"""
Slide 42: Slide 15
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-042/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 42 ===
> # SQLite -- файл на диске, идеален для dev / small-prod
  from langgraph.checkpoint.sqlite import SqliteSaver
>  
> with SqliteSaver.from_conn_string("./checkpoints.db") as cp:
>     app = g.compile(checkpointer=cp)
      cfg = {"configurable": {"thread_id": "u1"}}
      app.invoke({"messages": []}, cfg)

  # данные переживают рестарт процесса.
  # Для asyncio-варианта -- aiosqlite.

> # Postgres -- production-grade, multi-instance
  from langgraph.checkpoint.postgres import PostgresSaver
>  
  DB = "postgresql://user:pass@host:5432/lg"
  with PostgresSaver.from_conn_string(DB) as cp:
>     # первый запуск создаст schema
      cp.setup()
      app = g.compile(checkpointer=cp)
      cfg = {"configurable": {"thread_id": "u1"}}
      app.invoke({"messages": []}, cfg)