Merge remote-tracking branch 'origin/master'

# Conflicts:
#	main.py
#	themes/welcome.js

README.md

@@ -173,26 +173,32 @@ flowchart TD
     ```
 
 
-<details><summary>如果需要支持清华ChatGLM2/复旦MOSS/RWKV作为后端，请点击展开此处</summary>
+<details><summary>如果需要支持清华ChatGLM系列/复旦MOSS/RWKV作为后端，请点击展开此处</summary>
 <p>
 
-【可选步骤】如果需要支持清华ChatGLM3/复旦MOSS作为后端，需要额外安装更多依赖（前提条件：熟悉Python + 用过Pytorch + 电脑配置够强）：
+【可选步骤】如果需要支持清华ChatGLM系列/复旦MOSS作为后端，需要额外安装更多依赖（前提条件：熟悉Python + 用过Pytorch + 电脑配置够强）：
 
 ```sh
 # 【可选步骤I】支持清华ChatGLM3。清华ChatGLM备注：如果遇到"Call ChatGLM fail 不能正常加载ChatGLM的参数" 错误，参考如下： 1：以上默认安装的为torch+cpu版，使用cuda需要卸载torch重新安装torch+cuda； 2：如因本机配置不够无法加载模型，可以修改request_llm/bridge_chatglm.py中的模型精度, 将 AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) 都修改为 AutoTokenizer.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True)
 python -m pip install -r request_llms/requirements_chatglm.txt
 
-# 【可选步骤II】支持复旦MOSS
+# 【可选步骤II】支持清华ChatGLM4 注意：此模型至少需要24G显存
+python -m pip install -r request_llms/requirements_chatglm4.txt
+# 可使用modelscope下载ChatGLM4模型
+# pip install modelscope
+# modelscope download --model ZhipuAI/glm-4-9b-chat --local_dir ./THUDM/glm-4-9b-chat
+
+# 【可选步骤III】支持复旦MOSS
 python -m pip install -r request_llms/requirements_moss.txt
 git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss  # 注意执行此行代码时，必须处于项目根路径
 
-# 【可选步骤III】支持RWKV Runner
+# 【可选步骤IV】支持RWKV Runner
 参考wiki：https://github.com/binary-husky/gpt_academic/wiki/%E9%80%82%E9%85%8DRWKV-Runner
 
-# 【可选步骤IV】确保config.py配置文件的AVAIL_LLM_MODELS包含了期望的模型，目前支持的全部模型如下(jittorllms系列目前仅支持docker方案)：
+# 【可选步骤V】确保config.py配置文件的AVAIL_LLM_MODELS包含了期望的模型，目前支持的全部模型如下(jittorllms系列目前仅支持docker方案)：
 AVAIL_LLM_MODELS = ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "moss"] # + ["jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]
 
-# 【可选步骤V】支持本地模型INT8,INT4量化（这里所指的模型本身不是量化版本，目前deepseek-coder支持，后面测试后会加入更多模型量化选择）
+# 【可选步骤VI】支持本地模型INT8,INT4量化（这里所指的模型本身不是量化版本，目前deepseek-coder支持，后面测试后会加入更多模型量化选择）
 pip install bitsandbyte
 # windows用户安装bitsandbytes需要使用下面bitsandbytes-windows-webui
 python -m pip install bitsandbytes --prefer-binary --extra-index-url=https://jllllll.github.io/bitsandbytes-windows-webui

config.py

@@ -36,7 +36,7 @@ AVAIL_LLM_MODELS = ["gpt-4-1106-preview", "gpt-4-turbo-preview", "gpt-4-vision-p
                     "gpt-4o", "gpt-4o-mini", "gpt-4-turbo", "gpt-4-turbo-2024-04-09",
                     "gpt-3.5-turbo-1106", "gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5",
                     "gpt-4", "gpt-4-32k", "azure-gpt-4", "glm-4", "glm-4v", "glm-3-turbo",
-                    "gemini-1.5-pro", "chatglm3"
+                    "gemini-1.5-pro", "chatglm3", "chatglm4"
                     ]
 
 EMBEDDING_MODEL = "text-embedding-3-small"
@@ -55,6 +55,7 @@ EMBEDDING_MODEL = "text-embedding-3-small"
 #   "deepseek-chat" ,"deepseek-coder",
 #   "gemini-1.5-flash",
 #   "yi-34b-chat-0205","yi-34b-chat-200k","yi-large","yi-medium","yi-spark","yi-large-turbo","yi-large-preview",
+#   "grok-beta",
 # ]
 # --- --- --- ---
 # 此外，您还可以在接入one-api/vllm/ollama/Openroute时，
@@ -142,6 +143,9 @@ BAIDU_CLOUD_SECRET_KEY = ''
 BAIDU_CLOUD_QIANFAN_MODEL = 'ERNIE-Bot'    # 可选 "ERNIE-Bot-4"(文心大模型4.0), "ERNIE-Bot"(文心一言), "ERNIE-Bot-turbo", "BLOOMZ-7B", "Llama-2-70B-Chat", "Llama-2-13B-Chat", "Llama-2-7B-Chat", "ERNIE-Speed-128K", "ERNIE-Speed-8K", "ERNIE-Lite-8K"
 
 
+# 如果使用ChatGLM3或ChatGLM4本地模型，请把 LLM_MODEL="chatglm3" 或LLM_MODEL="chatglm4"，并在此处指定模型路径
+CHATGLM_LOCAL_MODEL_PATH = "THUDM/glm-4-9b-chat" # 例如"/home/hmp/ChatGLM3-6B/"
+
 # 如果使用ChatGLM2微调模型，请把 LLM_MODEL="chatglmft"，并在此处指定模型路径
 CHATGLM_PTUNING_CHECKPOINT = "" # 例如"/home/hmp/ChatGLM2-6B/ptuning/output/6b-pt-128-1e-2/checkpoint-100"
 
@@ -234,7 +238,6 @@ MOONSHOT_API_KEY = ""
 # 零一万物(Yi Model) API KEY
 YIMODEL_API_KEY = ""
 
-
 # 深度求索(DeepSeek) API KEY，默认请求地址为"https://api.deepseek.com/v1/chat/completions"
 DEEPSEEK_API_KEY = ""
 
@@ -242,6 +245,8 @@ DEEPSEEK_API_KEY = ""
 # 紫东太初大模型 https://ai-maas.wair.ac.cn
 TAICHU_API_KEY = ""
 
+# Grok API KEY
+GROK_API_KEY = ""
 
 # Mathpix 拥有执行PDF的OCR功能，但是需要注册账号
 MATHPIX_APPID = ""
@@ -373,6 +378,7 @@ DAAS_SERVER_URLS = [ f"https://niuziniu-biligpt{i}.hf.space/stream" for i in ran
 
 本地大模型示意图
 │
+├── "chatglm4"
 ├── "chatglm3"
 ├── "chatglm"
 ├── "chatglm_onnx"

crazy_functions/PDF_Translate.py

@@ -47,7 +47,7 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
                 yield from 解析PDF_基于DOC2X(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, DOC2X_API_KEY, user_request)
                 return
             except:
-                chatbot.append([None, f"DOC2X服务不可用，现在将执行效果稍差的旧版代码。{trimmed_format_exc_markdown()}"])
+                chatbot.append([None, f"DOC2X服务不可用，请检查报错详细。{trimmed_format_exc_markdown()}"])
                 yield from update_ui(chatbot=chatbot, history=history)
 
     if method == "GROBID":

crazy_functions/latex_fns/latex_actions.py

@@ -300,7 +300,8 @@ def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin
     write_html(pfg.sp_file_contents, pfg.sp_file_result, chatbot=chatbot, project_folder=project_folder)
 
     #  <-------- 写出文件 ---------->
-    msg = f"当前大语言模型: {llm_kwargs['llm_model']}，当前语言模型温度设定: {llm_kwargs['temperature']}。"
+    model_name = llm_kwargs['llm_model'].replace('_', '\\_')  # 替换LLM模型名称中的下划线为转义字符
+    msg = f"当前大语言模型: {model_name}，当前语言模型温度设定: {llm_kwargs['temperature']}。"
     final_tex = lps.merge_result(pfg.file_result, mode, msg)
     objdump((lps, pfg.file_result, mode, msg), file=pj(project_folder,'merge_result.pkl'))
 
@@ -351,6 +352,41 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
     chatbot.append([f"正在编译PDF文档", f'编译已经开始。当前工作路径为{work_folder}，如果程序停顿5分钟以上，请直接去该路径下取回翻译结果，或者重启之后再度尝试 ...']); yield from update_ui(chatbot=chatbot, history=history)
     chatbot.append([f"正在编译PDF文档", '...']); yield from update_ui(chatbot=chatbot, history=history); time.sleep(1); chatbot[-1] = list(chatbot[-1]) # 刷新界面
     yield from update_ui_lastest_msg('编译已经开始...', chatbot, history)   # 刷新Gradio前端界面
+    # 检查是否需要使用xelatex
+    def check_if_need_xelatex(tex_path):
+        try:
+            with open(tex_path, 'r', encoding='utf-8', errors='replace') as f:
+                content = f.read(5000)
+                # 检查是否有使用xelatex的宏包
+                need_xelatex = any(
+                    pkg in content 
+                    for pkg in ['fontspec', 'xeCJK', 'xetex', 'unicode-math', 'xltxtra', 'xunicode']
+                )
+                if need_xelatex:
+                    logger.info(f"检测到宏包需要xelatex编译, 切换至xelatex编译")
+                else:
+                    logger.info(f"未检测到宏包需要xelatex编译, 使用pdflatex编译")
+                return need_xelatex
+        except Exception:
+            return False
+
+    # 根据编译器类型返回编译命令
+    def get_compile_command(compiler, filename):
+        compile_command = f'{compiler} -interaction=batchmode -file-line-error {filename}.tex'
+        logger.info('Latex 编译指令: ', compile_command)
+        return compile_command
+
+    # 确定使用的编译器
+    compiler = 'pdflatex'
+    if check_if_need_xelatex(pj(work_folder_modified, f'{main_file_modified}.tex')):
+        logger.info("检测到宏包需要xelatex编译，切换至xelatex编译")
+        # Check if xelatex is installed
+        try:
+            import subprocess
+            subprocess.run(['xelatex', '--version'], capture_output=True, check=True)
+            compiler = 'xelatex'
+        except (subprocess.CalledProcessError, FileNotFoundError):
+            raise RuntimeError("检测到需要使用xelatex编译，但系统中未安装xelatex。请先安装texlive或其他提供xelatex的LaTeX发行版。")
 
     while True:
         import os
@@ -361,10 +397,10 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
 
         # https://stackoverflow.com/questions/738755/dont-make-me-manually-abort-a-latex-compile-when-theres-an-error
         yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译原始PDF ...', chatbot, history)   # 刷新Gradio前端界面
-        ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex', work_folder_original)
+        ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
 
         yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译转化后的PDF ...', chatbot, history)   # 刷新Gradio前端界面
-        ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex', work_folder_modified)
+        ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
 
         if ok and os.path.exists(pj(work_folder_modified, f'{main_file_modified}.pdf')):
             # 只有第二步成功，才能继续下面的步骤
@@ -375,10 +411,10 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
                 ok = compile_latex_with_timeout(f'bibtex  {main_file_modified}.aux', work_folder_modified)
 
             yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译文献交叉引用 ...', chatbot, history)  # 刷新Gradio前端界面
-            ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex', work_folder_original)
+            ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
-            ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex', work_folder_modified)
+            ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
-            ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex', work_folder_original)
+            ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
-            ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex', work_folder_modified)
+            ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
 
             if mode!='translate_zh':
                 yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 使用latexdiff生成论文转化前后对比 ...', chatbot, history) # 刷新Gradio前端界面
@@ -386,10 +422,10 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
                 ok = compile_latex_with_timeout(f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex  {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex', os.getcwd())
 
                 yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 正在编译对比PDF ...', chatbot, history)   # 刷新Gradio前端界面
-                ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex', work_folder)
