from fixed_f1 import FixedF1
from fixed_precision import FixedPrecision
from fixed_recall import FixedRecall

import gradio as gr

title = "'Combine' multiple metrics with this 🤗 Evaluate 🪲 Fix!"

description = """<p style='text-align: center'>
As I introduce myself to the entirety of the 🤗 ecosystem, I've put together this space to show off a workaround for a current 🪲 in the 🤗 Evaluate library. \n

Check out the original, longstanding issue [here](https://github.com/huggingface/evaluate/issues/234). This details how it is currently impossible to \
'evaluate.combine()' multiple metrics related to multilabel text classification. Particularly, one cannot 'combine()' the f1, precision, and recall scores for \
evaluation. I encountered this issue specifically while training [RoBERTa-base-DReiFT](https://huggingface.co/MarioBarbeque/RoBERTa-base-DReiFT) for multilabel \
text classification of 805 labeled medical conditions based on drug reviews for treatment received for the same underlying conditio. Use the space below for \
a preview of the workaround! \n

Try to use \t to write some code? \t or how does that work? </p>


"""

article = "<p style='text-align: center'>Check out the [original repo](https://github.com/johngrahamreynolds/FixedMetricsForHF) housing this code, and a quickly \
trained [multilabel text classicifcation model](https://github.com/johngrahamreynolds/RoBERTa-base-DReiFT/tree/main) that makes use of it during evaluation.</p>"

def show_off(input):
    f1 = FixedF1()
    precision = FixedPrecision()
    recall = FixedRecall()



    return "Checking this out! Here's what you put in: " + f"""{input} """


gr.Interface(
    fn=show_off,
    inputs="textbox",
    outputs="text",
    title=title,
    description=description,
    article=article,
    examples=[["What are you doing?"], ["Where should we time travel to?"]],
).launch()