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"""
import os
import keyfile
import warnings
import streamlit as st
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain.schema import HumanMessage, SystemMessage, AIMessage
# Ignore warnings
warnings.filterwarnings("ignore")
# Streamlit settings
st.set_page_config(page_title="Magical Healer")
st.header("Welcome, What help do you need?")
# Initialize session state for messages
if "sessionMessages" not in st.session_state:
st.session_state["sessionMessages"] = [
SystemMessage(content="You are a medieval magical healer known for your peculiar sarcasm")
]
# Set Google API key
os.environ["GOOGLE_API_KEY"] = keyfile.GOOGLEKEY
# Initialize the model
llm = ChatGoogleGenerativeAI(
model="gemini-1.5-pro",
temperature=0.7,
convert_system_message_to_human=True
)
# Response function
def load_answer(question):
# 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)
# 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")
return str(input_text)
# Main implementation
user_input = get_text()
submit = st.button("Generate")
if submit and user_input:
response = load_answer(user_input)
st.subheader("Answer:")
st.write(response)
"""
import os
import keyfile
import warnings
import streamlit as st
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain.schema import HumanMessage, SystemMessage, AIMessage
from streamlit_extras.add_vertical_space import add_vertical_space
# Ignore warnings
warnings.filterwarnings("ignore")
# Streamlit settings
st.set_page_config(page_title="🌿 Magical Healer", page_icon="🧙♀️", layout="centered")
st.markdown("<h1 style='text-align: center; color: #4B0082;'>Welcome to the Magical Healer 🧙♀️🌿</h1>", unsafe_allow_html=True)
st.write("### How can I assist with your ailments or worries? 🧪✨")
# Add some vertical space
add_vertical_space(2)
# Initialize session state for messages with an introductory message
if "sessionMessages" not in st.session_state:
st.session_state["sessionMessages"] = [
SystemMessage(content="You are a medieval magical healer known for your peculiar sarcasm.")
]
# Set Google API key
os.environ["GOOGLE_API_KEY"] = keyfile.GOOGLEKEY
# Initialize the model
llm = ChatGoogleGenerativeAI(
model="gemini-1.5-pro",
temperature=0.7,
convert_system_message_to_human=True
)
# Define a function to create chat bubbles
def chat_bubble(message, is_user=True):
align = 'right' if is_user else 'left'
color = '#ADD8E6' if is_user else '#E6E6FA'
border_radius = '25px' if is_user else '25px'
st.markdown(f"""
<div style="text-align: {align}; padding: 10px;">
<span style="display: inline-block; padding: 10px; background-color: {color}; color: black;
border-radius: {border_radius}; max-width: 70%;">
{message}
</span>
</div>
""", unsafe_allow_html=True)
# Response function
def load_answer(question):
# 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)
# 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", placeholder="Type your question here...")
return str(input_text)
# Main implementation
user_input = get_text()
submit = st.button("🌟 Get a Magical Answer 🌟")
if submit and user_input:
# Display the user's question
chat_bubble(user_input, is_user=True)
# Load the response and display it as a chat bubble
response = load_answer(user_input)
chat_bubble(response, is_user=False)
# Background styling and layout enhancements
st.markdown("""
<style>
.stApp {
background: linear-gradient(to right, #FFEFBA, #FFFFFF);
color: #4B0082;
font-family: Arial, sans-serif;
}
input[type="text"] {
padding: 8px;
border: 2px solid #4B0082;
border-radius: 15px;
outline: none;
}
button {
background-color: #4B0082;
color: white;
border-radius: 15px;
}
</style>
""", unsafe_allow_html=True)
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