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# --- Imports libs ---
import gradio as gr
import pandas as pd
import configparser
# --- Imports modules ---
from modules.model_embbeding import Embedding
from modules.module_vocabulary import Vocabulary
from modules.module_languageModel import LanguageModel
# --- Imports interfaces ---
from interfaces.interface_WordExplorer import interface as interface_wordExplorer
from interfaces.interface_BiasWordExplorer import interface as interface_biasWordExplorer
from interfaces.interface_data import interface as interface_data
from interfaces.interface_biasPhrase import interface as interface_biasPhrase
from interfaces.interface_crowsPairs import interface as interface_crowsPairs
# --- Tool config ---
cfg = configparser.ConfigParser()
cfg.read('tool.cfg')
LANGUAGE = cfg['INTERFACE']['language']
EMBEDDINGS_PATH = cfg['WORD_EXPLORER']['embeddings_path']
NN_METHOD = cfg['WORD_EXPLORER']['nn_method']
MAX_NEIGHBORS = int(cfg['WORD_EXPLORER']['max_neighbors'])
CONTEXTS_DATASET = cfg['DATA']['contexts_dataset']
VOCABULARY_SUBSET = cfg['DATA']['vocabulary_subset']
AVAILABLE_WORDCLOUD = cfg['DATA'].getboolean('available_wordcloud')
LANGUAGE_MODEL = cfg['LMODEL']['language_model']
AVAILABLE_LOGS = cfg['LOGS'].getboolean('available_logs')
# --- Init classes ---
embedding = Embedding(
path=EMBEDDINGS_PATH,
limit=100000,
randomizedPCA=False,
max_neighbors=MAX_NEIGHBORS,
nn_method=NN_METHOD
)
vocabulary = Vocabulary(
subset_name=VOCABULARY_SUBSET
)
beto_lm = LanguageModel(
model_name=LANGUAGE_MODEL
)
labels = pd.read_json(f"language/{LANGUAGE}.json")["app"]
# --- Main App ---
INTERFACE_LIST = [
interface_biasWordExplorer(
embedding=embedding,
available_logs=AVAILABLE_LOGS,
lang=LANGUAGE),
interface_wordExplorer(
embedding=embedding,
available_logs=AVAILABLE_LOGS,
max_neighbors=MAX_NEIGHBORS,
lang=LANGUAGE),
interface_data(
vocabulary=vocabulary,
contexts=CONTEXTS_DATASET,
available_logs=AVAILABLE_LOGS,
available_wordcloud=AVAILABLE_WORDCLOUD,
lang=LANGUAGE),
interface_biasPhrase(
language_model=beto_lm,
available_logs=AVAILABLE_LOGS,
lang=LANGUAGE),
interface_crowsPairs(
language_model=beto_lm,
available_logs=AVAILABLE_LOGS,
lang=LANGUAGE),
]
TAB_NAMES = [
labels["biasWordExplorer"],
labels["wordExplorer"],
labels["dataExplorer"],
labels["phraseExplorer"],
labels["crowsPairsExplorer"]
]
if LANGUAGE != 'es':
# Skip data tab when using other than spanish language
INTERFACE_LIST = INTERFACE_LIST[:2] + INTERFACE_LIST[3:]
TAB_NAMES = TAB_NAMES[:2] + TAB_NAMES[3:]
iface = gr.TabbedInterface(
interface_list= INTERFACE_LIST,
tab_names=TAB_NAMES
)
iface.queue(concurrency_count=8)
iface.launch(debug=False)
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