app.py

import os
import gradio as gr
from huggingface_hub import InferenceClient

# ─── STEP 1: read your token from the Spaces secrets
HF_TOKEN = os.environ.get("HF_HUB_TOKEN")
if HF_TOKEN is None:
    raise RuntimeError("❌  Please add your HF_HUB_TOKEN under Settings → Variables and secrets")

# ─── STEP 2: initialize the client (no repo_id arg any more)
client = InferenceClient(token=HF_TOKEN)

# ─── STEP 3: the generation function
def generate_video(prompt: str) -> str:
    try:
        # pass your model ID as the first arg, and the text as `inputs=…`
        result = client.text_to_video(
            "ali-vilab/text-to-video-ms-1.7b", 
            inputs=prompt
        )
        video_bytes = result["video"]
        out_path = "output.mp4"
        with open(out_path, "wb") as f:
            f.write(video_bytes)
        return out_path
    except Exception as e:
        # re-raise so Gradio logs it for you
        raise RuntimeError(f"Video generation failed: {e}")

# ─── STEP 4: wire it up in Gradio
with gr.Blocks() as demo:
    gr.Markdown("## 🎬 Video Generator")
    with gr.Row():
        inp = gr.Textbox(placeholder="Type your prompt here", label="Enter your prompt")
        vid = gr.Video(label="Generated Video")
    btn = gr.Button("Generate")
    btn.click(fn=generate_video, inputs=inp, outputs=vid)

# ─── STEP 5: launch
demo.launch()