Update app.py

app.py

@@ -1,40 +1,13 @@
 import streamlit as st
 import json
-from huggingface_hub import InferenceClient
+from gradio_client import Client
 import time
 
 st.set_page_config(page_title="AI Video Ad Generator", page_icon="🎬", layout="wide")
 
-# Initialize session state
-if 'api_token' not in st.session_state:
-    st.session_state.api_token = ""
-
-# Sidebar - API Token
-with st.sidebar:
-    st.header("🔑 Configuration")
-    api_token = st.text_input(
-        "HuggingFace API Token",
-        type="password",
-        value=st.session_state.api_token,
-        help="Get your token from https://huggingface.co/settings/tokens"
-    )
-    if api_token:
-        st.session_state.api_token = api_token
-    
-    st.divider()
-    st.markdown("### 📋 JSON Structure")
-    st.code("""{
-  "product": "laptop",
-  "style": "cinematic",
-  "mood": "premium",
-  "duration": "short",
-  "camera": "rotating",
-  "lighting": "studio"
-}""", language="json")
-
 # Main title
 st.title("🎬 AI Video Advertisement Generator")
-st.markdown("Generate professional video ads from JSON specifications using state-of-the-art AI")
+st.markdown("Generate professional video ads from JSON using free community GPU models")
 
 # Tabs
 tab1, tab2 = st.tabs(["🎥 Generate Video", "📖 Guide"])
@@ -62,16 +35,16 @@ with tab1:
             height=300
         )
         
-        # Advanced settings
-        with st.expander("⚙️ Advanced Settings"):
-            model_choice = st.selectbox(
-                "Model",
-                ["tencent/HunyuanVideo", "THUDM/CogVideoX-5b", "genmo/mochi-1-preview"],
-                help="HunyuanVideo: Best quality | CogVideoX: Longer videos | Mochi: Fastest"
+        # Model selection
+        with st.expander("⚙️ Model Settings"):
+            model_space = st.selectbox(
+                "Model Space",
+                [
+                    "THUDM/CogVideoX-5B",
+                    "THUDM/CogVideoX-2B"
+                ],
+                help="CogVideoX models via community Spaces"
             )
-            
-            resolution = st.selectbox("Resolution", ["720p", "1080p"], index=0)
-            fps = st.slider("FPS", 24, 30, 24)
         
         # Generate button
         generate_btn = st.button("🎬 Generate Video Ad", type="primary", use_container_width=True)
@@ -83,132 +56,121 @@ with tab1:
 
     # Generation logic
     if generate_btn:
-        if not st.session_state.api_token:
-            st.error("⚠️ Please enter your HuggingFace API token in the sidebar")
-        else:
-            try:
-                # Parse JSON
-                ad_config = json.loads(json_input)
-                
-                # Build cinematic prompt from JSON
-                prompt = f"""Professional commercial advertisement video showcasing {ad_config.get('product', 'product')}, 
+        try:
+            # Parse JSON
+            ad_config = json.loads(json_input)
+            
+            # Build cinematic prompt from JSON
+            prompt = f"""Professional commercial advertisement video showcasing {ad_config.get('product', 'product')}, 
 {ad_config.get('visual_style', 'cinematic')} style, {ad_config.get('camera_movement', 'smooth camera movement')}, 
 {ad_config.get('lighting', 'professional lighting')}, {ad_config.get('background', 'modern background')}, 
 {ad_config.get('mood', 'premium')} aesthetic, product-focused hero shot, 
 {', '.join(ad_config.get('key_features', []))}, commercial quality, 4K resolution, 
 professional advertising photography, luxury brand style, high-end production value"""
-                
-                status_placeholder.info(f"🎨 Generating with {model_choice}...")
-                
-                # Initialize client
-                client = InferenceClient(token=st.session_state.api_token)
-                
-                # Progress simulation
-                progress_bar = st.progress(0)
-                for i in range(100):
-                    time.sleep(0.3)
-                    progress_bar.progress(i + 1)
-                
-                # Generate video
-                with st.spinner("🎬 Creating your video ad... (this may take 30-60 seconds)"):
-                    video_bytes = client.text_to_video(
+            
+            status_placeholder.info(f"🎨 Connecting to {model_space}...")
+            
+            with st.spinner("🎬 Generating video... This takes 60-120 seconds"):
+                try:
+                    # Try to connect to community Space
+                    client = Client(model_space)
+                    
+                    # Generate video
+                    result = client.predict(
                         prompt=prompt,
-                        model=model_choice
+                        api_name="/predict"
                     )
-                
-                progress_bar.empty()
-                status_placeholder.success("✅ Video generated successfully!")
-                
-                # Display video
-                with col2:
-                    video_placeholder.video(video_bytes)
                     
