"""
Bill classifier and Member Effectiveness Score workers.

Tasks:
  classify_bill_category      — lightweight LLM call; triggered after brief generation
  fetch_bill_cosponsors       — Congress.gov cosponsor fetch; triggered on new bill
  calculate_effectiveness_scores — nightly beat task
  backfill_bill_categories    — one-time backfill for existing bills
  backfill_all_bill_cosponsors — one-time backfill for existing bills
"""
import json
import logging
import time
from datetime import datetime, timezone

from sqlalchemy import text

from app.config import settings
from app.database import get_sync_db
from app.models import Bill, BillCosponsor, BillDocument, Member
from app.models.setting import AppSetting
from app.services import congress_api
from app.services.llm_service import RateLimitError, get_llm_provider
from app.workers.celery_app import celery_app

logger = logging.getLogger(__name__)

# ── Classification ─────────────────────────────────────────────────────────────

_CLASSIFICATION_PROMPT = """\
Classify this bill into exactly one category.

Categories:
- substantive: Creates, modifies, or repeals policy, programs, regulations, funding, or rights. Real legislative work.
- commemorative: Names buildings/post offices, recognizes awareness days/weeks, honors individuals or events with no policy effect.
- administrative: Technical corrections, routine reauthorizations, housekeeping changes with no new policy substance.

Respond with ONLY valid JSON: {{"category": "substantive" | "commemorative" | "administrative"}}

BILL TITLE: {title}

BILL TEXT (excerpt):
{excerpt}

Classify now:"""

_VALID_CATEGORIES = {"substantive", "commemorative", "administrative"}


@celery_app.task(
    bind=True,
    max_retries=3,
    rate_limit=f"{settings.LLM_RATE_LIMIT_RPM}/m",
    name="app.workers.bill_classifier.classify_bill_category",
)
def classify_bill_category(self, bill_id: str, document_id: int):
    """Set bill_category via a cheap one-shot LLM call. Idempotent."""
    db = get_sync_db()
    try:
        bill = db.get(Bill, bill_id)
        if not bill or bill.bill_category:
            return {"status": "skipped"}

        doc = db.get(BillDocument, document_id)
        excerpt = (doc.raw_text[:1200] if doc and doc.raw_text else "").strip()

        prov_row = db.get(AppSetting, "llm_provider")
        model_row = db.get(AppSetting, "llm_model")
        provider = get_llm_provider(
            prov_row.value if prov_row else None,
            model_row.value if model_row else None,
        )

        prompt = _CLASSIFICATION_PROMPT.format(
            title=bill.title or "Unknown",
            excerpt=excerpt or "(no text available)",
        )

        raw = provider.generate_text(prompt).strip()
        # Strip markdown fences if present
        if raw.startswith("```"):
            raw = raw.split("```")[1].lstrip("json").strip()
            raw = raw.rstrip("```").strip()

        data = json.loads(raw)
        category = data.get("category", "").lower()
        if category not in _VALID_CATEGORIES:
            logger.warning(f"classify_bill_category: invalid category '{category}' for {bill_id}, defaulting to substantive")
            category = "substantive"

        bill.bill_category = category
        db.commit()
        logger.info(f"Bill {bill_id} classified as '{category}'")
        return {"status": "ok", "bill_id": bill_id, "category": category}

    except RateLimitError as exc:
        db.rollback()
        raise self.retry(exc=exc, countdown=exc.retry_after)
    except Exception as exc:
        db.rollback()
        logger.error(f"classify_bill_category failed for {bill_id}: {exc}")
        raise self.retry(exc=exc, countdown=120)
    finally:
        db.close()


@celery_app.task(bind=True, max_retries=3, name="app.workers.bill_classifier.backfill_bill_categories")
def backfill_bill_categories(self):
    """Queue classification for all bills with text but no category."""
    db = get_sync_db()
    try:
        rows = db.execute(text("""
            SELECT bd.bill_id, bd.id AS document_id
            FROM bill_documents bd
            JOIN bills b ON b.bill_id = bd.bill_id
            WHERE b.bill_category IS NULL AND bd.raw_text IS NOT NULL
        """)).fetchall()

        queued = 0
        for row in rows:
            classify_bill_category.delay(row.bill_id, row.document_id)
            queued += 1
            time.sleep(0.05)

        logger.info(f"backfill_bill_categories: queued {queued} classification tasks")
        return {"queued": queued}
    finally:
        db.close()


