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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, | |
| 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, | |
| ) | |
| 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") | |
| 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] | |
| 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 | |
| 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": 4, | |
| "gpt-4-0314": 4, | |
| "gpt-4-0613": 4, | |
| "gpt-4-turbo": 4, | |
| "gpt-4-1106-preview": 4, | |
| "gpt-4-0125-preview": 4, | |
| "gpt-3.5-turbo-0613": 2, | |
| "gpt-3.5-turbo-1106": 2, | |
| "gpt-3.5-turbo-0125": 4, | |
| "claude-2.1": 4, | |
| "claude-2.0": 2, | |
| "claude-1": 2, | |
| "claude-instant-1": 2, | |
| "gemini-pro": 4, | |
| "gemini-pro-dev-api": 4, | |
| "bard-jan-24-gemini-pro": 4, | |
| "bard-feb-2024": 4, | |
| "mixtral-8x7b-instruct-v0.1": 4, | |
| "mistral-medium": 4, | |
| "qwen1.5-72b-chat": 4, | |
| "qwen1.5-7b-chat": 2, | |
| "qwen1.5-4b-chat": 2, | |
| "nous-hermes-2-mixtral-8x7b-dpo": 2, | |
| "deepseek-llm-67b-chat": 2, | |
| "stripedhyena-nous-7b": 2, | |
| "openchat-3.5-0106": 2, | |
| "mistral-7b-instruct-v0.2": 2, | |
| "solar-10.7b-instruct-v1.0": 2, | |
| "dolphin-2.2.1-mistral-7b": 2, | |
| "starling-lm-7b-alpha": 2, | |
| "tulu-2-dpo-70b": 2, | |
| "yi-34b-chat": 2, | |
| "zephyr-7b-beta": 2, | |
| # tier 1 | |
| "deluxe-chat-v1.2": 4, | |
| "llama-2-70b-chat": 4, | |
| "llama-2-13b-chat": 2, | |
| "llama-2-7b-chat": 2, | |
| "mistral-7b-instruct": 2, | |
| "codellama-34b-instruct": 1.5, | |
| "vicuna-33b": 2, | |
| "vicuna-13b": 1.5, | |
| "wizardlm-13b": 1.5, | |
| "qwen-14b-chat": 1.5, | |
| # tier 2 | |
| "pplx-7b-online": 1, | |
| "pplx-70b-online": 1, | |
| "openhermes-2.5-mistral-7b": 1.0, | |
| "llama2-70b-steerlm-chat": 1.0, | |
| "chatglm3-6b": 1.0, | |
| "openchat-3.5": 1.0, | |
| "wizardlm-70b": 1.0, | |
| "vicuna-7b": 1.0, | |
| "chatglm2-6b": 1.0, | |
| # deprecated | |
| "zephyr-7b-alpha": 1.5, | |
| "codellama-13b-instruct": 1.0, | |
| "mpt-30b-chat": 1.5, | |
| "guanaco-33b": 1.0, | |
| "fastchat-t5-3b": 0.5, | |
| "alpaca-13b": 0.5, | |
| "mpt-7b-chat": 0.1, | |
| "oasst-pythia-12b": 0.1, | |
| "RWKV-4-Raven-14B": 0.1, | |
| "gpt4all-13b-snoozy": 0.1, | |
| "koala-13b": 0.1, | |
| "stablelm-tuned-alpha-7b": 0.1, | |
| "dolly-v2-12b": 0.1, | |
| "llama-13b": 0.1, | |
| "chatglm-6b": 0.5, | |
| "deluxe-chat-v1": 4, | |
| "palm-2": 1.5, | |
| } | |
| # target model sampling weights will be boosted. | |
| BATTLE_TARGETS = { | |
| "gpt-4": {"gpt-4-0314", "claude-2.1", "gpt-4-1106-preview"}, | |
| "gpt-4-0613": {"gpt-4-0314", "claude-2.1", "gpt-4-1106-preview"}, | |
| "gpt-4-0314": { | |
| "gpt-4-1106-preview", | |
| "gpt-4-0613", | |
| "claude-2.1", | |
| "gpt-3.5-turbo-0613", | |
| }, | |
| "gpt-4-1106-preview": { | |
| "gpt-4-0613", | |
| "gpt-3.5-turbo-0613", | |
| "gpt-3.5-turbo-1106", | |
