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from difflib import Differ
import gradio as gr
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
model = AutoModelForSeq2SeqLM.from_pretrained("Hnabil/t5-address-standardizer")
tokenizer = AutoTokenizer.from_pretrained("Hnabil/t5-address-standardizer")
def standardizer_adress(adress):
inputs = tokenizer(adress, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
std_adress = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
return std_adress
def diff_texts(adress):
std_adress = standardizer_adress(adress)
words1 = adress.split()
words2 = std_adress.split()
d = Differ()
return [
(token[2:], "Non-Standard" if token[0] != " " else None)
for token in d.compare(words1, words2)
if token[0] != "+" and token[0] != "?"
] + [
("β†’", "β†’")
] + [
(token[2:], "Standard" if token[0] != " " else None)
for token in d.compare(words1, words2)
if token[0] != "-" and token[0] != "?"
]
examples = [
["940, north pennsylvania avneue, mason icty, iowa, 50401, us"],
["537, 6th st s, mason city, ia, 50401, us"]
]
color_map = {"Non-Standard": "LightSalmon", "Standard": "LightGreen", "β†’": "LightBlue"}
demo = gr.Interface(
diff_texts,
[
gr.Textbox(
label="Adress",
info="Enter an adress to standardize",
lines=3,
)
],
[
gr.HighlightedText(
label="Standardized Adress",
show_legend=True,
).style(color_map=color_map),
],
examples=examples,
theme=gr.themes.Base()
)
if __name__ == "__main__":
demo.launch(share=False)