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GalileoAsyncCallback Objects

class GalileoAsyncCallback(AsyncCallbackHandler)
Async Langchain callback handler for logging traces to the Galileo platform. Arguments:
  • _galileo_logger (GalileoLogger): The Galileo logger instance.
  • _nodes (dict[UUID, Node]): A dictionary of nodes, where the key is the run_id and the value is the node.
  • _start_new_trace (bool): Whether to start a new trace when a chain starts. Set this to False to continue using the current trace.
  • _flush_on_chain_end (bool): Whether to flush the trace when a chain ends.

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on_chain_start

async def on_chain_start(serialized: dict[str, Any],
                         inputs: dict[str, Any],
                         *,
                         run_id: UUID,
                         parent_run_id: Optional[UUID] = None,
                         tags: Optional[list[str]] = None,
                         **kwargs: Any) -> Any
Langchain callback when a chain starts.

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on_chain_end

async def on_chain_end(outputs: dict[str, Any],
                       *,
                       run_id: UUID,
                       parent_run_id: Optional[UUID] = None,
                       **kwargs: Any) -> Any
Langchain callback when a chain ends.

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on_agent_finish

async def on_agent_finish(finish: AgentFinish, *, run_id: UUID,
                          **kwargs: Any) -> Any
Langchain callback when an agent finishes.

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on_llm_start

async def on_llm_start(serialized: dict[str, Any],
                       prompts: list[str],
                       *,
                       run_id: UUID,
                       parent_run_id: Optional[UUID] = None,
                       tags: Optional[list[str]] = None,
                       metadata: Optional[dict[str, Any]] = None,
                       **kwargs: Any) -> Any
Langchain callback when an LLM node starts. Note: This callback is only used for non-chat models.

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on_llm_new_token

async def on_llm_new_token(token: str, *, run_id: UUID, **kwargs: Any) -> Any
Langchain callback when an LLM node generates a new token.

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on_chat_model_start

async def on_chat_model_start(serialized: dict[str, Any],
                              messages: list[list[BaseMessage]],
                              *,
                              run_id: UUID,
                              parent_run_id: Optional[UUID] = None,
                              tags: Optional[list[str]] = None,
                              metadata: Optional[dict[str, Any]] = None,
                              **kwargs: Any) -> Any
Langchain callback when a chat model starts.

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on_llm_end

async def on_llm_end(response: LLMResult,
                     *,
                     run_id: UUID,
                     parent_run_id: Optional[UUID] = None,
                     **kwargs: Any) -> Any
Langchain callback when an LLM node ends.

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on_tool_start

async def on_tool_start(serialized: dict[str, Any],
                        input_str: str,
                        *,
                        run_id: UUID,
                        parent_run_id: Optional[UUID] = None,
                        tags: Optional[list[str]] = None,
                        metadata: Optional[dict[str, Any]] = None,
                        **kwargs: Any) -> Any
Langchain callback when a tool node starts.

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on_tool_end

async def on_tool_end(output: Any,
                      *,
                      run_id: UUID,
                      parent_run_id: Optional[UUID] = None,
                      **kwargs: Any) -> Any
Langchain callback when a tool node ends.

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on_retriever_start

async def on_retriever_start(serialized: dict[str, Any],
                             query: str,
                             *,
                             run_id: UUID,
                             parent_run_id: Optional[UUID] = None,
                             tags: Optional[list[str]] = None,
                             metadata: Optional[dict[str, Any]] = None,
                             **kwargs: Any) -> Any
Langchain callback when a retriever node starts.

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on_retriever_end

async def on_retriever_end(documents: list[Document],
                           *,
                           run_id: UUID,
                           parent_run_id: Optional[UUID] = None,
                           **kwargs: Any) -> Any
Langchain callback when a retriever node ends.

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on_chain_error

async def on_chain_error(error: Exception,
                         *,
                         run_id: UUID,
                         parent_run_id: Optional[UUID] = None,
                         **kwargs: Any) -> Any
Called when a chain errors.

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on_llm_error

async def on_llm_error(error: Exception,
                       *,
                       run_id: UUID,
                       parent_run_id: Optional[UUID] = None,
                       **kwargs: Any) -> Any
Called when an LLM errors.

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on_tool_error

async def on_tool_error(error: Exception,
                        *,
                        run_id: UUID,
                        parent_run_id: Optional[UUID] = None,
                        **kwargs: Any) -> Any
Called when a tool errors.

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on_retriever_error

async def on_retriever_error(error: Exception,
                             *,
                             run_id: UUID,
                             parent_run_id: Optional[UUID] = None,
                             **kwargs: Any) -> Any
Called when a retriever errors.