feat: add response body schemas for various API endpoints

--bug=1060032 --user=王孝刚 【桂物智慧】 api 调用客户端修改对话摘要接口，报错403，没有访问权限 https://www.tapd.cn/57709429/s/1757188

.github/dependabot.yml

@@ -0,0 +1,17 @@
+version: 2
+updates:
+  - package-ecosystem: "pip"
+    directory: "/"
+    schedule:
+      interval: "weekly"
+      timezone: "Asia/Shanghai"
+      day: "friday"
+    target-branch: "v2"
+    groups:
+      python-dependencies:
+        patterns:
+          - "*"
+#    ignore:
+#      - dependency-name: "pymupdf"
+#        versions: ["*"]
+

.github/workflows/build-and-push.yml

@@ -7,7 +7,7 @@ on:
     inputs:
       dockerImageTag:
         description: 'Image Tag'
-        default: 'v1.10.3-dev'
+        default: 'v1.10.7-dev'
         required: true
       dockerImageTagWithLatest:
         description: '是否发布latest tag（正式发版时选择，测试版本切勿选择）'
@@ -36,7 +36,7 @@ on:
 jobs:
   build-and-push-to-fit2cloud-registry:
     if: ${{ contains(github.event.inputs.registry, 'fit2cloud') }}
-    runs-on: ubuntu-22.04
+    runs-on: ubuntu-latest
     steps:
       - name: Check Disk Space
         run: df -h
@@ -52,10 +52,6 @@ jobs:
           swap-storage: true
       - name: Check Disk Space
         run: df -h
-      - name: Set Swap Space
-        uses: pierotofy/set-swap-space@master
-        with:
-          swap-size-gb: 8
       - name: Checkout
         uses: actions/checkout@v4
         with:
@@ -68,24 +64,17 @@ jobs:
           TAG_NAME=${{ github.event.inputs.dockerImageTag }}
           TAG_NAME_WITH_LATEST=${{ github.event.inputs.dockerImageTagWithLatest }}
           if [[ ${TAG_NAME_WITH_LATEST} == 'true' ]]; then            
-            DOCKER_IMAGE_TAGS="--tag ${DOCKER_IMAGE}:${TAG_NAME} --tag ${DOCKER_IMAGE}:latest"
+            DOCKER_IMAGE_TAGS="--tag ${DOCKER_IMAGE}:${TAG_NAME} --tag ${DOCKER_IMAGE}:${TAG_NAME%%.*}"
           else
             DOCKER_IMAGE_TAGS="--tag ${DOCKER_IMAGE}:${TAG_NAME}"
           fi
           echo ::set-output name=buildx_args::--platform ${DOCKER_PLATFORMS} --memory-swap -1 \
-            --build-arg DOCKER_IMAGE_TAG=${{ github.event.inputs.dockerImageTag }} --build-arg BUILD_AT=$(TZ=Asia/Shanghai date +'%Y-%m-%dT%H:%M') --build-arg GITHUB_COMMIT=${GITHUB_SHA::8} --no-cache \
+            --build-arg DOCKER_IMAGE_TAG=${{ github.event.inputs.dockerImageTag }} --build-arg BUILD_AT=$(TZ=Asia/Shanghai date +'%Y-%m-%dT%H:%M') --build-arg GITHUB_COMMIT=`git rev-parse --short HEAD` --no-cache \
             ${DOCKER_IMAGE_TAGS} .
       - name: Set up QEMU
         uses: docker/setup-qemu-action@v3
-        with:
-          # Until https://github.com/tonistiigi/binfmt/issues/215
-          image: tonistiigi/binfmt:qemu-v7.0.0-28
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
-        with:
-          buildkitd-config-inline: |
-            [worker.oci]
-              max-parallelism = 1
       - name: Login to GitHub Container Registry
         uses: docker/login-action@v3
         with:
@@ -100,11 +89,12 @@ jobs:
           password: ${{ secrets.FIT2CLOUD_REGISTRY_PASSWORD }}
       - name: Docker Buildx (build-and-push)
         run: |
+          sudo sync && echo 3 | sudo tee /proc/sys/vm/drop_caches && free -m
           docker buildx build --output "type=image,push=true" ${{ steps.prepare.outputs.buildx_args }} -f installer/Dockerfile
 
   build-and-push-to-dockerhub:
     if: ${{ contains(github.event.inputs.registry, 'dockerhub') }}
-    runs-on: ubuntu-22.04
+    runs-on: ubuntu-latest
     steps:
       - name: Check Disk Space
         run: df -h
@@ -120,10 +110,6 @@ jobs:
           swap-storage: true
       - name: Check Disk Space
         run: df -h
-      - name: Set Swap Space
-        uses: pierotofy/set-swap-space@master
-        with:
-          swap-size-gb: 8
       - name: Checkout
         uses: actions/checkout@v4
         with:
@@ -136,24 +122,17 @@ jobs:
           TAG_NAME=${{ github.event.inputs.dockerImageTag }}          
           TAG_NAME_WITH_LATEST=${{ github.event.inputs.dockerImageTagWithLatest }}
           if [[ ${TAG_NAME_WITH_LATEST} == 'true' ]]; then            
-            DOCKER_IMAGE_TAGS="--tag ${DOCKER_IMAGE}:${TAG_NAME} --tag ${DOCKER_IMAGE}:latest"
+            DOCKER_IMAGE_TAGS="--tag ${DOCKER_IMAGE}:${TAG_NAME} --tag ${DOCKER_IMAGE}:${TAG_NAME%%.*}"
           else
             DOCKER_IMAGE_TAGS="--tag ${DOCKER_IMAGE}:${TAG_NAME}"
           fi
           echo ::set-output name=buildx_args::--platform ${DOCKER_PLATFORMS} --memory-swap -1 \
-            --build-arg DOCKER_IMAGE_TAG=${{ github.event.inputs.dockerImageTag }} --build-arg BUILD_AT=$(TZ=Asia/Shanghai date +'%Y-%m-%dT%H:%M') --build-arg GITHUB_COMMIT=${GITHUB_SHA::8} --no-cache \
+            --build-arg DOCKER_IMAGE_TAG=${{ github.event.inputs.dockerImageTag }} --build-arg BUILD_AT=$(TZ=Asia/Shanghai date +'%Y-%m-%dT%H:%M') --build-arg GITHUB_COMMIT=`git rev-parse --short HEAD` --no-cache \
             ${DOCKER_IMAGE_TAGS} .
       - name: Set up QEMU
         uses: docker/setup-qemu-action@v3
-        with:
-          # Until https://github.com/tonistiigi/binfmt/issues/215
-          image: tonistiigi/binfmt:qemu-v7.0.0-28
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
-        with:
-          buildkitd-config-inline: |
-            [worker.oci]
-              max-parallelism = 1
       - name: Login to GitHub Container Registry
         uses: docker/login-action@v3
         with:
@@ -167,4 +146,5 @@ jobs:
           password: ${{ secrets.DOCKERHUB_TOKEN }}
       - name: Docker Buildx (build-and-push)
         run: |
+          sudo sync && echo 3 | sudo tee /proc/sys/vm/drop_caches && free -m
           docker buildx build --output "type=image,push=true" ${{ steps.prepare.outputs.buildx_args }} -f installer/Dockerfile

README.md

@@ -1,5 +1,6 @@
 <p align="center"><img src= "https://github.com/1Panel-dev/maxkb/assets/52996290/c0694996-0eed-40d8-b369-322bf2a380bf" alt="MaxKB" width="300" /></p>
-<h3 align="center">Ready-to-use AI Chatbot</h3>
+<h3 align="center">Open-source platform for building enterprise-grade agents</h3>
+<h3 align="center">强大易用的企业级智能体平台</h3>
 <p align="center"><a href="https://trendshift.io/repositories/9113" target="_blank"><img src="https://trendshift.io/api/badge/repositories/9113" alt="1Panel-dev%2FMaxKB | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a></p>
 <p align="center">
   <a href="https://www.gnu.org/licenses/gpl-3.0.html#license-text"><img src="https://img.shields.io/github/license/1Panel-dev/maxkb?color=%231890FF" alt="License: GPL v3"></a>
@@ -10,10 +11,10 @@
 </p>
 <hr/>
 
-MaxKB = Max Knowledge Base, it is a ready-to-use AI chatbot that integrates Retrieval-Augmented Generation (RAG) pipelines, supports robust workflows, and provides advanced MCP tool-use capabilities. MaxKB is widely applied in scenarios such as intelligent customer service, corporate internal knowledge bases, academic research, and education.
+MaxKB = Max Knowledge Brain, it is an open-source platform for building enterprise-grade agents. MaxKB integrates Retrieval-Augmented Generation (RAG) pipelines, supports robust workflows, and provides advanced MCP tool-use capabilities. MaxKB is widely applied in scenarios such as intelligent customer service, corporate internal knowledge bases, academic research, and education.
 
