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"""
Chatbot Arena (battle) tab.
Users chat with two anonymous models.
"""
import json
import time
import gradio as gr
import numpy as np
from fastchat.constants import (
MODERATION_MSG,
CONVERSATION_LIMIT_MSG,
SLOW_MODEL_MSG,
BLIND_MODE_INPUT_CHAR_LEN_LIMIT,
CONVERSATION_TURN_LIMIT,
)
from fastchat.model.model_adapter import get_conversation_template
from fastchat.serve.gradio_block_arena_named import flash_buttons
from fastchat.serve.gradio_web_server import (
State,
bot_response,
get_conv_log_filename,
no_change_btn,
enable_btn,
disable_btn,
invisible_btn,
acknowledgment_md,
get_ip,
get_model_description_md,
_prepare_text_with_image,
)
from fastchat.serve.remote_logger import get_remote_logger
from fastchat.utils import (
build_logger,
moderation_filter,
)
logger = build_logger("gradio_web_server_multi", "gradio_web_server_multi.log")
num_sides = 2
enable_moderation = False
anony_names = ["", ""]
models = []
def set_global_vars_anony(enable_moderation_):
global enable_moderation
enable_moderation = enable_moderation_
def load_demo_side_by_side_anony(models_, url_params):
global models
models = models_
states = (None,) * num_sides
selector_updates = (
gr.Markdown(visible=True),
gr.Markdown(visible=True),
)
return states + selector_updates
def vote_last_response(states, vote_type, model_selectors, request: gr.Request):
with open(get_conv_log_filename(), "a") as fout:
data = {
"tstamp": round(time.time(), 4),
"type": vote_type,
"models": [x for x in model_selectors],
"states": [x.dict() for x in states],
"ip": get_ip(request),
}
fout.write(json.dumps(data) + "\n")
get_remote_logger().log(data)
if ":" not in model_selectors[0]:
for i in range(5):
names = (
"### Model A: " + states[0].model_name,
"### Model B: " + states[1].model_name,
)
yield names + ("",) + (disable_btn,) * 4
time.sleep(0.1)
else:
names = (
"### Model A: " + states[0].model_name,
"### Model B: " + states[1].model_name,
)
yield names + ("",) + (disable_btn,) * 4
def leftvote_last_response(
state0, state1, model_selector0, model_selector1, request: gr.Request
):
logger.info(f"leftvote (anony). ip: {get_ip(request)}")
for x in vote_last_response(
[state0, state1], "leftvote", [model_selector0, model_selector1], request
):
yield x
def rightvote_last_response(
state0, state1, model_selector0, model_selector1, request: gr.Request
):
logger.info(f"rightvote (anony). ip: {get_ip(request)}")
for x in vote_last_response(
[state0, state1], "rightvote", [model_selector0, model_selector1], request
):
yield x
def tievote_last_response(
state0, state1, model_selector0, model_selector1, request: gr.Request
):
logger.info(f"tievote (anony). ip: {get_ip(request)}")
for x in vote_last_response(
[state0, state1], "tievote", [model_selector0, model_selector1], request
):
yield x
def bothbad_vote_last_response(
state0, state1, model_selector0, model_selector1, request: gr.Request
):
logger.info(f"bothbad_vote (anony). ip: {get_ip(request)}")
for x in vote_last_response(
[state0, state1], "bothbad_vote", [model_selector0, model_selector1], request
):
yield x
def regenerate(state0, state1, request: gr.Request):
