import argparse import datetime import json import os import time import gradio as gr import requests from mplug_owl2.conversation import (default_conversation, conv_templates, SeparatorStyle) from mplug_owl2.constants import LOGDIR from mplug_owl2.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": "mPLUG-Owl2 Client"} no_change_btn = gr.Button.update() enable_btn = gr.Button.update(interactive=True) disable_btn = gr.Button.update(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.update(visible=True) if "model" in url_params: model = url_params["model"] if model in models: dropdown_update = gr.Dropdown.update( 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.update( 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 = text + '<|image|>' text = '<|image|>' + text text = (text, image, image_process_mode) if len(state.get_images(return_pil=True)) > 0: 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 = "mplug_owl2" 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] = "▌" 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 + "▌" 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(start_tstamp, 4), "state": state.dict(), "images": all_image_hash, "ip": request.client.host, } fout.write(json.dumps(data) + "\n") title_markdown = ("""

mPLUG-Owl

mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration

If you like our project, please give us a star ✨ on Github for latest update.
""") 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): textbox = gr.Textbox(show_label=False, placeholder="Enter text and press ENTER", container=False) with gr.Blocks(title="mPLUG-Owl2", 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) cur_dir = os.path.dirname(os.path.abspath(__file__)) gr.Examples(examples=[ [f"{cur_dir}/examples/extreme_ironing.jpg", "What is unusual about this image?"], [f"{cur_dir}/examples/Rebecca_(1939_poster)_Small.jpeg", "What is the name of the movie in the poster?"], ], inputs=[imagebox, textbox]) with gr.Accordion("Parameters", open=True) 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="mPLUG-Owl2 Chatbot", height=600) 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="⚠ī¸ Flag", interactive=False) #stop_btn = gr.Button(value="⏚ī¸ Stop Generation", interactive=False) regenerate_btn = gr.Button(value="🔄 Regenerate", interactive=False) clear_btn = gr.Button(value="🗑ī¸ 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], queue=False ) downvote_btn.click( downvote_last_response, [state, model_selector], [textbox, upvote_btn, downvote_btn, flag_btn], queue=False ) flag_btn.click( flag_last_response, [state, model_selector], [textbox, upvote_btn, downvote_btn, flag_btn], queue=False ) regenerate_btn.click( regenerate, [state, 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 ) 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 ) submit_btn.click( 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 ) if args.model_list_mode == "once": demo.load( load_demo, [url_params], [state, model_selector], _js=get_window_url_params, queue=False ) 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=10) 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) demo.queue( concurrency_count=args.concurrency_count, api_open=False ).launch( server_name=args.host, server_port=args.port, share=False )