Update app.py

app.py

@@ -1,8 +1,7 @@
 import tempfile
+
 import edge_tts
 import gradio as gr
-import asyncio
-
 
 language_dict = {
     "Hindi": {
@@ -442,58 +441,33 @@ language_dict = {
   }
 }
 
-# Function to split text into manageable chunks
-def split_text(text, max_length=200):
-    return [text[i:i + max_length] for i in range(0, len(text), max_length)]
-
-# Async function to handle concurrent text-to-speech processing
-async def process_chunk(chunk, voice):
-    communicate = edge_tts.Communicate(chunk, voice)
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
-        tmp_path = tmp_file.name
-        await communicate.save(tmp_path)
-    return tmp_path
 
-# Main function to split and process text concurrently
 async def text_to_speech_edge(text, language_code, speaker, tashkeel_checkbox=False):
-    # Get the voice for the selected language and speaker
-    voice = language_dict.get(language_code, {}).get(speaker)
-    if not voice:
-        return "Error: Selected language or speaker is not valid.", None
-
-    # Split text into chunks
-    text_chunks = split_text(text)
+ 
     
-    # Process each chunk concurrently
-    tasks = [process_chunk(chunk, voice) for chunk in text_chunks]
-    audio_paths = await asyncio.gather(*tasks)
+    # Get the voice for the selected language and speaker
+    voice = language_dict[language_code][speaker]
+    communicate = edge_tts.Communicate(text, voice)
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
+      tmp_path = tmp_file.name
+      await communicate.save(tmp_path)
 
-    # Merge all audio files into a single output (if needed)
-    merged_audio_path = tempfile.mktemp(suffix=".mp3")
-    with open(merged_audio_path, "wb") as outfile:
-        for path in audio_paths:
-            with open(path, "rb") as infile:
-                outfile.write(infile.read())
+    return text, tmp_path
 
-    return text, merged_audio_path
 
-# update the lang box
 def get_speakers(language):
     print(language)
     speakers = list(language_dict[language].keys())
     return gr.Dropdown(choices=speakers, value=speakers[0], interactive=True), gr.Checkbox(visible=language == "Arabic", interactive=True)
 
-    
-# Default values
+
 default_language = None
 default_speaker = None
-
-# Gradio UI setup
 with gr.Blocks(title="Writoo AI V2") as demo:
     gr.HTML(" ")
-    gr.HTML("<h2 style='color:Tomato;'> 🎥 **Exciting News: 60+ Minutes File Creation is also Free !!** 🎥 </h2>")
-    gr.Markdown("✨ Features: • Convert text to speech with 60+ audio files • Choose from 72+ languages • It's Free 😍")
+    gr.HTML(f"<h2 style='color:Tomato;'> 🎥 **Exciting News: 60+ Minutes File Creation is also Free !!** 🎥 </h3>")
     
+    gr.Markdown("✨ Features: • Convert text to speech with 60+ audio files.• Choose from 72+ languages • Its Free 😍")
     with gr.Row():
         with gr.Column():
             input_text = gr.Textbox(lines=5, label="Input Text", placeholder="Enter text to convert to speech")
@@ -508,16 +482,8 @@ with gr.Blocks(title="Writoo AI V2") as demo:
             output_text = gr.Textbox(label="Output Text")
             output_audio = gr.Audio(type="filepath", label="Audio Output")
 
-    # Update speaker options and tashkeel checkbox visibility based on selected language
-    language.change(get_speakers, inputs=language, outputs=[speaker, tashkeel_checkbox])
-
-    # Trigger text-to-speech function on button click
-    run_btn.click(
-        text_to_speech_edge, 
-        inputs=[input_text, language, speaker, tashkeel_checkbox], 
-        outputs=[output_text, output_audio]
-    )
+    language.change(get_speakers, inputs=[language], outputs=[speaker, tashkeel_checkbox])
+    run_btn.click(text_to_speech_edge, inputs=[input_text, language, speaker, tashkeel_checkbox], outputs=[output_text, output_audio])
 
-# Launch the app
 if __name__ == "__main__":
-    demo.queue().launch(share=False)
+    demo.queue().launch(share=False)