75 lines
2.5 KiB
Python
75 lines
2.5 KiB
Python
import os
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import asyncio
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from langchain_openai import ChatOpenAI
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from langchain.tools import tool
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from langchain.agents import create_agent
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from langchain_core.messages import HumanMessage
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from deepagents import create_deep_agent
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from deepagents.backends import CompositeBackend, LocalShellBackend, FilesystemBackend
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# ---------- LLM ----------
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# Use OpenRouter – cloud API, no local GPU required
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llm = ChatOpenAI(
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model="openai/gpt-oss-20b:free",
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base_url="https://openrouter.ai/api/v1",
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api_key=os.getenv("OPENAI_API_KEY"),
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temperature=0.7,
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)
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# ---------- Backend ----------
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backend = CompositeBackend([
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LocalShellBackend(workspace_dir="./workspace"),
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FilesystemBackend(),
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])
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# ---------- Tool with sub‑agent ----------
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@tool
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def get_price(product: str, city: str) -> str:
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"""Return a realistic price table for a product in a city.
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The tool internally creates a sub‑agent that generates the table.
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"""
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# Sub‑agent that simply produces a price table
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sub_agent = create_agent(
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model=llm,
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tools=[],
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system_prompt=f"You are a price estimator for {city}. Provide a realistic price for {product} in a table format.",
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)
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prompt = (
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f"Generate a table with columns Продукт, Цена (руб.), Магазин for product '{product}' in city '{city}'."
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)
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result = sub_agent.invoke({"messages": [HumanMessage(content=prompt)]})
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# The last message contains the table
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return result["messages"][-1].content
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# ---------- Main agent ----------
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agent = create_deep_agent(
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model=llm,
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tools=[get_price],
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backend=backend,
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system_prompt="Ты помощник по планированию покупок.",
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)
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# ---------- Helper to pretty‑print messages ----------
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def format_message(msg):
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if hasattr(msg, "content") and msg.content:
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return msg.content
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if hasattr(msg, "tool_calls") and msg.tool_calls:
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call = msg.tool_calls[0]
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return f"{call['name']}({call['args']})"
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return ""
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# ---------- Main execution ----------
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async def main():
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user_query = "Помоги составить список покупок: молоко, хлеб, яблоки. Я нахожусь в Казани."
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result = await agent.ainvoke(
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{"messages": [HumanMessage(content=user_query)]},
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{"configurable": {"thread_id": "session-1"}},
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)
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# Print all messages in order
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for msg in result["messages"]:
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print(format_message(msg))
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print("---")
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if __name__ == "__main__":
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asyncio.run(main()) |