Update
Browse files- app.py +75 -29
- gradio_app.py +29 -0
app.py
CHANGED
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#
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import time
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import errant
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import streamlit as st
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from flair.data import Sentence
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from flair.models import SequenceTagger
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from highlighter import show_highlights
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checkpoints = [
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"qanastek/pos-french",
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]
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@st.cache(suppress_st_warning=True, allow_output_mutation=True)
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def get_model(model_name):
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# Load the model
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return SequenceTagger.load(model_name)
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@st.cache(suppress_st_warning=True, allow_output_mutation=True)
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def get_annotator(lang: str):
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return errant.load(lang)
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def main():
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st.title("🥖 French-Part-Of-Speech-Tagging")
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annotator = get_annotator("fr")
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checkpoint = st.selectbox("Choose model", checkpoints)
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model = get_model(checkpoint)
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default_text = "George Washington est allé à Washington"
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input_text = st.text_area(
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label="Original text",
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value=default_text,
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)
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start = None
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if st.button("🧠 Compute"):
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start = time.time()
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with st.spinner("Search for Part-Of-Speech Tags 🔍"):
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# Build Sentence
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sentence = Sentence(input_text)
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# predict tags
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model.predict(sentence)
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# print predicted pos tags
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result = sentence.to_tagged_string()
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try:
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show_highlights(annotator, input_text, result)
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st.write("")
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st.success(result)
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except Exception as e:
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st.error("Some error occured!" + str(e))
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st.stop()
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st.write("---")
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st.markdown(
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"Built by [Yanis Labrak](https://www.linkedin.com/in/yanis-labrak-8a7412145/) 🚀"
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)
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st.markdown(
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"_Source code made with [FlairNLP](https://github.com/flairNLP/flair)_"
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)
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if start is not None:
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st.text(f"prediction took {time.time() - start:.2f}s")
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if __name__ == "__main__":
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main()
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gradio_app.py
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@@ -0,0 +1,29 @@
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import gradio as gr
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from flair.data import Sentence
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from flair.models import SequenceTagger
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# Load the model
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model = SequenceTagger.load("qanastek/pos-french")
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def getPartOfSpeechFR(content):
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# George Washington est allé à Washington
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sentence = Sentence(content)
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# predict tags
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model.predict(sentence)
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# print predicted pos tags
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res = sentence.to_tagged_string()
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return res
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iface = gr.Interface(
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title="🥖 French Part Of Speech Tagging",
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fn=getPartOfSpeechFR,
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inputs="textbox",
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outputs="textbox",
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)
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iface.launch()
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