| import gradio as gr | |
| import matplotlib | |
| import models | |
| import utils | |
| def infer(gt: str, data: str) -> matplotlib.figure: | |
| nli_res = models.compute_metric(gt, data) | |
| tone_res = models.compare_tone(gt, data) | |
| res_text = "" | |
| if (nli_res["label"] == "neutral"): | |
| res_text += "Model's response is unrelated to the Ground Truth" | |
| if (nli_res["label"] == "contradiction"): | |
| res_text += "Model's response contradicts the Ground Truth" | |
| if (nli_res["label"] == "entailment"): | |
| res_text += "Model's response is consistant with the Ground Truth" | |
| return res_text, utils.create_pie_chart_nli(nli_res), utils.plot_tones(tone_res) | |
| examples = [["Cross-encoders are better than bi-encoders for analyzing the relationship betwen texts", "Bi-encoders are superior to cross-encoders"], | |
| ["Cross-encoders are better than bi-encoders for analyzing the relationship betwen texts", "The cosine similarity function can be used to compare the outputs of a bi-encoder"], | |
| ["Cross-encoders are better than bi-encoders for analyzing the relationship betwen texts", "Bi-encoders are outperformed by cross-encoders in the task of relationship analysis"], | |
| ["Birds can fly. There are fish in the sea.", "Fish inhabit the ocean. Birds can aviate."], | |
| ["Birds can fly. There are fish in the sea.", "Fish inhabit the ocean. Birds can not aviate."]] | |
| app = gr.Interface(fn=infer, inputs=[gr.Textbox(label="Ground Truth"), gr.Textbox(label="Model Response")], examples=examples, outputs=[gr.Textbox(label="Result"), gr.Plot(label="Comparison with GT"), gr.Plot(label="Difference in Tone")]) | |
| app.launch() |