-- **RAG Pipeline**: Supports direct uploading of documents / automatic crawling of online documents, with features for automatic text splitting, vectorization, and RAG (Retrieval-Augmented Generation). This effectively reduces hallucinations in large models, providing a superior smart Q&A interaction experience.
+- **RAG Pipeline**: Supports direct uploading of documents / automatic crawling of online documents, with features for automatic text splitting, vectorization. This effectively reduces hallucinations in large models, providing a superior smart Q&A interaction experience.
-- **Flexible Orchestration**: Equipped with a powerful workflow engine, function library and MCP tool-use, enabling the orchestration of AI processes to meet the needs of complex business scenarios. 
+- **Agentic Workflow**: Equipped with a powerful workflow engine, function library and MCP tool-use, enabling the orchestration of AI processes to meet the needs of complex business scenarios. 
 - **Seamless Integration**: Facilitates zero-coding rapid integration into third-party business systems, quickly equipping existing systems with intelligent Q&A capabilities to enhance user satisfaction.
 - **Model-Agnostic**: Supports various large models, including private models (such as DeepSeek, Llama, Qwen, etc.) and public models (like OpenAI, Claude, Gemini, etc.).
 - **Multi Modal**: Native support for input and output text, image, audio and video.
@@ -55,8 +56,6 @@ Access MaxKB web interface at `http://your_server_ip:8080` with default admin cr
 
 ## Feature Comparison
 
-MaxKB is positioned as an Ready-to-use RAG (Retrieval-Augmented Generation) intelligent Q&A application, rather than a middleware platform for building large model applications. The following table is merely a comparison from a functional perspective.
-
 <table style="width: 100%;">
   <tr>
     <th align="center">Feature</th>

README_CN.md

@@ -1,25 +1,25 @@
 <p align="center"><img src= "https://github.com/1Panel-dev/maxkb/assets/52996290/c0694996-0eed-40d8-b369-322bf2a380bf" alt="MaxKB" width="300" /></p>
-<h3 align="center">基于大模型和 RAG 的知识库问答系统</h3>
+<h3 align="center">强大易用的企业级智能体平台</h3>
-<h4 align="center">Ready-to-use, flexible RAG Chatbot</h4>
 <p align="center">
     <a href="https://trendshift.io/repositories/9113" target="_blank"><img src="https://trendshift.io/api/badge/repositories/9113" alt="1Panel-dev%2FMaxKB | Trendshift" style="width: 250px; height: auto;" /></a>
-    <a href="https://market.aliyun.com/products/53690006/cmjj00067609.html?userCode=kmemb8jp" target="_blank"><img src="https://img.alicdn.com/imgextra/i2/O1CN01H5JIwY1rZ0OobDjnJ_!!6000000005644-2-tps-1000-216.png" alt="1Panel-dev%2FMaxKB | Aliyun" style="width: 250px; height: auto;" /></a>
 </p>
 <p align="center">
   <a href="README_EN.md"><img src="https://img.shields.io/badge/English_README-blue" alt="English README"></a>
-  <a href="https://www.gnu.org/licenses/gpl-3.0.html#license-text"><img src="https://img.shields.io/github/license/1Panel-dev/maxkb" alt="License: GPL v3"></a>
+  <a href="https://www.gnu.org/licenses/gpl-3.0.html#license-text"><img src="https://img.shields.io/github/license/1Panel-dev/maxkb?color=%231890FF" alt="License: GPL v3"></a>
   <a href="https://github.com/1Panel-dev/maxkb/releases/latest"><img src="https://img.shields.io/github/v/release/1Panel-dev/maxkb" alt="Latest release"></a>
   <a href="https://github.com/1Panel-dev/maxkb"><img src="https://img.shields.io/github/stars/1Panel-dev/maxkb?style=flat-square" alt="Stars"></a>
   <a href="https://hub.docker.com/r/1panel/maxkb"><img src="https://img.shields.io/docker/pulls/1panel/maxkb?label=downloads" alt="Download"></a>
+  <a href="https://gitee.com/fit2cloud-feizhiyun/MaxKB"><img src="https://gitee.com/fit2cloud-feizhiyun/MaxKB/badge/star.svg?theme=gvp" alt="Gitee Stars"></a>
+  <a href="https://gitcode.com/feizhiyun/MaxKB"><img src="https://gitcode.com/feizhiyun/MaxKB/star/badge.svg" alt="GitCode Stars"></a>
 </p>
 <hr/>
 
-MaxKB = Max Knowledge Base，是一款开箱即用的 RAG Chatbot，具备强大的工作流和 MCP 工具调用能力。它支持对接各种主流大语言模型（LLMs），广泛应用于智能客服、企业内部知识库、学术研究与教育等场景。
+MaxKB = Max Knowledge Brain，是一款强大易用的企业级智能体平台，支持 RAG 检索增强生成、工作流编排、MCP 工具调用能力。MaxKB 支持对接各种主流大语言模型，广泛应用于智能客服、企业内部知识库问答、员工助手、学术研究与教育等场景。
 
-- **开箱即用**：支持直接上传文档 / 自动爬取在线文档，支持文本自动拆分、向量化和 RAG（检索增强生成），有效减少大模型幻觉，智能问答交互体验好；
+- **RAG 检索增强生成**：高效搭建本地 AI 知识库，支持直接上传文档 / 自动爬取在线文档，支持文本自动拆分、向量化，有效减少大模型幻觉，提升问答效果；
-- **模型中立**：支持对接各种大模型，包括本地私有大模型（DeepSeek R1 / Llama 3 / Qwen 2 等）、国内公共大模型（通义千问 / 腾讯混元 / 字节豆包 / 百度千帆 / 智谱 AI / Kimi 等）和国外公共大模型（OpenAI / Claude / Gemini 等）；
 - **灵活编排**：内置强大的工作流引擎、函数库和 MCP 工具调用能力，支持编排 AI 工作过程，满足复杂业务场景下的需求；
-- **无缝嵌入**：支持零编码快速嵌入到第三方业务系统，让已有系统快速拥有智能问答能力，提高用户满意度。
+- **无缝嵌入**：支持零编码快速嵌入到第三方业务系统，让已有系统快速拥有智能问答能力，提高用户满意度；
+- **模型中立**：支持对接各种大模型，包括本地私有大模型（DeepSeek R1 / Llama 3 / Qwen 2 等）、国内公共大模型（通义千问 / 腾讯混元 / 字节豆包 / 百度千帆 / 智谱 AI / Kimi 等）和国外公共大模型（OpenAI / Claude / Gemini 等）。
 
 MaxKB 三分钟视频介绍：https://www.bilibili.com/video/BV18JypYeEkj/
 

apps/application/flow/step_node/ai_chat_step_node/impl/base_chat_node.py

@@ -40,6 +40,7 @@ tool_message_template = """
 
 """
 
+
 def _write_context(node_variable: Dict, workflow_variable: Dict, node: INode, workflow, answer: str,
                    reasoning_content: str):
     chat_model = node_variable.get('chat_model')
@@ -102,7 +103,6 @@ def write_context_stream(node_variable: Dict, workflow_variable: Dict, node: INo
     _write_context(node_variable, workflow_variable, node, workflow, answer, reasoning_content)
 