-                    st.download_button(
-                        label="⬇️ Download Video",
-                        data=video_bytes,
-                        file_name=f"ad_{ad_config.get('product', 'video').replace(' ', '_')}.mp4",
-                        mime="video/mp4",
-                        use_container_width=True
-                    )
-                
-                # Show generated prompt
-                with st.expander("📝 Generated Prompt"):
-                    st.text(prompt)
+                    status_placeholder.success("✅ Video generated successfully!")
+                    
+                    # Display video
+                    if isinstance(result, str):
+                        video_placeholder.video(result)
+                        
+                        with open(result, "rb") as f:
+                            video_bytes = f.read()
+                        
+                        st.download_button(
+                            label="⬇️ Download Video",
+                            data=video_bytes,
+                            file_name=f"ad_{ad_config.get('product', 'video').replace(' ', '_')}.mp4",
+                            mime="video/mp4",
+                            use_container_width=True
+                        )
+                    
+                    # Show generated prompt
+                    with st.expander("📝 Generated Prompt"):
+                        st.text(prompt)
+                        
+                except Exception as api_error:
+                    status_placeholder.error(f"""
+                    ⚠️ **Free GPU queue is full or Space unavailable**
                     
-            except json.JSONDecodeError:
-                st.error("❌ Invalid JSON format. Please check your input.")
-            except Exception as e:
-                st.error(f"❌ Error: {str(e)}")
-                status_placeholder.empty()
+                    **Alternative Options:**
+                    1. Try again in a few minutes (queue clears)
+                    2. Use a paid service like Replicate or Fal.ai
+                    3. Deploy your own GPU Space (requires payment)
+                    
+                    Technical error: {str(api_error)}
+                    """)
+                    
+        except json.JSONDecodeError:
+            st.error("❌ Invalid JSON format. Please check your input.")
+        except Exception as e:
+            st.error(f"❌ Error: {str(e)}")
 
 with tab2:
     st.markdown("""
-    ## 🎯 How to Use
-    
-    ### 1️⃣ Get API Token
-    - Visit [HuggingFace Tokens](https://huggingface.co/settings/tokens)
-    - Create a new token with "read" permissions
-    - Paste it in the sidebar
+    ## 🎯 How It Works
     
-    ### 2️⃣ Configure Your Ad
-    Define your video ad using JSON with these properties:
+    This app calls **community-hosted HuggingFace Spaces** with free GPU access.
     
-    - **product**: What you're advertising
-    - **brand_style**: Your brand aesthetic (modern, minimal, bold)
-    - **visual_style**: Video style (cinematic, dynamic, elegant)
-    - **camera_movement**: How camera moves (rotation, zoom, pan)
-    - **lighting**: Lighting setup (dramatic, soft, studio)
-    - **background**: Background style (gradient, solid, abstract)
-    - **mood**: Overall feeling (premium, energetic, calm)
-    - **key_features**: List of product highlights
-    - **duration**: Video length preference
+    ### ⚠️ Important Limitations
     
-    ### 3️⃣ Generate
-    Click "Generate Video Ad" and wait 30-60 seconds
+    - **Queue wait times**: Popular Spaces have queues (2-5 minutes)
+    - **Availability**: Spaces may go offline
+    - **Generation time**: 60-120 seconds per video
+    - **Video length**: 5-10 seconds maximum
     
-    ### 🎨 Model Comparison
+    ### 🔄 If Generation Fails
     
-    - **HunyuanVideo**: Best quality, photorealistic, 5-6 seconds
-    - **CogVideoX**: Good quality, longer duration, 10+ seconds
-    - **Mochi**: Fastest generation, 3-5 seconds, lightweight
+    The free models have limited capacity. Options:
     
-    ### 💡 Tips for Best Results
+    1. **Wait and retry** - Queues clear quickly
+    2. **Use paid APIs**:
+       - Replicate.com ($0.01-0.05/video)
+       - Fal.ai ($0.05-0.15/video)
+       - Runway ML (paid plans)
+    3. **Self-host** with your own GPU Space
     
-    - Be specific about visual style and camera movement
-    - Include 3-5 key features maximum
-    - Use cinematic/commercial terminology
-    - Describe lighting and mood clearly
-    - Keep product name concise
+    ### 💡 JSON Configuration
     
-    ### ⚡ Example JSON Templates
-    
-    **Tech Product:**
     ```json
     {
-      "product": "smartphone",
-      "visual_style": "Apple-style commercial",
-      "camera_movement": "slow orbit around device",
-      "lighting": "soft gradient backlight",
-      "mood": "minimalist premium"
+      "product": "What you're advertising",
+      "visual_style": "cinematic/dynamic/elegant",
+      "camera_movement": "rotation/zoom/pan",
+      "lighting": "dramatic/soft/studio",
+      "background": "gradient/solid/abstract",
+      "mood": "premium/energetic/calm",
+      "key_features": ["feature1", "feature2"]
     }
     ```
     
-    **Fashion/Lifestyle:**
-    ```json
-    {
-      "product": "luxury watch",
-      "visual_style": "high-fashion editorial",
-      "camera_movement": "close-up macro details",
-      "lighting": "dramatic side lighting",
-      "mood": "elegant timeless"
-    }
-    ```
+    ### 🚀 For Production Use
+    
+    Free models are **NOT suitable for production**. Consider:
+    
+    - **Replicate API** - Pay per generation, reliable
+    - **Runway ML** - Professional video generation
+    - **Luma Dream Machine** - High quality, paid
+    - **Self-hosted GPU** - Full control, requires infrastructure
     """)
 
 # Footer
 st.divider()
 st.markdown("""
 <div style='text-align: center; color: #666;'>
-    <p>Powered by HuggingFace Inference API | Free GPU-accelerated video generation</p>
+    <p>⚠️ Using free community Spaces - expect wait times and availability issues</p>
 </div>
 """, unsafe_allow_html=True)