"""MCP tools for workflow status tracking."""

from __future__ import annotations

import json
from uuid import UUID

from legal_mcp.services import db


async def workflow_status(case_number: str) -> str:
    """סטטוס תהליך עבודה מלא לתיק - מסמכים, עיבוד, טיוטות.

    Args:
        case_number: מספר תיק הערר
    """
    case = await db.get_case_by_number(case_number)
    if not case:
        return f"תיק {case_number} לא נמצא."

    case_id = UUID(case["id"])
    docs = await db.list_documents(case_id)

    # Count chunks per document
    pool = await db.get_pool()
    async with pool.acquire() as conn:
        chunk_counts = await conn.fetch(
            "SELECT document_id, COUNT(*) as count FROM document_chunks WHERE case_id = $1 GROUP BY document_id",
            case_id,
        )
    chunk_map = {str(r["document_id"]): r["count"] for r in chunk_counts}

    doc_status = []
    for doc in docs:
        doc_status.append({
            "title": doc["title"],
            "type": doc["doc_type"],
            "extraction": doc["extraction_status"],
            "chunks": chunk_map.get(doc["id"], 0),
            "pages": doc.get("page_count"),
        })

    # Check draft status
    from pathlib import Path
    from legal_mcp import config

    case_dir = config.CASES_DIR / case_number
    draft_path = case_dir / "drafts" / "decision.md"
    has_draft = draft_path.exists()
    draft_size = draft_path.stat().st_size if has_draft else 0

    status = {
        "case_number": case["case_number"],
        "title": case["title"],
        "status": case["status"],
        "documents": doc_status,
        "total_documents": len(docs),
        "total_chunks": sum(chunk_map.values()),
        "has_draft": has_draft,
        "draft_size_bytes": draft_size,
        "next_steps": _suggest_next_steps(case, docs, has_draft),
    }

    return json.dumps(status, ensure_ascii=False, indent=2)


def _suggest_next_steps(case: dict, docs: list, has_draft: bool) -> list[str]:
    """Suggest next steps based on case state."""
    steps = []
    doc_types = {d["doc_type"] for d in docs}

    if not docs:
        steps.append("העלה מסמכים לתיק (כתב ערר, תשובת ועדה)")
    else:
        if "appeal" not in doc_types:
            steps.append("העלה כתב ערר")
        if "response" not in doc_types:
            steps.append("העלה תשובת ועדה/משיבים")

    pending = [d for d in docs if d["extraction_status"] == "pending"]
    if pending:
        steps.append(f"עיבוד {len(pending)} מסמכים ממתינים")

    if docs and not has_draft:
        steps.append("התחל ניסוח טיוטת החלטה (/draft-decision)")
    elif has_draft and case["status"] in ("new", "in_progress"):
        steps.append("סקור ועדכן את הטיוטה")
        steps.append("עדכן סטטוס ל-drafted")

    if case["status"] == "drafted":
        steps.append("סקירה סופית ועדכון סטטוס ל-reviewed")
    elif case["status"] == "reviewed":
        steps.append("אישור סופי ועדכון סטטוס ל-final")

    return steps


async def processing_status() -> str:
    """סטטוס כללי - מספר תיקים, מסמכים ממתינים לעיבוד."""
    pool = await db.get_pool()
    async with pool.acquire() as conn:
        case_count = await conn.fetchval("SELECT COUNT(*) FROM cases")
        doc_count = await conn.fetchval("SELECT COUNT(*) FROM documents")
        pending_count = await conn.fetchval(
            "SELECT COUNT(*) FROM documents WHERE extraction_status = 'pending'"
        )
        chunk_count = await conn.fetchval("SELECT COUNT(*) FROM document_chunks")
        corpus_count = await conn.fetchval("SELECT COUNT(*) FROM style_corpus")
        pattern_count = await conn.fetchval("SELECT COUNT(*) FROM style_patterns")

    return json.dumps({
        "cases": case_count,
        "documents": doc_count,
        "pending_processing": pending_count,
        "chunks": chunk_count,
        "style_corpus_entries": corpus_count,
        "style_patterns": pattern_count,
    }, ensure_ascii=False, indent=2)