 
-
 async def _yield_mcp_response(chat_model, message_list, mcp_servers):
     async with MultiServerMCPClient(json.loads(mcp_servers)) as client:
         agent = create_react_agent(chat_model, client.get_tools())
@@ -115,6 +115,7 @@ async def _yield_mcp_response(chat_model, message_list, mcp_servers):
             if isinstance(chunk[0], AIMessageChunk):
                 yield chunk[0]
 
+
 def mcp_response_generator(chat_model, message_list, mcp_servers):
     loop = asyncio.new_event_loop()
     try:
@@ -130,6 +131,7 @@ def mcp_response_generator(chat_model, message_list, mcp_servers):
     finally:
         loop.close()
 
+
 async def anext_async(agen):
     return await agen.__anext__()
 
@@ -186,7 +188,8 @@ class BaseChatNode(IChatNode):
         self.context['answer'] = details.get('answer')
         self.context['question'] = details.get('question')
         self.context['reasoning_content'] = details.get('reasoning_content')
-        self.answer_text = details.get('answer')
+        if self.node_params.get('is_result', False):
+            self.answer_text = details.get('answer')
 
     def execute(self, model_id, system, prompt, dialogue_number, history_chat_record, stream, chat_id, chat_record_id,
                 model_params_setting=None,
@@ -216,7 +219,7 @@ class BaseChatNode(IChatNode):
         message_list = self.generate_message_list(system, prompt, history_message)
         self.context['message_list'] = message_list
 
-        if mcp_enable and mcp_servers is not None:
+        if mcp_enable and mcp_servers is not None and '"stdio"' not in mcp_servers:
             r = mcp_response_generator(chat_model, message_list, mcp_servers)
             return NodeResult(
                 {'result': r, 'chat_model': chat_model, 'message_list': message_list,

apps/application/flow/step_node/application_node/impl/base_application_node.py

@@ -168,7 +168,8 @@ class BaseApplicationNode(IApplicationNode):
         self.context['question'] = details.get('question')
         self.context['type'] = details.get('type')
         self.context['reasoning_content'] = details.get('reasoning_content')
-        self.answer_text = details.get('answer')
+        if self.node_params.get('is_result', False):
+            self.answer_text = details.get('answer')
 
     def execute(self, application_id, message, chat_id, chat_record_id, stream, re_chat, client_id, client_type,
                 app_document_list=None, app_image_list=None, app_audio_list=None, child_node=None, node_data=None,
@@ -178,7 +179,8 @@ class BaseApplicationNode(IApplicationNode):
         current_chat_id = string_to_uuid(chat_id + application_id)
         Chat.objects.get_or_create(id=current_chat_id, defaults={
             'application_id': application_id,
-            'abstract': message[0:1024]
+            'abstract': message[0:1024],
+            'client_id': client_id,
         })
         if app_document_list is None:
             app_document_list = []

apps/application/flow/step_node/direct_reply_node/impl/base_reply_node.py

@@ -15,7 +15,9 @@ from application.flow.step_node.direct_reply_node.i_reply_node import IReplyNode
 class BaseReplyNode(IReplyNode):
     def save_context(self, details, workflow_manage):
         self.context['answer'] = details.get('answer')
-        self.answer_text = details.get('answer')
+        if self.node_params.get('is_result', False):
+            self.answer_text = details.get('answer')
+
     def execute(self, reply_type, stream, fields=None, content=None, **kwargs) -> NodeResult:
         if reply_type == 'referencing':
             result = self.get_reference_content(fields)

apps/application/flow/step_node/form_node/impl/base_form_node.py

@@ -38,7 +38,8 @@ class BaseFormNode(IFormNode):
         self.context['start_time'] = details.get('start_time')
         self.context['form_data'] = form_data
         self.context['is_submit'] = details.get('is_submit')
-        self.answer_text = details.get('result')
+        if self.node_params.get('is_result', False):
+            self.answer_text = details.get('result')
         if form_data is not None:
             for key in form_data:
                 self.context[key] = form_data[key]
@@ -70,7 +71,7 @@ class BaseFormNode(IFormNode):
                         "chat_record_id": self.flow_params_serializer.data.get("chat_record_id"),
                         'form_data': self.context.get('form_data', {}),
                         "is_submit": self.context.get("is_submit", False)}
-        form = f'<form_rander>{json.dumps(form_setting,ensure_ascii=False)}</form_rander>'
+        form = f'<form_rander>{json.dumps(form_setting, ensure_ascii=False)}</form_rander>'
         context = self.workflow_manage.get_workflow_content()
         form_content_format = self.workflow_manage.reset_prompt(form_content_format)
         prompt_template = PromptTemplate.from_template(form_content_format, template_format='jinja2')
@@ -85,7 +86,7 @@ class BaseFormNode(IFormNode):
                         "chat_record_id": self.flow_params_serializer.data.get("chat_record_id"),
                         'form_data': self.context.get('form_data', {}),
                         "is_submit": self.context.get("is_submit", False)}
-        form = f'<form_rander>{json.dumps(form_setting,ensure_ascii=False)}</form_rander>'
+        form = f'<form_rander>{json.dumps(form_setting, ensure_ascii=False)}</form_rander>'
         context = self.workflow_manage.get_workflow_content()
         form_content_format = self.workflow_manage.reset_prompt(form_content_format)
         prompt_template = PromptTemplate.from_template(form_content_format, template_format='jinja2')

apps/application/flow/step_node/function_lib_node/impl/base_function_lib_node.py

@@ -65,7 +65,7 @@ def valid_reference_value(_type, value, name):
 
 
 def convert_value(name: str, value, _type, is_required, source, node):
-    if not is_required and value is None:
+    if not is_required and (value is None or (isinstance(value, str) and len(value) == 0)):
         return None
     if not is_required and source == 'reference' and (value is None or len(value) == 0):
         return None
@@ -113,7 +113,8 @@ def valid_function(function_lib, user_id):
 class BaseFunctionLibNodeNode(IFunctionLibNode):
     def save_context(self, details, workflow_manage):
         self.context['result'] = details.get('result')
-        self.answer_text = str(details.get('result'))
+        if self.node_params.get('is_result'):
+            self.answer_text = str(details.get('result'))
 
     def execute(self, function_lib_id, input_field_list, **kwargs) -> NodeResult:
         function_lib = QuerySet(FunctionLib).filter(id=function_lib_id).first()

apps/application/flow/step_node/function_node/impl/base_function_node.py

@@ -49,7 +49,7 @@ def valid_reference_value(_type, value, name):
 
 
 def convert_value(name: str, value, _type, is_required, source, node):
-    if not is_required and value is None:
+    if not is_required and (value is None or (isinstance(value, str) and len(value) == 0)):
         return None
     if source == 'reference':
         value = node.workflow_manage.get_reference_field(
@@ -84,7 +84,8 @@ def convert_value(name: str, value, _type, is_required, source, node):
 class BaseFunctionNodeNode(IFunctionNode):
     def save_context(self, details, workflow_manage):
         self.context['result'] = details.get('result')
-        self.answer_text = str(details.get('result'))
+        if self.node_params.get('is_result', False):
+            self.answer_text = str(details.get('result'))
 
     def execute(self, input_field_list, code, **kwargs) -> NodeResult:
         params = {field.get('name'): convert_value(field.get('name'), field.get('value'), field.get('type'),

apps/application/flow/step_node/image_generate_step_node/impl/base_image_generate_node.py

@@ -16,7 +16,8 @@ class BaseImageGenerateNode(IImageGenerateNode):
     def save_context(self, details, workflow_manage):
         self.context['answer'] = details.get('answer')
         self.context['question'] = details.get('question')
-        self.answer_text = details.get('answer')
+        if self.node_params.get('is_result', False):
+            self.answer_text = details.get('answer')
 
     def execute(self, model_id, prompt, negative_prompt, dialogue_number, dialogue_type, history_chat_record, chat_id,
                 model_params_setting,
@@ -24,7 +25,8 @@ class BaseImageGenerateNode(IImageGenerateNode):
                 **kwargs) -> NodeResult:
         print(model_params_setting)
         application = self.workflow_manage.work_flow_post_handler.chat_info.application
-        tti_model = get_model_instance_by_model_user_id(model_id, self.flow_params_serializer.data.get('user_id'), **model_params_setting)
+        tti_model = get_model_instance_by_model_user_id(model_id, self.flow_params_serializer.data.get('user_id'),
+                                                        **model_params_setting)
         history_message = self.get_history_message(history_chat_record, dialogue_number)
         self.context['history_message'] = history_message
         question = self.generate_prompt_question(prompt)

apps/application/flow/step_node/image_understand_step_node/impl/base_image_understand_node.py

