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| import streamlit as st | |
| from flair.data import Sentence | |
| from flair.models import SequenceTagger | |
| import re | |
| import logging | |
| # Render Streamlit page | |
| st.title("Anonymise your text!") | |
| st.markdown( | |
| "This mini-app anonymises text using Bert. You can find the code on [GitHub(WIP)](#)" | |
| ) | |
| # Configure logger | |
| logging.basicConfig(format="\n%(asctime)s\n%(message)s", level=logging.INFO, force=True) | |
| # # Define functions | |
| def anonymise_text(text: str, metadata: str = "", white_listed_words: str = ""): | |
| """anonymise text""" | |
| if st.session_state.n_requests >= 5: | |
| st.session_state.text_error = "Too many requests. Please wait a few seconds before anonymising more text." | |
| logging.info(f"Session request limit reached: {st.session_state.n_requests}") | |
| st.session_state.n_requests = 1 | |
| return | |
| st.session_state.text = "" | |
| st.session_state.text_error = "" | |
| if not text: | |
| st.session_state.text_error = "Please enter your text" | |
| return | |
| with text_spinner_placeholder: | |
| with st.spinner("Please wait while your text is being anonymised..."): | |
| # flagged = openai.moderate(prompt) | |
| # if flagged: | |
| # st.session_state.text_error = "Input flagged as inappropriate." | |
| # logging.info(f"Topic: {topic}{mood_output}{style_output}\n") | |
| # return | |
| # else: | |
| # load tagger | |
| tagger = SequenceTagger.load("flair/ner-english-large") | |
| sentence = Sentence(text) | |
| # predict NER tags | |
| tagger.predict(sentence) | |
| # iterate over entities and redact | |
| enitities=[e.text for e in sentence.get_spans('ner')] | |
| regex = re.compile('|'.join(map(re.escape, enitities))) | |
| text_anon = regex.sub("<PID>", text) | |
| st.session_state.text_error = "" | |
| st.session_state.n_requests += 1 | |
| st.session_state.text_anon = text_anon | |
| logging.info( | |
| f"text: {text}{metadata}{white_listed_words}\n" | |
| f"text anonymised: {st.session_state.text_anon}" | |
| ) | |
| # def anonymise_text(text: str, metadata: str = "", white_listed_words: str = ""): | |
| # st.session_state.text_anon = "this is anonymised" | |
| if "text" not in st.session_state: | |
| st.session_state.text = "" | |
| if "text_error" not in st.session_state: | |
| st.session_state.text_error = "" | |
| if "text_anon" not in st.session_state: | |
| st.session_state.text_anon = "" | |
| if "n_requests" not in st.session_state: | |
| st.session_state.n_requests = 0 | |
| text = st.text_input(label="Text to be anonymised", placeholder="Write your text here") | |
| metadata = st.text_input( | |
| label="Data to be redacted (optional)", | |
| placeholder="inspirational", | |
| ) | |
| white_listed_words = st.text_input( | |
| label="Data to be ignored (optional)", | |
| placeholder="inspirational", | |
| ) | |
| # button return true when clicked | |
| anonymise_now = st.button( | |
| label="Anonymise text", | |
| type="primary", | |
| on_click=anonymise_text, | |
| args=(text, metadata, white_listed_words), | |
| ) | |
| text_spinner_placeholder = st.empty() | |
| if st.session_state.text_error: | |
| st.error(st.session_state.text_error) | |
| if st.session_state.text_anon: | |
| st.markdown("""---""") | |
| st.text_area(label="Text anonymised", value=st.session_state.text_anon, height=100) |