control whether to allow sharing translation results with GPTAC academic cloud.

* Update bridge_all.py

* Update bridge_chatgpt.py

* Update bridge_chatgpt.py

* Update bridge_all.py

* Update bridge_all.py

.github/workflows/build-with-jittorllms.yml

@@ -1,44 +0,0 @@
-# https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
-name: build-with-jittorllms
-
-on:
-  push:
-    branches:
-      - 'master'
-
-env:
-  REGISTRY: ghcr.io
-  IMAGE_NAME: ${{ github.repository }}_jittorllms
-
-jobs:
-  build-and-push-image:
-    runs-on: ubuntu-latest
-    permissions:
-      contents: read
-      packages: write
-
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v3
-
-      - name: Log in to the Container registry
-        uses: docker/login-action@v2
-        with:
-          registry: ${{ env.REGISTRY }}
-          username: ${{ github.actor }}
-          password: ${{ secrets.GITHUB_TOKEN }}
-
-      - name: Extract metadata (tags, labels) for Docker
-        id: meta
-        uses: docker/metadata-action@v4
-        with:
-          images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
-
-      - name: Build and push Docker image
-        uses: docker/build-push-action@v4
-        with:
-          context: .
-          push: true
-          file: docs/GithubAction+JittorLLMs
-          tags: ${{ steps.meta.outputs.tags }}
-          labels: ${{ steps.meta.outputs.labels }}

.github/workflows/build-with-latex-arm.yml

@@ -1,14 +1,14 @@
 # https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
-name: build-with-all-capacity-beta
+name: build-with-latex-arm
 
 on:
   push:
     branches:
-      - 'master'
+      - "master"
 
 env:
   REGISTRY: ghcr.io
-  IMAGE_NAME: ${{ github.repository }}_with_all_capacity_beta
+  IMAGE_NAME: ${{ github.repository }}_with_latex_arm
 
 jobs:
   build-and-push-image:
@@ -18,11 +18,17 @@ jobs:
       packages: write
 
     steps:
+      - name: Set up QEMU
+        uses: docker/setup-qemu-action@v3
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
       - name: Checkout repository
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
 
       - name: Log in to the Container registry
-        uses: docker/login-action@v2
+        uses: docker/login-action@v3
         with:
           registry: ${{ env.REGISTRY }}
           username: ${{ github.actor }}
@@ -35,10 +41,11 @@ jobs:
           images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
 
       - name: Build and push Docker image
-        uses: docker/build-push-action@v4
+        uses: docker/build-push-action@v6
         with:
           context: .
           push: true
-          file: docs/GithubAction+AllCapacityBeta
+          platforms: linux/arm64
+          file: docs/GithubAction+NoLocal+Latex+Arm
           tags: ${{ steps.meta.outputs.tags }}
-          labels: ${{ steps.meta.outputs.labels }}
+          labels: ${{ steps.meta.outputs.labels }}

README.md

@@ -1,5 +1,6 @@
 > [!IMPORTANT]
-> 2024.6.1: 版本3.80加入插件二级菜单功能（详见wiki）  
+> 2024.10.10: 突发停电，紧急恢复了提供[whl包](https://drive.google.com/file/d/19U_hsLoMrjOlQSzYS3pzWX9fTzyusArP/view?usp=sharing)的文件服务器  
+> 2024.10.8: 版本3.90加入对llama-index的初步支持，版本3.80加入插件二级菜单功能（详见wiki）  
 > 2024.5.1: 加入Doc2x翻译PDF论文的功能，[查看详情](https://github.com/binary-husky/gpt_academic/wiki/Doc2x)  
 > 2024.3.11: 全力支持Qwen、GLM、DeepseekCoder等中文大语言模型！ SoVits语音克隆模块，[查看详情](https://www.bilibili.com/video/BV1Rp421S7tF/) 
 > 2024.1.17: 安装依赖时，请选择`requirements.txt`中**指定的版本**。 安装命令：`pip install -r requirements.txt`。本项目完全开源免费，您可通过订阅[在线服务](https://github.com/binary-husky/gpt_academic/wiki/online)的方式鼓励本项目的发展。

crazy_functional.py

@@ -6,7 +6,6 @@ from loguru import logger
 def get_crazy_functions():
     from crazy_functions.读文章写摘要 import 读文章写摘要
     from crazy_functions.生成函数注释 import 批量生成函数注释
-    from crazy_functions.Rag_Interface import Rag问答
     from crazy_functions.SourceCode_Analyse import 解析项目本身
     from crazy_functions.SourceCode_Analyse import 解析一个Python项目
     from crazy_functions.SourceCode_Analyse import 解析一个Matlab项目
@@ -52,13 +51,6 @@ def get_crazy_functions():
     from crazy_functions.SourceCode_Comment import 注释Python项目
 
     function_plugins = {
-        "Rag智能召回": {
-            "Group": "对话",
-            "Color": "stop",
-            "AsButton": False,
-            "Info": "将问答数据记录到向量库中，作为长期参考。",
-            "Function": HotReload(Rag问答),
-        },
         "虚空终端": {
             "Group": "对话|编程|学术|智能体",
             "Color": "stop",
@@ -707,6 +699,31 @@ def get_crazy_functions():
         logger.error(trimmed_format_exc())
         logger.error("Load function plugin failed")
 
+    try:
+        from crazy_functions.Rag_Interface import Rag问答
+
+        function_plugins.update(
+            {
+                "Rag智能召回": {
+                    "Group": "对话",
+                    "Color": "stop",
+                    "AsButton": False,
+                    "Info": "将问答数据记录到向量库中，作为长期参考。",
+                    "Function": HotReload(Rag问答),
+                },
+            }
+        )
+    except:
+        logger.error(trimmed_format_exc())
+        logger.error("Load function plugin failed")
+
+
+    
+
+
+
+
+
     # try:
     #     from crazy_functions.高级功能函数模板 import 测试图表渲染
     #     function_plugins.update({

crazy_functions/Latex_Function.py

@@ -3,7 +3,7 @@ from toolbox import CatchException, report_exception, update_ui_lastest_msg, zip
 from functools import partial
 from loguru import logger
 