+                ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
                 ok = compile_latex_with_timeout(f'bibtex    merge_diff.aux', work_folder)
-                ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex', work_folder)
+                ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
-                ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex', work_folder)
+                ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
 
         # <---------- 检查结果 ----------->
         results_ = ""

crazy_functions/pdf_fns/parse_pdf_via_doc2x.py

@@ -6,75 +6,128 @@ from crazy_functions.crazy_utils import get_files_from_everything
 from shared_utils.colorful import *
 from loguru import logger
 import os
+import requests
 import time
 
-def refresh_key(doc2x_api_key):
-    import requests, json
-    url = "https://api.doc2x.noedgeai.com/api/token/refresh"
-    res = requests.post(
-        url,
-        headers={"Authorization": "Bearer " + doc2x_api_key}
-    )
-    res_json = []
-    if res.status_code == 200:
-        decoded = res.content.decode("utf-8")
-        res_json = json.loads(decoded)
-        doc2x_api_key = res_json['data']['token']
-    else:
-        raise RuntimeError(format("[ERROR] status code: %d, body: %s" % (res.status_code, res.text)))
-    return doc2x_api_key
 
+def retry_request(max_retries=3, delay=3):
+    """
+    Decorator for retrying HTTP requests
+    Args:
+        max_retries: Maximum number of retry attempts
+        delay: Delay between retries in seconds
+    """
+
+    def decorator(func):
+        def wrapper(*args, **kwargs):
+            for attempt in range(max_retries):
+                try:
+                    return func(*args, **kwargs)
+                except Exception as e:
+                    if attempt < max_retries - 1:
+                        logger.error(
+                            f"Request failed, retrying... ({attempt + 1}/{max_retries}) Error: {e}"
+                        )
+                        time.sleep(delay)
+                        continue
+                    raise e
+            return None
+
+        return wrapper
+
+    return decorator
+
+
+@retry_request()
+def make_request(method, url, **kwargs):
+    """
+    Make HTTP request with retry mechanism
+    """
+    return requests.request(method, url, **kwargs)
+
+
+def doc2x_api_response_status(response, uid=""):
+    """
+    Check the status of Doc2x API response
+    Args:
+        response_data: Response object from Doc2x API
+    """
+    response_json = response.json()
+    response_data = response_json.get("data", {})
+    code = response_json.get("code", "Unknown")
+    meg = response_data.get("message", response_json)
+    trace_id = response.headers.get("trace-id", "Failed to get trace-id")
+    if response.status_code != 200:
+        raise RuntimeError(
+            f"Doc2x return an error:\nTrace ID: {trace_id} {uid}\n{response.status_code} - {response_json}"
+        )
+    if code in ["parse_page_limit_exceeded", "parse_concurrency_limit"]:
+        raise RuntimeError(
+            f"Reached the limit of Doc2x:\nTrace ID: {trace_id} {uid}\n{code} - {meg}"
+        )
+    if code not in ["ok", "success"]:
+        raise RuntimeError(
+            f"Doc2x return an error:\nTrace ID: {trace_id} {uid}\n{code} - {meg}"
+        )
+    return response_data
 
 
 def 解析PDF_DOC2X_转Latex(pdf_file_path):
-    zip_file_path, unzipped_folder = 解析PDF_DOC2X(pdf_file_path, format='tex')
+    zip_file_path, unzipped_folder = 解析PDF_DOC2X(pdf_file_path, format="tex")
     return unzipped_folder
 
 
-def 解析PDF_DOC2X(pdf_file_path, format='tex'):
+def 解析PDF_DOC2X(pdf_file_path, format="tex"):
     """
-        format: 'tex', 'md', 'docx'
+    format: 'tex', 'md', 'docx'
     """
-    import requests, json, os
+
-    DOC2X_API_KEY = get_conf('DOC2X_API_KEY')
+    DOC2X_API_KEY = get_conf("DOC2X_API_KEY")
     latex_dir = get_log_folder(plugin_name="pdf_ocr_latex")
     markdown_dir = get_log_folder(plugin_name="pdf_ocr")
     doc2x_api_key = DOC2X_API_KEY
 
+    # < ------ 第1步：预上传获取URL，然后上传文件 ------ >
+    logger.info("Doc2x 上传文件：预上传获取URL")
+    res = make_request(
+        "POST",
+        "https://v2.doc2x.noedgeai.com/api/v2/parse/preupload",
+        headers={"Authorization": "Bearer " + doc2x_api_key},
+        timeout=15,
+    )
+    res_data = doc2x_api_response_status(res)
+    upload_url = res_data["url"]
+    uuid = res_data["uid"]
 
-    # < ------ 第1步：上传 ------ >
+    logger.info("Doc2x 上传文件：上传文件")
-    logger.info("Doc2x 第1步：上传")
+    with open(pdf_file_path, "rb") as file:
-    with open(pdf_file_path, 'rb') as file:
+        res = make_request("PUT", upload_url, data=file, timeout=60)
-        res = requests.post(
+    res.raise_for_status()
-            "https://v2.doc2x.noedgeai.com/api/v2/parse/pdf",
-            headers={"Authorization": "Bearer " + doc2x_api_key},
-            data=file
-        )
-    # res_json = []
-    if res.status_code == 200:
-        res_json = res.json()
-    else:
-        raise RuntimeError(f"Doc2x return an error: {res.json()}")
-    uuid = res_json['data']['uid']
 
     # < ------ 第2步：轮询等待 ------ >
-    logger.info("Doc2x 第2步：轮询等待")
+    logger.info("Doc2x 处理文件中：轮询等待")
-    params = {'uid': uuid}
+    params = {"uid": uuid}
-    while True:
+    max_attempts = 60
-        res = requests.get(
+    attempt = 0
-            'https://v2.doc2x.noedgeai.com/api/v2/parse/status',
+    while attempt < max_attempts:
+        res = make_request(
+            "GET",
+            "https://v2.doc2x.noedgeai.com/api/v2/parse/status",
             headers={"Authorization": "Bearer " + doc2x_api_key},
-            params=params
+            params=params,
+            timeout=15,
         )
-        res_json = res.json()
+        res_data = doc2x_api_response_status(res)
-        if res_json['data']['status'] == "success":
+        if res_data["status"] == "success":
             break
-        elif res_json['data']['status'] == "processing":
+        elif res_data["status"] == "processing":
-            time.sleep(3)
+            time.sleep(5)
-            logger.info(f"Doc2x is processing at {res_json['data']['progress']}%")
+            logger.info(f"Doc2x is processing at {res_data['progress']}%")
-        elif res_json['data']['status'] == "failed":
+            attempt += 1
-            raise RuntimeError(f"Doc2x return an error: {res_json}")
+        else:
-
+            raise RuntimeError(f"Doc2x return an error: {res_data}")
+    if attempt >= max_attempts:
+        raise RuntimeError("Doc2x processing timeout after maximum attempts")
 
     # < ------ 第3步：提交转化 ------ >
     logger.info("Doc2x 第3步：提交转化")
@@ -84,42 +137,44 @@ def 解析PDF_DOC2X(pdf_file_path, format='tex'):
         "formula_mode": "dollar",
         "filename": "output"
     }
-    res = requests.post(
+    res = make_request(
-        'https://v2.doc2x.noedgeai.com/api/v2/convert/parse',
+        "POST",
+        "https://v2.doc2x.noedgeai.com/api/v2/convert/parse",
         headers={"Authorization": "Bearer " + doc2x_api_key},
-        json=data
+        json=data,
+        timeout=15,
     )
-    if res.status_code == 200:
+    doc2x_api_response_status(res, uid=f"uid: {uuid}")
-        res_json = res.json()
-    else:
-        raise RuntimeError(f"Doc2x return an error: {res.json()}")
-
 
     # < ------ 第4步：等待结果 ------ >
     logger.info("Doc2x 第4步：等待结果")
-    params = {'uid': uuid}
+    params = {"uid": uuid}
-    while True:
+    max_attempts = 36
-        res = requests.get(
+    attempt = 0
-            'https://v2.doc2x.noedgeai.com/api/v2/convert/parse/result',
+    while attempt < max_attempts:
+        res = make_request(
+            "GET",
+            "https://v2.doc2x.noedgeai.com/api/v2/convert/parse/result",
             headers={"Authorization": "Bearer " + doc2x_api_key},
-            params=params
+            params=params,
+            timeout=15,
         )
-        res_json = res.json()
+        res_data = doc2x_api_response_status(res, uid=f"uid: {uuid}")
-        if res_json['data']['status'] == "success":
+        if res_data["status"] == "success":
             break
-        elif res_json['data']['status'] == "processing":
+        elif res_data["status"] == "processing":
             time.sleep(3)
-            logger.info(f"Doc2x still processing")
+            logger.info("Doc2x still processing to convert file")
-        elif res_json['data']['status'] == "failed":
+            attempt += 1
-            raise RuntimeError(f"Doc2x return an error: {res_json}")
+    if attempt >= max_attempts:
-
+        raise RuntimeError("Doc2x conversion timeout after maximum attempts")
 
     # < ------ 第5步：最后的处理 ------ >
-    logger.info("Doc2x 第5步：最后的处理")
+    logger.info("Doc2x 第5步：下载转换后的文件")
 
-    if format=='tex':
+    if format == "tex":
         target_path = latex_dir
-    if format=='md':
+    if format == "md":
         target_path = markdown_dir
     os.makedirs(target_path, exist_ok=True)
 
@@ -127,17 +182,18 @@ def 解析PDF_DOC2X(pdf_file_path, format='tex'):
     # < ------ 下载 ------ >
     for attempt in range(max_attempt):
         try:
-            result_url = res_json['data']['url']
+            result_url = res_data["url"]
-            res = requests.get(result_url)
+            res = make_request("GET", result_url, timeout=60)
-            zip_path = os.path.join(target_path, gen_time_str() + '.zip')
+            zip_path = os.path.join(target_path, gen_time_str() + ".zip")
             unzip_path = os.path.join(target_path, gen_time_str())
             if res.status_code == 200:
-                with open(zip_path, "wb") as f: f.write(res.content)
+                with open(zip_path, "wb") as f:
+                    f.write(res.content)
             else:
                 raise RuntimeError(f"Doc2x return an error: {res.json()}")
         except Exception as e:
             if attempt < max_attempt - 1:
