Fix: Prevent data wipe in initialize and set correct port

src/vector_db.py

@@ -22,47 +22,72 @@ class UnifiedQdrant:
         url = os.getenv("QDRANT_URL", ":memory:")
         api_key = os.getenv("QDRANT_API_KEY", None)
         print(f"Connecting to Qdrant at {url}...")
-        self.client = QdrantClient(location=url, api_key=api_key, timeout=60)
+        
+        # Relaxed connection settings for HF Spaces
+        port = 443 if url.startswith("https") else 6333
+        self.client = QdrantClient(
+            location=url, 
+            port=port,
+            api_key=api_key, 
+            timeout=60,
+            check_compatibility=False,
+            verify=False # Passed to httpx
+        )
         
         self.is_local = url == ":memory:" or not url.startswith("http")
+        
         if self.is_local:
-            print("WARNING: Running in local/memory mode. Custom Sharding is NOT supported. Simulating behavior.")
+            print("Running in local/memory mode. Custom Sharding is NOT supported. Simulating behavior.")
+            self.num_clusters = 1
+            if self.client.collection_exists(collection_name=self.collection_name):
+                self.client.delete_collection(collection_name=self.collection_name)
+            self.client.create_collection(
+                collection_name=self.collection_name,
+                vectors_config=VectorParams(size=self.vector_size, distance=Distance.COSINE)
+            )
+            print(f"Created standard collection '{self.collection_name}'.")
+        else:
+            # Check if exists first to avoid accidental deletion
+            if self.client.collection_exists(self.collection_name):
+                print(f"Collection '{self.collection_name}' already exists. Skipping initialization.")
+                return
 
-        # Check if collection exists, if so, recreate it for a clean slate (or handle gracefully)
-        if self.client.collection_exists(self.collection_name):
-            self.client.delete_collection(self.collection_name)
-            
-        # Try to create collection with full clusters
-        try:
-            self._create_collection_and_shards(self.num_clusters)
-            print(f"Successfully created collection with {self.num_clusters} clusters.")
-        except Exception as e:
-            print(f"Failed to create {self.num_clusters} clusters: {e}")
-            print("Attempting fallback to 8 clusters (Free Tier limit mitigation)...")
-            # Fallback 1: 8 Clusters
+            # Try to create collection with full clusters
             try:
-                self.num_clusters = 8
-                if self.client.collection_exists(self.collection_name):
-                    self.client.delete_collection(self.collection_name)
                 self._create_collection_and_shards(self.num_clusters)
-                print(f"Fallback successful: Created collection with {self.num_clusters} clusters.")
-            except Exception as e2:
-                print(f"Failed to create 8 clusters: {e2}")
-                print("CRITICAL: Custom Sharding not supported. Falling back to Standard Collection (No Sharding).")
-                # Fallback 2: Standard Collection
-                self.num_clusters = 1 # Virtual clusters only
-                if self.client.collection_exists(self.collection_name):
-                    self.client.delete_collection(self.collection_name)
-                
-                self.client.create_collection(
-                    collection_name=self.collection_name,
-                    vectors_config=VectorParams(size=self.vector_size, distance=Distance.COSINE)
-                )
-                print("Fallback successful: Created Standard Collection.")
+                print(f"Successfully created collection with {self.num_clusters} clusters.")
+            except Exception as e:
+                print(f"Failed to create {self.num_clusters} clusters: {e}")
+                print("Attempting fallback to 8 clusters (Free Tier limit mitigation)...")
+                # Fallback 1: 8 Clusters
+                try:
+                    self.num_clusters = 8
+                    if self.client.collection_exists(self.collection_name):
+                        self.client.delete_collection(self.collection_name)
+                    self._create_collection_and_shards(self.num_clusters)
+                    print(f"Fallback successful: Created collection with {self.num_clusters} clusters.")
+                except Exception as e2:
+                    print(f"Failed to create 8 clusters: {e2}")
+                    print("CRITICAL: Custom Sharding not supported. Falling back to Standard Collection (No Sharding).")
+                    # Fallback 2: Standard Collection
+                    self.num_clusters = 1 
+                    if self.client.collection_exists(self.collection_name):
+                        self.client.delete_collection(self.collection_name)
+                    
+                    self.client.create_collection(
+                        collection_name=self.collection_name,
+                        vectors_config=VectorParams(size=self.vector_size, distance=Distance.COSINE)
+                    )
+                    print("Fallback successful: Created Standard Collection.")
 
     def _create_collection_and_shards(self, n_clusters):
         print(f"Creating collection '{self.collection_name}' with custom sharding ({n_clusters} clusters)...")
         
+        if self.client.collection_exists(self.collection_name):
+            print(f"Collection '{self.collection_name}' already exists. Skipping creation.")
+            return
+
+        
         if self.is_local:
             # Local mode doesn't support sharding_method=CUSTOM
             self.client.create_collection(