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# `langchain_community.callbacks.aim_callback`.AimCallbackHandler

class langchain_community.callbacks.aim_callback.AimCallbackHandler(repo: Optional[str] = None, experiment_name: Optional[str] = None, system_tracking_interval: Optional[int] = 10, log_system_params: bool = True)

  Callback Handler that logs to Aim.

  Parameters

    - repo (`str`, optional) – Aim repository path or Repo object to which Run object is bound. If skipped, default Repo is used.

    - experiment_name (`str`, optional) – Sets Run’s experiment property. ‘default’ if not specified. Can be used later to query runs/sequences.

    - system_tracking_interval (`int`, optional) –

      Sets the tracking interval in seconds for system usage metrics (CPU, Memory, etc.). Set to None

      > to disable system metrics tracking.

    - log_system_params (`bool`, optional) – Enable/Disable logging of system params such as installed packages, git info, environment variables, etc.

  This handler will utilize the associated callback method called and formats the input of each callback function with metadata regarding the state of LLM run and then logs the response to Aim.

  Initialize callback handler.

  Attributes

  `always_verbose` | Whether to call verbose callbacks even if verbose is False.
  `ignore_agent` | Whether to ignore agent callbacks.
  `ignore_chain` | Whether to ignore chain callbacks.
  `ignore_chat_model` | Whether to ignore chat model callbacks.
  `ignore_llm` | Whether to ignore LLM callbacks.
  `ignore_retriever` | Whether to ignore retriever callbacks.
  `ignore_retry` | Whether to ignore retry callbacks.
  `raise_error` |
  `run_inline` |

  Methods

  `__init__`([repo, experiment_name, ...]) | Initialize callback handler.
  `flush_tracker`([repo, experiment_name, ...]) | Flush the tracker and reset the session.
  `get_custom_callback_meta`() |
  `on_agent_action`(action, **kwargs) | Run on agent action.
  `on_agent_finish`(finish, **kwargs) | Run when agent ends running.
  `on_chain_end`(outputs, **kwargs) | Run when chain ends running.
  `on_chain_error`(error, **kwargs) | Run when chain errors.
  `on_chain_start`(serialized, inputs, **kwargs) | Run when chain starts running.
  `on_chat_model_start`(serialized, messages, *, ...) | Run when a chat model starts running.
  `on_llm_end`(response, **kwargs) | Run when LLM ends running.
  `on_llm_error`(error, **kwargs) | Run when LLM errors.
  `on_llm_new_token`(token, **kwargs) | Run when LLM generates a new token.
  `on_llm_start`(serialized, prompts, **kwargs) | Run when LLM starts.
  `on_retriever_end`(documents, *, run_id[, ...]) | Run when Retriever ends running.
  `on_retriever_error`(error, *, run_id[, ...]) | Run when Retriever errors.
  `on_retriever_start`(serialized, query, *, run_id) | Run when Retriever starts running.
  `on_retry`(retry_state, *, run_id[, parent_run_id]) | Run on a retry event.
  `on_text`(text, **kwargs) | Run when agent is ending.
  `on_tool_end`(output, **kwargs) | Run when tool ends running.
  `on_tool_error`(error, **kwargs) | Run when tool errors.
  `on_tool_start`(serialized, input_str, **kwargs) | Run when tool starts running.
  `reset_callback_meta`() | Reset the callback metadata.
  `setup`(**kwargs) |

  __init__(repo: Optional[str] = None, experiment_name: Optional[str] = None, system_tracking_interval: Optional[int] = 10, log_system_params: bool = True) → None

    Initialize callback handler.

    Parameters

      - repo (Optional[str]) –

      - experiment_name (Optional[str]) –

      - system_tracking_interval (Optional[int]) –

      - log_system_params (bool) –

    Return type

      None

  flush_tracker(repo: Optional[str] = None, experiment_name: Optional[str] = None, system_tracking_interval: Optional[int] = 10, log_system_params: bool = True, langchain_asset: Optional[Any] = None, reset: bool = True, finish: bool = False) → None

    Flush the tracker and reset the session.

    Parameters

      - repo (`str`, optional) – Aim repository path or Repo object to which Run object is bound. If skipped, default Repo is used.

      - experiment_name (`str`, optional) – Sets Run’s experiment property. ‘default’ if not specified. Can be used later to query runs/sequences.

      - system_tracking_interval (`int`, optional) –

        Sets the tracking interval in seconds for system usage metrics (CPU, Memory, etc.). Set to None

        > to disable system metrics tracking.

      - log_system_params (`bool`, optional) – Enable/Disable logging of system params such as installed packages, git info, environment variables, etc.

      - langchain_asset (Optional[Any]) – The langchain asset to save.

      - reset (bool) – Whether to reset the session.

      - finish (bool) – Whether to finish the run.

