"""Deterministic CDM capabilities exposed through the Tool Broker."""

from __future__ import annotations

from typing import Any, Dict

from langchain_core.tools import tool

from src.tools.fhir_memory import get_observations_by_patient


def _trend_statistics(values: list[float]) -> Dict[str, Any]:
    if len(values) < 2:
        return {"trend": "insufficient", "slope": 0.0, "projection": None}
    slope = (values[-1] - values[0]) / (len(values) - 1)
    trend = "rising" if slope > 0.5 else "falling" if slope < -0.5 else "stable"
    return {
        "trend": trend,
        "slope": float(slope),
        "projection": float(values[-1] + slope),
    }


@tool
def analyze_trends(patient_id: str) -> Dict[str, Any]:
    """Compute deterministic trend summaries from authorized FHIR observations."""
    observations = get_observations_by_patient.invoke({"patient_id": patient_id})
    if not isinstance(observations, list):
        return {"patient_id": patient_id, "metrics": {}, "status": "unavailable"}

    grouped: Dict[str, list[float]] = {}
    for observation in observations:
        try:
            resource = observation.get("resource", observation)
            display = resource["code"]["coding"][0]["display"]
            value = float(resource["valueQuantity"]["value"])
        except (AttributeError, KeyError, IndexError, TypeError, ValueError):
            continue
        grouped.setdefault(display, []).append(value)

    return {
        "patient_id": patient_id,
        "metrics": {
            metric: {"values": values, **_trend_statistics(values)}
            for metric, values in grouped.items()
        },
        "status": "completed",
    }