crewAI/docs/tools/youtube-video-search-tool.mdx

---
title: YoutubeVideoSearchTool
description: A tool for semantic search within YouTube video content using RAG capabilities
icon: video
---

## YoutubeVideoSearchTool

The YoutubeVideoSearchTool enables semantic search capabilities for YouTube video content using Retrieval-Augmented Generation (RAG). It processes video content and allows searching through transcripts and metadata using natural language queries.

## Installation

```bash
pip install 'crewai[tools]'
```

## Usage Example

```python
from crewai import Agent
from crewai_tools import YoutubeVideoSearchTool

# Method 1: Initialize with specific video
video_tool = YoutubeVideoSearchTool(
    youtube_video_url="https://www.youtube.com/watch?v=example"
)

# Method 2: Initialize without video (specify at runtime)
flexible_video_tool = YoutubeVideoSearchTool()

# Create an agent with the tool
researcher = Agent(
    role='Video Researcher',
    goal='Search and analyze video content',
    backstory='Expert at finding relevant information in videos.',
    tools=[video_tool],
    verbose=True
)
```

## Input Schema

### Fixed Video Schema (when URL provided during initialization)
```python
class FixedYoutubeVideoSearchToolSchema(BaseModel):
    search_query: str = Field(
        description="Mandatory search query you want to use to search the Youtube Video content"
    )
```

### Flexible Video Schema (when URL provided at runtime)
```python
class YoutubeVideoSearchToolSchema(FixedYoutubeVideoSearchToolSchema):
    youtube_video_url: str = Field(
        description="Mandatory youtube_video_url path you want to search"
    )
```

## Function Signature

```python
def __init__(
    self,
    youtube_video_url: Optional[str] = None,
    **kwargs
):
    """
    Initialize the YouTube video search tool.

    Args:
        youtube_video_url (Optional[str]): URL of YouTube video (optional)
        **kwargs: Additional arguments for RAG tool configuration
    """

def _run(
    self,
    search_query: str,
    **kwargs: Any
) -> str:
    """
    Execute semantic search on video content.

    Args:
        search_query (str): Query to search in the video
        **kwargs: Additional arguments including youtube_video_url if not initialized

    Returns:
        str: Relevant content from the video matching the query
    """
```

## Best Practices

1. Video URL Management:
   - Use complete YouTube URLs
   - Verify video accessibility
   - Handle region restrictions

2. Search Optimization:
   - Use specific, focused queries
   - Consider video context
   - Test with sample queries first

3. Performance Considerations:
   - Pre-initialize for repeated searches
   - Handle long videos appropriately
   - Monitor processing time

4. Error Handling:
   - Verify video availability
   - Handle unavailable videos
   - Manage API limitations

## Integration Example

```python
from crewai import Agent, Task, Crew
from crewai_tools import YoutubeVideoSearchTool

# Initialize tool with specific video
video_tool = YoutubeVideoSearchTool(
    youtube_video_url="https://www.youtube.com/watch?v=example"
)

# Create agent
researcher = Agent(
    role='Video Researcher',
    goal='Extract insights from video content',
    backstory='Expert at analyzing video content.',
    tools=[video_tool]
)

# Define task
research_task = Task(
    description="""Find all mentions of machine learning 
    applications from the video content.""",
    agent=researcher
)

# The tool will use:
# {
#   "search_query": "machine learning applications"
# }

# Create crew
crew = Crew(
    agents=[researcher],
    tasks=[research_task]
)

# Execute
result = crew.kickoff()
```

## Advanced Usage

### Dynamic Video Selection
```python
# Initialize without video URL
flexible_tool = YoutubeVideoSearchTool()

# Search different videos
tech_results = flexible_tool.run(
    search_query="quantum computing",
    youtube_video_url="https://youtube.com/watch?v=tech123"
)

science_results = flexible_tool.run(
    search_query="particle physics",
    youtube_video_url="https://youtube.com/watch?v=science456"
)
```

### Multiple Video Analysis
```python
# Create tools for different videos
tech_tool = YoutubeVideoSearchTool(
    youtube_video_url="https://youtube.com/watch?v=tech123"
)
science_tool = YoutubeVideoSearchTool(
    youtube_video_url="https://youtube.com/watch?v=science456"
)

# Create agent with multiple tools
analyst = Agent(
    role='Content Analyst',
    goal='Cross-reference multiple videos',
    tools=[tech_tool, science_tool]
)
```

### Error Handling Example
```python
try:
    video_tool = YoutubeVideoSearchTool()
    results = video_tool.run(
        search_query="key concepts",
        youtube_video_url="https://youtube.com/watch?v=example"
    )
    print(results)
except Exception as e:
    print(f"Error processing video: {str(e)}")
```

## Notes

- Inherits from RagTool
- Uses embedchain for processing
- Supports semantic search
- Dynamic video specification
- Efficient content retrieval
- Thread-safe operations
- Maintains search context
- Handles video transcripts
- Processes video metadata
- Memory-efficient processing