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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
from examples.examples_es import examples_sesgos_frases
def interface(
language_model: str,
available_logs: bool,
lang: str="spanish"
) -> gr.Blocks:
# --- 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_phrases_bias"
)
btn.click(
fn=lambda *args: log_callback.flag(
flag_data=args,
flag_option="phrases_bias",
username="vialibre"
),
inputs=save_field,
outputs=None,
preprocess=False
)
return iface |