-                logger.error(f"Failed to download latex file, retrying... {e}")
+                logger.error(f"Failed to download uid = {uuid} file, retrying... {e}")
                 time.sleep(3)
                 continue
             else:
@@ -145,22 +201,31 @@ def 解析PDF_DOC2X(pdf_file_path, format='tex'):
 
     # < ------ 解压 ------ >
     import zipfile
-    with zipfile.ZipFile(zip_path, 'r') as zip_ref:
+    with zipfile.ZipFile(zip_path, "r") as zip_ref:
         zip_ref.extractall(unzip_path)
     return zip_path, unzip_path
 
 
-def 解析PDF_DOC2X_单文件(fp, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, DOC2X_API_KEY, user_request):
+def 解析PDF_DOC2X_单文件(
-
+    fp,
+    project_folder,
+    llm_kwargs,
+    plugin_kwargs,
+    chatbot,
+    history,
+    system_prompt,
+    DOC2X_API_KEY,
+    user_request,
+):
     def pdf2markdown(filepath):
         chatbot.append((None, f"Doc2x 解析中"))
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
 
-        md_zip_path, unzipped_folder = 解析PDF_DOC2X(filepath, format='md')
+        md_zip_path, unzipped_folder = 解析PDF_DOC2X(filepath, format="md")
 
         promote_file_to_downloadzone(md_zip_path, chatbot=chatbot)
         chatbot.append((None, f"完成解析 {md_zip_path} ..."))
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
         return md_zip_path
 
     def deliver_to_markdown_plugin(md_zip_path, user_request):
@@ -174,77 +239,97 @@ def 解析PDF_DOC2X_单文件(fp, project_folder, llm_kwargs, plugin_kwargs, cha
         os.makedirs(target_path_base, exist_ok=True)
         shutil.copyfile(md_zip_path, this_file_path)
         ex_folder = this_file_path + ".extract"
-        extract_archive(
+        extract_archive(file_path=this_file_path, dest_dir=ex_folder)
-            file_path=this_file_path, dest_dir=ex_folder
-        )
 
         # edit markdown files
-        success, file_manifest, project_folder = get_files_from_everything(ex_folder, type='.md')
+        success, file_manifest, project_folder = get_files_from_everything(
+            ex_folder, type=".md"
+        )
         for generated_fp in file_manifest:
             # 修正一些公式问题
-            with open(generated_fp, 'r', encoding='utf8') as f:
+            with open(generated_fp, "r", encoding="utf8") as f:
                 content = f.read()
             # 将公式中的\[ \]替换成$$
-            content = content.replace(r'\[', r'$$').replace(r'\]', r'$$')
+            content = content.replace(r"\[", r"$$").replace(r"\]", r"$$")
             # 将公式中的\( \)替换成$
-            content = content.replace(r'\(', r'$').replace(r'\)', r'$')
+            content = content.replace(r"\(", r"$").replace(r"\)", r"$")
-            content = content.replace('```markdown', '\n').replace('```', '\n')
+            content = content.replace("```markdown", "\n").replace("```", "\n")
-            with open(generated_fp, 'w', encoding='utf8') as f:
+            with open(generated_fp, "w", encoding="utf8") as f:
                 f.write(content)
             promote_file_to_downloadzone(generated_fp, chatbot=chatbot)
-            yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+            yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
 
             # 生成在线预览html
-            file_name = '在线预览翻译（原文）' + gen_time_str() + '.html'
+            file_name = "在线预览翻译（原文）" + gen_time_str() + ".html"
             preview_fp = os.path.join(ex_folder, file_name)
-            from shared_utils.advanced_markdown_format import markdown_convertion_for_file
+            from shared_utils.advanced_markdown_format import (
+                markdown_convertion_for_file,
+            )
+
             with open(generated_fp, "r", encoding="utf-8") as f:
                 md = f.read()
             #     # Markdown中使用不标准的表格，需要在表格前加上一个emoji，以便公式渲染
             #     md = re.sub(r'^<table>', r'.<table>', md, flags=re.MULTILINE)
             html = markdown_convertion_for_file(md)
-            with open(preview_fp, "w", encoding="utf-8") as f: f.write(html)
+            with open(preview_fp, "w", encoding="utf-8") as f:
+                f.write(html)
             chatbot.append([None, f"生成在线预览：{generate_file_link([preview_fp])}"])
             promote_file_to_downloadzone(preview_fp, chatbot=chatbot)
 
-
-
         chatbot.append((None, f"调用Markdown插件 {ex_folder} ..."))
-        plugin_kwargs['markdown_expected_output_dir'] = ex_folder
+        plugin_kwargs["markdown_expected_output_dir"] = ex_folder
 
-        translated_f_name = 'translated_markdown.md'
+        translated_f_name = "translated_markdown.md"
-        generated_fp = plugin_kwargs['markdown_expected_output_path'] = os.path.join(ex_folder, translated_f_name)
+        generated_fp = plugin_kwargs["markdown_expected_output_path"] = os.path.join(
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+            ex_folder, translated_f_name
-        yield from Markdown英译中(ex_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
+        )
+        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+        yield from Markdown英译中(
+            ex_folder,
+            llm_kwargs,
+            plugin_kwargs,
+            chatbot,
+            history,
+            system_prompt,
+            user_request,
+        )
         if os.path.exists(generated_fp):
             # 修正一些公式问题
-            with open(generated_fp, 'r', encoding='utf8') as f: content = f.read()
+            with open(generated_fp, "r", encoding="utf8") as f:
-            content = content.replace('```markdown', '\n').replace('```', '\n')
+                content = f.read()
+            content = content.replace("```markdown", "\n").replace("```", "\n")
             # Markdown中使用不标准的表格，需要在表格前加上一个emoji，以便公式渲染
             # content = re.sub(r'^<table>', r'.<table>', content, flags=re.MULTILINE)
-            with open(generated_fp, 'w', encoding='utf8') as f: f.write(content)
+            with open(generated_fp, "w", encoding="utf8") as f:
+                f.write(content)
             # 生成在线预览html
-            file_name = '在线预览翻译' + gen_time_str() + '.html'
+            file_name = "在线预览翻译" + gen_time_str() + ".html"
             preview_fp = os.path.join(ex_folder, file_name)
-            from shared_utils.advanced_markdown_format import markdown_convertion_for_file
+            from shared_utils.advanced_markdown_format import (
+                markdown_convertion_for_file,
+            )
+
             with open(generated_fp, "r", encoding="utf-8") as f:
                 md = f.read()
             html = markdown_convertion_for_file(md)
-            with open(preview_fp, "w", encoding="utf-8") as f: f.write(html)
+            with open(preview_fp, "w", encoding="utf-8") as f:
+                f.write(html)
             promote_file_to_downloadzone(preview_fp, chatbot=chatbot)
             # 生成包含图片的压缩包
             dest_folder = get_log_folder(chatbot.get_user())
-            zip_name = '翻译后的带图文档.zip'
+            zip_name = "翻译后的带图文档.zip"
-            zip_folder(source_folder=ex_folder, dest_folder=dest_folder, zip_name=zip_name)
+            zip_folder(
+                source_folder=ex_folder, dest_folder=dest_folder, zip_name=zip_name
+            )
             zip_fp = os.path.join(dest_folder, zip_name)
             promote_file_to_downloadzone(zip_fp, chatbot=chatbot)
-            yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+            yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+
     md_zip_path = yield from pdf2markdown(fp)
     yield from deliver_to_markdown_plugin(md_zip_path, user_request)
 
+
 def 解析PDF_基于DOC2X(file_manifest, *args):
     for index, fp in enumerate(file_manifest):
         yield from 解析PDF_DOC2X_单文件(fp, *args)
     return
-
-

main.py

@@ -59,8 +59,8 @@ def main():
     # 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
     from check_proxy import get_current_version
-    from themes.theme import adjust_theme, advanced_css, theme_declaration, js_code_clear, js_code_reset, js_code_show_or_hide, js_code_show_or_hide_group2
+    from themes.theme import adjust_theme, advanced_css, theme_declaration, js_code_clear, js_code_show_or_hide, js_code_show_or_hide_group2
-    from themes.theme import js_code_for_toggle_darkmode, js_code_for_persistent_cookie_init
+    from themes.theme import js_code_for_toggle_darkmode
     from themes.theme import load_dynamic_theme, to_cookie_str, from_cookie_str, assign_user_uuid
     title_html = f"""
                 <h1 align="center">GPT Academic {get_current_version()}</h1>
@@ -112,7 +112,7 @@ def main():
             with gr_L2(scale=2, elem_id="gpt-chat"):
                 chatbot = gr.Chatbot(label=f"当前模型：{LLM_MODEL}", elem_id="gpt-chatbot")
                 if LAYOUT == "TOP-DOWN":  chatbot.style(height=CHATBOT_HEIGHT)
-                history, history_cache, history_cache_update = make_history_cache() # 定义 后端state（history）、前端（history_cache）、后端setter（history_cache_update）三兄弟
+                history, _, _ = make_history_cache() # 定义 后端state（history）、前端（history_cache）、后端setter（history_cache_update）三兄弟
             with gr_L2(scale=1, elem_id="gpt-panel"):
                 with gr.Accordion("输入区", open=True, elem_id="input-panel") as area_input_primary:
                     with gr.Row():
@@ -151,7 +151,7 @@ def main():
                         gr.Markdown("<small>插件可读取“输入区”文本/路径作为参数（上传文件自动修正路径）</small>")
                     with gr.Row(elem_id="input-plugin-group"):
                         plugin_group_sel = gr.Dropdown(choices=all_plugin_groups, label='', show_label=False, value=DEFAULT_FN_GROUPS,
-                                                       multiselect=True, interactive=True, elem_classes='normal_mut_select').style(container=False)
+                                                      multiselect=True, interactive=True, elem_classes='normal_mut_select').style(container=False)
                     with gr.Row():
                         for index, (k, plugin) in enumerate(plugins.items()):
