Update streamlit_app.py

streamlit_app.py

@@ -1,55 +1,49 @@
-# 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 os
+os.environ["STREAMLIT_BROWSER_GATHER_USAGE_STATS"] = "false"
 
 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.")
+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))