Code Editor for app.py

import streamlit as st
import requests
import json

# --- API Details ---
API_ENDPOINT_URL = "https://emea.snaplogic.com/api/1/rest/slsched/feed/ConnectFasterInc/snapLogic4snapLogic/Bootcamp_EMEA_August_2025/CRM_retriver_Chandra%20Task"
AUTHORIZATION_TOKEN = "111222"

# --- Streamlit App Setup ---
st.set_page_config(page_title="CRM Chatbot", page_icon="🤖")
st.title("CRM Chatbot 💬")

# --- Function to interact with the API ---
def get_api_response(question):
    """
    Sends a user's question to the specified API and returns the response.
    """
    headers = {
        "Authorization": AUTHORIZATION_TOKEN,
        "Content-Type": "application/json"
    }
    payload = [{"Question": question}]

    try:
        response = requests.post(API_ENDPOINT_URL, headers=headers, data=json.dumps(payload))
        response.raise_for_status()  # Raise an exception for bad status codes (4xx or 5xx)

        api_response_data = response.json()
        if api_response_data and isinstance(api_response_data, list) and "Response" in api_response_data[0]:
            return api_response_data[0]["Response"]
        else:
            return "Error: Unexpected response format from the API."

    except requests.exceptions.RequestException as e:
        return f"An error occurred while calling the API: {e}"

# --- Chat Interface ---
# Initialize chat history
if "messages" not in st.session_state:
    st.session_state.messages = []
    st.session_state.messages.append({"role": "assistant", "content": "Hello! I'm a CRM assistant. How can I help you today?"})

# Display chat messages from history on app rerun
for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.markdown(message["content"])

# React to user input
if prompt := st.chat_input("Ask a question about your CRM data..."):
    # Display user message in chat message container
    st.chat_message("user").markdown(prompt)
    # Add user message to chat history
    st.session_state.messages.append({"role": "user", "content": prompt})

    # Get response from the API
    with st.spinner("Thinking..."):
        api_response = get_api_response(prompt)
    
    # Display assistant response in chat message container
    with st.chat_message("assistant"):
        st.markdown(api_response)
    # Add assistant response to chat history
    st.session_state.messages.append({"role": "assistant", "content": api_response})
import pandas as pd
import numpy as np

# Create some sample data
x = np.linspace(0, 10, 100)
y = np.sin(x)

# Add some text
st.title('Simple Streamlit App')
st.write('Welcome! This is a basic demonstration of Streamlit.')

# Display the data
st.subheader('Sample Data')
df = pd.DataFrame({
    'x': x,
    'y': y
})
st.dataframe(df.head())

# Create some plots
st.subheader('Line Plot')
st.line_chart(df.set_index('x'))

st.subheader('Area Chart')
st.area_chart(df.set_index('x'))

# Add interactive elements
st.subheader('Interactive Elements')
name = st.text_input('Enter your name')
if name:
    st.write(f'Hello {name}!')