app.py

import spacy
import json
from datetime import datetime
import streamlit as st
import pandas as pd

nlp = spacy.load('la_core_web_lg')

def tokenize_with_spacy(text):
    doc = nlp(text)
    return [token.text for token in doc]

def annotate_text(segmented_text):
    annotated_tokens = []
    for token in segmented_text:
        doc = nlp(token)
        annotated_token = {
            'token': token,
            'pos': str(doc[0].pos_),
            'lemma': str(doc[0].lemma_),
            'aspect': ', '.join(doc[0].morph.get("Aspect", default=[""])),
            'tense': ', '.join(doc[0].morph.get("Tense", default=[""])),
            'verbForm': ', '.join(doc[0].morph.get("VerbForm", default=[""])),
            'voice': ', '.join(doc[0].morph.get("Voice", default=[""])),
            'mood': ', '.join(doc[0].morph.get("Mood", default=[""])),
            'number': ', '.join(doc[0].morph.get("Number", default=[""])),
            'person': ', '.join(doc[0].morph.get("Person", default=[""])),
            'case': ', '.join(doc[0].morph.get("Case", default=[""])),
            'gender': ', '.join(doc[0].morph.get("Gender", default=[""]))
        }
        annotated_tokens.append(annotated_token)
    return annotated_tokens

def save_annotations_as_json(annotated_text, filename):
    with open(filename, 'w', encoding='utf-8') as json_file:
        json.dump(annotated_text, json_file, ensure_ascii=False, indent=4)

st.title("Annotation Tool")
text = st.text_area("Text")
if st.button("Annotate"):
    if text:
        segmented_text = tokenize_with_spacy(text)
        annotated_text = annotate_text(segmented_text)
        st.subheader("Segmented Text:")
        st.write(segmented_text)
        st.subheader("Annotated Text:")

        # Create a DataFrame from the annotated text
        df = pd.DataFrame(annotated_text)
        st.dataframe(df)

        if st.button("Save Modifications as JSON"):
            save_annotations_as_json(df.to_dict(orient='records'), 'annotations.json')
            st.success("Annotations saved as annotations.json")

    else:
        st.warning("Please enter some text.")