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parse_langchain_provider

def parse_langchain_provider(serialized: Dict[str, Any])
Parses langchain provider from serialized data Arguments:
NameDescription
serializedDict[str, Any]: Serialized data to parse provider from
Returns:
NameDescription
strParsed provider

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parse_langchain_llm_error

def parse_langchain_llm_error(
    error: Union[Exception, BaseException,
                 KeyboardInterrupt]) -> GenerationError
Parses langchain LLM error into a format that is accepted by Maxim logger Arguments:
NameDescription
errorUnion[Exception, KeyboardInterrupt]: Error to be parsed
Returns:
NameDescription
[GenerationError](/sdk/python/references/logger/components/types)Parsed LLM error

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parse_langchain_model_parameters

def parse_langchain_model_parameters(**kwargs: Any
                                     ) -> Tuple[str, Dict[str, Any]]
Parses langchain kwargs into model and model parameters. You can use this function with any langchain _start callback function Arguments:
NameDescription
kwargsDict[str, Any]: Kwargs to be parsed
Returns: Tuple[str, Dict[str, Any]]: Model and model parameters Raises:
  • Exception - If model_name is not found in kwargs

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parse_base_message_to_maxim_generation

def parse_base_message_to_maxim_generation(message: BaseMessage)
Parses langchain BaseMessage into a format that is accepted by Maxim logger Arguments:
NameDescription
messageBaseMessage
Returns: Dict[str, Any]: Parsed message

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parse_langchain_message

def parse_langchain_message(message: BaseMessage)
Parses langchain BaseMessage into a choice of openai message Arguments:
NameDescription
messageBaseMessage
Returns: Dict[str, Any]: Parsed message

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parse_langchain_generation

def parse_langchain_generation(generation: Generation)
Parses langchain generation into a format that is accepted by Maxim logger Arguments:
NameDescription
generation[Generation](/sdk/python/references/logger/components/generation): Generation to be parsed
Returns: Dict[str, Any]: Parsed generation

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parse_token_usage_for_result

def parse_token_usage_for_result(result: LLMResult)
Parses token usage for a given LLM result

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parse_langchain_chat_result

def parse_langchain_chat_result(result: ChatResult) -> Dict[str, Any]
Parses langchain Chat result into a format that is accepted by Maxim logger Arguments:
NameDescription
resultChatResult: Chat result to be parsed
Returns: Dict[str, Any]: Parsed Chat result Raises:
  • Exception - If error parsing Chat result

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parse_langchain_llm_result

def parse_langchain_llm_result(result: LLMResult) -> Dict[str, Any]
Parses langchain LLM result into a format that is accepted by Maxim logger Arguments:
NameDescription
resultLLMResult: LLM result to be parsed
Returns: Dict[str, Any]: Parsed LLM result Raises:
  • Exception - If error parsing LLM result

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parse_langchain_messages

def parse_langchain_messages(input: Union[List[str], List[List[Any]]],
                             default_role="user")
Parses langchain messages into messages that are accepted by Maxim logger Arguments:
NameDescription
inputList[str] or List[List[Any]]: List of messages to be parsed
default_rolestr: Default role to assign to messages without a role
Returns: List[Dict[str, str]]: List of messages with role and content Raises:
  • Exception - If input is not List[str] or List[List[Any]]
  • Exception - If message type is not str or list
  • Exception - If message type is not recognized