# ── Co-sponsor fetching ────────────────────────────────────────────────────────

@celery_app.task(bind=True, max_retries=3, name="app.workers.bill_classifier.fetch_bill_cosponsors")
def fetch_bill_cosponsors(self, bill_id: str):
    """Fetch and store cosponsor list from Congress.gov. Idempotent."""
    db = get_sync_db()
    try:
        bill = db.get(Bill, bill_id)
        if not bill or bill.cosponsors_fetched_at:
            return {"status": "skipped"}

        known_bioguides = {row[0] for row in db.execute(text("SELECT bioguide_id FROM members")).fetchall()}
        inserted = 0
        offset = 0

        while True:
            data = congress_api.get_bill_cosponsors(
                bill.congress_number, bill.bill_type, bill.bill_number, offset=offset
            )
            cosponsors = data.get("cosponsors", [])
            if not cosponsors:
                break

            for cs in cosponsors:
                bioguide_id = cs.get("bioguideId")
                # Only link to members we've already ingested
                if bioguide_id and bioguide_id not in known_bioguides:
                    bioguide_id = None

                # Skip if we already have this (bioguide_id, bill_id) pair
                if bioguide_id:
                    exists = db.query(BillCosponsor).filter_by(
                        bill_id=bill_id, bioguide_id=bioguide_id
                    ).first()
                    if exists:
                        continue

                date_str = cs.get("sponsorshipDate")
                try:
                    sponsored_date = datetime.strptime(date_str, "%Y-%m-%d").date() if date_str else None
                except ValueError:
                    sponsored_date = None

                db.add(BillCosponsor(
                    bill_id=bill_id,
                    bioguide_id=bioguide_id,
                    name=cs.get("fullName") or cs.get("name"),
                    party=cs.get("party"),
                    state=cs.get("state"),
                    sponsored_date=sponsored_date,
                ))
                inserted += 1

            db.commit()
            offset += 250
            if len(cosponsors) < 250:
                break
            time.sleep(0.25)

        bill.cosponsors_fetched_at = datetime.now(timezone.utc)
        db.commit()
        return {"bill_id": bill_id, "inserted": inserted}

    except Exception as exc:
        db.rollback()
        logger.error(f"fetch_bill_cosponsors failed for {bill_id}: {exc}")
        raise self.retry(exc=exc, countdown=60)
    finally:
        db.close()


@celery_app.task(bind=True, name="app.workers.bill_classifier.backfill_all_bill_cosponsors")
def backfill_all_bill_cosponsors(self):
    """Queue cosponsor fetches for all bills that haven't been fetched yet."""
    db = get_sync_db()
    try:
        rows = db.execute(text(
            "SELECT bill_id FROM bills WHERE cosponsors_fetched_at IS NULL"
        )).fetchall()

        queued = 0
        for row in rows:
            fetch_bill_cosponsors.delay(row.bill_id)
            queued += 1
            time.sleep(0.05)

        logger.info(f"backfill_all_bill_cosponsors: queued {queued} tasks")
        return {"queued": queued}
    finally:
        db.close()


# ── Effectiveness scoring ──────────────────────────────────────────────────────

def _distance_points(latest_action_text: str | None) -> int:
    """Map latest action text to a distance-traveled score."""
    text = (latest_action_text or "").lower()
    if "became public law" in text or "signed by president" in text or "enacted" in text:
        return 50
    if "passed house" in text or "passed senate" in text or "agreed to in" in text:
        return 20
    if "placed on" in text and "calendar" in text:
        return 10
    if "reported by" in text or "ordered to be reported" in text or "discharged" in text:
        return 5
    return 1


