"""
Slide 39: Slide 12
Section 2: LangGraph 1.0
Source: slides/section2-langgraph/section2.pptx

Сгенерировано автоматически из slide-NN.js / sectionN.pptx.
Паттерн провайдера скопирован из
bro-js/agents/teacher/assistant/src/angry_teacher/llm.py.

Запуск:
  cd langchain-evolution-deck
  cp .env.example .env   # заполни OPENAI_API_KEY
  python examples/slide-039/script.py
"""
import os
from dotenv import load_dotenv
from langchain_openai import ChatOpenAI

load_dotenv()

llm = ChatOpenAI(
    # model="openrouter/free",
    # model="qwen/qwen3.5-35b-a3b",
    model="openai/gpt-oss-20b",
    # model="nvidia/nemotron-3-nano",
    # model="qwen/qwen3.5-9b",
    base_url="https://llm.brojs.ru/v1",
    # base_url="https://api.minimax.io/v1",
    # base_url="http://0.0.0.0:8090/v1",
    # base_url="https://openrouter.ai/api/v1",
    # api_key=os.getenv("MINIMAX_API_KEY"),
    api_key=(os.getenv("OPENAI_API_KEY") or "").strip() or None,
    temperature=0.7,
    stream_usage=True,
)


# === Code from slide 39 ===
  from typing_extensions import TypedDict
  from langgraph.graph import StateGraph, START, END

  class State(TypedDict):
      needs_tool: bool
      answer: str

  def agent(state: State) -> dict:
      return {"answer": "model-output"}

  def tool_node(state: State) -> dict:
      return {"answer": "tool-output"}

  def route(state: State) -> str:
      # возвращаем ключ, который есть в path_map ниже
      return "tool_node" if state["needs_tool"] else END

  g = StateGraph(State)
> g.add_node("agent",     agent)
> g.add_node("tool_node", tool_node)
> g.add_edge(START, "agent")
> g.add_conditional_edges("agent", route, {
>     "tool_node": "tool_node",
      END: END,
  })
  g.add_edge("tool_node", END)
  app = g.compile()
  print(app.invoke({"needs_tool": True, "answer": ""}))

// note: snippet has 28 lines, card fits ~18