Update agent.py

agent.py

@@ -126,21 +126,32 @@ 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
 vector_store = SupabaseVectorStore(
     client=supabase,
     embedding=embeddings,
     table_name="documents",
-    query_name="match_documents",  # Your unified function name
+    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
+    }
 )
+
+# Create retriever with search parameters
+retriever = vector_store.as_retriever(
+    search_kwargs={
+        "k": 3,
+        "filter": {}
+    }
+)
+
+# Create tool with the configured retriever
 retriever_tool = create_retriever_tool(
-    retriever=vector_store.as_retriever(
-        search_kwargs={
-            "k": 3,
-            "filter": {}
-        }
-    ),
+    retriever=retriever,
     name="document_retriever",
-    description="Searches for similar documents",
+    description="Searches for similar documents in knowledge base",
 )