> ## 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.

# YouTube Search PraisonAI Integration

> Guide for integrating YouTube search capabilities with PraisonAI agents using the YouTube Search API

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

agent = Agent(
    name="YouTubeAgent",
    instructions="Extract and analyse YouTube video content.",
)
agent.start("Summarise the key points from this video: https://www.youtube.com/watch?v=example")
```

The user shares a video link or search topic; the agent finds content and summarises transcripts or metadata.

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
graph LR
    U[Input] --> A[Agent]
    A --> T[Tool]
    T --> O[Output]

    classDef agent fill:#8B0000,color:#fff
    classDef tool fill:#189AB4,color:#fff

    class A agent
    class U,O tool
    class T tool
```

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
sequenceDiagram
    participant User
    participant Agent
    participant Feature as YouTube Search PraisonAI Integration

    User->>Agent: Request
    Agent->>Feature: Process request
    Feature-->>Agent: Result
    Agent-->>User: Response
```

# YouTube Search PraisonAI Integration

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
pip install youtube_search praisonai langchain_community langchain
```

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
# tools.py
from langchain_community.tools import YouTubeSearchTool
```

```yaml theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
# agents.yaml
framework: crewai
topic: research about the causes of lung disease
agents:  # Canonical: use 'agents' instead of 'roles'
  research_analyst:
    instructions:  # Canonical: use 'instructions' instead of 'backstory' Experienced in analyzing scientific data related to respiratory health.
    goal: Analyze data on lung diseases
    role: Research Analyst
    tasks:
      data_analysis:
        description: Gather and analyze data on the causes and risk factors of lung
          diseases.
        expected_output: Report detailing key findings on lung disease causes.
    tools:
    - 'YouTubeSearchTool'
```

## Quick Start

<Steps>
  <Step title="Install">
    ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
    pip install praisonaiagents youtube-transcript-api
    ```
  </Step>

  <Step title="Extract video content with agent">
    ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
    from praisonaiagents import Agent

    agent = Agent(
        name="YouTubeAgent",
        instructions="Extract and analyze YouTube video content.",
    )

    agent.start("Summarize the key points from this video: https://www.youtube.com/watch?v=example")
    ```
  </Step>
</Steps>

## Best Practices

<AccordionGroup>
  <Accordion title="Use transcript extraction for content analysis">
    YouTube transcripts provide the full spoken content - much richer than titles or descriptions.
  </Accordion>

  <Accordion title="Search before extracting">
    Search for videos first, then extract transcripts from the most relevant ones.
  </Accordion>

  <Accordion title="Handle missing transcripts">
    Not all videos have transcripts - always check for `None` before processing.
  </Accordion>

  <Accordion title="Chunk long transcripts">
    Long video transcripts may exceed context limits - chunk them into segments for analysis.
  </Accordion>
</AccordionGroup>

## Related

<CardGroup cols={2}>
  <Card title="Custom Tools" icon="wrench" href="/docs/tools/custom">
    Build your own agent tools
  </Card>

  <Card title="Tools Overview" icon="toolbox" href="/docs/tools/tools">
    Browse PraisonAI tool documentation
  </Card>
</CardGroup>