# rag-v2

This is a Retrieval-Augmented Generation (RAG) plugin for LM Studio. This plugin enhances your local LLM with the ability to answer questions based on the content of provided documents.

## Features

- **Retrieval-Augmented Generation (RAG)**: Automatically retrieves relevant information from your documents to answer your questions.
- **Two Context Strategies**:
  - **Inject Full Content**: For smaller documents, the plugin injects the entire content into the context.
  - **Retrieval**: For larger documents, it uses an embedding model to find and inject only the most relevant parts.
- **Automatic Embedding Model Detection**: The plugin can automatically detect and use a compatible embedding model that you have loaded or downloaded in LM Studio.
- **Configurable**: You can configure the retrieval parameters to suit your needs.

## Getting Started

### Development

The source code resides in the `src/` directory. For development purposes, you can run the plugin in development mode using:

```
lms dev
```

### Publishing

To share your plugin with the community, you can publish it to LM Studio Hub using:

```
lms push
```

The same command can also be used to update an existing plugin.

## Configuration

You can configure the plugin from the LM Studio UI. Here are the available options:

- **Embedding Model**: Choose an embedding model to use. It defaults to "Auto-Detect".
- **Manual Model ID (Optional)**: Specify a model ID to override the auto-detection.
- **Auto-Unload Model**: If enabled, the embedding model will be unloaded from memory after retrieval.
- **Retrieval Limit**: The maximum number of text chunks to retrieve from the documents.
- **Retrieval Affinity Threshold**: The minimum similarity score for a chunk to be considered relevant.

## Author

- **GitHub**: [AcidicSoil](https://github.com/AcidicSoil)
- **X (Twitter)**: [@d1rt7d4t4](https://x.com/d1rt7d4t4)
- **Discord**: the_almighty_shade (ID: 187893603920642048)

## Community & Help

- [lmstudio-js GitHub](https://github.com/lmstudio-ai/lmstudio-js)
- [Documentation](/content/docs/index.html)
- [Discord](https://discord.gg/6Q7Xn6MRVS)
- [Twitter](https://twitter.com/LMStudioAI)