mirror of https://github.com/corca-ai/EVAL
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88 lines
2.6 KiB
Python
88 lines
2.6 KiB
Python
from typing import Any, Dict, List, Optional, Union
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from langchain.callbacks.base import BaseCallbackHandler
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from langchain.schema import AgentAction, AgentFinish, LLMResult
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from ansi import ANSI, Color, Style, dim_multiline
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from logger import logger
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class EVALCallbackHandler(BaseCallbackHandler):
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def on_llm_start(
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self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
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) -> None:
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pass
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def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
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pass
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def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
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pass
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def on_llm_error(
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self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
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) -> None:
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pass
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def on_chain_start(
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self, serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any
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) -> None:
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logger.info(ANSI(f"Entering new chain.").to(Color.green(), Style.italic()))
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logger.info(ANSI("Prompted Text").to(Color.yellow()) + f': {inputs["input"]}\n')
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def on_chain_end(self, outputs: Dict[str, Any], **kwargs: Any) -> None:
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logger.info(ANSI(f"Finished chain.").to(Color.green(), Style.italic()))
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def on_chain_error(
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self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
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) -> None:
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logger.error(
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ANSI(f"Chain Error").to(Color.red()) + ": " + dim_multiline(str(error))
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)
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def on_tool_start(
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self,
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serialized: Dict[str, Any],
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input_str: str,
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**kwargs: Any,
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) -> None:
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pass
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def on_agent_action(self, action: AgentAction, **kwargs: Any) -> Any:
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pass
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def on_tool_end(
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self,
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output: str,
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observation_prefix: Optional[str] = None,
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llm_prefix: Optional[str] = None,
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**kwargs: Any,
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) -> None:
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logger.info(
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ANSI("Observation").to(Color.magenta()) + ": " + dim_multiline(output)
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)
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logger.info(ANSI("Thinking...").to(Color.green(), Style.italic()))
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def on_tool_error(
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self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
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) -> None:
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logger.error(ANSI("Tool Error").to(Color.red()) + f": {error}")
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def on_text(
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self,
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text: str,
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color: Optional[str] = None,
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end: str = "",
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**kwargs: Optional[str],
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) -> None:
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pass
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def on_agent_finish(
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self, finish: AgentFinish, color: Optional[str] = None, **kwargs: Any
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) -> None:
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logger.info(
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ANSI("Final Answer").to(Color.yellow())
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+ ": "
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+ dim_multiline(finish.return_values.get("output", ""))
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)
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