import logging
from typing import Dict, List

from dotenv import load_dotenv
from langchain_openai import ChatOpenAI

from src.core.AgentCommand import AgentCommand
from src.core.FinanceState import FinanceState
from src.core.errors import add_error
from src.core.settings import get_settings

logger = logging.getLogger(__name__)


class GoalPlanningAgent(AgentCommand):
    """
    Education-focused goal planning. Produces a plan and assumptions without directing trades.
    """

    def __init__(self, state: FinanceState):
        load_dotenv()
        self.state = state
        settings = get_settings()
        self.client = ChatOpenAI(model=settings.models.agent_model)

    def process(self):
        trace_id = str(self.state.get("trace_id") or "")
        logger.info("[trace=%s] GoalPlanningAgent.start", trace_id)
        user_query = self.state.get("user_query", "")
        user_profile = self.state.get("user_profile", {}) or {}
        history: List[Dict[str, str]] = self.state.get("conversation_history", []) or []

        system = (
            "You are a financial education assistant. You must NOT provide personalized financial advice, "
            "trade instructions, or guarantees. Provide general education and planning frameworks only. "
            "Always include a short disclaimer: 'Educational only, not financial advice.' "
            "Be conservative and highlight risks and assumptions."
        )

        # Keep history short to avoid blowing context. We only pass the last few turns.
        recent = history[-6:] if isinstance(history, list) else []
        history_text = "\n".join(
            [f"{m.get('role','')}: {m.get('content','')}" for m in recent]
        ).strip()

        prompt = f"""
Create an education-only financial goal plan for the user.

User profile (may be incomplete):
{user_profile}

Recent conversation:
{history_text if history_text else "(none)"}

User request:
{user_query}

Output format:
1) Quick disclaimer line
2) Clarifying questions (max 5) if needed
3) A simple plan with assumptions:
   - Goal
   - Time horizon
   - Monthly/annual contribution estimate approach (no promises)
   - Asset allocation ranges by risk level (broad ranges only)
   - What to track monthly
4) Risks and what could change
"""

        try:
            msg = self.client.invoke(
                [
                    {"role": "system", "content": system},
                    {"role": "user", "content": prompt},
                ],
                temperature=0.2,
            )
            self.state["response"] = msg.content
        except Exception as e:
            logger.exception("[trace=%s] GoalPlanningAgent failed", trace_id)
            add_error(
                self.state,
                code="goal_planning_error",
                message=str(e),
                agent="goal_planning_agent",
            )
            self.state["response"] = (
                "Educational only, not financial advice.\n\n"
                f"I couldn't generate a goal plan due to an internal error: {e}"
            )
        return self.state