autogen.agentchat.contrib.capabilities.transform_messages.TransformMessages

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TransformMessages

TransformMessages(
    *,
    transforms: list[MessageTransform] = [],
    verbose: bool = True
)

Agent capability for transforming messages before reply generation.
This capability allows you to apply a series of message transformations to a ConversableAgent’s incoming messages before they are processed for response generation. This is useful for tasks such as:
- Limiting the number of messages considered for context.
- Truncating messages to meet token limits.
- Filtering sensitive information.
- Customizing message formatting.
To use TransformMessages:
1. Create message transformations (e.g., MessageHistoryLimiter, MessageTokenLimiter).
2. Instantiate TransformMessages with a list of these transformations.
3. Add the TransformMessages instance to your ConversableAgent using add_to_agent.
NOTE: Order of message transformations is important. You could get different results based on the order of transformations.
Example:
```python from agentchat import ConversableAgent from agentchat.contrib.capabilities import TransformMessages, MessageHistoryLimiter, MessageTokenLimiter

max_messages = MessageHistoryLimiter(max_messages=2) truncate_messages = MessageTokenLimiter(max_tokens=500) transform_messages = TransformMessages(transforms=[max_messages, truncate_messages])

agent = ConversableAgent(…) transform_messages.add_to_agent(agent)

<b>Parameters:</b>
| Name | Description |
|--|--|
| `transforms` | **Type:** list[[MessageTransform](/docs/api-reference/autogen/agentchat/contrib/capabilities/transforms/MessageTransform)]<br/><br/>**Default:** [] |
| `verbose` | **Type:** bool<br/><br/>**Default:** True |

### Instance Methods

<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code>
#### add_to_agent

```python
add_to_agent(self, agent: ConversableAgent) -> 

Adds the message transformations capability to the specified ConversableAgent.
This function performs the following modifications to the agent:
1. Registers a hook that automatically transforms all messages before they are processed for response generation.