logger.info(f"regenerate (anony). ip: {get_ip(request)}")
states = [state0, state1]
if state0.regen_support and state1.regen_support:
for i in range(num_sides):
states[i].conv.update_last_message(None)
return (
states + [x.to_gradio_chatbot() for x in states] + [""] + [disable_btn] * 6
)
states[0].skip_next = True
states[1].skip_next = True
return states + [x.to_gradio_chatbot() for x in states] + [""] + [no_change_btn] * 6
def clear_history(request: gr.Request):
logger.info(f"clear_history (anony). ip: {get_ip(request)}")
return (
[None] * num_sides
+ [None] * num_sides
+ anony_names
+ [""]
+ [invisible_btn] * 4
+ [disable_btn] * 2
+ [""]
)
def share_click(state0, state1, model_selector0, model_selector1, request: gr.Request):
logger.info(f"share (anony). ip: {get_ip(request)}")
if state0 is not None and state1 is not None:
vote_last_response(
[state0, state1], "share", [model_selector0, model_selector1], request
)
SAMPLING_WEIGHTS = {
# tier 0
"gpt-4-0314": 4,
"gpt-4-0613": 4,
"gpt-4-1106-preview": 2,
"gpt-4-0125-preview": 4,
"gpt-4-turbo-2024-04-09": 4,
"gpt-3.5-turbo-0125": 2,
"claude-3-opus-20240229": 4,
"claude-3-sonnet-20240229": 4,
"claude-3-haiku-20240307": 4,
"claude-2.1": 1,
"zephyr-orpo-141b-A35b-v0.1": 2,
"dbrx-instruct": 1,
"command-r-plus": 4,
"command-r": 2,
"reka-flash": 4,
"reka-flash-online": 4,
"qwen1.5-72b-chat": 2,
"qwen1.5-32b-chat": 2,
"qwen1.5-14b-chat": 2,
"qwen1.5-7b-chat": 2,
"gemma-1.1-7b-it": 2,
"gemma-1.1-2b-it": 1,
"mixtral-8x7b-instruct-v0.1": 4,
"mistral-7b-instruct-v0.2": 2,
"mistral-large-2402": 4,
"mistral-medium": 2,
"starling-lm-7b-beta": 2,
# tier 1
"deluxe-chat-v1.3": 2,
"llama-2-70b-chat": 2,
"llama-2-13b-chat": 1,
"llama-2-7b-chat": 1,
"vicuna-33b": 1,
"vicuna-13b": 1,
"yi-34b-chat": 1,
}
# target model sampling weights will be boosted.
BATTLE_TARGETS = {
"gpt-4-turbo-2024-04-09": {
"gpt-4-1106-preview",
"gpt-4-0125-preview",
"claude-3-opus-20240229",
"gemini-pro-dev-api",
},
"gemini-pro-dev-api": {
"gpt-4-turbo-2024-04-09",
"claude-3-opus-20240229",
"gpt-4-0125-preview",
"claude-3-sonnet-20240229",
},
"reka-flash": {
"qwen1.5-72b-chat",
"claude-3-haiku-20240307",
"command-r-plus",
"command-r",
},
"reka-flash-online": {
"qwen1.5-72b-chat",
"claude-3-haiku-20240307",
"command-r-plus",
"command-r",
},
"deluxe-chat-v1.3": {
"gpt-4-1106-preview",
"gpt-4-0125-preview",
"claude-3-opus-20240229",
"claude-3-sonnet-20240229",
},
"qwen1.5-32b-chat": {
"gpt-3.5-turbo-0125",
"gpt-4-0613",
"gpt-4-0125-preview",
"llama-2-70b-chat",
"mixtral-8x7b-instruct-v0.1",
"mistral-large-2402",
"yi-34b-chat",
},
"qwen1.5-14b-chat": {
"starling-lm-7b-alpha",
"claude-3-haiku-20240307",
"gpt-3.5-turbo-0125",
"openchat-3.5-0106",
"mixtral-8x7b-instruct-v0.1",
},
"mistral-large-2402": {
"gpt-4-0125-preview",
"gpt-4-0613",
"mixtral-8x7b-instruct-v0.1",
"mistral-medium",
"mistral-next",
"claude-3-sonnet-20240229",
},
"gemma-1.1-2b-it": {
"gpt-3.5-turbo-0125",
"mixtral-8x7b-instruct-v0.1",
"starling-lm-7b-beta",
"llama-2-7b-chat",
"mistral-7b-instruct-v0.2",
"gemma-1.1-7b-it",
},
"zephyr-orpo-141b-A35b-v0.1": {
"qwen1.5-72b-chat",
"mistral-large-2402",
"command-r-plus",
"claude-3-haiku-20240307",
},
}
SAMPLING_BOOST_MODELS = []
