import os
import sys
import warnings

# HF Spaces currently emits a noisy FutureWarning from a vendored dependency:
# `torch.distributed.reduce_op` is deprecated ...
warnings.filterwarnings(
    "ignore",
    category=FutureWarning,
    message=r"`torch\.distributed\.reduce_op` is deprecated.*",
    module=r"spaces\._vendor\.codefind\.registry",
)
import gradio as gr

from caption_blip import UserOptions, caption_image_path, caption_video


# Some environments (notably containers) can emit noisy asyncio unraisable exceptions
# on shutdown like: ValueError: Invalid file descriptor: -1
# This is harmless but can confuse users and clutter logs.
def _unraisablehook_filter_asyncio_fd(unraisable: "sys.UnraisableHookArgs") -> None:  # type: ignore[name-defined]
    exc = unraisable.exc_value
    if isinstance(exc, ValueError) and "Invalid file descriptor" in str(exc):
        return
    sys.__unraisablehook__(unraisable)


sys.unraisablehook = _unraisablehook_filter_asyncio_fd


def _require_openrouter() -> None:
    if not os.environ.get("OPENROUTER_API_KEY"):
        raise gr.Error(
            "Missing server secret OPENROUTER_API_KEY. "
            "In Hugging Face Spaces: Settings → Secrets → add OPENROUTER_API_KEY, then restart the Space."
        )


def _run_image(
    image_path: str,
    text_style: str,
    platform: str,
    keywords: str,
    description: str,
    hashtags: bool,
    emojis: bool,
    language: str,
    caption_length: str,
) -> str:
    _require_openrouter()
    opts = UserOptions(
        text_style=text_style,
        platform=platform,
        keywords=keywords or None,
        description=description or None,
        hashtags=hashtags,
        emojis=emojis,
        language=language,
        caption_length=caption_length,
    )

    base = caption_image_path(image_path)
    from caption_blip import compose_image_caption

    try:
        return compose_image_caption(base, opts, use_openrouter=True)
    except RuntimeError as e:
        msg = str(e)
        if "openrouter" in msg.lower() or "timed out" in msg.lower() or "timeout" in msg.lower():
            raise gr.Error(
                "The AI service (OpenRouter) timed out. Please try again in a moment. "
                "If this keeps happening, switch to a faster OpenRouter model or increase OPENROUTER_TIMEOUT_S."
            )
        raise


def _run_video(
    video_path: str,
    text_style: str,
    platform: str,
    keywords: str,
    description: str,
    hashtags: bool,
    emojis: bool,
    language: str,
    caption_length: str,
) -> str:
    _require_openrouter()
    opts = UserOptions(
        text_style=text_style,
        platform=platform,
        keywords=keywords or None,
        description=description or None,
        hashtags=hashtags,
        emojis=emojis,
        language=language,
        caption_length=caption_length,
    )
    try:
        return caption_video(video_path, opts, use_openrouter=True)
    except RuntimeError as e:
        msg = str(e)
        if "openrouter" in msg.lower() or "timed out" in msg.lower() or "timeout" in msg.lower():
            raise gr.Error(
                "The AI service (OpenRouter) timed out. Please try again in a moment. "
                "If this keeps happening, switch to a faster OpenRouter model or increase OPENROUTER_TIMEOUT_S."
            )
        raise


def build_demo() -> gr.Blocks:
    with gr.Blocks(title="AI Caption Generator") as demo:
        gr.Markdown("# AI Caption Generator\nUpload an image or a short video and get a caption.")

        platforms = ["Instagram", "LinkedIn", "X(Twitter)", "TikTok", "Facebook", "Pinterest", "Threads"]
        languages = ["English", "French", "Spanish", "German", "Italian", "Arabic", "Chinese"]
        lengths = ["small", "medium", "large"]

        with gr.Tab("Image"):
            image = gr.Image(type="filepath", label="Upload image")
            out = gr.Textbox(label="Caption", lines=4)

            with gr.Row():
                text_style = gr.Dropdown(
                    [
                        "casual",
                        "formal",
                        "educational",
                        "funny",
                        "dry",
                        "direct",
                        "Storytelling",
                        "Emotional",
                        "Hook-first",
                        "Motivational",
                        "Call-to-Action",
                    ],
                    value="educational",
                    label="Text style",
                )
                platform = gr.Dropdown(platforms, value="LinkedIn", label="Platform")

            keywords = gr.Textbox(label="Keywords (optional)", placeholder="e.g. AI, startups, productivity")
            description = gr.Textbox(label="Description / additional context (optional)", lines=3, placeholder="Add any extra info you want reflected in the caption")

            with gr.Row():
                language = gr.Dropdown(languages, value="English", label="Language")
                caption_length = gr.Dropdown(lengths, value="medium", label="Caption length")

            with gr.Row():
                hashtags = gr.Checkbox(value=False, label="Add hashtags")
                emojis = gr.Checkbox(value=False, label="Use emojis")

            btn = gr.Button("Generate caption")
            btn.click(
                _run_image,
                inputs=[image, text_style, platform, keywords, description, hashtags, emojis, language, caption_length],
                outputs=[out],
                api_name="caption_image",
            )

        with gr.Tab("Video"):
            video = gr.Video(label="Upload video")
            outv = gr.Textbox(label="Caption", lines=5)

            with gr.Row():
                text_style_v = gr.Dropdown(
                    [
                        "casual",
                        "formal",
                        "educational",
                        "funny",
                        "dry",
                        "direct",
                        "Storytelling",
                        "Emotional",
                        "Hook-first",
                        "Motivational",
                        "Call-to-Action",
                    ],
                    value="educational",
                    label="Text style",
                )
                platform_v = gr.Dropdown(platforms, value="LinkedIn", label="Platform")

            keywords_v = gr.Textbox(label="Keywords (optional)", placeholder="e.g. product launch, demo")
            description_v = gr.Textbox(label="Description / additional context (optional)", lines=3, placeholder="Add any extra info you want reflected in the caption")

            with gr.Row():
                language_v = gr.Dropdown(languages, value="English", label="Language")
                caption_length_v = gr.Dropdown(lengths, value="medium", label="Caption length")

            with gr.Row():
                hashtags_v = gr.Checkbox(value=False, label="Add hashtags")
                emojis_v = gr.Checkbox(value=False, label="Use emojis")

            btnv = gr.Button("Generate caption")
            btnv.click(
                _run_video,
                inputs=[video, text_style_v, platform_v, keywords_v, description_v, hashtags_v, emojis_v, language_v, caption_length_v],
                outputs=[outv],
                api_name="caption_video",
            )

        gr.Markdown(
            "**Notes**\n"
            "- First run downloads the BLIP model from Hugging Face unless `BLIP_OFFLINE=1`.\n"
            "- This demo requires the server-side secret `OPENROUTER_API_KEY`."
        )

    return demo


# Hugging Face Spaces expects a top-level variable named `demo` (or `app`).
demo = build_demo()
demo.queue()


if __name__ == "__main__":
    demo.launch(
        server_name="0.0.0.0",
        server_port=int(os.environ.get("PORT", "7860")),
        ssr_mode=False,
    )