Update agent.py

agent.py

@@ -126,32 +126,26 @@ 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 correct configuration
+# Initialize vector store with proper type handling
 vector_store = SupabaseVectorStore(
     client=supabase,
     embedding=embeddings,
     table_name="documents",
-    query_name="match_documents"
+    query_name="match_documents",
+    columns={
+        "content": "result_content",
+        "metadata": "result_metadata"
+    }
 )
 
-# Create retriever with proper search configuration
+# Create retriever with jsonb-compatible filters
 retriever = vector_store.as_retriever(
     search_kwargs={
-        "k": 3,           # Number of results
-        "filter": {},     # Default filter
-        "score_threshold": 0.7  # Optional similarity threshold
+        "k": 3,
+        "filter": {}  # Will be automatically converted to jsonb
     }
 )
 
-# Create tool with the configured retriever
-retriever_tool = create_retriever_tool(
-    retriever=retriever,
-    name="document_retriever",
-    description="Searches for similar documents using vector similarity",
-)
-
-
-
 tools = [
     multiply,
     add,