import gradio as gr
import json

def build_json(
    api_key,
    reference_image,
    scene,
    subject_type,
    age_range,
    hair,
    makeup,
    jewellery,
    top,
    bottom,
    footwear,
    wardrobe_notes,
    pose_angle,
    body_pose,
    hands_pose,
    framing,
    camera_device,
    flash,
    orientation,
    aspect_ratio,
    distance,
    focus,
    texture,
    sharpness,
    color,
    effects,
    background_environment,
    background_props,
    style_genre,
    authenticity,
    use_original_structure,
    face_description,
    ban_mirror,
    ban_phone,
    ban_selfie,
    ban_grainy,
    ban_harsh_flash,
    ban_logos,
    ban_nsfw,
    ban_cropped_feet,
    output_count,
    output_size,
    safety,
    variant_name,
    variant_angle,
):
    banned_items = []
    if ban_mirror:
        banned_items.append("mirror")
    if ban_phone:
        banned_items.append("phone")
    if ban_selfie:
        banned_items.append("selfie look")
    if ban_grainy:
        banned_items.append("grainy noise")
    if ban_harsh_flash:
        banned_items.append("harsh LED flash")
    if ban_logos:
        banned_items.append("logos/brand text")
    if ban_nsfw:
        banned_items.append("nsfw")
    if ban_cropped_feet:
        banned_items.append("cropped feet")

    output_json = {
        "scene": scene,
        "subject": {
            "type": subject_type,
            "age_range": age_range,
            "hair": hair,
            "makeup": makeup,
            "jewellery": jewellery,
        },
        "wardrobe": {
            "top": top,
            "bottom": bottom,
            "footwear": footwear,
            "notes": wardrobe_notes,
        },
        "pose": {
            "angle": pose_angle,
            "body": body_pose,
            "hands": hands_pose,
            "framing": framing,
        },
        "camera": {
            "device": camera_device,
            "flash": flash,
            "orientation": orientation,
            "aspect_ratio": aspect_ratio,
            "distance": distance,
            "focus": focus,
        },
        "look": {
            "texture": texture,
            "sharpness": sharpness,
            "color": color,
            "effects": effects,
        },
        "background": {
            "environment": background_environment,
            "props": background_props,
        },
        "style": {"genre": style_genre, "authenticity": authenticity},
        "reference_face": {
            "use_original_structure": use_original_structure,
            "description": face_description,
        },
        "ban": banned_items,
        "output": {
            "count": output_count,
            "size": output_size,
            "safety": safety
        },
        "variants": [{"name": variant_name, "angle": variant_angle}],
    }

    # The user's API key is available in the 'api_key' variable.
    # You can now use this key and the reference_image path to call the
    # gemini nano banana API with the generated 'output_json'.

    # For this example, we will just return the generated JSON.
    return json.dumps(output_json, indent=4)


with gr.Blocks() as demo:
    gr.Markdown("# Gemini Nano Banana Image Generator Interface")
    gr.Markdown(
        "Fill in the details below to generate the JSON input for the image generation model."
    )

    with gr.Tabs():
        with gr.TabItem("Authentication and Image"):
            api_key_input = gr.Textbox(
                label="Gemini Nano Banana API Key", type="password"
            )
            reference_image_input = gr.Image(
                label="Reference Image", type="filepath"
            )

        with gr.TabItem("Scene and Subject"):
            with gr.Row():
                scene_input = gr.Textbox(
                    label="Scene", value="cinematic outdoor portrait; professional photography"
                )
            with gr.Row():
                subject_type_input = gr.Textbox(
                    label="Subject Type", value="adult woman (idol vibe)"
                )
                age_range_input = gr.Textbox(label="Age Range", value="20s")
            with gr.Row():
                hair_input = gr.Textbox(
                    label="Hair",
                    value="straight or styled natural open hair with natural shine",
                )
                makeup_input = gr.Textbox(
                    label="Makeup", value="glossy lips, soft eyeliner, luminous skin"
                )
                jewellery_input = gr.Textbox(
                    label="Jewellery", value="small hoops, thin chain, subtle bracelets"
                )

        with gr.TabItem("Wardrobe"):
            with gr.Row():
                top_input = gr.Textbox(label="Top", value="basic tee or camisole")
                bottom_input = gr.Textbox(
                    label="Bottom", value="denim shorts or mini skirt"
                )
                footwear_input = gr.Textbox(
                    label="Footwear", value="sneakers or ankle boots"
                )
            with gr.Row():
                wardrobe_notes_input = gr.Textbox(
                    label="Wardrobe Notes",
                    value="casual modern look, styled for natural setting",
                )

        with gr.TabItem("Pose and Framing"):
            with gr.Row():
                pose_angle_input = gr.Dropdown(
                    label="Pose Angle",
                    choices=["three-quarter", "full body"],
                    value="three-quarter",
                )
                body_pose_input = gr.Textbox(
                    label="Body Pose",
                    value="standing or walking casually, relaxed natural posture",
                )
            with gr.Row():
                hands_pose_input = gr.Textbox(
                    label="Hands Pose",
                    value="one resting by side or touching hair, the other relaxed",
                )
                framing_input = gr.Dropdown(
                    label="Framing",
                    choices=["head-to-toe", "waist-up"],
                    value="waist-up",
                )

