Update app.py

app.py

@@ -1,30 +1,31 @@
 import streamlit as st
 from groq import Groq
 import time
+import matplotlib.pyplot as plt
 
 # API Key (replace with yours)
 API_KEY = "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"
 
 # Function to interact with the model
 def get_model_response(prompt):
-  try:
-    client = Groq(api_key=API_KEY)
-    chat_completion = client.chat.completions.create(
-        messages=[
-            {
-                "role": "user",
-                "content": prompt,
-            }
-        ],
-        model="llama3-8b-8192",  # Update with your desired model
-    )
-    response = chat_completion.choices[0].message.content
-    return response
-  except Exception as e:
-    return f"An error occurred: {str(e)}"
+    try:
+        client = Groq(api_key=API_KEY)
+        chat_completion = client.chat.completions.create(
+            messages=[
+                {
+                    "role": "user",
+                    "content": prompt,
+                }
+            ],
+            model="llama3-8b-8192",  # Update with your desired model
+        )
+        response = chat_completion.choices[0].message.content
+        return response
+    except Exception as e:
+        return f"An error occurred: {str(e)}"
 
 # Streamlit App
-st.set_page_config(page_title="AI Chat Interface", page_icon="")  # Set title and icon
+st.set_page_config(page_title="AI Chat Interface", page_icon="🤖", layout="wide")
 
 # Add a header with logo (optional)
 st.markdown("""
@@ -36,15 +37,36 @@ st.markdown("""
 
 # Progress bar animation for loading
 with st.spinner("Thinking..."):
-  time.sleep(2)  # Simulate processing time
+    time.sleep(2)  # Simulate processing time
 
-user_input = st.text_input("Your Prompt", placeholder="Type your question here...", key="prompt")
+# User input with placeholder and help text
+user_input = st.text_input("Your Prompt", placeholder="Type your question here...", help="Feel free to ask anything!")
 
 # Display "Thinking..." animation while fetching response
 if st.button("Get Response"):
-  with st.spinner("Fetching Response..."):
-    response = get_model_response(user_input)
-  st.write(f"**Model Response:** {response}")
+    with st.spinner("Fetching Response..."):
+        response = get_model_response(user_input)
+    st.write(f"**Model Response:** {response}")
 
 # Success message animation
-st.success("Response retrieved successfully!")
+st.success("Response retrieved successfully!")
+
+# Example of a simple chart (if applicable)
+if "chart" in response.lower():
+    # Generate some random data
+    x = [1, 2, 3, 4, 5]
+    y = [2, 4, 5, 4, 5]
+
+    # Create a simple line chart
+    plt.plot(x, y)
+    plt.xlabel("X-axis")
+    plt.ylabel("Y-axis")
+    plt.title("Simple Line Chart")
+    st.pyplot(plt)
+
+# Additional tips:
+# - Use custom CSS to style the app further.
+# - Explore Streamlit's components library for more interactive elements.
+# - Consider using a library like `plotly` for more advanced visualizations.
+# - Implement error handling and logging for a robust app.
+# - Test your app thoroughly on different browsers and devices.