"""JSON API endpoints for the JA4 SOC Dashboard."""

from __future__ import annotations

import json
import logging
import os
from pathlib import Path
from typing import Any

from fastapi import APIRouter, HTTPException, Query
from pydantic import BaseModel

from backend.config import DB_PROCESSING, DB_LOGS, safe_identifier
from backend.database import query, query_scalar, execute

logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api")

# Pre-validate DB identifiers at import time
_DB = safe_identifier(DB_PROCESSING)
_DB_LOGS = safe_identifier(DB_LOGS)

# Whitelists for sort/order to prevent SQL injection
_DETECTION_SORT_COLS = {
    "detected_at", "src_ip", "ja4", "host", "anomaly_score",
    "threat_level", "recurrence", "hits", "hit_velocity",
    "fuzzing_index", "post_ratio", "campaign_id",
}
_SCORE_SORT_COLS = {
    "detected_at", "window_start", "src_ip", "ja4", "host",
    "anomaly_score", "raw_anomaly_score", "threat_level",
    "hits", "hit_velocity", "xgb_prob", "ae_recon_error",
}
_TRAFFIC_SORT_COLS = {
    "time", "src_ip", "method", "host", "path", "http_version",
    "header_user_agent", "ja4", "src_country_code",
}
_ORDER_VALUES = {"ASC", "DESC"}


def _validate_sort(value: str, whitelist: set[str], default: str) -> str:
    return value if value in whitelist else default


def _validate_order(value: str) -> str:
    return value.upper() if value.upper() in _ORDER_VALUES else "DESC"


# ---------------------------------------------------------------------------
# GET /api/overview
# ---------------------------------------------------------------------------
@router.get("/overview")
async def overview() -> dict[str, Any]:
    try:
        detections_24h = query_scalar(
            f"SELECT count() FROM {_DB}.ml_detected_anomalies "
            "WHERE detected_at >= now() - INTERVAL 1 DAY"
        ) or 0

        scored_24h = query_scalar(
            f"SELECT count() FROM {_DB}.ml_all_scores "
            "WHERE detected_at >= now() - INTERVAL 1 DAY"
        ) or 0

        threat_distribution = query(
            f"SELECT threat_level, count() AS cnt "
            f"FROM {_DB}.ml_all_scores "
            "WHERE detected_at >= now() - INTERVAL 1 DAY "
            "GROUP BY threat_level"
        )

        # Compute critical / high counts from distribution
        threat_map = {r["threat_level"]: r["cnt"] for r in threat_distribution}
        critical_count = threat_map.get("CRITICAL", 0)
        high_count = threat_map.get("HIGH", 0)

        unique_ips = query_scalar(
            f"SELECT uniq(src_ip) FROM {_DB}.ml_detected_anomalies "
            "WHERE detected_at >= now() - INTERVAL 1 DAY"
        ) or 0

        top_ips = query(
            f"SELECT toString(src_ip) AS src_ip, count() AS cnt, "
            f"max(anomaly_score) AS worst_score, "
            f"any(threat_level) AS threat_level, "
            f"any(asn_org) AS asn_org, any(country_code) AS country_code "
            f"FROM {_DB}.ml_detected_anomalies "
            "WHERE detected_at >= now() - INTERVAL 1 DAY "
            "GROUP BY src_ip ORDER BY cnt DESC LIMIT 10"
        )

        timeline = query(
            f"SELECT toStartOfHour(detected_at) AS hour, count() AS cnt "
            f"FROM {_DB}.ml_detected_anomalies "
            "WHERE detected_at >= now() - INTERVAL 1 DAY "
            "GROUP BY hour ORDER BY hour"
        )

        traffic_24h = query_scalar(
            f"SELECT count() FROM {_DB_LOGS}.http_logs "
            "WHERE time >= now() - INTERVAL 1 DAY"
        ) or 0

        models = query(
            f"SELECT model_name, count() AS scored "
            f"FROM {_DB}.ml_all_scores "
            "WHERE detected_at >= now() - INTERVAL 1 DAY "
            "GROUP BY model_name"
        )

        return {
            "detections_24h": detections_24h,
            "scored_24h": scored_24h,
            "traffic_24h": traffic_24h,
            "unique_ips": unique_ips,
            "critical_count": critical_count,
            "high_count": high_count,
            "threat_distribution": threat_distribution,
            "top_ips": top_ips,
            "timeline": [{"hour": str(r["hour"]), "cnt": r["cnt"]} for r in timeline],
            "models": models,
        }
    except Exception as exc:
        logger.exception("overview query failed")
        raise HTTPException(status_code=500, detail=str(exc))


