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 = "

展示你的机器学习模型

" 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(server_name="0.0.0.0", share=True, server_port=PORT, auth=AUTHENTICATION)