|
""" |
|
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 = { |
|
|
|
"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, |
|
|
|
"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, |
|
} |
|
|
|
|
|
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 = [] |
|
|
|
|
|
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] |
|
|
|
|
|
|
|
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] |
|
): |
|
|
|
weight = total_weight / len(battle_targets[chosen_model]) |
|
rival_models.append(model) |
|
rival_weights.append(weight) |
|
|
|
|
|
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] |
|
|
|
|
|
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)] |
|
|
|
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}") |
|
|
|
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] |
|
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: |
|
|
|
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: |
|
|
|
|
|
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) |
|
|
|
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 |
|
|