app copy.py

import os
import sys
import subprocess
from huggingface_hub import hf_hub_download
from pydub import AudioSegment
import gradio as gr
import time

# Thêm thư mục src vào sys.path
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), 'src')))

def run_f5_tts(ref_audio_path, ref_text, gen_text, model="F5TTS_Base", speed=1.2, vocoder_name="vocos"):
    current_dir = os.path.dirname(os.path.abspath(__file__))
    infer_cli_path = os.path.join(current_dir, "src", "f5_tts", "infer", "infer_cli.py")
    tests_dir = os.path.join(current_dir, "tests")

    print(f"Infer CLI path: {infer_cli_path}")
    print(f"Does infer_cli.py exist? {os.path.exists(infer_cli_path)}")
    if not os.path.exists(infer_cli_path):
        return None, "File infer_cli.py không tồn tại!"

    try:
        vocab_file = hf_hub_download(repo_id="nguyensu27/TTS", filename="vocab.txt")
        ckpt_file = hf_hub_download(repo_id="nguyensu27/TTS", filename="model_last.pt")
    except Exception as e:
        return None, f"Lỗi khi tải model/vocab: {str(e)}"

    os.environ['PYTHONIOENCODING'] = 'utf-8'
    env = os.environ.copy()
    env['PYTHONPATH'] = os.path.abspath(os.path.join(current_dir, 'src'))

    command = [
        sys.executable,
        infer_cli_path,
        "--model", model,
        "--ref_audio", ref_audio_path,
        "--ref_text", ref_text,
        "--gen_text", gen_text,
        "--speed", str(speed),
        "--vocoder_name", vocoder_name,
        "--vocab_file", vocab_file,
        "--ckpt_file", ckpt_file
    ]

    print(f"Running command: {' '.join(command)}")
    try:
        result = subprocess.run(
            command,
            check=True,
            capture_output=True,
            text=True,
            env=env
        )
        print("Subprocess stdout:", result.stdout)
        if os.path.exists(tests_dir):
            wav_files = [f for f in os.listdir(tests_dir) if f.endswith('.wav')]
            if wav_files:
                latest_wav = max(wav_files, key=lambda x: os.path.getmtime(os.path.join(tests_dir, x)))
                output_wav = os.path.join(tests_dir, latest_wav)
                audio = AudioSegment.from_wav(output_wav)
                output_mp3 = os.path.join(tests_dir, "output.mp3")
                audio.export(output_mp3, format="mp3")
                return output_mp3, "Suy luận thành công!"
        return None, "Không tìm thấy file âm thanh trong thư mục tests"
    except subprocess.CalledProcessError as e:
        return None, f"Lỗi khi chạy infer_cli.py: {e.stderr}"
    except Exception as e:
        return None, str(e)

def generate_speech(ref_audio, ref_text, gen_text, speed, model):
    if ref_audio is None:
        return None, "Vui lòng tải lên file audio tham chiếu!"
    # ref_audio là đường dẫn file, tải bằng AudioSegment
    audio_segment = AudioSegment.from_file(ref_audio)
    audio_segment = audio_segment.set_channels(1)  # Chuyển sang mono
    ref_audio_path = f"temp_ref_{int(time.time())}.wav"
    audio_segment.export(ref_audio_path, format="wav")

    output_mp3, message = run_f5_tts(ref_audio_path, ref_text, gen_text, model, float(speed))
    os.remove(ref_audio_path)

    if output_mp3 and os.path.exists(output_mp3):
        return output_mp3, message
    return None, message

interface = gr.Interface(
    fn=generate_speech,
    inputs=[
        gr.Audio(type="filepath", label="Tải lên file audio tham chiếu (.wav hoặc .mp3)"),
        gr.Textbox(label="Text tham chiếu", placeholder="Nhập text của audio tham chiếu"),
        gr.Textbox(label="Text cần sinh", placeholder="Nhập text bạn muốn sinh"),
        gr.Slider(minimum=0.5, maximum=2.0, value=1.0, label="Tốc độ"),
        gr.Dropdown(choices=["F5TTS_Base"], value="F5TTS_Base", label="Mô hình")
    ],
    outputs=[
        gr.Audio(type="filepath", label="Kết quả audio (.mp3)"),
        gr.Textbox(label="Trạng thái")
    ],
    title="F5-TTS Suy luận",
    description="Tải lên audio tham chiếu, nhập text, và sinh audio mới với F5-TTS."
)

if __name__ == "__main__":
    interface.launch(server_name="0.0.0.0", server_port=7860)



