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import streamlit as st | |
from intent_classifier.model import IntentClassifier | |
from consts import FLAN_T5_SMALL, FLAN_T5_BASE | |
def load_model(model_name="Serj/intent-classifier", device=None): | |
st.write(f"model path: {model_name}") | |
m = IntentClassifier(model_name=model_name, device=device) | |
return m | |
model = load_model() | |
# text = "Hey, I want to stop my subscription. Can I do that?" | |
text = "I was expecting my card to get this week and I'm wandering why didn't I receive it yet?" | |
input = st.text_area("text", value=text) | |
prompt_options_values = " # how do I locate my card # my card hasn't arrived yet # I would like to reactivate my card # where do I link my card? # How do I re add my card? # how do I add the card to my account? # status of the card order " | |
prompt_options = st.text_area("prompt_options", value=prompt_options_values) | |
is_clicked = st.button("Submit") | |
if is_clicked: | |
output = model.structured_predict(input, prompt_options, print_input=True) | |
st.write(output) | |