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import argparse
import datetime
import json
import os
import time
import gradio as gr
import requests
from cumo.conversation import (default_conversation, conv_templates,
SeparatorStyle)
from cumo.constants import LOGDIR
from cumo.utils import (build_logger, server_error_msg,
violates_moderation, moderation_msg)
import hashlib
logger = build_logger("gradio_web_server", "gradio_web_server.log")
headers = {"User-Agent": "CuMo"}
no_change_btn = gr.Button()
enable_btn = gr.Button(interactive=True)
disable_btn = gr.Button(interactive=False)
priority = {
"mistral-7b": "aaaaaaa",
"mistral-8x7b": "aaaaaab",
}
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 get_model_list():
ret = requests.post(args.controller_url + "/refresh_all_workers")
assert ret.status_code == 200
ret = requests.post(args.controller_url + "/list_models")
models = ret.json()["models"]
models.sort(key=lambda x: priority.get(x, x))
logger.info(f"Models: {models}")
return models
get_window_url_params = """
function() {
const params = new URLSearchParams(window.location.search);
url_params = Object.fromEntries(params);
console.log(url_params);
return url_params;
}
"""
def load_demo(url_params, request: gr.Request):
logger.info(f"load_demo. ip: {request.client.host}. params: {url_params}")
dropdown_update = gr.Dropdown(visible=True)
if "model" in url_params:
model = url_params["model"]
if model in models:
dropdown_update = gr.Dropdown(value=model, visible=True)
state = default_conversation.copy()
return state, dropdown_update
def load_demo_refresh_model_list(request: gr.Request):
logger.info(f"load_demo. ip: {request.client.host}")
models = get_model_list()
state = default_conversation.copy()
dropdown_update = gr.Dropdown(
choices=models,
value=models[0] if len(models) > 0 else ""
)
return state, dropdown_update
def vote_last_response(state, vote_type, model_selector, request: gr.Request):
with open(get_conv_log_filename(), "a") as fout:
data = {
"tstamp": round(time.time(), 4),
"type": vote_type,
"model": model_selector,
"state": state.dict(),
"ip": request.client.host,
}
fout.write(json.dumps(data) + "\n")
def upvote_last_response(state, model_selector, request: gr.Request):
logger.info(f"upvote. ip: {request.client.host}")
vote_last_response(state, "upvote", model_selector, request)
return ("",) + (disable_btn,) * 3
def downvote_last_response(state, model_selector, request: gr.Request):
logger.info(f"downvote. ip: {request.client.host}")
vote_last_response(state, "downvote", model_selector, request)
return ("",) + (disable_btn,) * 3
def flag_last_response(state, model_selector, request: gr.Request):
logger.info(f"flag. ip: {request.client.host}")
vote_last_response(state, "flag", model_selector, request)
return ("",) + (disable_btn,) * 3
def regenerate(state, image_process_mode, request: gr.Request):
logger.info(f"regenerate. ip: {request.client.host}")
state.messages[-1][-1] = None
prev_human_msg = state.messages[-2]
if type(prev_human_msg[1]) in (tuple, list):
prev_human_msg[1] = (*prev_human_msg[1][:2], image_process_mode)
state.skip_next = False
return (state, state.to_gradio_chatbot(), "", None) + (disable_btn,) * 5
def clear_history(request: gr.Request):
logger.info(f"clear_history. ip: {request.client.host}")
state = default_conversation.copy()
return (state, state.to_gradio_chatbot(), "", None) + (disable_btn,) * 5
def add_text(state, text, image, image_process_mode, request: gr.Request):
logger.info(f"add_text. ip: {request.client.host}. len: {len(text)}")
if len(text) <= 0 and image is None:
state.skip_next = True
return (state, state.to_gradio_chatbot(), "", None) + (no_change_btn,) * 5
if args.moderate:
flagged = violates_moderation(text)
if flagged:
state.skip_next = True
return (state, state.to_gradio_chatbot(), moderation_msg, None) + (
no_change_btn,) * 5
text = text[:1536] # Hard cut-off
if image is not None:
text = text[:1200] # Hard cut-off for images
if '<image>' not in text:
# text = '<Image><image></Image>' + text
text = text + '\n<image>'
text = (text, image, image_process_mode)
state = default_conversation.copy()
state.append_message(state.roles[0], text)
state.append_message(state.roles[1], None)
state.skip_next = False
return (state, state.to_gradio_chatbot(), "", None) + (disable_btn,) * 5
def http_bot(state, model_selector, temperature, top_p, max_new_tokens, request: gr.Request):
