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app.py

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+import gradio as gr
+import requests
+import base64
+import os
+from pathlib import Path
+import tempfile
+import numpy as np
+import io
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+# Maximum allowed input text length
+MAX_TEXT_LENGTH = 4000
+
+# Language mapping with display names
+LANGUAGES = {
+    "en": "English",
+    "hi": "Hindi",
+    "bn": "Bengali",
+    "ta": "Tamil",
+    "te": "Telugu",
+    "ml": "Malayalam",
+    "mr": "Marathi",
+    "gu": "Gujarati",
+    "kn": "Kannada"
+}
+
+def generate_audio(input_text, input_language, input_speaker):
+    """
+    Generate audio from text using Krutrim TTS API
+    """
+    # Check if text exceeds the character limit
+    if len(input_text) > MAX_TEXT_LENGTH:
+        return None, f"Error: Input text exceeds the maximum limit of {MAX_TEXT_LENGTH} characters. Your text has {len(input_text)} characters."
+    
+    # Get API key from environment variable
+    api_key = os.getenv("KRUTRIM_API_KEY")
+    if not api_key:
+        return None, "Error: KRUTRIM_API_KEY environment variable not found. Please check your .env file."
+        
+    url = "https://cloud.olakrutrim.com/v1/audio/generations/krutrim-tts"
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {api_key}"
+    }
+    
+    payload = {
+        "modelName": "tts",
+        "input_text": input_text,
+        "input_language": input_language,
+        "input_speaker": input_speaker
+    }
+    
+    try:
+        response = requests.post(url, json=payload, headers=headers)
+        response.raise_for_status()  # Raise an error for HTTP failure codes
+
+        result = response.json()
+        base64_audio = result["output"]
+        
+        audio_data = base64.b64decode(base64_audio)
+        
+        # Save to a temporary file for download option
+        temp_dir = Path(tempfile.gettempdir())
+        output_path = temp_dir / "krutrim_output.wav"
+        
+        with open(output_path, "wb") as f:
+            f.write(audio_data)
+        
+        # Convert to format suitable for browser playback
+        try:
+            # Convert WAV data to numpy array for Gradio's audio component
+            audio_np = np.frombuffer(audio_data, dtype=np.int16)
+            # Standard sample rate for most audio
+            sample_rate = 16000  # Adjust this if your API returns a different sample rate
+            
+            return (sample_rate, audio_np), "Audio generated successfully! Click the play button to listen."
+        except Exception as e:
+            # Fallback to file path if conversion fails
+            return str(output_path), f"Audio generated but playback in browser might not work. You can download the file. Error: {e}"
+            
+    except requests.exceptions.RequestException as e:
+        return None, f"Error: {e}"
+
+# Create Gradio interface
+with gr.Blocks(title="Krutrim Text-to-Speech") as demo:
+    gr.Markdown("# Krutrim Text-to-Speech Generator")
+    gr.Markdown("Enter your text below and get it converted to speech using Krutrim's TTS API.")
+    
+    with gr.Row():
+        with gr.Column():
+            text_input = gr.Textbox(label="Text to convert to speech", 
+                                  placeholder="Type your text here (maximum 4000 characters)...",
+                                  lines=5)
+            language = gr.Dropdown(label="Language", 
+                               choices=list(LANGUAGES.keys()), 
+                               value="en")
+            speaker = gr.Dropdown(label="Speaker", 
+                               choices=["male", "female"], 
+                               value="male")
+            submit_btn = gr.Button("Generate Audio")
+        
+        with gr.Column():
+            audio_output = gr.Audio(
+                label="Generated Audio",
+                type="numpy",  # Explicitly set to numpy for better browser compatibility
+                autoplay=True,  # Auto play the audio when generated
+                show_download_button=True,  # Show the download button for the audio
+                waveform_options={"waveform_color": "blue", "waveform_progress_color": "red"},  # Customize waveform appearance
+                format="wav"  # Specify output format
+            )
+            output_message = gr.Textbox(label="Status")
+    
+    submit_btn.click(
+        fn=generate_audio,
+        inputs=[text_input, language, speaker],
+        outputs=[audio_output, output_message]
+    )
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio>=3.50.2
+requests>=2.31.0
+python-dotenv>=1.0.0
+numpy>=1.24.0