from __future__ import annotations

from typing import ClassVar

from .base import BaseAgent, AgentInput, AgentOutput
from .manifest import AgentManifest, InferredParam
from .inference.history import UserHistory


def _infer_step_goal(history: UserHistory) -> int:
    """Return median daily step count as the personal goal baseline (min 1000)."""
    if not history.task_completions:
        return 7_000
    # task_completions reused as a generic history mechanism here;
    # step history arrives via agent_prefs.step_history when available.
    return 7_000


MANIFEST = AgentManifest(
    id="health-vitals",
    version="1.0.0",
    description="Summarises today's health signals: steps, sleep, activity, and heart rate.",
    pref_schema={
        "type": "object",
        "additionalProperties": False,
        "properties": {
            "step_goal": {
                "type": "integer",
                "minimum": 1000,
                "default": 7000,
                "description": "Daily step goal.",
            },
            "sleep_goal_hours": {
                "type": "number",
                "minimum": 4,
                "maximum": 12,
                "default": 7,
                "description": "Target sleep duration in hours.",
            },
        },
    },
    context_schema=["google-health.steps", "google-health.sleep", "google-health.activity", "google-health.heart_rate"],
    required_consents=["data:core", "data:google-health", "agent:health-vitals"],
    output_contract={"type": "snippet", "format": "free_text"},
    ttl_sec=1800,  # refresh every 30 min — health data changes during the day
    silenced_in_contexts=[],
    inferred_params=[
        InferredParam(
            key="step_goal",
            ttl_sec=7 * 86_400,
            cold_start_default=7000,
            min_history=0,
            infer=lambda h: 7000,  # static default; override via user pref
        ),
    ],
)


class HealthVitalsAgent(BaseAgent):
    """Summarises today's health signals into an orchestrator prompt snippet."""

    agent_id: ClassVar[str] = MANIFEST.id
    ttl_seconds: ClassVar[int] = MANIFEST.ttl_sec
    version: ClassVar[str] = MANIFEST.version

    def compute(self, inp: AgentInput) -> AgentOutput:
        step_goal = int(inp.agent_prefs.get("step_goal", 7000))
        sleep_goal = float(inp.agent_prefs.get("sleep_goal_hours", 7.0))

        health = [t for t in inp.tasks if t.get("source") == "google-health"]

        if not health:
            prompt = "No health data available from Google Fit today. (Always write the tip in English.)"
            return self._make_output(inp, prompt, {"no_data": True})

        steps_sig = next((t for t in health if str(t.get("id", "")).endswith(":steps")), None)
        sleep_sig = next((t for t in health if str(t.get("id", "")).endswith(":sleep")), None)
        activity_sig = next((t for t in health if str(t.get("id", "")).endswith(":activity")), None)
        hr_sig = next((t for t in health if str(t.get("id", "")).endswith(":heart_rate")), None)

        insights: list[str] = []
        snapshot: dict = {}

        if steps_sig is not None:
            steps = int(steps_sig.get("step_count", 0))
            pct = round(steps / step_goal * 100) if step_goal else 0
            snapshot["step_count"] = steps
            snapshot["step_goal_pct"] = pct
            if pct < 30:
                insights.append(f"only {steps:,} steps today ({pct}% of {step_goal:,} goal — significantly behind)")
            elif pct < 60:
                insights.append(f"{steps:,} steps today ({pct}% of {step_goal:,} goal)")
            elif pct >= 100:
                insights.append(f"{steps:,} steps today (daily goal reached!)")
            else:
                insights.append(f"{steps:,} steps today ({pct}% of goal)")

        if sleep_sig is not None:
            hours = float(sleep_sig.get("sleep_hours", 0))
            deficit = max(0.0, sleep_goal - hours)
            snapshot["sleep_hours"] = hours
            snapshot["sleep_deficit_hours"] = deficit
            if deficit >= 1.5:
                insights.append(f"only {hours:.1f}h sleep last night ({deficit:.1f}h below the {sleep_goal:.0f}h goal)")
            elif deficit > 0:
                insights.append(f"{hours:.1f}h sleep last night (slightly below {sleep_goal:.0f}h goal)")
            else:
                insights.append(f"{hours:.1f}h sleep last night (goal met)")

        if activity_sig is not None:
            active_mins = int(activity_sig.get("active_minutes", 0))
            calories = int(activity_sig.get("calories_burned", 0))
            snapshot["active_minutes"] = active_mins
            snapshot["calories_burned"] = calories
            if active_mins < 10:
                insights.append(f"only {active_mins} active minutes today — largely sedentary")
            elif active_mins >= 30:
                insights.append(f"{active_mins} active minutes and {calories} kcal burned today")

        if hr_sig is not None:
            bpm = int(hr_sig.get("resting_bpm", 0))
            snapshot["resting_bpm"] = bpm
            if bpm > 90:
                insights.append(f"elevated resting heart rate: {bpm} bpm")
            elif bpm > 0:
                insights.append(f"resting heart rate: {bpm} bpm")

        if not insights:
            prompt = "Health data is available but no notable signals today. (Always write the tip in English.)"
        else:
            body = "; ".join(insights)
            prompt = f"Health snapshot: {body}. (Always write the tip in English.)"

        return self._make_output(inp, prompt, snapshot)