"""
Slide 31: Slide 4
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-031/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 31 ===
  from typing_extensions import TypedDict
  from langgraph.graph import StateGraph, START, END

> class State(TypedDict):
>     question: str
>     answer:   str
      steps:    int

  def answer(state: State) -> dict:
      return {"answer": f"echo: {state['question']}", "steps": 1}

  builder = StateGraph(State)
  builder.add_node("answer", answer)
  builder.add_edge(START, "answer")
  builder.add_edge("answer", END)
  graph = builder.compile()
>  
> print(graph.invoke({"question": "hi", "steps": 0}))
> # -> {'question': 'hi', 'answer': 'echo: hi', 'steps': 1}

// note: snippet has 19 lines, card fits ~17