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

# models • AI Agent SDK

> RAG Data Models for PraisonAI Agents.

# models

<Badge color="blue">AI Agent</Badge>

RAG Data Models for PraisonAI Agents.

Lightweight dataclasses for RAG results and configuration.
No heavy imports - only stdlib and typing.

## Import

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents.rag import models
```

## Classes

<CardGroup cols={2}>
  <Card title="RetrievalStrategy" icon="brackets-curly" href="../classes/RetrievalStrategy">
    Available retrieval strategies for RAG.
  </Card>

  <Card title="Citation" icon="brackets-curly" href="../classes/Citation">
    Source citation for RAG answers.
  </Card>

  <Card title="ContextPack" icon="brackets-curly" href="../classes/ContextPack">
    Context pack for orchestrator pattern - retrieval without generation.
  </Card>

  <Card title="RAGResult" icon="brackets-curly" href="../classes/RAGResult">
    Result from a RAG query.
  </Card>

  <Card title="RAGConfig" icon="brackets-curly" href="../classes/RAGConfig">
    Configuration for RAG pipeline.
  </Card>
</CardGroup>
