# -*- coding: utf-8 -*- """ @Author : Jiangjie Chen @Time : 2021/12/13 17:17 @Contact : jjchen19@fudan.edu.cn @Description: """ import os import gradio as gr from src.loren import Loren from huggingface_hub import snapshot_download from prettytable import PrettyTable import pandas as pd config = { "input": "demo", "model_type": "roberta", "model_name_or_path": "roberta-large", "logic_lambda": 0.5, "prior": "random", "mask_rate": 0.0, "cand_k": 3, "max_seq2_length": 256, "max_seq1_length": 128, "max_num_questions": 8 } model_dir = snapshot_download('Jiangjie/loren') config['fc_dir'] = os.path.join(model_dir, 'fact_checking/roberta-large/') config['mrc_dir'] = os.path.join(model_dir, 'mrc_seq2seq/bart-base/') config['er_dir'] = os.path.join(model_dir, 'evidence_retrieval/') loren = Loren(config) try: # js = { # 'id': 0, # 'evidence': ['EVIDENCE1', 'EVIDENCE2'], # 'question': ['QUESTION1', 'QUESTION2'], # 'claim_phrase': ['CLAIMPHRASE1', 'CLAIMPHRASE2'], # 'local_premise': [['E1 ' * 100, 'E1' * 100, 'E1' * 10], ['E2', 'E2', 'E2']], # 'phrase_veracity': [[0.1, 0.5, 0.4], [0.1, 0.7, 0.2]], # 'claim_veracity': 'SUPPORT' # } js = loren.check('Donald Trump won the 2020 U.S. presidential election.') except Exception as e: raise ValueError(e) def gradio_formatter(js, output_type): if output_type == 'e': data = {'Evidence': js['evidence']} elif output_type == 'z': data = { 'Claim Phrase': js['claim_phrase'], 'Local Premise': [x[0] for x in js['local_premise']], 'p_SUP': [round(x[2], 4) for x in js['phrase_veracity']], 'p_REF': [round(x[0], 4) for x in js['phrase_veracity']], 'p_NEI': [round(x[1], 4) for x in js['phrase_veracity']], } else: raise NotImplementedError data = pd.DataFrame(data) pt = PrettyTable(field_names=list(data.columns)) for v in data.values: pt.add_row(v) html = pt.get_html_string(attributes={ 'style': 'border-width: 1px; border-collapse: collapse', }, format=True) return html def run(claim): js = loren.check(claim) ev_html = gradio_formatter(js, 'e') z_html = gradio_formatter(js, 'z') return ev_html, z_html, js['claim_veracity'], js iface = gr.Interface( fn=run, inputs="text", outputs=[ 'html', 'html', 'label', 'json' ], examples=['Donald Trump won the U.S. 2020 presidential election.', 'The first inauguration of Bill Clinton was in the United States.'], title="LOREN", layout='vertical', description="LOREN is an interpretable Fact Verification model against Wikipedia. " "This is a demo system for \"LOREN: Logic-Regularized Reasoning for Interpretable Fact Verification\". " "See the paper for technical details. You can add FLAG on the bottom to record interesting or bad cases!", flagging_dir='results/flagged/', allow_flagging=True, flagging_options=['Good Case!', 'Error: MRC', 'Error: Parsing', 'Error: Commonsense', 'Error: Evidence', 'Error: Other'], enable_queue=True ) iface.launch()