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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 | |
Only offline generations are available now, online services are coming soon! \n | |
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 | |
<div class="image-container"> | |
<p> Our code base is built upon <a href="https://github.com/lm-sys/FastChat" target="_blank">FastChat</a> and <a href="https://github.com/TIGER-AI-Lab/GenAI-Arena" target="_blank">GenAI-Arena</a></p>. | |
</div> | |
""" | |
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; | |
font-weight: bold; | |
} | |
#about_markdown { | |
font-size: 110% | |
} | |
#ack_markdown { | |
font-size: 110% | |
} | |
#evaldim_markdown { | |
font-weight: bold; | |
text-align: center; | |
background-color: white; | |
} | |
#input_box textarea { | |
font-weight: bold; | |
font-size: 125%; | |
} | |
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, None, None, None) + 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, state_0.geo_video = None, None, None | |
state_1.normal_video, state_1.rgb_video, state_1.geo_video = None, None, None | |
state_0.evaluted_dims, state_1.evaluted_dims = 0, 0 | |
return (state_0, state_1) \ | |
+ (None,) * 6\ | |
+ 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, state_0.geo_video = None, None, None | |
state_1.normal_video, state_1.rgb_video, state_1.geo_video = None, 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))\ | |
+ (None,) * 6 \ | |
+ 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, None | |
def clear_t2s_history_side_by_side(): | |
return [None] * 2 + [""] + [None] * 6 | |
def clear_t2s_history_side_by_side_anony(): | |
return [None] * 2 + [""] + [None] * 6 + [gr.Markdown("", visible=False), gr.Markdown("", visible=False)] | |
def clear_i2s_history(): | |
return None, None, None, None, None | |
def clear_i2s_history_side_by_side(): | |
return [None] * 2 + [None] + [None] * 6 | |
def clear_i2s_history_side_by_side_anony(): | |
return [None] * 2 + [None] + [None] * 6 + [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 |