added stuff

agent.py

@@ -121,21 +121,21 @@ with open("system_prompt.txt", "r", encoding="utf-8") as f:
 sys_msg = SystemMessage(content=system_prompt)
 
 # build a retriever
-# embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2") #  dim=768
-# supabase: Client = create_client(
-#     os.environ.get("SUPABASE_URL"), 
-#     os.environ.get("SUPABASE_SERVICE_KEY"))
-# vector_store = SupabaseVectorStore(
-#     client=supabase,
-#     embedding= embeddings,
-#     table_name="documents",
-#     query_name="match_documents_langchain",
-# )
-# create_retriever_tool = create_retriever_tool(
-#     retriever=vector_store.as_retriever(),
-#     name="Question Search",
-#     description="A tool to retrieve similar questions from a vector store.",
-# )
+embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2") #  dim=768
+supabase: Client = create_client(
+    os.environ.get("SUPABASE_URL"), 
+    os.environ.get("SUPABASE_SERVICE_KEY"))
+vector_store = SupabaseVectorStore(
+    client=supabase,
+    embedding= embeddings,
+    table_name="documents",
+    query_name="match_documents_langchain",
+)
+create_retriever_tool = create_retriever_tool(
+    retriever=vector_store.as_retriever(),
+    name="Question Search",
+    description="A tool to retrieve similar questions from a vector store.",
+)
 
 
 
@@ -189,20 +189,20 @@ def build_graph(provider: str = "groq"):
         """Assistant node"""
         return {"messages": [llm_with_tools.invoke(state["messages"])]}
     
-    # def retriever(state: MessagesState):
-    #     """Retriever node"""
-    #     similar_question = vector_store.similarity_search(state["messages"][0].content)
-    #     example_msg = HumanMessage(
-    #         content=f"Here I provide a similar question and answer for reference: \n\n{similar_question[0].page_content}",
-    #     )
-    #     return {"messages": [sys_msg] + state["messages"] + [example_msg]}
+    def retriever(state: MessagesState):
+        """Retriever node"""
+        similar_question = vector_store.similarity_search(state["messages"][0].content)
+        example_msg = HumanMessage(
+            content=f"Here I provide a similar question and answer for reference: \n\n{similar_question[0].page_content}",
+        )
+        return {"messages": [sys_msg] + state["messages"] + [example_msg]}
 
     builder = StateGraph(MessagesState)
-    # builder.add_node("retriever", retriever)
+    builder.add_node("retriever", retriever)
     builder.add_node("assistant", assistant)
     builder.add_node("tools", ToolNode(tools))
     builder.add_edge(START, "assistant")
-    # builder.add_edge("retriever", "assistant")
+    builder.add_edge("retriever", "assistant")
     builder.add_conditional_edges(
         "assistant",
         tools_condition,