# ---------------------------------------------------------------------------
# GET /api/detections
# ---------------------------------------------------------------------------
@router.get("/detections")
async def detections(
    page: int = Query(1, ge=1),
    per_page: int = Query(50, ge=1, le=500),
    sort: str = Query("detected_at"),
    order: str = Query("DESC"),
    threat_level: str | None = Query(None),
    search: str | None = Query(None),
) -> dict[str, Any]:
    sort = _validate_sort(sort, _DETECTION_SORT_COLS, "detected_at")
    order = _validate_order(order)
    offset = (page - 1) * per_page

    where_clauses = ["detected_at >= now() - INTERVAL 30 DAY"]
    params: dict[str, Any] = {}

    if threat_level:
        where_clauses.append("threat_level = {tl:String}")
        params["tl"] = threat_level

    if search:
        where_clauses.append(
            "(toString(src_ip) LIKE {search:String} OR host LIKE {search:String})"
        )
        params["search"] = f"%{search}%"

    where = " AND ".join(where_clauses)

    try:
        total = query_scalar(
            f"SELECT count() FROM {_DB}.ml_detected_anomalies WHERE {where}",
            params,
        )

        rows = query(
            f"SELECT *, toString(src_ip) AS src_ip_str "
            f"FROM {_DB}.ml_detected_anomalies "
            f"WHERE {where} ORDER BY {sort} {order} "
            f"LIMIT {{lim:UInt32}} OFFSET {{off:UInt32}}",
            {**params, "lim": per_page, "off": offset},
        )

        return {
            "data": rows,
            "total": total or 0,
            "page": page,
            "per_page": per_page,
            "pages": max(1, -(-((total or 0)) // per_page)),
        }
    except Exception as exc:
        logger.exception("detections query failed")
        raise HTTPException(status_code=500, detail=str(exc))


# ---------------------------------------------------------------------------
# GET /api/scores
# ---------------------------------------------------------------------------
@router.get("/scores")
async def scores(
    page: int = Query(1, ge=1),
    per_page: int = Query(50, ge=1, le=500),
    sort: str = Query("detected_at"),
    order: str = Query("DESC"),
    threat_level: str | None = Query(None),
    search: str | None = Query(None),
) -> dict[str, Any]:
    sort = _validate_sort(sort, _SCORE_SORT_COLS, "detected_at")
    order = _validate_order(order)
    offset = (page - 1) * per_page

    where_clauses = ["detected_at >= now() - INTERVAL 3 DAY"]
    params: dict[str, Any] = {}

    if threat_level:
        where_clauses.append("threat_level = {tl:String}")
        params["tl"] = threat_level

    if search:
        where_clauses.append(
            "(toString(src_ip) LIKE {search:String} OR host LIKE {search:String})"
        )
        params["search"] = f"%{search}%"

    where = " AND ".join(where_clauses)

    try:
        total = query_scalar(
            f"SELECT count() FROM {_DB}.ml_all_scores WHERE {where}",
            params,
        )

        rows = query(
            f"SELECT *, toString(src_ip) AS src_ip_str "
            f"FROM {_DB}.ml_all_scores "
            f"WHERE {where} ORDER BY {sort} {order} "
            f"LIMIT {{lim:UInt32}} OFFSET {{off:UInt32}}",
            {**params, "lim": per_page, "off": offset},
        )

        return {
            "data": rows,
            "total": total or 0,
            "page": page,
            "per_page": per_page,
            "pages": max(1, -(-((total or 0)) // per_page)),
        }
    except Exception as exc:
        logger.exception("scores query failed")
        raise HTTPException(status_code=500, detail=str(exc))


