Update app.py

app.py

@@ -1,94 +1,26 @@
-import os
-import gc
-import torch
 from flask import Flask, request, send_file
-from rvc_python.infer import RVCInference
 from gtts import gTTS
-from pydub import AudioSegment
+import os
 
 app = Flask(__name__)
 
-# Engine lazy load
-rvc_engine = None
-
-def get_engine():
-    global rvc_engine
-    if rvc_engine is None:
-        print("📥 Loading RVC Engine (CPU Mode)...")
-        rvc_engine = RVCInference(device="cpu")
-    return rvc_engine
-
-@app.route('/')
+@app.route("/")
 def home():
-    return "✅ RVC Engine is Running!", 200
-
-@app.route('/convert', methods=['POST'])
-def convert():
-    raw_mp3 = "input.mp3"
-    raw_wav = "input.wav"
-    out_file = "output.wav"
-
-    try:
-        data = request.json
-        text = data.get('text', '')
-        model_name = data.get('model', 'elvish')
-
-        if not text:
-            return "❌ No text provided", 400
-
-        print("📥 Text:", text)
-        print("📦 Model:", model_name)
-
-        # 🔊 STEP 1: gTTS (MP3)
-        tts = gTTS(text=text, lang='hi')
-        tts.save(raw_mp3)
-
-        # 🔁 STEP 2: MP3 → WAV (RVC compatible)
-        sound = AudioSegment.from_mp3(raw_mp3)
-        sound = sound.set_channels(1).set_frame_rate(16000)
-        sound.export(raw_wav, format="wav")
-
-        # ⚙️ STEP 3: Load RVC Engine
-        engine = get_engine()
-
-        # 📁 Model paths
-        m_path = f"./models/{model_name}.pth"
-        i_path = f"./models/{model_name}.index"
-
-        print("📁 Model exists:", os.path.exists(m_path))
-        print("📁 Index exists:", os.path.exists(i_path))
-
-        if not os.path.exists(m_path):
-            return "❌ Model file missing", 404
-
-        idx = i_path if os.path.exists(i_path) else None
-
-        # 🎤 STEP 4: Voice Convert
-        print("🚀 Starting RVC inference...")
-        engine.infer(
-            input_path=raw_wav,
-            model_path=m_path,
-            index_path=idx,
-            output_path=out_file
-        )
+    return "TTS API Running"
 
-        print("✅ Conversion done!")
+@app.route("/tts", methods=["POST"])
+def tts():
+    text = request.json.get("text")
 
-        return send_file(out_file, mimetype="audio/wav")
+    if not text:
+        return "No text", 400
 
-    except Exception as e:
-        print("❌ ERROR:", str(e))
-        return str(e), 500
+    file = "out.mp3"
 
-    finally:
-        # 🧹 Cleanup
-        for f in [raw_mp3, raw_wav]:
-            if os.path.exists(f):
-                os.remove(f)
+    tts = gTTS(text=text, lang='hi')
+    tts.save(file)
 
-        gc.collect()
-        if torch.cuda.is_available():
-            torch.cuda.empty_cache()
+    return send_file(file, mimetype="audio/mpeg")
 
 if __name__ == "__main__":
     app.run(host="0.0.0.0", port=7860)