ChatGLM改成多进程运行

crazy_functions/crazy_utils.py

@@ -66,7 +66,7 @@ def request_gpt_model_in_new_thread_with_ui_alive(
     chatbot.append([inputs_show_user, ""])
     yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面
     executor = ThreadPoolExecutor(max_workers=16)
-    mutable = ["", time.time()]
+    mutable = ["", time.time(), ""]
     def _req_gpt(inputs, history, sys_prompt):
         retry_op = retry_times_at_unknown_error
         exceeded_cnt = 0

crazy_functions/询问多个大语言模型.py

@@ -20,7 +20,8 @@ def 同时问询(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
     gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
         inputs=txt, inputs_show_user=txt, 
         llm_kwargs=llm_kwargs, chatbot=chatbot, history=history, 
-        sys_prompt=system_prompt
+        sys_prompt=system_prompt,
+        retry_times_at_unknown_error=0
     )
 
     history.append(txt)

docs/Dockerfile+ChatGLM

@@ -24,7 +24,7 @@ RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
 
 # 下载分支
 WORKDIR /gpt
-RUN $useProxyNetwork git clone https://github.com/binary-husky/chatgpt_academic.git -b v3.0
+RUN $useProxyNetwork git clone https://github.com/binary-husky/chatgpt_academic.git -b v3.1
 WORKDIR /gpt/chatgpt_academic
 RUN $useProxyNetwork python3 -m pip install -r requirements.txt
 RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_chatglm.txt

main.py

@@ -1,177 +1,182 @@
 import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
-import gradio as gr
-from request_llm.bridge_all import predict
-from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, DummyWith
 
-# 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, LAYOUT, API_KEY = \
-    get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'API_KEY')
+def main():
+    import gradio as gr
+    from request_llm.bridge_all import predict
+    from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, DummyWith
+    # 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, LAYOUT, API_KEY = \
+        get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'API_KEY')
 
-# 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
+    # 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
 
-from check_proxy import get_current_version
-initial_prompt = "Serve me as a writing and programming assistant."
-title_html = f"<h1 align=\"center\">ChatGPT 学术优化 {get_current_version()}</h1>"
-description =  """代码开源和更新[地址🚀](https://github.com/binary-husky/chatgpt_academic)，感谢热情的[开发者们❤️](https://github.com/binary-husky/chatgpt_academic/graphs/contributors)"""
+    from check_proxy import get_current_version
+    initial_prompt = "Serve me as a writing and programming assistant."
+    title_html = f"<h1 align=\"center\">ChatGPT 学术优化 {get_current_version()}</h1>"
+    description =  """代码开源和更新[地址🚀](https://github.com/binary-husky/chatgpt_academic)，感谢热情的[开发者们❤️](https://github.com/binary-husky/chatgpt_academic/graphs/contributors)"""
 
-# 问询记录, python 版本建议3.9+（越新越好）
-import logging
-os.makedirs("gpt_log", exist_ok=True)
-try:logging.basicConfig(filename="gpt_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！")
+    # 问询记录, python 版本建议3.9+（越新越好）
+    import logging
+    os.makedirs("gpt_log", exist_ok=True)
+    try:logging.basicConfig(filename="gpt_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 core_functional import get_core_functions
-functional = get_core_functions()
+    # 一些普通功能模块
+    from core_functional import get_core_functions
+    functional = get_core_functions()
 
-# 高级函数插件
-from crazy_functional import get_crazy_functions
-crazy_fns = get_crazy_functions()
+    # 高级函数插件
+    from crazy_functional import get_crazy_functions
+    crazy_fns = get_crazy_functions()
 
-# 处理markdown文本格式的转变
-gr.Chatbot.postprocess = format_io
+    # 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()
+    # 做一些外观色彩上的调整
+    from theme import adjust_theme, advanced_css
+    set_theme = adjust_theme()
 
-# 代理与自动更新
-from check_proxy import check_proxy, auto_update
-proxy_info = check_proxy(proxies)
+    # 代理与自动更新
+    from check_proxy import check_proxy, auto_update
+    proxy_info = check_proxy(proxies)
 
