Create app.py

app.py

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+import gradio as gr
+from gradio_client import Client
+
+# Call the existing chat model
+chat_client = Client("Futuresony/Mr.Events")
+
+# Load the Whisper model - using the public space as the specific model was not found
+# You might need to adjust this if a specific space for whisper-large-v3-turbo becomes available or accessible
+try:
+    whisper_client = Client("openai/whisper-large-v3-turbo")
+except Exception as e:
+    print(f"Could not load 'openai/whisper-large-v3-turbo', falling back to 'openai/whisper'. Error: {e}")
+    whisper_client = Client("openai/whisper")
+
+def chat_with_model(user_input):
+    """Sends text input to the chat model and returns the response."""
+    result = chat_client.predict(
+        query=user_input,
+        api_name="/chat"
+    )
+    return result
+
+def transcribe_audio(audio_input):
+    """Transcribes audio input using the Whisper model."""
+    if audio_input is None:
+        return ""
+    try:
+        # The API name might vary depending on the specific Whisper space
+        # Common API names are "/predict", "/run"
+        transcript = whisper_client.predict(audio_input, api_name="/predict")
+        return transcript
+    except Exception as e:
+        print(f"Error during transcription: {e}")
+        return f"Transcription failed: {e}"
+
+def send_message(transcribed_text, manual_text_input):
+    """Determines which input to send to the chat model and returns the response."""
+    if transcribed_text:
+        return chat_with_model(transcribed_text)
+    elif manual_text_input:
+        return chat_with_model(manual_text_input)
+    else:
+        return "Please provide audio or text input."
+
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("## 💬 Test the ABSA Model Chat with Audio Input")
+    with gr.Row():
+        with gr.Column(scale=3):
+            audio_input = gr.Audio(sources=["microphone", "upload"], label="Audio Input")
+            transcribed_text = gr.Textbox(label="Transcribed Text", lines=3, interactive=False) # Make transcribed text non-interactive
+            manual_text_input = gr.Textbox(label="Or type your message here", lines=3)
+            submit_btn = gr.Button("Send")
+        with gr.Column(scale=5):
+            output_text = gr.Textbox(label="Model Response", lines=6, interactive=False) # Make output non-interactive
+
+    # Connect interface elements to functions
+    audio_input.change(fn=transcribe_audio, inputs=audio_input, outputs=transcribed_text)
+    submit_btn.click(fn=send_message, inputs=[transcribed_text, manual_text_input], outputs=output_text)
+
+# Launch the Gradio application
+demo.launch(share=True) # share=True is required for Colab