Update app.py

app.py

@@ -1,32 +1,71 @@
 # app.py
 import os
+import streamlit as st
 from groq import Groq
-import gradio as gr
-from dotenv import load_dotenv
-
-# Load .env file (contains your API key)
-load_dotenv()
-client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
-
-def groq_chat(message, history):
-    messages = [{"role": "system", "content": "You are a helpful assistant."}]
-    for user, bot in history:
-        messages.append({"role": "user", "content": user})
-        messages.append({"role": "assistant", "content": bot})
-    messages.append({"role": "user", "content": message})
-
-    response = client.chat.completions.create(
-        model="llama-3.3-70b-versatile",  # Change model if needed
-        messages=messages,
-        temperature=0.7,
-    )
-    return response.choices[0].message.content
-
-demo = gr.ChatInterface(
-    fn=groq_chat,
-    title="Groq Chatbot",
-    description="Chat with a lightning-fast LLM via Groq API",
-    theme=gr.themes.Soft()
-)
-
-demo.launch()
+
+# Initialize Groq client
+client = Groq(api_key=os.getenv("GROQ_API_KEY"))
+
+# ---------------- UI Setup ----------------
+st.set_page_config(page_title="Advanced Groq Chatbot", layout="centered")
+st.title("🤖 Groq Chatbot")
+st.markdown("Chat using lightning-fast open-source LLMs on Groq!")
+
+# Model selector (friendly names)
+model_options = {
+    "💬 Fast Chat (LLaMA 3 8B)": "llama3-8b-8192",
+    "🧠 Deep Reasoning (LLaMA 3 70B)": "llama3-70b-8192",
+    "📊 Math Solver (Mixtral)": "mixtral-8x7b-32768"
+}
+model_choice = st.selectbox("Choose assistant type:", list(model_options.keys()))
+model_id = model_options[model_choice]
+
+# Personality selector
+style_options = {
+    "Friendly": "You are a friendly assistant who replies casually.",
+    "Professional": "You are a formal and helpful assistant.",
+    "Technical": "You are a technical assistant providing accurate information."
+}
+personality = st.selectbox("Choose assistant personality:", list(style_options.keys()))
+system_prompt = style_options[personality]
+
+# Initialize session history
+if "messages" not in st.session_state:
+    st.session_state.messages = [{"role": "system", "content": system_prompt}]
+
+# Clear chat button
+if st.button("🔄 Clear Chat"):
+    st.session_state.messages = [{"role": "system", "content": system_prompt}]
+    st.rerun()
+
+# Show chat history
+for msg in st.session_state.messages[1:]:
+    with st.chat_message(msg["role"]):
+        st.markdown(msg["content"])
+
+# Chat input
+if prompt := st.chat_input("Type your message..."):
+    st.chat_message("user").markdown(prompt)
+    st.session_state.messages.append({"role": "user", "content": prompt})
+
+    # Call Groq with streaming
+    try:
+        response = client.chat.completions.create(
+            model=model_id,
+            messages=st.session_state.messages,
+            temperature=0.7,
+            stream=True
+        )
+
+        reply_text = ""
+        with st.chat_message("assistant"):
+            reply_box = st.empty()
+            for chunk in response:
+                content = chunk.choices[0].delta.content or ""
+                reply_text += content
+                reply_box.markdown(reply_text)
+
+        st.session_state.messages.append({"role": "assistant", "content": reply_text})
+
+    except Exception as e:
+        st.error(f"❌ Error: {e}")