Create app.py

app.py

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+import os
+import gradio as gr
+import whisper
+from groq import Groq
+from gtts import gTTS
+import tempfile
+
+# Load the open-source Whisper model
+model = whisper.load_model("base")  # Options: "tiny", "base", "small", "medium", "large"
+
+# Set your Groq API key directly
+client = Groq(api_key="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")
+
+# Function to transcribe, generate response, and convert to speech
+def chat_with_bot(audio_input):
+    try:
+        # Step 1: Transcribe audio input using open-source Whisper
+        try:
+            result = model.transcribe(audio_input)
+            user_input = result['text']
+        except Exception as e:
+            return "Error during transcription: " + str(e), "", None
+
+        # Step 2: Generate response using Groq API with Llama 8B model
+        try:
+            chat_completion = client.chat.completions.create(
+                messages=[
+                    {
+                        "role": "user",
+                        "content": user_input,
+                    }
+                ],
+                model="llama3-8b-8192",
+            )
+            response_text = chat_completion.choices[0].message.content
+        except Exception as e:
+            return "Error during Groq API call: " + str(e), "", None
+
+        # Step 3: Convert the response text to speech using gTTS
+        try:
+            tts = gTTS(text=response_text, lang='en')
+            # Save the TTS output to a temporary file
+            with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as f:
+                tts.save(f.name)
+                output_audio = f.name
+        except Exception as e:
+            return "Error during text-to-speech conversion: " + str(e), "", None
+
+        # Step 4: Return the transcription, response, and audio file for display in Gradio UI
+        return user_input, response_text, output_audio
+
+    except Exception as e:
+        return "An unexpected error occurred: " + str(e), "", None
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=chat_with_bot,
+    inputs=gr.Audio(type="filepath"),  # Use 'type="filepath"' for audio input
+    outputs=[
+        gr.Textbox(label="Transcription"),
+        gr.Textbox(label="Response"),
+        gr.Audio(label="Generated Speech")  # Output to replay the generated speech
+    ],
+    live=True,
+    title="Real-Time Voice-to-Voice Chatbot",
+    description="Speak into the microphone to chat with the Llama 8B model via Groq API."
+)
+
+# Launch the Gradio Interface
+iface.launch()