92 lines
3.1 KiB
Python
92 lines
3.1 KiB
Python
import os
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from langchain_openai import ChatOpenAI
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from langchain_core.messages import HumanMessage, SystemMessage
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from langchain.tools import tool
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from langgraph.checkpoint.memory import MemorySaver
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from langgraph.types import Command
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from langgraph.graph import StateGraph, START, END
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from langgraph.graph.message import add_messages
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from rich.console import Console
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# LLM setup
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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=0.0,
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)
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console = Console()
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# Dummy tool – can be replaced by real implementation
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@tool
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def get_price(query: str) -> str:
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"""Return a fake price for demonstration."""
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return f"Цена для {query} – 100₽"
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# State definition
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class ChatState(dict):
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messages: list = add_messages
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location: str = "start"
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inventory: list = []
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# Agent graph
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builder = StateGraph(ChatState)
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# Node that runs the LLM and returns tool calls
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async def llm_node(state: ChatState):
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system = SystemMessage(content="You are a helpful assistant. Use the get_price tool if needed.")
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response = await llm.ainvoke([system] + state["messages"], config={"configurable": {"thread_id": "chat-1"}})
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return {"messages": [response]}
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# Node that handles tool calls (only get_price)
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async def tool_node(state: ChatState):
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last_msg = state["messages"][-1]
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if hasattr(last_msg, "tool_calls") and last_msg.tool_calls:
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tool_call = last_msg.tool_calls[0]
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name = tool_call["name"]
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args = tool_call["args"]
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if name == "get_price":
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result = get_price(args)
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# Append tool result to messages
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state["messages"].append(HumanMessage(content=result))
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return state
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builder.add_node("llm", llm_node)
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builder.add_node("tool", tool_node)
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builder.add_edge(START, "llm")
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builder.add_edge("llm", "tool")
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builder.add_edge("tool", END)
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chat = builder.compile(checkpointer=MemorySaver(), interrupt_before=["tool"])
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# Main loop
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while True:
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user_input = console.input("\nВы: ")
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if user_input.lower() in {"exit", "quit"}:
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break
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# Add user message
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chat.add_state({"messages": [HumanMessage(content=user_input)]})
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# Run graph with interrupt handling
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state = chat.get_state({"configurable": {"thread_id": "chat-1"}})
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while True:
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result = await chat.ainvoke(state, {"configurable": {"thread_id": "chat-1"}})
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# If interrupted before tool
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if "__interrupt__" in result and result["__interrupt__"][0]["name"] == "tool":
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console.print("\nАгент хочет вызвать инструмент: get_price")
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ans = console.input("Разрешить? (Y/n): ")
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if ans.lower() in {"", "y", "yes"}:
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# resume
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state = chat.get_state({"configurable": {"thread_id": "chat-1"}})
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continue
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else:
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console.print("Отменено")
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break
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# Print assistant response
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for msg in result["messages"]:
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if msg.role == "assistant":
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console.print(msg.content)
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break
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console.print("\nДо свидания!")
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