                             if not plugin.get("AsButton", True): continue
@@ -180,6 +180,7 @@ def main():
                         with gr.Accordion("点击展开“文件下载区”。", open=False) as area_file_up:
                             file_upload = gr.Files(label="任何文件, 推荐上传压缩文件(zip, tar)", file_count="multiple", elem_id="elem_upload")
 
+
         # 左上角工具栏定义
         from themes.gui_toolbar import define_gui_toolbar
         checkboxes, checkboxes_2, max_length_sl, theme_dropdown, system_prompt, file_upload_2, md_dropdown, top_p, temperature = \
@@ -190,6 +191,9 @@ def main():
         area_input_secondary, txt2, area_customize, _, resetBtn2, clearBtn2, stopBtn2 = \
             define_gui_floating_menu(customize_btns, functional, predefined_btns, cookies, web_cookie_cache)
 
+        # 浮动时间线定义
+        gr.Spark()
+
         # 插件二级菜单的实现
         from themes.gui_advanced_plugin_class import define_gui_advanced_plugin_class
         new_plugin_callback, route_switchy_bt_with_arg, usr_confirmed_arg = \
@@ -228,11 +232,11 @@ def main():
         multiplex_sel.select(
             None, [multiplex_sel], None, _js=f"""(multiplex_sel)=>run_multiplex_shift(multiplex_sel)""")
         cancel_handles.append(submit_btn.click(**predict_args))
-        resetBtn.click(None, None, [chatbot, history, status], _js=js_code_reset)   # 先在前端快速清除chatbot&status
+        resetBtn.click(None, None, [chatbot, history, status], _js="""(a,b,c)=>clear_conversation(a,b,c)""")   # 先在前端快速清除chatbot&status
-        resetBtn2.click(None, None, [chatbot, history, status], _js=js_code_reset)  # 先在前端快速清除chatbot&status
+        resetBtn2.click(None, None, [chatbot, history, status], _js="""(a,b,c)=>clear_conversation(a,b,c)""")  # 先在前端快速清除chatbot&status
-        reset_server_side_args = (lambda history: ([], [], "已重置", json.dumps(history)), [history], [chatbot, history, status, history_cache])
+        # reset_server_side_args = (lambda history: ([], [], "已重置"), [history], [chatbot, history, status])
-        resetBtn.click(*reset_server_side_args)    # 再在后端清除history，把history转存history_cache备用
+        # resetBtn.click(*reset_server_side_args)    # 再在后端清除history
-        resetBtn2.click(*reset_server_side_args)   # 再在后端清除history，把history转存history_cache备用
+        # resetBtn2.click(*reset_server_side_args)   # 再在后端清除history
         clearBtn.click(None, None, [txt, txt2], _js=js_code_clear)
         clearBtn2.click(None, None, [txt, txt2], _js=js_code_clear)
         if AUTO_CLEAR_TXT:
@@ -332,7 +336,7 @@ def main():
         from shared_utils.cookie_manager import load_web_cookie_cache__fn_builder
         load_web_cookie_cache = load_web_cookie_cache__fn_builder(customize_btns, cookies, predefined_btns)
         app_block.load(load_web_cookie_cache, inputs = [web_cookie_cache, cookies],
-                       outputs = [web_cookie_cache, cookies, *customize_btns.values(), *predefined_btns.values()], _js=js_code_for_persistent_cookie_init)
+            outputs = [web_cookie_cache, cookies, *customize_btns.values(), *predefined_btns.values()], _js="""persistent_cookie_init""")
         app_block.load(None, inputs=[], outputs=None, _js=f"""()=>GptAcademicJavaScriptInit("{DARK_MODE}","{INIT_SYS_PROMPT}","{ADD_WAIFU}","{LAYOUT}","{TTS_TYPE}")""")    # 配置暗色主题或亮色主题
         app_block.load(None, inputs=[], outputs=None, _js="""()=>{REP}""".replace("REP", register_advanced_plugin_init_arr))
 

request_llms/bridge_all.py

@@ -26,6 +26,9 @@ from .bridge_chatglm import predict as chatglm_ui
 from .bridge_chatglm3 import predict_no_ui_long_connection as chatglm3_noui
 from .bridge_chatglm3 import predict as chatglm3_ui
 
+from .bridge_chatglm4 import predict_no_ui_long_connection as chatglm4_noui
+from .bridge_chatglm4 import predict as chatglm4_ui
+
 from .bridge_qianfan import predict_no_ui_long_connection as qianfan_noui
 from .bridge_qianfan import predict as qianfan_ui
 
@@ -76,6 +79,7 @@ cohere_endpoint = "https://api.cohere.ai/v1/chat"
 ollama_endpoint = "http://localhost:11434/api/chat"
 yimodel_endpoint = "https://api.lingyiwanwu.com/v1/chat/completions"
 deepseekapi_endpoint = "https://api.deepseek.com/v1/chat/completions"
+grok_model_endpoint = "https://api.x.ai/v1/chat/completions"
 
 if not AZURE_ENDPOINT.endswith('/'): AZURE_ENDPOINT += '/'
 azure_endpoint = AZURE_ENDPOINT + f'openai/deployments/{AZURE_ENGINE}/chat/completions?api-version=2023-05-15'
@@ -97,6 +101,7 @@ if cohere_endpoint in API_URL_REDIRECT: cohere_endpoint = API_URL_REDIRECT[coher
 if ollama_endpoint in API_URL_REDIRECT: ollama_endpoint = API_URL_REDIRECT[ollama_endpoint]
 if yimodel_endpoint in API_URL_REDIRECT: yimodel_endpoint = API_URL_REDIRECT[yimodel_endpoint]
 if deepseekapi_endpoint in API_URL_REDIRECT: deepseekapi_endpoint = API_URL_REDIRECT[deepseekapi_endpoint]
+if grok_model_endpoint in API_URL_REDIRECT: grok_model_endpoint = API_URL_REDIRECT[grok_model_endpoint]
 
 # 获取tokenizer
 tokenizer_gpt35 = LazyloadTiktoken("gpt-3.5-turbo")
@@ -414,6 +419,7 @@ model_info = {
         "token_cnt": get_token_num_gpt4,
     },
 
+    # ChatGLM本地模型
     # 将 chatglm 直接对齐到 chatglm2
     "chatglm": {
         "fn_with_ui": chatglm_ui,
@@ -439,6 +445,14 @@ model_info = {
         "tokenizer": tokenizer_gpt35,
         "token_cnt": get_token_num_gpt35,
     },
+    "chatglm4": {
+        "fn_with_ui": chatglm4_ui,
+        "fn_without_ui": chatglm4_noui,
+        "endpoint": None,
+        "max_token": 8192,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
     "qianfan": {
         "fn_with_ui": qianfan_ui,
         "fn_without_ui": qianfan_noui,
@@ -886,6 +900,31 @@ if any(item in yi_models for item in AVAIL_LLM_MODELS):
         })
     except:
         logger.error(trimmed_format_exc())
+
+
+# -=-=-=-=-=-=- Grok model from x.ai -=-=-=-=-=-=-
+grok_models = ["grok-beta"]
+if any(item in grok_models for item in AVAIL_LLM_MODELS):
+    try:
+        grok_beta_128k_noui, grok_beta_128k_ui = get_predict_function(
+            api_key_conf_name="GROK_API_KEY", max_output_token=8192, disable_proxy=False
+            )
+        
+        model_info.update({
+            "grok-beta": {
+                "fn_with_ui": grok_beta_128k_ui,
+                "fn_without_ui": grok_beta_128k_noui,
+                "can_multi_thread": True,  
+                "endpoint": grok_model_endpoint,
+                "max_token": 128000,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            
+        })
+    except:
+        logger.error(trimmed_format_exc())
+
 # -=-=-=-=-=-=- 讯飞星火认知大模型 -=-=-=-=-=-=-
 if "spark" in AVAIL_LLM_MODELS:
     try:

request_llms/bridge_chatglm3.py

@@ -23,39 +23,33 @@ class GetGLM3Handle(LocalLLMHandle):
         import os
         import platform
 
-        LOCAL_MODEL_QUANT, device = get_conf("LOCAL_MODEL_QUANT", "LOCAL_MODEL_DEVICE")
+        LOCAL_MODEL_PATH, LOCAL_MODEL_QUANT, device = get_conf("CHATGLM_LOCAL_MODEL_PATH", "LOCAL_MODEL_QUANT", "LOCAL_MODEL_DEVICE")
-        _model_name_ = "THUDM/chatglm3-6b"
+        model_path = LOCAL_MODEL_PATH
-        # if LOCAL_MODEL_QUANT == "INT4":  # INT4
-        #     _model_name_ = "THUDM/chatglm3-6b-int4"
-        # elif LOCAL_MODEL_QUANT == "INT8":  # INT8
-        #     _model_name_ = "THUDM/chatglm3-6b-int8"
-        # else:
-        #     _model_name_ = "THUDM/chatglm3-6b"  # FP16
         with ProxyNetworkActivate("Download_LLM"):
             chatglm_tokenizer = AutoTokenizer.from_pretrained(
-                _model_name_, trust_remote_code=True
+                model_path, trust_remote_code=True
             )
             if device == "cpu":
                 chatglm_model = AutoModel.from_pretrained(
-                    _model_name_,
+                    model_path,
                     trust_remote_code=True,
                     device="cpu",
                 ).float()
             elif LOCAL_MODEL_QUANT == "INT4":  # INT4
                 chatglm_model = AutoModel.from_pretrained(
-                    pretrained_model_name_or_path=_model_name_,
+                    pretrained_model_name_or_path=model_path,
                     trust_remote_code=True,
                     quantization_config=BitsAndBytesConfig(load_in_4bit=True),
                 )
             elif LOCAL_MODEL_QUANT == "INT8":  # INT8
                 chatglm_model = AutoModel.from_pretrained(
-                    pretrained_model_name_or_path=_model_name_,
+                    pretrained_model_name_or_path=model_path,
                     trust_remote_code=True,
                     quantization_config=BitsAndBytesConfig(load_in_8bit=True),
                 )
             else:
                 chatglm_model = AutoModel.from_pretrained(
-                    pretrained_model_name_or_path=_model_name_,
+                    pretrained_model_name_or_path=model_path,
                     trust_remote_code=True,
                     device="cuda",
                 )

request_llms/bridge_chatglm4.py

@@ -0,0 +1,81 @@
+model_name = "ChatGLM4"
+cmd_to_install = """
+`pip install -r request_llms/requirements_chatglm4.txt`
+`pip install modelscope`
+`modelscope download --model ZhipuAI/glm-4-9b-chat --local_dir ./THUDM/glm-4-9b-chat`
+"""
+
+
+from toolbox import get_conf, ProxyNetworkActivate
+from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns
+
+
+# ------------------------------------------------------------------------------------------------------------------------
+# 🔌💻 Local Model
+# ------------------------------------------------------------------------------------------------------------------------
+class GetGLM4Handle(LocalLLMHandle):
+
+    def load_model_info(self):
+        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
+        self.model_name = model_name
+        self.cmd_to_install = cmd_to_install
+
+    def load_model_and_tokenizer(self):
+        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
+        import torch
+        from transformers import AutoModel, AutoModelForCausalLM, AutoTokenizer