@@ -69,7 +69,8 @@ class BaseImageUnderstandNode(IImageUnderstandNode):
     def save_context(self, details, workflow_manage):
         self.context['answer'] = details.get('answer')
         self.context['question'] = details.get('question')
-        self.answer_text = details.get('answer')
+        if self.node_params.get('is_result', False):
+            self.answer_text = details.get('answer')
 
     def execute(self, model_id, system, prompt, dialogue_number, dialogue_type, history_chat_record, stream, chat_id,
                 model_params_setting,

apps/application/flow/step_node/mcp_node/impl/base_mcp_node.py

@@ -14,7 +14,8 @@ class BaseMcpNode(IMcpNode):
         self.context['result'] = details.get('result')
         self.context['tool_params'] = details.get('tool_params')
         self.context['mcp_tool'] = details.get('mcp_tool')
-        self.answer_text = details.get('result')
+        if self.node_params.get('is_result', False):
+            self.answer_text = details.get('result')
 
     def execute(self, mcp_servers, mcp_server, mcp_tool, tool_params, **kwargs) -> NodeResult:
         servers = json.loads(mcp_servers)
@@ -27,7 +28,8 @@ class BaseMcpNode(IMcpNode):
                 return s
 
         res = asyncio.run(call_tool(servers, mcp_server, mcp_tool, params))
-        return NodeResult({'result': [content.text for content in res.content], 'tool_params': params, 'mcp_tool': mcp_tool}, {})
+        return NodeResult(
+            {'result': [content.text for content in res.content], 'tool_params': params, 'mcp_tool': mcp_tool}, {})
 
     def handle_variables(self, tool_params):
         # 处理参数中的变量

apps/application/flow/step_node/question_node/impl/base_question_node.py

@@ -80,7 +80,8 @@ class BaseQuestionNode(IQuestionNode):
         self.context['answer'] = details.get('answer')
         self.context['message_tokens'] = details.get('message_tokens')
         self.context['answer_tokens'] = details.get('answer_tokens')
-        self.answer_text = details.get('answer')
+        if self.node_params.get('is_result', False):
+            self.answer_text = details.get('answer')
 
     def execute(self, model_id, system, prompt, dialogue_number, history_chat_record, stream, chat_id, chat_record_id,
                 model_params_setting=None,

apps/application/flow/step_node/speech_to_text_step_node/impl/base_speech_to_text_node.py

@@ -18,7 +18,8 @@ class BaseSpeechToTextNode(ISpeechToTextNode):
 
     def save_context(self, details, workflow_manage):
         self.context['answer'] = details.get('answer')
-        self.answer_text = details.get('answer')
+        if self.node_params.get('is_result', False):
+            self.answer_text = details.get('answer')
 
     def execute(self, stt_model_id, chat_id, audio, **kwargs) -> NodeResult:
         stt_model = get_model_instance_by_model_user_id(stt_model_id, self.flow_params_serializer.data.get('user_id'))

apps/application/flow/step_node/start_node/impl/base_start_node.py

@@ -40,10 +40,13 @@ class BaseStartStepNode(IStarNode):
         self.context['document'] = details.get('document_list')
         self.context['image'] = details.get('image_list')
         self.context['audio'] = details.get('audio_list')
+        self.context['other'] = details.get('other_list')
         self.status = details.get('status')
         self.err_message = details.get('err_message')
         for key, value in workflow_variable.items():
             workflow_manage.context[key] = value
+        for item in details.get('global_fields', []):
+            workflow_manage.context[item.get('key')] = item.get('value')
 
     def get_node_params_serializer_class(self) -> Type[serializers.Serializer]:
         pass
@@ -59,7 +62,8 @@ class BaseStartStepNode(IStarNode):
             'question': question,
             'image': self.workflow_manage.image_list,
             'document': self.workflow_manage.document_list,
-            'audio': self.workflow_manage.audio_list
+            'audio': self.workflow_manage.audio_list,
+            'other': self.workflow_manage.other_list,
         }
         return NodeResult(node_variable, workflow_variable)
 
@@ -83,5 +87,6 @@ class BaseStartStepNode(IStarNode):
             'image_list': self.context.get('image'),
             'document_list': self.context.get('document'),
             'audio_list': self.context.get('audio'),
+            'other_list': self.context.get('other'),
             'global_fields': global_fields
         }

apps/application/flow/step_node/text_to_speech_step_node/impl/base_text_to_speech_node.py

@@ -37,7 +37,8 @@ def bytes_to_uploaded_file(file_bytes, file_name="generated_audio.mp3"):
 class BaseTextToSpeechNode(ITextToSpeechNode):
     def save_context(self, details, workflow_manage):
         self.context['answer'] = details.get('answer')
-        self.answer_text = details.get('answer')
+        if self.node_params.get('is_result', False):
+            self.answer_text = details.get('answer')
 
     def execute(self, tts_model_id, chat_id,
                 content, model_params_setting=None,

apps/application/flow/workflow_manage.py

@@ -238,6 +238,7 @@ class WorkflowManage:
                  base_to_response: BaseToResponse = SystemToResponse(), form_data=None, image_list=None,
                  document_list=None,
                  audio_list=None,
+                 other_list=None,
                  start_node_id=None,
                  start_node_data=None, chat_record=None, child_node=None):
         if form_data is None:
@@ -248,12 +249,15 @@ class WorkflowManage:
             document_list = []
         if audio_list is None:
             audio_list = []
+        if other_list is None:
+            other_list = []
         self.start_node_id = start_node_id
         self.start_node = None
         self.form_data = form_data
         self.image_list = image_list
         self.document_list = document_list
         self.audio_list = audio_list
+        self.other_list = other_list
         self.params = params
         self.flow = flow
         self.context = {}

apps/application/models/application.py

@@ -11,7 +11,7 @@ import uuid
 from django.contrib.postgres.fields import ArrayField
 from django.db import models
 from langchain.schema import HumanMessage, AIMessage
-
+from django.utils.translation import gettext as _
 from common.encoder.encoder import SystemEncoder
 from common.mixins.app_model_mixin import AppModelMixin
 from dataset.models.data_set import DataSet
@@ -167,7 +167,11 @@ class ChatRecord(AppModelMixin):
         return HumanMessage(content=self.problem_text)
 
     def get_ai_message(self):
-        return AIMessage(content=self.answer_text)
+        answer_text = self.answer_text
+        if answer_text is None or len(str(answer_text).strip()) == 0:
+            answer_text = _(
+                'Sorry, no relevant content was found. Please re-describe your problem or provide more information. ')
+        return AIMessage(content=answer_text)
 
     def get_node_details_runtime_node_id(self, runtime_node_id):
         return self.details.get(runtime_node_id, None)

apps/application/serializers/application_serializers.py

@@ -148,10 +148,12 @@ class ModelSettingSerializer(serializers.Serializer):
                                                         error_messages=ErrMessage.char(_("Thinking process switch")))
     reasoning_content_start = serializers.CharField(required=False, allow_null=True, default="<think>",
                                                     allow_blank=True, max_length=256,
+                                                    trim_whitespace=False,
                                                     error_messages=ErrMessage.char(
                                                         _("The thinking process begins to mark")))
     reasoning_content_end = serializers.CharField(required=False, allow_null=True, allow_blank=True, default="</think>",
                                                   max_length=256,
+                                                  trim_whitespace=False,
                                                   error_messages=ErrMessage.char(_("End of thinking process marker")))
 
