Delete app.py

app.py

@@ -1,50 +0,0 @@
-!pip install gradio groq openai-whisper gtts
-
-
-import os
-import gradio as gr
-from groq import Groq
-import whisper
-from gtts import gTTS
-import tempfile
-
-# Set up Groq API key
-os.environ['GROQ_API_KEY'] = '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'
-groq_client = Groq(api_key=os.environ.get('GROQ_API_KEY'))
-
-# Load Whisper model
-whisper_model = whisper.load_model("base")
-
-def process_audio(audio_file):
-    # Transcribe audio using Whisper
-    result = whisper_model.transcribe(audio_file)
-    user_text = result['text']
-
-    # Generate response using Llama 8b model with Groq API
-    chat_completion = groq_client.chat.completions.create(
-        messages=[
-            {
-                "role": "user",
-                "content": user_text,
-            }
-        ],
-        model="llama3-8b-8192",
-    )
-    response_text = chat_completion.choices[0].message.content
-
-    # Convert response text to speech using gTTS
-    tts = gTTS(text=response_text, lang='en')
-    audio_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp3')
-    tts.save(audio_file.name)
-
-    return response_text, audio_file.name
-
-# Create Gradio interface
-iface = gr.Interface(
-    fn=process_audio,
-    inputs=gr.Audio(type="filepath"),
-    outputs=[gr.Textbox(label="Response"), gr.Audio(label="Response Audio")],
-    live=True
-)
-
-iface.launch()