> ## 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.

# Knowledge

> Give agents access to your documents and data

Knowledge lets agents answer questions using your documents, files, and data.

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
graph LR
    subgraph "Knowledge Base"
        D[📄 Documents] --> K[📚 Knowledge]
        K --> A[🤖 Agent]
        A --> R[💬 Informed Response]
    end
    
    classDef docs fill:#6366F1,stroke:#7C90A0,color:#fff
    classDef knowledge fill:#F59E0B,stroke:#7C90A0,color:#fff
    classDef output fill:#10B981,stroke:#7C90A0,color:#fff
    
    class D docs
    class K,A knowledge
    class R output
```

## Quick Start

<Steps>
  <Step title="Create Knowledge Base">
    ```rust theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
    use praisonai::{Knowledge, Document};

    // Create knowledge instance
    let mut knowledge = Knowledge::new().build()?;

    // Add content directly
    knowledge.add("Our refund policy allows returns within 30 days.", None)?;
    knowledge.add("Premium members get free shipping.", None)?;
    ```
  </Step>

  <Step title="Add Documents">
    ```rust theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
    use praisonai::{Knowledge, Document};

    let mut knowledge = Knowledge::new().build()?;

    // Create document with metadata
    let doc = Document::new("Company policies and procedures...")
        .source("policies.pdf")
        .filename("policies.pdf");

    knowledge.add_document(doc)?;
    ```
  </Step>

  <Step title="Search Knowledge">
    ```rust theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
    use praisonai::Knowledge;

    let knowledge = Knowledge::new().build()?;
    // ... add content ...

    // Search with limit
    let results = knowledge.search("refund policy", 5)?;

    for item in results.results {
        println!("{}: {}", item.score, item.text);
    }
    ```
  </Step>
</Steps>

***

## How It Works

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
sequenceDiagram
    participant User
    participant App
    participant Knowledge
    
    User->>App: "What is the refund policy?"
    App->>Knowledge: search("refund policy", 5)
    Knowledge-->>App: SearchResult with items
    App-->>User: "Our refund policy allows..."
```

***

## Knowledge Methods

| Method                   | Signature                                                       | Description         |
| ------------------------ | --------------------------------------------------------------- | ------------------- |
| `add(content, metadata)` | `fn add(&mut self, &str, Option<HashMap>) -> Result<AddResult>` | Add text content    |
| `add_document(doc)`      | `fn add_document(&mut self, Document) -> Result<AddResult>`     | Add a document      |
| `search(query, limit)`   | `fn search(&self, &str, usize) -> Result<SearchResult>`         | Search knowledge    |
| `get(id)`                | `fn get(&self, &str) -> Option<&Document>`                      | Get document by ID  |
| `delete(id)`             | `fn delete(&mut self, &str) -> bool`                            | Delete document     |
| `clear()`                | `fn clear(&mut self)`                                           | Clear all documents |
| `len()`                  | `fn len(&self) -> usize`                                        | Document count      |
| `chunk(text)`            | `fn chunk(&self, &str) -> Vec<String>`                          | Chunk text          |

***

## KnowledgeBuilder Methods

| Method                  | Signature                                          | Description         |
| ----------------------- | -------------------------------------------------- | ------------------- |
| `config(cfg)`           | `fn config(KnowledgeConfig) -> Self`               | Set full config     |
| `chunking(cfg)`         | `fn chunking(ChunkingConfig) -> Self`              | Set chunking config |
| `retrieval_strategy(s)` | `fn retrieval_strategy(RetrievalStrategy) -> Self` | Set retrieval       |
| `build()`               | `fn build(self) -> Result<Knowledge>`              | Build instance      |

***

## Best Practices

<AccordionGroup>
  <Accordion title="Use specific file types">
    PDF, TXT, and MD files work best. Keep documents focused and organized.
  </Accordion>

  <Accordion title="Chunk size matters">
    Smaller chunks (500-1000) for specific answers, larger for context.
  </Accordion>

  <Accordion title="Update knowledge regularly">
    Rebuild knowledge base when documents change.
  </Accordion>
</AccordionGroup>

***

## Related

<CardGroup cols={2}>
  <Card title="Agent" icon="robot" href="/docs/rust/agent">
    Agent configuration
  </Card>

  <Card title="Memory" icon="brain" href="/docs/rust/memory">
    Conversation memory
  </Card>
</CardGroup>