import streamlit as st
from langchain_community.llms import OpenAI
from langchain_google_genai import ChatGoogleGenerativeAI

def main():
    st.title("Open AI or Gemini Options")

    # Radio
    st.header("Radio:")
    radio = st.radio("Radio", ["Open AI", "Gemini", "TBD"])
    st.write("Selected option:", radio)
    role = st.text_input("Enter Role")
    st.write("Entered role:", role)   
    
    # Slider
    st.header("Slider:")
    temp = st.slider("Temperature", min_value=0.0, max_value=1.0, value=0.7, step=0.1)
    st.write("Selected value:", temp)

    # Topic
    with st.form("my_form"):
        topic = st.text_area("Enter the topic for your LinkedIn post:")
        submitted = st.form_submit_button("Generate Post")
        if submitted and topic:
            post = generate_linkedin_post(topic, role, temp, radio)
            st.info(post)
        elif submitted and not topic:
            st.error("Please enter a topic to generate a post.")

def generate_linkedin_post(topic, role, temp, radio):
    prompt = (
        f"You as {role} Create a professional, engaging LinkedIn post about {topic}. "
        f"Adjust the tone and style based on a temperature of {temp}. " 
        "It should start with an attention grabbing hook based on audience pain. "
        "Then a line to agitate the user. This should be in the next line. "
        "The post should be concise, informative, and suitable for a professional audience. "
        "It should provide value, insights, or thought-provoking content related to the topic. "
        "And only contain 3 points."
    )
    if radio == "Open AI":
        llm = OpenAI(temperature=temp, openai_api_key=st.secrets["OPENAI_API_KEY"])
        response = llm(prompt)
        return response
            
    elif radio == "Gemini":
        llm = ChatGoogleGenerativeAI(model="gemini-pro",google_api_key =st.secrets["YOUR_GEMINI_API_KEY"])
        result = llm.invoke(prompt)
        return result.content

if __name__ == "__main__":
    main()