Update agent.py

agent.py

@@ -1,5 +1,3 @@
-# agent.py
-
 import os
 from dotenv import load_dotenv
 from langgraph.graph import START, StateGraph, MessagesState
@@ -17,7 +15,6 @@ from langchain_core.tools import tool
 from langchain.tools.retriever import create_retriever_tool
 from supabase.client import Client, create_client
 
-
 load_dotenv()
 
 @tool
@@ -122,6 +119,7 @@ with open("system_prompt.txt", "r", encoding="utf-8") as f:
 # System message
 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"), 
@@ -139,6 +137,7 @@ create_retriever_tool = create_retriever_tool(
 )
 
 
+
 tools = [
     multiply,
     add,
@@ -151,7 +150,7 @@ tools = [
 ]
 
 # Build graph function
-def build_graph(provider: str = "google"):
+def build_graph(provider: str = "groq"):
     """Build the graph"""
     # Load environment variables from .env file
     if provider == "google":
@@ -199,4 +198,15 @@ def build_graph(provider: str = "google"):
     builder.add_edge("tools", "assistant")
 
     # Compile graph
-    return builder.compile()
+    return builder.compile()
+
+# test
+if __name__ == "__main__":
+    question = "When was a picture of St. Thomas Aquinas first added to the Wikipedia page on the Principle of double effect?"
+    # Build the graph
+    graph = build_graph(provider="groq")
+    # Run the graph
+    messages = [HumanMessage(content=question)]
+    messages = graph.invoke({"messages": messages})
+    for m in messages["messages"]:
+        m.pretty_print()