langchain/libs/core/langchain_core/exceptions.py
Leonid Ganeline 2f2b77602e
docs: modules descriptions (#17844)
Several `core` modules do not have descriptions, like the
[agent](https://api.python.langchain.com/en/latest/core_api_reference.html#module-langchain_core.agents)
module.
- Added missed module descriptions. The descriptions are mostly copied
from the `langchain` or `community` package modules.
2024-02-21 15:58:21 -08:00

50 lines
1.9 KiB
Python

"""Custom **exceptions** for LangChain. """
from typing import Any, Optional
class LangChainException(Exception):
"""General LangChain exception."""
class TracerException(LangChainException):
"""Base class for exceptions in tracers module."""
class OutputParserException(ValueError, LangChainException):
"""Exception that output parsers should raise to signify a parsing error.
This exists to differentiate parsing errors from other code or execution errors
that also may arise inside the output parser. OutputParserExceptions will be
available to catch and handle in ways to fix the parsing error, while other
errors will be raised.
Args:
error: The error that's being re-raised or an error message.
observation: String explanation of error which can be passed to a
model to try and remediate the issue.
llm_output: String model output which is error-ing.
send_to_llm: Whether to send the observation and llm_output back to an Agent
after an OutputParserException has been raised. This gives the underlying
model driving the agent the context that the previous output was improperly
structured, in the hopes that it will update the output to the correct
format.
"""
def __init__(
self,
error: Any,
observation: Optional[str] = None,
llm_output: Optional[str] = None,
send_to_llm: bool = False,
):
super(OutputParserException, self).__init__(error)
if send_to_llm:
if observation is None or llm_output is None:
raise ValueError(
"Arguments 'observation' & 'llm_output'"
" are required if 'send_to_llm' is True"
)
self.observation = observation
self.llm_output = llm_output
self.send_to_llm = send_to_llm