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87 lines
2.8 KiB
Python
87 lines
2.8 KiB
Python
# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
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# Licensed under the 【火山方舟】原型应用软件自用许可协议
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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# https://www.volcengine.com/docs/82379/1433703
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import logging
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from typing import Any, Dict, List
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from langchain_core.callbacks import BaseCallbackHandler
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from langchain_core.messages import BaseMessage
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from langchain_core.outputs import LLMResult
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root_logger = logging.getLogger()
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for handler in root_logger.handlers:
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formatter = logging.Formatter(
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'%(asctime)s - %(levelname)s - %(message)s',
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'%Y-%m-%d %H:%M:%S'
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)
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handler.setFormatter(formatter)
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s',
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datefmt='%Y-%m-%d %H:%M:%S'
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)
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def enforce_log_format():
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root_logger = logging.getLogger()
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for handler in root_logger.handlers:
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formatter = logging.Formatter(
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'%(asctime)s - %(levelname)s - %(message)s',
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'%Y-%m-%d %H:%M:%S'
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)
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handler.setFormatter(formatter)
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class ModelLoggingCallback(BaseCallbackHandler):
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def on_chat_model_start(
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self, serialized: Dict[str, Any], messages: List[List[BaseMessage]], **kwargs
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) -> None:
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logging.info(
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f"[Model] Chat model started\n")
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def on_llm_end(self, response: LLMResult, **kwargs) -> None:
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logging.info(
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f"[Model] Chat model ended, response: {response}")
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def on_llm_error(self, error: BaseException, **kwargs) -> Any:
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logging.info(
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f"[Model] Chat model error, response: {error}")
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def on_chain_start(
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self, serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs
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) -> None:
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logging.info(
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f"[Model] Chain {serialized.get('name')} started")
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def on_chain_end(self, outputs: Dict[str, Any], **kwargs) -> None:
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logging.info(f"[Model] Chain ended, outputs: {outputs}")
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# class that wraps another class and logs all function calls being executed
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class Wrapper:
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def __init__(self, wrapped_class):
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self.wrapped_class = wrapped_class
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def __getattr__(self, attr):
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original_func = getattr(self.wrapped_class, attr)
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def wrapper(*args, **kwargs):
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print(f"Calling function: {attr}")
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print(f"Arguments: {args}, {kwargs}")
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result = original_func(*args, **kwargs)
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print(f"Response: {result}")
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return result
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return wrapper
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