-import glob, os, requests, time, json, tarfile
+import glob, os, requests, time, json, tarfile, threading
 
 pj = os.path.join
 ARXIV_CACHE_DIR = get_conf("ARXIV_CACHE_DIR")
@@ -138,25 +138,43 @@ def arxiv_download(chatbot, history, txt, allow_cache=True):
     cached_translation_pdf = check_cached_translation_pdf(arxiv_id)
     if cached_translation_pdf and allow_cache: return cached_translation_pdf, arxiv_id
 
-    url_tar = url_.replace('/abs/', '/e-print/')
-    translation_dir = pj(ARXIV_CACHE_DIR, arxiv_id, 'e-print')
     extract_dst = pj(ARXIV_CACHE_DIR, arxiv_id, 'extract')
-    os.makedirs(translation_dir, exist_ok=True)
-
-    # <-------------- download arxiv source file ------------->
+    translation_dir = pj(ARXIV_CACHE_DIR, arxiv_id, 'e-print')
     dst = pj(translation_dir, arxiv_id + '.tar')
-    if os.path.exists(dst):
-        yield from update_ui_lastest_msg("调用缓存", chatbot=chatbot, history=history)  # 刷新界面
+    os.makedirs(translation_dir, exist_ok=True)
+    # <-------------- download arxiv source file ------------->
+
+    def fix_url_and_download():
+        # for url_tar in [url_.replace('/abs/', '/e-print/'), url_.replace('/abs/', '/src/')]:
+        for url_tar in [url_.replace('/abs/', '/src/'), url_.replace('/abs/', '/e-print/')]:
+            proxies = get_conf('proxies')
+            r = requests.get(url_tar, proxies=proxies)
+            if r.status_code == 200:
+                with open(dst, 'wb+') as f:
+                    f.write(r.content)
+                return True
+        return False
+
+    if os.path.exists(dst) and allow_cache:
+        yield from update_ui_lastest_msg(f"调用缓存 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+        success = True
     else:
-        yield from update_ui_lastest_msg("开始下载", chatbot=chatbot, history=history)  # 刷新界面
-        proxies = get_conf('proxies')
-        r = requests.get(url_tar, proxies=proxies)
-        with open(dst, 'wb+') as f:
-            f.write(r.content)
+        yield from update_ui_lastest_msg(f"开始下载 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+        success = fix_url_and_download()
+        yield from update_ui_lastest_msg(f"下载完成 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+
+
+    if not success:
+        yield from update_ui_lastest_msg(f"下载失败 {arxiv_id}", chatbot=chatbot, history=history)
+        raise tarfile.ReadError(f"论文下载失败 {arxiv_id}")
+
     # <-------------- extract file ------------->
-    yield from update_ui_lastest_msg("下载完成", chatbot=chatbot, history=history)  # 刷新界面
     from toolbox import extract_archive
-    extract_archive(file_path=dst, dest_dir=extract_dst)
+    try:
+        extract_archive(file_path=dst, dest_dir=extract_dst)
+    except tarfile.ReadError:
+        os.remove(dst)
+        raise tarfile.ReadError(f"论文下载失败")
     return extract_dst, arxiv_id
 
 
@@ -320,11 +338,17 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
     # <-------------- more requirements ------------->
     if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
     more_req = plugin_kwargs.get("advanced_arg", "")
-    no_cache = more_req.startswith("--no-cache")
-    if no_cache: more_req.lstrip("--no-cache")
+
+    no_cache = ("--no-cache" in more_req)
+    if no_cache: more_req = more_req.replace("--no-cache", "").strip()
+
+    allow_gptac_cloud_io = ("--allow-cloudio" in more_req)  # 从云端下载翻译结果，以及上传翻译结果到云端
+    if allow_gptac_cloud_io: more_req = more_req.replace("--allow-cloudio", "").strip()
+
     allow_cache = not no_cache
     _switch_prompt_ = partial(switch_prompt, more_requirement=more_req)
 
+
     # <-------------- check deps ------------->
     try:
         import glob, os, time, subprocess
@@ -351,6 +375,20 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
         yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
         return
 
+    # #################################################################
+    if allow_gptac_cloud_io and arxiv_id:
+        # 访问 GPTAC学术云，查询云端是否存在该论文的翻译版本
+        from crazy_functions.latex_fns.latex_actions import check_gptac_cloud
+        success, downloaded = check_gptac_cloud(arxiv_id, chatbot)
+        if success:
+            chatbot.append([
+                f"检测到GPTAC云端存在翻译版本, 如果不满意翻译结果, 请禁用云端分享, 然后重新执行。", 
+                None
+            ])
+            yield from update_ui(chatbot=chatbot, history=history)
+            return
+    #################################################################
+
     if os.path.exists(txt):
         project_folder = txt
     else:
@@ -388,14 +426,21 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
     # <-------------- zip PDF ------------->
     zip_res = zip_result(project_folder)
     if success:
+        if allow_gptac_cloud_io and arxiv_id:
+            # 如果用户允许，我们将翻译好的arxiv论文PDF上传到GPTAC学术云
+            from crazy_functions.latex_fns.latex_actions import upload_to_gptac_cloud_if_user_allow
+            threading.Thread(target=upload_to_gptac_cloud_if_user_allow, 
+                args=(chatbot, arxiv_id), daemon=True).start()
+
         chatbot.append((f"成功啦", '请查收结果（压缩包）...'))
-        yield from update_ui(chatbot=chatbot, history=history);
+        yield from update_ui(chatbot=chatbot, history=history)
         time.sleep(1)  # 刷新界面
         promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
+
     else:
         chatbot.append((f"失败了",
                         '虽然PDF生成失败了, 但请查收结果（压缩包）, 内含已经翻译的Tex文档, 您可以到Github Issue区, 用该压缩包进行反馈。如系统是Linux，请检查系统字体（见Github wiki） ...'))
-        yield from update_ui(chatbot=chatbot, history=history);
+        yield from update_ui(chatbot=chatbot, history=history)
         time.sleep(1)  # 刷新界面
         promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
 

crazy_functions/Latex_Function_Wrap.py

@@ -30,6 +30,9 @@ class Arxiv_Localize(GptAcademicPluginTemplate):
                             default_value="", type="string").model_dump_json(), # 高级参数输入区，自动同步
             "allow_cache":
                 ArgProperty(title="是否允许从缓存中调取结果", options=["允许缓存", "从头执行"], default_value="允许缓存", description="无", type="dropdown").model_dump_json(),
+            "allow_cloudio":
+                ArgProperty(title="是否允许向GPTAC学术云共享翻译结果", options=["允许", "禁止"], default_value="禁止", description="人人为我，我为人人", type="dropdown").model_dump_json(),
+
         }
         return gui_definition
 
