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import streamlit as st | |
#from langchain.llms import OpenAI | |
from langchain_community.llms import OpenAI | |
st.title("🔗 Marketing Brand Guidelines Generator") | |
def generate_linkedin_post(topic): | |
# Enhanced prompt with additional context for better post generation | |
prompt = ( | |
"Imagine you are a brand marketing designer, expert in this particular field. " | |
"The user is going to provide some insights about the user persona, customer persona. " | |
f"And right now we are giving a very brief, which is customer for {topic} " | |
"And then the emotion that we want to generate for this particular customer persona is rich, affordable, luxury kind of a brand. " | |
"As an output, what we want is recommend the brand guidelines or a document where I understand the colors for this particular " | |
"client persona, the typography of it, as much detail as possible. Give colors, two, three options in combinations, " | |
"give the exact code that is required, the shapes that can be associated with this brand to play around with it, and " | |
"some hints of what logos resonate with this kind of audience. Also, some basic pricing ranges for an Indian context." | |
) | |
llm = OpenAI(temperature=0.7, openai_api_key=st.secrets["OPENAI_API_KEY"]) | |
response = llm(prompt) | |
return response | |
with st.form("my_form"): | |
topic = st.text_area("Enter the Customer Product") | |
submitted = st.form_submit_button("Generate Brand") | |
if submitted and topic: | |
post = generate_linkedin_post(topic) | |
st.info(post) | |
elif submitted and not topic: | |
st.error("Please enter a topic to generate a brand guidelines.") |