# ---------------------------------------------------------------------------
# GET /api/traffic
# ---------------------------------------------------------------------------
@router.get("/traffic")
async def traffic(
    page: int = Query(1, ge=1),
    per_page: int = Query(50, ge=1, le=500),
    sort: str = Query("time"),
    order: str = Query("DESC"),
    method: str | None = Query(None),
    host: str | None = Query(None),
    status: str | None = Query(None),
) -> dict[str, Any]:
    sort = _validate_sort(sort, _TRAFFIC_SORT_COLS, "time")
    order = _validate_order(order)
    offset = (page - 1) * per_page

    where_clauses = ["time >= now() - INTERVAL 1 DAY"]
    params: dict[str, Any] = {}

    if method:
        where_clauses.append("method = {method:String}")
        params["method"] = method

    if host:
        where_clauses.append("host LIKE {host:String}")
        params["host"] = f"%{host}%"

    if status is not None:
        where_clauses.append("http_version = {status:String}")
        params["status"] = status

    where = " AND ".join(where_clauses)

    try:
        total = query_scalar(
            f"SELECT count() FROM {_DB_LOGS}.http_logs WHERE {where}",
            params,
        )

        rows = query(
            f"SELECT time, toString(src_ip) AS src_ip, method, host, path, "
            f"http_version, header_user_agent, ja4, src_country_code "
            f"FROM {_DB_LOGS}.http_logs "
            f"WHERE {where} ORDER BY {sort} {order} "
            f"LIMIT {{lim:UInt32}} OFFSET {{off:UInt32}}",
            {**params, "lim": per_page, "off": offset},
        )

        return {
            "data": rows,
            "total": total or 0,
            "page": page,
            "per_page": per_page,
            "pages": max(1, -(-((total or 0)) // per_page)),
        }
    except Exception as exc:
        logger.exception("traffic query failed")
        raise HTTPException(status_code=500, detail=str(exc))


# ---------------------------------------------------------------------------
# GET /api/ip/{ip}
# ---------------------------------------------------------------------------
@router.get("/ip/{ip}")
async def ip_detail(ip: str) -> dict[str, Any]:
    # Strip ::ffff: prefix for IPv4-mapped addresses
    clean_ip = ip.replace("::ffff:", "")
    params = {"ip": clean_ip}
    try:
        detections = query(
            f"SELECT *, toString(src_ip) AS src_ip_str "
            f"FROM {_DB}.ml_detected_anomalies "
            "WHERE src_ip = toIPv6({ip:String}) "
            "AND detected_at >= now() - INTERVAL 30 DAY "
            "ORDER BY detected_at DESC",
            params,
        )

        all_scores = query(
            f"SELECT *, toString(src_ip) AS src_ip_str "
            f"FROM {_DB}.ml_all_scores "
            "WHERE src_ip = toIPv6({ip:String}) "
            "AND detected_at >= now() - INTERVAL 3 DAY "
            "ORDER BY detected_at DESC",
            params,
        )

        http_logs = query(
            f"SELECT time, method, host, path, http_version, header_user_agent, ja4 "
            f"FROM {_DB_LOGS}.http_logs "
            "WHERE src_ip = toIPv4OrZero({ip:String}) "
            "AND time >= now() - INTERVAL 1 DAY "
            "ORDER BY time DESC LIMIT 100",
            params,
        )

        ai_features: list[dict] = []
        try:
            ai_features = query(
                f"SELECT * FROM {_DB}.view_ai_features_1h "
                "WHERE src_ip = toIPv6({ip:String}) LIMIT 1",
                params,
            )
        except Exception:
            logger.debug("view_ai_features_1h unavailable for %s", ip)

        recurrence: list[dict] = []
        try:
            recurrence = query(
                f"SELECT * FROM {_DB}.view_ip_recurrence "
                "WHERE src_ip = toIPv6({ip:String})",
                params,
            )
        except Exception:
            logger.debug("view_ip_recurrence unavailable for %s", ip)

        return {
            "ip": ip,
            "detections": detections,
            "scores": all_scores,
            "http_logs": http_logs,
            "ai_features": ai_features,
            "recurrence": recurrence,
        }
    except Exception as exc:
        logger.exception("ip detail query failed for %s", ip)
        raise HTTPException(status_code=500, detail=str(exc))


