Update app.py

app.py

@@ -4,8 +4,6 @@ import numpy as np
 from scipy.io import wavfile
 from voice_processing import tts, get_model_names, voice_mapping
 from io import BytesIO
-import json
-from concurrent.futures import ThreadPoolExecutor, as_completed
 import asyncio
 
 async def convert_tts(model_name, tts_text, selected_voice, slang_rate, use_uploaded_voice, voice_upload):
@@ -36,42 +34,6 @@ async def convert_tts(model_name, tts_text, selected_voice, slang_rate, use_uplo
     audio_data_uri = f"data:audio/wav;base64,{base64.b64encode(audio_bytes).decode('utf-8')}"
     return {"info": info}, audio_data_uri
 
-def convert_tts_sync(*args):
-    loop = asyncio.new_event_loop()
-    asyncio.set_event_loop(loop)
-    return loop.run_until_complete(convert_tts(*args))
-
-def batch_convert_tts(json_input):
-    results = []
-
-    try:
-        batch_data = json.loads(json_input)
-    except Exception as e:
-        return {"error": f"Failed to parse JSON input: {str(e)}"}
-
-    with ThreadPoolExecutor() as executor:
-        future_to_entry = {
-            executor.submit(
-                convert_tts_sync,
-                entry.get("model_name"),
-                entry.get("text"),
-                entry.get("voice"),
-                entry.get("slang_rate", 0.5),
-                entry.get("use_uploaded_voice", False),
-                entry.get("voice_upload", None)
-            ): entry for entry in batch_data
-        }
-
-        for future in as_completed(future_to_entry):
-            entry = future_to_entry[future]
-            try:
-                result = future.result()
-                results.append({"info": result[0], "audio_uri": result[1]})
-            except Exception as e:
-                results.append({"error": str(e)})
-
-    return json.dumps(results, indent=4)
-
 def get_models():
     return get_model_names()
 
@@ -79,7 +41,7 @@ def get_voices():
     return list(voice_mapping.keys())
 
 iface = gr.Interface(
-    fn=convert_tts_sync,
+    fn=convert_tts,
     inputs=[
         gr.Dropdown(choices=get_models(), label="Model", interactive=True),
         gr.Textbox(label="Text", placeholder="Enter text here"),
@@ -92,24 +54,9 @@ iface = gr.Interface(
         gr.JSON(label="Info"),
         gr.Textbox(label="Audio URI")
     ],
-    title="Text-to-Speech Conversion",
-    allow_flagging="never"
-)
-
-batch_iface = gr.Interface(
-    fn=batch_convert_tts,
-    inputs=gr.Textbox(label="JSON Input", lines=20, placeholder='Paste your JSON input here'),
-    outputs=gr.JSON(label="Batch Results"),
-    title="Batch Text-to-Speech Conversion",
-    allow_flagging="never"
-)
-
-app = gr.TabbedInterface(
-    interface_list=[iface, batch_iface],
-    tab_names=["Single Conversion", "Batch Conversion"]
-)
-
-app.launch(debug=True)
+    title="Text-to-Speech Conversion"
+).queue(default_concurrency_limit=6)  # Set concurrency limit to 6 based on your hardware
 
+iface.launch()