@@ -38,9 +41,14 @@ class Arxiv_Localize(GptAcademicPluginTemplate):
         执行插件
         """
         allow_cache = plugin_kwargs["allow_cache"]
+        allow_cloudio = plugin_kwargs["allow_cloudio"]
         advanced_arg = plugin_kwargs["advanced_arg"]
 
         if allow_cache == "从头执行": plugin_kwargs["advanced_arg"] = "--no-cache " + plugin_kwargs["advanced_arg"]
+
+        # 从云端下载翻译结果，以及上传翻译结果到云端；人人为我，我为人人。
+        if allow_cloudio == "允许": plugin_kwargs["advanced_arg"] = "--allow-cloudio " + plugin_kwargs["advanced_arg"]
+
         yield from Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
 
 

crazy_functions/Rag_Interface.py

@@ -1,53 +1,108 @@
+import os,glob
+from typing import List
+
+from shared_utils.fastapi_server import validate_path_safety
+
+from toolbox import report_exception
 from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_lastest_msg
+from shared_utils.fastapi_server import validate_path_safety
 from crazy_functions.crazy_utils import input_clipping
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 
-VECTOR_STORE_TYPE = "Milvus"
-
-if VECTOR_STORE_TYPE == "Milvus":
-    try:
-        from crazy_functions.rag_fns.milvus_worker import MilvusRagWorker as LlamaIndexRagWorker
-    except:
-        VECTOR_STORE_TYPE = "Simple"
-
-if VECTOR_STORE_TYPE == "Simple":
-    from crazy_functions.rag_fns.llama_index_worker import LlamaIndexRagWorker
-
-
 RAG_WORKER_REGISTER = {}
-
 MAX_HISTORY_ROUND = 5
 MAX_CONTEXT_TOKEN_LIMIT = 4096
 REMEMBER_PREVIEW = 1000
 
+@CatchException
+def handle_document_upload(files: List[str], llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request, rag_worker):
+    """
+    Handles document uploads by extracting text and adding it to the vector store.
+    """
+    from llama_index.core import Document
+    from crazy_functions.rag_fns.rag_file_support import extract_text, supports_format
+    user_name = chatbot.get_user()
+    checkpoint_dir = get_log_folder(user_name, plugin_name='experimental_rag')
+
+    for file_path in files:
+        try:
+            validate_path_safety(file_path, user_name)
+            text = extract_text(file_path)
+            if text is None:
+                chatbot.append(
+                    [f"上传文件: {os.path.basename(file_path)}", f"文件解析失败，无法提取文本内容，请更换文件。失败原因可能为：1.文档格式过于复杂；2. 不支持的文件格式，支持的文件格式后缀有:" + ", ".join(supports_format)])
+            else:
+                chatbot.append(
+                    [f"上传文件: {os.path.basename(file_path)}", f"上传文件前50个字符为:{text[:50]}。"])
+                document = Document(text=text, metadata={"source": file_path})
+                rag_worker.add_documents_to_vector_store([document])
+                chatbot.append([f"上传文件: {os.path.basename(file_path)}", "文件已成功添加到知识库。"])
+        except Exception as e:
+            report_exception(chatbot, history, a=f"处理文件: {file_path}", b=str(e))
+
+    yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+
+
+
+# Main Q&A function with document upload support
 @CatchException
 def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
 
+    # import vector store lib
+    VECTOR_STORE_TYPE = "Milvus"
+    if VECTOR_STORE_TYPE == "Milvus":
+        try:
+            from crazy_functions.rag_fns.milvus_worker import MilvusRagWorker as LlamaIndexRagWorker
+        except:
+            VECTOR_STORE_TYPE = "Simple"
+    if VECTOR_STORE_TYPE == "Simple":
+        from crazy_functions.rag_fns.llama_index_worker import LlamaIndexRagWorker
+
     # 1. we retrieve rag worker from global context
     user_name = chatbot.get_user()
     checkpoint_dir = get_log_folder(user_name, plugin_name='experimental_rag')
+
     if user_name in RAG_WORKER_REGISTER:
         rag_worker = RAG_WORKER_REGISTER[user_name]
     else:
         rag_worker = RAG_WORKER_REGISTER[user_name] = LlamaIndexRagWorker(
-            user_name, 
-            llm_kwargs, 
-            checkpoint_dir=checkpoint_dir, 
-            auto_load_checkpoint=True)
+            user_name,
+            llm_kwargs,
+            checkpoint_dir=checkpoint_dir,
+            auto_load_checkpoint=True
+        )
+
     current_context = f"{VECTOR_STORE_TYPE} @ {checkpoint_dir}"
     tip = "提示：输入“清空向量数据库”可以清空RAG向量数据库"
-    if txt == "清空向量数据库":
-        chatbot.append([txt, f'正在清空 ({current_context}) ...'])
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-        rag_worker.purge()
-        yield from update_ui_lastest_msg('已清空', chatbot, history, delay=0) # 刷新界面
+
+    # 2. Handle special commands
+    if os.path.exists(txt) and os.path.isdir(txt):
+        project_folder = txt
+        validate_path_safety(project_folder, chatbot.get_user())
+        # Extract file paths from the user input
+        # Assuming the user inputs file paths separated by commas after the command
+        file_paths =  [f for f in glob.glob(f'{project_folder}/**/*', recursive=True)]
+        chatbot.append([txt, f'正在处理上传的文档 ({current_context}) ...'])
+        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+
+        yield from handle_document_upload(file_paths, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request, rag_worker)
         return
 
