Metadata-Version: 2.1
Name: llama-index-packs-query-understanding-agent
Version: 0.2.1
Summary: llama-index packs query understanding agent integration
License: MIT
Author: Sasha Sheng
Author-email: hackgoofer@gmail.com
Requires-Python: >=3.8.1,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: llama-index-core (>=0.11.0,<0.12.0)
Requires-Dist: llama-index-llms-openai (>=0.2.0,<0.3.0)
Description-Content-Type: text/markdown

# LlamaIndex Packs Integration: Query Understanding Agent

This LlamaPack implements Query Understanding Agent

Taking inspiration from Humans - when asked a query, humans would clarify what the query means before proceeding if the human sensed the query is unclear. This LlamaPack implements this.

Check out the [full notebook here](https://github.com/run-llama/llama_index/blob/main/llama-index-packs/llama-index-packs-query-understanding-agent/examples/query_understanding_agent.ipynb).

### Installation

```bash
pip install llama-index
```

## CLI Usage

You can download llamapacks directly using `llamaindex-cli`, which comes installed with the `llama-index` python package:

```bash
llamaindex-cli download-llamapack QueryUnderstandingAgent --download-dir ./query_understanding_agent
```

You can then inspect the files at `./query_understanding_agent` and use them as a template for your own project.

## Code Usage

You can download the pack to a the `./query_understanding_agent` directory:

```python
from llama_index.core.llama_pack import download_llama_pack

# download and install dependencies
QueryUnderstandingAgentPack = download_llama_pack(
    "QueryUnderstandingAgent", "./query_understanding_agent"
)

# You can use any llama-hub loader to get documents!
```

From here, you can use the pack, or inspect and modify the pack in `./query_understanding_agent`.
See example notebook for usage.

