Upload backend/hue_portal/hue-portal-backendDocker/set_embedding_model_1024.py with huggingface_hub

backend/hue_portal/hue-portal-backendDocker/set_embedding_model_1024.py

@@ -0,0 +1,69 @@
+#!/usr/bin/env python3
+"""
+Script to set embedding model to 1024 dim (multilingual-e5-large) on Hugging Face Spaces.
+This fixes the dimension mismatch: query=768, stored=1024.
+"""
+
+import os
+from huggingface_hub import HfApi
+from huggingface_hub.utils import HfFolder
+
+def get_hf_token():
+    """Get Hugging Face token from cache."""
+    token = HfFolder.get_token()
+    if not token:
+        print("❌ No Hugging Face token found!")
+        print("💡 Run: huggingface-cli login")
+        return None
+    return token
+
+def set_secret(api, repo_id, key, value):
+    """Set a secret on Hugging Face Space."""
+    try:
+        # Delete existing secret first
+        try:
+            api.delete_space_secret(repo_id=repo_id, key=key, token=api.token)
+            print(f"🗑️  Deleted existing secret: {key}")
+        except Exception:
+            pass  # Secret doesn't exist, continue
+        
+        # Add new secret
+        api.add_space_secret(repo_id=repo_id, key=key, value=value, token=api.token)
+        print(f"✅ Set secret: {key}={value}")
+        return True
+    except Exception as e:
+        print(f"❌ Error setting secret {key}: {e}")
+        return False
+
+def main():
+    repo_id = "davidtran999/hue-portal-backend"
+    
+    print("🔧 Setting embedding model to 1024 dim (multilingual-e5-large)")
+    print(f"📦 Repository: {repo_id}\n")
+    
+    # Get token
+    token = get_hf_token()
+    if not token:
+        return
+    
+    api = HfApi(token=token)
+    
+    # Set embedding model to multilingual-e5-large (1024 dim)
+    success = set_secret(api, repo_id, "EMBEDDING_MODEL", "multilingual-e5-large")
+    
+    if success:
+        print("\n✅ Successfully set embedding model to multilingual-e5-large (1024 dim)")
+        print("\n📊 This will fix dimension mismatch:")
+        print("   - Before: query=768, stored=1024 ❌")
+        print("   - After:  query=1024, stored=1024 ✅")
+        print("\n🔄 Rebuild your HF Space to apply changes!")
+        print("   → Vector search will work again after rebuild")
+    else:
+        print("\n❌ Failed to set embedding model")
+
+if __name__ == "__main__":
+    main()
+
+
+
+