-    chatbot.append([txt, f'正在召回知识 ({current_context}) ...'])
-    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+    elif txt == "清空向量数据库":
+        chatbot.append([txt, f'正在清空 ({current_context}) ...'])
+        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+        rag_worker.purge_vector_store()
+        yield from update_ui_lastest_msg('已清空', chatbot, history, delay=0)  # 刷新界面
+        return
 
-    # 2. clip history to reduce token consumption
-    #   2-1. reduce chat round
+    else:
+        report_exception(chatbot, history, a=f"上传文件路径错误: {txt}", b="请检查并提供正确路径。")
+
+    # 3. Normal Q&A processing
+    chatbot.append([txt, f'正在召回知识 ({current_context}) ...'])
+    yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+
+    # 4. Clip history to reduce token consumption
     txt_origin = txt
 
     if len(history) > MAX_HISTORY_ROUND * 2:
@@ -55,41 +110,47 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
     txt_clip, history, flags = input_clipping(txt, history, max_token_limit=MAX_CONTEXT_TOKEN_LIMIT, return_clip_flags=True)
     input_is_clipped_flag = (flags["original_input_len"] != flags["clipped_input_len"])
 
-    #   2-2. if input is clipped, add input to vector store before retrieve
+    # 5. If input is clipped, add input to vector store before retrieve
     if input_is_clipped_flag:
-        yield from update_ui_lastest_msg('检测到长输入, 正在向量化 ...', chatbot, history, delay=0) # 刷新界面
-        # save input to vector store
+        yield from update_ui_lastest_msg('检测到长输入, 正在向量化 ...', chatbot, history, delay=0)  # 刷新界面
+        # Save input to vector store
         rag_worker.add_text_to_vector_store(txt_origin)
-        yield from update_ui_lastest_msg('向量化完成 ...', chatbot, history, delay=0) # 刷新界面
+        yield from update_ui_lastest_msg('向量化完成 ...', chatbot, history, delay=0)  # 刷新界面
+
         if len(txt_origin) > REMEMBER_PREVIEW:
-            HALF = REMEMBER_PREVIEW//2
+            HALF = REMEMBER_PREVIEW // 2
             i_say_to_remember = txt[:HALF] + f" ...\n...(省略{len(txt_origin)-REMEMBER_PREVIEW}字)...\n... " + txt[-HALF:]
             if (flags["original_input_len"] - flags["clipped_input_len"]) > HALF:
-                txt_clip = txt_clip  + f" ...\n...(省略{len(txt_origin)-len(txt_clip)-HALF}字)...\n... " + txt[-HALF:]
-            else:
-                pass
-            i_say = txt_clip
+                txt_clip = txt_clip + f" ...\n...(省略{len(txt_origin)-len(txt_clip)-HALF}字)...\n... " + txt[-HALF:]
         else:
             i_say_to_remember = i_say = txt_clip
     else:
         i_say_to_remember = i_say = txt_clip
 
-    # 3. we search vector store and build prompts
+    # 6. Search vector store and build prompts
     nodes = rag_worker.retrieve_from_store_with_query(i_say)
     prompt = rag_worker.build_prompt(query=i_say, nodes=nodes)
+    # 7. Query language model
+    if len(chatbot) != 0:
+        chatbot.pop(-1)  # Pop temp chat, because we are going to add them again inside `request_gpt_model_in_new_thread_with_ui_alive`
 
-    # 4. it is time to query llms
-    if len(chatbot) != 0: chatbot.pop(-1) # pop temp chat, because we are going to add them again inside `request_gpt_model_in_new_thread_with_ui_alive`
     model_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-        inputs=prompt, inputs_show_user=i_say,
-        llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
+        inputs=prompt,
+        inputs_show_user=i_say,
+        llm_kwargs=llm_kwargs,
+        chatbot=chatbot,
+        history=history,
         sys_prompt=system_prompt,
         retry_times_at_unknown_error=0
     )
 
-    # 5. remember what has been asked / answered
-    yield from update_ui_lastest_msg(model_say + '</br></br>' + f'对话记忆中, 请稍等 ({current_context}) ...', chatbot, history, delay=0.5) # 刷新界面
+    # 8. Remember Q&A
+    yield from update_ui_lastest_msg(
+        model_say + '</br></br>' + f'对话记忆中, 请稍等 ({current_context}) ...',
+        chatbot, history, delay=0.5
+    )
     rag_worker.remember_qa(i_say_to_remember, model_say)
     history.extend([i_say, model_say])
 
-    yield from update_ui_lastest_msg(model_say, chatbot, history, delay=0, msg=tip) # 刷新界面
+    # 9. Final UI Update
+    yield from update_ui_lastest_msg(model_say, chatbot, history, delay=0, msg=tip)