| "claude-2.1", | |
| "bard-feb-2024", | |
| }, | |
| "gpt-4-0125-preview": { | |
| "gpt-4-1106-preview", | |
| "gpt-4-0613", | |
| "gpt-3.5-turbo-0613", | |
| "claude-2.1", | |
| "mistral-medium", | |
| "bard-feb-2024", | |
| }, | |
| "gpt-3.5-turbo-0613": {"claude-instant-1", "gpt-4-0613", "claude-2.1"}, | |
| "gpt-3.5-turbo-1106": {"gpt-4-0613", "claude-instant-1", "gpt-3.5-turbo-0613"}, | |
| "gpt-3.5-turbo-0125": { | |
| "gpt-4-0613", | |
| "gpt-4-1106-preview", | |
| "gpt-3.5-turbo-0613", | |
| "gpt-3.5-turbo-1106", | |
| "mixtral-8x7b-instruct-v0.1", | |
| }, | |
| "qwen1.5-72b-chat": { | |
| "gpt-3.5-turbo-0125", | |
| "gpt-4-0613", | |
| "gpt-4-1106-preview", | |
| "llama-2-70b-chat", | |
| "mixtral-8x7b-instruct-v0.1", | |
| "mistral-medium", | |
| "yi-34b-chat", | |
| }, | |
| "qwen1.5-7b-chat": { | |
| "gpt-3.5-turbo-0125", | |
| "starling-lm-7b-alpha", | |
| "llama-2-70b-chat", | |
| "openchat-3.5", | |
| "mixtral-8x7b-instruct-v0.1", | |
| }, | |
| "qwen1.5-4b-chat": { | |
| "llama-2-70b-chat", | |
| "llama-2-13b-chat", | |
| "llama-2-7b-chat", | |
| "openchat-3.5", | |
| }, | |
| "openchat-3.5-0106": { | |
| "gpt-3.5-turbo-0125", | |
| "gpt-3.5-turbo-0613", | |
| "llama-2-70b-chat", | |
| "openchat-3.5", | |
| "mixtral-8x7b-instruct-v0.1", | |
| }, | |
| "nous-hermes-2-mixtral-8x7b-dpo": { | |
| "gpt-4-1106-preview", | |
| "claude-2.1", | |
| "mistral-medium", | |
| "gpt-3.5-turbo-0613", | |
| "mixtral-8x7b-instruct-v0.1", | |
| }, | |
| "mistral-7b-instruct-v0.2": { | |
| "llama-2-70b-chat", | |
| "mixtral-8x7b-instruct-v0.1", | |
| "starling-lm-7b-alpha", | |
| "openhermes-2.5-mistral-7b", | |
| }, | |
| "solar-10.7b-instruct-v1.0": { | |
| "mixtral-8x7b-instruct-v0.1", | |
| "gpt-3.5-turbo-0613", | |
| "llama-2-70b-chat", | |
| }, | |
| "mistral-medium": { | |
| "gpt-3.5-turbo-0125", | |
| "gpt-3.5-turbo-0613", | |
| "gpt-4-1106-preview", | |
| "mixtral-8x7b-instruct-v0.1", | |
| "bard-feb-2024", | |
| }, | |
| "mixtral-8x7b-instruct-v0.1": { | |
| "gpt-3.5-turbo-0125", | |
| "gpt-3.5-turbo-0613", | |
| "gpt-4-1106-preview", | |
| "llama-2-70b-chat", | |
| }, | |
| "claude-2.1": {"gpt-4-1106-preview", "gpt-4-0613", "claude-1"}, | |
| "claude-2.0": {"gpt-4-1106-preview", "gpt-4-0613", "claude-1"}, | |
| "claude-1": {"claude-2.1", "gpt-4-0613", "gpt-3.5-turbo-0613"}, | |
| "claude-instant-1": {"gpt-3.5-turbo-0125", "claude-2.1"}, | |
| "gemini-pro": {"gpt-4-1106-preview", "gpt-4-0613", "gpt-3.5-turbo-0613"}, | |
| "gemini-pro-dev-api": { | |
| "gpt-4-1106-preview", | |
| "gpt-4-0613", | |
| "gpt-3.5-turbo-0613", | |
| "bard-feb-2024", | |
| }, | |
| "bard-jan-24-gemini-pro": { | |
| "gpt-4-1106-preview", | |
| "gpt-4-0613", | |
| "gpt-3.5-turbo-0613", | |
| "gemini-pro-dev-api", | |
| }, | |
| "bard-feb-2024": { | |
| "gpt-4-1106-preview", | |
| "gpt-4-0613", | |
| "gpt-3.5-turbo-0613", | |
| "bard-jan-24-gemini-pro", | |
| }, | |
| "deepseek-llm-67b-chat": { | |