logger.info(f"http_bot. ip: {request.client.host}")
start_tstamp = time.time()
model_name = model_selector
if state.skip_next:
# This generate call is skipped due to invalid inputs
yield (state, state.to_gradio_chatbot()) + (no_change_btn,) * 5
return
if len(state.messages) == state.offset + 2:
# First round of conversation
template_name = "mistral_instruct_system"
new_state = conv_templates[template_name].copy()
new_state.append_message(new_state.roles[0], state.messages[-2][1])
new_state.append_message(new_state.roles[1], None)
state = new_state
# Query worker address
controller_url = args.controller_url
ret = requests.post(controller_url + "/get_worker_address",
json={"model": model_name})
worker_addr = ret.json()["address"]
logger.info(f"model_name: {model_name}, worker_addr: {worker_addr}")
# No available worker
if worker_addr == "":
state.messages[-1][-1] = server_error_msg
yield (state, state.to_gradio_chatbot(), disable_btn, disable_btn, disable_btn, enable_btn, enable_btn)
return
# Construct prompt
prompt = state.get_prompt()
all_images = state.get_images(return_pil=True)
all_image_hash = [hashlib.md5(image.tobytes()).hexdigest() for image in all_images]
for image, hash in zip(all_images, all_image_hash):
t = datetime.datetime.now()
filename = os.path.join(LOGDIR, "serve_images", f"{t.year}-{t.month:02d}-{t.day:02d}", f"{hash}.jpg")
if not os.path.isfile(filename):
os.makedirs(os.path.dirname(filename), exist_ok=True)
image.save(filename)
# Make requests
pload = {
"model": model_name,
"prompt": prompt,
"temperature": float(temperature),
"top_p": float(top_p),
"max_new_tokens": min(int(max_new_tokens), 1536),
"stop": state.sep if state.sep_style in [SeparatorStyle.SINGLE, SeparatorStyle.MPT] else state.sep2,
"images": f'List of {len(state.get_images())} images: {all_image_hash}',
}
logger.info(f"==== request ====\n{pload}")
pload['images'] = state.get_images()
state.messages[-1][-1] = "β"
yield (state, state.to_gradio_chatbot()) + (disable_btn,) * 5
try:
# Stream output
response = requests.post(worker_addr + "/worker_generate_stream",
headers=headers, json=pload, stream=True, timeout=10)
for chunk in response.iter_lines(decode_unicode=False, delimiter=b"\0"):
if chunk:
data = json.loads(chunk.decode())
if data["error_code"] == 0:
output = data["text"][len(prompt):].strip()
state.messages[-1][-1] = output + "β"
yield (state, state.to_gradio_chatbot()) + (disable_btn,) * 5
else:
output = data["text"] + f" (error_code: {data['error_code']})"
state.messages[-1][-1] = output
yield (state, state.to_gradio_chatbot()) + (disable_btn, disable_btn, disable_btn, enable_btn, enable_btn)
return
time.sleep(0.03)
except requests.exceptions.RequestException as e:
state.messages[-1][-1] = server_error_msg
yield (state, state.to_gradio_chatbot()) + (disable_btn, disable_btn, disable_btn, enable_btn, enable_btn)
return
state.messages[-1][-1] = state.messages[-1][-1][:-1]
yield (state, state.to_gradio_chatbot()) + (enable_btn,) * 5
finish_tstamp = time.time()
logger.info(f"{output}")
with open(get_conv_log_filename(), "a") as fout:
data = {
"tstamp": round(finish_tstamp, 4),
"type": "chat",
"model": model_name,
"start": round(start_tstamp, 4),
"finish": round(finish_tstamp, 4),
"state": state.dict(),
"images": all_image_hash,
"ip": request.client.host,
}
fout.write(json.dumps(data) + "\n")
title_markdown = ("""
# CuMo: Scaling Multimodal LLM with Co-Upcycled Mixture-of-Experts
[[Project Page](https://chrisjuniorli.github.io/project/CuMo/)] [[Code](https://github.com/SHI-Labs/CuMo)] [[Model](https://huggingface.co/jiachenl/CuMo-mistral-7b)] | π [[Arxiv]()]]
""")
tos_markdown = ("""
### Terms of use
By using this service, users are required to agree to the following terms:
The service is a research preview intended for non-commercial use only. It only provides limited safety measures and may generate offensive content. It must not be used for any illegal, harmful, violent, racist, or sexual purposes. The service may collect user dialogue data for future research.
Please click the "Flag" button if you get any inappropriate answer! We will collect those to keep improving our moderator.
For an optimal experience, please use desktop computers for this demo, as mobile devices may compromise its quality.
""")
learn_more_markdown = ("""
### License
The service is a research preview intended for non-commercial use only, subject to the. Please contact us if you find any potential violation.