crazy_functions/latex_fns/latex_actions.py

@@ -3,7 +3,7 @@ import re
 import shutil
 import numpy as np
 from loguru import logger
-from toolbox import update_ui, update_ui_lastest_msg, get_log_folder
+from toolbox import update_ui, update_ui_lastest_msg, get_log_folder, gen_time_str
 from toolbox import get_conf, promote_file_to_downloadzone
 from crazy_functions.latex_fns.latex_toolbox import PRESERVE, TRANSFORM
 from crazy_functions.latex_fns.latex_toolbox import set_forbidden_text, set_forbidden_text_begin_end, set_forbidden_text_careful_brace
@@ -423,6 +423,9 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
                 except Exception as e:
                     logger.error(e)
                     pass
+
+
+
             return True # 成功啦
         else:
             if n_fix>=max_try: break
@@ -468,3 +471,66 @@ def write_html(sp_file_contents, sp_file_result, chatbot, project_folder):
     except:
         from toolbox import trimmed_format_exc
         logger.error('writing html result failed:', trimmed_format_exc())
+
+
+def upload_to_gptac_cloud_if_user_allow(chatbot, arxiv_id):
+    try:
+        # 如果用户允许，我们将arxiv论文PDF上传到GPTAC学术云
+        from toolbox import map_file_to_sha256
+        # 检查是否顺利，如果没有生成预期的文件，则跳过
+        is_result_good = False
+        for file_path in chatbot._cookies.get("files_to_promote", []):
+            if file_path.endswith('translate_zh.pdf'):
+                is_result_good = True
+        if not is_result_good:
+            return
+        # 上传文件
+        for file_path in chatbot._cookies.get("files_to_promote", []):
+            align_name = None
+            # normalized name
+            for name in ['translate_zh.pdf', 'comparison.pdf']:
+                if file_path.endswith(name): align_name = name
+            # if match any align name
+            if align_name:
+                logger.info(f'Uploading to GPTAC cloud as the user has set `allow_cloud_io`: {file_path}')
+                with open(file_path, 'rb') as f:
+                    import requests
+                    url = 'https://cloud-2.agent-matrix.com/upload'
+                    files = {'file': (align_name, f, 'application/octet-stream')}
+                    data = {
+                        'arxiv_id': arxiv_id,
+                        'file_hash': map_file_to_sha256(file_path),
+                    }
+                    resp = requests.post(url=url, files=files, data=data, timeout=30)
+                logger.info(f'Uploading terminate ({resp.status_code})`: {file_path}')
+    except:
+        # 如果上传失败，不会中断程序，因为这是次要功能
+        pass
+
+def check_gptac_cloud(arxiv_id, chatbot):
+    import requests
+    success = False
+    downloaded = []
+    try:
+        for pdf_target in ['translate_zh.pdf', 'comparison.pdf']:
+            url = 'https://cloud-2.agent-matrix.com/paper_exist'
+            data = {
+                'arxiv_id': arxiv_id,
+                'name': pdf_target,
+            }
+            resp = requests.post(url=url, data=data)
+            cache_hit_result = resp.text.strip('"')
+            if cache_hit_result.startswith("http"):
+                url = cache_hit_result
+                logger.info(f'Downloading from GPTAC cloud: {url}')
+                resp = requests.get(url=url, timeout=30)
+                target = os.path.join(get_log_folder(plugin_name='gptac_cloud'), gen_time_str(), pdf_target)
+                os.makedirs(os.path.dirname(target), exist_ok=True)
+                with open(target, 'wb') as f:
+                    f.write(resp.content)
+                new_path = promote_file_to_downloadzone(target, chatbot=chatbot)
+                success = True
+                downloaded.append(new_path)
+    except:
+        pass
+    return success, downloaded

crazy_functions/latex_fns/latex_toolbox.py

@@ -644,6 +644,216 @@ def run_in_subprocess(func):
 