        with gr.TabItem("Camera and Look"):
            with gr.Row():
                camera_device_input = gr.Textbox(
                    label="Camera Device",
                    value="professional cinema camera / DSLR with prime lens",
                )
                flash_input = gr.Textbox(
                    label="Flash", value="none; natural golden hour light or soft reflectors"
                )
            with gr.Row():
                orientation_input = gr.Dropdown(
                    label="Orientation", choices=["vertical", "horizontal"], value="vertical"
                )
                aspect_ratio_input = gr.Dropdown(
                    label="Aspect Ratio", choices=["16:9", "3:2", "4:3", "1:1"], value="16:9"
                )
            with gr.Row():
                distance_input = gr.Textbox(
                    label="Distance", value="cinematic portrait distance with shallow depth"
                )
                focus_input = gr.Textbox(
                    label="Focus", value="sharp on subject; soft bokeh background"
                )
            with gr.Row():
                texture_input = gr.Textbox(
                    label="Texture", value="smooth high-resolution detail"
                )
                sharpness_input = gr.Textbox(
                    label="Sharpness", value="very high; crisp cinematic clarity"
                )
            with gr.Row():
                color_input = gr.Textbox(
                    label="Color", value="warm cinematic grading; golden tones and soft contrast"
                )
                effects_input = gr.Textbox(
                    label="Effects",
                    value="subtle film grain; natural light flares, depth of field",
                )

        with gr.TabItem("Background and Style"):
            with gr.Row():
                background_environment_input = gr.Textbox(
                    label="Background Environment",
                    value="nature setting — forest, park, or meadow with soft light",
                )
                background_props_input = gr.Textbox(
                    label="Background Props", value="none; focus on subject against natural backdrop"
                )
            with gr.Row():
                style_genre_input = gr.Textbox(
                    label="Style Genre", value="cinematic portrait photography"
                )
                authenticity_input = gr.Textbox(
                    label="Authenticity", value="natural, elegant, polished"
                )

        with gr.TabItem("Reference Face and Bans"):
            with gr.Row():
                use_original_structure_input = gr.Checkbox(
                    label="Use Original Face Structure", value=True
                )
            with gr.Row():
                face_description_input = gr.Textbox(
                    label="Face Description",
                    value="maintain the same face shape, features, and proportions as in the provided reference image",
                )
            with gr.Row():
                gr.Markdown("#### Banned Items")
            with gr.Row():
                ban_mirror_input = gr.Checkbox(label="Mirror")
                ban_phone_input = gr.Checkbox(label="Phone")
                ban_selfie_input = gr.Checkbox(label="Selfie Look")
                ban_grainy_input = gr.Checkbox(label="Grainy Noise")
            with gr.Row():
                ban_harsh_flash_input = gr.Checkbox(label="Harsh LED Flash")
                ban_logos_input = gr.Checkbox(label="Logos/Brand Text")
                ban_nsfw_input = gr.Checkbox(label="NSFW")
                ban_cropped_feet_input = gr.Checkbox(label="Cropped Feet")

        with gr.TabItem("Output and Variants"):
            with gr.Row():
                output_count_input = gr.Slider(
                    label="Output Count", minimum=1, maximum=10, step=1, value=1
                )
                output_size_input = gr.Textbox(label="Output Size", value="1920x1080")
                safety_input = gr.Dropdown(
                    label="Safety", choices=["strict", "moderate", "none"], value="strict"
                )
            with gr.Row():
                variant_name_input = gr.Textbox(
                    label="Variant Name", value="cinematic_nature_fullbody"
                )
                variant_angle_input = gr.Textbox(
                    label="Variant Angle",
                    value="full-body shot in meadow or forest path, subject centered with depth of field",
                )

    generate_button = gr.Button("Generate JSON")
    json_output = gr.JSON(label="Generated JSON")

    generate_button.click(
        fn=build_json,
        inputs=[
            api_key_input,
            reference_image_input,
            scene_input,
            subject_type_input,
            age_range_input,
            hair_input,
            makeup_input,
            jewellery_input,
            top_input,
            bottom_input,
            footwear_input,
            wardrobe_notes_input,
            pose_angle_input,
            body_pose_input,
            hands_pose_input,
            framing_input,
            camera_device_input,
            flash_input,
            orientation_input,
            aspect_ratio_input,
            distance_input,
            focus_input,
            texture_input,
            sharpness_input,
            color_input,
            effects_input,
            background_environment_input,
            background_props_input,
            style_genre_input,
            authenticity_input,
            use_original_structure_input,
            face_description_input,
            ban_mirror_input,
            ban_phone_input,
            ban_selfie_input,
            ban_grainy_input,
            ban_harsh_flash_input,
            ban_logos_input,
            ban_nsfw_input,
            ban_cropped_feet_input,
            output_count_input,
            output_size_input,
            safety_input,
            variant_name_input,
            variant_angle_input,
        ],
        outputs=json_output,
    )

if __name__ == "__main__":
    demo.launch()