-gr_L1 = lambda: gr.Row().style()
-gr_L2 = lambda scale: gr.Column(scale=scale)
-if LAYOUT == "TOP-DOWN": 
-    gr_L1 = lambda: DummyWith()
-    gr_L2 = lambda scale: gr.Row()
-    CHATBOT_HEIGHT /= 2
+    gr_L1 = lambda: gr.Row().style()
+    gr_L2 = lambda scale: gr.Column(scale=scale)
+    if LAYOUT == "TOP-DOWN": 
+        gr_L1 = lambda: DummyWith()
+        gr_L2 = lambda scale: gr.Row()
+        CHATBOT_HEIGHT /= 2
 
-cancel_handles = []
-with gr.Blocks(title="ChatGPT 学术优化", theme=set_theme, analytics_enabled=False, css=advanced_css) as demo:
-    gr.HTML(title_html)
-    cookies = gr.State({'api_key': API_KEY, 'llm_model': LLM_MODEL})
-    with gr_L1():
-        with gr_L2(scale=2):
-            chatbot = gr.Chatbot()
-            chatbot.style(height=CHATBOT_HEIGHT)
-            history = gr.State([])
-        with gr_L2(scale=1):
-            with gr.Accordion("输入区", open=True) as area_input_primary:
-                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.Row():
-                    status = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行。当前模型: {LLM_MODEL} \n {proxy_info}")
-            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("函数插件区", open=True) as area_crazy_fn:
-                with gr.Row():
-                    gr.Markdown("注意：以下“红颜色”标识的函数插件需从输入区读取路径作为参数.")
-                with gr.Row():
-                    for k in crazy_fns:
-                        if not crazy_fns[k].get("AsButton", True): continue
-                        variant = crazy_fns[k]["Color"] if "Color" in crazy_fns[k] else "secondary"
-                        crazy_fns[k]["Button"] = gr.Button(k, variant=variant)
-                        crazy_fns[k]["Button"].style(size="sm")
-                with gr.Row():
-                    with gr.Accordion("更多函数插件", open=True):
-                        dropdown_fn_list = [k for k in crazy_fns.keys() if not crazy_fns[k].get("AsButton", True)]
-                        with gr.Column(scale=1):
-                            dropdown = gr.Dropdown(dropdown_fn_list, value=r"打开插件列表", label="").style(container=False)
-                        with gr.Column(scale=1):
-                            switchy_bt = gr.Button(r"请先从插件列表中选择", variant="secondary")
-                with gr.Row():
-                    with gr.Accordion("点击展开“文件上传区”。上传本地文件可供红色函数插件调用。", open=False) as area_file_up:
-                        file_upload = gr.Files(label="任何文件, 但推荐上传压缩文件(zip, tar)", file_count="multiple")
-            with gr.Accordion("展开SysPrompt & 交互界面布局 & Github地址", open=(LAYOUT == "TOP-DOWN")):
-                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",)
-                max_length_sl = gr.Slider(minimum=256, maximum=4096, value=512, step=1, interactive=True, label="MaxLength",)
-                checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区", "底部输入区"], value=["基础功能区", "函数插件区"], label="显示/隐藏功能区")