| "gpt-4-1106-preview", | |
| "gpt-4-turbo", | |
| "gpt-3.5-turbo-0613", | |
| }, | |
| "llama2-70b-steerlm-chat": { | |
| "llama-2-70b-chat", | |
| "tulu-2-dpo-70b", | |
| "yi-34b-chat", | |
| }, | |
| "stripedhyena-nous-7b": { | |
| "starling-lm-7b-alpha", | |
| "openhermes-2.5-mistral-7b", | |
| "mistral-7b-instruct", | |
| "llama-2-7b-chat", | |
| }, | |
| "deluxe-chat-v1.1": {"gpt-4-0613", "gpt-4-1106-preview"}, | |
| "deluxe-chat-v1.2": {"gpt-4-0613", "gpt-4-1106-preview"}, | |
| "pplx-7b-online": {"gpt-3.5-turbo-0125", "llama-2-70b-chat"}, | |
| "pplx-70b-online": {"gpt-3.5-turbo-0125", "llama-2-70b-chat"}, | |
| "openhermes-2.5-mistral-7b": { | |
| "gpt-3.5-turbo-0613", | |
| "openchat-3.5", | |
| "zephyr-7b-beta", | |
| }, | |
| "dolphin-2.2.1-mistral-7b": { | |
| "gpt-3.5-turbo-0613", | |
| "vicuna-33b", | |
| "starling-lm-7b-alpha", | |
| "openhermes-2.5-mistral-7b", | |
| }, | |
| "starling-lm-7b-alpha": {"gpt-3.5-turbo-0613", "openchat-3.5", "zephyr-7b-beta"}, | |
| "tulu-2-dpo-70b": {"gpt-3.5-turbo-0613", "vicuna-33b", "claude-instant-1"}, | |
| "yi-34b-chat": {"gpt-3.5-turbo-0613", "vicuna-33b", "claude-instant-1"}, | |
| "openchat-3.5": {"gpt-3.5-turbo-0613", "llama-2-70b-chat", "zephyr-7b-beta"}, | |
| "chatglm3-6b": {"yi-34b-chat", "qwen-14b-chat"}, | |
| "qwen-14b-chat": {"vicuna-13b", "llama-2-13b-chat", "llama-2-70b-chat"}, | |
| "zephyr-7b-alpha": {"mistral-7b-instruct", "llama-2-13b-chat"}, | |
| "zephyr-7b-beta": { | |
| "mistral-7b-instruct", | |
| "llama-2-13b-chat", | |
| "llama-2-7b-chat", | |
| "wizardlm-13b", | |
| }, | |
| "llama-2-70b-chat": {"gpt-3.5-turbo-0125", "claude-instant-1"}, | |
| "llama-2-13b-chat": {"mistral-7b-instruct", "vicuna-13b", "llama-2-70b-chat"}, | |
| "llama-2-7b-chat": {"mistral-7b-instruct", "vicuna-7b", "llama-2-13b-chat"}, | |
| "mistral-7b-instruct": { | |
| "llama-2-7b-chat", | |
| "llama-2-13b-chat", | |
| "llama-2-70b-chat", | |
| }, | |
| "vicuna-33b": {"llama-2-70b-chat", "gpt-3.5-turbo-0613", "claude-instant-1"}, | |
| "vicuna-13b": {"llama-2-13b-chat", "llama-2-70b-chat"}, | |
| "vicuna-7b": {"llama-2-7b-chat", "mistral-7b-instruct", "llama-2-13b-chat"}, | |
| "wizardlm-70b": {"gpt-3.5-turbo-0613", "vicuna-33b", "claude-instant-1"}, | |
| } | |
| SAMPLING_BOOST_MODELS = [ | |
| # "claude-2.1", | |
| # "gpt-4-0613", | |
| # "gpt-4-0314", | |
| # "gpt-4-1106-preview", | |
| # "gpt-4-0125-preview", | |
| "gpt-3.5-turbo-0125", | |
| # "mistral-medium", | |
| "nous-hermes-2-mixtral-8x7b-dpo", | |
| "openchat-3.5-0106", | |
| "qwen1.5-72b-chat", | |
| "qwen1.5-7b-chat", | |
| "qwen1.5-4b-chat", | |
| # "mistral-7b-instruct-v0.2", | |
| ] | |
| # outage models won't be sampled. | |
| OUTAGE_MODELS = [] | |
| def get_sample_weight(model): | |
| if model in OUTAGE_MODELS: | |
| return 0 | |
| weight = SAMPLING_WEIGHTS.get(model, 1.0) | |
| if model in SAMPLING_BOOST_MODELS: | |
| weight *= 5 | |
