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								main.py
									
									
									
									
									
								
							
							
						
						
									
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								main.py
									
									
									
									
									
								
							@ -1,7 +1,7 @@
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import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
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import gradio as gr
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from predict import predict
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from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf
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from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper
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# 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
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proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT = \
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@ -87,8 +87,12 @@ with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as de
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                system_prompt = gr.Textbox(show_label=True, placeholder=f"System Prompt", label="System prompt", value=initial_prompt)
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                top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)",)
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                temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0, step=0.01, interactive=True, label="Temperature",)
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                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")
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                checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区", "输入区2"], value=["基础功能区", "函数插件区"], label="显示/隐藏功能区")
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                gr.Markdown(description)
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            with gr.Accordion("输入区", open=True, visible=False) as input_crazy_fn:
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                with gr.Row():
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                    txt2 = gr.Textbox(show_label=False, placeholder="Input question here.", label="输入区2").style(container=False)
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    # 功能区显示开关与功能区的互动
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    def fn_area_visibility(a):
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        ret = {}
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@ -97,17 +101,16 @@ with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as de
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        return ret
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    checkboxes.select(fn_area_visibility, [checkboxes], [area_basic_fn, area_crazy_fn] )
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    # 整理反复出现的控件句柄组合
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    input_combo = [txt, top_p, temperature, chatbot, history, system_prompt]
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    input_combo = [txt, txt2, top_p, temperature, chatbot, history, system_prompt]
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    output_combo = [chatbot, history, status]
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    predict_args = dict(fn=predict, inputs=input_combo, outputs=output_combo)
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    empty_txt_args = dict(fn=lambda: "", inputs=[], outputs=[txt]) # 用于在提交后清空输入栏
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    predict_args = dict(fn=ArgsGeneralWrapper(predict), inputs=input_combo, outputs=output_combo)
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    # 提交按钮、重置按钮
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    cancel_handles.append(txt.submit(**predict_args)) #; txt.submit(**empty_txt_args) 在提交后清空输入栏
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    cancel_handles.append(submitBtn.click(**predict_args)) #; submitBtn.click(**empty_txt_args) 在提交后清空输入栏
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    cancel_handles.append(txt.submit(**predict_args))
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    cancel_handles.append(submitBtn.click(**predict_args))
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    resetBtn.click(lambda: ([], [], "已重置"), None, output_combo)
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    # 基础功能区的回调函数注册
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    for k in functional:
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        click_handle = functional[k]["Button"].click(predict, [*input_combo, gr.State(True), gr.State(k)], output_combo)
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        click_handle = functional[k]["Button"].click(fn=ArgsGeneralWrapper(predict), inputs=[*input_combo, gr.State(True), gr.State(k)], outputs=output_combo)
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        cancel_handles.append(click_handle)
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    # 文件上传区,接收文件后与chatbot的互动
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    file_upload.upload(on_file_uploaded, [file_upload, chatbot, txt], [chatbot, txt])
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								toolbox.py
									
									
									
									
									
								
							
							
						
						
									
										16
									
								
								toolbox.py
									
									
									
									
									
								
							@ -2,6 +2,18 @@ import markdown, mdtex2html, threading, importlib, traceback, importlib, inspect
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from show_math import convert as convert_math
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from functools import wraps, lru_cache
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def ArgsGeneralWrapper(f):
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    """
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        装饰器函数,用于重组输入参数,改变输入参数的顺序与结构。
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    """
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    def decorated(txt, txt2, top_p, temperature, chatbot, history, system_prompt, *args, **kwargs):
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        txt_passon = txt
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        if txt == "" and txt2 != "": txt_passon = txt2
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        yield from f(txt_passon, top_p, temperature, chatbot, history, system_prompt, *args, **kwargs)
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    return decorated
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def get_reduce_token_percent(text):
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    try:
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        # text = "maximum context length is 4097 tokens. However, your messages resulted in 4870 tokens"
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@ -116,7 +128,7 @@ def CatchException(f):
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            from toolbox import get_conf
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            proxies, = get_conf('proxies')
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            tb_str = '```\n' + traceback.format_exc() + '```'
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            if len(chatbot) == 0: chatbot.append(["插件调度异常","异常原因"])
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            if chatbot is None or len(chatbot) == 0: chatbot = [["插件调度异常","异常原因"]]
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            chatbot[-1] = (chatbot[-1][0], f"[Local Message] 实验性函数调用出错: \n\n{tb_str} \n\n当前代理可用性: \n\n{check_proxy(proxies)}")
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            yield chatbot, history, f'异常 {e}'
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    return decorated
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@ -129,7 +141,7 @@ def HotReload(f):
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    def decorated(*args, **kwargs):
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        fn_name = f.__name__
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        f_hot_reload = getattr(importlib.reload(inspect.getmodule(f)), fn_name)
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        yield from f_hot_reload(*args, **kwargs)
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        yield from ArgsGeneralWrapper(f_hot_reload)(*args, **kwargs)
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    return decorated
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def report_execption(chatbot, history, a, b):
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