Update app.py

app.py

@@ -27,6 +27,20 @@ model = AutoModelForTokenClassification.from_pretrained("AhmedTaha012/finance-ne
 # torch.compile(model)
 # torch.compile(model)
 nlpPipe = pipeline("ner", model=model, tokenizer=tokenizer, grouped_entities=True)
+
+
+
+if "disabled" not in st.session_state:
+    st.session_state["disabled"] = False
+
+def disable():
+    st.session_state["disabled"] = True
+
+st.text_input(
+    "Enter some text", 
+    disabled=st.session_state.disabled, 
+    on_change=disable
+)
 def getSpeakers(data):
     if "Speakers" in data:
         return "\n".join([x for x in data.split("Speakers")[-1].split("\n") if "--" in x])
@@ -245,8 +259,10 @@ st.header("Transcript Analysis", divider='rainbow')
 mainTranscript = st.text_area("Enter the transcript:", height=100)
 doc = nlp(mainTranscript)
 sentences = [sent.text for sent in doc.sents]
-quarter = st.text_input('Enter your quarter', '')
-year = st.text_input('Enter your year', '')
+quarter = st.text_input('Enter your quarter', '',disabled=st.session_state.disabled, 
+    on_change=disable)
+year = st.text_input('Enter your year', '',disabled=st.session_state.disabled, 
+    on_change=disable)
 if st.button("Analyze"):
     transcript=replace_abbreviations(mainTranscript)
     transcript=replace_abbreviations(transcript)