import os import gradio as gr from llama2 import GradioLLaMA2ChatPPManager from llama2 import gen_text from styles import MODEL_SELECTION_CSS from js import GET_LOCAL_STORAGE, UPDATE_LEFT_BTNS_STATE, UPDATE_PLACEHOLDERS from templates import templates from pingpong.context import CtxLastWindowStrategy TOKEN = os.getenv('HF_TOKEN') MODEL_ID = 'meta-llama/Llama-2-70b-chat-hf' def build_prompts(ppmanager, global_context, win_size=3): dummy_ppm = copy.deepcopy(ppmanager) dummy_ppm.ctx = global_context lws = CtxLastWindowStrategy(win_size) return lws(dummy_ppm) ex_file = open("examples.txt", "r") examples = ex_file.read().split("\n") ex_btns = [] chl_file = open("channels.txt", "r") channels = chl_file.read().split("\n") channel_btns = [] def fill_up_placeholders(txt): placeholders = get_placeholders(txt) highlighted_txt = txt return ( gr.update( visible=True, value=highlighted_txt ), gr.update( visible=True if len(placeholders) >= 1 else False, placeholder=placeholders[0] if len(placeholders) >= 1 else "" ), gr.update( visible=True if len(placeholders) >= 2 else False, placeholder=placeholders[1] if len(placeholders) >= 2 else "" ), gr.update( visible=True if len(placeholders) >= 3 else False, placeholder=placeholders[2] if len(placeholders) >= 3 else "" ), "" if len(placeholders) >= 1 else txt ) async def chat_stream(idx, local_data, instruction_txtbox, chat_state): res = [ chat_state["ppmanager_type"].from_json(json.dumps(ppm)) for ppm in local_data ] ppm = res[idx] ppm.add_pingpong( PingPong(instruction_txtbox, "") ) prompt = build_prompts(ppm, "global context", 3) for result in await gen_text(prompt, hf_model=MODEL_ID, hf_token=TOKEN): ppm.append_pong(result) yield ppm.build_uis(), str(res) with gr.Blocks(css=MODEL_SELECTION_CSS, theme='gradio/soft') as demo: with gr.Column() as chat_view: idx = gr.State(0) chat_state = gr.State({ "ppmanager_type": GradioLLaMA2ChatPPManager }) local_data = gr.JSON({}, visible=False) with gr.Row(): with gr.Column(scale=1, min_width=180): gr.Markdown("GradioChat", elem_id="left-top") with gr.Column(elem_id="left-pane"): chat_back_btn = gr.Button("Back", elem_id="chat-back-btn") with gr.Accordion("Histories", elem_id="chat-history-accordion", open=True): channel_btns.append(gr.Button(channels[0], elem_classes=["custom-btn-highlight"])) for channel in channels[1:]: channel_btns.append(gr.Button(channel, elem_classes=["custom-btn"])) with gr.Column(scale=8, elem_id="right-pane"): with gr.Column( elem_id="initial-popup", visible=False ) as example_block: with gr.Row(scale=1): with gr.Column(elem_id="initial-popup-left-pane"): gr.Markdown("GradioChat", elem_id="initial-popup-title") gr.Markdown("Making the community's best AI chat models available to everyone.") with gr.Column(elem_id="initial-popup-right-pane"): gr.Markdown("Chat UI is now open sourced on Hugging Face Hub") gr.Markdown("check out the [↗ repository](https://huggingface.co/spaces/chansung/test-multi-conv)") with gr.Column(scale=1): gr.Markdown("Examples") with gr.Row(): for example in examples: ex_btns.append(gr.Button(example, elem_classes=["example-btn"])) with gr.Column(elem_id="aux-btns-popup", visible=True): with gr.Row(): stop = gr.Button("Stop", elem_classes=["aux-btn"]) regenerate = gr.Button("Regen", interactive=False, elem_classes=["aux-btn"]) clean = gr.Button("Clean", elem_classes=["aux-btn"]) with gr.Accordion("Context Inspector", elem_id="aux-viewer", open=False): context_inspector = gr.Textbox( "", elem_id="aux-viewer-inspector", label="", lines=30, max_lines=50, ) chatbot = gr.Chatbot(elem_id='chatbot') instruction_txtbox = gr.Textbox(placeholder="Ask anything", label="", elem_id="prompt-txt") with gr.Accordion("Example Templates", open=False): template_txt = gr.Textbox(visible=False) template_md = gr.Markdown(label="Chosen Template", visible=False, elem_classes="template-txt") with gr.Row(): placeholder_txt1 = gr.Textbox(label="placeholder #1", visible=False, interactive=True) placeholder_txt2 = gr.Textbox(label="placeholder #2", visible=False, interactive=True) placeholder_txt3 = gr.Textbox(label="placeholder #3", visible=False, interactive=True) for template in templates: with gr.Tab(template['title']): gr.Examples( template['template'], inputs=[template_txt], outputs=[template_md, placeholder_txt1, placeholder_txt2, placeholder_txt3, instruction_txtbox], run_on_click=True, fn=fill_up_placeholders, ) with gr.Accordion("Control Panel", open=False) as control_panel: with gr.Column(): with gr.Column(): gr.Markdown("#### Global context") with gr.Accordion("global context will persist during conversation, and it is placed at the top of the prompt", open=False): global_context = gr.Textbox( "global context", lines=5, max_lines=10, interactive=True, elem_id="global-context" ) # gr.Markdown("#### Internet search") # with gr.Row(): # internet_option = gr.Radio(choices=["on", "off"], value="off", label="mode") # serper_api_key = gr.Textbox( # value= "" if args.serper_api_key is None else args.serper_api_key, # placeholder="Get one by visiting serper.dev", # label="Serper api key" # ) gr.Markdown("#### GenConfig for **response** text generation") with gr.Row(): res_temp = gr.Slider(0.0, 2.0, 0, step=0.1, label="temp", interactive=True) res_topp = gr.Slider(0.0, 2.0, 0, step=0.1, label="top_p", interactive=True) res_topk = gr.Slider(20, 1000, 0, step=1, label="top_k", interactive=True) res_rpen = gr.Slider(0.0, 2.0, 0, step=0.1, label="rep_penalty", interactive=True) res_mnts = gr.Slider(64, 8192, 0, step=1, label="new_tokens", interactive=True) res_beams = gr.Slider(1, 4, 0, step=1, label="beams") res_cache = gr.Radio([True, False], value=0, label="cache", interactive=True) res_sample = gr.Radio([True, False], value=0, label="sample", interactive=True) res_eosid = gr.Number(value=0, visible=False, precision=0) res_padid = gr.Number(value=0, visible=False, precision=0) with gr.Column(visible=False): gr.Markdown("#### GenConfig for **summary** text generation") with gr.Row(): sum_temp = gr.Slider(0.0, 2.0, 0, step=0.1, label="temp", interactive=True) sum_topp = gr.Slider(0.0, 2.0, 0, step=0.1, label="top_p", interactive=True) sum_topk = gr.Slider(20, 1000, 0, step=1, label="top_k", interactive=True) sum_rpen = gr.Slider(0.0, 2.0, 0, step=0.1, label="rep_penalty", interactive=True) sum_mnts = gr.Slider(64, 8192, 0, step=1, label="new_tokens", interactive=True) sum_beams = gr.Slider(1, 8, 0, step=1, label="beams", interactive=True) sum_cache = gr.Radio([True, False], value=0, label="cache", interactive=True) sum_sample = gr.Radio([True, False], value=0, label="sample", interactive=True) sum_eosid = gr.Number(value=0, visible=False, precision=0) sum_padid = gr.Number(value=0, visible=False, precision=0) with gr.Column(): gr.Markdown("#### Context managements") with gr.Row(): ctx_num_lconv = gr.Slider(2, 10, 3, step=1, label="number of recent talks to keep", interactive=True) ctx_sum_prompt = gr.Textbox( "summarize our conversations. what have we discussed about so far?", label="design a prompt to summarize the conversations", visible=False ) instruction_txtbox.submit( chat_stream, [idx, local_data, instruction_txtbox, chat_state] [chatbot, local_data] ) demo.launch()