app.py

"""
"""
import random
import config
from app_util import *

user_simulator_pre_doc = """\
You are a helpful assistant, and the agent acts as user. 
"""

user_simulator_post_doc = """\
## How does it work?
There are maily two types of user simulator:
- prompt-based user-simulator (role-play)
- model-based user-simulator

This demo is a model-based user simulator.
"""


# In most cases, large language models (LLMs) are used to serve as assistant generator.
# Besides, it can also used as user simulator.

assistant_simulator_pre_doc = """\
You are a user, and the agent acts as assistant.
"""

assistant_simulator_post_doc = """\
"""

self_chat_pre_doc = """\
Self-chat is a demo which make the model talk to itself. Dual-agent. 
"""

self_chat_post_doc = """\
## How does it work?
It is a combination of user simulator and response generator.
"""

survey = """\
## knowledge distillation 知识蒸馏

Essentially, it is a form of model compression.

## distilling knowledge != knowledge distillation

知识的形式可以是 QA纯文本，也可以是 QA+概率。

## 有不用概率的知识蒸馏吗？
"""
gr.set_static_paths(paths=["assets/"])

"""
<div class="avatar-container"><img src="file=assets/man.png" class="avatar-image" alt="user avatar"></div>
"""


css="""
.image_center {
      display: block;
      margin: auto;
}
"""

with gr.Blocks(head=None, css=css) as demo:
    # Knowledge Distillation through Self Chatting
    # Distilling the Knowledge from LLM through Self Chatting
    # Generating Synthetic Data through Self Chat
    gr.HTML("""<h1 align="center">Generating Synthetic Data via Self-Chatting</h1>""")
    with gr.Row():
        with gr.Column(scale=5):
            system = gr.Dropdown(
                choices=system_list,
                # value=system_list[0],
                allow_custom_value=True,
                interactive=True,
                label="System message",
                scale=5,
            )

            chatbot = gr.Chatbot(show_copy_button=True,
                                 show_share_button=True,
                                 # avatar_images=("assets/man.png", "assets/bot.png"),
                                 avatar_images=("assets/man.png", "assets/女客服.png"),
                                 likeable=True)

            # gr.Textbox("For faster inference, you can build locally with  ")
            # ss
            with gr.Tab("Self Chat") as tab_dual_agent:
                gr.Markdown(self_chat_pre_doc)
                input_text_1 = gr.Textbox(show_label=False, placeholder="...", lines=10, visible=False)
                generate_btn = gr.Button("🤖Self-Chat🤖", variant="primary")
                with gr.Row():
                    retry_btn = gr.Button("🔄  Regenerate", variant="secondary", size="sm")
                    undo_btn = gr.Button("↩️ Undo", variant="secondary", size="sm")
                    # clear_btn = gr.Button("🗑️  Clear", variant="secondary", size="sm")
                    clear_btn = gr.Button("🧹 Clear History", variant="secondary", size="sm")
                gr.Markdown(self_chat_post_doc)

            # 也叫 chat-assistant, 🎧，🤖 ，💁，
            with gr.Tab("Response Generator") as tab_assistant_agent:
                gr.Markdown(assistant_simulator_pre_doc)
                with gr.Row():
                    # gr.HTML(
                    #     value='<div><img src="/file=./assets/man.png" alt="Big Boat" width="40px" height="40px"></div>',
                    #     elem_classes=["image_center"]
                    # )
                    gr.Image("assets/man.png", interactive=False, show_download_button=False, width=40, height=40,
                             min_width=40,
                             show_share_button=False, show_fullscreen_button=False, container=False,
                             elem_classes=["image_center"])
                    input_text_2 = gr.Textbox(show_label=False, lines=2, placeholder="Please type user input",
                                              container=False, scale=12)
                    generate_btn_2 = gr.Button("Send", variant="primary", min_width=80)
                with gr.Row():
                    retry_btn_2 = gr.Button("🔄  Regenerate", variant="secondary", size="sm", )
                    undo_btn_2 = gr.Button("↩️ Undo", variant="secondary", size="sm", )
                    clear_btn_2 = gr.Button("🧹 Clear History", variant="secondary", size="sm")
                gr.Markdown(assistant_simulator_post_doc)

            #
            with gr.Tab("User Simulator") as tab_user_agent:  # 👨，🔊，
                gr.Markdown(user_simulator_pre_doc)
                with gr.Row():
                    # gr.HTML(value='<div class="avatar-container"><img src="file=assets/man.png" class="avatar-image" alt="user avatar"></div>')
                    # gr.Image("assets/女客服.jpg",
                    gr.Image("assets/女客服.png",
                    # gr.Image("assets/男客服.png",
                             interactive=False, show_download_button=False, width=40, height=40,
                             min_width=40,
                             show_share_button=False, show_fullscreen_button=False, container=False, elem_classes=["image_center"])
                    input_text_3 = gr.Textbox(show_label=False, lines=2, placeholder="Please type assistant response",
                                              container=False, scale=12)
                    generate_btn_3 = gr.Button("Send", variant="primary", min_width=80)
                with gr.Row():
                    retry_btn_3 = gr.Button("🔄  Regenerate", variant="secondary", size="sm")
                    undo_btn_3 = gr.Button("↩️ Undo", variant="secondary", size="sm")
                    # clear_btn_3 = gr.Button("🗑️  Clear", variant="secondary", size="sm")
                    clear_btn_3 = gr.Button("🧹 Clear History", variant="secondary", size="sm")  # 🧹 Clear History (清除历史)
                gr.Markdown(user_simulator_post_doc)

