Deploy Gradio app with multiple files

app.py

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+import gradio as gr
+import requests
+
+def generate_video(prompt, duration, progress=gr.Progress()):
+    """Generate video using akhaliq-Sora-2 API"""
+    if not prompt.strip():
+        raise gr.Error("Please enter a text prompt")
+    
+    progress(0.1, desc="Starting video generation...")
+    
+    try:
+        # API endpoint for akhaliq-Sora-2
+        api_url = "https://akhaliq-sora-2.hf.space/api/predict"
+        
+        # Prepare the payload
+        payload = {
+            "data": [
+                prompt,  # text prompt
+                duration,  # duration in seconds
+                30,  # fps (fixed)
+                512,  # width (fixed)
+                512,  # height (fixed)
+            ]
+        }
+        
+        progress(0.5, desc="Generating video...")
+        
+        # Make the API request
+        response = requests.post(api_url, json=payload)
+        
+        if response.status_code == 200:
+            progress(0.9, desc="Processing...")
+            result = response.json()
+            
+            # Check if the generation is complete
+            if "data" in result and len(result["data"]) > 0:
+                video_url = result["data"][0]
+                if video_url:
+                    progress(1.0, desc="Complete!")
+                    return video_url
+                else:
+                    raise gr.Error("Video generation failed")
+            else:
+                raise gr.Error("Invalid response from API")
+        else:
+            raise gr.Error(f"API request failed with status code: {response.status_code}")
+            
+    except requests.exceptions.RequestException as e:
+        raise gr.Error(f"Network error: {str(e)}")
+    except Exception as e:
+        raise gr.Error(f"Error generating video: {str(e)}")
+
+# Create the Gradio interface
+with gr.Blocks(title="Text-to-Video AI Generator") as demo:
+    
+    gr.Markdown("# 🎬 Text-to-Video AI Generator")
+    gr.Markdown("Transform your text into AI-generated videos using Sora-2 model")
+    gr.Markdown('<p><a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank">Built with anycoder</a></p>')
+    
+    with gr.Row():
+        with gr.Column():
+            prompt_input = gr.Textbox(
+                label="Video Description",
+                placeholder="Describe the video you want to generate...",
+                lines=3
+            )
+            
+            duration_slider = gr.Slider(
+                minimum=1,
+                maximum=10,
+                value=4,
+                step=1,
+                label="Video Duration (seconds)"
+            )
+            
+            generate_btn = gr.Button("Generate Video", variant="primary")
+        
+        with gr.Column():
+            video_output = gr.Video(
+                label="Generated Video",
+                height=400
+            )
+    
+    gr.Examples(
+        examples=[
+            ["A cat playing piano", 4],
+            ["A robot dancing", 6],
+            ["A sunset over the ocean", 3],
+        ],
+        inputs=[prompt_input, duration_slider]
+    )
+    
+    generate_btn.click(
+        fn=generate_video,
+        inputs=[prompt_input, duration_slider],
+        outputs=[video_output],
+        show_progress=True
+    )
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+requests
+gradio
+Pillow
+numpy
+scipy
+joblib
+pandas
+openpyxl
+matplotlib
+torch
+torchvision
+torchaudio
+accelerate
+tokenizers
+datasets
+uvicorn
+pydantic
+streamlit
+opencv-python
+python-docx
+PyPDF2
+git+https://github.com/huggingface/transformers
+sentencepiece
+git+https://github.com/huggingface/diffusers