+        import os
+
+        LOCAL_MODEL_PATH, device = get_conf("CHATGLM_LOCAL_MODEL_PATH", "LOCAL_MODEL_DEVICE")
+        model_path = LOCAL_MODEL_PATH
+        chatglm_tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
+        chatglm_model = AutoModelForCausalLM.from_pretrained(
+            model_path,
+            torch_dtype=torch.bfloat16,
+            low_cpu_mem_usage=True,
+            trust_remote_code=True,
+            device=device
+        ).eval().to(device)
+        self._model = chatglm_model
+        self._tokenizer = chatglm_tokenizer
+        return self._model, self._tokenizer
+
+
+    def llm_stream_generator(self, **kwargs):
+        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
+        def adaptor(kwargs):
+            query = kwargs["query"]
+            max_length = kwargs["max_length"]
+            top_p = kwargs["top_p"]
+            temperature = kwargs["temperature"]
+            history = kwargs["history"]
+            return query, max_length, top_p, temperature, history
+
+        query, max_length, top_p, temperature, history = adaptor(kwargs)
+        inputs = self._tokenizer.apply_chat_template([{"role": "user", "content": query}],
+                                       add_generation_prompt=True,
+                                       tokenize=True,
+                                       return_tensors="pt",
+                                       return_dict=True
+                                       ).to(self._model.device)
+        gen_kwargs = {"max_length": max_length, "do_sample": True, "top_k": top_p}
+
+        outputs = self._model.generate(**inputs, **gen_kwargs)
+        outputs = outputs[:, inputs['input_ids'].shape[1]:]
+        response = self._tokenizer.decode(outputs[0], skip_special_tokens=True)
+        yield response
+
+    def try_to_import_special_deps(self, **kwargs):
+        # import something that will raise error if the user does not install requirement_*.txt
+        # 🏃‍♂️🏃‍♂️🏃‍♂️ 主进程执行
+        import importlib
+
+        # importlib.import_module('modelscope')
+
+
+# ------------------------------------------------------------------------------------------------------------------------
+# 🔌💻 GPT-Academic Interface
+# ------------------------------------------------------------------------------------------------------------------------
+predict_no_ui_long_connection, predict = get_local_llm_predict_fns(
+    GetGLM4Handle, model_name, history_format="chatglm3"
+)

request_llms/bridge_ollama.py

@@ -75,7 +75,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
             # make a POST request to the API endpoint, stream=False
             from .bridge_all import model_info
             endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
-            response = requests.post(endpoint, headers=headers, proxies=proxies,
+            response = requests.post(endpoint, headers=headers, proxies=None,
                                     json=payload, stream=True, timeout=TIMEOUT_SECONDS); break
         except requests.exceptions.ReadTimeout as e:
             retry += 1
@@ -152,10 +152,12 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
     history.append(inputs); history.append("")
 
     retry = 0
+    if proxies is not None:
+        logger.error("Ollama不会使用代理服务器, 忽略了proxies的设置。")
     while True:
         try:
             # make a POST request to the API endpoint, stream=True
-            response = requests.post(endpoint, headers=headers, proxies=proxies,
+            response = requests.post(endpoint, headers=headers, proxies=None,
                                     json=payload, stream=True, timeout=TIMEOUT_SECONDS);break
         except:
             retry += 1

request_llms/requirements_chatglm4.txt

@@ -0,0 +1,7 @@
+protobuf
+cpm_kernels
+torch>=1.10
+transformers>=4.44
+mdtex2html
+sentencepiece
+accelerate

requirements.txt

@@ -1,4 +1,4 @@
-https://public.agent-matrix.com/publish/gradio-3.32.11-py3-none-any.whl
+https://public.agent-matrix.com/publish/gradio-3.32.12-py3-none-any.whl
 fastapi==0.110
 gradio-client==0.8
 pypdf2==2.12.1
@@ -25,7 +25,7 @@ pyautogen
 colorama
 Markdown
 pygments
-edge-tts
+edge-tts>=7.0.0
 pymupdf
 openai
 rjsmin

shared_utils/cookie_manager.py

@@ -77,16 +77,28 @@ def make_history_cache():
     # 定义 后端state（history）、前端（history_cache）、后端setter（history_cache_update）三兄弟
     import gradio as gr
     # 定义history的后端state
-    history = gr.State([])
+    # history = gr.State([])
-    # 定义history的一个孪生的前端存储区（隐藏）
+    history = gr.Textbox(visible=False, elem_id="history-ng")
-    history_cache = gr.Textbox(visible=False, elem_id="history_cache")
+    # # 定义history的一个孪生的前端存储区（隐藏）
-    # 定义history_cache->history的更新方法（隐藏）。在触发这个按钮时，会先执行js代码更新history_cache，然后再执行python代码更新history
+    # history_cache = gr.Textbox(visible=False, elem_id="history_cache")
-    def process_history_cache(history_cache):
+    # # 定义history_cache->history的更新方法（隐藏）。在触发这个按钮时，会先执行js代码更新history_cache，然后再执行python代码更新history
-        return json.loads(history_cache)
+    # def process_history_cache(history_cache):
-    # 另一种更简单的setter方法
+    #     return json.loads(history_cache)
-    history_cache_update = gr.Button("", elem_id="elem_update_history", visible=False).click(
+    # # 另一种更简单的setter方法
-        process_history_cache, inputs=[history_cache], outputs=[history])
+    # history_cache_update = gr.Button("", elem_id="elem_update_history", visible=False).click(
-    return history, history_cache, history_cache_update
+    #     process_history_cache, inputs=[history_cache], outputs=[history])
+    # # save history to history_cache
+    # def process_history_cache(history_cache):
+    #     return json.dumps(history_cache)
+    # # 定义history->history_cache的更新方法（隐藏）
+    # def sync_history_cache(history):
+    #     print("sync_history_cache", history)
+    #     return json.dumps(history)
+    # # history.change(sync_history_cache, inputs=[history], outputs=[history_cache])
+
+    # # history_cache_sync = gr.Button("", elem_id="elem_sync_history", visible=False).click(
+    # #     lambda history: (json.dumps(history)), inputs=[history_cache], outputs=[history])
+    return history, None, None
 
 
 

tests/test_tts.py

@@ -0,0 +1,33 @@
+import edge_tts
+import os
+import httpx
+from toolbox import get_conf
+
+
+async def test_tts():    
+    async with httpx.AsyncClient() as client:
+        try:
+            # Forward the request to the target service
+            import tempfile
+            import edge_tts
+            import wave
+            import uuid
+            from pydub import AudioSegment
+            voice = get_conf("EDGE_TTS_VOICE")
+            tts = edge_tts.Communicate(text="测试", voice=voice)
+            temp_folder = tempfile.gettempdir()
+            temp_file_name = str(uuid.uuid4().hex)
+            temp_file = os.path.join(temp_folder, f'{temp_file_name}.mp3')
+            await tts.save(temp_file)
+            try:
+                mp3_audio = AudioSegment.from_file(temp_file, format="mp3")
+                mp3_audio.export(temp_file, format="wav")
+                with open(temp_file, 'rb') as wav_file: t = wav_file.read()
+            except:
+                raise RuntimeError("ffmpeg未安装，无法处理EdgeTTS音频。安装方法见`https://github.com/jiaaro/pydub#getting-ffmpeg-set-up`")
+        except httpx.RequestError as e:
+            raise RuntimeError(f"请求失败: {e}")
+        
+if __name__ == "__main__":
+    import asyncio
+    asyncio.run(test_tts())

themes/common.css

@@ -270,4 +270,9 @@
 }
 #gpt-submit-row #gpt-submit-dropdown > *:hover {
     cursor: context-menu;
+}
+
+.tooltip.svelte-p2nen8.svelte-p2nen8 {
+    box-shadow: 10px 10px 15px rgba(0, 0, 0, 0.5);
+    left: 10px;
 }

themes/common.js

@@ -318,7 +318,7 @@ function addCopyButton(botElement, index, is_last_in_arr) {
         }
     });
 
-    if (enable_tts){
+    if (enable_tts) {
         var audioButton = document.createElement('button');
         audioButton.classList.add('audio-toggle-btn');
         audioButton.innerHTML = audioIcon;
@@ -346,7 +346,7 @@ function addCopyButton(botElement, index, is_last_in_arr) {
     var messageBtnColumn = document.createElement('div');
     messageBtnColumn.classList.add('message-btn-row');
     messageBtnColumn.appendChild(copyButton);
-    if (enable_tts){
+    if (enable_tts) {
         messageBtnColumn.appendChild(audioButton);
     }
     botElement.appendChild(messageBtnColumn);
@@ -391,6 +391,8 @@ function chatbotContentChanged(attempt = 1, force = false) {
 
                 // Now pass both the message element and the is_last_in_arr boolean to addCopyButton
                 addCopyButton(message, index, is_last_in_arr);
+
+                save_conversation_history();
             });
             // gradioApp().querySelectorAll('#gpt-chatbot .message-wrap .message.bot').forEach(addCopyButton);
         }, i === 0 ? 0 : 200);
@@ -854,8 +856,7 @@ function limit_scroll_position() {
 // -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
 
 function loadLive2D() {
-    if (document.querySelector(".waifu") )
+    if (document.querySelector(".waifu")) {
-    {
         $('.waifu').show();
     } else {
         try {
@@ -922,12 +923,12 @@ function gpt_academic_gradio_saveload(
     if (save_or_load === "load") {
         let value = getCookie(cookie_key);
         if (value) {
-            console.log('加载cookie', elem_id, value)
+            // console.log('加载cookie', elem_id, value)
             push_data_to_gradio_component(value, elem_id, load_type);
         }
         else {
             if (load_default) {
-                console.log('加载cookie的默认值', elem_id, load_default_value)
+                // console.log('加载cookie的默认值', elem_id, load_default_value)
                 push_data_to_gradio_component(load_default_value, elem_id, load_type);
             }
         }
@@ -937,113 +938,149 @@ function gpt_academic_gradio_saveload(
     }
 }
 
