update docker & add api

Dockerfile

@@ -11,4 +11,4 @@ EXPOSE 7860
 ENV NUMBA_CACHE_DIR=/tmp/numba_cache
 ENV NUMBA_DISABLE_CACHING=1
 
-CMD ["uvicorn", "webui:app", "--host", "0.0.0.0", "--port", "7860"]
+CMD ["uvicorn", "api:app", "--host", "0.0.0.0", "--port", "7860"]

api.py

@@ -0,0 +1,167 @@
+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