| return weight | |
| def get_battle_pair(): | |
| if len(models) == 1: | |
| return models[0], models[0] | |
| model_weights = [] | |
| for model in models: | |
| weight = get_sample_weight(model) | |
| 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) | |
| 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, 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() | |
| 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] | |
| + [""] | |
| + [ | |
| no_change_btn, | |
| ] | |
| * 6 | |
| + [""] | |
| ) | |
| model_list = [states[i].model_name for i in range(num_sides)] | |
| flagged = moderation_filter(text, model_list) | |
| 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] | |
| + [ | |
| no_change_btn, | |
| ] | |
| * 6 | |
| + [""] | |
| ) | |
| text = text[:INPUT_CHAR_LEN_LIMIT] # Hard cut-off | |
| for i in range(num_sides): | |
| states[i].conv.append_message(states[i].conv.roles[0], 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] | |
| + [""] | |
| + [ | |
| 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, | |
| ) | |
| ) | |
| is_gemini = [] | |
| for i in range(num_sides): | |
| is_gemini.append(states[i].model_name in ["gemini-pro", "gemini-pro-dev-api"]) | |
| 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_gemini[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 = """ | |
| # ⚔️ 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) | | |
| ## 📜 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. | |
| ## 🏆 Arena Elo [Leaderboard](https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboard) | |
| We collect **200K+** human votes to compute an Elo-based LLM leaderboard. | |
| Find out who is the 🥇LLM Champion! | |
| ## 👇 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"🔍 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("", elem_id="notice_markdown") | |
| with gr.Row(): | |
| leftvote_btn = gr.Button( | |
| value="👈 A is better", visible=False, interactive=False | |
| ) | |
| rightvote_btn = gr.Button( | |
| value="👉 B is better", visible=False, interactive=False | |
| ) | |
| tie_btn = gr.Button(value="🤝 Tie", visible=False, interactive=False) | |
| bothbad_btn = gr.Button( | |
| value="👎 Both are bad", visible=False, interactive=False | |
| ) | |
| with gr.Row(): | |
| textbox = gr.Textbox( | |
| show_label=False, | |
| placeholder="👉 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="🎲 New Round", interactive=False) | |
| regenerate_btn = gr.Button(value="🔄 Regenerate", interactive=False) | |
| share_btn = gr.Button(value="📷 Share") | |
| with gr.Accordion("Parameters", open=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") | |
| # 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], | |
| states + chatbots + [textbox] + 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], | |
| 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 | |
| ) | |
| return states + model_selectors | |