+function update_conversation_metadata() {
+    // Create a conversation UUID and timestamp
+    const conversationId = crypto.randomUUID();
+    const timestamp = new Date().toISOString();
+    const conversationData = {
+        id: conversationId,
+        timestamp: timestamp
+    };
+    // Save to cookie
+    setCookie("conversation_metadata", JSON.stringify(conversationData), 2);
+    // read from cookie
+    let conversation_metadata = getCookie("conversation_metadata");
+    // console.log("conversation_metadata", conversation_metadata);
+}
+
+
+// Helper function to generate conversation preview
+function generatePreview(conversation, timestamp, maxLength = 100) {
+    if (!conversation || conversation.length === 0) return "";
+    // Join all messages with dash separator
+    let preview = conversation.join("\n");
+    const readableDate = new Date(timestamp).toLocaleString();
+    preview = readableDate + "\n" + preview;
+    if (preview.length <= maxLength) return preview;
+    return preview.substring(0, maxLength) + "...";
+}
+
+async function save_conversation_history() {
+    // 505030475
+    let chatbot = await get_data_from_gradio_component('gpt-chatbot');
+    let history = await get_data_from_gradio_component('history-ng');
+    let conversation_metadata = getCookie("conversation_metadata");
+    conversation_metadata = JSON.parse(conversation_metadata);
+    // console.log("conversation_metadata", conversation_metadata);
+    let conversation = {
+        timestamp: conversation_metadata.timestamp,
+        id: conversation_metadata.id,
+        metadata: conversation_metadata,
+        conversation: chatbot,
+        history: history,
+        preview: generatePreview(JSON.parse(history), conversation_metadata.timestamp)
+    };
+
+    // Get existing conversation history from local storage
+    let conversation_history = [];
+    try {
+        const stored = localStorage.getItem('conversation_history');
+        if (stored) {
+            conversation_history = JSON.parse(stored);
+        }
+    } catch (e) {
+        // console.error('Error reading conversation history from localStorage:', e);
+    }
+
+    // Find existing conversation with same ID
+    const existingIndex = conversation_history.findIndex(c => c.id === conversation.id);
+
+    if (existingIndex >= 0) {
+        // Update existing conversation
+        conversation_history[existingIndex] = conversation;
+    } else {
+        // Add new conversation
+        conversation_history.push(conversation);
+    }
+
+    // Sort conversations by timestamp, newest first
+    conversation_history.sort((a, b) => {
+        const timeA = new Date(a.timestamp).getTime();
+        const timeB = new Date(b.timestamp).getTime();
+        return timeB - timeA;
+    });
+
+    // Save back to local storage
+    try {
+        localStorage.setItem('conversation_history', JSON.stringify(conversation_history));
+        const LOCAL_STORAGE_UPDATED = "gptac_conversation_history_updated";
+        window.dispatchEvent(
+            new CustomEvent(LOCAL_STORAGE_UPDATED, {
+                detail: conversation_history
+            })
+        );
+    } catch (e) {
+        console.error('Error saving conversation history to localStorage:', e);
+    }
+}
+
+
+function restore_chat_from_local_storage(event) {
+    let conversation = event.detail;
+    push_data_to_gradio_component(conversation.conversation, "gpt-chatbot", "obj");
+    push_data_to_gradio_component(conversation.history, "history-ng", "obj");
+    // console.log("restore_chat_from_local_storage", conversation);
+
+    // Create a conversation UUID and timestamp
+    const conversationId = conversation.id;
+    const timestamp = conversation.timestamp;
+    const conversationData = {
+        id: conversationId,
+        timestamp: timestamp
+    };
+    // Save to cookie
+    setCookie("conversation_metadata", JSON.stringify(conversationData), 2);
+    // read from cookie
+    let conversation_metadata = getCookie("conversation_metadata");
+
+}
+
+
+function clear_conversation(a, b, c) {
+    update_conversation_metadata();
+    let stopButton = document.getElementById("elem_stop");
+    stopButton.click();
+    // console.log("clear_conversation");
+    return reset_conversation(a, b);
+}
+
 
 function reset_conversation(a, b) {
     // console.log("js_code_reset");
     a = btoa(unescape(encodeURIComponent(JSON.stringify(a))));
     setCookie("js_previous_chat_cookie", a, 1);
-    gen_restore_btn();
+    b = btoa(unescape(encodeURIComponent(JSON.stringify(b))));
+    setCookie("js_previous_history_cookie", b, 1);
+    // gen_restore_btn();
     return [[], [], "已重置"];
 }
 
+
 // clear -> 将 history 缓存至 history_cache -> 点击复原 -> restore_previous_chat() -> 触发elem_update_history -> 读取 history_cache
 function restore_previous_chat() {
-    console.log("restore_previous_chat");
+    // console.log("restore_previous_chat");
     let chat = getCookie("js_previous_chat_cookie");
     chat = JSON.parse(decodeURIComponent(escape(atob(chat))));
     push_data_to_gradio_component(chat, "gpt-chatbot", "obj");
-    document.querySelector("#elem_update_history").click(); // in order to call set_history_gr_state, and send history state to server
+    let history = getCookie("js_previous_history_cookie");
+    history = JSON.parse(decodeURIComponent(escape(atob(history))));
+    push_data_to_gradio_component(history, "history-ng", "obj");
+    // document.querySelector("#elem_update_history").click(); // in order to call set_history_gr_state, and send history state to server
 }
 
-function gen_restore_btn() {
-
-
-    // 创建按钮元素
-    const button = document.createElement('div');
-    // const recvIcon = '<span><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" height=".8em" width=".8em" xmlns="http://www.w3.org/2000/svg"><polyline points="20 6 9 17 4 12"></polyline></svg></span>';
-    const rec_svg = '<svg t="1714361184567" style="transform:translate(1px, 2.5px)" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="4389" width="35" height="35"><path d="M320 512h384v64H320zM320 384h384v64H320zM320 640h192v64H320z" p-id="4390" fill="#ffffff"></path><path d="M863.7 544c-1.9 44-11.4 86.8-28.5 127.2-18.5 43.8-45.1 83.2-78.9 117-33.8 33.8-73.2 60.4-117 78.9C593.9 886.3 545.7 896 496 896s-97.9-9.7-143.2-28.9c-43.8-18.5-83.2-45.1-117-78.9-33.8-33.8-60.4-73.2-78.9-117C137.7 625.9 128 577.7 128 528s9.7-97.9 28.9-143.2c18.5-43.8 45.1-83.2 78.9-117s73.2-60.4 117-78.9C398.1 169.7 446.3 160 496 160s97.9 9.7 143.2 28.9c23.5 9.9 45.8 22.2 66.5 36.7l-119.7 20 9.9 59.4 161.6-27 59.4-9.9-9.9-59.4-27-161.5-59.4 9.9 19 114.2C670.3 123.8 586.4 96 496 96 257.4 96 64 289.4 64 528s193.4 432 432 432c233.2 0 423.3-184.8 431.7-416h-64z" p-id="4391" fill="#ffffff"></path></svg>'
-    const recvIcon = '<span>' + rec_svg + '</span>';
-
-    // 设置按钮的样式和属性
-    button.id = 'floatingButton';
-    button.className = 'glow';
-    button.style.textAlign = 'center';
-    button.style.position = 'fixed';
-    button.style.bottom = '10px';
-    button.style.left = '10px';
-    button.style.width = '50px';
-    button.style.height = '50px';
-    button.style.borderRadius = '50%';
-    button.style.backgroundColor = '#007bff';
-    button.style.color = 'white';
-    button.style.display = 'flex';
-    button.style.alignItems = 'center';
-    button.style.justifyContent = 'center';
-    button.style.cursor = 'pointer';
-    button.style.transition = 'all 0.3s ease';
-    button.style.boxShadow = '0 0 10px rgba(0,0,0,0.2)';
-
-    button.innerHTML = recvIcon;
-
-    // 添加发光动画的关键帧
-    const styleSheet = document.createElement('style');
-    styleSheet.id = 'floatingButtonStyle';
-    styleSheet.innerText = `
-    @keyframes glow {
-        from {
-        box-shadow: 0 0 10px rgba(0,0,0,0.2);
-        }
-        to {
-        box-shadow: 0 0 13px rgba(0,0,0,0.5);
-        }
-    }
-    #floatingButton.glow {
-        animation: glow 1s infinite alternate;
-    }
-    #floatingButton:hover {
-        transform: scale(1.2);
-        box-shadow: 0 0 20px rgba(0,0,0,0.4);
-    }
-    #floatingButton.disappearing {
-        animation: shrinkAndDisappear 0.5s forwards;
-    }
-    `;
-
-    // only add when not exist
-    if (!document.getElementById('recvButtonStyle'))
-    {
-        document.head.appendChild(styleSheet);
-    }
-
-    // 鼠标悬停和移开的事件监听器
-    button.addEventListener('mouseover', function () {
-        this.textContent = "还原\n对话";
-    });
-
-    button.addEventListener('mouseout', function () {
-        this.innerHTML = recvIcon;
-    });
-
-    // 点击事件监听器
-    button.addEventListener('click', function () {
-        // 添加一个类来触发缩小和消失的动画
-        restore_previous_chat();
-        this.classList.add('disappearing');
-        // 在动画结束后移除按钮
-        document.body.removeChild(this);
-    });
-    // only add when not exist
-    if (!document.getElementById('recvButton'))
-    {
-        document.body.appendChild(button);
-    }
-
-    // 将按钮添加到页面中
-
-}
 
 async function on_plugin_exe_complete(fn_name) {
-    console.log(fn_name);
+    // console.log(fn_name);
     if (fn_name === "保存当前的对话") {
         // get chat profile path
         let chatbot = await get_data_from_gradio_component('gpt-chatbot');
@@ -1062,15 +1099,15 @@ async function on_plugin_exe_complete(fn_name) {
         }
         let href = get_href(may_have_chat_profile_info);
         if (href) {
-            const cleanedHref = href.replace('file=', ''); // /home/fuqingxu/chatgpt_academic/gpt_log/default_user/chat_history/GPT-Academic对话存档2024-04-12-00-35-06.html
+            const cleanedHref = href.replace('file=', ''); // gpt_log/default_user/chat_history/GPT-Academic对话存档2024-04-12-00-35-06.html
-            console.log(cleanedHref);
+            // console.log(cleanedHref);
         }
 
     }
 }
 
 
-async function generate_menu(guiBase64String, btnName){
+async function generate_menu(guiBase64String, btnName) {
     // assign the button and menu data