# import os
# import sys
# import subprocess
# from huggingface_hub import hf_hub_download
# from pydub import AudioSegment
# import gradio as gr
# import time

# # Thêm thư mục src vào sys.path
# sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), 'src')))

# def run_f5_tts(ref_audio_path, ref_text, gen_text, model="F5TTS_Base", speed=1.2, vocoder_name="vocos"):
#     current_dir = os.path.dirname(os.path.abspath(__file__))
#     infer_cli_path = os.path.join(current_dir, "src", "f5_tts", "infer", "infer_cli.py")
#     tests_dir = os.path.join(current_dir, "tests")

#     # Debug: In đường dẫn để kiểm tra
#     print(f"Infer CLI path: {infer_cli_path}")
#     print(f"Tests dir: {tests_dir}")

#     # Tải file từ Hugging Face Hub
#     try:
#         vocab_file = hf_hub_download(repo_id="nguyensu27/TTS", filename="vocab.txt")
#         ckpt_file = hf_hub_download(repo_id="nguyensu27/TTS", filename="model_last.pt")
#     except Exception as e:
#         return None, f"Lỗi khi tải model/vocab từ Hugging Face: {str(e)}"

#     os.environ['PYTHONIOENCODING'] = 'utf-8'
#     env = os.environ.copy()
#     env['PYTHONPATH'] = os.path.abspath(os.path.join(current_dir, 'src'))

#     command = [
#         sys.executable,
#         infer_cli_path,
#         "--model", model,
#         "--ref_audio", ref_audio_path,
#         "--ref_text", ref_text,
#         "--gen_text", gen_text,
#         "--speed", str(speed),
#         "--vocoder_name", vocoder_name,
#         "--vocab_file", vocab_file,
#         "--ckpt_file", ckpt_file
#     ]

#     print(f"Running command: {' '.join(command)}")
#     try:
#         result = subprocess.run(
#             command,
#             check=True,
#             capture_output=True,
#             text=True,
#             env=env
#         )
#         print("Subprocess stdout:", result.stdout)
#         if os.path.exists(tests_dir):
#             wav_files = [f for f in os.listdir(tests_dir) if f.endswith('.wav')]
#             if wav_files:
#                 latest_wav = max(wav_files, key=lambda x: os.path.getmtime(os.path.join(tests_dir, x)))
#                 output_wav = os.path.join(tests_dir, latest_wav)
#                 audio = AudioSegment.from_wav(output_wav)
#                 output_mp3 = os.path.join(tests_dir, "output.mp3")
#                 audio.export(output_mp3, format="mp3")
#                 return output_mp3, "Suy luận thành công!"

#         return None, "Không tìm thấy file âm thanh trong thư mục tests"
#     except subprocess.CalledProcessError as e:
#         return None, f"Lỗi khi chạy infer_cli.py: {e.stderr}"
#     except Exception as e:
#         return None, str(e)

# def generate_speech(ref_audio, ref_text, gen_text, speed, model):
#     if ref_audio is None:
#         return None, "Vui lòng tải lên file audio tham chiếu!"
#     ref_audio_path = f"temp_ref_{int(time.time())}.wav"
#     ref_audio.convert_audio_channels(1)  # Chuyển sang mono
#     ref_audio.export(ref_audio_path, format="wav")

#     output_mp3, message = run_f5_tts(ref_audio_path, ref_text, gen_text, model, float(speed))
#     os.remove(ref_audio_path)

