# validation.py

## Purpose
Input validation utilities for Nano Banana Streamlit. Validates user inputs, parameters, and system state to ensure data integrity and provide clear error messages.

## Responsibilities
- Validate generation parameters (temperature, aspect ratio, backend)
- Validate text inputs (prompts, character names)
- Validate images (format, dimensions, file size)
- Validate complete generation requests
- Check backend availability
- Provide clear, user-friendly error messages

## Dependencies

### Imports
- `pathlib.Path` - File path operations
- `PIL.Image` - Image validation
- `config.settings.Settings` - Validation constraints
- `utils.logging_utils.get_logger` - Logging validation errors

### Used By
- All UI pages - Validate user inputs before submission
- All services - Validate parameters before generation
- Backend clients - Validate configuration
- `models/generation_request.py` - Validate request objects

## Public Interface

All validation functions return `Tuple[bool, Optional[str]]`:
- `(True, None)` if valid
- `(False, error_message)` if invalid

### Parameter Validation

#### `validate_temperature(temperature: float) -> Tuple[bool, Optional[str]]`
Validates temperature is in valid range [0.0, 1.0].

**Example:**
```python
valid, error = validate_temperature(0.5)
if not valid:
    st.error(error)
```

#### `validate_aspect_ratio(aspect_ratio: str) -> Tuple[bool, Optional[str]]`
Validates aspect ratio is in Settings.ASPECT_RATIOS.

Accepts both display names ("16:9 (1344x768)") and values ("16:9").

**Example:**
```python
valid, error = validate_aspect_ratio("16:9")
if valid:
    # Use aspect ratio
    pass
```

#### `validate_backend(backend: str) -> Tuple[bool, Optional[str]]`
Validates backend is in Settings.AVAILABLE_BACKENDS.

**Example:**
```python
valid, error = validate_backend("Gemini API (Cloud)")
```

#### `validate_prompt(prompt: str, min_length: int = 1, max_length: int = 5000) -> Tuple[bool, Optional[str]]`
Validates text prompt length.

**Parameters:**
- `prompt`: Text to validate
- `min_length`: Minimum length (default: 1)
- `max_length`: Maximum length (default: 5000)

**Example:**
```python
valid, error = validate_prompt(user_input, min_length=10)
if not valid:
    st.warning(error)
```

#### `validate_character_name(name: str) -> Tuple[bool, Optional[str]]`
Validates character name (1-100 characters).

**Example:**
```python
valid, error = validate_character_name(character_name)
if not valid:
    st.error(error)
    return
```

### Image Validation

#### `validate_image(image: Image.Image) -> Tuple[bool, Optional[str]]`
Validates PIL Image object.

**Checks:**
- Is valid Image instance
- Dimensions > 0
- Dimensions < 8192x8192 (reasonable limit)
- Mode is supported (RGB, RGBA, L, P)

**Example:**
```python
valid, error = validate_image(uploaded_image)
if not valid:
    st.error(f"Invalid image: {error}")
```

#### `validate_image_file(file_path: Path) -> Tuple[bool, Optional[str]]`
Validates image file on disk.

**Checks:**
- File exists
- Is a file (not directory)
- Has valid extension (.png, .jpg, .jpeg, .webp, .bmp)
- Can be opened as image
- Passes validate_image() checks

**Example:**
```python
valid, error = validate_image_file(Path("character.png"))
if valid:
    image = Image.open("character.png")
```

#### `validate_image_upload_size(file_size_bytes: int) -> Tuple[bool, Optional[str]]`
Validates uploaded file size against Settings.MAX_IMAGE_UPLOAD_SIZE.

**Example:**
```python
if uploaded_file:
    valid, error = validate_image_upload_size(uploaded_file.size)
    if not valid:
        st.error(error)
```

### Request Validation

#### `validate_generation_request(...) -> Tuple[bool, Optional[str]]`
Validates complete generation request.

**Parameters:**
- `prompt`: Text prompt
- `backend`: Backend name
- `aspect_ratio`: Aspect ratio
- `temperature`: Temperature value
- `input_images`: Optional list of input images

**Validates:**
- All individual parameters
- Input images (if provided, max 3)

**Example:**
```python
valid, error = validate_generation_request(
    prompt=prompt,
    backend=backend,
    aspect_ratio=aspect_ratio,
    temperature=temperature,
    input_images=[img1, img2]
)

if not valid:
    st.error(error)
    return

# Proceed with generation
result = generate(...)
```

#### `validate_character_forge_request(...) -> Tuple[bool, Optional[str]]`
Validates Character Forge-specific request.

**Parameters:**
- `character_name`: Character name
- `initial_image`: Initial image (Face Only / Full Body modes)
- `face_image`: Face image (Face+Body Separate)
- `body_image`: Body image (Face+Body Separate)
- `image_type`: Input mode type
- `backend`: Backend name

**Validates:**
- Character name
- Backend
- Correct images for selected mode

**Example:**
```python
valid, error = validate_character_forge_request(
    character_name="Hero",
    initial_image=None,
    face_image=face_img,
    body_image=body_img,
    image_type="Face + Body (Separate)",
    backend="Gemini API (Cloud)"
)

if not valid:
    st.error(error)
    return
```

### Backend Availability

#### `validate_backend_available(backend: str, api_key: Optional[str] = None) -> Tuple[bool, Optional[str]]`
Check if backend is available and configured.

