"""
Simple graph nodes.

- greeting_node: contextualized LLM response (greeting / thanks / goodbye)
- default_node: static response for out-of-scope requests
"""

from langchain_core.messages import AIMessage, SystemMessage, HumanMessage
from langchain_openai import ChatOpenAI
from utils.config import LLM_MODEL_NAME
from utils.i18n import t, greeting_prompt


# Dedicated LLM for greetings with high temperature (variability in the responses).
# The global LLM (temperature=0) is deterministic for classification/translation.
_greeting_llm = ChatOpenAI(model=LLM_MODEL_NAME, temperature=0.9)


def create_greeting_node():
    """Creates the greetings node with a dedicated LLM (temperature=0.9) for varied responses."""
    def greeting_node(state):
        greeting_type = state.get("greeting_type", "greeting")
        prompt = greeting_prompt(greeting_type)  # localized via RESPONSE_LANG
        user_msg = state["messages"][-1].content

        try:
            response = _greeting_llm.invoke([
                SystemMessage(content=prompt),
                HumanMessage(content=user_msg),
            ])
            return {"messages": [AIMessage(content=response.content.strip())]}
        except Exception:
            return {"messages": [AIMessage(content=t("greeting_fallback"))]}

    return greeting_node


def default_node(state):
    """Handles out-of-scope requests (returns, shipping, account, bugs).
    Refers to human support."""
    return {"messages": [AIMessage(content=t("default_out_of_scope"))]}