"""
jobs.py - Lightweight async job registry for conflict checks.

A conflict check takes minutes, so the HTTP request must not block on it. Each
upload becomes a job that runs on a background thread; the client gets a job_id
immediately and can either poll GET /jobs/{id} or just close the page and wait
for the completion email.

State is in-memory (fine for a single-user tool); the report is also persisted
to outputs/<job_id>/ so results survive a restart even though live status does
not. No external queue/DB.
"""

import json
import contextlib
import os
import sys
import time
import uuid
import shutil
import threading
from typing import Dict, Optional

from backend import config
from backend import llm
from backend.agents.runner import run_agent_pipeline
from backend.pipeline.runner import run_pipeline
from backend.email_sender import send_conflict_report, send_review_required

_jobs: Dict[str, Dict] = {}
_lock = threading.Lock()
PIPELINE_MODES = {"classic", "agent"}


class _Tee:
    """Write to both the real stream and the job log file."""

    def __init__(self, stream, log_file) -> None:
        self._stream = stream
        self._log = log_file

    def write(self, data):
        self._stream.write(data)
        self._log.write(data)

    def flush(self):
        self._stream.flush()
        self._log.flush()


@contextlib.contextmanager
def _tee_log(log_path: str, header: str):
    """Mirror stdout/stderr into a per-job log file for the duration of a run.

    sys.stdout is process-global, so two concurrent jobs would interleave in
    each other's logs - acceptable for this single-user tool (same tradeoff as
    the LLM cost globals in llm.py).
    """
    with open(log_path, "a", encoding="utf-8") as log_file:
        log_file.write(header + "\n")
        real_out, real_err = sys.stdout, sys.stderr
        sys.stdout, sys.stderr = _Tee(real_out, log_file), _Tee(real_err, log_file)
        try:
            yield
        finally:
            sys.stdout, sys.stderr = real_out, real_err


def _set(job_id: str, **fields) -> None:
    with _lock:
        _jobs[job_id].update(fields)


def create_job(pdf_path: str, source_filename: str, email: Optional[str] = None,
               project_input: Optional[Dict] = None, text_local: bool = False,
               pipeline_mode: str = "classic", model: Optional[str] = None) -> str:
    """Register a job and kick off its background thread. Returns the job_id."""
    pipeline_mode = pipeline_mode.strip().lower()
    if pipeline_mode not in PIPELINE_MODES:
        raise ValueError(f"Unsupported pipeline mode: {pipeline_mode!r}")
    # Agent mode v1 is OpenRouter-only.
    text_local = bool(text_local and pipeline_mode == "classic")
    model = (model or "").strip() or None
    job_id = uuid.uuid4().hex[:12]
    with _lock:
        _jobs[job_id] = {
            "job_id": job_id,
            "status": "queued",          # queued -> running -> done | needs_review | error
            "source": source_filename,
            "email": email or None,
            "project_input": project_input or {},
            "text_local": text_local,
            "pipeline_mode": pipeline_mode,
            "model": model,
            "stage": None,
            "created_at": time.time(),
            "finished_at": None,
            "report": None,
            "error": None,
        }
    threading.Thread(target=_run, args=(
        job_id, pdf_path, project_input, text_local, pipeline_mode, model,
    ),
                     daemon=True).start()
    return job_id


def _run(job_id: str, pdf_path: str, project_input: Optional[Dict] = None,
         text_local: bool = False, pipeline_mode: str = "classic",
         model: Optional[str] = None) -> None:
    out_dir = os.path.join(config.OUTPUT_DIR, job_id)
    try:
        _set(job_id, status="running")
        # Keep a copy of the source PDF so its sheets can be viewed later.
        os.makedirs(out_dir, exist_ok=True)
        header = (f"=== Job {job_id} | {pipeline_mode} | {_jobs[job_id].get('source')} | "
                  f"model={model or 'default'} | "
                  f"started {time.strftime('%Y-%m-%d %H:%M:%S %Z', time.gmtime())} UTC ===")
        with _tee_log(os.path.join(out_dir, "job.log"), header):
            _run_pipeline(job_id, pdf_path, out_dir, project_input, text_local,
                          pipeline_mode, model)
    except Exception as e:
        print(f"[Jobs] Job {job_id} failed: {e}")
        _set(job_id, status="error", error=str(e), finished_at=time.time())
        _notify_error(job_id)
    finally:
        try:
            os.remove(pdf_path)
        except OSError:
            pass


