Update app.py

app.py

@@ -20,13 +20,20 @@ import gradio as gr
 # Initialize the Kokoro pipeline
 pipeline = KPipeline(lang_code='a')  # 'a' stands for American English
 
-# Define audio output path
-AUDIO_OUTPUT_PATH = "tools/output.wav"
-
 @tool
 def text_to_speech_kokoro(text: str, voice: str = 'af_heart', speed: float = 1.0) -> str:
-    """Convert text to speech using Kokoro-82M model and return audio file path."""
+    """Convert text to speech using the Kokoro-82M model.
+    
+    Args:
+        text (str): The text to be converted to speech.
+        voice (str, optional): The voice to use for speech synthesis. Defaults to 'af_heart'.
+        speed (float, optional): The speed of the speech. Defaults to 1.0.
+    
+    Returns:
+        str: The path to the generated audio file.
+    """
     try:
+        # Generate speech audio
         generator = pipeline(text, voice=voice, speed=speed, split_pattern=r'\n+')
         audio_segments = []
         for _, _, audio in generator:
@@ -35,38 +42,18 @@ def text_to_speech_kokoro(text: str, voice: str = 'af_heart', speed: float = 1.0
         if not audio_segments:
             raise ValueError("No audio generated.")
         
+        # Concatenate segments into one audio array
         full_audio = np.concatenate(audio_segments)
         sample_rate = 24000  # Kokoro outputs at 24 kHz
-        
-        os.makedirs("tools", exist_ok=True)
-        sf.write(AUDIO_OUTPUT_PATH, full_audio, sample_rate)
-        
-        return AUDIO_OUTPUT_PATH
-    except Exception as e:
-        return f"Error generating speech: {str(e)}"
 
+        # Ensure the tools folder exists and save the file there
+        os.makedirs("tools", exist_ok=True)
+        filename = os.path.join("tools", "output.wav")
+        sf.write(filename, full_audio, sample_rate)
 
-@tool
-def search_dad_jokes(term: str) -> str:
-    """A tool that searches for dad jokes containing a specific term.
-    Args:
-        term: The keyword to search for in dad jokes.
-    """
-    try:
-        headers = {
-            "Accept": "application/json",
-            "User-Agent": "YourAppName (https://yourappurl.com)"
-        }
-        response = requests.get(f"https://icanhazdadjoke.com/search?term={term}", headers=headers)
-        data = response.json()
-        if data['results']:
-            jokes = [joke['joke'] for joke in data['results']]
-            return f"Found {len(jokes)} jokes:\n" + "\n\n".join(jokes)
-        else:
-            return f"No jokes found for the term '{term}'."
+        return filename  # Return the file path
     except Exception as e:
-        return f"Error searching for jokes: {str(e)}"
-
+        return f"Error generating speech: {str(e)}"
 
 
 
@@ -106,21 +93,6 @@ agent = CodeAgent(
 )
 
 
-#GradioUI(agent).launch()
+GradioUI(agent).launch()
 
-# Gradio wrapper function
-def gradio_text_to_speech(text):
-    audio_path = text_to_speech_kokoro(text)
-    return audio_path if os.path.exists(audio_path) else "Error: No audio file generated."
-
-# Define the Gradio UI
-with gr.Blocks() as demo:
-    gr.Markdown("### Text-to-Speech with Kokoro AI 🎙️")
-    with gr.Row():
-        input_box = gr.Textbox(label="Enter text")
-        output_audio = gr.Audio(label="Generated Speech", type="filepath")
-    
-    btn = gr.Button("Generate Speech")
-    btn.click(gradio_text_to_speech, inputs=input_box, outputs=output_audio)
 
-demo.launch()