# outage models won't be sampled.
OUTAGE_MODELS = []
def get_sample_weight(model, outage_models, sampling_weights, sampling_boost_models):
if model in outage_models:
return 0
weight = sampling_weights.get(model, 0)
if model in sampling_boost_models:
weight *= 5
return weight
def get_battle_pair(
models, battle_targets, outage_models, sampling_weights, sampling_boost_models
):
if len(models) == 1:
return models[0], models[0]
model_weights = []
for model in models:
weight = get_sample_weight(
model, outage_models, sampling_weights, sampling_boost_models
)
model_weights.append(weight)
total_weight = np.sum(model_weights)
model_weights = model_weights / total_weight
chosen_idx = np.random.choice(len(models), p=model_weights)
chosen_model = models[chosen_idx]
# for p, w in zip(models, model_weights):
# print(p, w)
rival_models = []
rival_weights = []
for model in models:
if model == chosen_model:
continue
weight = get_sample_weight(
model, outage_models, sampling_weights, sampling_boost_models
)
if (
weight != 0
and chosen_model in battle_targets
and model in battle_targets[chosen_model]
):
# boost to 50% chance
weight = total_weight / len(battle_targets[chosen_model])
rival_models.append(model)
rival_weights.append(weight)
# for p, w in zip(rival_models, rival_weights):
# print(p, w)
rival_weights = rival_weights / np.sum(rival_weights)
rival_idx = np.random.choice(len(rival_models), p=rival_weights)
rival_model = rival_models[rival_idx]
swap = np.random.randint(2)
if swap == 0:
return chosen_model, rival_model
else:
return rival_model, chosen_model
def add_text(
state0, state1, model_selector0, model_selector1, text, image, request: gr.Request
):
ip = get_ip(request)
logger.info(f"add_text (anony). ip: {ip}. len: {len(text)}")
states = [state0, state1]
model_selectors = [model_selector0, model_selector1]
# Init states if necessary
if states[0] is None:
assert states[1] is None
model_left, model_right = get_battle_pair(
models,
BATTLE_TARGETS,
OUTAGE_MODELS,
SAMPLING_WEIGHTS,
SAMPLING_BOOST_MODELS,
)
states = [
State(model_left),
State(model_right),
]
if len(text) <= 0:
for i in range(num_sides):
states[i].skip_next = True
return (
states
+ [x.to_gradio_chatbot() for x in states]
+ ["", None]
+ [
no_change_btn,
]
* 6
+ [""]
)
model_list = [states[i].model_name for i in range(num_sides)]
# turn on moderation in battle mode
all_conv_text_left = states[0].conv.get_prompt()
all_conv_text_right = states[0].conv.get_prompt()
all_conv_text = (
all_conv_text_left[-1000:] + all_conv_text_right[-1000:] + "\nuser: " + text
)
flagged = moderation_filter(all_conv_text, model_list, do_moderation=True)
if flagged:
logger.info(f"violate moderation (anony). ip: {ip}. text: {text}")
# overwrite the original text
text = MODERATION_MSG
conv = states[0].conv
if (len(conv.messages) - conv.offset) // 2 >= CONVERSATION_TURN_LIMIT:
