from __future__ import annotations

import asyncio
import json
import os
import shutil
import subprocess
import uuid
from contextlib import asynccontextmanager
from pathlib import Path
from typing import Literal

from dotenv import load_dotenv
from fastapi import BackgroundTasks, FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import FileResponse
from pydantic import BaseModel, Field

load_dotenv()

JOBS_DIR = Path(os.getenv("JOBS_DIR", "./jobs")).resolve()
JOBS_DIR.mkdir(parents=True, exist_ok=True)
CORS_ORIGINS = [o.strip() for o in os.getenv("CORS_ORIGINS", "http://localhost:4290").split(",") if o.strip()]
GEMINI_API_KEY = os.getenv("GEMINI_API_KEY", "").strip()
GEMINI_MODEL = os.getenv("GEMINI_MODEL", "gemini-2.5-flash")

# Pipeline 状态：created → downloading → splitting → frames_extracted → transcribing → transcribed | failed
JobStatus = Literal[
    "created", "downloading", "splitting", "frames_extracted",
    "transcribing", "transcribed", "failed",
]


class KeyFrame(BaseModel):
    index: int
    timestamp: float
    url: str


class TranscriptSegment(BaseModel):
    index: int
    start: float
    end: float
    en: str
    zh: str = ""


class Job(BaseModel):
    id: str
    url: str
    status: JobStatus = "created"
    progress: int = 0
    message: str = ""
    video_url: str = ""
    duration: float = 0.0
    width: int = 0
    height: int = 0
    frames: list[KeyFrame] = Field(default_factory=list)
    transcript: list[TranscriptSegment] = Field(default_factory=list)
    error: str = ""


JOBS: dict[str, Job] = {}


def job_dir(job_id: str) -> Path:
    d = JOBS_DIR / job_id
    d.mkdir(parents=True, exist_ok=True)
    return d


def save_state(job: Job) -> None:
    (job_dir(job.id) / "state.json").write_text(job.model_dump_json(indent=2))


def update(job: Job, **kw) -> None:
    for k, v in kw.items():
        setattr(job, k, v)
    save_state(job)


@asynccontextmanager
async def lifespan(_: FastAPI):
    # 启动时从磁盘恢复 jobs（简化版：只列目录）
    for p in JOBS_DIR.iterdir():
        if p.is_dir() and (p / "state.json").exists():
            try:
                JOBS[p.name] = Job.model_validate_json((p / "state.json").read_text())
            except Exception:
                pass
    yield


app = FastAPI(title="SKG TK 二创 API", lifespan=lifespan)
app.add_middleware(
    CORSMiddleware,
    allow_origins=CORS_ORIGINS,
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)


# ---------- Pipeline 实现 ----------

def run(cmd: list[str], cwd: Path | None = None) -> str:
    res = subprocess.run(cmd, cwd=cwd, capture_output=True, text=True)
    if res.returncode != 0:
        raise RuntimeError(f"cmd failed: {' '.join(cmd[:3])}... · {res.stderr[:500]}")
    return res.stdout


def ffprobe_meta(mp4: Path) -> dict:
    out = run([
        "ffprobe", "-v", "error", "-print_format", "json", "-show_streams", "-show_format", str(mp4),
    ])
    return json.loads(out)


async def pipeline_download_split_frames(job_id: str) -> None:
    """步骤 1+2+3：下载 + 拆音轨 + 抽取关键帧"""
    job = JOBS[job_id]
    d = job_dir(job_id)
    try:
        # ---- 1. yt-dlp 下载
        update(job, status="downloading", message="yt-dlp 下载中…", progress=5)
        mp4 = d / "source.mp4"
        run([
            "yt-dlp", "-f", "best[ext=mp4]/best",
            "-o", str(mp4),
            "--no-warnings", "--no-playlist",
            "--retries", "3",
            job.url,
        ])
        if not mp4.exists():
            raise RuntimeError("下载完成但找不到 source.mp4")

        # 元数据
        meta = ffprobe_meta(mp4)
        v_stream = next((s for s in meta["streams"] if s["codec_type"] == "video"), None)
        duration = float(meta["format"]["duration"])
        update(
            job,
            video_url=f"/jobs/{job_id}/video.mp4",
            duration=duration,
            width=int(v_stream["width"]) if v_stream else 0,
            height=int(v_stream["height"]) if v_stream else 0,
            progress=20,
            message=f"下载完成 · {duration:.1f}s",
        )

        # ---- 2. 拆音轨
        update(job, status="splitting", message="ffmpeg 拆分音轨…", progress=30)
        wav = d / "audio.wav"
        run([
            "ffmpeg", "-y", "-i", str(mp4),
            "-vn", "-ac", "1", "-ar", "16000", "-c:a", "pcm_s16le",
            str(wav),
        ])

        # ---- 3. 关键帧抽取（场景切换 + 均匀采样兜底，最多 10 张）
        update(job, message="抽取关键帧…", progress=50)
        frames_dir = d / "frames"
        if frames_dir.exists():
            shutil.rmtree(frames_dir)
        frames_dir.mkdir(parents=True)

        # 先用场景切换检测
        run([
            "ffmpeg", "-y", "-i", str(mp4),
            "-vf", "select='gt(scene,0.4)',showinfo",
            "-vsync", "vfr",
            "-frames:v", "30",
            str(frames_dir / "scene_%03d.jpg"),
        ])
        scene_frames = sorted(frames_dir.glob("scene_*.jpg"))

