Support modern Qdrant search API

backend/app/search.py

@@ -3,7 +3,7 @@ from typing import List, Dict, Any, Optional
 from pathlib import Path
 
 from .config import settings
-from .vector_store import get_client, _collection_name as VECTOR_COLLECTION
+from .vector_store import get_client, query_points
 from .embeddings import embed_text, get_embedding_size
 from .db import get_chunks_for_library, list_libraries
 
@@ -55,12 +55,7 @@ def search_docs(
                 search_filter = None
         
         # Perform vector search
-        results = client.search(
+        results = query_points(client, query_embedding, limit, search_filter)
-            collection_name=VECTOR_COLLECTION,
-            query_vector=query_embedding,
-            limit=limit,
-            search_filter=search_filter
-        )
         
         # Format and return results
         formatted_results = []

backend/app/vector_store.py

@@ -64,6 +64,37 @@ def get_embedding_size() -> int:
         return 384
 
 
+def query_points(
+    client: Any,
+    query_vector: List[float],
+    limit: int,
+    search_filter: Optional[Any] = None,
+) -> List[Any]:
+    """Run a vector query across old and new qdrant-client APIs."""
+    legacy_search = getattr(client, "search", None)
+    if callable(legacy_search):
+        return legacy_search(
+            collection_name=_collection_name,
+            query_vector=query_vector,
+            limit=limit,
+            search_filter=search_filter,
+        )
+
+    modern_query = getattr(client, "query_points", None)
+    if not callable(modern_query):
+        raise RuntimeError(
+            "Installed qdrant-client supports neither search() nor query_points()"
+        )
+
+    response = modern_query(
+        collection_name=_collection_name,
+        query=query_vector,
+        limit=limit,
+        query_filter=search_filter,
+    )
+    return list(response.points)
+
+
 def create_collection(client: Any, collection_name: str, size: int, distance: Any) -> None:
     """Create a Qdrant collection across qdrant-client keyword changes."""
     vector_params = VectorParams(size=size, distance=distance)
@@ -255,12 +286,7 @@ async def search_vectors(
             )
         
         # Perform vector search
-        results = client.search(
+        results = query_points(client, query_vector, limit, search_filter)
-            collection_name=_collection_name,
-            query_vector=query_vector,
-            limit=limit,
-            search_filter=search_filter
-        )
         
         # Format results
         formatted_results = []

tests/test_search.py

@@ -178,6 +178,40 @@ class TestSearchDocs:
                 assert "title" in result
                 assert "chunk_index" in result
 
+    def test_uses_modern_qdrant_query_points_api(self):
+        """New qdrant-client versions expose query_points instead of search."""
+        from unittest.mock import patch
+        from backend.app.search import search_docs
+
+        point = type("ScoredPoint", (), {
+            "score": 0.91,
+            "payload": {
+                "id": "modern-result",
+                "library_id": "documentation",
+                "path": "docs/index.md",
+                "title": "Index",
+                "chunk_index": 0,
+            },
+        })()
+
+        class Response:
+            points = [point]
+
+        class ModernClient:
+            def query_points(self, **kwargs):
+                assert kwargs["query"] == [0.1, 0.2]
+                assert kwargs["limit"] == 3
+                return Response()
+
+        with (
+            patch("backend.app.search.embed_text", return_value=[0.1, 0.2]),
+            patch("backend.app.search.get_client", return_value=ModernClient()),
+        ):
+            results = search_docs("world generation", limit=3)
+
+        assert len(results) == 1
+        assert results[0]["id"] == "modern-result"
+
 
 class TestGetLibraryDocs:
     """Tests for get_library_docs() - document retrieval."""