@ class LLM_request:
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completion_tokens=completion_tokens,
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total_tokens=total_tokens,
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user_id=user_id,
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request_type = request_type if request_type is not None else self.request_type,
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request_type=request_type if request_type is not None else self.request_type,
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endpoint=endpoint,
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)
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@@ -546,13 +562,14 @@ class LLM_request:
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list: embedding向量，如果失败则返回None
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"""
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if(len(text) < 1):
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if len(text) < 1:
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logger.debug("该消息没有长度，不再发送获取embedding向量的请求")
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return None
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def embedding_handler(result):
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"""处理响应"""
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if "data" in result and len(result["data"]) > 0:
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# 提取 token 使用信息
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# 提取 token 使用信息
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usage = result.get("usage", {})
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if usage:
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prompt_tokens = usage.get("prompt_tokens", 0)
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@@ -565,7 +582,7 @@ class LLM_request:
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total_tokens=total_tokens,
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user_id="system", # 可以根据需要修改 user_id
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request_type="embedding", # 请求类型为 embedding
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endpoint="/embeddings" # API 端点
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endpoint="/embeddings", # API 端点
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)
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return result["data"][0].get("embedding", None)
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return result["data"][0].get("embedding", None)
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