Update agent.py

agent.py

@@ -126,17 +126,12 @@ embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-b
 supabase: Client = create_client(
     os.environ.get("SUPABASE_URL"), 
     os.environ.get("SUPABASE_SERVICE_KEY"))
-# Initialize vector store with proper column mappings
+# Initialize vector store without the 'columns' parameter
 vector_store = SupabaseVectorStore(
     client=supabase,
     embedding=embeddings,
     table_name="documents",
-    query_name="match_documents",
-    columns={
-        "id": "document_id",          # Maps to function output
-        "content": "document_content", # Maps to function output
-        "metadata": "document_metadata" # Maps to function output
-    }
+    query_name="match_documents"
 )
 
 # Create retriever with search parameters