-                md_dropdown = gr.Dropdown(["gpt-3.5-turbo", "chatglm"], value=LLM_MODEL, label="").style(container=False)
+    cancel_handles = []
+    with gr.Blocks(title="ChatGPT 学术优化", theme=set_theme, analytics_enabled=False, css=advanced_css) as demo:
+        gr.HTML(title_html)
+        cookies = gr.State({'api_key': API_KEY, 'llm_model': LLM_MODEL})
+        with gr_L1():
+            with gr_L2(scale=2):
+                chatbot = gr.Chatbot()
+                chatbot.style(height=CHATBOT_HEIGHT)
+                history = gr.State([])
+            with gr_L2(scale=1):
+                with gr.Accordion("输入区", open=True) as area_input_primary:
+                    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.Row():
+                        status = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行。当前模型: {LLM_MODEL} \n {proxy_info}")
+                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("函数插件区", open=True) as area_crazy_fn:
+                    with gr.Row():
+                        gr.Markdown("注意：以下“红颜色”标识的函数插件需从输入区读取路径作为参数.")
+                    with gr.Row():
+                        for k in crazy_fns:
+                            if not crazy_fns[k].get("AsButton", True): continue
+                            variant = crazy_fns[k]["Color"] if "Color" in crazy_fns[k] else "secondary"
+                            crazy_fns[k]["Button"] = gr.Button(k, variant=variant)
+                            crazy_fns[k]["Button"].style(size="sm")
+                    with gr.Row():
+                        with gr.Accordion("更多函数插件", open=True):
+                            dropdown_fn_list = [k for k in crazy_fns.keys() if not crazy_fns[k].get("AsButton", True)]
+                            with gr.Column(scale=1):
+                                dropdown = gr.Dropdown(dropdown_fn_list, value=r"打开插件列表", label="").style(container=False)
+                            with gr.Column(scale=1):
+                                switchy_bt = gr.Button(r"请先从插件列表中选择", variant="secondary")
+                    with gr.Row():
+                        with gr.Accordion("点击展开“文件上传区”。上传本地文件可供红色函数插件调用。", open=False) as area_file_up:
+                            file_upload = gr.Files(label="任何文件, 但推荐上传压缩文件(zip, tar)", file_count="multiple")
+                with gr.Accordion("展开SysPrompt & 交互界面布局 & Github地址", open=(LAYOUT == "TOP-DOWN")):
+                    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",)
+                    max_length_sl = gr.Slider(minimum=256, maximum=4096, value=512, step=1, interactive=True, label="MaxLength",)
+                    checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区", "底部输入区"], value=["基础功能区", "函数插件区"], label="显示/隐藏功能区")
+                    md_dropdown = gr.Dropdown(["gpt-3.5-turbo", "chatglm"], value=LLM_MODEL, label="").style(container=False)
 
