langchain_md_files/concepts/callbacks.mdx

# Callbacks

:::note Prerequisites
- [Runnable interface](/docs/concepts/runnables)
:::

LangChain provides a callback system that allows you to hook into the various stages of your LLM application. This is useful for logging, monitoring, streaming, and other tasks.

You can subscribe to these events by using the `callbacks` argument available throughout the API. This argument is list of handler objects, which are expected to implement one or more of the methods described below in more detail.

## Callback events

| Event            | Event Trigger                               | Associated Method     |
|------------------|---------------------------------------------|-----------------------|
| Chat model start | When a chat model starts                    | `on_chat_model_start` |
| LLM start        | When a llm starts                           | `on_llm_start`        |
| LLM new token    | When an llm OR chat model emits a new token | `on_llm_new_token`    |
| LLM ends         | When an llm OR chat model ends              | `on_llm_end`          |
| LLM errors       | When an llm OR chat model errors            | `on_llm_error`        |
| Chain start      | When a chain starts running                 | `on_chain_start`      |
| Chain end        | When a chain ends                           | `on_chain_end`        |
| Chain error      | When a chain errors                         | `on_chain_error`      |
| Tool start       | When a tool starts running                  | `on_tool_start`       |
| Tool end         | When a tool ends                            | `on_tool_end`         |
| Tool error       | When a tool errors                          | `on_tool_error`       |
| Agent action     | When an agent takes an action               | `on_agent_action`     |
| Agent finish     | When an agent ends                          | `on_agent_finish`     |
| Retriever start  | When a retriever starts                     | `on_retriever_start`  |
| Retriever end    | When a retriever ends                       | `on_retriever_end`    |
| Retriever error  | When a retriever errors                     | `on_retriever_error`  |
| Text             | When arbitrary text is run                  | `on_text`             |
| Retry            | When a retry event is run                   | `on_retry`            |

## Callback handlers

Callback handlers can either be `sync` or `async`:

* Sync callback handlers implement the [BaseCallbackHandler](https://python.langchain.com/api_reference/core/callbacks/langchain_core.callbacks.base.BaseCallbackHandler.html) interface.
* Async callback handlers implement the [AsyncCallbackHandler](https://python.langchain.com/api_reference/core/callbacks/langchain_core.callbacks.base.AsyncCallbackHandler.html) interface.

During run-time LangChain configures an appropriate callback manager (e.g., [CallbackManager](https://python.langchain.com/api_reference/core/callbacks/langchain_core.callbacks.manager.CallbackManager.html) or [AsyncCallbackManager](https://python.langchain.com/api_reference/core/callbacks/langchain_core.callbacks.manager.AsyncCallbackManager.html) which will be responsible for calling the appropriate method on each "registered" callback handler when the event is triggered.

## Passing callbacks

The `callbacks` property is available on most objects throughout the API (Models, Tools, Agents, etc.) in two different places:

- **Request time callbacks**: Passed at the time of the request in addition to the input data.
Available on all standard `Runnable` objects. These callbacks are INHERITED by all children
of the object they are defined on. For example, `chain.invoke({"number": 25}, {"callbacks": [handler]})`.
- **Constructor callbacks**: `chain = TheNameOfSomeChain(callbacks=[handler])`. These callbacks
are passed as arguments to the constructor of the object. The callbacks are scoped
only to the object they are defined on, and are **not** inherited by any children of the object.

:::warning
Constructor callbacks are scoped only to the object they are defined on. They are **not** inherited by children
of the object.
:::

If you're creating a custom chain or runnable, you need to remember to propagate request time
callbacks to any child objects.

:::important Async in Python<=3.10

Any `RunnableLambda`, a `RunnableGenerator`, or `Tool` that invokes other runnables
and is running `async` in python<=3.10, will have to propagate callbacks to child
objects manually. This is because LangChain cannot automatically propagate
callbacks to child objects in this case.

This is a common reason why you may fail to see events being emitted from custom
runnables or tools.
:::

For specifics on how to use callbacks, see the [relevant how-to guides here](/docs/how_to/#callbacks).