Update app.py

app.py

@@ -1,34 +1,29 @@
-from fastapi import FastAPI, Form
-from fastapi.responses import FileResponse
-import torch
-from diffusers import StableDiffusionPipeline, StableVideoDiffusionPipeline
-from diffusers.utils import export_to_video
-from PIL import Image
+import gradio as gr
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
 
-app = FastAPI()
+# Load ModelScope pipeline
+video_pipe = pipeline(
+    Tasks.text_to_video_synthesis,
+    model='damo/text-to-video-synthesis',
+    device='cuda'
+)
 
-# Force CPU setup
-device = "cpu"
-dtype = torch.float32
-variant = None  # Don't use "fp16" on CPU
+def generate(prompt, image):
+    image_path = "input.png"
+    image.save(image_path)
+    result = video_pipe({
+        'text': prompt,
+        'input_image': image_path
+    })
+    return result['video_path']
 
-# Load text-to-image model
-text2img_pipe = StableDiffusionPipeline.from_pretrained(
-    "runwayml/stable-diffusion-v1-5", torch_dtype=dtype
-).to(device)
+with gr.Blocks() as demo:
+    gr.Markdown("## 🎬 Text + Image → Shorts-Ready Video")
+    prompt = gr.Textbox(label="🔤 লিখুন (Bengali/English)")
+    image_input = gr.Image(type="pil", label="🖼️ একটি ছবি দিন")
+    video_output = gr.Video(label="🎥 Generated Video")
+    generate_btn = gr.Button("🎞️ ভিডিও তৈরি করুন")
+    generate_btn.click(fn=generate, inputs=[prompt, image_input], outputs=video_output)
 
-# Load image-to-video model
-video_pipe = StableVideoDiffusionPipeline.from_pretrained(
-    "stabilityai/stable-video-diffusion-img2vid-xt", torch_dtype=dtype, variant=variant
-).to(device)
-
-@app.post("/generate")
-def generate_video(prompt: str = Form(...), aspect: str = Form("16:9")):
-    image = text2img_pipe(prompt).images[0]
-    image = image.resize((1024, 576) if aspect == "16:9" else (576, 1024))
-
-    generator = torch.manual_seed(42)
-    frames = video_pipe(image, decode_chunk_size=8, generator=generator).frames[0]
-    export_to_video(frames, "output.mp4", fps=7)
-
-    return FileResponse("output.mp4", media_type="video/mp4", filename="output.mp4")
+demo.launch()