Upload folder using huggingface_hub

app.py

@@ -40,6 +40,17 @@ if requirements_file.exists():
     print("Installing dependencies...")
     subprocess.run([sys.executable, "-m", "pip", "install", "-r", "requirements.txt"], cwd=str(repo_dir), check=True)
 
+# 4.5. Pre-download models to cache during startup
+print("Pre-downloading models to local cache...")
+try:
+    from huggingface_hub import snapshot_download
+    snapshot_download(repo_id="fastino/gliner2-large-v1")
+    snapshot_download(repo_id="ai4data/datause-extraction-v1")
+    snapshot_download(repo_id="ai4data-use/bert-base-uncased-data-use")
+    print("Models pre-downloaded successfully.")
+except Exception as e:
+    print(f"Warning: Failed to pre-download models: {e}")
+
 # 5. Add to Python path and launch the app
 sys.path.insert(0, str(repo_dir))
 sys.path.insert(0, str(repo_dir / "src"))
@@ -49,6 +60,17 @@ import gradio as gr
 from app import demo, CUSTOM_CSS
 
 if __name__ == "__main__":
+    # Pre-load models into RAM to avoid first-use delay
+    print("Pre-loading models into RAM...")
+    try:
+        from ai4data import DatasetExtractor
+        extractor = DatasetExtractor()
+        _ = extractor.model
+        _ = extractor.classifier
+        print("Models successfully pre-loaded into RAM.")
+    except Exception as e:
+        print(f"Warning: Failed to pre-load models: {e}")
+
     theme = gr.themes.Base(
         primary_hue="slate",
         neutral_hue="slate",