# API Documentation

## ModelHandler

### `generate(prompt, **kwargs)`

Generate an image from a text prompt.

**Parameters:**
- `prompt` (str): Text prompt for generation
- `negative_prompt` (str, optional): Negative prompt. Default: ""
- `guidance_scale` (float, optional): Guidance scale. Default: 7.5
- `num_inference_steps` (int, optional): Number of inference steps. Default: 50
- `seed` (int, optional): Random seed. Default: None (random)
- `width` (int, optional): Image width. Default: 1024
- `height` (int, optional): Image height. Default: 1024
- `cfg_scale` (float, optional): CFG scale. Default: None (uses guidance_scale)
- `lora_strength` (float, optional): LoRA strength. Default: 1.0

**Returns:**
- `tuple`: (image, metadata_dict)

**Example:**
```python
from src.model_handler import ModelHandler

handler = ModelHandler()
image, metadata = handler.generate(
    prompt="seamless wood texture",
    guidance_scale=7.5,
    num_inference_steps=50,
    seed=12345,
)
```

### `generate_batch(prompts, base_params=None)`

Generate multiple images in batch.

**Parameters:**
- `prompts` (List[str]): List of prompts to generate
- `base_params` (dict, optional): Base parameters for all generations

**Returns:**
- `Generator`: Yields (image, metadata, index) tuples

**Example:**
```python
prompts = ["wood texture", "fabric texture", "metal texture"]
for image, metadata, idx in handler.generate_batch(prompts):
    # Process each image
    pass
```

## Image Processor

### `save_image(image, prompt, params, metadata=None)`

Save an image with metadata.

**Parameters:**
- `image` (PIL.Image): Image to save
- `prompt` (str): Prompt used
- `params` (dict): Generation parameters
- `metadata` (dict, optional): Additional metadata

**Returns:**
- `Path`: Path to saved image file

### `create_thumbnail(image, size=(256, 256))`

Create a thumbnail from an image.

**Parameters:**
- `image` (PIL.Image): Source image
- `size` (tuple): Thumbnail size (width, height)

**Returns:**
- `PIL.Image`: Thumbnail image

### `create_zip(files, output_path)`

Create a ZIP archive from multiple files.

**Parameters:**
- `files` (List[Path]): List of file paths
- `output_path` (Path): Output ZIP path

**Returns:**
- `Path`: Path to created ZIP file

## Presets

### `get_preset(name)`

Get a preset by name.

**Parameters:**
- `name` (str): Preset name

**Returns:**
- `dict` or `None`: Preset dictionary

### `list_presets()`

List all available preset names.

**Returns:**
- `List[str]`: List of preset names

## Utils

### `validate_prompt(prompt, max_length=500)`

Validate a prompt string.

**Parameters:**
- `prompt` (str): Prompt to validate
- `max_length` (int): Maximum allowed length

**Returns:**
- `tuple`: (is_valid, error_message)

### `validate_params(params)`

Validate generation parameters.

**Parameters:**
- `params` (dict): Parameters to validate

**Returns:**
- `tuple`: (is_valid, error_message)