app.py

import gradio as gr
import spacy  # noqa
from transformers import pipeline

from mathtext.nlutils import text2int


sentiment = pipeline(task="sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")


def get_sentiment(text):
    return sentiment(text)


with gr.Blocks() as html_block:
    gr.Markdown("# Rori - Mathbot")

    with gr.Tab("Text to integer"):
        inputs_text2int = [gr.Text(
            placeholder="Type a number as text or a sentence",
            label="Text to process",
            value="forty two")]

        outputs_text2int = gr.Textbox(label="Output integer")

        button_text2int = gr.Button("text2int")

        button_text2int.click(
            fn=text2int,
            inputs=inputs_text2int,
            outputs=outputs_text2int,
            api_name="text2int",
        )

        examples_text2int = [
            "one thousand forty seven",
            "one hundred",
        ]

        gr.Examples(examples=examples_text2int, inputs=inputs_text2int)

        gr.Markdown(r"""
        ## API
        ```python
        import requests

        requests.post(
            url="https://tangibleai-mathtext.hf.space/run/text2int", json={"data": ["one hundred forty five"]}
        ).json()
        ```

        Or using `curl`:

        ```bash
        curl -X POST https://tangibleai-mathtext.hf.space/run/text2int -H 'Content-Type: application/json' -d '{"data": ["one hundred forty five"]}'
        ```
        """)

    with gr.Tab("Sentiment Analysis"):
        inputs_sentiment = [
            gr.Text(placeholder="Type a number as text or a sentence", label="Text to process",
                    value="I really like it!"),
        ]

        outputs_sentiment = gr.Textbox(label="Sentiment result")

        button_sentiment = gr.Button("sentiment analysis")

        button_sentiment.click(
            get_sentiment,
            inputs=inputs_sentiment,
            outputs=outputs_sentiment,
            api_name="sentiment-analysis"
        )

        examples_sentiment = [
            ["Totally agree!"],
            ["Sorry, I can not accept this!"],
        ]

        gr.Examples(examples=examples_sentiment, inputs=inputs_sentiment)

        gr.Markdown(r"""
        ## API
        ```python
        import requests
        
        requests.post(
            url="https://tangibleai-mathtext.hf.space/run/sentiment-analysis", json={"data": ["You are right!"]}
        ).json()
        ```
        
        Or using `curl`:
        
        ```bash
        curl -X POST https://tangibleai-mathtext.hf.space/run/sentiment-analysis -H 'Content-Type: application/json' -d '{"data": ["You are right!"]}'
        ```
        """)

# interface = gr.Interface(lambda x: x, inputs=["text"], outputs=["text"])
# html_block.input_components = interface.input_components
# html_block.output_components = interface.output_components
# html_block.examples = None

html_block.predict_durations = []

if __name__ == "__main__":
    html_block.launch()