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

# API Reference Introduction

> Introduction to the Transfer Learning API

# Transfer Learning API Reference

Transfer Learning can be used not only as a CLI tool but also as a Python library in your own applications. This API reference documents the core components, classes, and functions available for developers.

## Installation

To use Transfer Learning as a library, install it using UV:

```bash theme={null}
uv pip install transfer-learning
```

Or using pip:

```bash theme={null}
pip install transfer-learning
```

## Basic Usage

Here's a simple example of using Transfer Learning in your Python code:

```python theme={null}
import asyncio
from transfer_learning.core.video_processor import process_videos_async
from transfer_learning.guide.generator import GuideGenerator

async def process_and_generate():
    # Process a video
    result = await process_videos_async("path/to/video.mp4")
    
    # Generate a guide
    generator = GuideGenerator(result["output_dir"])
    guide = await generator.generate()
    
    print(f"Guide generated: {guide}")

# Run the async function
asyncio.run(process_and_generate())
```

## Core Components

Transfer Learning is organized into several core components:

### Video Processing

* [Video Processor](/api-reference/video-processor): Process videos and extract frames
* [Frame Extractor](/api-reference/frame-extractor): Extract frames from videos
* [Content Analyzer](/api-reference/content-analyzer): Analyze frame content using AI

### Audio Processing

* [Audio Transcriber](/api-reference/audio-transcriber): Transcribe audio from videos

### Guide Generation

* [Guide Generator](/api-reference/guide-generator): Generate step-by-step guides

### Utilities

* [Downloader](/api-reference/downloader): Download videos from various sources
* [Validation](/api-reference/validation): Validate inputs and outputs
* [Path Utilities](/api-reference/path-utils): Handle file and directory paths
* [Monitoring](/api-reference/monitoring): Logging and metrics collection

## Asynchronous API

Most of the Transfer Learning API is asynchronous, using Python's `async`/`await` syntax. This allows for efficient processing of multiple videos or frames concurrently.

```python theme={null}
import asyncio
from transfer_learning.core.video_processor import process_videos_async

async def process_multiple_videos():
    # Process multiple videos concurrently
    tasks = [
        process_videos_async("video1.mp4"),
        process_videos_async("video2.mp4"),
        process_videos_async("video3.mp4")
    ]
    results = await asyncio.gather(*tasks)
    return results

# Run the async function
results = asyncio.run(process_multiple_videos())
```

## Configuration

You can configure the library using the settings module:

```python theme={null}
from transfer_learning.config import settings

# Override settings
settings.batch_size = 20
settings.max_concurrent_batches = 8
settings.openai_api_key = "your-api-key"
```

## Error Handling

The library uses custom exceptions for error handling:

```python theme={null}
from transfer_learning.utils.exceptions import VideoProcessingError, GuideGenerationError

try:
    # Process a video
    result = await process_videos_async("path/to/video.mp4")
except VideoProcessingError as e:
    print(f"Error processing video: {e}")
```

## Next Steps

Explore the API reference for detailed documentation of each component:

* [Video Processor](/api-reference/video-processor)
* [Audio Transcriber](/api-reference/audio-transcriber)
* [Guide Generator](/api-reference/guide-generator)

For CLI usage, refer to the [CLI Commands](/cli/overview) documentation.