Code Editor for app.py

import streamlit as st
import requests
import json

# --- CONFIGURATION ---
# The backend URL for your AI agent
BACKEND_API_URL = "https://emea.snaplogic.com/api/1/rest/slsched/feed/ConnectFasterInc/snapLogic4snapLogic/Bootcamp_EMEA_August_2025/AgentDriver_Anjana_Task"

# The authorization token
AUTH_TOKEN = "Bearer 2345"

# Set up the Streamlit page configuration
st.set_page_config(page_title="AI Chatbot", page_icon="🤖")

# App title and a brief description
st.title("🤖 AI Agent Chatbot")
st.markdown("Feel free to ask me anything!")

# --- STATE MANAGEMENT ---
# Initialize chat history if it doesn't exist
if "messages" not in st.session_state:
    st.session_state.messages = []

# --- DISPLAY CHAT MESSAGES ---
# Display all previous messages on app rerun
for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.markdown(message["content"])

# --- API CALL FUNCTION ---
def send_message_to_backend(prompt):
    """Sends a user message to the backend API and returns the response."""
    
    # Define the request headers, including the Authorization token
    headers = {
        "Content-Type": "application/json",
        "Authorization": AUTH_TOKEN
    }
    
    # Define the JSON payload. This example assumes the API expects a single key like "prompt".
    # Adjust this payload format if your backend requires something different.
    payload = json.dumps({
        "prompt": prompt
    })
    
    try:
        # Make the POST request to the backend API
        response = requests.post(BACKEND_API_URL, headers=headers, data=payload)
        
        # Raise an exception for HTTP errors (4xx or 5xx)
        response.raise_for_status() 
        
        # Parse the JSON response and return it
        return response.json()
        
    except requests.exceptions.RequestException as e:
        # Handle connection errors or other request issues
        st.error(f"Error communicating with the backend: {e}")
        return None

# --- USER INPUT AND CHAT LOGIC ---
# Get user input from the chat box
if prompt := st.chat_input("Enter your message here..."):
    # 1. Add user message to chat history and display it
    st.session_state.messages.append({"role": "user", "content": prompt})
    with st.chat_message("user"):
        st.markdown(prompt)

    # 2. Call the backend API with the user's prompt
    with st.spinner("Thinking..."):
        api_response = send_message_to_backend(prompt)

    # 3. Handle the API response
    if api_response:
        # NOTE: You need to inspect the exact format of the JSON response from your API.
        # This example assumes the response is a dictionary with a "response" key.
        # e.g., {"response": "Hello, how can I help?"}
        
        # We'll use a more robust approach to handle potential variations in the API response structure.
        # This code will try to find a response in a few common formats.
        if isinstance(api_response, list) and len(api_response) > 0 and "Response" in api_response[0]:
            assistant_response = api_response[0]["Response"]
        elif isinstance(api_response, dict) and "response" in api_response:
            assistant_response = api_response["response"]
        else:
            assistant_response = f"Sorry, I received an unexpected response format: {api_response}"
        
        # Display the assistant's response
        with st.chat_message("assistant"):
            st.markdown(assistant_response)
        
        # Add the assistant's response to the chat history
        st.session_state.messages.append({"role": "assistant", "content": assistant_response})