Script for inference

inference_M2.py

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+from flask import Flask, request, send_file, jsonify
+from TTS.utils.synthesizer import Synthesizer
+from romanizer import sinhala_to_roman
+import io
+from datetime import datetime
+import torch
+
+# Model paths
+MODEL_PATH = "Roshan_270000.pth"
+CONFIG_PATH = "Roshan_config.json"
+
+# Init Flask app
+app = Flask(__name__)
+
+# Load model (use CUDA if available)
+use_cuda = torch.cuda.is_available()
+synth = Synthesizer(tts_checkpoint=MODEL_PATH, tts_config_path=CONFIG_PATH, use_cuda=use_cuda)
+
+@app.route("/tts", methods=["POST"])
+def tts():
+    """POST JSON: { "text": "<Sinhala text>" }"""
+    data = request.get_json()
+    sinhala_text = (data.get("text") or "").strip()
+    if not sinhala_text:
+        return jsonify({"error": "No text provided"}), 400
+
+    # Romanize Sinhala text
+    roman_text = sinhala_to_roman(sinhala_text)
+
+    # Generate audio
+    wav = synth.tts(roman_text)
+    out = io.BytesIO()
+    synth.save_wav(wav, out)
+    out.seek(0)
+
+    # Optional local save (timestamped)
+    filename = f"tts_{datetime.now().strftime('%Y%m%d_%H%M%S')}.wav"
+    synth.save_wav(wav, filename)
+
+    # Return WAV directly
+    return send_file(out, mimetype="audio/wav", as_attachment=True, download_name="output.wav")
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=8000)