 
@@ -162,7 +164,7 @@ class ApplicationWorkflowSerializer(serializers.Serializer):
                                  max_length=256, min_length=1,
                                  error_messages=ErrMessage.char(_("Application Description")))
     work_flow = serializers.DictField(required=False, error_messages=ErrMessage.dict(_("Workflow Objects")))
-    prologue = serializers.CharField(required=False, allow_null=True, allow_blank=True, max_length=4096,
+    prologue = serializers.CharField(required=False, allow_null=True, allow_blank=True, max_length=102400,
                                      error_messages=ErrMessage.char(_("Opening remarks")))
 
     @staticmethod
@@ -225,7 +227,7 @@ class ApplicationSerializer(serializers.Serializer):
                                                min_value=0,
                                                max_value=1024,
                                                error_messages=ErrMessage.integer(_("Historical chat records")))
-    prologue = serializers.CharField(required=False, allow_null=True, allow_blank=True, max_length=4096,
+    prologue = serializers.CharField(required=False, allow_null=True, allow_blank=True, max_length=102400,
                                      error_messages=ErrMessage.char(_("Opening remarks")))
     dataset_id_list = serializers.ListSerializer(required=False, child=serializers.UUIDField(required=True),
                                                  allow_null=True,
@@ -493,7 +495,7 @@ class ApplicationSerializer(serializers.Serializer):
                                                    min_value=0,
                                                    max_value=1024,
                                                    error_messages=ErrMessage.integer(_("Historical chat records")))
-        prologue = serializers.CharField(required=False, allow_null=True, allow_blank=True, max_length=4096,
+        prologue = serializers.CharField(required=False, allow_null=True, allow_blank=True, max_length=102400,
                                          error_messages=ErrMessage.char(_("Opening remarks")))
         dataset_id_list = serializers.ListSerializer(required=False, child=serializers.UUIDField(required=True),
                                                      error_messages=ErrMessage.list(_("Related Knowledge Base"))
@@ -1010,7 +1012,8 @@ class ApplicationSerializer(serializers.Serializer):
                  'stt_autosend': application.stt_autosend,
                  'file_upload_enable': application.file_upload_enable,
                  'file_upload_setting': application.file_upload_setting,
-                 'work_flow': application.work_flow,
+                 'work_flow': {'nodes': [node for node in ((application.work_flow or {}).get('nodes', []) or []) if
+                                         node.get('id') == 'base-node']},
                  'show_source': application_access_token.show_source,
                  'language': application_access_token.language,
                  **application_setting_dict})
@@ -1071,6 +1074,7 @@ class ApplicationSerializer(serializers.Serializer):
             for update_key in update_keys:
                 if update_key in instance and instance.get(update_key) is not None:
                     application.__setattr__(update_key, instance.get(update_key))
+            print(application.name)
             application.save()
 
             if 'dataset_id_list' in instance:
@@ -1089,6 +1093,7 @@ class ApplicationSerializer(serializers.Serializer):
                 chat_cache.clear_by_application_id(application_id)
             application_access_token = QuerySet(ApplicationAccessToken).filter(application_id=application_id).first()
             # 更新缓存数据
+            print(application.name)
             get_application_access_token(application_access_token.access_token, False)
             return self.one(with_valid=False)
 
@@ -1141,6 +1146,8 @@ class ApplicationSerializer(serializers.Serializer):
                         instance['file_upload_enable'] = node_data['file_upload_enable']
                     if 'file_upload_setting' in node_data:
                         instance['file_upload_setting'] = node_data['file_upload_setting']
+                    if 'name' in node_data:
+                        instance['name'] = node_data['name']
                     break
 
         def speech_to_text(self, file, with_valid=True):
@@ -1318,6 +1325,8 @@ class ApplicationSerializer(serializers.Serializer):
         def get_mcp_servers(self, with_valid=True):
             if with_valid:
                 self.is_valid(raise_exception=True)
+                if '"stdio"' in self.data.get('mcp_servers'):
+                    raise AppApiException(500, _('stdio is not supported'))
             servers = json.loads(self.data.get('mcp_servers'))
 
             async def get_mcp_tools(servers):

apps/application/serializers/chat_message_serializers.py

@@ -213,12 +213,21 @@ class OpenAIChatSerializer(serializers.Serializer):
         return instance.get('messages')[-1].get('content')
 
     @staticmethod
-    def generate_chat(chat_id, application_id, message, client_id):
+    def generate_chat(chat_id, application_id, message, client_id, asker=None):
         if chat_id is None:
             chat_id = str(uuid.uuid1())
         chat = QuerySet(Chat).filter(id=chat_id).first()
         if chat is None:
-            Chat(id=chat_id, application_id=application_id, abstract=message[0:1024], client_id=client_id).save()
+            asker_dict = {'user_name': '游客'}
+            if asker is not None:
+                if isinstance(asker, str):
+                    asker_dict = {
+                        'user_name': asker
+                    }
+                elif isinstance(asker, dict):
+                    asker_dict = asker
+            Chat(id=chat_id, application_id=application_id, abstract=message[0:1024], client_id=client_id,
+                 asker=asker_dict).save()
         return chat_id
 
     def chat(self, instance: Dict, with_valid=True):
@@ -232,7 +241,8 @@ class OpenAIChatSerializer(serializers.Serializer):
         application_id = self.data.get('application_id')
         client_id = self.data.get('client_id')
         client_type = self.data.get('client_type')
-        chat_id = self.generate_chat(chat_id, application_id, message, client_id)
+        chat_id = self.generate_chat(chat_id, application_id, message, client_id,
+                                     asker=instance.get('form_data', {}).get("asker"))
         return ChatMessageSerializer(
             data={
                 'chat_id': chat_id, 'message': message,
@@ -245,6 +255,7 @@ class OpenAIChatSerializer(serializers.Serializer):
                 'image_list': instance.get('image_list', []),
                 'document_list': instance.get('document_list', []),
                 'audio_list': instance.get('audio_list', []),
+                'other_list': instance.get('other_list', []),
             }
         ).chat(base_to_response=OpenaiToResponse())
 
@@ -274,6 +285,7 @@ class ChatMessageSerializer(serializers.Serializer):
     image_list = serializers.ListField(required=False, error_messages=ErrMessage.list(_("picture")))
     document_list = serializers.ListField(required=False, error_messages=ErrMessage.list(_("document")))
     audio_list = serializers.ListField(required=False, error_messages=ErrMessage.list(_("Audio")))
+    other_list = serializers.ListField(required=False, error_messages=ErrMessage.list(_("Other")))
     child_node = serializers.DictField(required=False, allow_null=True,
                                        error_messages=ErrMessage.dict(_("Child Nodes")))
 
@@ -372,6 +384,7 @@ class ChatMessageSerializer(serializers.Serializer):
         image_list = self.data.get('image_list')
         document_list = self.data.get('document_list')
         audio_list = self.data.get('audio_list')
+        other_list = self.data.get('other_list')
         user_id = chat_info.application.user_id
         chat_record_id = self.data.get('chat_record_id')
         chat_record = None
@@ -388,7 +401,7 @@ class ChatMessageSerializer(serializers.Serializer):
                                            'client_id': client_id,
                                            'client_type': client_type,
                                            'user_id': user_id}, WorkFlowPostHandler(chat_info, client_id, client_type),
-                                          base_to_response, form_data, image_list, document_list, audio_list,
+                                          base_to_response, form_data, image_list, document_list, audio_list, other_list,
                                           self.data.get('runtime_node_id'),
                                           self.data.get('node_data'), chat_record, self.data.get('child_node'))
         r = work_flow_manage.run()

apps/application/serializers/chat_serializers.py

@@ -174,7 +174,14 @@ class ChatSerializers(serializers.Serializer):
                 condition = base_condition & min_trample_query
             else:
                 condition = base_condition
-            return query_set.filter(condition).order_by("-application_chat.update_time")
+            inner_queryset = QuerySet(Chat).filter(application_id=self.data.get("application_id"))
+            if 'abstract' in self.data and self.data.get('abstract') is not None:
+                inner_queryset = inner_queryset.filter(abstract__icontains=self.data.get('abstract'))
+
+            return {
+                'inner_queryset': inner_queryset,
+                'default_queryset': query_set.filter(condition).order_by("-application_chat.update_time")
+            }
 