 
 def _merge_pdfs(pdf1_path, pdf2_path, output_path):
+    try:
+        logger.info("Merging PDFs using _merge_pdfs_ng")
+        _merge_pdfs_ng(pdf1_path, pdf2_path, output_path)
+    except:
+        logger.info("Merging PDFs using _merge_pdfs_legacy")
+        _merge_pdfs_legacy(pdf1_path, pdf2_path, output_path)
+
+
+def _merge_pdfs_ng(pdf1_path, pdf2_path, output_path):
+    import PyPDF2  # PyPDF2这个库有严重的内存泄露问题，把它放到子进程中运行，从而方便内存的释放
+    from PyPDF2.generic import NameObject, TextStringObject, ArrayObject, FloatObject, NumberObject
+
+    Percent = 1
+    # raise RuntimeError('PyPDF2 has a serious memory leak problem, please use other tools to merge PDF files.')
+    # Open the first PDF file
+    with open(pdf1_path, "rb") as pdf1_file:
+        pdf1_reader = PyPDF2.PdfFileReader(pdf1_file)
+        # Open the second PDF file
+        with open(pdf2_path, "rb") as pdf2_file:
+            pdf2_reader = PyPDF2.PdfFileReader(pdf2_file)
+            # Create a new PDF file to store the merged pages
+            output_writer = PyPDF2.PdfFileWriter()
+            # Determine the number of pages in each PDF file
+            num_pages = max(pdf1_reader.numPages, pdf2_reader.numPages)
+            # Merge the pages from the two PDF files
+            for page_num in range(num_pages):
+                # Add the page from the first PDF file
+                if page_num < pdf1_reader.numPages:
+                    page1 = pdf1_reader.getPage(page_num)
+                else:
+                    page1 = PyPDF2.PageObject.createBlankPage(pdf1_reader)
+                # Add the page from the second PDF file
+                if page_num < pdf2_reader.numPages:
+                    page2 = pdf2_reader.getPage(page_num)
+                else:
+                    page2 = PyPDF2.PageObject.createBlankPage(pdf1_reader)
+                # Create a new empty page with double width
+                new_page = PyPDF2.PageObject.createBlankPage(
+                    width=int(
+                        int(page1.mediaBox.getWidth())
+                        + int(page2.mediaBox.getWidth()) * Percent
+                    ),
+                    height=max(page1.mediaBox.getHeight(), page2.mediaBox.getHeight()),
+                )
+                new_page.mergeTranslatedPage(page1, 0, 0)
+                new_page.mergeTranslatedPage(
+                    page2,
+                    int(
+                        int(page1.mediaBox.getWidth())
+                        - int(page2.mediaBox.getWidth()) * (1 - Percent)
+                    ),
+                    0,
+                )
+                if "/Annots" in new_page:
+                    annotations = new_page["/Annots"]
+                    for i, annot in enumerate(annotations):
+                        annot_obj = annot.get_object()
+
+                        # 检查注释类型是否是链接（/Link）
+                        if annot_obj.get("/Subtype") == "/Link":
+                            # 检查是否为内部链接跳转（/GoTo）或外部URI链接（/URI）
+                            action = annot_obj.get("/A")
+                            if action:
+
+                                if "/S" in action and action["/S"] == "/GoTo":
+                                    # 内部链接：跳转到文档中的某个页面
+                                    dest = action.get("/D")  # 目标页或目标位置
+                                    # if dest and annot.idnum in page2_annot_id:
+                                    # if dest in pdf2_reader.named_destinations:
+                                    if dest and page2.annotations:
+                                        if annot in page2.annotations:
+                                            # 获取原始文件中跳转信息，包括跳转页面
+                                            destination = pdf2_reader.named_destinations[
+                                                dest
+                                            ]
+                                            page_number = (
+                                                pdf2_reader.get_destination_page_number(
+                                                    destination
+                                                )
+                                            )
+                                            # 更新跳转信息，跳转到对应的页面和，指定坐标 (100, 150)，缩放比例为 100%
+                                            # “/D”:[10,'/XYZ',100,100,0]
+                                            if destination.dest_array[1] == "/XYZ":
+                                                annot_obj["/A"].update(
+                                                    {
+                                                        NameObject("/D"): ArrayObject(
+                                                            [
+                                                                NumberObject(page_number),
+                                                                destination.dest_array[1],
+                                                                FloatObject(
+                                                                    destination.dest_array[
+                                                                        2
+                                                                    ]
+                                                                    + int(
+                                                                        page1.mediaBox.getWidth()
+                                                                    )
+                                                                ),
+                                                                destination.dest_array[3],
+                                                                destination.dest_array[4],
+                                                            ]
+                                                        )  # 确保键和值是 PdfObject
+                                                    }
+                                                )
+                                            else:
+                                                annot_obj["/A"].update(
+                                                    {
+                                                        NameObject("/D"): ArrayObject(
+                                                            [
+                                                                NumberObject(page_number),
+                                                                destination.dest_array[1],
+                                                            ]
+                                                        )  # 确保键和值是 PdfObject
+                                                    }
+                                                )
+
+                                            rect = annot_obj.get("/Rect")
+                                            # 更新点击坐标
+                                            rect = ArrayObject(
+                                                [
+                                                    FloatObject(
+                                                        rect[0]
+                                                        + int(page1.mediaBox.getWidth())
+                                                    ),
+                                                    rect[1],
+                                                    FloatObject(
+                                                        rect[2]
+                                                        + int(page1.mediaBox.getWidth())
+                                                    ),
+                                                    rect[3],
+                                                ]
+                                            )
+                                            annot_obj.update(
+                                                {
+                                                    NameObject(
+                                                        "/Rect"
+                                                    ): rect  # 确保键和值是 PdfObject
+                                                }
+                                            )
+                                    # if dest and annot.idnum in page1_annot_id:
+                                    # if dest in pdf1_reader.named_destinations:
+                                    if dest and page1.annotations:
+                                        if annot in page1.annotations:
+                                            # 获取原始文件中跳转信息，包括跳转页面
+                                            destination = pdf1_reader.named_destinations[
+                                                dest
+                                            ]
+                                            page_number = (
+                                                pdf1_reader.get_destination_page_number(
+                                                    destination
+                                                )
+                                            )
+                                            # 更新跳转信息，跳转到对应的页面和，指定坐标 (100, 150)，缩放比例为 100%
+                                            # “/D”:[10,'/XYZ',100,100,0]
+                                            if destination.dest_array[1] == "/XYZ":
+                                                annot_obj["/A"].update(
+                                                    {
+                                                        NameObject("/D"): ArrayObject(
+                                                            [
+                                                                NumberObject(page_number),
+                                                                destination.dest_array[1],
+                                                                FloatObject(
+                                                                    destination.dest_array[
+                                                                        2
+                                                                    ]
+                                                                ),
+                                                                destination.dest_array[3],
+                                                                destination.dest_array[4],
+                                                            ]
+                                                        )  # 确保键和值是 PdfObject
+                                                    }
+                                                )
+                                            else:
+                                                annot_obj["/A"].update(
+                                                    {
+                                                        NameObject("/D"): ArrayObject(
+                                                            [
+                                                                NumberObject(page_number),
+                                                                destination.dest_array[1],
+                                                            ]
+                                                        )  # 确保键和值是 PdfObject
+                                                    }
+                                                )
+
+                                            rect = annot_obj.get("/Rect")
+                                            rect = ArrayObject(
+                                                [
+                                                    FloatObject(rect[0]),
+                                                    rect[1],
+                                                    FloatObject(rect[2]),
+                                                    rect[3],
+                                                ]
+                                            )
+                                            annot_obj.update(
+                                                {
+                                                    NameObject(
+                                                        "/Rect"
+                                                    ): rect  # 确保键和值是 PdfObject
+                                                }
+                                            )
+
+                                elif "/S" in action and action["/S"] == "/URI":
+                                    # 外部链接：跳转到某个URI
+                                    uri = action.get("/URI")
+                output_writer.addPage(new_page)
+            # Save the merged PDF file
+            with open(output_path, "wb") as output_file:
+                output_writer.write(output_file)
+
+
+def _merge_pdfs_legacy(pdf1_path, pdf2_path, output_path):
     import PyPDF2  # PyPDF2这个库有严重的内存泄露问题，把它放到子进程中运行，从而方便内存的释放
 
     Percent = 0.95

crazy_functions/rag_fns/llama_index_worker.py

@@ -1,17 +1,13 @@
-import llama_index
-import os
 import atexit
 from loguru import logger
 from typing import List
+
 from llama_index.core import Document
-from llama_index.core.schema import TextNode
-from request_llms.embed_models.openai_embed import OpenAiEmbeddingModel
-from shared_utils.connect_void_terminal import get_chat_default_kwargs
-from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
-from crazy_functions.rag_fns.vector_store_index import GptacVectorStoreIndex
 from llama_index.core.ingestion import run_transformations
-from llama_index.core import PromptTemplate
-from llama_index.core.response_synthesizers import TreeSummarize
+from llama_index.core.schema import TextNode
+
+from crazy_functions.rag_fns.vector_store_index import GptacVectorStoreIndex
+from request_llms.embed_models.openai_embed import OpenAiEmbeddingModel
 
 DEFAULT_QUERY_GENERATION_PROMPT = """\
 Now, you have context information as below:
@@ -63,7 +59,7 @@ class SaveLoad():
     def purge(self):
         import shutil
         shutil.rmtree(self.checkpoint_dir, ignore_errors=True)
-        self.vs_index = self.create_new_vs()
+        self.vs_index = self.create_new_vs(self.checkpoint_dir)
 
 
 class LlamaIndexRagWorker(SaveLoad):
@@ -75,7 +71,7 @@ class LlamaIndexRagWorker(SaveLoad):
         if auto_load_checkpoint:
             self.vs_index = self.load_from_checkpoint(checkpoint_dir)
         else:
-            self.vs_index = self.create_new_vs(checkpoint_dir)
+            self.vs_index = self.create_new_vs()
         atexit.register(lambda: self.save_to_checkpoint(checkpoint_dir))
 
     def assign_embedding_model(self):
@@ -91,40 +87,52 @@ class LlamaIndexRagWorker(SaveLoad):
         logger.info('oo --------inspect_vector_store end--------')
         return vector_store_preview
 
