Update app.py

app.py

@@ -1,33 +1,24 @@
 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)}"
+# Added simple character response system
+def get_historical_response(context, user_input):
+    # Basic response templates based on context
+    if "born" in context.lower():
+        return f"Indeed, as someone who experienced those times, I can tell you that {user_input}"
+    elif "died" in context.lower():
+        return f"In my time, we would have approached this by {user_input}"
+    else:
+        return f"Based on my experiences, I would say that {user_input}"
 
 st.title("Historical Figures Chat")
+st.write("Chat with historical figures using Wikipedia information!")
+
 person_name = st.text_input("Enter historical figure name:")
 
 if "messages" not in st.session_state:
@@ -44,7 +35,12 @@ if user_input := st.chat_input("Message..."):
     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)
+    with st.spinner("Researching..."):
+        context = get_wikipedia_summary(person_name)
+        if context:
+            st.write("Historical Context:", context)
+            response = get_historical_response(context, user_input)
+            st.session_state.messages.append({"role": "assistant", "content": response})
+            st.chat_message("assistant").write(response)
+        else:
+            st.error(f"Could not find information about {person_name}")