Spaces:
Runtime error
Runtime error
File size: 4,847 Bytes
ddec2c4 f1ad590 ddec2c4 f1ad590 ddec2c4 f1ad590 ddec2c4 c4d5284 ddec2c4 c4d5284 ddec2c4 c4d5284 ddec2c4 f1ad590 ddec2c4 f1ad590 ddec2c4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 |
import gradio as gr
import pandas as pd
from tool_info import TOOL_INFO
from modules.module_logsManager import HuggingFaceDatasetSaver
from modules.module_connection import PhraseBiasExplorerConnector
def interface(
language_model: str,
available_logs: bool,
lang: str="es"
) -> gr.Blocks:
# -- Load examples --
if lang == 'es':
from examples.examples_es import examples_sesgos_frases
elif lang == 'en':
from examples.examples_en import examples_sesgos_frases
# --- Init logs ---
log_callback = HuggingFaceDatasetSaver(
available_logs=available_logs,
dataset_name=f"logs_edia_lmodels_{lang}"
)
# --- Init vars ---
connector = PhraseBiasExplorerConnector(
language_model=language_model,
lang=lang
)
# --- Get language labels---
labels = pd.read_json(
f"language/{lang}.json"
)["PhraseExplorer_interface"]
# --- Init Interface ---
iface = gr.Blocks(
css=".container {max-width: 90%; margin: auto;}"
)
with iface:
with gr.Row():
with gr.Column():
with gr.Group():
gr.Markdown(
value=labels["step1"]
)
sent = gr.Textbox(
label=labels["sent"]["title"],
placeholder=labels["sent"]["placeholder"],
show_label=False
)
gr.Markdown(
value=labels["step2"]
)
word_list = gr.Textbox(
label=labels["wordList"]["title"],
placeholder=labels["wordList"]["placeholder"],
show_label=False
)
with gr.Group():
gr.Markdown(
value=labels["step3"]
)
banned_word_list = gr.Textbox(
label=labels["bannedWordList"]["title"],
placeholder=labels["bannedWordList"]["placeholder"]
)
with gr.Row():
with gr.Row():
articles = gr.Checkbox(
label=labels["excludeArticles"],
value=False
)
with gr.Row():
prepositions = gr.Checkbox(
label=labels["excludePrepositions"],
value=False
)
with gr.Row():
conjunctions = gr.Checkbox(
label=labels["excludeConjunctions"],
value=False
)
with gr.Row():
btn = gr.Button(
value=labels["resultsButton"]
)
with gr.Column():
with gr.Group():
gr.Markdown(
value=labels["plot"]
)
dummy = gr.CheckboxGroup(
value="",
show_label=False,
choices=[]
)
out = gr.HTML(
label=""
)
out_msj = gr.Markdown(
value=""
)
with gr.Row():
examples = gr.Examples(
fn=connector.rank_sentence_options,
inputs=[sent, word_list],
outputs=[out, out_msj],
examples=examples_sesgos_frases,
label=labels["examples"]
)
with gr.Row():
gr.Markdown(
value=TOOL_INFO
)
btn.click(
fn=connector.rank_sentence_options,
inputs=[sent, word_list, banned_word_list, articles, prepositions, conjunctions],
outputs=[out_msj, out, dummy]
)
# --- Logs ---
save_field = [sent, word_list]
log_callback.setup(
components=save_field,
flagging_dir="logs_phrase_bias"
)
btn.click(
fn=lambda *args: log_callback.flag(
flag_data=args,
flag_option="phrase_bias",
username="vialibre"
),
inputs=save_field,
outputs=None,
preprocess=False
)
return iface |