Create app.py

app.py

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+import os
+import shutil
+import subprocess
+import spaces
+import gradio as gr
+from pathlib import Path
+from huggingface_hub import snapshot_download
+
+# --- 1. CONFIGURATION & WEIGHT HYDRATION ---
+REPO_ID = "Macfeigh/visor-weights" 
+CHECKPOINT_DIR = "/app/SadTalker/checkpoints"
+
+def hydrate_workspace():
+    # Clone SadTalker and Wav2Lip if they don't exist
+    if not os.path.exists("/app/SadTalker"):
+        print("📥 Cloning SadTalker...")
+        subprocess.run(["git", "clone", "https://github.com/OpenTalker/SadTalker.git", "/app/SadTalker"])
+        
+    if not os.path.exists("/app/Wav2Lip"):
+        print("📥 Cloning Wav2Lip...")
+        subprocess.run(["git", "clone", "https://github.com/Rudrabha/Wav2Lip.git", "/app/Wav2Lip"])
+
+    # Download weights from your model repo
+    print(f"🌡️ Pulling weights from {REPO_ID}...")
+    snapshot_download(
+        repo_id=REPO_ID,
+        local_dir=CHECKPOINT_DIR,
+        local_dir_use_symlinks=False
+    )
+    print("✅ Weights ready.")
+
+# Initialize workspace before Gradio starts
+hydrate_workspace()
+
+# --- 2. GPU INFERENCE ENGINE ---
+@spaces.GPU(duration=120)
+def visor_execute(image_path, audio_path):
+    output_dir = "/tmp/visor_output"
+    if os.path.exists(output_dir):
+        shutil.rmtree(output_dir)
+    os.makedirs(output_dir, exist_ok=True)
+
+    print("🚀 Executing Phase 3: Animation...")
+    
+    # Run SadTalker
+    st_proc = subprocess.run([
+        "python", "/app/SadTalker/inference.py",
+        "--driven_audio", audio_path,
+        "--source_image", image_path,
+        "--result_dir", output_dir,
+        "--still",
+        "--preprocess", "full",
+        "--checkpoint_dir", CHECKPOINT_DIR
+    ], env={**os.environ, "PYTHONPATH": "/app/SadTalker"})
+
+    # Find result
+    generated_videos = list(Path(output_dir).glob("**/*.mp4"))
+    if not generated_videos:
+        return None
+    
+    return str(generated_videos[0])
+
+# --- 3. INTERFACE ---
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🛡️ VisorFlow Core: Sovereign Intelligence Node")
+    gr.Markdown("Zero-cost execution environment running on NVIDIA H200.")
+    
+    with gr.Row():
+        with gr.Column():
+            img = gr.Image(type="filepath", label="Source Portrait")
+            aud = gr.Audio(type="filepath", label="Voice Command")
+            btn = gr.Button("RUN PHASE 3", variant="primary")
+        with gr.Column():
+            out = gr.Video(label="Generated Output")
+
+    btn.click(fn=visor_execute, inputs=[img, aud], outputs=[out])
+
+demo.launch()