feat: solution for 'Экзамен: Самокорректирующийся агент'

main.py

@@ -1,14 +1,25 @@
-from langchain_openai import OpenAI
-from langgraph import Graph
+from langgraph.graph import StateGraph
+from src.graph import build_graph
+from langchain_core.messages import HumanMessage
 
 def main():
-    # Initialize OpenAI LLM
-    llm = OpenAI(model="gpt-3.5-turbo")
-    # Create a simple LangGraph graph instance
-    graph = Graph()
-    print("OpenAI and LangGraph imports succeeded.")
-    print(f"LLM instance: {llm}")
-    print(f"Graph instance: {graph}")
+    # Build and compile the graph
+    graph = build_graph()
+    app = graph.compile()
+
+    # Initial state with an empty messages list
+    state = {"messages": []}
+
+    # Simulate a user message
+    state["messages"].append(HumanMessage(content="Hello, agent!"))
+
+    # Run the graph
+    result = app.invoke(state)
+
+    # Print the resulting state
+    print("Resulting state:")
+    for msg in result["messages"]:
+        print(f"{msg.__class__.__name__}: {msg.content}")
 
 if __name__ == "__main__":
     main()