     push_data_to_gradio_component(guiBase64String, "invisible_current_pop_up_plugin_arg", "string");
     push_data_to_gradio_component(btnName, "invisible_callback_btn_for_plugin_exe", "string");
@@ -1104,22 +1141,22 @@ async function generate_menu(guiBase64String, btnName){
             ///////////////////////////////////////////////////////////////////////////////////////////
             ////////////////////////////////////    Textbox   ////////////////////////////////////
             ///////////////////////////////////////////////////////////////////////////////////////////
-            if (gui_args[key].type=='string'){ // PLUGIN_ARG_MENU
+            if (gui_args[key].type == 'string') { // PLUGIN_ARG_MENU
                 const component_name = "plugin_arg_txt_" + text_cnt;
                 push_data_to_gradio_component({
                     visible: true,
-                    label: gui_args[key].title + "(" + gui_args[key].description +  ")",
+                    label: gui_args[key].title + "(" + gui_args[key].description + ")",
                     // label: gui_args[key].title,
                     placeholder: gui_args[key].description,
                     __type__: 'update'
                 }, component_name, "obj");
-                if (key === "main_input"){
+                if (key === "main_input") {
                     // 为了与旧插件兼容，生成菜单时，自动加载输入栏的值
                     let current_main_input = await get_data_from_gradio_component('user_input_main');
                     let current_main_input_2 = await get_data_from_gradio_component('user_input_float');
                     push_data_to_gradio_component(current_main_input + current_main_input_2, component_name, "obj");
                 }
-                else if (key === "advanced_arg"){
+                else if (key === "advanced_arg") {
                     // 为了与旧插件兼容，生成菜单时，自动加载旧高级参数输入区的值
                     let advance_arg_input_legacy = await get_data_from_gradio_component('advance_arg_input_legacy');
                     push_data_to_gradio_component(advance_arg_input_legacy, component_name, "obj");
@@ -1134,12 +1171,12 @@ async function generate_menu(guiBase64String, btnName){
             ///////////////////////////////////////////////////////////////////////////////////////////
             ////////////////////////////////////    Dropdown   ////////////////////////////////////
             ///////////////////////////////////////////////////////////////////////////////////////////
-            if (gui_args[key].type=='dropdown'){ // PLUGIN_ARG_MENU
+            if (gui_args[key].type == 'dropdown') { // PLUGIN_ARG_MENU
                 const component_name = "plugin_arg_drop_" + dropdown_cnt;
                 push_data_to_gradio_component({
                     visible: true,
                     choices: gui_args[key].options,
-                    label: gui_args[key].title + "(" + gui_args[key].description +  ")",
+                    label: gui_args[key].title + "(" + gui_args[key].description + ")",
                     // label: gui_args[key].title,
                     placeholder: gui_args[key].description,
                     __type__: 'update'
@@ -1154,7 +1191,7 @@ async function generate_menu(guiBase64String, btnName){
     }
 }
 
-async function execute_current_pop_up_plugin(){
+async function execute_current_pop_up_plugin() {
     let guiBase64String = await get_data_from_gradio_component('invisible_current_pop_up_plugin_arg');
     const stringData = atob(guiBase64String);
     let guiJsonData = JSON.parse(stringData);
@@ -1170,8 +1207,8 @@ async function execute_current_pop_up_plugin(){
     let text_cnt = 0;
     for (const key in gui_args) {
         if (gui_args.hasOwnProperty(key)) {
-            if (gui_args[key].type=='string'){ // PLUGIN_ARG_MENU
+            if (gui_args[key].type == 'string') { // PLUGIN_ARG_MENU
-                corrisponding_elem_id = "plugin_arg_txt_"+text_cnt
+                corrisponding_elem_id = "plugin_arg_txt_" + text_cnt
                 gui_args[key].user_confirmed_value = await get_data_from_gradio_component(corrisponding_elem_id);
                 text_cnt += 1;
             }
@@ -1180,8 +1217,8 @@ async function execute_current_pop_up_plugin(){
     let dropdown_cnt = 0;
     for (const key in gui_args) {
         if (gui_args.hasOwnProperty(key)) {
-            if (gui_args[key].type=='dropdown'){ // PLUGIN_ARG_MENU
+            if (gui_args[key].type == 'dropdown') { // PLUGIN_ARG_MENU
-                corrisponding_elem_id = "plugin_arg_drop_"+dropdown_cnt
+                corrisponding_elem_id = "plugin_arg_drop_" + dropdown_cnt
                 gui_args[key].user_confirmed_value = await get_data_from_gradio_component(corrisponding_elem_id);
                 dropdown_cnt += 1;
             }
@@ -1200,29 +1237,29 @@ async function execute_current_pop_up_plugin(){
 
 }
 
-function hide_all_elem(){
+function hide_all_elem() {
-     // PLUGIN_ARG_MENU
+    // PLUGIN_ARG_MENU
-    for (text_cnt = 0; text_cnt < 8; text_cnt++){
+    for (text_cnt = 0; text_cnt < 8; text_cnt++) {
         push_data_to_gradio_component({
             visible: false,
             label: "",
             __type__: 'update'
-        }, "plugin_arg_txt_"+text_cnt, "obj");
+        }, "plugin_arg_txt_" + text_cnt, "obj");
-        document.getElementById("plugin_arg_txt_"+text_cnt).parentNode.parentNode.style.display = 'none';
+        document.getElementById("plugin_arg_txt_" + text_cnt).parentNode.parentNode.style.display = 'none';
     }
-    for (dropdown_cnt = 0; dropdown_cnt < 8; dropdown_cnt++){
+    for (dropdown_cnt = 0; dropdown_cnt < 8; dropdown_cnt++) {
         push_data_to_gradio_component({
             visible: false,
             choices: [],
             label: "",
             __type__: 'update'
-        }, "plugin_arg_drop_"+dropdown_cnt, "obj");
+        }, "plugin_arg_drop_" + dropdown_cnt, "obj");
-        document.getElementById("plugin_arg_drop_"+dropdown_cnt).parentNode.style.display = 'none';
+        document.getElementById("plugin_arg_drop_" + dropdown_cnt).parentNode.style.display = 'none';
     }
 }
 
-function close_current_pop_up_plugin(){
+function close_current_pop_up_plugin() {
-     // PLUGIN_ARG_MENU
+    // PLUGIN_ARG_MENU
     push_data_to_gradio_component({
         visible: false,
         __type__: 'update'
@@ -1233,15 +1270,13 @@ function close_current_pop_up_plugin(){
 
 // 生成高级插件的选择菜单
 plugin_init_info_lib = {}
-function register_plugin_init(key, base64String){
+function register_plugin_init(key, base64String) {
     // console.log('x')
     const stringData = atob(base64String);
     let guiJsonData = JSON.parse(stringData);
-    if (key in plugin_init_info_lib)
+    if (key in plugin_init_info_lib) {
-    {
     }
-    else
+    else {
-    {
         plugin_init_info_lib[key] = {};
     }
     plugin_init_info_lib[key].info = guiJsonData.Info;
@@ -1251,28 +1286,26 @@ function register_plugin_init(key, base64String){
     plugin_init_info_lib[key].enable_advanced_arg = guiJsonData.AdvancedArgs;
     plugin_init_info_lib[key].arg_reminder = guiJsonData.ArgsReminder;
 }
-function register_advanced_plugin_init_code(key, code){
+function register_advanced_plugin_init_code(key, code) {
-    if (key in plugin_init_info_lib)
+    if (key in plugin_init_info_lib) {
-    {
     }
-    else
+    else {
-    {
         plugin_init_info_lib[key] = {};
     }
     plugin_init_info_lib[key].secondary_menu_code = code;
 }
-function run_advanced_plugin_launch_code(key){
+function run_advanced_plugin_launch_code(key) {
     // convert js code string to function
     generate_menu(plugin_init_info_lib[key].secondary_menu_code, key);
 }
-function on_flex_button_click(key){
+function on_flex_button_click(key) {
-    if (plugin_init_info_lib.hasOwnProperty(key) && plugin_init_info_lib[key].hasOwnProperty('secondary_menu_code')){
+    if (plugin_init_info_lib.hasOwnProperty(key) && plugin_init_info_lib[key].hasOwnProperty('secondary_menu_code')) {
         run_advanced_plugin_launch_code(key);
-    }else{
+    } else {
         document.getElementById("old_callback_btn_for_plugin_exe").click();
     }
 }
-async function run_dropdown_shift(dropdown){
+async function run_dropdown_shift(dropdown) {
     let key = dropdown;
     push_data_to_gradio_component({
         value: key,
@@ -1281,7 +1314,7 @@ async function run_dropdown_shift(dropdown){
         __type__: 'update'
     }, "elem_switchy_bt", "obj");
 
-    if (plugin_init_info_lib[key].enable_advanced_arg){
+    if (plugin_init_info_lib[key].enable_advanced_arg) {
         push_data_to_gradio_component({
             visible: true,
             label: plugin_init_info_lib[key].label,
@@ -1303,9 +1336,9 @@ async function duplicate_in_new_window() {
     window.open(url, '_blank');
 }
 
-async function run_classic_plugin_via_id(plugin_elem_id){
+async function run_classic_plugin_via_id(plugin_elem_id) {
-    for (key in plugin_init_info_lib){
+    for (key in plugin_init_info_lib) {
-        if (plugin_init_info_lib[key].elem_id == plugin_elem_id){
+        if (plugin_init_info_lib[key].elem_id == plugin_elem_id) {
             // 获取按钮名称
             let current_btn_name = await get_data_from_gradio_component(plugin_elem_id);
             // 执行
@@ -1326,7 +1359,7 @@ async function call_plugin_via_name(current_btn_name) {
     hide_all_elem();
     // 为了与旧插件兼容，生成菜单时，自动加载旧高级参数输入区的值
     let advance_arg_input_legacy = await get_data_from_gradio_component('advance_arg_input_legacy');
-    if (advance_arg_input_legacy.length != 0){
+    if (advance_arg_input_legacy.length != 0) {
         gui_args["advanced_arg"] = {};
         gui_args["advanced_arg"].user_confirmed_value = advance_arg_input_legacy;
     }
@@ -1353,7 +1386,7 @@ async function multiplex_function_begin(multiplex_sel) {
     // do not delete `REPLACE_EXTENDED_MULTIPLEX_FUNCTIONS_HERE`! It will be read and replaced by Python code.
