File size: 2,377 Bytes
99ca370 aeb51ae 99ca370 aeb51ae | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 | # app.py
import os
import streamlit as st
from groq import Groq
# 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}")
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