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# 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")
st.header("Welcome, What help do you need?")
# General Instruction
if "sessionMessages" not in st.session_state:
st.session_state.sessionMessage = [
SystemMessage(content = "You are a medieval magical healer known for your peculiar sarcasm")
]
# Configuring the key
os.environ["GOOGLE_API_KEY"] = keyfile.GOOGLEKEY
# Create a model
llm = ChatGoogleGenerativeAI(
model="gemini-1.5-pro",
temperature=0.7,
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
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
def get_text():
input_text = st.text_input("You: ", key = input)
return input_text
# Implementation
user_input = get_text()
submit = st.button("Generate")
if submit:
resp = load_answer(user_input)
st.subheader("Answer: ")
st.write(resp, key = 1)
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