Deploy 6de2fc7

app/main.py

@@ -61,12 +61,17 @@ async def lifespan(app: FastAPI):
         timeout=10,
     )
 
+    vector_store = VectorStore(qdrant, settings.QDRANT_COLLECTION)
+    # Idempotent: creates collection if absent so a cold-start before first
+    # ingest run doesn't crash every search with "collection not found".
+    vector_store.ensure_collection()
+
     app.state.pipeline = build_pipeline({
         "classifier": GuardClassifier(),
         "cache": app.state.semantic_cache,
         "embedder": embedder,
         "llm": get_llm_client(settings),
-        "vector_store": VectorStore(qdrant, settings.QDRANT_COLLECTION),
+        "vector_store": vector_store,
         "reranker": reranker,
         "db_path": settings.DB_PATH,
     })

app/pipeline/nodes/retrieve.py

@@ -31,7 +31,7 @@ def make_retrieve_node(vector_store: VectorStore, embedder: Embedder, reranker:
         reranked = await reranker.rerank(state["query"], unique_chunks, top_k=5)
 
         # Low-confidence fallback: skip generation and return early.
-        if reranker.min_score < 0.45:
+        if not reranked or reranker.min_score < 0.45:
             return {
                 "answer": "I don't have enough information about this in my knowledge base. Try asking about my specific projects or blog posts.",
                 "retrieved_chunks": [],

app/services/vector_store.py

@@ -100,5 +100,5 @@ class VectorStore:
 
         except Exception as e:
             raise RetrievalError(
-                f"Vector search failed", context={"error": str(e)}
+                f"Vector search failed: {e}", context={"error": str(e)}
             ) from e