-                gr.Markdown(description)
-            with gr.Accordion("备选输入区", open=True, visible=False) as area_input_secondary:
-                with gr.Row():
-                    txt2 = gr.Textbox(show_label=False, placeholder="Input question here.", label="输入区2").style(container=False)
-                with gr.Row():
-                    submitBtn2 = gr.Button("提交", variant="primary")
-                with gr.Row():
-                    resetBtn2 = gr.Button("重置", variant="secondary"); resetBtn.style(size="sm")
-                    stopBtn2 = gr.Button("停止", variant="secondary"); stopBtn.style(size="sm")
-    # 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))})
-        ret.update({area_crazy_fn: gr.update(visible=("函数插件区" in a))})
-        ret.update({area_input_primary: gr.update(visible=("底部输入区" not in a))})
-        ret.update({area_input_secondary: gr.update(visible=("底部输入区" in a))})
-        if "底部输入区" in a: ret.update({txt: gr.update(value="")})
-        return ret
-    checkboxes.select(fn_area_visibility, [checkboxes], [area_basic_fn, area_crazy_fn, area_input_primary, area_input_secondary, txt, txt2] )
-    # 整理反复出现的控件句柄组合
-    input_combo = [cookies, max_length_sl, md_dropdown, txt, txt2, top_p, temperature, chatbot, history, system_prompt]
-    output_combo = [cookies, chatbot, history, status]
-    predict_args = dict(fn=ArgsGeneralWrapper(predict), inputs=input_combo, outputs=output_combo)
-    # 提交按钮、重置按钮
-    cancel_handles.append(txt.submit(**predict_args))
-    cancel_handles.append(txt2.submit(**predict_args))
-    cancel_handles.append(submitBtn.click(**predict_args))
-    cancel_handles.append(submitBtn2.click(**predict_args))
-    resetBtn.click(lambda: ([], [], "已重置"), None, [chatbot, history, status])
-    resetBtn2.click(lambda: ([], [], "已重置"), None, [chatbot, history, status])
-    # 基础功能区的回调函数注册
-    for k in functional:
-        click_handle = functional[k]["Button"].click(fn=ArgsGeneralWrapper(predict), inputs=[*input_combo, gr.State(True), gr.State(k)], outputs=output_combo)
-        cancel_handles.append(click_handle)
-    # 文件上传区，接收文件后与chatbot的互动
-    file_upload.upload(on_file_uploaded, [file_upload, chatbot, txt], [chatbot, txt])
-    # 函数插件-固定按钮区
-    for k in crazy_fns:
-        if not crazy_fns[k].get("AsButton", True): continue
-        click_handle = crazy_fns[k]["Button"].click(ArgsGeneralWrapper(crazy_fns[k]["Function"]), [*input_combo, gr.State(PORT)], output_combo)
+                    gr.Markdown(description)
+                with gr.Accordion("备选输入区", open=True, visible=False) as area_input_secondary:
+                    with gr.Row():
+                        txt2 = gr.Textbox(show_label=False, placeholder="Input question here.", label="输入区2").style(container=False)
+                    with gr.Row():
+                        submitBtn2 = gr.Button("提交", variant="primary")
+                    with gr.Row():
+                        resetBtn2 = gr.Button("重置", variant="secondary"); resetBtn.style(size="sm")
+                        stopBtn2 = gr.Button("停止", variant="secondary"); stopBtn.style(size="sm")
+        # 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))})
+            ret.update({area_crazy_fn: gr.update(visible=("函数插件区" in a))})
+            ret.update({area_input_primary: gr.update(visible=("底部输入区" not in a))})
+            ret.update({area_input_secondary: gr.update(visible=("底部输入区" in a))})
+            if "底部输入区" in a: ret.update({txt: gr.update(value="")})
+            return ret
+        checkboxes.select(fn_area_visibility, [checkboxes], [area_basic_fn, area_crazy_fn, area_input_primary, area_input_secondary, txt, txt2] )
+        # 整理反复出现的控件句柄组合
+        input_combo = [cookies, max_length_sl, md_dropdown, txt, txt2, top_p, temperature, chatbot, history, system_prompt]
+        output_combo = [cookies, chatbot, history, status]
+        predict_args = dict(fn=ArgsGeneralWrapper(predict), inputs=input_combo, outputs=output_combo)
+        # 提交按钮、重置按钮
+        cancel_handles.append(txt.submit(**predict_args))
+        cancel_handles.append(txt2.submit(**predict_args))
