import os
import asyncio
import edge_tts
import soundfile as sf
import torch
import fairseq
from fastapi import FastAPI, HTTPException
from fastapi.responses import FileResponse
from pydantic import BaseModel
# from modules import models
from uuid import uuid4
import requests
from modules.core import preload
from modules.models import load_model

app = FastAPI()

preload()

path_models = [
    {
        "name": "zeta",
        "label": "Zeta",
        "ckpt_path": "weights/zet_test1.pth",
        "index_path": "weights/zet_test1.0.index"
    },
]

# List model edge_tts (voice) dengan label, name, gender
edge_tts_voices = [
    {"name": "id-ID-GadisNeural", "label": "Indonesian Female (Gadis)", "gender": "Female", "language": "Indonesian"},
    {"name": "id-ID-ArdiNeural", "label": "Indonesian Male (Ardi)", "gender": "Male", "language": "Indonesian"},
    {"name": "en-US-JennyNeural", "label": "English US Female (Jenny)", "gender": "Female", "language": "English"},
    {"name": "en-US-GuyNeural", "label": "English US Male (Guy)", "gender": "Male", "language": "English"},
    {"name": "ja-JP-NanamiNeural", "label": "Japanese Female (Nanami)", "gender": "Female", "language": "Japanese"},
    {"name": "ja-JP-KeitaNeural", "label": "Japanese Male (Keita)", "gender": "Male", "language": "Japanese"},
]

BACK4APP_TTS_URL = os.getenv("BACK4APP_TTS_URL")

async def generate_tts_with_back4app(text: str, voice: str, tts_wav: str):
    try:
        response = requests.post(
            f"{BACK4APP_TTS_URL}/tts",
            json={"text": text, "voice": voice},
            timeout=60
        )
        if response.status_code != 200:
            raise HTTPException(status_code=500, detail=f"Back4App TTS failed: {response.text}")
        response.raise_for_status()
        data = response.json()

        # 2. Ambil file URL dari response
        tts_url = data["file"]
        r = requests.get(f"{BACK4APP_TTS_URL}{tts_url}", stream=True)
        r.raise_for_status()
        with open(tts_wav, "wb") as f:
            for chunk in r.iter_content(8192):
                f.write(chunk)

    except Exception as e:
        raise HTTPException(status_code=500, detail=f"TTS error via Back4App: {e}")

class TTSRequest(BaseModel):
    text: str
    name: str  # nama model yang sesuai dengan daftar di 'models'
    tts_voice: str = "id-ID-GadisNeural"
    f0_up_key: int = 0

def limit_tts_files(output_dir, max_files=10):
    files = sorted(
        [os.path.join(output_dir, f) for f in os.listdir(output_dir)],
        key=os.path.getmtime
    )
    while len(files) > max_files:
        os.remove(files[0])
        files.pop(0)

@app.post("/tts")
async def tts_api(req: TTSRequest):
    # Cari model berdasarkan name
    model = next((m for m in path_models if m["name"] == req.name), None)
    if not model:
        raise HTTPException(status_code=404, detail=f"Model '{req.name}' not found.")

    ckpt_path = model["ckpt_path"]
    index_path = model["index_path"]

    # Cek file model dan index
    if not os.path.isfile(ckpt_path):
        raise HTTPException(status_code=404, detail=f"Model file not found: {ckpt_path}")
    if not os.path.isfile(index_path):
        raise HTTPException(status_code=404, detail=f"Index file not found: {index_path}")
    
    # Path output
    output_dir = "/tmp/tts"
    os.makedirs(output_dir, exist_ok=True)
    limit_tts_files(output_dir, max_files=10)
    tts_wav = f"{output_dir}/{uuid4().hex}_tts.wav"
    output_wav = f"{output_dir}/{uuid4().hex}_rvc.wav"
    index_rate = 0.75

    # 1. Generate TTS
    try:
        # Ganti pakai Back4App TTS
        communicate = edge_tts.Communicate(req.text, req.tts_voice)
        with open(tts_wav, "wb") as f:
            async for chunk in communicate.stream():
                if chunk["type"] == "audio":
                    f.write(chunk["data"])
        # await generate_tts_with_back4app(req.text, req.tts_voice, tts_wav)
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"TTS error: {e}")

    # 2. Voice Conversion
    try:
        # models.load_model(ckpt_path)
        # vc = models.vc_model
        vc = load_model(ckpt_path, config_json="configs/48k-768.json")
        
        if vc is None:
            raise Exception("Failed to load model")

        # Run conversion menggunakan method single() yang benar
        result = vc.single(
            sid=0,                           # speaker id
            input_audio=tts_wav,         # path audio input
            embedder_model_name="auto",       # auto detect embedder
            embedding_output_layer="auto",    # auto detect layer
            f0_up_key=req.f0_up_key,             # pitch shift
            f0_file="",                       # f0 curve file (kosong)
            f0_method="harvest",             # f0 method
            auto_load_index=True,            # auto load index
            faiss_index_file=index_path,      # index file path
            index_rate=index_rate,                  # index rate
            output_dir=output_dir            # output directory
        )

        # Cek apakah result tuple atau string error
        if not (isinstance(result, tuple) and isinstance(result[1], tuple)):
            raise HTTPException(status_code=500, detail=f"RVC error: {result}")
        info, (tgt_sr, audio_opt) = result
        sf.write(output_wav, audio_opt, tgt_sr)
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"RVC error: {e}")

    # Ambil domain dari environment Hugging Face
    space_id = os.environ.get("SPACE_ID")
    if space_id:
        username, space_name = space_id.split("/")
        space_url = f"https://{username}-rvc-tts.hf.space"
        public_url = f"{space_url}/file-tmp?path={output_wav}"
    else:
        public_url = f"/file-tmp?path={output_wav}"

    return {"result": public_url}

@app.get("/file-tmp")
def get_tmp_file(path: str):
    # Security: hanya izinkan akses file di /tmp/tts
    if not path.startswith("/tmp/tts/"):
        raise HTTPException(status_code=403, detail="Forbidden")
    if not os.path.isfile(path):
        raise HTTPException(status_code=404, detail="File not found")
    return FileResponse(path)

# Jalankan dengan: uvicorn api_tts:app --reload