app.py

import streamlit as st
import wikipediaapi
import requests

API_URL = "https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta"
headers = {"Authorization": f"Bearer {st.secrets['HUGGINGFACE_TOKEN']}"}

@st.cache_data
def get_wikipedia_summary(name):
    wiki = wikipediaapi.Wikipedia('en')
    page = wiki.page(name)
    return page.summary if page.exists() else None

def query_model(payload):
    response = requests.post(API_URL, headers=headers, json=payload)
    return response.json()

def chat_with_ai(person_name, user_input):
    context = get_wikipedia_summary(person_name)
    if not context:
        return f"Could not find information about {person_name}"
    
    prompt = f"You are {person_name}. Context: {context}\n\nUser: {user_input}\n{person_name}:"
    try:
        response = query_model({"inputs": prompt})
        return response[0]["generated_text"].split("User:")[0].strip()
    except Exception as e:
        return f"Error: {str(e)}"

st.title("Historical Figures Chat")
person_name = st.text_input("Enter historical figure name:")

if "messages" not in st.session_state:
    st.session_state.messages = []

for msg in st.session_state.messages:
    st.chat_message(msg["role"]).write(msg["content"])

if user_input := st.chat_input("Message..."):
    if not person_name:
        st.error("Please enter a historical figure's name")
        st.stop()
        
    st.session_state.messages.append({"role": "user", "content": user_input})
    st.chat_message("user").write(user_input)
    
    with st.spinner("Thinking..."):
        response = chat_with_ai(person_name, user_input)
        st.session_state.messages.append({"role": "assistant", "content": response})
        st.chat_message("assistant").write(response)