import argparse import datetime import json import os import time import gradio as gr import requests from llava.conversation import (default_conversation, conv_templates, SeparatorStyle) from llava.constants import LOGDIR from llava.utils import (build_logger, server_error_msg, violates_moderation, moderation_msg) import hashlib from PIL import Image, ImageDraw,ImageFont def get_scale_factor(original_size): original_width, original_height = original_size new_width = min(nearest_multiple_of_224_at_least_224(original_width, ceiling=False), 1344) scale_factor = new_width / original_width return scale_factor def nearest_multiple_of_224_at_least_224(num, ceiling=False): if num <= 224: return 224 division, remainder = divmod(num, 224) if ceiling and remainder > 0: return (division + 1) * 224 if remainder < 112: return division * 224 else: return (division + 1) * 224 logger = build_logger("gradio_web_server", "gradio_web_server.log") headers = {"User-Agent": "UGround Client"} no_change_btn = gr.Button() enable_btn = gr.Button(interactive=True) disable_btn = gr.Button(interactive=False) priority = { "vicuna-13b": "aaaaaaa", "koala-13b": "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 image is not None: # 默认的宽度和高度 default_width = (1344, 896) # 读取图像 original_width, original_height = image.size # Resize逻辑基于宽度和高度比较 if original_width >= original_height: # 基于宽度调整大小 new_width = default_width[0] resize_scale = new_width / original_width new_height = round(original_height * resize_scale) else: # 基于高度调整大小 new_width = default_width[1] resize_scale = new_width / original_width new_height = round(original_height * resize_scale) # 调整图像大小 image = image.resize((new_width, new_height)) 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[:16384] # Hard cut-off if image is not None: text = text[:16384] # Hard cut-off for images if '' not in text: # text = '' + text text ="In the screenshot, where are the pixel coordinates (x, y) of the element corresponding to "+ f"\"{text}\"?" + '\n' 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 model_name="osunlp/UGround" 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 # if "llava" in model_name.lower(): # if 'llama-2' in model_name.lower(): # template_name = "llava_llama_2" # elif "mistral" in model_name.lower() or "mixtral" in model_name.lower(): # if 'orca' in model_name.lower(): # template_name = "mistral_orca" # elif 'hermes' in model_name.lower(): # template_name = "chatml_direct" # else: # template_name = "mistral_instruct" # elif 'llava-v1.6-34b' in model_name.lower(): # template_name = "chatml_direct" # elif "v1" in model_name.lower(): # if 'mmtag' in model_name.lower(): # template_name = "v1_mmtag" # elif 'plain' in model_name.lower() and 'finetune' not in model_name.lower(): # template_name = "v1_mmtag" # else: # template_name = "llava_v1" # elif "mpt" in model_name.lower(): # template_name = "mpt" # else: # if 'mmtag' in model_name.lower(): # template_name = "v0_mmtag" # elif 'plain' in model_name.lower() and 'finetune' not in model_name.lower(): # template_name = "v0_mmtag" # else: # template_name = "llava_v0" # elif "mpt" in model_name: # template_name = "mpt_text" # elif "llama-2" in model_name: # template_name = "llama_2" # else: # template_name = "vicuna_v1" template_name='llava_v1' 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), 16384), "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] = "▌" 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=20) 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 + "▌" 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 = (""" # UGround: Universal Visual Grounding For GUI Agents [[Project Page]](https://osu-nlp-group.github.io/UGround/) [[Paper]](https://github.com/OSU-NLP-Group/UGround/blob/gh-pages/static/papers/UGround_paper.pdf) [[Code]](https://github.com/OSU-NLP-Group/UGround) [[Model]](https://huggingface.co/osunlp/UGround) """) 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 model [License](https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md) of LLaMA, [Terms of Use](https://openai.com/policies/terms-of-use) of the data generated by OpenAI, and [Privacy Practices](https://chrome.google.com/webstore/detail/sharegpt-share-your-chatg/daiacboceoaocpibfodeljbdfacokfjb) of ShareGPT. 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 an element description (referring expression) and press ENTER", container=False) with gr.Blocks(title="UGround", 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}/amazon.jpg", "Where is the search bar at the top of the page?"], # [f"{cur_dir}/examples/waterview.jpg", "What are the things I should be cautious about when I visit here?"], ], inputs=[imagebox, textbox]) with gr.Accordion("Parameters", open=False) as parameter_row: temperature = gr.Slider(minimum=0.0, maximum=1.0, value=0.1, 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=16384, value=16384, step=64, interactive=True, label="Max output tokens",) with gr.Column(scale=8): chatbot = gr.Chatbot( elem_id="chatbot", label="UGround 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="👍 Upvote", interactive=False) downvote_btn = gr.Button(value="👎 Downvote", interactive=False) flag_btn = gr.Button(value="⚠️ Flag", interactive=False) #stop_btn = gr.Button(value="⏹️ Stop Generation", interactive=False) regenerate_btn = gr.Button(value="🔄 Regenerate", interactive=False) clear_btn = gr.Button(value="🗑️ 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=2) 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 )