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| import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染 | |
| import gradio as gr | |
| from predict import predict | |
| from funtional_picture import infer_text2img | |
| from toolbox import format_io, find_free_port, get_conf | |
| import numpy as np | |
| # 建议您复制一个config_private.py放自己的秘密, 如API和代理网址, 避免不小心传github被别人看到 | |
| proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT = \ | |
| get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT') | |
| # 如果WEB_PORT是-1, 则随机选取WEB端口 | |
| PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT | |
| if not AUTHENTICATION: AUTHENTICATION = None | |
| initial_prompt = "Serve me as a writing and programming assistant." | |
| title_html = "<h1 align=\"center\">展示你的机器学习模型</h1>" | |
| description = """""" | |
| # 问询记录, python 版本建议3.9+（越新越好） | |
| import logging | |
| os.makedirs("work_log", exist_ok=True) | |
| try:logging.basicConfig(filename="work_log/chat_secrets.log", level=logging.INFO, encoding="utf-8") | |
| except:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO) | |
| print("所有问询记录将自动保存在本地目录./gpt_log/chat_secrets.log, 请注意自我隐私保护哦！") | |
| # 一些普通功能模块 | |
| from functional import get_functionals | |
| functional = get_functionals() | |
| # 处理markdown文本格式的转变 | |
| gr.Chatbot.postprocess = format_io | |
| # 做一些外观色彩上的调整 | |
| from theme import adjust_theme, advanced_css | |
| set_theme = adjust_theme() | |
| cancel_handles = [] | |
| with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as demo: | |
| gr.HTML(title_html) | |
| with gr.Tab("ChatGPT"): | |
| with gr.Row().style(equal_height=True): | |
| with gr.Column(scale=2): | |
| chatbot = gr.Chatbot() | |
| chatbot.style(height=CHATBOT_HEIGHT/2) | |
| history = gr.State([]) | |
| with gr.Row(): | |
| txt = gr.Textbox(show_label=False, placeholder="Input question here.").style(container=False) | |
| with gr.Row(): | |
| submitBtn = gr.Button("提交", variant="primary") | |
| with gr.Row(): | |
| resetBtn = gr.Button("重置", variant="secondary"); | |
| resetBtn.style(size="sm") | |
| stopBtn = gr.Button("停止", variant="secondary"); | |
| stopBtn.style(size="sm") | |
| with gr.Column(scale=1): | |
| with gr.Row(): | |
| from check_proxy import check_proxy | |
| status = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行。当前模型: {LLM_MODEL} \n {check_proxy(proxies)}") | |
| with gr.Accordion("基础功能区", open=True) as area_basic_fn: | |
| with gr.Row(): | |
| for k in functional: | |
| variant = functional[k]["Color"] if "Color" in functional[k] else "secondary" | |
| functional[k]["Button"] = gr.Button(k, variant=variant) | |
| with gr.Accordion("展开SysPrompt & 交互界面布局 & Github地址", open=True): | |
| system_prompt = gr.Textbox(show_label=True, placeholder=f"System Prompt", label="System prompt", value=initial_prompt) | |
| top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)",) | |
| temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0, step=0.01, interactive=True, label="Temperature",) | |
| checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区"], value=["基础功能区", "函数插件区"], label="显示/隐藏功能区") | |
| gr.Markdown(description) | |
| with gr.Tab("AI绘画"): | |
| examples = [ | |
| ["铁马冰河入梦来, 梦幻, 插画"], | |
| ["东临碣石, 以观沧海, 波涛汹涌, 插画"], | |
| ["孤帆远影碧空尽，惟见长江天际流,油画"], | |
| ["动漫化，帅气，插画"], | |
| ["女孩背影, 日落, 唯美插画"], | |
| ] | |
| with gr.Row(): | |
| with gr.Column(scale=1, ): | |
| image_out = gr.Image(label='输出(output)') | |
| with gr.Column(scale=1, ): | |
| image_in = gr.Image(source='upload', elem_id="image_upload", type="pil", label="参考图（非必须）(ref)") | |
| prompt = gr.Textbox(label='提示词(prompt)') | |
| submit_btn = gr.Button("生成图像(Generate)") | |
| with gr.Row(scale=0.5): | |
| guide = gr.Slider(2, 15, value=7, step=0.1, label='文本引导强度(guidance scale)') | |
| steps = gr.Slider(10, 30, value=20, step=1, label='迭代次数(inference steps)') | |
| width = gr.Slider(384, 640, value=512, step=64, label='宽度(width)') | |
| height = gr.Slider(384, 640, value=512, step=64, label='高度(height)') | |
| strength = gr.Slider(0, 1.0, value=0.8, step=0.02, label='参考图改变程度(strength)') | |
| ex = gr.Examples(examples, fn=infer_text2img, inputs=[prompt, guide, steps, width, height], | |
| outputs=image_out) | |
| submit_btn.click(fn=infer_text2img, inputs=[prompt, guide, steps, width, height, image_in, strength], | |
| outputs=image_out) | |
| # demo.queue(concurrency_count=1, max_size=8).launch() | |
| # 功能区显示开关与功能区的互动 | |
| def fn_area_visibility(a): | |
| ret = {} | |
| ret.update({area_basic_fn: gr.update(visible=("基础功能区" in a))}) | |
| return ret | |
| checkboxes.select(fn_area_visibility, [checkboxes], [area_basic_fn]) | |
| # 整理反复出现的控件句柄组合 | |
| input_combo = [txt, top_p, temperature, chatbot, history, system_prompt] | |
| output_combo = [chatbot, history, status] | |
| predict_args = dict(fn=predict, inputs=input_combo, outputs=output_combo) | |
| empty_txt_args = dict(fn=lambda: "", inputs=[], outputs=[txt]) # 用于在提交后清空输入栏 | |
| # 提交按钮、重置按钮 | |
| cancel_handles.append(txt.submit(**predict_args)) #; txt.submit(**empty_txt_args) 在提交后清空输入栏 | |
| cancel_handles.append(submitBtn.click(**predict_args)) #; submitBtn.click(**empty_txt_args) 在提交后清空输入栏 | |
| resetBtn.click(lambda: ([], [], "已重置"), None, output_combo) | |
| # 基础功能区的回调函数注册 | |
| for k in functional: | |
| click_handle = functional[k]["Button"].click(predict, [*input_combo, gr.State(True), gr.State(k)], output_combo) | |
| cancel_handles.append(click_handle) | |
| cancel_handles.append(click_handle) | |
| # 终止按钮的回调函数注册 | |
| stopBtn.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles) | |
| # gradio的inbrowser触发不太稳定，回滚代码到原始的浏览器打开函数 | |
| def auto_opentab_delay(): | |
| import threading, webbrowser, time | |
| print(f"如果浏览器没有自动打开，请复制并转到以下URL: http://localhost:{PORT}") | |
| def open(): | |
| time.sleep(2) | |
| webbrowser.open_new_tab(f"http://localhost:{PORT}") | |
| threading.Thread(target=open, name="open-browser", daemon=True).start() | |
| auto_opentab_delay() | |
| demo.title = "展示你的机器学习模型" | |
| demo.queue(concurrency_count=CONCURRENT_COUNT).launch() | |