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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 |