-    def add_documents_to_vector_store(self, document_list):
-        documents = [Document(text=t) for t in document_list]
+    def add_documents_to_vector_store(self, document_list: List[Document]):
+        """
+        Adds a list of Document objects to the vector store after processing.
+        """
+        documents = document_list
         documents_nodes = run_transformations(
-                        documents,  # type: ignore
-                        self.vs_index._transformations,
-                        show_progress=True
-                    )
+            documents,  # type: ignore
+            self.vs_index._transformations,
+            show_progress=True
+        )
         self.vs_index.insert_nodes(documents_nodes)
-        if self.debug_mode: self.inspect_vector_store()
+        if self.debug_mode:
+            self.inspect_vector_store()
 
-    def add_text_to_vector_store(self, text):
+    def add_text_to_vector_store(self, text: str):
         node = TextNode(text=text)
         documents_nodes = run_transformations(
-                        [node],
-                        self.vs_index._transformations,
-                        show_progress=True
-                    )
+            [node],
+            self.vs_index._transformations,
+            show_progress=True
+        )
         self.vs_index.insert_nodes(documents_nodes)
-        if self.debug_mode: self.inspect_vector_store()
+        if self.debug_mode:
+            self.inspect_vector_store()
 
     def remember_qa(self, question, answer):
         formatted_str = QUESTION_ANSWER_RECORD.format(question=question, answer=answer)
         self.add_text_to_vector_store(formatted_str)
 
     def retrieve_from_store_with_query(self, query):
-        if self.debug_mode: self.inspect_vector_store()
+        if self.debug_mode:
+            self.inspect_vector_store()
         retriever = self.vs_index.as_retriever()
         return retriever.retrieve(query)
 
     def build_prompt(self, query, nodes):
         context_str = self.generate_node_array_preview(nodes)
         return DEFAULT_QUERY_GENERATION_PROMPT.format(context_str=context_str, query_str=query)
-        
+
     def generate_node_array_preview(self, nodes):
         buf = "\n".join(([f"(No.{i+1} | score {n.score:.3f}): {n.text}" for i, n in enumerate(nodes)]))
         if self.debug_mode: logger.info(buf)
         return buf
+
+    def purge_vector_store(self):
+        """
+        Purges the current vector store and creates a new one.
+        """
+        self.purge()

crazy_functions/rag_fns/rag_file_support.py

@@ -0,0 +1,22 @@
+import os
+from llama_index.core import SimpleDirectoryReader
+
+supports_format = ['.csv', '.docx', '.epub', '.ipynb',  '.mbox', '.md', '.pdf',  '.txt', '.ppt',
+                   '.pptm', '.pptx']
+
+
+# 修改后的 extract_text 函数，结合 SimpleDirectoryReader 和自定义解析逻辑
+def extract_text(file_path):
+    _, ext = os.path.splitext(file_path.lower())
+
+    # 使用 SimpleDirectoryReader 处理它支持的文件格式
+    if ext in supports_format:
+        try:
+            reader = SimpleDirectoryReader(input_files=[file_path])
+            documents = reader.load_data()
+            if len(documents) > 0:
+                return documents[0].text
+        except Exception as e:
+            pass
+
+    return None

docs/Dockerfile+JittorLLM

@@ -1 +0,0 @@
-# 此Dockerfile不再维护，请前往docs/GithubAction+JittorLLMs

docs/GithubAction+AllCapacityBeta

@@ -1,57 +0,0 @@
-# docker build -t gpt-academic-all-capacity -f docs/GithubAction+AllCapacity  --network=host --build-arg http_proxy=http://localhost:10881 --build-arg https_proxy=http://localhost:10881 .
-# docker build -t gpt-academic-all-capacity -f docs/GithubAction+AllCapacityBeta  --network=host .
-# docker run -it --net=host gpt-academic-all-capacity  bash
-
-# 从NVIDIA源，从而支持显卡（检查宿主的nvidia-smi中的cuda版本必须>=11.3）
-FROM fuqingxu/11.3.1-runtime-ubuntu20.04-with-texlive:latest
-
-# edge-tts需要的依赖，某些pip包所需的依赖
-RUN apt update && apt install ffmpeg build-essential -y
-
-# use python3 as the system default python
-WORKDIR /gpt
-RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
-
-# # 非必要步骤，更换pip源 （以下三行，可以删除）
-# RUN echo '[global]' > /etc/pip.conf && \
-#     echo 'index-url = https://mirrors.aliyun.com/pypi/simple/' >> /etc/pip.conf && \
-#     echo 'trusted-host = mirrors.aliyun.com' >> /etc/pip.conf
-
-# 下载pytorch
-RUN python3 -m pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/cu113
-# 准备pip依赖
-RUN python3 -m pip install openai numpy arxiv rich
-RUN python3 -m pip install colorama Markdown pygments pymupdf
-RUN python3 -m pip install python-docx moviepy pdfminer
-RUN python3 -m pip install zh_langchain==0.2.1 pypinyin
-RUN python3 -m pip install rarfile py7zr
-RUN python3 -m pip install aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
-# 下载分支
-WORKDIR /gpt
-RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git
-WORKDIR /gpt/gpt_academic
-RUN git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss
-
-RUN python3 -m pip install -r requirements.txt
-RUN python3 -m pip install -r request_llms/requirements_moss.txt
-RUN python3 -m pip install -r request_llms/requirements_qwen.txt
-RUN python3 -m pip install -r request_llms/requirements_chatglm.txt
-RUN python3 -m pip install -r request_llms/requirements_newbing.txt
-RUN python3 -m pip install nougat-ocr
-
-
-# 预热Tiktoken模块
-RUN python3  -c 'from check_proxy import warm_up_modules; warm_up_modules()'
-
-# 安装知识库插件的额外依赖
-RUN apt-get update && apt-get install libgl1 -y
-RUN pip3 install transformers protobuf langchain sentence-transformers  faiss-cpu nltk beautifulsoup4 bitsandbytes tabulate icetk --upgrade
-RUN pip3 install unstructured[all-docs] --upgrade
-RUN python3  -c 'from check_proxy import warm_up_vectordb; warm_up_vectordb()'
-RUN rm -rf /usr/local/lib/python3.8/dist-packages/tests
-
-
-# COPY .cache /root/.cache
-# COPY config_private.py config_private.py
-# 启动
-CMD ["python3", "-u", "main.py"]