#     if output_mp3 and os.path.exists(output_mp3):
#         return output_mp3, message
#     return None, message

# interface = gr.Interface(
#     fn=generate_speech,
#     inputs=[
#         gr.Audio(type="filepath", label="Tải lên file audio tham chiếu (.wav hoặc .mp3)"),
#         gr.Textbox(label="Text tham chiếu", placeholder="Nhập text của audio tham chiếu"),
#         gr.Textbox(label="Text cần sinh", placeholder="Nhập text bạn muốn sinh"),
#         gr.Slider(minimum=0.5, maximum=2.0, value=1.0, label="Tốc độ"),
#         gr.Dropdown(choices=["F5TTS_Base"], value="F5TTS_Base", label="Mô hình")
#     ],
#     outputs=[
#         gr.Audio(type="filepath", label="Kết quả audio (.mp3)"),
#         gr.Textbox(label="Trạng thái")
#     ],
#     title="F5-TTS Suy luận",
#     description="Tải lên audio tham chiếu, nhập text, và sinh audio mới với F5-TTS."
# )

# if __name__ == "__main__":
#     interface.launch(server_name="0.0.0.0", server_port=7860)




# from flask import Flask, request, send_file
# import subprocess
# import os
# import sys
# from huggingface_hub import hf_hub_download
# from pydub import AudioSegment

# sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), 'src')))

# app = Flask(__name__)

# def run_f5_tts(ref_audio_path, ref_text, gen_text, model="F5TTS_Base", speed=1.2, vocoder_name="vocos"):
#     current_dir = os.path.dirname(os.path.abspath(__file__))
#     infer_cli_path = os.path.join(current_dir, "src", "f5_tts", "infer", "infer_cli.py")
#     tests_dir = os.path.join(current_dir, "tests")

#     vocab_file = hf_hub_download(repo_id="nguyensu27/TTS", filename="vocab.txt")
#     ckpt_file = hf_hub_download(repo_id="nguyensu27/TTS", filename="model_last.pt")

#     os.environ['PYTHONIOENCODING'] = 'utf-8'
#     env = os.environ.copy()
#     env['PYTHONPATH'] = os.path.abspath(os.path.join(current_dir, 'src'))

#     command = [
#         sys.executable,
#         infer_cli_path,
#         "--model", model,
#         "--ref_audio", ref_audio_path,
#         "--ref_text", ref_text,
#         "--gen_text", gen_text,
#         "--speed", str(speed),
#         "--vocoder_name", vocoder_name,
#         "--vocab_file", vocab_file,
#         "--ckpt_file", ckpt_file
#     ]

#     try:
#         result = subprocess.run(
#             command,
#             check=True,
#             capture_output=True,
#             text=True,
#             encoding='utf-8',
#             env=env
#         )

#         if os.path.exists(tests_dir):
#             wav_files = [f for f in os.listdir(tests_dir) if f.endswith('.wav')]
#             if wav_files:
#                 latest_wav = max(wav_files, key=lambda x: os.path.getmtime(os.path.join(tests_dir, x)))
#                 output_wav = os.path.join(tests_dir, latest_wav)
#                 audio = AudioSegment.from_wav(output_wav)
#                 output_mp3 = os.path.join(tests_dir, "output.mp3")
#                 audio.export(output_mp3, format="mp3")
#                 return True, output_mp3

#         return False, "Không tìm thấy file âm thanh trong thư mục tests"
#     except subprocess.CalledProcessError as e:
#         return False, f"Lỗi khi chạy infer_cli.py: {e.stderr}"
#     except Exception as e:
#         return False, str(e)

# @app.route('/')
# def home():
#     return "F5-TTS API is running. Use POST /api/generate to generate audio."

# @app.route('/api/generate', methods=['POST'])
# def generate_speech():
#     if 'ref_audio' not in request.files:
#         return {"error": "Missing ref_audio"}, 400
#     ref_audio = request.files['ref_audio']
#     ref_text = request.form.get('ref_text', '')
#     gen_text = request.form.get('gen_text', '')
#     model = request.form.get('model', 'F5TTS_Base')
#     speed = float(request.form.get('speed', 1.2))

