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import subprocess
import torch
import streamlit as st
from streamlit import session_state as state
import streamlit_ace
import pipline
if "app" not in state:
state.app = "model"
state.out = ""
in_area = st.container()
out_area = st.container()
in_area.title("Streamlit using Huggingface Transformers and langchain")
out_area.header("Output")
def __run_TTI():
out_area.markdown(":green[Running pipline]")
out_area.text(pipline.chain_TI(state.input_text))
def __run_CC():
out_area.markdown(":green[Running pipline]")
words = state.input_text.rstrip().split()
if len(words) != 2:
out_area.error("Please enter two terms")
else:
out_area.markdown(":green[Running pipline]")
out_area.text(pipline.chain_CC({"term1": words[0], "term2": words[1]}))
in_area.text_area("input_text", key="input_text")
tti_button , cc_button = in_area.columns(2)
tti_button.button("What are you trying to imply?", on_click=__run_TTI)
cc_button.button("What is the connection between the two terms?", on_click=__run_CC)
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