      - Returns – None

    Return type

      None

  get_custom_callback_meta() → Dict[str, Any]
    Return type

      Dict[str, Any]

  on_agent_action(action: AgentAction, **kwargs: Any) → Any

    Run on agent action.

    Parameters

      - action (AgentAction) –

      - kwargs (Any) –

    Return type

      Any

  on_agent_finish(finish: AgentFinish, **kwargs: Any) → None

    Run when agent ends running.

    Parameters

      - finish (AgentFinish) –

      - kwargs (Any) –

    Return type

      None

  on_chain_end(outputs: Dict[str, Any], **kwargs: Any) → None

    Run when chain ends running.

    Parameters

      - outputs (Dict[str, Any]) –

      - kwargs (Any) –

    Return type

      None

  on_chain_error(error: BaseException, **kwargs: Any) → None

    Run when chain errors.

    Parameters

      - error (BaseException) –

      - kwargs (Any) –

    Return type

      None

  on_chain_start(serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any) → None

    Run when chain starts running.

    Parameters

      - serialized (Dict[str, Any]) –

      - inputs (Dict[str, Any]) –

      - kwargs (Any) –

    Return type

      None

  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

    Run when a chat model starts running.

    ATTENTION: This method is called for chat models. If you’re implementing

      a handler for a non-chat model, you should use on_llm_start instead.

    Parameters

      - serialized (Dict[str, Any]) –

      - messages (List[List[BaseMessage]]) –

      - run_id (UUID) –

      - parent_run_id (Optional[UUID]) –

      - tags (Optional[List[str]]) –

      - metadata (Optional[Dict[str, Any]]) –

      - kwargs (Any) –

    Return type

      Any

  on_llm_end(response: LLMResult, **kwargs: Any) → None

    Run when LLM ends running.

    Parameters

      - response (LLMResult) –

      - kwargs (Any) –

    Return type

      None

  on_llm_error(error: BaseException, **kwargs: Any) → None

    Run when LLM errors.

    Parameters

      - error (BaseException) –

      - kwargs (Any) –

    Return type

      None

  on_llm_new_token(token: str, **kwargs: Any) → None

    Run when LLM generates a new token.

    Parameters

      - token (str) –

      - kwargs (Any) –

    Return type

      None

  on_llm_start(serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) → None

    Run when LLM starts.

    Parameters

      - serialized (Dict[str, Any]) –

      - prompts (List[str]) –

      - kwargs (Any) –

    Return type

      None

  on_retriever_end(documents: Sequence[Document], *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any

    Run when Retriever ends running.

    Parameters

      - documents (Sequence[Document]) –

      - run_id (UUID) –

      - parent_run_id (Optional[UUID]) –

      - kwargs (Any) –

    Return type

      Any

  on_retriever_error(error: BaseException, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any

    Run when Retriever errors.

    Parameters

      - error (BaseException) –

      - run_id (UUID) –

      - parent_run_id (Optional[UUID]) –

      - kwargs (Any) –

    Return type

      Any

  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

    Run when Retriever starts running.

    Parameters

      - serialized (Dict[str, Any]) –

      - query (str) –

      - run_id (UUID) –

      - parent_run_id (Optional[UUID]) –

      - tags (Optional[List[str]]) –

      - metadata (Optional[Dict[str, Any]]) –

      - kwargs (Any) –

    Return type

      Any

  on_retry(retry_state: RetryCallState, *, run_id: UUID, parent_run_id: Optional[UUID] = None, **kwargs: Any) → Any

    Run on a retry event.

    Parameters

      - retry_state (RetryCallState) –

      - run_id (UUID) –

      - parent_run_id (Optional[UUID]) –

      - kwargs (Any) –

    Return type

      Any

  on_text(text: str, **kwargs: Any) → None

    Run when agent is ending.

    Parameters

      - text (str) –

      - kwargs (Any) –

    Return type

      None

  on_tool_end(output: Any, **kwargs: Any) → None

    Run when tool ends running.

    Parameters

      - output (Any) –

      - kwargs (Any) –

    Return type

      None

  on_tool_error(error: BaseException, **kwargs: Any) → None

    Run when tool errors.

    Parameters

      - error (BaseException) –

      - kwargs (Any) –

    Return type

      None

  on_tool_start(serialized: Dict[str, Any], input_str: str, **kwargs: Any) → None

    Run when tool starts running.

    Parameters

      - serialized (Dict[str, Any]) –

      - input_str (str) –

      - kwargs (Any) –

    Return type

      None

  reset_callback_meta() → None

    Reset the callback metadata.

    Return type

      None

  setup(**kwargs: Any) → None
    Parameters

      kwargs (Any) –

    Return type

      None

# Examples using AimCallbackHandler

- scenario 1 - LLM