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def main():
from dotenv import load_dotenv
load_dotenv()
# Step_1 : Setup UI with streamlit (model provider, model, system prompt, web search query)
import requests
import streamlit as st
from streamlit_lottie import st_lottie
# ---------- Page Configuration ----------
st.set_page_config(
page_title="LangGraph AI Chatbot",
layout="centered",
initial_sidebar_state="collapsed"
)
# ----------------- CUSTOM CSS ------------------
st.markdown(
"""
<style>
body {
background-color: #111827;
color: #d1d5db;
font-family: 'Segoe UI', sans-serif;
}
.sidebar-content {
background-color: #1f2937;
padding: 20px;
}
.chat-message {
padding: 10px;
border-radius: 10px;
margin-bottom: 10px;
font-size: 16px;
}
.user-message {
background-color: #374151;
}
.bot-message {
background-color: #4b5563;
}
.avatar {
width: 30px;
height: 30px;
border-radius: 50%;
margin-right: 10px;
}
button[kind="primary"] {
background-color: #10b981;
color: white;
border-radius: 10px;
border: none;
}
</style>
""",
unsafe_allow_html=True
)
# ---------- Lottie Animation ----------
def load_lottie_url(url: str):
r = requests.get(url)
if r.status_code != 200:
return None
return r.json()
lottie_ai = load_lottie_url("https://assets10.lottiefiles.com/packages/lf20_kkflmtur.json")
st_lottie(lottie_ai, height=200)
# ---------- Avatar Config ----------
USER_AVATAR = "https://cdn-icons-png.flaticon.com/512/9131/9131529.png"
AGENT_AVATAR = "https://cdn-icons-png.flaticon.com/512/4712/4712100.png"
# ---------- Title and Prompt ----------
st.title("AI Chatbot")
st.caption("Ask your AI agent anything — powered by Groq and LangGraph!")
# ---------- Initialize Session State ----------
if "chat_history" not in st.session_state:
st.session_state.chat_history = []
# ---------- Inputs ----------
MODEL_NAMES_GROQ = ["llama-3.3-70b-versatile", "llama3-70b-8192"]
system_prompt = st.text_area("Define your AI Agent : ", height=68, placeholder="Type your system prompt here...")
select_model = st.selectbox("Select Model (Groq Only) : ", MODEL_NAMES_GROQ)
allow_web_search = st.checkbox("Allow Web Search")
user_query = st.text_area("Enter you query :", height=150, placeholder="Ask Anything!")
API_URL = "https://ai-agent-backend-uzhn.onrender.com/chat"
# ---------- Chat History Display ----------
for entry in st.session_state.chat_history:
with st.chat_message("user", avatar=USER_AVATAR):
st.markdown(entry["user"])
with st.chat_message("assistant", avatar=AGENT_AVATAR):
st.markdown(entry["agent"])
# ---------- Submit Button ----------
if st.button("Ask Agent!"):
if user_query.strip():
# Step_2 : Connect with backend via URL
payload = {
"model_name" : select_model,
"system_prompt" : system_prompt,
"messages" : [user_query],
"allow_search" : allow_web_search
}
with st.spinner("Thinking... 💭"):
try:
response = requests.post(API_URL, json=payload)
if response.status_code == 200:
try:
response_data = response.json()
except ValueError:
st.error("⚠️ Unable to parse the server response.")
response_data = {"response": response.text}
if isinstance(response_data, dict) and "error" in response_data:
st.error(response_data["error"])
else:
final_response = (
response_data if isinstance(response_data, str)
else response_data .get("response", str(response_data))
)
# Display new message
with st.chat_message("user", avatar=USER_AVATAR):
st.markdown(user_query)
with st.chat_message("assistant", avatar=AGENT_AVATAR):
st.markdown(final_response)
# Feedback section
feedback = st.radio("Was this helpful?", ["👍 Yes", "👎 No"], horizontal=True)
# Export option
st.download_button(
label = "📄 Download Response",
data = final_response,
file_name = "agent_response.txt",
mime = "text/plain"
)
else:
st.error(f"🚫 Server error: {response.status_code}")
except Exception as e:
st.error(f"❌ Backend connection error: {e}")
# End of main
if __name__ == "__main__":
main()
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