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parlbert-topic-german-test / app.py

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add upload todo for the future

d3adc06 over 1 year ago

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	from transformers import pipeline
	from transformers import AutoModelForSequenceClassification
	from transformers import AutoTokenizer
	import gradio as gr
	import torch
	import pandas as pd

	# Load trained model
	model = AutoModelForSequenceClassification.from_pretrained("chkla/parlbert-topic-german")
	tokenizer = AutoTokenizer.from_pretrained("bert-base-german-cased")
	pipeline_classification_topics = pipeline("text-classification", model="chkla/parlbert-topic-german", tokenizer="bert-base-german-cased", return_all_scores=False)

	def upload_file(files):
	file_paths = [file.name for file in files]
	return file_paths

	def predict_topic(input_text):
	prediction = pipeline_classification_topics(input_text)
	# predicted_label = prediction[0]['label']
	return prediction[0]['label']

	# Build Gradio interface
	with gr.Blocks() as demo:
	# Instruction
	gr.Markdown('''## Topic Modelling for German Political Texts''')

	# Input text to be reframed
	text = gr.Textbox(label="Text")
	# predictions = gr.outputs.Textbox(label="Topic")
	predictions = gr.Label()

	# Trigger button for topic prediction
	greet_btn = gr.Button("Predict Topic")
	greet_btn.click(fn=predict_topic, inputs=[text], outputs=[predictions])

	# Default examples of text and strategy pairs for user to have a quick start
	gr.Markdown("## Examples")
	gr.Examples(
	["Sachgebiet Ausschließliche Gesetzgebungskompetenz des Bundes über die Zusammenarbeit des Bundes und der Länder zum Schutze der freiheitlichen demokratischen Grundordnung, des Bestandes und der Sicherheit des Bundes oder eines Landes.", "Sachgebiet Investive Ausgaben des Bundes Bundesfinanzminister Apel hat gemäß BMF Finanznachrichten vom . Januar erklärt , die Investitionsquote des Bundes sei in den letzten zehn Jahren nahezu konstant geblieben."],
	[text],
	[predictions],
	fn=predict_topic,
	cache_examples=True,
	)

	# Upload file
	# file_output = gr.File()
	# upload_button = gr.UploadButton("Click to Upload a File", outputs=[file_output])
	# gr.Dataframe(pd.DataFrame(file_output))

	# Link to paper and Github repo
	gr.Markdown('''For more details: You can read our [paper](http://www.lrec-conf.org/proceedings/lrec2022/workshops/ParlaCLARINIII/pdf/2022.parlaclariniii-1.13.pdf) or access our [code](https://github.com/chkla/FrameASt).''')
	gr.Markdown('''Enjoy and stay tuned 🚀''')

	def main():
	demo.launch()

	if __name__ == "__main__":
	main()