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import google.generativeai as genai | |
import streamlit as st | |
from dotenv import load_dotenv | |
import os | |
def get_llm(): | |
load_dotenv() | |
api_key = os.environ.get('API_KEY') | |
genai.configure(api_key=api_key) | |
model = genai.GenerativeModel( | |
'gemini-pro', generation_config={"temperature": temperature}) | |
return model | |
st.title("Medium.com Blog Generator π§π»βπ»!!!") | |
def get_genai_response(prompt, question): | |
response = model.generate_content([prompt, question]) | |
# print(response.text) | |
return response.text | |
prompt = """ | |
Imagine you're a friendly expert at a local library. Tailor your explanation to a general audience who might have some curiosity about the topic but no prior in-depth knowledge. Make the information engaging and informative, and keep in mind the best practices for writing on Medium.com""" | |
topic = st.text_input("Topic") | |
creativity_arr = ["High Accuracy", | |
"Balanced Accuracy & Creativity", "High Creativity "] | |
creativity = st.selectbox("Choose creativity level:", creativity_arr) | |
if creativity == "High Accuracy": | |
temperature = 0.1 | |
elif creativity == "Balanced Accuracy & Creativity": | |
temperature = 0.5 | |
else: | |
temperature = 0.8 | |
submit_button = st.button("Submit") | |
model = get_llm() | |
if submit_button: | |
st.header("Response") | |
with st.spinner(text="Fetching response from LLM..."): | |
text = get_genai_response( | |
prompt, topic) | |
st.write(text) | |