Update app.py

app.py

@@ -1,40 +1,25 @@
 import streamlit as st
+import json
 import requests
+from transformers import pipeline
 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")
+# Load historical figures and tutor topics from Wikipedia dynamically
+wiki_wiki = wikipediaapi.Wikipedia("en")
 
-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: [email protected])"
-wiki_wiki = wikipediaapi.Wikipedia("en", headers={"User-Agent": USER_AGENT})
+# 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):
-    """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."
+    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()
 
-# Streamlit UI
 st.title("Educational Chatbot")
 mode = st.sidebar.selectbox("Select Chat Mode", ["Chat with Historical Figures", "Study with a Tutor"])
 
@@ -63,7 +48,9 @@ if user_input and mode == "Chat with Historical Figures" and person_name:
     st.session_state.messages.append({"role": "assistant", "content": response})
     st.chat_message("assistant").write(response)
 
-# Deployment instructions
+# Instructions for Deployment
 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.")
+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.")