     // REPLACE_EXTENDED_MULTIPLEX_FUNCTIONS_HERE
 }
-async function run_multiplex_shift(multiplex_sel){
+async function run_multiplex_shift(multiplex_sel) {
     let key = multiplex_sel;
     if (multiplex_sel === "常规对话") {
         key = "提交";
@@ -1365,3 +1398,8 @@ async function run_multiplex_shift(multiplex_sel){
         __type__: 'update'
     }, "elem_submit_visible", "obj");
 }
+
+
+async function persistent_cookie_init(web_cookie_cache, cookie) {
+    return [localStorage.getItem('web_cookie_cache'), cookie];
+}

themes/gui_floating_menu.py

@@ -1,7 +1,7 @@
 import gradio as gr
 
 def define_gui_floating_menu(customize_btns, functional, predefined_btns, cookies, web_cookie_cache):
-    with gr.Floating(init_x="20%", init_y="50%", visible=False, width="40%", drag="top") as area_input_secondary:
+    with gr.Floating(init_x="20%", init_y="50%", visible=False, width="40%", drag="top", elem_id="f_area_input_secondary") as area_input_secondary:
         with gr.Accordion("浮动输入区", open=True, elem_id="input-panel2"):
             with gr.Row() as row:
                 row.style(equal_height=True)
@@ -17,7 +17,7 @@ def define_gui_floating_menu(customize_btns, functional, predefined_btns, cookie
                     clearBtn2 = gr.Button("清除", elem_id="elem_clear2", variant="secondary", visible=False); clearBtn2.style(size="sm")
 
 
-    with gr.Floating(init_x="20%", init_y="50%", visible=False, width="40%", drag="top") as area_customize:
+    with gr.Floating(init_x="20%", init_y="50%", visible=False, width="40%", drag="top", elem_id="f_area_customize") as area_customize:
         with gr.Accordion("自定义菜单", open=True, elem_id="edit-panel"):
             with gr.Row() as row:
                 with gr.Column(scale=10):
@@ -35,9 +35,9 @@ def define_gui_floating_menu(customize_btns, functional, predefined_btns, cookie
                     # update btn
                     h = basic_fn_confirm.click(assign_btn, [web_cookie_cache, cookies, basic_btn_dropdown, basic_fn_title, basic_fn_prefix, basic_fn_suffix],
                                             [web_cookie_cache, cookies, *customize_btns.values(), *predefined_btns.values()])
-                    h.then(None, [web_cookie_cache], None, _js="""(web_cookie_cache)=>{setCookie("web_cookie_cache", web_cookie_cache, 365);}""")
+                    h.then(None, [web_cookie_cache], None, _js="""(web_cookie_cache)=>{localStorage.setItem("web_cookie_cache", web_cookie_cache);}""")
                     # clean up btn
                     h2 = basic_fn_clean.click(assign_btn, [web_cookie_cache, cookies, basic_btn_dropdown, basic_fn_title, basic_fn_prefix, basic_fn_suffix, gr.State(True)],
                                             [web_cookie_cache, cookies, *customize_btns.values(), *predefined_btns.values()])
-                    h2.then(None, [web_cookie_cache], None, _js="""(web_cookie_cache)=>{setCookie("web_cookie_cache", web_cookie_cache, 365);}""")
+                    h2.then(None, [web_cookie_cache], None, _js="""(web_cookie_cache)=>{localStorage.setItem("web_cookie_cache", web_cookie_cache);}""")
     return area_input_secondary, txt2, area_customize, submitBtn2, resetBtn2, clearBtn2, stopBtn2

themes/init.js

@@ -3,6 +3,8 @@ async function GptAcademicJavaScriptInit(dark, prompt, live2d, layout, tts) {
     audio_fn_init();
     minor_ui_adjustment();
     ButtonWithDropdown_init();
+    update_conversation_metadata();
+    window.addEventListener("gptac_restore_chat_from_local_storage", restore_chat_from_local_storage);
     
     // 加载欢迎页面
     const welcomeMessage = new WelcomeMessage();

themes/theme.py

@@ -87,21 +87,6 @@ js_code_for_toggle_darkmode = """() => {
 }"""
 
 
-js_code_for_persistent_cookie_init = """(web_cookie_cache, cookie) => {
-    return [getCookie("web_cookie_cache"), cookie];
-}
-"""
-
-# 详见 themes/common.js
-js_code_reset = """
-(a,b,c)=>{
-    let stopButton = document.getElementById("elem_stop");
-    stopButton.click();
-    return reset_conversation(a,b);
-}
-"""
-
-
 js_code_clear = """
 (a,b)=>{
     return ["", ""];

toolbox.py

@@ -8,6 +8,7 @@ import base64
 import gradio
 import shutil
 import glob
+import json
 import uuid
 from loguru import logger
 from functools import wraps
@@ -92,8 +93,9 @@ def ArgsGeneralWrapper(f):
     """
     def decorated(request: gradio.Request, cookies:dict, max_length:int, llm_model:str,
                   txt:str, txt2:str, top_p:float, temperature:float, chatbot:list,
-                  history:list, system_prompt:str, plugin_advanced_arg:dict, *args):
+                  json_history:str, system_prompt:str, plugin_advanced_arg:dict, *args):
         txt_passon = txt
+        history = json.loads(json_history) if json_history else []
         if txt == "" and txt2 != "": txt_passon = txt2
         # 引入一个有cookie的chatbot
         if request.username is not None:
@@ -148,10 +150,11 @@ def ArgsGeneralWrapper(f):
     return decorated
 
 
-def update_ui(chatbot:ChatBotWithCookies, history, msg="正常", **kwargs):  # 刷新界面
+def update_ui(chatbot:ChatBotWithCookies, history:list, msg:str="正常", **kwargs):  # 刷新界面
     """
     刷新用户界面
     """
+    assert isinstance(history, list), "history必须是一个list"
     assert isinstance(
         chatbot, ChatBotWithCookies
     ), "在传递chatbot的过程中不要将其丢弃。必要时, 可用clear将其清空, 然后用for+append循环重新赋值。"
@@ -175,10 +178,11 @@ def update_ui(chatbot:ChatBotWithCookies, history, msg="正常", **kwargs):  #
     else:
         chatbot_gr = chatbot
 
-    yield cookies, chatbot_gr, history, msg
+    json_history = json.dumps(history, ensure_ascii=False)
+    yield cookies, chatbot_gr, json_history, msg
 
 
-def update_ui_lastest_msg(lastmsg:str, chatbot:ChatBotWithCookies, history:list, delay=1, msg="正常"):  # 刷新界面
+def update_ui_lastest_msg(lastmsg:str, chatbot:ChatBotWithCookies, history:list, delay:float=1, msg:str="正常"):  # 刷新界面
     """
     刷新用户界面
     """

version

@@ -1,5 +1,5 @@
 {
-  "version": 3.90,
+  "version": 3.91,
   "show_feature": true,
-  "new_feature": "支持chatgpt-4o-latest <-> 增加RAG组件 <-> 升级多合一主提交键"
+  "new_feature": "优化前端并修复TTS的BUG <-> 添加时间线回溯功能 <-> 支持chatgpt-4o-latest <-> 增加RAG组件 <-> 升级多合一主提交键"
 }