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import streamlit as st | |
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
from peft import PeftModel | |
# Loading LED IN Model | |
base_model = "nsi319/legal-led-base-16384" | |
led = AutoModelForSeq2SeqLM.from_pretrained(base_model) | |
adapter_model_in = f"Legal-LED_IN_ABS" | |
led_in = PeftModel.from_pretrained(led, adapter_model_in) | |
led_in_tokenizer = AutoTokenizer.from_pretrained(base_model) | |
# Generating Summary | |
def summarize(model, tokenizer, text): | |
input_tokenized = tokenizer.encode(text, return_tensors='pt', max_length=4096, truncation=True) | |
summary_ids = model.generate(input_tokenized, num_beams=4, length_penalty=0.1, min_length=32, max_length=256) | |
summary = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=False) for g in summary_ids][0] | |
return summary | |
# Reading Txt File | |
def read_txt_file(file): | |
text = file.read().decode('utf-8') | |
return text | |
st.set_page_config(page_title="Legal AI Summarizer", page_icon="img.png") | |
title = "Legal AI Summarizer" | |
col1, col2 = st.columns([1,7]) | |
with col1: | |
st.image("img.png") | |
with col2: st.title(title) | |
st.write("Stuck with long legal documents? Our AI summarizer can help! Just copy-paste the text or upload a .txt file, and it will give you a quick and easy summary in plain English, so you can understand the key points without all the legalese.") | |
if "user_text" not in st.session_state: | |
st.session_state.user_text = "" | |
upload_file = st.file_uploader("Upload a .txt file", type="txt") | |
if upload_file is not None: | |
user_text = read_txt_file(upload_file) | |
else: | |
user_text = st.text_area("Paste your legal document here:", value=st.session_state.user_text, height=300) | |
if st.button("Generate Summary"): | |
with st.spinner("Generating summary..."): | |
try: | |
summary_text = summarize(led_in, led_in_tokenizer, user_text) | |
st.session_state.user_text = user_text | |
st.write("") | |
st.success(summary_text) | |
print(summary_text) | |
except Exception as e: | |
st.error(f"An error occurred: {e}") |