+        cancel_handles.append(submitBtn.click(**predict_args))
+        cancel_handles.append(submitBtn2.click(**predict_args))
+        resetBtn.click(lambda: ([], [], "已重置"), None, [chatbot, history, status])
+        resetBtn2.click(lambda: ([], [], "已重置"), None, [chatbot, history, status])
+        # 基础功能区的回调函数注册
+        for k in functional:
+            click_handle = functional[k]["Button"].click(fn=ArgsGeneralWrapper(predict), inputs=[*input_combo, gr.State(True), gr.State(k)], outputs=output_combo)
+            cancel_handles.append(click_handle)
+        # 文件上传区，接收文件后与chatbot的互动
+        file_upload.upload(on_file_uploaded, [file_upload, chatbot, txt], [chatbot, txt])
+        # 函数插件-固定按钮区
+        for k in crazy_fns:
+            if not crazy_fns[k].get("AsButton", True): continue
+            click_handle = crazy_fns[k]["Button"].click(ArgsGeneralWrapper(crazy_fns[k]["Function"]), [*input_combo, gr.State(PORT)], output_combo)
+            click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
+            cancel_handles.append(click_handle)
+        # 函数插件-下拉菜单与随变按钮的互动
+        def on_dropdown_changed(k):
+            variant = crazy_fns[k]["Color"] if "Color" in crazy_fns[k] else "secondary"
+            return {switchy_bt: gr.update(value=k, variant=variant)}
+        dropdown.select(on_dropdown_changed, [dropdown], [switchy_bt] )
+        # 随变按钮的回调函数注册
+        def route(k, *args, **kwargs):
+            if k in [r"打开插件列表", r"请先从插件列表中选择"]: return 
+            yield from ArgsGeneralWrapper(crazy_fns[k]["Function"])(*args, **kwargs)
+        click_handle = switchy_bt.click(route,[switchy_bt, *input_combo, gr.State(PORT)], output_combo)
         click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
+        # def expand_file_area(file_upload, area_file_up):
+        #     if len(file_upload)>0: return {area_file_up: gr.update(open=True)}
+        # click_handle.then(expand_file_area, [file_upload, area_file_up], [area_file_up])
         cancel_handles.append(click_handle)
-    # 函数插件-下拉菜单与随变按钮的互动
-    def on_dropdown_changed(k):
-        variant = crazy_fns[k]["Color"] if "Color" in crazy_fns[k] else "secondary"
-        return {switchy_bt: gr.update(value=k, variant=variant)}
-    dropdown.select(on_dropdown_changed, [dropdown], [switchy_bt] )
-    # 随变按钮的回调��数注册
-    def route(k, *args, **kwargs):
-        if k in [r"打开插件列表", r"请先从插件列表中选择"]: return 
-        yield from ArgsGeneralWrapper(crazy_fns[k]["Function"])(*args, **kwargs)
-    click_handle = switchy_bt.click(route,[switchy_bt, *input_combo, gr.State(PORT)], output_combo)
-    click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
-    # def expand_file_area(file_upload, area_file_up):
-    #     if len(file_upload)>0: return {area_file_up: gr.update(open=True)}
-    # click_handle.then(expand_file_area, [file_upload, area_file_up], [area_file_up])
-    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)
-    stopBtn2.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：")
-    print(f"\t（亮色主题）: http://localhost:{PORT}")
-    print(f"\t（暗色主题）: http://localhost:{PORT}/?__dark-theme=true")
-    def open(): 
-        time.sleep(2)       # 打开浏览器
-        webbrowser.open_new_tab(f"http://localhost:{PORT}/?__dark-theme=true")
-    threading.Thread(target=open, name="open-browser", daemon=True).start()
-    threading.Thread(target=auto_update, name="self-upgrade", daemon=True).start()
+        # 终止按钮的回调函数注册
+        stopBtn.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
+        stopBtn2.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：")
+        print(f"\t（亮色主题）: http://localhost:{PORT}")
+        print(f"\t（暗色主题）: http://localhost:{PORT}/?__dark-theme=true")
+        def open(): 
+            time.sleep(2)       # 打开浏览器
+            webbrowser.open_new_tab(f"http://localhost:{PORT}/?__dark-theme=true")
+        threading.Thread(target=open, name="open-browser", daemon=True).start()
+        threading.Thread(target=auto_update, name="self-upgrade", daemon=True).start()
+
+    auto_opentab_delay()
+    demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION)
 
