---
myst:
   html_meta:
      title: AutoRAG - Tree Summarize
      description: Learn about passage compressor module in AutoRAG
      keywords: AutoRAG,RAG,Advanced RAG,Passage Compressor,tree summarize
---
# Tree Summarize

The `Tree_summarize` module is compressor based on [llama_index](https://docs.llamaindex.ai/en/latest/examples/response_synthesizers/tree_summarize.html).
It recursively merges retrieved texts and summarizes them in a bottom-up fashion.

## **Module Parameters**

**LLM**: The tree summarize module requires setting parameters related to the Large Language Model (LLM) being used.
This includes specifying the LLM provider (e.g., `openai` or a list of providers like `[openai, huggingfacellm]`) and the model configuration.
By default, if only `openai` is specified without a model, the system uses the default model set in `llama_index`, which is `gpt-3.5-turbo`.
```{tip}
Information about the LLM model can be found [Supporting LLM models](../../local_model.md#supporting-llm-models).
```
- **Additional Parameters**:
  - **batch**: How many calls to make at once. Default is 16.
  - Other LLM-related parameters such as `model`, `temperature`, and `max_tokens` can be set. These are passed as keyword arguments (`kwargs`) to the LLM object, allowing for further customization of the LLM's behavior.


## **Example config.yaml**
```yaml
modules:
  - module_type: tree_summarize
    llm: openai
    model: gpt-3.5-turbo-16k
```