# ---------------------------------------------------------------------------
# GET /api/features
# ---------------------------------------------------------------------------
@router.get("/features")
async def features() -> dict[str, Any]:
    result: dict[str, Any] = {"ai_features": {}, "thesis_features": {}}
    try:
        ai_stats = query(
            f"SELECT count() AS total, "
            f"avg(hits) AS avg_hits, "
            f"avg(hit_velocity) AS avg_hit_velocity, "
            f"avg(fuzzing_index) AS avg_fuzzing_index, "
            f"avg(post_ratio) AS avg_post_ratio "
            f"FROM {_DB}.view_ai_features_1h"
        )
        if ai_stats:
            result["ai_features"] = ai_stats[0]
    except Exception:
        logger.debug("view_ai_features_1h not available")

    try:
        thesis_stats = query(
            f"SELECT count() AS total, "
            f"avg(hits) AS avg_hits, "
            f"avg(hit_velocity) AS avg_hit_velocity, "
            f"avg(fuzzing_index) AS avg_fuzzing_index, "
            f"avg(post_ratio) AS avg_post_ratio "
            f"FROM {_DB}.view_thesis_features_1h"
        )
        if thesis_stats:
            result["thesis_features"] = thesis_stats[0]
    except Exception:
        logger.debug("view_thesis_features_1h not available")

    return result


# ---------------------------------------------------------------------------
# GET /api/models
# ---------------------------------------------------------------------------
_MODEL_DIR = Path("/data/models")


@router.get("/models")
async def models() -> dict[str, Any]:
    model_info: list[dict[str, Any]] = []

    if _MODEL_DIR.is_dir():
        for p in sorted(_MODEL_DIR.glob("*.json")):
            try:
                data = json.loads(p.read_text())
                model_info.append(data)
            except Exception:
                logger.warning("Could not read model metadata %s", p)

    # Also fetch latest scoring stats from ClickHouse
    scoring_stats: list[dict] = []
    try:
        scoring_stats = query(
            f"SELECT model_name, count() AS scored, "
            f"min(detected_at) AS first_seen, max(detected_at) AS last_seen "
            f"FROM {_DB}.ml_all_scores "
            "WHERE detected_at >= now() - INTERVAL 7 DAY "
            "GROUP BY model_name"
        )
    except Exception:
        logger.debug("could not fetch model scoring stats")

    return {"models": model_info, "scoring_stats": scoring_stats}


# ---------------------------------------------------------------------------
# POST /api/classify  — SOC analyst feedback
# ---------------------------------------------------------------------------
class ClassifyRequest(BaseModel):
    src_ip: str
    classification: str  # bot | legitimate | suspicious
    comment: str = ""


_VALID_CLASSIFICATIONS = {"bot", "legitimate", "suspicious"}
_feedback_table_ensured = False


def _ensure_feedback_table() -> None:
    global _feedback_table_ensured
    if _feedback_table_ensured:
        return
    execute(
        f"CREATE TABLE IF NOT EXISTS {_DB}.soc_feedback ("
        "  created_at DateTime DEFAULT now(),"
        "  src_ip IPv6,"
        "  classification LowCardinality(String),"
        "  comment String"
        ") ENGINE = MergeTree() ORDER BY (src_ip, created_at)"
    )
    _feedback_table_ensured = True


@router.post("/classify")
async def classify(body: ClassifyRequest) -> dict[str, Any]:
    if body.classification not in _VALID_CLASSIFICATIONS:
        raise HTTPException(
            status_code=422,
            detail=f"classification must be one of {_VALID_CLASSIFICATIONS}",
        )
    try:
        _ensure_feedback_table()
        execute(
            f"INSERT INTO {_DB}.soc_feedback (src_ip, classification, comment) VALUES "
            "(toIPv6({ip:String}), {cls:String}, {cmt:String})",
            {"ip": body.src_ip, "cls": body.classification, "cmt": body.comment},
        )
        return {"status": "ok", "src_ip": body.src_ip, "classification": body.classification}
    except Exception as exc:
        logger.exception("classify insert failed")
        raise HTTPException(status_code=500, detail=str(exc))


# ---------------------------------------------------------------------------
# GET /api/classifications — recent SOC feedback
# ---------------------------------------------------------------------------
@router.get("/classifications")
async def classifications() -> dict[str, Any]:
    try:
        _ensure_feedback_table()
        rows = query(
            f"SELECT created_at, toString(src_ip) AS src_ip, classification, comment "
            f"FROM {_DB}.soc_feedback "
            "ORDER BY created_at DESC LIMIT 50"
        )
        return {"data": rows}
    except Exception as exc:
        logger.exception("classifications query failed")
        return {"data": []}