"""
Gradio widget builders for the interpretability app.

This module provides small UI factory functions:
- create_model_selector: dropdown for selecting a model size/name.
- create_feature_level_selector: radio control for feature granularity (word/sentence/paragraph).
- create_attribution_method_toggle: radio control for attribution method.
"""

import gradio as gr
from typing import List


def create_model_selector() -> gr.Dropdown:
    """
    Create a dropdown for model selection.

    Usage:
        models = list_models()  # from loader/models.py (optional API)
    """
    return gr.Dropdown(
        choices=[
            ("Qwen3 4B Instruct", "small"),
            ("Mistral 7B Instruct v0.2", "medium"),
            ("Qwen3 30B Instruct", "large"),
        ],
        value="small",
        label="Model",
        interactive=True,
        elem_id="model-selector",
        elem_classes=["bubble-select"],
    )


def create_multimodal_model_selector() -> gr.Dropdown:
    """
    Create a dropdown for multimodal (image-capable) model selection.

    Keys must match loader/models_mm_vllm.py.
    """
    return gr.Dropdown(
        choices=["vl_small", "vl_large"],
        value="vl_small",
        label="Multimodal Model",
        interactive=True,
        elem_id="multimodal-model-selector",
    )


def create_feature_level_selector(value: str = "sentence") -> gr.Radio:
    """Create the feature granularity selector."""
    return gr.Radio(
        choices=["word", "sentence", "paragraph"],
        value=value,
        label="Feature Level",
        interactive=True,
    )


def create_attribution_method_toggle(methods: List[str] | None = None) -> gr.Radio:
    """Create the attribution method toggle."""
    choices = methods or ["shapley", "banzhaf", "influence"]
    default_value = choices[0] if choices else "shapley"
    return gr.Radio(
        choices=choices,
        value=default_value,
        label="Attribution Method",
        interactive=True,
    )