Update agent.py

agent.py

@@ -18,10 +18,11 @@ from langgraph.graph.message import add_messages
 from langchain_core.messages import AnyMessage, SystemMessage, HumanMessage, AIMessage
 from langgraph.graph import StateGraph, START, END, MessagesState
 from langgraph.prebuilt import ToolNode, tools_condition
-from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
+from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace, HuggingFaceEmbeddings
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_groq import ChatGroq
-
+from langchain_community.vectorstores import SupabaseVectorStore
+from supabase.client import Client, create_client
 
 HUGGINGFACEHUB_API_TOKEN = getenv("HUGGINGFACEHUB_API_TOKEN")
 
@@ -30,6 +31,25 @@ HUGGINGFACEHUB_API_TOKEN = getenv("HUGGINGFACEHUB_API_TOKEN")
 with open("prompt.txt", "r", encoding="utf-8") as f:
     system_prompt = f.read()
 
+# 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_ROLE_KEY")
+)
+vector_store = SupabaseVectorStore(
+    client=supabase,
+    embedding=embeddings,
+    table_name="documents2",
+    query_name="match_documents_2",
+)
+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.",
+)
+
 # System message
 sys_msg = SystemMessage(content=system_prompt)
 
@@ -62,12 +82,21 @@ def simple_graph():
 
     def retriever(state: MessagesState):
         """Retriever node"""
-        # I don't want to use a Retriever / Using similar questions.
-        return {"messages": [sys_msg] + state["messages"]}
+        similar_question = vector_store.similarity_search(state["messages"][0].content)
+
+        if similar_question:  # Check if the list is not empty
+            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]}
+        else:
+            # Handle the case when no similar questions are found
+            return {"messages": [sys_msg] + state["messages"]}
+
     
     # Build graph / nodes
     builder = StateGraph(MessagesState)
-    builder.add_node("retriever", retriever) # Assistant
+    builder.add_node("retriever", retriever) # Retriever
     builder.add_node("assistant", assistant) # Assistant
     builder.add_node("tools", ToolNode(tools)) # Tools