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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
CVNSS4.0 Vietnamese TTS Studio
- Fix: Python 3.12 Compatibility (Missing 'imp' module)
- Fix: Auto-download 'src'
"""
import os
import sys
import types
import importlib
import importlib.util
import hashlib
import tempfile
import json
import time
import glob
import re
import shutil
import subprocess
from pathlib import Path
# =========================================================
# 0) CRITICAL PATCH: FIX PYTHON 3.12 'imp' ERROR
# =========================================================
# Python 3.12 đã xóa module 'imp', nhưng code TTS cũ vẫn gọi nó.
# Đoạn code này tạo ra một module 'imp' giả để đánh lừa hệ thống.
try:
import imp
except ImportError:
print("🔧 Đang vá lỗi tương thích Python 3.12+ (Mocking 'imp' module)...")
imp = types.ModuleType('imp')
imp.new_module = types.ModuleType
imp.reload = importlib.reload
# Hàm find_module giả lập (thường được dùng trong code cũ)
def _find_module(name, path=None):
spec = importlib.util.find_spec(name, path)
if spec is None:
raise ImportError(f"No module named {name}")
return (None, spec.origin, ("", "", 0)) # Trả về tuple giả
imp.find_module = _find_module
# Hàm load_module giả lập
def _load_module(name, file, pathname, description):
spec = importlib.util.spec_from_file_location(name, pathname)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
sys.modules[name] = module
return module
imp.load_module = _load_module
sys.modules['imp'] = imp
print("✅ Đã vá xong module 'imp'.")
# Các import nặng khác sau khi đã vá lỗi
import torch
import numpy as np
import soundfile as sf
import gradio as gr
# =========================================================
# 1) AUTO-HEALING: DOWNLOAD MISSING CORE MODULES
# =========================================================
def setup_environment():
"""Tự động tải thư mục src nếu bị thiếu"""
if not os.path.exists("src"):
print("🔄 Phát hiện thiếu thư mục 'src'. Đang tải mã nguồn cốt lõi...")
try:
# Clone repo chứa src
subprocess.run(
["git", "clone", "https://huggingface.co/spaces/valtecAI-team/valtec-vietnamese-tts", "temp_repo"],
check=True
)
# Di chuyển thư mục src
if os.path.exists("temp_repo/src"):
if os.path.exists("src"): shutil.rmtree("src") # Xóa cũ nếu lỗi
shutil.move("temp_repo/src", "./src")
print("✅ Đã cài đặt xong 'src'.")
else:
print("❌ Không tìm thấy 'src' trong repo đã tải.")
shutil.rmtree("temp_repo", ignore_errors=True)
except Exception as e:
print(f"❌ Lỗi khi tải mã nguồn: {e}")
# Chạy setup
setup_environment()
# Add src to path
sys.path.insert(0, str(Path(__file__).parent))
# Import core modules
try:
# Import theo thứ tự để tránh lỗi vòng lặp
from src.text.symbols import symbols
from src.vietnamese.text_processor import process_vietnamese_text
from src.vietnamese.phonemizer import text_to_phonemes, VIPHONEME_AVAILABLE
from src.models.synthesizer import SynthesizerTrn
print("✅ Core modules imported successfully.")
except ImportError as e:
print(f"🔥 Vẫn còn lỗi Import: {e}")
# Fallback objects
VIPHONEME_AVAILABLE = False
symbols = []
SynthesizerTrn = None
# =========================================================
# 2) SYSTEM CONFIGURATION & CSS
# =========================================================
NEON_CSS = r"""
:root { --bg-dark: #0f172a; --text-primary: #e2e8f0; --neon-cyan: #06b6d4; }
body, .gradio-container, .app { background: radial-gradient(circle at 50% 0%, #1e293b 0%, #0f172a 100%) !important; color: white !important; }
.panelNeon { background: rgba(30, 41, 59, 0.7); border: 1px solid rgba(255,255,255,0.08); border-radius: 16px; padding: 20px; margin-bottom: 20px; }
.panelNeon textarea, .panelNeon input, .panelNeon select { background: #f1f5f9 !important; color: #0f4c81 !important; font-weight: 500; }
button.primary { background: linear-gradient(135deg, #06b6d4 0%, #3b82f6 100%) !important; color: white; font-weight: bold; border: none; }
"""
# =========================================================
# 3) UTILITIES
# =========================================================
def md5_key(*parts): return hashlib.md5("|".join(parts).encode("utf-8")).hexdigest()
def find_latest_checkpoint(model_dir, prefix="G"):
pattern = os.path.join(model_dir, f"{prefix}*.pth")
checkpoints = glob.glob(pattern)
if not checkpoints: return None
checkpoints.sort(key=lambda x: int(re.search(rf"{prefix}(\d+)\.pth", x).group(1)) if re.search(rf"{prefix}(\d+)\.pth", x) else 0, reverse=True)
return checkpoints[0]
def download_model():
from huggingface_hub import snapshot_download
hf_repo = "valtecAI-team/valtec-tts-pretrained"
cache_base = Path(os.environ.get("XDG_CACHE_HOME", Path.home() / ".cache"))
if os.name == "nt": cache_base = Path(os.environ.get("LOCALAPPDATA", Path.home() / "AppData" / "Local"))
model_dir = cache_base / "valtec_tts" / "models" / "vits-vietnamese"
if (model_dir / "config.json").exists() and list(model_dir.glob("G_*.pth")):
return str(model_dir)
print(f"⬇️ Downloading Model {hf_repo}...")