         def list(self, with_valid=True):
             if with_valid:

apps/application/sql/export_application_chat.sql

@@ -23,6 +23,8 @@ FROM
 		chat_id
 	FROM
 		application_chat_record
+	WHERE chat_id IN (
+	  SELECT id FROM application_chat ${inner_queryset})
 	GROUP BY
 		application_chat_record.chat_id
 	) chat_record_temp ON application_chat."id" = chat_record_temp.chat_id
@@ -36,3 +38,4 @@ FROM
 		FROM
 		application_chat_record application_chat_record
 	) application_chat_record_temp ON application_chat_record_temp.chat_id = application_chat."id"
+	${default_queryset}

apps/application/sql/list_application_chat.sql

@@ -11,6 +11,9 @@ FROM
 		chat_id
 	FROM
 		application_chat_record
+	WHERE chat_id IN (
+	  SELECT id FROM application_chat ${inner_queryset})
 	GROUP BY
 	application_chat_record.chat_id
 	) chat_record_temp ON application_chat."id" = chat_record_temp.chat_id
+${default_queryset}

apps/application/swagger_api/application_api.py

@@ -38,6 +38,15 @@ class ApplicationApi(ApiMixin):
                 }
             )
 
+        @staticmethod
+        def get_response_body_api():
+            return openapi.Schema(
+                type=openapi.TYPE_STRING,
+                title=_("Application authentication token"),
+                description=_("Application authentication token"),
+                default="token"
+            )
+
     @staticmethod
     def get_response_body_api():
         return openapi.Schema(
@@ -133,6 +142,27 @@ class ApplicationApi(ApiMixin):
                     }
                 )
 
+            @staticmethod
+            def get_response_body_api():
+                return openapi.Schema(
+                    type=openapi.TYPE_OBJECT,
+                    properties={
+                        'id': openapi.Schema(type=openapi.TYPE_STRING, title=_("Primary key id"),
+                                             description=_("Primary key id")),
+                        'secret_key': openapi.Schema(type=openapi.TYPE_STRING, title=_("Secret key"),
+                                                     description=_("Secret key")),
+                        'is_active': openapi.Schema(type=openapi.TYPE_BOOLEAN, title=_("Is activation"),
+                                                    description=_("Is activation")),
+                        'application_id': openapi.Schema(type=openapi.TYPE_STRING, title=_("Application ID"),
+                                                         description=_("Application ID")),
+                        'allow_cross_domain': openapi.Schema(type=openapi.TYPE_BOOLEAN,
+                                                             title=_("Is cross-domain allowed"),
+                                                             description=_("Is cross-domain allowed")),
+                        'cross_domain_list': openapi.Schema(type=openapi.TYPE_ARRAY, title=_('Cross-domain list'),
+                                                            items=openapi.Schema(type=openapi.TYPE_STRING))
+                    }
+                )
+
     class AccessToken(ApiMixin):
         @staticmethod
         def get_request_params_api():
@@ -171,6 +201,37 @@ class ApplicationApi(ApiMixin):
                 }
             )
 
+        @staticmethod
+        def get_response_body_api():
+            return openapi.Schema(
+                type=openapi.TYPE_OBJECT,
+                required=[],
+                properties={
+                    'id': openapi.Schema(type=openapi.TYPE_STRING, title=_("Primary key id"),
+                                         description=_("Primary key id")),
+                    'access_token': openapi.Schema(type=openapi.TYPE_STRING, title=_("Access Token"),
+                                                   description=_("Access Token")),
+                    'access_token_reset': openapi.Schema(type=openapi.TYPE_BOOLEAN, title=_("Reset Token"),
+                                                         description=_("Reset Token")),
+
+                    'is_active': openapi.Schema(type=openapi.TYPE_BOOLEAN, title=_("Is activation"),
+                                                description=_("Is activation")),
+                    'access_num': openapi.Schema(type=openapi.TYPE_NUMBER, title=_("Number of visits"),
+                                                 description=_("Number of visits")),
+                    'white_active': openapi.Schema(type=openapi.TYPE_BOOLEAN, title=_("Whether to enable whitelist"),
+                                                   description=_("Whether to enable whitelist")),
+                    'white_list': openapi.Schema(type=openapi.TYPE_ARRAY,
+                                                 items=openapi.Schema(type=openapi.TYPE_STRING), title=_("Whitelist"),
+                                                 description=_("Whitelist")),
+                    'show_source': openapi.Schema(type=openapi.TYPE_BOOLEAN,
+                                                  title=_("Whether to display knowledge sources"),
+                                                  description=_("Whether to display knowledge sources")),
+                    'language': openapi.Schema(type=openapi.TYPE_STRING,
+                                               title=_("language"),
+                                               description=_("language"))
+                }
+            )
+
     class Edit(ApiMixin):
         @staticmethod
         def get_request_body_api():
@@ -367,6 +428,56 @@ class ApplicationApi(ApiMixin):
                 }
             )
 
+        @staticmethod
+        def get_response_body_api():
+            return openapi.Schema(
+                type=openapi.TYPE_OBJECT,
+                required=['id', 'name', 'desc', 'model_id', 'dialogue_number', 'dataset_setting', 'model_setting',
+                          'problem_optimization', 'stt_model_enable', 'stt_model_enable', 'tts_type',
+                          'work_flow'],
+                properties={
+                    'id': openapi.Schema(type=openapi.TYPE_STRING, title=_("Primary key id"),
+                                         description=_("Primary key id")),
+                    'name': openapi.Schema(type=openapi.TYPE_STRING, title=_("Application Name"),
+                                           description=_("Application Name")),
+                    'desc': openapi.Schema(type=openapi.TYPE_STRING, title=_("Application Description"),
+                                           description=_("Application Description")),
+                    'model_id': openapi.Schema(type=openapi.TYPE_STRING, title=_("Model id"),
+                                               description=_("Model id")),
+                    "dialogue_number": openapi.Schema(type=openapi.TYPE_NUMBER,
+                                                      title=_("Number of multi-round conversations"),
+                                                      description=_("Number of multi-round conversations")),
+                    'prologue': openapi.Schema(type=openapi.TYPE_STRING, title=_("Opening remarks"),
+                                               description=_("Opening remarks")),
+                    'dataset_id_list': openapi.Schema(type=openapi.TYPE_ARRAY,
+                                                      items=openapi.Schema(type=openapi.TYPE_STRING),
+                                                      title=_("List of associated knowledge base IDs"),
+                                                      description=_("List of associated knowledge base IDs")),
+                    'dataset_setting': ApplicationApi.DatasetSetting.get_request_body_api(),
+                    'model_setting': ApplicationApi.ModelSetting.get_request_body_api(),
+                    'problem_optimization': openapi.Schema(type=openapi.TYPE_BOOLEAN, title=_("Problem Optimization"),
+                                                           description=_("Problem Optimization"), default=True),
+                    'type': openapi.Schema(type=openapi.TYPE_STRING, title=_("Application Type"),
+                                           description=_("Application Type   SIMPLE |  WORK_FLOW")),
+                    'problem_optimization_prompt': openapi.Schema(type=openapi.TYPE_STRING,
+                                                                  title=_('Question optimization tips'),
+                                                                  description=_("Question optimization tips"),
+                                                                  default=_(
+                                                                      "() contains the user's question. Answer the guessed user's question based on the context ({question}) Requirement: Output a complete question and put it in the <data></data> tag")),
+                    'tts_model_id': openapi.Schema(type=openapi.TYPE_STRING, title=_("Text-to-speech model ID"),
+                                                   description=_("Text-to-speech model ID")),
+                    'stt_model_id': openapi.Schema(type=openapi.TYPE_STRING, title=_("Speech-to-text model id"),
+                                                   description=_("Speech-to-text model id")),
+                    'stt_model_enable': openapi.Schema(type=openapi.TYPE_STRING, title=_("Is speech-to-text enabled"),
+                                                       description=_("Is speech-to-text enabled")),
+                    'tts_model_enable': openapi.Schema(type=openapi.TYPE_STRING, title=_("Is text-to-speech enabled"),
+                                                       description=_("Is text-to-speech enabled")),
+                    'tts_type': openapi.Schema(type=openapi.TYPE_STRING, title=_("Text-to-speech type"),
+                                               description=_("Text-to-speech type")),
+                    'work_flow': ApplicationApi.WorkFlow.get_request_body_api(),
+                }
+            )
+
     class Query(ApiMixin):
         @staticmethod
         def get_request_params_api():

apps/application/swagger_api/chat_api.py

@@ -319,6 +319,15 @@ class ChatApi(ApiMixin):
                 }
             )
 