-auto_opentab_delay()
-demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION)
+if __name__ == "__main__":
+    main()

request_llm/bridge_all.py

@@ -31,6 +31,24 @@ methods = {
     "tgui-ui": tgui_ui,
 }
 
+def LLM_CATCH_EXCEPTION(f):
+    """
+        装饰器函数，将错误显示出来
+    """
+    def decorated(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience):
+        try:
+            return f(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience)
+        except Exception as e:
+            from toolbox import get_conf
+            import traceback
+            proxies, = get_conf('proxies')
+            tb_str = '\n```\n' + traceback.format_exc() + '\n```\n'
+            observe_window[0] = tb_str
+            return tb_str
+    return decorated
+
+colors = ['#FF00FF', '#00FFFF', '#FF0000''#990099', '#009999', '#990044']
+
 def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience=False):
     """
         发送至LLM，等待回复，一次性完成，不显示中间过程。但内部用stream的方法避免中途网线被掐。
@@ -62,17 +80,13 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, obser
         return method(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience)
     else:
         # 如果同时询问多个大语言模型：
-        executor = ThreadPoolExecutor(max_workers=16)
+        executor = ThreadPoolExecutor(max_workers=4)
         models = model.split('&')
         n_model = len(models)
         
         window_len = len(observe_window)
-        if window_len==0:
-            window_mutex = [[] for _ in range(n_model)] + [True]
-        elif window_len==1:
-            window_mutex = [[""] for _ in range(n_model)] + [True]
-        elif window_len==2:
-            window_mutex = [["", time.time()] for _ in range(n_model)] + [True]
+        assert window_len==3
+        window_mutex = [["", time.time(), ""] for _ in range(n_model)] + [True]
 
         futures = []
         for i in range(n_model):
@@ -85,12 +99,12 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, obser
                 method = methods['tgui-no-ui']
             llm_kwargs_feedin = copy.deepcopy(llm_kwargs)
             llm_kwargs_feedin['llm_model'] = model
-            future = executor.submit(method, inputs, llm_kwargs_feedin, history, sys_prompt, window_mutex[i], console_slience)
+            future = executor.submit(LLM_CATCH_EXCEPTION(method), inputs, llm_kwargs_feedin, history, sys_prompt, window_mutex[i], console_slience)
             futures.append(future)
 
         def mutex_manager(window_mutex, observe_window):
             while True:
-                time.sleep(0.2)
+                time.sleep(0.5)
                 if not window_mutex[-1]: break
                 # 看门狗（watchdog）
                 for i in range(n_model): 
@@ -98,8 +112,8 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, obser
                 # 观察窗（window）
                 chat_string = []
                 for i in range(n_model):
-                    chat_string.append( f"[{str(models[i])} 说]: {window_mutex[i][0]}" )
-                res = '\n\n---\n\n'.join(chat_string)
+                    chat_string.append( f"【{str(models[i])} 说】: <font color=\"{colors[i]}\"> {window_mutex[i][0]} </font>" )
+                res = '<br/><br/>\n\n---\n\n'.join(chat_string)
                 # # # # # # # # # # #
                 observe_window[0] = res
 
@@ -107,10 +121,18 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, obser
         t_model.start()
 
         return_string_collect = []
+        while True:
+            worker_done = [h.done() for h in futures]
+            if all(worker_done):
+                executor.shutdown()
+                break
+            time.sleep(1)
+
         for i, future in enumerate(futures):  # wait and get
-            return_string_collect.append( f"[{str(models[i])} 说]: {future.result()}" )
+            return_string_collect.append( f"【{str(models[i])} 说】: <font color=\"{colors[i]}\"> {future.result()} </font>" )
+
         window_mutex[-1] = False # stop mutex thread
-        res = '\n\n---\n\n'.join(return_string_collect)
+        res = '<br/>\n\n---\n\n'.join(return_string_collect)
         return res
 
 

request_llm/bridge_chatglm.py

@@ -3,35 +3,69 @@ from transformers import AutoModel, AutoTokenizer
 import time
 import importlib
 from toolbox import update_ui, get_conf
+from multiprocessing import Process, Pipe
 
+#################################################################################
+class GetGLMHandle(Process):
+    def __init__(self):
+        super().__init__(daemon=True)
+        self.parent, self.child = Pipe()
+        self.chatglm_model = None
+        self.chatglm_tokenizer = None
+        self.start()
+        print('初始化')
+        
+    def ready(self):
+        return self.chatglm_model is not None
 
-global chatglm_model, chatglm_tokenizer
-
-chatglm_model = None
-chatglm_tokenizer = None
-
-def model_loader():
-    global chatglm_model, chatglm_tokenizer
-    if chatglm_tokenizer is None:
-        chatglm_tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
-    if chatglm_model is None: # 尚未加载
-        device, = get_conf('LOCAL_MODEL_DEVICE')
-        if device=='cpu':
-            chatglm_model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).float()
-        else:
-            chatglm_model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda()
-        chatglm_model = chatglm_model.eval()
-    chatglm_model = chatglm_model.eval()
+    def run(self):
+        while True:
+            try:
+                if self.chatglm_model is None:
+                    self.chatglm_tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
+                    device, = get_conf('LOCAL_MODEL_DEVICE')
+                    if device=='cpu':
+                        self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).float()
+                    else:
+                        self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda()
+                    self.chatglm_model = self.chatglm_model.eval()
+                    break
+                else:
+                    break
+            except:
+                pass
+        while True:
+            kwargs = self.child.recv()
+            try:
+                for response, history in self.chatglm_model.stream_chat(self.chatglm_tokenizer, **kwargs):
+                    self.child.send(response)
+            except:
+                self.child.send('[Local Message] Call ChatGLM fail.')
+            self.child.send('[Finish]')
 
