| import io |
| import torch |
| import soundfile as sf |
| from flask import Flask, request, send_file |
| from transformers import AutoModelForTextToSpeech, AutoProcessor |
|
|
| app = Flask(__name__) |
|
|
| print("⏳ SPRINGLab/F5-Hindi-24KHz मॉडल लोड हो रहा है...") |
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
|
|
| |
| model = AutoModelForTextToSpeech.from_pretrained("SPRINGLab/F5-Hindi-24KHz").to(device) |
| processor = AutoProcessor.from_pretrained("SPRINGLab/F5-Hindi-24KHz") |
|
|
| print("✅ मॉडल तैयार है!") |
|
|
| @app.route('/tts', methods=['POST']) |
| def tts_api(): |
| text = request.form.get('text', '') |
| if not text: |
| return "Error: 'text' parameter is missing", 400 |
|
|
| |
| inputs = processor(text=text, return_tensors="pt").to(device) |
|
|
| with torch.no_grad(): |
| output = model(**inputs) |
| waveform = output.waveform.cpu().numpy().squeeze() |
| sample_rate = output.sample_rate |
|
|
| |
| audio_buffer = io.BytesIO() |
| sf.write(audio_buffer, waveform, sample_rate, format='WAV') |
| audio_buffer.seek(0) |
|
|
| return send_file( |
| audio_buffer, |
| mimetype='audio/wav', |
| as_attachment=True, |
| download_name='output.wav' |
| ) |
|
|
| @app.route('/') |
| def home(): |
| return "🎙️ SPRINGLab/F5-Hindi-24KHz TTS API चल रही है!" |
