Add main.py

main.py

@@ -0,0 +1,63 @@
+import sys
+from langgraph.checkpoint.memory import MemorySaver
+from langgraph.graph import StateGraph
+from langchain_openai import ChatOpenAI
+from langchain.tools import tool
+from rich.console import Console
+
+console = Console()
+
+# Simple tool example
+@tool
+def echo(text: str) -> str:
+    """Return the same text."""
+    return text
+
+# Define graph state
+class State(dict):
+    pass
+
+# Agent node
+async def agent_node(state: State, config=None):
+    # Use LangChain LLM with tool calling
+    llm = ChatOpenAI(model="gpt-4o-mini", temperature=0)
+    from langchain.agents import create_openai_functions_agent
+    agent = create_openai_functions_agent(llm, [echo])
+    messages = state.get("messages", [])
+    # Run agent
+    result = await agent.ainvoke({"messages": messages})
+    return {"messages": result["messages"]}
+
+# Build graph
+builder = StateGraph(State)
+builder.add_node("agent", agent_node)
+builder.set_entry_point("agent")
+
+graph = builder.compile(checkpointer=MemorySaver(), interrupt_before=["tools"])  # memory and pause before tools
+
+config = {"configurable": {"thread_id": "chat-1"}}
+
+async def run_chat():
+    import asyncio
+    while True:
+        user_input = input("Вы: ")
+        if user_input.lower() in ("exit", "quit"):
+            break
+        state = {"messages": [{"role": "user", "content": user_input}]}
+        # Stream output and handle pauses
+        async for chunk in graph.astream(state, config=config):
+            if isinstance(chunk, dict) and chunk.get("__interrupt__"):
+                # Pause before tool call
+                console.print("\n[bold yellow]Agent wants to call a tool. Confirm? (y/n)\b")
+                ans = input()
+                if ans.lower() != "y":
+                    console.print("[red]Cancelled by user.[/]")
+                    break
+            else:
+                # Print token stream
+                console.print(chunk.get("messages", [])[0].get("content", ""), end="")
+        console.print()
+
+if __name__ == "__main__":
+    import asyncio
+    asyncio.run(run_chat())