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import os
from zipfile import ZipFile
import torch
from fastapi import FastAPI
from fastapi.responses import StreamingResponse
from OpenVoice import se_extractor # لاحقاً لو حبيت تعمل voice cloning
from OpenVoice.api import BaseSpeakerTTS, ToneColorConverter
app = FastAPI()
# -------- إعداد الموديل عند تشغيل الـ Space --------
CHECKPOINT_ZIP_URL = "https://myshell-public-repo-hosting.s3.amazonaws.com/checkpoints_1226.zip"
CKPT_DIR = "checkpoints"
EN_CKPT_BASE = os.path.join(CKPT_DIR, "base_speakers", "EN")
CONVERTER_CKPT = os.path.join(CKPT_DIR, "converter")
os.makedirs("outputs", exist_ok=True)
if not os.path.exists(CKPT_DIR):
print("Downloading OpenVoice checkpoints ...")
os.system(f"wget {CHECKPOINT_ZIP_URL} -O ckpt.zip")
print("Extracting checkpoints ...")
ZipFile("ckpt.zip").extractall()
print("Checkpoints ready.")
device = "cuda" if torch.cuda.is_available() else "cpu"
# Base TTS (إنجليزي أساساً – العربي عن طريق cross-lingual cloning)
base_speaker_tts = BaseSpeakerTTS(f"{EN_CKPT_BASE}/config.json", device=device)
base_speaker_tts.load_ckpt(f"{EN_CKPT_BASE}/checkpoint.pth")
# لو لاحقاً حابب تعمل cloning لصوت معيّن:
# tone_color_converter = ToneColorConverter(f"{CONVERTER_CKPT}/config.json", device=device)
# tone_color_converter.load_ckpt(f"{CONVERTER_CKPT}/checkpoint.pth")
# -------- API Endpoint --------
@app.post("/tts")
async def tts_endpoint(
text: str,
speaker: str = "default", # ممكن تجرب: default, cheerful, sad, angry ...
speed: float = 1.0,
):
"""
يحوّل النص إلى صوت WAV باستخدام OpenVoice.
"""
out_path = "outputs/out.wav"
# اللغة الافتراضية EN – لو هتكتب عربي ممكن يطلع لكن بجودة أقل
language = "English"
# دالة tts من BaseSpeakerTTS
base_speaker_tts.tts(
text=text,
output_path=out_path,
speaker=speaker,
language=language,
speed=speed,
)
audio_file = open(out_path, "rb")
return StreamingResponse(audio_file, media_type="audio/wav")
# مهم جدًا لـ Hugging Face Spaces
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=7860)
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