add: main.py

main.py

@@ -0,0 +1,73 @@
+import os
+import asyncio
+from langchain_openai import ChatOpenAI
+from langchain.tools import tool
+from deepagents import create_deep_agent
+from deepagents.backends import CompositeBackend, LocalShellBackend, FilesystemBackend
+from langchain.agents import create_agent
+
+# --- LLM configuration (OpenRouter) ---
+llm = ChatOpenAI(
+    model="openai/gpt-oss-20b:free",
+    base_url="https://openrouter.ai/api/v1",
+    api_key=os.getenv("OPENAI_API_KEY"),
+    temperature=0.7,
+)
+
+# --- Backend for deepagents ---
+backend = CompositeBackend([
+    LocalShellBackend(workspace_dir="./workspace"),
+    FilesystemBackend(),
+])
+
+# --- Tool with sub‑agent that returns a price table ---
+@tool
+def get_price(product: str, city: str) -> str:
+    """Retrieve price for product in city. Returns a Markdown table:
+    | Продукт | Цена (руб.) | Магазин |
+    """
+    # Sub‑agent to generate a realistic price table
+    sub_llm = ChatOpenAI(
+        model="openai/gpt-oss-20b:free",
+        base_url="https://openrouter.ai/api/v1",
+        api_key=os.getenv("OPENAI_API_KEY"),
+        temperature=0.0,
+    )
+    sub_agent = create_agent(
+        model=sub_llm,
+        tools=[],
+        system_prompt=f"Generate a realistic price for {product} in {city}. Return the result as a Markdown table with columns Продукт, Цена (руб.), Магазин.",
+    )
+    # Ask sub‑agent to produce the table
+    res = sub_agent.invoke(
+        {"messages": [{"role": "user", "content": "Provide the price table"}]}
+    )
+    return res["messages"][-1]["content"]
+
+# --- Main hierarchical agent ---
+main_agent = create_deep_agent(
+    model=llm,
+    tools=[get_price],
+    backend=backend,
+    system_prompt="Ты помощник по планированию покупок. Принимаешь список продуктов, узнаёшь цены и считаешь итоговую стоимость.",
+)
+
+async def main():
+    question = "Помоги составить список покупок: молоко, хлеб, яблоки. Я нахожусь в Казани."
+    result = await main_agent.ainvoke(
+        {"messages": [{"role": "human", "content": question}]},
+        {"configurable": {"thread_id": "shopping-session-1"}},
+    )
+    # Print all messages in order (tool calls and final answer)
+    for msg in result["messages"]:
+        if "content" in msg:
+            print(msg["content"])
+        if "tool_calls" in msg:
+            for call in msg["tool_calls"]:
+                print(f"{call['name']}({call['args']})")
+    # Final answer (last message)
+    print("\n--- Final answer ---")
+    print(result["messages"][-1]["content"])
+
+if __name__ == "__main__":
+    asyncio.run(main())