Update agent.py

agent.py

@@ -126,26 +126,29 @@ 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 type handling
+# Initialize vector store without 'columns' parameter
 vector_store = SupabaseVectorStore(
     client=supabase,
     embedding=embeddings,
     table_name="documents",
-    query_name="match_documents",
-    columns={
-        "content": "result_content",
-        "metadata": "result_metadata"
-    }
+    query_name="match_documents"
 )
 
-# Create retriever with jsonb-compatible filters
+# Create retriever with proper search configuration
 retriever = vector_store.as_retriever(
     search_kwargs={
         "k": 3,
-        "filter": {}  # Will be automatically converted to jsonb
+        "filter": {}
     }
 )
 
+# Create tool with the configured retriever
+retriever_tool = create_retriever_tool(
+    retriever=retriever,
+    name="document_retriever",
+    description="Searches for similar documents in knowledge base",
+)
+
 tools = [
     multiply,
     add,