import google.generativeai as genai
import streamlit as st
from dotenv import load_dotenv
import os


@st.cache_resource
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 🧑🏻‍💻!!!")


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)