Create app.py

app.py

@@ -0,0 +1,72 @@
+import streamlit as st
+from streamlit.components.v1 import html
+import os
+from groq import Groq
+
+# Initialize Groq Client
+client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
+
+# Set the title of the app
+st.title("AI Chatbot with Groq LLaMA Model")
+
+# Custom CSS for a professional look
+css = """
+    <style>
+        body {
+            background-color: #f0f2f6;
+            font-family: 'Arial', sans-serif;
+        }
+        .stTextInput, .stButton {
+            margin-top: 20px;
+        }
+        .custom-box {
+            padding: 20px;
+            background-color: #ffffff;
+            border-radius: 8px;
+            box-shadow: 0px 4px 10px rgba(0, 0, 0, 0.1);
+        }
+        .error-msg {
+            color: red;
+            font-weight: bold;
+        }
+    </style>
+"""
+
+html(css)
+
+st.markdown(
+    """
+    <div class='custom-box'>
+    <h2>Ask anything about Data Science</h2>
+    <p>Powered by Groq LLaMA 3.1 Model 🚀</p>
+    </div>
+    """, unsafe_allow_html=True
+)
+
+# Input for user queries
+user_input = st.text_input("Ask your question here:")
+
+# Function to handle Groq API call
+def get_groq_response(query):
+    try:
+        chat_completion = client.chat.completions.create(
+            messages=[{"role": "user", "content": query}],
+            model="llama-3.1-70b-versatile",
+        )
+        return chat_completion.choices[0].message.content
+    except Exception as e:
+        return f"An error occurred: {str(e)}"
+
+# Submit button for the chatbot
+if st.button("Submit"):
+    if user_input:
+        with st.spinner("Fetching response..."):
+            response = get_groq_response(user_input)
+            st.success(response)
+    else:
+        st.error("Please enter a question!")
+
+# Copy Button for User to easily copy the result
+if response:
+    st.code(response)
+    st.button("Copy to clipboard", on_click=st.experimental_rerun)