Update app.py

app.py

@@ -5,62 +5,68 @@ from soprano import SopranoTTS
 from scipy.io.wavfile import write as wav_write
 import tempfile
 import os
-import spaces
 
+# Detect device
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
-print(DEVICE)
+print(f"Using device: {DEVICE}")
 
-# Load model once
+# Load model once - works on both CUDA and CPU
 model = SopranoTTS(
-    backend="auto",
+    backend="auto",  # Will automatically choose best backend for device
     device=DEVICE,
-    cache_size_mb=100,
+    cache_size_mb=100,  # Only relevant for CUDA
     decoder_batch_size=1,
 )
 
 SAMPLE_RATE = 32000
 
-
-@spaces.GPU
+# Remove @spaces.GPU decorator - not needed for CPU support
 def tts_stream(text, temperature, top_p, repetition_penalty, state):
     if not text.strip():
         yield None, state
         return
-
+    
     out = model.infer(
         text,
         temperature=temperature,
         top_p=top_p,
         repetition_penalty=repetition_penalty,
     )
-
+    
     audio_np = out.cpu().numpy()
     yield (SAMPLE_RATE, audio_np), audio_np
 
-
 def save_audio(state):
     if state is None or len(state) == 0:
         return None
+    
     fd, path = tempfile.mkstemp(suffix=".wav")
     os.close(fd)
     wav_write(path, SAMPLE_RATE, state)
     return path
 
-
 with gr.Blocks() as demo:
     state_audio = gr.State(None)
-
+    
     with gr.Row():
         with gr.Column():
-            gr.Markdown("# Soprano Demo\n\nSoprano is an ultra‑lightweight, open‑source text‑to‑speech (TTS) model designed for real‑time, high‑fidelity speech synthesis at unprecedented speed. Soprano can achieve **<15 ms streaming latency** and up to **2000x real-time generation**, all while being easy to deploy at **<1 GB VRAM usage**.\n\nGithub: https://github.com/ekwek1/soprano\n\nModel Weights: https://huggingface.co/ekwek/Soprano-80M")
-
+            gr.Markdown(
+                f"# Soprano Demo\n\n"
+                f"**Running on: {DEVICE.upper()}**\n\n"
+                "Soprano is an ultra‑lightweight, open‑source text‑to‑speech (TTS) model designed for real‑time, "
+                "high‑fidelity speech synthesis at unprecedented speed. Soprano can achieve **<15 ms streaming latency** "
+                "and up to **2000x real-time generation**, all while being easy to deploy at **<1 GB VRAM usage**.\n\n"
+                "Github: https://github.com/ekwek1/soprano\n\n"
+                "Model Weights: https://huggingface.co/ekwek/Soprano-80M"
+            )
+            
             text_in = gr.Textbox(
                 label="Input Text",
                 placeholder="Enter text to synthesize...",
                 value="Soprano is an extremely lightweight text to speech model designed to produce highly realistic speech at unprecedented speed.",
                 lines=4,
             )
-
+            
             with gr.Accordion("Advanced options", open=False):
                 temperature = gr.Slider(
                     0.0, 1.0, value=0.3, step=0.05, label="Temperature"
@@ -71,37 +77,41 @@ with gr.Blocks() as demo:
                 repetition_penalty = gr.Slider(
                     1.0, 2.0, value=1.2, step=0.05, label="Repetition penalty"
                 )
-
+            
             gen_btn = gr.Button("Generate")
-
+        
         with gr.Column():
             audio_out = gr.Audio(
                 label="Output Audio",
                 autoplay=True,
                 streaming=False,
             )
-            #download_btn = gr.Button("Download")
-            #file_out = gr.File(label="Download file")
+            
+            download_btn = gr.Button("Download")
+            file_out = gr.File(label="Download file")
+            
             gr.Markdown(
                 "Usage tips:\n\n"
                 "- Soprano works best when each sentence is between 2 and 15 seconds long.\n"
-                "- Although Soprano recognizes numbers and some special characters, it occasionally mispronounces them. Best results can be achieved by converting these into their phonetic form. (1+1 -> one plus one, etc)\n"
-                "- If Soprano produces unsatisfactory results, you can easily regenerate it for a new, potentially better generation. You may also change the sampling settings for more varied results.\n"
-                "- Avoid improper grammar such as not using contractions, multiple spaces, etc."
+                "- Although Soprano recognizes numbers and some special characters, it occasionally mispronounces them. "
+                "Best results can be achieved by converting these into their phonetic form. (1+1 -> one plus one, etc)\n"
+                "- If Soprano produces unsatisfactory results, you can easily regenerate it for a new, potentially better generation. "
+                "You may also change the sampling settings for more varied results.\n"
+                "- Avoid improper grammar such as not using contractions, multiple spaces, etc.\n\n"
+                f"**Note:** {'GPU acceleration active' if DEVICE == 'cuda' else 'Running on CPU - generation may be slower'}"
             )
-
-
+    
     gen_btn.click(
         fn=tts_stream,
         inputs=[text_in, temperature, top_p, repetition_penalty, state_audio],
         outputs=[audio_out, state_audio],
     )
-
-    #download_btn.click(
-    #    fn=save_audio,
-    #    inputs=[state_audio],
-    #    outputs=[file_out],
-    #)
+    
+    download_btn.click(
+        fn=save_audio,
+        inputs=[state_audio],
+        outputs=[file_out],
+    )
 
 demo.queue()
 demo.launch()