fixed FAISS initial document

agent.py

@@ -15,6 +15,7 @@ from langchain_community.embeddings import HuggingFaceEmbeddings
 from langchain_community.vectorstores import FAISS
 from langchain_openai import ChatOpenAI
 from langchain_core.messages import HumanMessage, SystemMessage
+from langchain_core.documents import Document
 from langchain.tools.retriever import create_retriever_tool
 from langgraph.graph import StateGraph, START, END, MessagesState
 from langgraph.prebuilt import ToolNode, tools_condition
@@ -126,10 +127,10 @@ sys_msg = SystemMessage(content=system_prompt)
 
 embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2")
 
-# Ensure `documents` is defined – this should be a list of LangChain Document objects
-# Example: documents = [Document(page_content="Q: What is 2+2? A: 4", metadata={}), ...]
-# If you don't have documents yet, load or define them here.
-documents = []  # <-- You MUST fill this with actual documents
+documents = [
+    Document(page_content="What is the capital of France? Paris.", metadata={"source": "example"}),
+    Document(page_content="How many legs does a spider have? 8.", metadata={"source": "example"}),
+]
 vector_store = FAISS.from_documents(documents, embeddings)
 
 retriever_tool = create_retriever_tool(