from __future__ import annotations
from typing import Dict, Any, List, Tuple

from gridgent.core.types import Step
from gridgent.tools.grid_stub import run_power_flow_scenario, get_feeder_summary


class PlanningAgent:
    def plan_and_analyze(self, query: str, intent_info: Dict[str, Any]) -> Tuple[str, Dict[str, Any], List[Step]]:
        intent = intent_info["intent"]
        steps: List[Step] = []

        if intent == "unknown":
            msg = (
                "Received an underspecified or conversational query; no grid scenario was run. "
                "Please mention at least a feeder (F1/F2/F3) and a change in MW load or PV."
            )
            steps.append(
                Step(
                    role="planning_agent",
                    content=msg,
                    meta={"intent": intent},
                )
            )
            technical_summary: Dict[str, Any] = {
                "intent": intent,
                "message": msg,
            }
            return "no_scenario", technical_summary, steps

        has_mw = bool(intent_info.get("has_mw"))
        has_feeder = bool(intent_info.get("has_feeder"))

        if intent == "explanation" and not has_mw and not has_feeder:
            steps.append(
                Step(
                    role="planning_agent",
                    content="No specific feeder or MW change detected; treating as conceptual explanation request.",
                    meta={"intent": intent},
                )
            )
            technical_summary = {
                "intent": intent,
                "topic_hint": query.strip(),
            }
            return "conceptual", technical_summary, steps

        feeder = intent_info.get("feeder")
        defaulted_feeder = False
        if not feeder:
            feeder = "F1"
            defaulted_feeder = True

        added_pv = float(intent_info.get("added_pv_mw", 0.0))
        added_load = float(intent_info.get("added_load_mw", 0.0))

        summary = (
            f"Analyzing feeder {feeder} with added PV={added_pv:.1f} MW, "
            f"added load={added_load:.1f} MW using a simplified power-flow stub."
        )
        steps.append(
            Step(
                role="planning_agent",
                content=summary,
                meta={"feeder": feeder, "defaulted_feeder": defaulted_feeder},
            )
        )

        pf_result = run_power_flow_scenario(feeder, added_pv_mw=added_pv, added_load_mw=added_load)
        pf_dict = pf_result.to_dict()
        steps.append(
            Step(
                role="tool",
                content="Ran simplified power-flow scenario (demo).",
                meta=pf_dict,
            )
        )

        feeder_meta = get_feeder_summary(feeder)
        steps.append(
            Step(
                role="tool",
                content="Retrieved static feeder metadata from config.",
                meta=feeder_meta,
            )
        )

        technical_summary: Dict[str, Any] = {
            "intent": intent,
            "feeder": feeder,
            "added_pv_mw": added_pv,
            "added_load_mw": added_load,
            "power_flow": pf_dict,
            "feeder_meta": feeder_meta,
        }

        rating_pct = pf_dict["peak_loading_pct"]
        technical_summary["loading_margin_pct"] = max(0.0, 100.0 - rating_pct)

        return "ok", technical_summary, steps