""")
block_css = """
#buttons button {
min-width: min(120px,100%);
}
"""
def build_demo(embed_mode, cur_dir=None, concurrency_count=10):
textbox = gr.Textbox(show_label=False, placeholder="Enter text and press ENTER", container=False)
with gr.Blocks(title="CuMo", theme=gr.themes.Default(), css=block_css) as demo:
state = gr.State()
if not embed_mode:
gr.Markdown(title_markdown)
with gr.Row():
with gr.Column(scale=3):
with gr.Row(elem_id="model_selector_row"):
model_selector = gr.Dropdown(
choices=models,
value=models[0] if len(models) > 0 else "",
interactive=True,
show_label=False,
container=False)
imagebox = gr.Image(type="pil")
image_process_mode = gr.Radio(
["Crop", "Resize", "Pad", "Default"],
value="Default",
label="Preprocess for non-square image", visible=False)
if cur_dir is None:
cur_dir = os.path.dirname(os.path.abspath(__file__))
gr.Examples(examples=[
[f"{cur_dir}/examples/aveger.jpg", "Can you introduce this movie based on the poster?"],
[f"{cur_dir}/examples/fridge.webp", "Can you describe what groceries are presented in this fridge?"],
[f"{cur_dir}/examples/su7_4.jpg", "What car is it in this image?"],
[f"{cur_dir}/examples/nvidia.jpeg", "Can you tell me what happened in this image?"],
[f"{cur_dir}/examples/animal.webp", "What animals are in this image?"],
[f"{cur_dir}/examples/disney.jpeg", "How many characters in this image?"],
[f"{cur_dir}/examples/reka_6.jpeg", "What colour is my hat (im sitting on the bear)?"],
], inputs=[imagebox, textbox])
with gr.Accordion("Parameters", open=False) as parameter_row:
temperature = gr.Slider(minimum=0.0, maximum=1.0, value=0.2, step=0.1, interactive=True, label="Temperature",)
top_p = gr.Slider(minimum=0.0, maximum=1.0, value=0.7, step=0.1, interactive=True, label="Top P",)
max_output_tokens = gr.Slider(minimum=0, maximum=1024, value=512, step=64, interactive=True, label="Max output tokens",)
with gr.Column(scale=8):
chatbot = gr.Chatbot(
elem_id="chatbot",
label="CuMo Chatbot",
height=650,
layout="panel",
)
with gr.Row():
with gr.Column(scale=8):
textbox.render()
with gr.Column(scale=1, min_width=50):
submit_btn = gr.Button(value="Send", variant="primary")
with gr.Row(elem_id="buttons") as button_row:
upvote_btn = gr.Button(value="π Upvote", interactive=False)
downvote_btn = gr.Button(value="π Downvote", interactive=False)
flag_btn = gr.Button(value="β οΈ Flag", interactive=False)
#stop_btn = gr.Button(value="βΉοΈ Stop Generation", interactive=False)
regenerate_btn = gr.Button(value="π Regenerate", interactive=False)
clear_btn = gr.Button(value="ποΈ Clear", interactive=False)
if not embed_mode:
gr.Markdown(tos_markdown)
gr.Markdown(learn_more_markdown)
url_params = gr.JSON(visible=False)
# Register listeners
btn_list = [upvote_btn, downvote_btn, flag_btn, regenerate_btn, clear_btn]
upvote_btn.click(
upvote_last_response,
[state, model_selector],
[textbox, upvote_btn, downvote_btn, flag_btn]
)
downvote_btn.click(
downvote_last_response,
[state, model_selector],
[textbox, upvote_btn, downvote_btn, flag_btn]
)
flag_btn.click(
flag_last_response,
[state, model_selector],
[textbox, upvote_btn, downvote_btn, flag_btn]
)
regenerate_btn.click(
regenerate,
[state, image_process_mode],
[state, chatbot, textbox, imagebox] + btn_list
).then(
http_bot,
[state, model_selector, temperature, top_p, max_output_tokens],
[state, chatbot] + btn_list,
concurrency_limit=concurrency_count
)
clear_btn.click(
clear_history,
None,
[state, chatbot, textbox, imagebox] + btn_list,
queue=False
)
textbox.submit(
add_text,
[state, textbox, imagebox, image_process_mode],
[state, chatbot, textbox, imagebox] + btn_list,
queue=False
).then(
http_bot,
[state, model_selector, temperature, top_p, max_output_tokens],
[state, chatbot] + btn_list,
concurrency_limit=concurrency_count
)
submit_btn.click(
add_text,
[state, textbox, imagebox, image_process_mode],
[state, chatbot, textbox, imagebox] + btn_list
).then(
http_bot,
[state, model_selector, temperature, top_p, max_output_tokens],
[state, chatbot] + btn_list,
concurrency_limit=concurrency_count
)
if args.model_list_mode == "once":
demo.load(
load_demo,
[url_params],
[state, model_selector],
js=get_window_url_params
)
elif args.model_list_mode == "reload":
demo.load(
load_demo_refresh_model_list,
None,
[state, model_selector],
queue=False
)
else:
raise ValueError(f"Unknown model list mode: {args.model_list_mode}")
return demo
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--host", type=str, default="0.0.0.0")
parser.add_argument("--port", type=int)
parser.add_argument("--controller-url", type=str, default="http://localhost:21001")
parser.add_argument("--concurrency-count", type=int, default=16)
parser.add_argument("--model-list-mode", type=str, default="once",
choices=["once", "reload"])
parser.add_argument("--share", action="store_true")
parser.add_argument("--moderate", action="store_true")
parser.add_argument("--embed", action="store_true")
args = parser.parse_args()
logger.info(f"args: {args}")
models = get_model_list()
logger.info(args)
demo = build_demo(args.embed, concurrency_count=args.concurrency_count)
demo.queue(
api_open=False
).launch(
server_name=args.host,
server_port=args.port,
share=args.share
)
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