import os

os.environ["PIP_ROOT_USER_ACTION"] = "ignore"
os.environ["GRADIO_SSR_MODE"] = "false"
os.environ["GRADIO_DISABLE_SSR"] = "1"

import gradio as gr
import spaces  # Mandatory for ZeroGPU Spaces

RESOURCES = [
    {
        "name": "Vidi (ByteDance)",
        "category": "Video Model",
        "description": "ByteDance's multimodal video understanding and generation framework.",
        "links": [
            ("🐙 GitHub", "https://github.com/bytedance/vidi"),
            ("🚀 Live Demo", "https://vidi.byteintl.com"),
        ],
    },
    {
        "name": "Molmo2-8B (AllenAI)",
        "category": "Open-Weight VLM",
        "description": "AllenAI's open multimodal vision-language model for rich video and image reasoning.",
        "links": [
            ("🤗 Hugging Face", "https://huggingface.co/allenai/Molmo2-8B"),
            ("🚀 Playground Demo", "https://playground.allenai.org/?model=molmo2-8b"),
            ("📝 Blog Post", "https://allenai.org/blog/molmo2"),
            ("▶️ YouTube Video", "https://youtu.be/Ej3Hb3kRiac"),
        ],
    },
    {
        "name": "VideoLLaMA 3 (DAMO-NLP-SG)",
        "category": "Video-LLM",
        "description": "Frontier multimodal foundation model tailored for image and video understanding.",
        "links": [
            ("🐙 GitHub", "https://github.com/DAMO-NLP-SG/VideoLLaMA3"),
            ("🚀 HF Space Demo", "https://huggingface.co/spaces/lixin4ever/VideoLLaMA3"),
        ],
    },
    {
        "name": "VideoJev-35B-A3B",
        "category": "MoE Video-LLM",
        "description": "35B total parameter (3B active) Mixture-of-Experts model for efficient video understanding.",
        "links": [
            ("🤗 Hugging Face", "https://huggingface.co/ZhuYuhan/VideoJev-35B-A3B"),
            ("🚀 HF Space Demo", "https://huggingface.co/spaces/hugging-apps/videojev-35b-a3b"),
        ],
    },
    {
        "name": "Gemini Agentic Video Understanding",
        "category": "API & Developer Guides",
        "description": "Official Google AI Studio and Gemini API guides for agentic video reasoning and frame-level understanding.",
        "links": [
            ("🛠️ AI Studio Developer Guide", "https://aistudio.google.com/learn/agentic-video-understanding-with-gemini"),
            ("📚 Gemini Video Docs", "https://ai.google.dev/gemini-api/docs/video-understanding"),
        ],
    },
]


@spaces.GPU  # Satisfies the ZeroGPU startup scanner
def filter_resources(search_query: str, category_filter: str) -> str:
    query = (search_query or "").strip().lower()
    sections = []

    for item in RESOURCES:
        if category_filter != "All" and item["category"] != category_filter:
            continue
        if query and (
            query not in item["name"].lower()
            and query not in item["description"].lower()
            and query not in item["category"].lower()
        ):
            continue

        links_md = "  |  ".join(
            f"**[{label}]({url})**" for label, url in item["links"]
        )
        section = (
            f"### {item['name']}  `[{item['category']}]`\n"
            f"{item['description']}\n\n"
            f"🔗 {links_md}\n\n---"
        )
        sections.append(section)

    if not sections:
        return "### No matching models or resources found."

    return "\n\n".join(sections)


categories = ["All"] + sorted(list({r["category"] for r in RESOURCES}))

with gr.Blocks(title="Video Understanding Models & Demos Hub") as demo:
    gr.Markdown(
        """
        # 🎬 Video Understanding Models, Demos & Resources
        Quick-access directory of multimodal video foundation models, Hugging Face checkpoints, interactive playgrounds, and developer guides.
        """
    )

    with gr.Row():
        search_box = gr.Textbox(
            label="Search Models / Links",
            placeholder="Filter by keyword (e.g., Molmo, VideoLLaMA, Gemini, ByteDance, Vidi)...",
            scale=3,
        )
        category_dropdown = gr.Dropdown(
            choices=categories,
            value="All",
            label="Category",
            scale=1,
        )

    gr.Markdown("---")
    results_markdown = gr.Markdown(value=filter_resources("", "All"))

    with gr.Accordion("📋 Summary Comparison Table", open=True):
        gr.Markdown(
            """
| Model / Resource | Category | Model / Repo Link | Live Demo / Space | Extra Links |
| :--- | :--- | :--- | :--- | :--- |
| **Vidi (ByteDance)** | Video Model | [GitHub](https://github.com/bytedance/vidi) | [Vidi Demo](https://vidi.byteintl.com) | — |
| **Molmo2-8B (AllenAI)** | Open-Weight VLM | [Hugging Face](https://huggingface.co/allenai/Molmo2-8B) | [AllenAI Playground](https://playground.allenai.org/?model=molmo2-8b) | [Blog](https://allenai.org/blog/molmo2) · [YouTube](https://youtu.be/Ej3Hb3kRiac) |
| **VideoLLaMA 3** | Video-LLM | [GitHub](https://github.com/DAMO-NLP-SG/VideoLLaMA3) | [HF Space](https://huggingface.co/spaces/lixin4ever/VideoLLaMA3) | — |
| **VideoJev-35B-A3B** | MoE Video-LLM | [Hugging Face](https://huggingface.co/ZhuYuhan/VideoJev-35B-A3B) | [HF Space](https://huggingface.co/spaces/hugging-apps/videojev-35b-a3b) | — |
| **Gemini Video Understanding** | API & Developer Guides | [AI Studio Guide](https://aistudio.google.com/learn/agentic-video-understanding-with-gemini) | — | [API Docs](https://ai.google.dev/gemini-api/docs/video-understanding) |
            """
        )

    search_box.change(
        fn=filter_resources,
        inputs=[search_box, category_dropdown],
        outputs=results_markdown,
    )
    category_dropdown.change(
        fn=filter_resources,
        inputs=[search_box, category_dropdown],
        outputs=results_markdown,
    )

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860, ssr_mode=False)