def _bipartisan_multiplier(db, bill_id: str, sponsor_party: str | None) -> float:
    """1.5x if ≥20% of cosponsors are from the opposing party."""
    if not sponsor_party:
        return 1.0
    cosponsors = db.query(BillCosponsor).filter_by(bill_id=bill_id).all()
    if not cosponsors:
        return 1.0
    opposing = [c for c in cosponsors if c.party and c.party != sponsor_party]
    if len(cosponsors) > 0 and len(opposing) / len(cosponsors) >= 0.20:
        return 1.5
    return 1.0


def _substance_multiplier(bill_category: str | None) -> float:
    return 0.1 if bill_category == "commemorative" else 1.0


def _leadership_multiplier(member: Member, congress_number: int) -> float:
    """1.2x if member chaired a committee during this Congress."""
    if not member.leadership_json:
        return 1.0
    for role in member.leadership_json:
        if (role.get("congress") == congress_number and
                "chair" in (role.get("type") or "").lower()):
            return 1.2
    return 1.0


def _seniority_tier(terms_json: list | None) -> str:
    """Return 'junior' | 'mid' | 'senior' based on number of terms served."""
    if not terms_json:
        return "junior"
    count = len(terms_json)
    if count <= 2:
        return "junior"
    if count <= 5:
        return "mid"
    return "senior"


@celery_app.task(bind=True, name="app.workers.bill_classifier.calculate_effectiveness_scores")
def calculate_effectiveness_scores(self):
    """Nightly: compute effectiveness score and within-tier percentile for all members."""
    db = get_sync_db()
    try:
        members = db.query(Member).all()
        if not members:
            return {"status": "no_members"}

        # Map bioguide_id → Member for quick lookup
        member_map = {m.bioguide_id: m for m in members}

        # Load all bills sponsored by current members (current congress only)
        current_congress = congress_api.get_current_congress()
        bills = db.query(Bill).filter_by(congress_number=current_congress).all()

        # Compute raw score per member
        raw_scores: dict[str, float] = {m.bioguide_id: 0.0 for m in members}

        for bill in bills:
            if not bill.sponsor_id or bill.sponsor_id not in member_map:
                continue
            sponsor = member_map[bill.sponsor_id]

            pts = _distance_points(bill.latest_action_text)
            bipartisan = _bipartisan_multiplier(db, bill.bill_id, sponsor.party)
            substance = _substance_multiplier(bill.bill_category)
            leadership = _leadership_multiplier(sponsor, current_congress)

            raw_scores[bill.sponsor_id] = raw_scores.get(bill.sponsor_id, 0.0) + (
                pts * bipartisan * substance * leadership
            )

        # Group members by (tier, party) for percentile normalisation
        # We treat party as a proxy for majority/minority — grouped separately so
        # a minority-party junior isn't unfairly compared to a majority-party senior.
        from collections import defaultdict
        buckets: dict[tuple, list[str]] = defaultdict(list)
        for m in members:
            tier = _seniority_tier(m.terms_json)
            party_bucket = m.party or "Unknown"
            buckets[(tier, party_bucket)].append(m.bioguide_id)

        # Compute percentile within each bucket
        percentiles: dict[str, float] = {}
        tiers: dict[str, str] = {}
        for (tier, _), ids in buckets.items():
            scores = [(bid, raw_scores.get(bid, 0.0)) for bid in ids]
            scores.sort(key=lambda x: x[1])
            n = len(scores)
            for rank, (bid, _) in enumerate(scores):
                percentiles[bid] = round((rank / max(n - 1, 1)) * 100, 1)
                tiers[bid] = tier

        # Bulk update members
        updated = 0
        for m in members:
            score = raw_scores.get(m.bioguide_id, 0.0)
            pct = percentiles.get(m.bioguide_id)
            tier = tiers.get(m.bioguide_id, _seniority_tier(m.terms_json))
            m.effectiveness_score = round(score, 2)
            m.effectiveness_percentile = pct
            m.effectiveness_tier = tier
            updated += 1

        db.commit()
        logger.info(f"calculate_effectiveness_scores: updated {updated} members for Congress {current_congress}")
        return {"status": "ok", "updated": updated, "congress": current_congress}

    except Exception as exc:
        db.rollback()
        logger.error(f"calculate_effectiveness_scores failed: {exc}")
        raise
    finally:
        db.close()