import os import pandas as pd import requests from plotnine import aes, geom_point, ggplot, labs, theme_light from shiny import module, reactive, render, ui @module.ui def query_output_ui(): out = ui.row( {"style": "border: 1px solid gray; border-radius: 5px; margin:10px"}, ui.column( 4, ui.input_text("prompt", "Prompt", placeholder="Enter query"), ), ui.column(4, ui.output_table("score_table")), ui.column(4, ui.output_plot("score_plot")), ) return out @module.server def query_output_server(input, output, session): @reactive.Calc def response_table(): # This is included to both show the expected API response, and populate # the downstream item with zeros before a prompt is entered. if input.prompt() == "": resp = [ [ {"label": "neutral", "score": 0}, {"label": "surprise", "score": 0}, {"label": "fear", "score": 0}, {"label": "anger", "score": 0}, {"label": "disgust", "score": 0}, {"label": "sadness", "score": 0}, {"label": "joy", "score": 0}, ] ] else: resp = query(input.prompt()) df = pd.DataFrame( { "sentiment": [x["label"] for x in resp[0]], "score": [x["score"] for x in resp[0]], } ) return df @output @render.plot def score_plot(): return plot_response(response_table(), input.prompt()) @output @render.table() def score_table(): return response_table() def plot_response(df, plot_title): out = ( ggplot(df, aes(y="reorder(sentiment, score)", x="score")) + geom_point() + theme_light() + labs(title=f'Prompt: "{plot_title}"', y="Sentiment", x="Score") ) return out def query(text): API_URL = "https://api-inference.huggingface.co/models/j-hartmann/emotion-english-roberta-large" headers = {"Authorization": "Bearer " + os.environ["HF_API_KEY"]} payload = {"inputs": text} response = requests.post(API_URL, headers=headers, json=payload) return response.json()