init

app.py

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+import gradio as gr
+import requests
+import os
+import dwani
+
+# List of supported languages
+LANGUAGES = ["malayalam", "tamil", "telugu", "hindi", "kannada"]
+dwani.api_key = os.getenv("DWANI_API_KEY")
+
+dwani.api_base = os.getenv("DWANI_API_BASE_URL")
+
+# Function to extract language name
+def get_lang_name(lang_string):
+    return lang_string.split("(")[0].strip().lower()
+
+def transcribe_api(audio_file, language):
+    # Get the base URL from environment variable
+    result = dwani.ASR.transcribe(file_path=audio_file, language=language)
+    return result
+
+# Create Gradio interface
+with gr.Blocks(title="Speech to Text API Interface") as demo:
+    gr.Markdown("# Speech to Text API Interface")
+    
+    with gr.Row():
+        with gr.Column():
+            # Input components
+            audio_input = gr.Audio(
+                label="Audio File",
+                type="filepath",
+                sources=["upload"]
+            )
+            language_input = gr.Dropdown(
+                label="Language",
+                choices=LANGUAGES,
+                value="kannada"
+            )
+            
+            submit_btn = gr.Button("Transcribe")
+        
+        with gr.Column():
+            # Output component
+            output = gr.JSON(label="Transcription Response")
+    
+    # Connect the button click to the API function
+    submit_btn.click(
+        fn=transcribe_api,
+        inputs=[audio_input, language_input],
+        outputs=output
+    )
+
+# Launch the interface
+demo.launch()

requirements.txt

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+gradio
+dwani