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import streamlit as st
from flair.data import Sentence
from flair.models import SequenceTagger
# Load the Flair model
model_path = "onurkeles/hamshetsnag-pos-tagger"
pos_tagger = SequenceTagger.load(model_path)
def tag_pos(text, detailed_output):
"""Tag parts of speech in a given text, with optional detailed output."""
sentence = Sentence(text)
pos_tagger.predict(sentence)
if detailed_output:
# Generate detailed information with tag values and probabilities
output = []
for label in sentence.get_labels():
output.append(
f"{label.data_point.text}: {label.value} ({label.score:.2f})"
)
return "\n".join(output)
else:
return sentence.to_tagged_string()
def write():
st.markdown("# Part-of-Speech Tagging for Hamshetsnag")
st.sidebar.header("POS Tagging")
st.write("Detect parts of speech in Hamshetsnag text using the fine-tuned model.")
# Sidebar for configurations
st.sidebar.subheader("Configurable Parameters")
# Detailed Output Checkbox
detailed_output = st.sidebar.checkbox(
"Detailed Output",
value=False,
help="If checked, output shows detailed tag information (probability scores, etc.).",
)
# Input text area
input_text = st.text_area("Enter a text:", height=100, value=st.session_state.get('input_text', 'Put example text here.'))
# Tag POS button with unique color styling
if st.button("Tag POS", key="tag_pos"):
with st.spinner('Processing...'):
output = tag_pos(input_text, detailed_output)
st.success(output)
# Example Sentences and Translations
example_sentences = [
("tuute acertsetser topoldetser aaav ta.", "Kâğıdı büzüştürdün attın. Oldu mu?"),
("Baran u Baden teran.", "Baran ve Bade koştu."),
("Onurun ennush nu İremin terchushe intzi shad kızdırmısh aaav.", "Onur'un düşüşü ve İrem'in koşuşu beni kızdırdı."),
]
st.write("## Example Sentences:")
for hamshetsnag, turkish in example_sentences:
if st.button(f"Use: {hamshetsnag}", key=hamshetsnag):
st.session_state['input_text'] = hamshetsnag # Update input text
break
st.markdown(f'<p style="font-size:12px;">(TR: {turkish})</p>', unsafe_allow_html=True) # Display translation in smaller font
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