import streamlit as st import json import requests from transformers import pipeline import wikipediaapi # Load historical figures and tutor topics from Wikipedia dynamically wiki_wiki = wikipediaapi.Wikipedia("en") # Load local AI model (Mistral-7B or Llama-2) chat_model = pipeline("text-generation", model="mistralai/Mistral-7B-Instruct-v0.1") def get_wikipedia_summary(name): 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): 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}:" response = chat_model(prompt, max_length=200, truncation=True) return response[0]["generated_text"].split("User:")[0].strip() 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) # Instructions for Deployment st.sidebar.subheader("Deployment Instructions") st.sidebar.markdown("1. Ensure `transformers` and `wikipedia-api` libraries are installed.") st.sidebar.markdown("2. Run `streamlit run chatbot.py` locally.") st.sidebar.markdown("3. Deploy on [Hugging Face Spaces](https://huggingface.co/spaces) or Replit.")