> ## Documentation Index
> Fetch the complete documentation index at: https://docs.swarms.world/llms.txt
> Use this file to discover all available pages before exploring further.

# RAG Examples Overview

> Retrieval-augmented generation patterns and examples built with Swarms.

Enhance your agents with Retrieval-Augmented Generation (RAG). Swarms does not bundle a vector database — you wire your own retrieval code into an agent as a [tool](/agents/agent-tools), which keeps you free to use any store you already run.

## What You'll Learn

| Topic                   | Description                                            |
| ----------------------- | ------------------------------------------------------ |
| **RAG Fundamentals**    | Understanding retrieval-augmented generation           |
| **Retrieval Tools**     | Exposing your own store to an agent as a callable tool |
| **Document Processing** | Ingesting and indexing documents                       |
| **Semantic Search**     | Finding relevant context for queries                   |

***

## RAG Examples

| Example            | Description                                                | Vector DB  | Link                                                                                                                            |
| ------------------ | ---------------------------------------------------------- | ---------- | ------------------------------------------------------------------------------------------------------------------------------- |
| **Full Agent RAG** | End-to-end retrieval and generation over a document folder | LlamaIndex | [View Example](https://github.com/kyegomez/swarms/blob/master/examples/single_agent/capabilities/rag/full_agent_rag_example.py) |
| **Qdrant Agent**   | Agent backed by a Qdrant collection                        | Qdrant     | [View Example](https://github.com/kyegomez/swarms/blob/master/examples/single_agent/capabilities/rag/qdrant_agent.py)           |
| **Pinecone**       | Semantic search over a Pinecone index                      | Pinecone   | [View Example](https://github.com/kyegomez/swarms/blob/master/examples/single_agent/capabilities/rag/pinecone_example.py)       |

***

## Use Cases

| Use Case               | Description                           |
| ---------------------- | ------------------------------------- |
| **Document Q\&A**      | Answer questions about your documents |
| **Knowledge Base**     | Query internal company knowledge      |
| **Research Assistant** | Search through research papers        |
| **Code Documentation** | Query codebase documentation          |
| **Customer Support**   | Access product knowledge              |

***

## Related Resources

* [Agent Memory](/agents/agent-memory) - Persistent memory, compression, and conversation history
* [External Knowledge](/agents/agent-memory#external-knowledge) - Wiring a retrieval tool into an agent
* [Agent Tools](/agents/agent-tools) - The tool interface retrieval code plugs into