Update app.py

app.py

@@ -1,60 +1,59 @@
-# Generics
 import os
 import keyfile
 import warnings
 import streamlit as st
-warnings.filterwarnings("ignore")
-
-# Langchain packages
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain.schema import HumanMessage, SystemMessage, AIMessage
 
-# First message that will pop on the screen
-st.set_page_config(page_title = "Magical Healer")
+# Ignore warnings
+warnings.filterwarnings("ignore")
+
+# Streamlit settings
+st.set_page_config(page_title="Magical Healer")
 st.header("Welcome, What help do you need?")
 
-# initializing the sessionMessages
-if "sessionMessages" not in st.session_state:
-    st.session_state["sessionMessages"] = []
-# General Instruction
+# Initialize session state for messages
 if "sessionMessages" not in st.session_state:
-    st.session_state.sessionMessage = [
-         SystemMessage(content = "You are a medieval magical healer known for your peculiar sarcasm")
+    st.session_state["sessionMessages"] = [
+        SystemMessage(content="You are a medieval magical healer known for your peculiar sarcasm")
     ]
 
-# Configuring the key
+# Set Google API key
 os.environ["GOOGLE_API_KEY"] = keyfile.GOOGLEKEY
 
-# Create a model
+# Initialize the model
 llm = ChatGoogleGenerativeAI(
     model="gemini-1.5-pro",
     temperature=0.7,
-    convert_system_message_to_human= True
+    convert_system_message_to_human=True
 )
 
-
 # Response function
 def load_answer(question):
-    # This is code, where we are adding new message to the model
-    st.session_state.sessionMessages.append(HumanMessage(content = question))
-    # We will get output from the model
+    # Add user question to the message history
+    st.session_state.sessionMessages.append(HumanMessage(content=question))
+    
+    # Get AI's response
     assistant_answer = llm.invoke(st.session_state.sessionMessages)
-    # Appending the assistance answer in conversation
-    st.session_state.sessionMessages.append(AIMessage(content = assistant_answer))
-
-    return assistant_answer.content
-
-# User message
+    
+    # Append AI's answer to the session messages
+    if isinstance(assistant_answer, AIMessage):
+        st.session_state.sessionMessages.append(assistant_answer)
+        return assistant_answer.content
+    else:
+        st.session_state.sessionMessages.append(AIMessage(content=assistant_answer))
+        return assistant_answer
+
+# Capture user input
 def get_text():
-    input_text = st.text_input("You: ", key = input)
+    input_text = st.text_input("You: ", key="input")
     return str(input_text)
 
-
-# Implementation
+# Main implementation
 user_input = get_text()
 submit = st.button("Generate")
 
-if submit:
-    resp = load_answer(user_input)
-    st.subheader("Answer: ")
-    st.write(resp, key = 1)
+if submit and user_input:
+    response = load_answer(user_input)
+    st.subheader("Answer:")
+    st.write(response)