streamlit_app.py

import streamlit as st
import requests

# Your FastAPI endpoint
API_URL = "http://localhost:8000/api/analytics-chatbot"   # change if deployed

st.set_page_config(page_title="Analytics Chatbot", page_icon="🤖", layout="centered")

st.title("📊 Analytics Chatbot")

# Initialize chat history
if "messages" not in st.session_state:
    st.session_state["messages"] = []

# Display previous messages
for chat in st.session_state["messages"]:
    role = "🧑 You" if chat["role"] == "user" else "🤖 Bot"
    with st.chat_message(chat["role"]):
        st.markdown(f"**{role}:** {chat['content']}")

# User input box
if prompt := st.chat_input("Ask something about analytics..."):
    # Store user message
    st.session_state["messages"].append({"role": "user", "content": prompt})

    # Show user message
    with st.chat_message("user"):
        st.markdown(f"**🧑 You:** {prompt}")

    try:
        # Call FastAPI backend
        response = requests.post(API_URL, json={"message": prompt})

        if response.status_code == 200:
            bot_reply = response.json()
            # bot_reply = f"**Endpoint:** {data['endpoint']}\n\n" \
            #             f"**Parameters:** `{data['parameters']}`\n\n" \
            #             f"**Response:** {data['response']}"
        else:
            bot_reply = f"⚠️ Error {response.status_code}: {response.text}"

    except Exception as e:
        bot_reply = f"❌ Failed to connect to API: {e}"

    # Store bot message
    st.session_state["messages"].append({"role": "assistant", "content": bot_reply['response']})

    # Show bot reply
    with st.chat_message("assistant"):
        st.json(bot_reply['response'])