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# 1) MUST be the FIRST command
# -----------------------------------------------------
import streamlit as st
st.set_page_config(page_title="ClauseWise", layout="wide")
# -----------------------------------------------------
# 2) All other imports AFTER set_page_config
# -----------------------------------------------------
from pypdf import PdfReader
from docx import Document
import re
from multilingual import UI_TEXT, translate_text
from backup_features import (
extract_entities,
extract_clauses,
get_risks,
fairness_score,
alternative_clauses
)
from transformers import T5Tokenizer, T5ForConditionalGeneration
# -----------------------------------------------------
# 3) Load model
# -----------------------------------------------------
@st.cache_resource
def load_chat_model():
tokenizer = T5Tokenizer.from_pretrained("t5-small")
model = T5ForConditionalGeneration.from_pretrained("t5-small")
return tokenizer, model
tokenizer, chat_model = load_chat_model()
# -----------------------------------------------------
# 4) Chat response function
# -----------------------------------------------------
def chat_response(user_msg, lang):
msg = user_msg.lower()
# Store conversation
if "history" not in st.session_state:
st.session_state["history"] = []
# Basic rule-based NDA responses
if "nda" in msg:
reply = "This NDA helps protect confidential information between parties."
elif "duration" in msg or "how long" in msg:
reply = "NDAs commonly last 1β5 years depending on the agreement."
elif "penalty" in msg or "violate" in msg:
reply = "Penalties depend on governing law and agreement provisions."
elif "can i work" in msg or "competition" in msg:
reply = "NDAs do NOT restrict employment. That is a Non-Compete Agreement."
elif "termination" in msg:
reply = "Termination clauses define when the NDA ends and obligations after that."
else:
reply = "I can help with NDA clauses, risks, obligations, confidentiality."
reply += "\n\nβ οΈ Educational only, not legal advice."
return translate_text(reply, lang)
# -------------------------------
# Utility Functions
# -------------------------------
def is_nda(text):
return "nda" in text.lower() or "non-disclosure" in text.lower()
def read_pdf(file):
reader = PdfReader(file)
return "\n".join(page.extract_text() for page in reader.pages)
def read_docx(file):
doc = Document(file)
return "\n".join(p.text for p in doc.paragraphs)
def read_txt(file):
return file.read().decode("utf-8")
# -------------------------------
# Streamlit UI
# -------------------------------
st.set_page_config(page_title="ClauseWise", layout="wide")
# Language Selector
lang = st.sidebar.selectbox("π Language", ["en", "hi", "ta", "te", "kn"])
# Title
st.title("π ClauseWise β Multilingual NDA Analyzer")
uploaded = st.file_uploader(UI_TEXT["upload_title"][lang], type=["pdf", "txt", "docx"])
if uploaded:
ext = uploaded.name.split(".")[-1]
if ext == "pdf":
text = read_pdf(uploaded)
elif ext == "txt":
text = read_txt(uploaded)
elif ext == "docx":
text = read_docx(uploaded)
else:
st.error(UI_TEXT["error_not_nda"][lang])
st.stop()
if not is_nda(text):
st.error(UI_TEXT["error_not_nda"][lang])
st.stop()
st.success(UI_TEXT["success_nda"][lang])
tabs = st.tabs([
UI_TEXT["tab_clauses"][lang],
UI_TEXT["tab_risks"][lang],
UI_TEXT["tab_fairness"][lang],
UI_TEXT["tab_entities"][lang],
UI_TEXT["tab_alternatives"][lang],
UI_TEXT["tab_chat"][lang]
])
# -----------------------------
# TAB 1 β CLAUSE SIMPLIFICATION
# -----------------------------
with tabs[0]:
st.header(UI_TEXT["clause_simplify"][lang])
clauses = extract_clauses(text)
mode = st.radio(UI_TEXT["choose_mode"][lang],
[UI_TEXT["eli5"][lang],
UI_TEXT["simple"][lang],
UI_TEXT["pro"][lang]])
for c in clauses:
st.subheader(c["title"])
if mode == UI_TEXT["eli5"][lang]:
st.write(translate_text(c["eli5"], lang))
elif mode == UI_TEXT["simple"][lang]:
st.write(translate_text(c["simple"], lang))
else:
# β
FIXED SYNTAX ERROR HERE
st.write(translate_text(c["pro"], lang))
# -----------------------------
# TAB 2 β RISKS
# -----------------------------
with tabs[1]:
st.header(UI_TEXT["risk_title"][lang])
risks = get_risks(text)
for r in risks:
st.error("β οΈ " + translate_text(r, lang))
# -----------------------------
# TAB 3 β FAIRNESS
# -----------------------------
with tabs[2]:
st.header(UI_TEXT["fairness_title"][lang])
score = fairness_score(text)
st.write(f"**{UI_TEXT['your_position'][lang]}:** {score['user']}%")
st.write(f"**{UI_TEXT['company_position'][lang]}:** {score['company']}%")
st.progress(score["user"] / 100)
# -----------------------------
# TAB 4 β ENTITIES
# -----------------------------
with tabs[3]:
st.header(UI_TEXT["entities_title"][lang])
ents = extract_entities(text)
st.write("**Parties:**", ents["parties"])
st.write("**Dates:**", ents["dates"])
st.write("**Amounts:**", ents["money"])
# -----------------------------
# TAB 5 β ALTERNATIVES
# -----------------------------
with tabs[4]:
st.header(UI_TEXT["alt_title"][lang])
alts = alternative_clauses(text)
for a in alts:
st.info(translate_text(a, lang))
# -----------------------------
# TAB 6 β LEGAL CHAT
# -----------------------------
with tabs[5]:
st.header(UI_TEXT["chat_title"][lang])
if "chat_history" not in st.session_state:
st.session_state.chat_history = []
for msg in st.session_state.chat_history:
st.chat_message(msg["role"]).write(msg["text"])
user_msg = st.chat_input(UI_TEXT["chat_placeholder"][lang])
if user_msg:
st.session_state.chat_history.append({"role": "user", "text": user_msg})
st.chat_message("user").write(user_msg)
bot_reply = chat_response(user_msg, lang)
st.session_state.chat_history.append({"role": "assistant", "text": bot_reply})
st.chat_message("assistant").write(bot_reply)
# Footer Disclaimer
st.info("β οΈ ClauseWise provides **educational legal insights only** β this is **NOT legal advice**.")
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