+    def stream_chat(self, **kwargs):
+        self.parent.send(kwargs)
+        while True:
+            res = self.parent.recv()
+            if res != '[Finish]':
+                yield res
+            else:
+                break
+        return
+    
+global glm_handle
+glm_handle = None
+#################################################################################
 def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
     """
+        多线程方法
         函数的说明请见 request_llm/bridge_all.py
     """
-    global chatglm_model, chatglm_tokenizer
-    if chatglm_model is None:
-        observe_window[0] = "ChatGLM尚未加载，加载需要一段时间 ……"
+    global glm_handle
+    if glm_handle is None:
+        glm_handle = GetGLMHandle()
+        observe_window[0] = "ChatGLM尚未加载，加载需要一段时间。注意，取决于`config.py`的配置，ChatGLM消耗大量的内存（CPU）或显存（GPU），也许会导致低配计算机卡死 ……"
 
-    model_loader()
     # chatglm 没有 sys_prompt 接口，因此把prompt加入 history
     history_feedin = []
     for i in range(len(history)//2):
@@ -40,29 +74,27 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
 
     watch_dog_patience = 5 # 看门狗 (watchdog) 的耐心, 设置5秒即可
     response = ""
-    for response, history in chatglm_model.stream_chat(chatglm_tokenizer, inputs, history=history_feedin, max_length=llm_kwargs['max_length'],
-                                                       top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
-        # 观测窗，把已经获取的数据显示出去
+    for response in glm_handle.stream_chat(query=inputs, history=history_feedin, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
         observe_window[0] = response
-        # 看门狗 (watchdog)，如果超过期限没有喂狗，则终止
         if len(observe_window) >= 2:  
             if (time.time()-observe_window[1]) > watch_dog_patience:
                 raise RuntimeError("程序终止。")
-        # if not console_slience:
-        #     print(response)
     return response
 
 
+
 def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
     """
+        单线程方法
         函数的说明请见 request_llm/bridge_all.py
     """
-    global chatglm_model, chatglm_tokenizer
     chatbot.append((inputs, ""))
-    if chatglm_model is None:
-        chatbot[-1] = (inputs, "ChatGLM尚未加载，加载需要一段时间 ……")
+
+    global glm_handle
+    if glm_handle is None:
+        glm_handle = GetGLMHandle()
+        chatbot[-1] = (inputs, "ChatGLM尚未加载，加载需要一段时间。注意，取决于`config.py`的配置，ChatGLM消耗大量的内存（CPU）或显存（GPU），也许会导致低配计算机卡死 ……")
         yield from update_ui(chatbot=chatbot, history=[])
-    model_loader()
 
     if additional_fn is not None:
         import core_functional
@@ -71,13 +103,11 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
         if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs)  # 获取预处理函数（如果有的话）
         inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
 
-
     history_feedin = []
     for i in range(len(history)//2):
         history_feedin.append(["What can I do?", system_prompt] )
         history_feedin.append([history[2*i], history[2*i+1]] )
 
-    for response, history in chatglm_model.stream_chat(chatglm_tokenizer, inputs, history=history_feedin, max_length=llm_kwargs['max_length'],
-                                                       top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
+    for response in glm_handle.stream_chat(query=inputs, history=history_feedin, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
         chatbot[-1] = (inputs, response)
         yield from update_ui(chatbot=chatbot, history=history)

version

@@ -1,5 +1,5 @@
 {
-  "version": 3.0,
+  "version": 3.1,
   "show_feature": true,
   "new_feature": "支持ChatGLM <-> 支持多LLM模型同时对话"
 }