logger.info(f"conversation turn limit. ip: {get_ip(request)}. text: {text}")
for i in range(num_sides):
states[i].skip_next = True
return (
states
+ [x.to_gradio_chatbot() for x in states]
+ [CONVERSATION_LIMIT_MSG, None]
+ [
no_change_btn,
]
* 6
+ [""]
)
text = text[:BLIND_MODE_INPUT_CHAR_LEN_LIMIT] # Hard cut-off
for i in range(num_sides):
post_processed_text = _prepare_text_with_image(
states[i], text, image, csam_flag=False
)
states[i].conv.append_message(states[i].conv.roles[0], post_processed_text)
states[i].conv.append_message(states[i].conv.roles[1], None)
states[i].skip_next = False
hint_msg = ""
for i in range(num_sides):
if "deluxe" in states[i].model_name:
hint_msg = SLOW_MODEL_MSG
return (
states
+ [x.to_gradio_chatbot() for x in states]
+ ["", None]
+ [
disable_btn,
]
* 6
+ [hint_msg]
)
def bot_response_multi(
state0,
state1,
temperature,
top_p,
max_new_tokens,
request: gr.Request,
):
logger.info(f"bot_response_multi (anony). ip: {get_ip(request)}")
if state0 is None or state0.skip_next:
# This generate call is skipped due to invalid inputs
yield (
state0,
state1,
state0.to_gradio_chatbot(),
state1.to_gradio_chatbot(),
) + (no_change_btn,) * 6
return
states = [state0, state1]
gen = []
for i in range(num_sides):
gen.append(
bot_response(
states[i],
temperature,
top_p,
max_new_tokens,
request,
apply_rate_limit=False,
use_recommended_config=True,
)
)
is_stream_batch = []
for i in range(num_sides):
is_stream_batch.append(
states[i].model_name
in [
"gemini-pro",
"gemini-pro-dev-api",
"gemini-1.0-pro-vision",
"gemini-1.5-pro",
"gemini-1.5-flash",
"gemma-1.1-2b-it",
"gemma-1.1-7b-it",
]
)
chatbots = [None] * num_sides
iters = 0
while True:
stop = True
iters += 1
for i in range(num_sides):
try:
# yield gemini fewer times as its chunk size is larger
# otherwise, gemini will stream too fast
if not is_stream_batch[i] or (iters % 30 == 1 or iters < 3):
ret = next(gen[i])
states[i], chatbots[i] = ret[0], ret[1]
stop = False
except StopIteration:
pass
yield states + chatbots + [disable_btn] * 6
if stop:
break
def build_side_by_side_ui_anony(models):
notice_markdown = """
# βοΈ LMSYS Chatbot Arena: Benchmarking LLMs in the Wild
- | [Blog](https://lmsys.org/blog/2023-05-03-arena/) | [GitHub](https://github.com/lm-sys/FastChat) | [Paper](https://arxiv.org/abs/2306.05685) | [Dataset](https://github.com/lm-sys/FastChat/blob/main/docs/dataset_release.md) | [Twitter](https://twitter.com/lmsysorg) | [Discord](https://discord.gg/HSWAKCrnFx) |
## π Rules
- Ask any question to two anonymous models (e.g., ChatGPT, Claude, Llama) and vote for the better one!
- You can continue chatting until you identify a winner.
- Vote won't be counted if model identity is revealed during conversation.
## π LMSYS Arena [Leaderboard](https://leaderboard.lmsys.org)
We've collected **500K+** human votes to compute an LLM Elo leaderboard.
Find out who is the π₯LLM Champion!