def _run_pipeline(job_id: str, pdf_path: str, out_dir: str,
                  project_input: Optional[Dict], text_local: bool,
                  pipeline_mode: str, model: Optional[str]) -> None:
    """The body of a job run; executes inside the job's tee'd log capture."""
    # Persist minimal job metadata so the disk fallback in get_job can
    # recover the recipient email / pipeline mode after a server restart
    # (plain json.dump, matching the _dump style used elsewhere).
    with open(os.path.join(out_dir, "job.json"), "w", encoding="utf-8") as f:
        json.dump({
            "job_id": job_id,
            "email": _jobs[job_id].get("email"),
            "pipeline_mode": pipeline_mode,
            "source": _jobs[job_id].get("source"),
        }, f, indent=2)
    shutil.copy2(pdf_path, os.path.join(out_dir, "source.pdf"))
    runner = run_agent_pipeline if pipeline_mode == "agent" else run_pipeline
    runner_kwargs = {
        "out_dir": out_dir,
        "on_stage": lambda name: _set(job_id, stage=name),
        "project_input": project_input,
        "source_name": _jobs[job_id].get("source"),
    }
    if pipeline_mode == "classic":
        runner_kwargs["text_local"] = text_local
    else:
        runner_kwargs["require_review"] = config.AGENT_REQUIRE_REVIEW
    if model:
        print(f"[Jobs] Model override for this run: {model}")
        llm.set_model_override(model)
    try:
        report = runner(pdf_path, **runner_kwargs)
    finally:
        if model:
            llm.set_model_override(None)
    report.setdefault("summary", {})["pipeline_mode"] = pipeline_mode
    if report["summary"].get("agent_status") == "needs_review":
        # Human-review gate: hold the job, don't email the unreviewed report.
        _set(job_id, status="needs_review", report=report,
             finished_at=time.time(), stage=None)
        email = _jobs[job_id].get("email")
        if email:
            review_url = f"{config.APP_BASE_URL.rstrip('/')}/?job={job_id}"
            send_review_required(email, report, review_url)
    else:
        _set(job_id, status="done", report=report, finished_at=time.time(), stage=None)
        _notify(job_id, report, out_dir)


def _notify(job_id: str, report: Dict, out_dir: str) -> None:
    email = _jobs[job_id].get("email")
    if not email:
        return
    results_url = f"{config.APP_BASE_URL.rstrip('/')}/?job={job_id}"
    attachments = [
        os.path.join(out_dir, "report.md"),
        os.path.join(out_dir, "conflicts.json"),
        os.path.join(out_dir, "validated_issues.json"),
        os.path.join(out_dir, "rfis.json"),
    ]
    send_conflict_report(email, report, results_url=results_url, attachments=attachments)


def _notify_error(job_id: str) -> None:
    job = _jobs[job_id]
    email = job.get("email")
    if not email:
        return
    # Reuse the report mailer with a minimal error-shaped payload.
    err_report = {
        "source": job.get("source", ""),
        "summary": {"conflicts_found": 0, "by_severity": {}, "disciplines": []},
    }
    try:
        from backend.email_sender import _smtp_ready, _send
        from email.message import EmailMessage
        if not _smtp_ready():
            print(f"[Email] SMTP not configured - skipping error notice to {email}")
            return
        msg = EmailMessage()
        msg["Subject"] = f"Conflict Checker - {job.get('source','')} - run FAILED"
        msg["From"] = config.SMTP_FROM or config.SMTP_USER
        msg["To"] = email
        msg.set_content(
            "Your conflict check did not complete.\n\n"
            f"Drawing set: {job.get('source','')}\n"
            f"Error: {job.get('error','unknown')}\n\n"
            "Generated by Conflict Checker"
        )
        _send(msg)
    except Exception as e:
        print(f"[Email] Failed to send error notice: {e}")


def get_job(job_id: str) -> Optional[Dict]:
    """Public job view. Includes the full report only when done.

    Falls back to the on-disk conflicts.json when the job isn't in the
    in-memory registry (e.g. after a server restart).
    """
    with _lock:
        job = _jobs.get(job_id)
        if job:
            return dict(job)

    # Try loading from disk
    report_path = os.path.join(config.OUTPUT_DIR, job_id, "conflicts.json")
    if not os.path.isfile(report_path):
        return None
    try:
        with open(report_path, encoding="utf-8") as f:
            report = json.load(f)
        summary = report.get("summary", {})
        # Recover the job's real state: a job that stopped at the review gate
        # must come back as needs_review (not done) or it can never finalize.
        status = "needs_review" if summary.get("agent_status") == "needs_review" else "done"
        # job.json (written at job start) carries the recipient email and
        # pipeline mode so the final notification still fires after a restart.
        # Missing/corrupt job.json degrades to the previous derivations.
        meta: Dict = {}
        meta_path = os.path.join(config.OUTPUT_DIR, job_id, "job.json")
        try:
            with open(meta_path, encoding="utf-8") as f:
                loaded = json.load(f)
            if isinstance(loaded, dict):
                meta = loaded
        except (OSError, json.JSONDecodeError):
            pass
        source_pdf = os.path.join(config.OUTPUT_DIR, job_id, "source.pdf")
        job = {
            "job_id":       job_id,
            "status":       status,
            "source":       meta.get("source") or report.get("source", os.path.basename(report_path)),
            "email":        meta.get("email"),
            "project_input": report.get("project_input", {}),
            "text_local":   summary.get("text_backend") == "local",
            "pipeline_mode": meta.get("pipeline_mode") or summary.get("pipeline_mode", "classic"),
            "stage":        None,
            "created_at":   os.path.getmtime(source_pdf) if os.path.isfile(source_pdf) else None,
            "finished_at":  os.path.getmtime(report_path),
            "report":       report,
            "error":        None,
        }
        # Hydrate the in-memory registry so _set(...) transitions (reviewing,
        # finalizing, done) work for restart-recovered jobs.
        with _lock:
            return dict(_jobs.setdefault(job_id, job))
    except Exception as e:
        print(f"[Jobs] Failed to load job {job_id} from disk: {e}")
        return None