#     import time
#     ref_audio_path = f"temp_ref_{int(time.time())}.wav"
#     ref_audio.save(ref_audio_path)

#     success, result = run_f5_tts(ref_audio_path, ref_text, gen_text, model, speed)
#     os.remove(ref_audio_path)

#     if success:
#         return send_file(result, mimetype='audio/mpeg')
#     else:
#         return {"error": result}, 500

# if __name__ == "__main__":
#     port = int(os.environ.get("PORT", 7860))
#     app.run(host="0.0.0.0", port=port, debug=False)



# from flask import Flask, request, send_file
# import subprocess
# import os
# import sys
# from huggingface_hub import hf_hub_download
# sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), 'src')))

# app = Flask(__name__)

# # =========================
# # Hàm chạy F5-TTS
# # =========================
# def run_f5_tts(ref_audio_path, ref_text, gen_text, model="F5TTS_Base", speed=1.2, vocoder_name="vocos"):
#     current_dir = os.path.dirname(os.path.abspath(__file__))
#     infer_cli_path = os.path.join(current_dir, "src", "f5_tts", "infer", "infer_cli.py")
#     tests_dir = os.path.join(current_dir, "tests")

#     # Dùng huggingface_hub để tải file model và vocab từ repo 'nguyensu27/TTS'
#     vocab_file = hf_hub_download(repo_id="nguyensu27/TTS", filename="vocab.txt")
#     ckpt_file = hf_hub_download(repo_id="nguyensu27/TTS", filename="model_last.pt")

#     os.environ['PYTHONIOENCODING'] = 'utf-8'

#     command = [
#         sys.executable,
#         infer_cli_path,
#         "--model", model,
#         "--ref_audio", ref_audio_path,
#         "--ref_text", ref_text,
#         "--gen_text", gen_text,
#         "--speed", str(speed),
#         "--vocoder_name", vocoder_name,
#         "--vocab_file", vocab_file,
#         "--ckpt_file", ckpt_file
#     ]

#     try:
#         result = subprocess.run(
#             command,
#             check=True,
#             capture_output=True,
#             text=True,
#             encoding='utf-8'
#         )

#         if os.path.exists(tests_dir):
#             wav_files = [f for f in os.listdir(tests_dir) if f.endswith('.wav')]
#             if wav_files:
#                 latest_wav = max(
#                     wav_files, key=lambda x: os.path.getmtime(os.path.join(tests_dir, x))
#                 )
#                 output_file = os.path.join(tests_dir, latest_wav)
#                 return True, output_file

#         return False, "Không tìm thấy file âm thanh trong thư mục tests"
#     except subprocess.CalledProcessError as e:
#         return False, e.stderr
#     except Exception as e:
#         return False, str(e)


# # =========================
# # Routes
# # =========================
# @app.route('/')
# def home():
#     return "F5-TTS API is running. Use POST /api/generate to generate audio."


# @app.route('/api/generate', methods=['POST'])
# def generate_speech():
#     if 'ref_audio' not in request.files:
#         return {"error": "Missing ref_audio"}, 400
#     ref_audio = request.files['ref_audio']
#     ref_text = request.form.get('ref_text', '')
#     gen_text = request.form.get('gen_text', '')
#     model = request.form.get('model', 'F5TTS_Base')
#     speed = float(request.form.get('speed', 1.2))

#     ref_audio_path = 'temp_ref.wav'
#     ref_audio.save(ref_audio_path)

#     success, result = run_f5_tts(ref_audio_path, ref_text, gen_text, model, speed)
#     os.remove(ref_audio_path)

#     if success:
#         return send_file(result, mimetype='audio/wav')
#     else:
#         return {"error": result}, 500


# # =========================
# # Main
# # =========================
# if __name__ == "__main__":
#     port = int(os.environ.get("PORT", 7860))
#     app.run(host="0.0.0.0", port=port, debug=False)