File size: 3,375 Bytes
a630adb 322907f 1fb5170 a630adb 197a2d3 a630adb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 |
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="🌿 ArchanaCare 🧙♀️", page_icon="🧙♀️", layout="centered")
st.markdown("<h1 style='text-align: center; color: #4B0082;'>Welcome to ArchanaCare 🌿✨</h1>", unsafe_allow_html=True)
st.markdown("<h3 style='color: #003366;'>How can I assist with your ailments or worries today? 🧪💫</h3>", unsafe_allow_html=True)
# Adding vertical space without streamlit_extras
st.markdown("<br><br>", unsafe_allow_html=True)
# 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)
|