        with gr.Column(variant="compact", scale=1, min_width=300):
            # with gr.Column():
            model = gr.Dropdown(
                ["Qwen2-0.5B-Instruct", "llama3.1", "gemini", "MiniCPM3-4B"],
                value="Qwen2-0.5B-Instruct",
                label="Model",
                interactive=True,
                # visible=False
            )
            with gr.Accordion(label="Parameters", open=True):
                slider_max_new_tokens = gr.Slider(minimum=1, maximum=4096,
                                                  value=config.DEFAULT_MAX_NEW_TOKENS, step=1, label="Max New tokens")
                slider_temperature = gr.Slider(minimum=0.1, maximum=10.0,
                                               value=config.DEFAULT_TEMPERATURE, step=0.1, label="Temperature",
                                               info="Larger temperature increase the randomness")
                slider_top_p = gr.Slider(
                    minimum=0.1,
                    maximum=1.0,
                    value=config.DEFAULT_TOP_P,
                    step=0.05,
                    label="Top-p (nucleus sampling)",
                )
                slider_top_k = gr.Slider(
                    minimum=1,
                    maximum=200,
                    value=config.DEFAULT_TOP_K,
                    step=1,
                    label="Top-k",
                )

    # TODO: gr.State 不能通过API传参。
    gr_false = gr.State(False)
    history = gr.State([{"role": "system", "content": system_list[0]}])  # 有用信息只有个system，其他和chatbot内容重叠
    system.change(reset_state, inputs=[system], outputs=[chatbot, history])

    ######## tab1: self-chat
    generate_btn.click(chat, [chatbot, history], outputs=[chatbot, history],
                       show_progress="full")
    retry_btn.click(undo_generate, [chatbot, history], outputs=[chatbot, history], show_api=False) \
        .then(chat, [chatbot, history], outputs=[chatbot, history],
              show_progress="full", show_api=False)
    undo_btn.click(undo_generate, [chatbot, history], outputs=[chatbot, history], show_api=False)
    clear_btn.click(reset_state, inputs=[system], outputs=[chatbot, history], show_api=False)

    ######## tab2:  response-generator
    generate_btn_2.click(append_user_to_history, [input_text_2, chatbot, history], outputs=[chatbot, history],
                         show_api=False) \
        .then(generate_assistant_message, [chatbot, history], outputs=[chatbot, history],
              show_progress="full", show_api=False)
    retry_btn_2.click(undo_generate, [chatbot, history], outputs=[chatbot, history], show_api=False) \
        .then(chat, [chatbot, history], outputs=[chatbot, history],
              show_progress="full", show_api=False)
    undo_btn_2.click(undo_generate, [chatbot, history], outputs=[chatbot, history], show_api=False)
    clear_btn_2.click(reset_state, inputs=[system], outputs=[chatbot, history], show_api=False) \
        .then(reset_user_input, outputs=[input_text_2], show_api=False)
    tab_assistant_agent.select(generate_assistant_message, [chatbot, history, gr_false], outputs=[chatbot, history],
              show_progress="full", show_api=False)   # 点击tab，生成response (不warning)

    ######## tab3: user-simulator
    generate_btn_3.click(append_assistant_to_history, [input_text_3, chatbot, history], outputs=[chatbot, history],
                         show_api=False) \
        .then(generate_user_message, [chatbot, history], outputs=[chatbot, history],
              show_progress="full", show_api=False)
    retry_btn_3.click(undo_generate, [chatbot, history], outputs=[chatbot, history], show_api=False) \
        .then(chat, [chatbot, history], outputs=[chatbot, history],
              show_progress="full", show_api=False)
    undo_btn_3.click(undo_generate, [chatbot, history], outputs=[chatbot, history], show_api=False)
    clear_btn_3.click(reset_state, inputs=[system], outputs=[chatbot, history], show_api=False) \
        .then(reset_user_input, outputs=[input_text_3], show_api=False)

    tab_user_agent.select(generate_user_message, [chatbot, history, gr_false], outputs=[chatbot, history],
              show_progress="full", show_api=False)  # 点击tab，生成user-input

    slider_max_new_tokens.change(set_max_new_tokens, inputs=[slider_max_new_tokens])
    slider_temperature.change(set_temperature, inputs=[slider_temperature])
    slider_top_p.change(set_top_p, inputs=[slider_top_p])
    slider_top_k.change(set_top_k, inputs=[slider_top_k])

    demo.load(lambda: gr.update(value=random.choice(system_list)), None, system, show_api=False)

# demo.queue().launch(share=False, server_name="0.0.0.0", debug=True)
# demo.queue().launch(concurrency_count=1, max_size=5)
demo.queue().launch()