Update app.py

app.py

@@ -1,7 +1,7 @@
 import os
 import sys
 import subprocess
-import time 
+import time
 
 # 1. Clone the repo if it doesn't exist
 if not os.path.exists("LuxTTS"):
@@ -20,75 +20,126 @@ from zipvoice.luxvoice import LuxTTS
 
 # Init Model
 device = "cuda" if torch.cuda.is_available() else "cpu"
-# Note: 2 threads on a 2-core CPU is the bottleneck
-lux_tts = LuxTTS('YatharthS/LuxTTS', device=device, threads=2)
+lux_tts = LuxTTS("YatharthS/LuxTTS", device=device, threads=2)
 
-def infer(text, audio_prompt, rms, t_shift, num_steps, speed, return_smooth):
+def infer(
+    text,
+    audio_prompt,
+    rms,
+    ref_duration,
+    t_shift,
+    num_steps,
+    speed,
+    return_smooth,
+):
     if audio_prompt is None or not text:
         return None, "Please provide text and reference audio."
-    
+
     start_time = time.time()
-    
-    # Encode reference
-    encoded_prompt = lux_tts.encode_prompt(audio_prompt, rms=rms)
-    
+
+    # Encode reference (WITH duration)
+    encoded_prompt = lux_tts.encode_prompt(
+        audio_prompt,
+        duration=ref_duration,
+        rms=rms,
+    )
+
     # Generate speech
     final_wav = lux_tts.generate_speech(
-        text, 
-        encoded_prompt, 
-        num_steps=int(num_steps), 
-        t_shift=t_shift, 
-        speed=speed, 
-        return_smooth=return_smooth
+        text,
+        encoded_prompt,
+        num_steps=int(num_steps),
+        t_shift=t_shift,
+        speed=speed,
+        return_smooth=return_smooth,
     )
-    
-    end_time = time.time()
-    duration = round(end_time - start_time, 2)
-    
+
+    duration = round(time.time() - start_time, 2)
+
     final_wav = final_wav.cpu().squeeze(0).numpy()
     final_wav = (np.clip(final_wav, -1.0, 1.0) * 32767).astype(np.int16)
-    
+
     stats_msg = f"✨ Generation complete in **{duration}s**."
     return (48000, final_wav), stats_msg
 
+# =======================
 # Gradio UI
+# =======================
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
     gr.Markdown("# 🎙️ LuxTTS Voice Cloning")
-    
-    # Info Panel
+
     gr.Markdown(
         """
-        > **Note:** Processing may feel slow as this instance uses a **2-core CPU** (lower specs than most modern phones). 
-        > 
-        > **Tip:** If you notice words are being **cut off** at the end, try **lowering the speed** further.
+        > **Note:** This demo runs on a **2-core CPU**, so expect slower inference.  
+        > **Tip:** If words get cut off, lower **Speed** or increase **Ref Duration**.
         """
     )
-    
+
     with gr.Row():
         with gr.Column():
-            input_text = gr.Textbox(label="Text to Synthesize", value="Hey, what's up? I'm feeling really great!")
-            input_audio = gr.Audio(label="Reference Audio (.wav)", type="filepath")
-            
+            input_text = gr.Textbox(
+                label="Text to Synthesize",
+                value="Hey, what's up? I'm feeling really great!",
+            )
+            input_audio = gr.Audio(
+                label="Reference Audio (.wav)",
+                type="filepath",
+            )
+
             with gr.Row():
-                rms_val = gr.Number(value=0.01, label="RMS (Loudness)")
-                t_shift_val = gr.Number(value=0.9, label="T-Shift")
-                steps_val = gr.Slider(1, 10, value=4, step=1, label="Num Steps")
-            
+                rms_val = gr.Number(
+                    value=0.01,
+                    label="RMS (Loudness)",
+                )
+                ref_duration_val = gr.Number(
+                    value=5,
+                    label="Reference Duration (sec)",
+                    info="Lower = faster. Set ~1000 if you hear artifacts.",
+                )
+                t_shift_val = gr.Number(
+                    value=0.9,
+                    label="T-Shift",
+                )
+
             with gr.Row():
-                # Default speed set to 0.8
-                speed_val = gr.Slider(0.5, 2.0, value=0.8, step=0.1, label="Speed (Lower = Longer/Clearer)")
-                smooth_val = gr.Checkbox(label="Return Smooth", value=False)
-            
+                steps_val = gr.Slider(
+                    1,
+                    10,
+                    value=4,
+                    step=1,
+                    label="Num Steps",
+                )
+                speed_val = gr.Slider(
+                    0.5,
+                    2.0,
+                    value=0.8,
+                    step=0.1,
+                    label="Speed (Lower = Longer / Clearer)",
+                )
+                smooth_val = gr.Checkbox(
+                    label="Return Smooth",
+                    value=False,
+                )
+
             btn = gr.Button("Generate Speech", variant="primary")
-            
+
         with gr.Column():
             audio_out = gr.Audio(label="Result")
             status_text = gr.Markdown("Ready to generate...")
 
     btn.click(
-        fn=infer, 
-        inputs=[input_text, input_audio, rms_val, t_shift_val, steps_val, speed_val, smooth_val], 
-        outputs=[audio_out, status_text]
+        fn=infer,
+        inputs=[
+            input_text,
+            input_audio,
+            rms_val,
+            ref_duration_val,
+            t_shift_val,
+            steps_val,
+            speed_val,
+            smooth_val,
+        ],
+        outputs=[audio_out, status_text],
     )
 
-demo.launch()
+demo.launch()