Upload app.py

app.py

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+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. Rename `chatbot.py` to `app.py` for Hugging Face Spaces.")
+st.sidebar.markdown("3. Run `streamlit run app.py` locally.")
+st.sidebar.markdown("4. Deploy on [Hugging Face Spaces](https://huggingface.co/spaces) or Replit.")