import streamlit as st
import requests
import wikipediaapi
import os  # For accessing environment variables

# Securely fetch Hugging Face API key from environment variables
HUGGINGFACE_API_KEY = os.getenv("HUGGINGFACE_API_KEY")

if not HUGGINGFACE_API_KEY:
    st.error("⚠️ API Key Missing! Please add your Hugging Face API key as a secret in your Space settings.")
    st.stop()

# Set up Wikipedia API
USER_AGENT = "HistoricalChatbot/1.0 (Contact: your-email@example.com)"
wiki_wiki = wikipediaapi.Wikipedia("en", headers={"User-Agent": USER_AGENT})

def get_wikipedia_summary(name):
    """Fetch summary from Wikipedia"""
    page = wiki_wiki.page(name)
    return page.summary if page.exists() else "Sorry, I couldn't find information on that historical figure."

def chat_with_ai(person_name, user_input):
    """Query Hugging Face API for response"""
    context = get_wikipedia_summary(person_name)
    prompt = f"You are {person_name}. Based on this historical information: {context}\\n\\nUser: {user_input}\\n{person_name}:"
    
    API_URL = "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.1"
    headers = {"Authorization": f"Bearer {HUGGINGFACE_API_KEY}"}

    response = requests.post(API_URL, headers=headers, json={"inputs": prompt})
    
    if response.status_code == 200:
        return response.json()[0]["generated_text"]
    else:
        return "I'm sorry, but I couldn't generate a response at this time."

# Streamlit UI
st.title("Educational Chatbot")
mode = st.sidebar.selectbox("Select Chat Mode", ["Chat with Historical Figures", "Study with a Tutor"])

if mode == "Chat with Historical Figures":
    person_name = st.text_input("Enter the name of a historical figure:")
    if person_name:
        st.write(f"You are now chatting with **{person_name}**!")

elif mode == "Study with a Tutor":
    topic = st.sidebar.selectbox("Choose a Study Topic", ["Mathematics", "History", "Physics"])
    st.write(f"You are now studying **{topic}**!")

# Chat input
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"])

user_input = st.chat_input("Type your message here...")

if user_input and mode == "Chat with Historical Figures" and person_name:
    st.session_state.messages.append({"role": "user", "content": user_input})
    st.chat_message("user").write(user_input)
    response = chat_with_ai(person_name, user_input)
    st.session_state.messages.append({"role": "assistant", "content": response})
    st.chat_message("assistant").write(response)

# Deployment instructions
st.sidebar.subheader("Deployment Instructions")
st.sidebar.markdown("1. Add the API key as a secret in Hugging Face Spaces.")
st.sidebar.markdown("2. Run `streamlit run app.py` locally or deploy on Hugging Face Spaces.")