Update agent.py

agent.py

@@ -130,9 +130,6 @@ vector_store = SupabaseVectorStore(
     embedding=embeddings,
     table_name="documents",
     query_name="match_documents",
-    # Add these required parameters
-    match_count=5,  # Number of documents to return
-    match_threshold=0.7,  # Similarity threshold (between 0 and 1)
 )
 create_retriever_tool = create_retriever_tool(
     retriever=vector_store.as_retriever(),