+        @staticmethod
+        def get_response_body_api():
+            return openapi.Schema(
+                type=openapi.TYPE_STRING,
+                title=_("Conversation ID"),
+                description=_("Conversation ID"),
+                default="chat_id"
+            )
+
     @staticmethod
     def get_request_params_api():
         return [openapi.Parameter(name='application_id',

apps/application/views/application_views.py

@@ -373,7 +373,8 @@ class Application(APIView):
                                  operation_id=_("Modify application API_KEY"),
                                  tags=[_('Application/API_KEY')],
                                  manual_parameters=ApplicationApi.ApiKey.Operate.get_request_params_api(),
-                                 request_body=ApplicationApi.ApiKey.Operate.get_request_body_api())
+                                 request_body=ApplicationApi.ApiKey.Operate.get_request_body_api(),
+                                 responses=result.get_api_response(ApplicationApi.ApiKey.Operate.get_response_body_api()))
             @has_permissions(ViewPermission(
                 [RoleConstants.ADMIN, RoleConstants.USER],
                 [lambda r, keywords: Permission(group=Group.APPLICATION, operate=Operate.MANAGE,
@@ -415,7 +416,8 @@ class Application(APIView):
                              operation_id=_("Modify Application AccessToken"),
                              tags=[_('Application/Public Access')],
                              manual_parameters=ApplicationApi.AccessToken.get_request_params_api(),
-                             request_body=ApplicationApi.AccessToken.get_request_body_api())
+                             request_body=ApplicationApi.AccessToken.get_request_body_api(),
+                             responses=result.get_api_response(ApplicationApi.AccessToken.get_response_body_api()))
         @has_permissions(ViewPermission(
             [RoleConstants.ADMIN, RoleConstants.USER],
             [lambda r, keywords: Permission(group=Group.APPLICATION, operate=Operate.MANAGE,
@@ -455,6 +457,7 @@ class Application(APIView):
         @swagger_auto_schema(operation_summary=_("Application Certification"),
                              operation_id=_("Application Certification"),
                              request_body=ApplicationApi.Authentication.get_request_body_api(),
+                             responses=result.get_api_response(ApplicationApi.Authentication.get_response_body_api()),
                              tags=[_("Application/Certification")],
                              security=[])
         def post(self, request: Request):
@@ -472,6 +475,7 @@ class Application(APIView):
     @swagger_auto_schema(operation_summary=_("Create an application"),
                          operation_id=_("Create an application"),
                          request_body=ApplicationApi.Create.get_request_body_api(),
+                         responses=result.get_api_response(ApplicationApi.Create.get_response_body_api()),
                          tags=[_('Application')])
     @has_permissions(PermissionConstants.APPLICATION_CREATE, compare=CompareConstants.AND)
     @log(menu='Application', operate="Create an application",

apps/application/views/chat_views.py

@@ -94,6 +94,7 @@ class ChatView(APIView):
         @swagger_auto_schema(operation_summary=_("Get the workflow temporary session id"),
                              operation_id=_("Get the workflow temporary session id"),
                              request_body=ChatApi.OpenWorkFlowTemp.get_request_body_api(),
+                             responses=result.get_api_response(ChatApi.OpenTempChat.get_response_body_api()),
                              tags=[_("Application/Chat")])
         def post(self, request: Request):
             return result.success(ChatSerializers.OpenWorkFlowChat(
@@ -106,6 +107,7 @@ class ChatView(APIView):
         @swagger_auto_schema(operation_summary=_("Get a temporary session id"),
                              operation_id=_("Get a temporary session id"),
                              request_body=ChatApi.OpenTempChat.get_request_body_api(),
+                             responses=result.get_api_response(ChatApi.OpenTempChat.get_response_body_api()),
                              tags=[_("Application/Chat")])
         @has_permissions(RoleConstants.ADMIN, RoleConstants.USER)
         def post(self, request: Request):
@@ -144,6 +146,8 @@ class ChatView(APIView):
                                                    'document_list') if 'document_list' in request.data else [],
                                                'audio_list': request.data.get(
                                                    'audio_list') if 'audio_list' in request.data else [],
+                                               'other_list': request.data.get(
+                                                   'other_list') if 'other_list' in request.data else [],
                                                'client_type': request.auth.client_type,
                                                'node_id': request.data.get('node_id', None),
                                                'runtime_node_id': request.data.get('runtime_node_id', None),
@@ -237,9 +241,10 @@ class ChatView(APIView):
             @swagger_auto_schema(operation_summary=_("Client modifies dialogue summary"),
                                  operation_id=_("Client modifies dialogue summary"),
                                  request_body=ChatClientHistoryApi.Operate.ReAbstract.get_request_body_api(),
+                                 responses=result.get_default_response(),
                                  tags=[_("Application/Conversation Log")])
             @has_permissions(ViewPermission(
-                [RoleConstants.APPLICATION_ACCESS_TOKEN],
+                [RoleConstants.APPLICATION_ACCESS_TOKEN, RoleConstants.ADMIN, RoleConstants.USER],
                 [lambda r, keywords: Permission(group=Group.APPLICATION, operate=Operate.USE,
                                                 dynamic_tag=keywords.get('application_id'))],
                 compare=CompareConstants.AND),
@@ -416,6 +421,7 @@ class ChatView(APIView):
                                  operation_id=_("Add to Knowledge Base"),
                                  manual_parameters=ImproveApi.get_request_params_api_post(),
                                  request_body=ImproveApi.get_request_body_api_post(),
+                                 responses=result.get_default_response(),
                                  tags=[_("Application/Conversation Log/Add to Knowledge Base")]
                                  )
             @has_permissions(

apps/common/config/embedding_config.py

@@ -11,35 +11,50 @@ import time
 
 from common.cache.mem_cache import MemCache
 
-lock = threading.Lock()
+_lock = threading.Lock()
+locks = {}
 
 
 class ModelManage:
     cache = MemCache('model', {})
     up_clear_time = time.time()
 
+    @staticmethod
+    def _get_lock(_id):
+        lock = locks.get(_id)
+        if lock is None:
+            with _lock:
+                lock = locks.get(_id)
+                if lock is None:
+                    lock = threading.Lock()
+                    locks[_id] = lock
+
+        return lock
+
     @staticmethod
     def get_model(_id, get_model):
-        # 获取锁
+        model_instance = ModelManage.cache.get(_id)
-        lock.acquire()
+        if model_instance is None:
-        try:
+            lock = ModelManage._get_lock(_id)
-            model_instance = ModelManage.cache.get(_id)
+            with lock:
-            if model_instance is None or not model_instance.is_cache_model():
+                model_instance = ModelManage.cache.get(_id)
+                if model_instance is None:
+                    model_instance = get_model(_id)
+                    ModelManage.cache.set(_id, model_instance, timeout=60 * 60 * 8)
+        else:
+            if model_instance.is_cache_model():
+                ModelManage.cache.touch(_id, timeout=60 * 60 * 8)
+            else:
                 model_instance = get_model(_id)
-                ModelManage.cache.set(_id, model_instance, timeout=60 * 30)
+                ModelManage.cache.set(_id, model_instance, timeout=60 * 60 * 8)
-                return model_instance
+        ModelManage.clear_timeout_cache()
-            # 续期
+        return model_instance
-            ModelManage.cache.touch(_id, timeout=60 * 30)
-            ModelManage.clear_timeout_cache()
-            return model_instance
-        finally:
-            # 释放锁
-            lock.release()
 
