| | import gradio as gr |
| | import pandas as pd |
| | from nltk.corpus import wordnet as wn |
| | import nltk |
| | nltk.download('wordnet') |
| |
|
| | df_tree = pd.read_csv("data/20k_tree.csv") |
| | df_metrics = pd.read_csv("data/benchmark.csv") |
| |
|
| | def query_interface(model, synset): |
| | if model == "*": |
| | return df_metrics.query(f"synset =='{synset}'") |
| | else: |
| | return df_metrics.query(f"synset =='{synset}' and model == '{model}'") |
| |
|
| | def find_synsets(lemma): |
| | synsets = wn.synsets(lemma) |
| | valid_set = set(df_metrics.synset.values) |
| | synset_names = [s.name() for s in synsets if s.name() in valid_set] |
| | return df_tree.query(f"synset in @synset_names", engine='python') |
| | |
| | with gr.Blocks() as app: |
| | gr.Label("WordNet Explorer", style="h1") |
| | lemma = gr.Textbox(label="find synsets") |
| | gr.Button("Search").click(find_synsets, lemma, outputs=[gr.DataFrame()]) |
| | |
| | gr.Label("Benchmark Explorer", style="h1") |
| | model_list = list(set(df_metrics.model.values.tolist())) |
| | gr.TextArea(f"This is a simple interface to query the benchmark results. You can use * as a wildcard for the model name. The available models are {', '.join(model_list)}.", lines=2) |
| | with gr.Row(): |
| | |
| | model = gr.Textbox(label="model") |
| | synset = gr.inputs.Textbox(label="synset") |
| | btn = gr.Button("Query", label="query") |
| | btn.click(query_interface, inputs=[model, synset], outputs=[gr.DataFrame()]) |
| | |
| | app.launch() |
