Update streamlit_app.py

streamlit_app.py

@@ -1,49 +1,55 @@
-import os
-os.environ["STREAMLIT_BROWSER_GATHER_USAGE_STATS"] = "false"
+# 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
-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))
+
+st.title("✅ Custom App Loaded")
+st.write("If you can see this, your `streamlit_app.py` is correctly loaded by Hugging Face.")