        # 均匀采样兜底 / 补足
        if len(scene_frames) < 10:
            sample_count = 10 - len(scene_frames)
            step = duration / (sample_count + 1)
            for i in range(sample_count):
                t = step * (i + 1)
                out = frames_dir / f"sample_{i:03d}.jpg"
                run([
                    "ffmpeg", "-y", "-ss", str(t), "-i", str(mp4),
                    "-frames:v", "1", "-q:v", "3", str(out),
                ])

        # 统一排序、按时间戳读取、限制 10 张
        all_frames = sorted(frames_dir.glob("*.jpg"))[:10]
        renamed: list[KeyFrame] = []
        for i, src in enumerate(all_frames):
            dst = frames_dir / f"{i:03d}.jpg"
            if src != dst:
                src.rename(dst)
            # 简化：用均匀分布估算时间戳（场景切换的精确时间需要解析 showinfo 输出，先省）
            ts = duration * (i + 0.5) / max(len(all_frames), 1)
            renamed.append(KeyFrame(index=i, timestamp=round(ts, 2), url=f"/jobs/{job_id}/frames/{i}.jpg"))

        update(
            job,
            status="frames_extracted",
            frames=renamed,
            progress=70,
            message=f"已抽取 {len(renamed)} 张关键帧",
        )

    except Exception as e:
        update(job, status="failed", error=str(e), message="管线失败")


# ---------- Gemini ASR + 翻译 ----------

async def pipeline_transcribe(job_id: str) -> None:
    job = JOBS[job_id]
    d = job_dir(job_id)
    wav = d / "audio.wav"
    try:
        if not wav.exists():
            raise RuntimeError("audio.wav 不存在")

        update(job, status="transcribing", message="Gemini ASR 处理中…", progress=75)

        if not GEMINI_API_KEY:
            # 无 key 模式：mock 数据，方便 UI 联调
            await asyncio.sleep(1.2)
            mock_segments = [
                TranscriptSegment(index=0, start=0.0, end=3.5,
                                  en="Welcome back to my channel, today we're testing something new.",
                                  zh="欢迎回来我的频道，今天我们要测试一些新东西。"),
                TranscriptSegment(index=1, start=3.5, end=7.2,
                                  en="This device looks really sleek and the design is quite minimal.",
                                  zh="这个设备看起来非常时尚，设计也相当简约。"),
                TranscriptSegment(index=2, start=7.2, end=11.0,
                                  en="Let me show you how it works in real life situations.",
                                  zh="让我向你展示它在实际场景中如何工作。"),
            ]
            update(job, transcript=mock_segments, status="transcribed", progress=100,
                   message="转录完成（MOCK 模式 · 未设 GEMINI_API_KEY）")
            return

        # 真模式：调 Gemini
        import google.generativeai as genai
        genai.configure(api_key=GEMINI_API_KEY)
        model = genai.GenerativeModel(GEMINI_MODEL)

        audio_file = genai.upload_file(str(wav), mime_type="audio/wav")
        prompt = (
            "Transcribe the English audio with sentence-level timestamps. "
            "Then provide a Chinese translation for each segment. "
            "Return strictly as JSON array, no prose, schema: "
            '[{"start": float_seconds, "end": float_seconds, "en": "...", "zh": "..."}]'
        )
        resp = await asyncio.to_thread(
            model.generate_content,
            [audio_file, prompt],
            generation_config={"response_mime_type": "application/json"},
        )
        raw = resp.text or "[]"
        data = json.loads(raw)
        segs = [
            TranscriptSegment(
                index=i,
                start=float(s.get("start", 0)),
                end=float(s.get("end", 0)),
                en=str(s.get("en", "")),
                zh=str(s.get("zh", "")),
            )
            for i, s in enumerate(data)
        ]
        update(job, transcript=segs, status="transcribed", progress=100,
               message=f"转录完成 · {len(segs)} 段")

    except Exception as e:
        update(job, status="failed", error=str(e), message="转录失败")


# ---------- API 路由 ----------

class CreateJobReq(BaseModel):
    url: str


@app.get("/health")
def health() -> dict:
    return {"ok": True, "gemini_configured": bool(GEMINI_API_KEY), "model": GEMINI_MODEL}


@app.post("/jobs", response_model=Job)
async def create_job(req: CreateJobReq, bg: BackgroundTasks) -> Job:
    if not req.url.strip():
        raise HTTPException(400, "url required")
    job_id = uuid.uuid4().hex[:12]
    job = Job(id=job_id, url=req.url.strip())
    JOBS[job_id] = job
    save_state(job)
    bg.add_task(pipeline_download_split_frames, job_id)
    return job


@app.get("/jobs/{job_id}", response_model=Job)
def get_job(job_id: str) -> Job:
    job = JOBS.get(job_id)
    if not job:
        raise HTTPException(404, "job not found")
    return job


@app.post("/jobs/{job_id}/transcribe", response_model=Job)
async def trigger_transcribe(job_id: str, bg: BackgroundTasks) -> Job:
    job = JOBS.get(job_id)
    if not job:
        raise HTTPException(404, "job not found")
    if job.status != "frames_extracted":
        raise HTTPException(409, f"status must be frames_extracted, got {job.status}")
    bg.add_task(pipeline_transcribe, job_id)
    return job


@app.get("/jobs/{job_id}/video.mp4")
def get_video(job_id: str):
    p = job_dir(job_id) / "source.mp4"
    if not p.exists():
        raise HTTPException(404, "video not found")
    return FileResponse(p, media_type="video/mp4")


@app.get("/jobs/{job_id}/frames/{idx}.jpg")
def get_frame(job_id: str, idx: int):
    p = job_dir(job_id) / "frames" / f"{idx:03d}.jpg"
    if not p.exists():
        raise HTTPException(404, "frame not found")
    return FileResponse(p, media_type="image/jpeg")