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