try:
snapshot_download(repo_id=hf_repo, local_dir=str(model_dir))
return str(model_dir)
except Exception as e:
print(f"Lỗi tải model: {e}")
return str(model_dir) # Trả về đường dẫn dù lỗi để tránh crash ngay
# =========================================================
# 4) MANAGER & MODEL WRAPPER
# =========================================================
class TTSManager:
def __init__(self):
self.device = "cuda" if torch.cuda.is_available() else "cpu"
print(f"🔧 Initializing TTS on {self.device}...")
if SynthesizerTrn is None:
raise RuntimeError("Lỗi nghiêm trọng: Không thể tải class SynthesizerTrn do lỗi import.")
self.model_dir = download_model()
self.ckpt_path = find_latest_checkpoint(self.model_dir, "G")
self.cfg_path = os.path.join(self.model_dir, "config.json")
if not self.ckpt_path or not os.path.exists(self.cfg_path):
raise FileNotFoundError("Không tìm thấy Model Checkpoint hoặc Config.")
self.tts = VietnameseTTS(self.ckpt_path, self.cfg_path, self.device)
self.temp_dir = Path(tempfile.gettempdir()) / "neon_tts_cache"
self.temp_dir.mkdir(parents=True, exist_ok=True)
def synthesize(self, text, speaker, speed):
try:
if not text: return None, "⚠️ Chưa nhập nội dung"
key = md5_key(speaker, str(speed), text[:30])
out_path = self.temp_dir / f"{key}.wav"
if out_path.exists(): return str(out_path), "✅ Lấy từ Cache"
audio, sr = self.tts.synthesize(text, speaker, speed)
sf.write(str(out_path), audio, sr)
return str(out_path), "✅ Tạo thành công"
except Exception as e:
return None, f"❌ Lỗi: {str(e)}"
class VietnameseTTS:
def __init__(self, ckpt, cfg, device="cpu"):
self.device = device
with open(cfg, "r", encoding="utf-8") as f: self.config = json.load(f)
self.spk2id = self.config["data"]["spk2id"]
self.speakers = list(self.spk2id.keys())
self.model = SynthesizerTrn(
len(symbols),
self.config["data"]["filter_length"] // 2 + 1,
self.config["train"]["segment_size"] // self.config["data"]["hop_length"],
n_speakers=self.config["data"]["n_speakers"],
**self.config["model"]
).to(self.device)
state = torch.load(ckpt, map_location=self.device)["model"]
self.model.load_state_dict({k.replace("module.", ""): v for k,v in state.items()}, strict=False)
self.model.eval()
def synthesize(self, text, speaker, speed):
from src.text import cleaned_text_to_sequence
from src.nn import commons
norm_text = process_vietnamese_text(text)
phones, tones, _ = text_to_phonemes(norm_text, use_viphoneme=VIPHONEME_AVAILABLE)
phone_ids, tone_ids, lang_ids = cleaned_text_to_sequence(phones, tones, "VI")
phone_ids = commons.intersperse(phone_ids, 0)
tone_ids = commons.intersperse(tone_ids, 0)
lang_ids = commons.intersperse(lang_ids, 0)
x = torch.LongTensor(phone_ids).unsqueeze(0).to(self.device)
x_len = torch.LongTensor([len(phone_ids)]).to(self.device)
tone = torch.LongTensor(tone_ids).unsqueeze(0).to(self.device)
lang = torch.LongTensor(lang_ids).unsqueeze(0).to(self.device)
sid = torch.LongTensor([self.spk2id.get(speaker, 0)]).to(self.device)
with torch.no_grad():
bert = torch.zeros(1024, len(phone_ids)).unsqueeze(0).to(self.device)
ja_bert = torch.zeros(768, len(phone_ids)).unsqueeze(0).to(self.device)
outputs = self.model.infer(x, x_len, sid, tone, lang, bert, ja_bert, noise_scale=0.667, noise_scale_w=0.8, length_scale=speed)
audio = outputs[0][0,0].detach().cpu().numpy()
return audio, self.config["data"]["sampling_rate"]
# =========================================================
# 5) UI
# =========================================================
def create_ui(manager: TTSManager):
def run(text, spk, spd):
start = time.time()
path, msg = manager.synthesize(text, spk, spd)
dur = time.time() - start
return path, f"<div style='padding:10px; color:#38bdf8'>⏱️ {dur:.2f}s | {msg}</div>"
with gr.Blocks(css=NEON_CSS, title="Fixed TTS") as app:
gr.Markdown("## 🎛️ CVNSS4.0 TTS (Python 3.12 Patched)")
with gr.Row():
with gr.Column():
with gr.Group(elem_classes=["panelNeon"]):
txt = gr.Textbox(label="Văn bản", value="Xin chào, hệ thống đã sửa lỗi thư viện imp.", lines=4)
spk = gr.Dropdown(choices=manager.tts.speakers, value=manager.tts.speakers[0], label="Người đọc")
spd = gr.Slider(0.5, 2.0, 1.0, step=0.1, label="Tốc độ")
btn = gr.Button("Đọc ngay", variant="primary")
with gr.Column():
out_audio = gr.Audio(label="Audio", type="filepath")
out_msg = gr.HTML()
btn.click(run, [txt, spk, spd], [out_audio, out_msg])
return app
# =========================================================
# 6) MAIN
# =========================================================
if __name__ == "__main__":
try:
manager = TTSManager()
app = create_ui(manager)
app.launch()
except Exception as e:
print(f"🔥 Lỗi khởi động cuối cùng: {e}") |