docs/GithubAction+NoLocal+Latex+Arm

@@ -0,0 +1,25 @@
+# 此Dockerfile适用于“无本地模型”的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM
+# - 1 修改 `config.py`
+# - 2 构建 docker build -t gpt-academic-nolocal-latex -f docs/GithubAction+NoLocal+Latex .
+# - 3 运行 docker run -v /home/fuqingxu/arxiv_cache:/root/arxiv_cache --rm -it --net=host gpt-academic-nolocal-latex
+
+FROM menghuan1918/ubuntu_uv_ctex:latest
+ENV DEBIAN_FRONTEND=noninteractive
+SHELL ["/bin/bash", "-c"]
+WORKDIR /gpt
+COPY . .
+RUN /root/.cargo/bin/uv venv --seed \
+    && source .venv/bin/activate \
+    && /root/.cargo/bin/uv pip install openai numpy arxiv rich colorama Markdown pygments pymupdf python-docx pdfminer \
+    && /root/.cargo/bin/uv pip install -r requirements.txt \
+    && /root/.cargo/bin/uv clean
+
+# 对齐python3
+RUN rm -f /usr/bin/python3 && ln -s /gpt/.venv/bin/python /usr/bin/python3
+RUN rm -f /usr/bin/python && ln -s /gpt/.venv/bin/python /usr/bin/python
+
+# 可选步骤，用于预热模块
+RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
+
+# 启动
+CMD ["python3", "-u", "main.py"]

request_llms/bridge_all.py

@@ -256,6 +256,8 @@ model_info = {
         "max_token": 128000,
         "tokenizer": tokenizer_gpt4,
         "token_cnt": get_token_num_gpt4,
+        "openai_disable_system_prompt": True,
+        "openai_disable_stream": True,
     },
     "o1-mini": {
         "fn_with_ui": chatgpt_ui,
@@ -264,6 +266,8 @@ model_info = {
         "max_token": 128000,
         "tokenizer": tokenizer_gpt4,
         "token_cnt": get_token_num_gpt4,
+        "openai_disable_system_prompt": True,
+        "openai_disable_stream": True,
     },
 
     "gpt-4-turbo": {
@@ -1281,4 +1285,3 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot,
 
     # 更新一下llm_kwargs的参数，否则会出现参数不匹配的问题
     yield from method(inputs, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, stream, additional_fn)
-

request_llms/bridge_chatgpt.py

@@ -202,10 +202,13 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[],
                     if (time.time()-observe_window[1]) > watch_dog_patience:
                         raise RuntimeError("用户取消了程序。")
         else: raise RuntimeError("意外Json结构："+delta)
-    if json_data and json_data['finish_reason'] == 'content_filter':
-        raise RuntimeError("由于提问含不合规内容被Azure过滤。")
-    if json_data and json_data['finish_reason'] == 'length':
+
+    finish_reason = json_data.get('finish_reason', None) if json_data else None
+    if finish_reason == 'content_filter':
+        raise RuntimeError("由于提问含不合规内容被过滤。")
+    if finish_reason == 'length':
         raise ConnectionAbortedError("正常结束，但显示Token不足，导致输出不完整，请削减单次输入的文本量。")
+
     return result
 
 
@@ -536,4 +539,3 @@ def generate_payload(inputs:str, llm_kwargs:dict, history:list, system_prompt:st
 
     return headers,payload
 
-

requirements.txt

@@ -2,14 +2,15 @@ https://public.agent-matrix.com/publish/gradio-3.32.10-py3-none-any.whl
 fastapi==0.110
 gradio-client==0.8
 pypdf2==2.12.1
+httpx<=0.25.2
 zhipuai==2.0.1
 tiktoken>=0.3.3
 requests[socks]
-pydantic==2.5.2
-llama-index~=0.10
+pydantic==2.9.2
 protobuf==3.20
 transformers>=4.27.1,<4.42
 scipdf_parser>=0.52
+spacy==3.7.4
 anthropic>=0.18.1
 python-markdown-math
 pymdown-extensions
@@ -32,3 +33,14 @@ loguru
 arxiv
 numpy
 rich
+
+
+llama-index-core==0.10.68
+llama-index-legacy==0.9.48
+llama-index-readers-file==0.1.33
+llama-index-readers-llama-parse==0.1.6
+llama-index-embeddings-azure-openai==0.1.10
+llama-index-embeddings-openai==0.1.10
+llama-parse==0.4.9
+mdit-py-plugins>=0.3.3
+linkify-it-py==2.0.3

tests/test_anim_gen.py

@@ -0,0 +1,12 @@
+"""
+对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py
+"""
+
+import init_test
+import os, sys
+
+
+if __name__ == "__main__":
+    from test_utils import plugin_test
+
+    plugin_test(plugin='crazy_functions.数学动画生成manim->动画生成', main_input="A point moving along function culve y=sin(x), starting from x=0 and stop at x=4*\pi.")

tests/test_latex_auto_correct.py

@@ -19,4 +19,8 @@ if __name__ == "__main__":
     plugin_test = importlib.import_module('test_utils').plugin_test
 
 
-    plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2203.01927")
+    # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2203.01927")
+    # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="gpt_log/arxiv_cache/2203.01927/workfolder")
+    # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2410.05779")
+    plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="gpt_log/default_user/workfolder")
+

version

@@ -1,5 +1,5 @@
 {
-  "version": 3.83,
+  "version": 3.90,
   "show_feature": true,
-  "new_feature": "增加欢迎页面 <-> 优化图像生成插件 <-> 添加紫东太初大模型支持 <-> 保留主题选择 <-> 支持更复杂的插件框架 <-> 上传文件时显示进度条"
+  "new_feature": "增加RAG组件 <-> 升级多合一主提交键"
 }