Update app.py

app.py

@@ -1,41 +1,17 @@
-import streamlit as st
-from groq import Client, ModelType
+import os
 
-# Replace with your Groq API key
-GROQ_API_KEY = "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"
+from groq import Groq
 
-# Define a function to get chatbot response
-def get_response(prompt):
-  client = Client(api_key=GROQ_API_KEY)
-  model = client.model(ModelType.Claude_V1)  # Change model type if desired
-  response = model.generate(prompt)
-  return response.text
-
-# Streamlit app layout
-st.title("Interactive Chatbot")
-
-# Input field for user message
-user_input = st.text_input("You: ", key="user_input")
-
-# Display chat history (optional, can be implemented with a list)
+# Initialize Groq client
+client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
 
-# Generate response if user enters something
-if user_input:
-  # Get response from Groq API
-  bot_response = get_response(user_input)
-  st.write("Bot: ", bot_response)
-
-# Deployment on Hugging Face (refer to their documentation)
-# This code snippet is not included as it involves specific steps on their platform.
-# You can find deployment instructions for Streamlit apps on Hugging Face Spaces here:
-# https://docs.huggingface.com/notebooks/streamlit/
-
-# Run the app
-if __name__ == "__main__":
-  st.sidebar.title("Settings")
-  # Add any additional settings options here (e.g., model selection)
-  st.sidebar.write("Groq API Key: (hidden for security)")
-  st.sidebar.success("Connected to Groq!")
-  st.balloons()  # Enable notification popups for user interaction
-  st.experimental_autogenerated_data_reports()  # Enable data reports
-  st.server.main()
+def get_response(prompt):
+  # Create chat completion request
+  chat_completion = client.chat.completions.create(
+      messages=[{"role": "user", "content": prompt}],
+      model="your_desired_model"  # Replace with your preferred model
+  )
+  # Return the first choice's message content
+  return chat_completion.choices[0].message.content
+
+# Rest of your Streamlit app code using get_response function