## π Chat now!
"""
states = [gr.State() for _ in range(num_sides)]
model_selectors = [None] * num_sides
chatbots = [None] * num_sides
gr.Markdown(notice_markdown, elem_id="notice_markdown")
with gr.Group(elem_id="share-region-anony"):
with gr.Accordion(
f"π Expand to see the descriptions of {len(models)} models", open=False
):
model_description_md = get_model_description_md(models)
gr.Markdown(model_description_md, elem_id="model_description_markdown")
with gr.Row():
for i in range(num_sides):
label = "Model A" if i == 0 else "Model B"
with gr.Column():
chatbots[i] = gr.Chatbot(
label=label,
elem_id="chatbot",
height=550,
show_copy_button=True,
)
with gr.Row():
for i in range(num_sides):
with gr.Column():
model_selectors[i] = gr.Markdown(
anony_names[i], elem_id="model_selector_md"
)
with gr.Row():
slow_warning = gr.Markdown("")
with gr.Row():
leftvote_btn = gr.Button(
value="π A is better", visible=False, interactive=False
)
rightvote_btn = gr.Button(
value="π B is better", visible=False, interactive=False
)
tie_btn = gr.Button(value="π€ Tie", visible=False, interactive=False)
bothbad_btn = gr.Button(
value="π Both are bad", visible=False, interactive=False
)
with gr.Row():
textbox = gr.Textbox(
show_label=False,
placeholder="π Enter your prompt and press ENTER",
elem_id="input_box",
)
send_btn = gr.Button(value="Send", variant="primary", scale=0)
with gr.Row() as button_row:
clear_btn = gr.Button(value="π² New Round", interactive=False)
regenerate_btn = gr.Button(value="π Regenerate", interactive=False)
share_btn = gr.Button(value="π· Share")
with gr.Accordion("Parameters", open=False, visible=False) as parameter_row:
temperature = gr.Slider(
minimum=0.0,
maximum=1.0,
value=0.7,
step=0.1,
interactive=True,
label="Temperature",
)
top_p = gr.Slider(
minimum=0.0,
maximum=1.0,
value=1.0,
step=0.1,
interactive=True,
label="Top P",
)
max_output_tokens = gr.Slider(
minimum=16,
maximum=2048,
value=1024,
step=64,
interactive=True,
label="Max output tokens",
)
gr.Markdown(acknowledgment_md, elem_id="ack_markdown")
imagebox = gr.State(None)
# Register listeners
btn_list = [
leftvote_btn,
rightvote_btn,
tie_btn,
bothbad_btn,
regenerate_btn,
clear_btn,
]
leftvote_btn.click(
leftvote_last_response,
states + model_selectors,
model_selectors + [textbox, leftvote_btn, rightvote_btn, tie_btn, bothbad_btn],
)
rightvote_btn.click(
rightvote_last_response,
states + model_selectors,
model_selectors + [textbox, leftvote_btn, rightvote_btn, tie_btn, bothbad_btn],
)
tie_btn.click(
tievote_last_response,
states + model_selectors,
model_selectors + [textbox, leftvote_btn, rightvote_btn, tie_btn, bothbad_btn],
)
bothbad_btn.click(
bothbad_vote_last_response,
states + model_selectors,
model_selectors + [textbox, leftvote_btn, rightvote_btn, tie_btn, bothbad_btn],
)
regenerate_btn.click(
regenerate, states, states + chatbots + [textbox] + btn_list
).then(
bot_response_multi,
states + [temperature, top_p, max_output_tokens],
states + chatbots + btn_list,
).then(
flash_buttons, [], btn_list
)
clear_btn.click(
clear_history,
None,
states + chatbots + model_selectors + [textbox] + btn_list + [slow_warning],
)
share_js = """
function (a, b, c, d) {
const captureElement = document.querySelector('#share-region-anony');
html2canvas(captureElement)
.then(canvas => {
canvas.style.display = 'none'
document.body.appendChild(canvas)
return canvas
})
.then(canvas => {
const image = canvas.toDataURL('image/png')
const a = document.createElement('a')
a.setAttribute('download', 'chatbot-arena.png')
a.setAttribute('href', image)
a.click()
canvas.remove()
});
return [a, b, c, d];
}
"""
share_btn.click(share_click, states + model_selectors, [], js=share_js)
textbox.submit(
add_text,
states + model_selectors + [textbox, imagebox],
states + chatbots + [textbox, imagebox] + btn_list + [slow_warning],
).then(
bot_response_multi,
states + [temperature, top_p, max_output_tokens],
states + chatbots + btn_list,
).then(
flash_buttons,
[],
btn_list,
)
send_btn.click(
add_text,
states + model_selectors + [textbox, imagebox],
states + chatbots + [textbox, imagebox] + btn_list,
).then(
bot_response_multi,
states + [temperature, top_p, max_output_tokens],
states + chatbots + btn_list,
).then(
flash_buttons, [], btn_list
)
return states + model_selectors
|