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from modules.module_logsManager import HuggingFaceDatasetSaver
from modules.module_connection import Word2ContextExplorerConnector
from tool_info import TOOL_INFO
import gradio as gr
import pandas as pd
def interface(
vocabulary, # Vocabulary class instance
contexts: str,
available_logs: bool,
available_wordcloud: bool,
lang: str="es"
) -> gr.Blocks:
# --- Init logs ---
log_callback = HuggingFaceDatasetSaver(
available_logs=available_logs,
dataset_name=f"logs_edia_datos_{lang}"
)
# --- Init Class ---
connector = Word2ContextExplorerConnector(
vocabulary=vocabulary,
context=contexts
)
# --- Load language ---
labels = pd.read_json(
f"language/{lang}.json"
)["DataExplorer_interface"]
# --- 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"]
)
with gr.Row():
input_word = gr.Textbox(
label=labels["inputWord"]["title"],
show_label=False,
placeholder=labels["inputWord"]["placeholder"]
)
with gr.Row():
btn_get_w_info = gr.Button(
value=labels["wordInfoButton"]
)
with gr.Group():
gr.Markdown(
value=labels["step2"]
)
n_context = gr.Slider(
label="",
step=1, minimum=1, maximum=30, value=5,
visible=True,
interactive=True
)
with gr.Group():
gr.Markdown(
value=labels["step3"]
)
subsets_choice = gr.CheckboxGroup(
label="Conjuntos",
show_label=False,
interactive=True,
visible=True
)
with gr.Row():
btn_get_contexts = gr.Button(
value=labels["wordContextButton"],
visible=True
)
with gr.Row():
out_msj = gr.Markdown(
label="",
visible=True
)
with gr.Column():
with gr.Group():
gr.Markdown(
value=labels["wordDistributionTitle"]
)
dist_plot = gr.Plot(
label="",
show_label=False
)
wc_plot = gr.Plot(
label="",
show_label=False,
visible=available_wordcloud
)
with gr.Group():
gr.Markdown(
value=labels["frequencyPerSetTitle"]
)
subsets_freq = gr.HTML(
label=""
)
with gr.Row():
with gr.Group():
with gr.Row():
gr.Markdown(
value=labels["contextList"]
)
with gr.Row():
out_context = gr.Dataframe(
label="",
interactive=False,
value=pd.DataFrame([], columns=['']),
wrap=True,
datatype=['str','markdown','str','markdown']
)
with gr.Group():
gr.Markdown(
value=TOOL_INFO
)
btn_get_w_info.click(
fn=connector.get_word_info,
inputs=[input_word],
outputs=[out_msj,
out_context,
subsets_freq,
dist_plot,
wc_plot,
subsets_choice
]
)
btn_get_contexts.click(
fn=connector.get_word_context,
inputs=[input_word, n_context, subsets_choice],
outputs=[out_msj, out_context]
)
# --- Logs ---
save_field = [input_word, subsets_choice]
log_callback.setup(
components=save_field,
flagging_dir="logs"
)
btn_get_contexts.click(
fn=lambda *args: log_callback.flag(
flag_data=args,
flag_option="datos",
username="vialibre"
),
inputs=save_field,
outputs=None,
preprocess=False
)
return iface |