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import streamlit as st | |
import openai | |
#streamlit run main.py | |
# import os | |
# os.environ.getattribute("openai.api_key") | |
header = st.container() | |
about = st.container() | |
model_output = st.container() | |
with header: | |
st.title('RHYME THYME') | |
#st.text('This this bot-bop-shop uses Artificail Ingredients \ | |
#(AI) to produce natural flavors.') | |
with model_output: | |
st.header('Half-baked Takes:') | |
sel_col, disp_col = st.columns(2) | |
sel_col.subheader('Input ideas') | |
#input_poem = sel_col.selectbox('What type of poem do you want to write?', options=['limerick', 'haiku', 'sonnet', 'acrostic', 'villanelle', 'ode', 'elegy', 'ballad', 'couplet', 'tercet', 'quatrain', 'cinquan', 'sestet']) | |
input_word1 = sel_col.text_input('Input a word to use in the poem:') | |
input_word2 = sel_col.text_input('Input another word to use in the poem:') | |
# This is the NLP model | |
def generate_poem(input_word1, input_word2): | |
# Use GPT-3 to generate a limerick based on the user's input word | |
prompt = f"Write a limerick in AABBA rhyme scheme about {input_word1} and '{input_word2}':" | |
completions = openai.Completion.create( | |
engine="text-davinci-002", | |
prompt=prompt, | |
max_tokens=1024, | |
n=1, | |
stop=None, | |
temperature=0.5, | |
) | |
# Return the generated limerick | |
return completions.choices[0].text | |
limerick = generate_poem(input_word1.lower(), input_word2.lower()) | |
# This is where the results are displayed on the app | |
disp_col.subheader('Limerick output') | |
disp_col.write(limerick) | |