**For Gemini:**
- Checks if API key is provided

**For OmniGen2:**
- Makes HTTP request to /health endpoint
- Checks server is responding and healthy

**Example:**
```python
valid, error = validate_backend_available(
    backend=st.session_state.backend,
    api_key=st.session_state.gemini_api_key
)

if not valid:
    st.warning(error)
    st.stop()
```

### Helper Functions

#### `raise_if_invalid(is_valid: bool, error_message: Optional[str], exception_type=ValueError)`
Convert validation result to exception.

**Example:**
```python
valid, error = validate_temperature(temp)
raise_if_invalid(valid, error, ValueError)
# Raises ValueError if invalid
```

#### `log_validation_error(validation_result: Tuple[bool, Optional[str]], context: str = "")`
Log validation error if validation failed.

**Example:**
```python
result = validate_prompt(prompt)
log_validation_error(result, context="user_input")
# Logs: "Validation failed [user_input]: Prompt must be at least 1 character(s)"
```

## Usage Examples

### Page Input Validation
```python
import streamlit as st
from utils.validation import (
    validate_prompt,
    validate_backend_available,
    validate_generation_request
)

# Get user inputs
prompt = st.text_area("Prompt")
backend = st.session_state.backend

if st.button("Generate"):
    # Validate prompt
    valid, error = validate_prompt(prompt, min_length=5)
    if not valid:
        st.error(error)
        st.stop()

    # Check backend available
    valid, error = validate_backend_available(backend, api_key)
    if not valid:
        st.warning(error)
        st.stop()

    # Validate complete request
    valid, error = validate_generation_request(
        prompt=prompt,
        backend=backend,
        aspect_ratio=aspect_ratio,
        temperature=temperature
    )
    if not valid:
        st.error(error)
        st.stop()

    # All valid - proceed
    result = generate_image(...)
```

### Service Parameter Validation
```python
from utils.validation import validate_generation_request, raise_if_invalid

class GenerationService:
    def generate(self, prompt, backend, aspect_ratio, temperature, ...):
        # Validate inputs
        valid, error = validate_generation_request(
            prompt, backend, aspect_ratio, temperature
        )
        raise_if_invalid(valid, error, ValueError)

        # Proceed with generation
        ...
```

### Backend Status Check
```python
import streamlit as st
from utils.validation import validate_backend_available

def render_backend_status(backend, api_key):
    valid, error = validate_backend_available(backend, api_key)

    if valid:
        st.success(f"✅ {backend}: Ready")
    else:
        st.error(f"❌ {backend}: {error}")
```

## Error Messages

All error messages are user-friendly and actionable:

**Good Examples:**
- ❌ "Prompt must be at least 5 character(s)" (specific, clear)
- ❌ "File too large: 25.3MB (max: 20MB)" (includes values)
- ❌ "OmniGen2 server not responding. Start it with: omnigen2_plugin/server.bat start" (includes solution)

**Not Used:**
- ❌ "Invalid input" (too vague)
- ❌ "Error" (no information)
- ❌ "NoneType has no attribute..." (technical, not user-friendly)

## Validation Strategy

### When to Validate

1. **Before submission** (UI layer)
   - Validate on button click
   - Show errors immediately
   - Prevent submission if invalid

2. **In service layer** (redundant validation)
   - Validate again for safety
   - Raise exceptions if invalid
   - Protects against programmatic calls

3. **Backend availability** (startup + on demand)
   - Check on app startup
   - Check when user switches backend
   - Check before expensive operations

### What NOT to Validate

- Don't validate Streamlit widget outputs (they enforce types)
- Don't validate internal function calls between modules
- Don't validate data from trusted sources (Settings constants)

## Known Limitations
- Backend availability check makes network request (slow)
- Image validation loads entire image into memory
- No async validation support
- No batch validation support
- No custom validation rules (extension mechanism)

## Future Improvements
- Add async validation for slow checks
- Add batch validation functions
- Add validation caching (avoid redundant checks)
- Add custom validation rule registration
- Add validation result serialization
- Add more granular image checks (color space, DPI, etc.)
- Add prompt content validation (detect harmful content)

## Testing
- Test all parameter validators with valid/invalid inputs
- Test boundary conditions (min/max values)
- Test image validators with various formats
- Test backend availability with server running/stopped
- Test request validators with complete/incomplete data
- Test error message clarity and helpfulness

## Related Files
- `config/settings.py` - Validation constraints
- `utils/logging_utils.py` - Error logging
- All UI pages - Input validation
- All services - Parameter validation
- `models/generation_request.py` - Request validation

## Performance Considerations
- validate_backend_available() makes network request (~100ms)
- validate_image() loads image into memory
- validate_image_file() opens file (I/O)
- All other validators are fast (<1ms)

## Change History
- 2025-10-23: Initial creation for Streamlit migration
  - Comprehensive parameter validation
  - Image validation utilities
  - Request validation functions
  - Backend availability checks
  - User-friendly error messages
  - Helper functions for error handling