import os import json import random import datetime import requests import numpy as np import gradio as gr from pathlib import Path from model.model_registry import * from constants import LOGDIR, LOG_SERVER_ADDR, APPEND_JSON, SAVE_IMAGE, SAVE_LOG, EVALUATE_DIMS from typing import Union enable_btn = gr.update(interactive=True, visible=True) disable_btn = gr.update(interactive=False) invisible_btn = gr.update(interactive=False, visible=False) no_change_btn = gr.update(value="No Change", interactive=True, visible=True) def build_about(): about_markdown = f""" # About Us Supported by Shanghai AI Laboratory ## Contributors: Yuhan Zhang, Mengchen Zhang, Tong Wu, Tengfei Wang, Ziwei Liu, Dahua Lin ## Contact: Email: yhzhang4778@gmail.com ## Sponsorship We are keep looking for sponsorship to support the arena project for the long term. Please contact us if you are interested in supporting this project. """ gr.Markdown(about_markdown, elem_id="about_markdown") acknowledgment_md = """ ### Acknowledgment

Our code base is built upon FastChat and GenAI-Arena

.
""" block_css = """ #notice_markdown { font-size: 110% } #notice_markdown th { display: none; } #notice_markdown td { padding-top: 6px; padding-bottom: 6px; } #model_description_markdown { font-size: 110% } #leaderboard_markdown { font-size: 110% } #leaderboard_markdown td { padding-top: 6px; padding-bottom: 6px; } #leaderboard_dataframe td { line-height: 0.1em; } #about_markdown { font-size: 110% } #ack_markdown { font-size: 110% } #evaldim_markdown { font-weight: bold; text-align: center; background-color: white; } #input_box textarea { } footer { display:none !important } .image-about img { margin: 0 30px; margin-top: 30px; height: 60px; max-height: 100%; width: auto; float: left; .input-image, .image-preview { margin: 0 30px; height: 30px; max-height: 100%; width: auto; max-width: 30%;} } """ def enable_mds(): return tuple(gr.update(visible=True) for _ in range(EVALUATE_DIMS)) def disable_mds(): return tuple(gr.update(visible=False) for _ in range(EVALUATE_DIMS)) def enable_buttons_side_by_side(): return tuple(gr.update(visible=True, interactive=True) for i in range(EVALUATE_DIMS*4 + 2)) def disable_buttons_side_by_side(): return tuple(gr.update(visible=(i>=EVALUATE_DIMS*4), interactive=False) for i in range(EVALUATE_DIMS*4 + 2)) def enable_buttons(): return tuple(gr.update(interactive=True) for _ in range(EVALUATE_DIMS*3 + 2)) def disable_buttons(): return tuple(gr.update(interactive=False) for _ in range(EVALUATE_DIMS*3 + 2)) def reset_state(state): state.normal_video, state.rgb_video = None, None state.evaluted_dims = 0 return (state,) + tuple(gr.update(interactive=False) for _ in range(EVALUATE_DIMS*3 + 2)) def reset_states_side_by_side(state_0, state_1): state_0.normal_video, state_0.rgb_video = None, None state_1.normal_video, state_1.rgb_video = None, None state_0.evaluted_dims, state_1.evaluted_dims = 0, 0 return (state_0, state_1) \ + tuple(gr.update(visible=(i>=EVALUATE_DIMS*4), interactive=False) for i in range(EVALUATE_DIMS*4 + 2)) \ + tuple(gr.update(visible=False) for _ in range(EVALUATE_DIMS)) def reset_states_side_by_side_anony(state_0, state_1): state_0.model_name, state_1.model_name = "", "" state_0.normal_video, state_0.rgb_video = None, None state_1.normal_video, state_1.rgb_video = None, None state_0.evaluted_dims, state_1.evaluted_dims = 0, 0 return (state_0, state_1) \ + (gr.Markdown("", visible=False), gr.Markdown("", visible=False))\ + tuple(gr.update(visible=(i>=EVALUATE_DIMS*4), interactive=False) for i in range(EVALUATE_DIMS*4 + 2)) \ + tuple(gr.update(visible=False) for _ in range(EVALUATE_DIMS)) def clear_t2s_history(): return None, "", None, None def clear_t2s_history_side_by_side(): return [None] * 2 + [""] + [None] * 4 def clear_t2s_history_side_by_side_anony(): return [None] * 2 + [""] + [None] * 4 + [gr.Markdown("", visible=False), gr.Markdown("", visible=False)] def clear_i2s_history(): return None, None, None, None def clear_i2s_history_side_by_side(): return [None] * 2 + [None] + [None] * 4 def clear_i2s_history_side_by_side_anony(): return [None] * 2 + [None] + [None] * 4 + [gr.Markdown("", visible=False), gr.Markdown("", visible=False)] def get_ip(request: gr.Request): if request: if "cf-connecting-ip" in request.headers: ip = request.headers["cf-connecting-ip"] or request.client.host else: ip = request.client.host else: ip = None return ip def get_conv_log_filename(): t = datetime.datetime.now() name = os.path.join(LOGDIR, f"{t.year}-{t.month:02d}-{t.day:02d}-conv.json") return name def save_image_file_on_log_server(image_file:str): image_file = Path(image_file).absolute().relative_to(os.getcwd()) image_file = str(image_file) # Open the image file in binary mode url = f"{LOG_SERVER_ADDR}/{SAVE_IMAGE}" with open(image_file, 'rb') as f: # Make the POST request, sending the image file and the image path response = requests.post(url, files={'image': f}, data={'image_path': image_file}) return response def append_json_item_on_log_server(json_item: Union[dict, str], log_file: str): if isinstance(json_item, dict): json_item = json.dumps(json_item) log_file = Path(log_file).absolute().relative_to(os.getcwd()) log_file = str(log_file) url = f"{LOG_SERVER_ADDR}/{APPEND_JSON}" # Make the POST request, sending the JSON string and the log file name response = requests.post(url, data={'json_str': json_item, 'file_name': log_file}) return response def save_log_str_on_log_server(log_str: str, log_file: str): log_file = Path(log_file).absolute().relative_to(os.getcwd()) log_file = str(log_file) url = f"{LOG_SERVER_ADDR}/{SAVE_LOG}" # Make the POST request, sending the log message and the log file name response = requests.post(url, data={'message': log_str, 'log_path': log_file}) return response