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# import os
# os.environ["STREAMLIT_BROWSER_GATHER_USAGE_STATS"] = "false"
# import streamlit as st
# import spacy
# import benepar
# from nltk import Tree
# import nltk
# # Setup NLTK and benepar
# nltk.download('punkt')
# benepar.download('benepar_en3')
# nlp = spacy.load("en_core_web_sm")
# if "benepar" not in nlp.pipe_names:
# nlp.add_pipe("benepar", config={"model": "benepar_en3"})
# st.set_page_config(page_title="Syntax Parser Comparison Tool", layout="wide")
# st.title("🌐 Syntax Parser Comparison Tool")
# st.write("This tool compares Dependency Parsing, Constituency Parsing, and a simulated Abstract Syntax Representation (ASR).")
# sentence = st.text_input("Enter a sentence:", "John eats an apple.")
# if sentence:
# doc = nlp(sentence)
# sent = list(doc.sents)[0]
# col1, col2, col3 = st.columns(3)
# with col1:
# st.header("Dependency Parsing")
# for token in sent:
# st.write(f"{token.text} --> {token.dep_} --> {token.head.text}")
# st.code(" ".join(f"({token.text}, {token.dep_}, {token.head.text})" for token in sent))
# with col2:
# st.header("Constituency Parsing")
# tree = sent._.parse_string
# st.text(tree)
# st.code(Tree.fromstring(tree).pformat())
# with col3:
# st.header("Simulated ASR Output")
# st.write("Combining phrase structure with dependency head annotations:")
# for token in sent:
# if token.dep_ in ("nsubj", "obj", "det", "ROOT"):
# st.write(f"[{token.text}] - {token.dep_} --> {token.head.text} ({token.pos_})")
# st.markdown("_(ASR is simulated by combining POS tags, dependency heads, and phrase information.)_")
# st.code(" ".join(f"[{token.text}: {token.dep_} → {token.head.text}]({token.pos_})" for token in sent))
import streamlit as st
st.title("✅ Custom App Loaded")
st.write("If you can see this, your `streamlit_app.py` is correctly loaded by Hugging Face.")
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