     @staticmethod
     def clear_timeout_cache():
-        if time.time() - ModelManage.up_clear_time > 60:
+        if time.time() - ModelManage.up_clear_time > 60 * 60:
-            ModelManage.cache.clear_timeout_data()
+            threading.Thread(target=lambda: ModelManage.cache.clear_timeout_data()).start()
+            ModelManage.up_clear_time = time.time()
 
     @staticmethod
     def delete_key(_id):

apps/common/event/listener_manage.py

@@ -238,11 +238,8 @@ class ListenerManagement:
         for key in params_dict:
             _value_ = params_dict[key]
             exec_sql = exec_sql.replace(key, str(_value_))
-        lock.acquire()
+        with lock:
-        try:
             native_update(query_set, exec_sql)
-        finally:
-            lock.release()
 
     @staticmethod
     def embedding_by_document(document_id, embedding_model: Embeddings, state_list=None):
@@ -272,7 +269,6 @@ class ListenerManagement:
             ListenerManagement.update_status(QuerySet(Document).filter(id=document_id), TaskType.EMBEDDING,
                                              State.STARTED)
 
-
             # 根据段落进行向量化处理
             page_desc(QuerySet(Paragraph)
                       .annotate(

apps/common/forms/__init__.py

@@ -22,3 +22,4 @@ from .table_checkbox import *
 from .radio_card_field import *
 from .label import *
 from .slider_field import *
+from .switch_field import *

apps/common/forms/switch_field.py

@@ -28,6 +28,6 @@ class SwitchField(BaseField):
         @param props_info:
         """
 
-        super().__init__('Switch', label, required, default_value, relation_show_field_dict,
+        super().__init__('SwitchInput', label, required, default_value, relation_show_field_dict,
                          {},
                          TriggerType.OPTION_LIST, attrs, props_info)

apps/common/handle/impl/doc_split_handle.py

@@ -112,11 +112,7 @@ def get_image_id_func():
 
 title_font_list = [
     [36, 100],
-    [26, 36],
+    [30, 36]
-    [24, 26],
-    [22, 24],
-    [18, 22],
-    [16, 18]
 ]
 
 
@@ -130,7 +126,7 @@ def get_title_level(paragraph: Paragraph):
         if len(paragraph.runs) == 1:
             font_size = paragraph.runs[0].font.size
             pt = font_size.pt
-            if pt >= 16:
+            if pt >= 30:
                 for _value, index in zip(title_font_list, range(len(title_font_list))):
                     if pt >= _value[0] and pt < _value[1]:
                         return index + 1

apps/common/handle/impl/table/xls_parse_table_handle.py

@@ -82,7 +82,10 @@ class XlsSplitHandle(BaseParseTableHandle):
                 for row in data:
                     # 将每个单元格中的内容替换换行符为 <br> 以保留原始格式
                     md_table += '| ' + ' | '.join(
-                        [str(cell).replace('\n', '<br>') if cell else '' for cell in row]) + ' |\n'
+                        [str(cell)
+                         .replace('\r\n', '<br>')
+                         .replace('\n', '<br>')
+                         if cell else '' for cell in row]) + ' |\n'
                 md_tables += md_table + '\n\n'
 
             return md_tables

apps/common/handle/impl/table/xlsx_parse_table_handle.py

@@ -19,36 +19,24 @@ class XlsxSplitHandle(BaseParseTableHandle):
 
     def fill_merged_cells(self, sheet, image_dict):
         data = []
-
-        # 获取第一行作为标题行
-        headers = []
-        for idx, cell in enumerate(sheet[1]):
-            if cell.value is None:
-                headers.append(' ' * (idx + 1))
-            else:
-                headers.append(cell.value)
-
         # 从第二行开始遍历每一行
-        for row in sheet.iter_rows(min_row=2, values_only=False):
+        for row in sheet.iter_rows(values_only=False):
-            row_data = {}
+            row_data = []
             for col_idx, cell in enumerate(row):
                 cell_value = cell.value
-
-                # 如果单元格为空，并且该单元格在合并单元格内，获取合并单元格的值
-                if cell_value is None:
-                    for merged_range in sheet.merged_cells.ranges:
-                        if cell.coordinate in merged_range:
-                            cell_value = sheet[merged_range.min_row][merged_range.min_col - 1].value
-                            break
-
                 image = image_dict.get(cell_value, None)
                 if image is not None:
                     cell_value = f'![](/api/image/{image.id})'
 
                 # 使用标题作为键，单元格的值作为值存入字典
-                row_data[headers[col_idx]] = cell_value
+                row_data.insert(col_idx, cell_value)
             data.append(row_data)
 
+        for merged_range in sheet.merged_cells.ranges:
+            cell_value = data[merged_range.min_row - 1][merged_range.min_col - 1]
+            for row_index in range(merged_range.min_row, merged_range.max_row + 1):
+                for col_index in range(merged_range.min_col, merged_range.max_col + 1):
+                    data[row_index - 1][col_index - 1] = cell_value
         return data
 
     def handle(self, file, get_buffer, save_image):
@@ -65,11 +53,13 @@ class XlsxSplitHandle(BaseParseTableHandle):
                 paragraphs = []
                 ws = wb[sheetname]
                 data = self.fill_merged_cells(ws, image_dict)
-
+                if len(data) >= 2:
-                for row in data:
+                    head_list = data[0]
-                    row_output = "; ".join([f"{key}: {value}" for key, value in row.items()])
+                    for row_index in range(1, len(data)):
-                    # print(row_output)
+                        row_output = "; ".join(
-                    paragraphs.append({'title': '', 'content': row_output})
+                            [f"{head_list[col_index]}: {data[row_index][col_index]}" for col_index in
+                             range(0, len(data[row_index]))])
+                        paragraphs.append({'title': '', 'content': row_output})
 
                 result.append({'name': sheetname, 'paragraphs': paragraphs})
 
@@ -78,7 +68,6 @@ class XlsxSplitHandle(BaseParseTableHandle):
             return [{'name': file.name, 'paragraphs': []}]
         return result
 
-
     def get_content(self, file, save_image):
         try:
             # 加载 Excel 文件
@@ -94,18 +83,18 @@ class XlsxSplitHandle(BaseParseTableHandle):
             # 如果未指定 sheet_name，则使用第一个工作表
             for sheetname in workbook.sheetnames:
                 sheet = workbook[sheetname] if sheetname else workbook.active
-                rows = self.fill_merged_cells(sheet, image_dict)
+                data = self.fill_merged_cells(sheet, image_dict)
-                if len(rows) == 0:
+                if len(data) == 0:
                     continue
                 # 提取表头和内容
 
-                headers = [f"{key}" for key, value in rows[0].items()]
+                headers = [f"{value}" for value in data[0]]
 
                 # 构建 Markdown 表格
                 md_table = '| ' + ' | '.join(headers) + ' |\n'
                 md_table += '| ' + ' | '.join(['---'] * len(headers)) + ' |\n'
-                for row in rows:
+                for row_index in range(1, len(data)):
-                    r = [f'{value}' for key, value in row.items()]
+                    r = [f'{value}' for value in data[row_index]]
                     md_table += '| ' + ' | '.join(
                         [str(cell).replace('\n', '<br>') if cell is not None else '' for cell in r]) + ' |\n'
 

apps/common/handle/impl/xls_split_handle.py

@@ -14,7 +14,7 @@ from common.handle.base_split_handle import BaseSplitHandle
 
 
 def post_cell(cell_value):
-    return cell_value.replace('\n', '<br>').replace('|', '&#124;')
+    return cell_value.replace('\r\n', '<br>').replace('\n', '<br>').replace('|', '&#124;')
 
 
 def row_to_md(row):

apps/common/management/commands/services/services/local_model.py

@@ -24,12 +24,13 @@ class GunicornLocalModelService(BaseService):
         os.environ.setdefault('SERVER_NAME', 'local_model')
         log_format = '%(h)s %(t)s %(L)ss "%(r)s" %(s)s %(b)s '
         bind = f'{CONFIG.get("LOCAL_MODEL_HOST")}:{CONFIG.get("LOCAL_MODEL_PORT")}'
+        worker = CONFIG.get("LOCAL_MODEL_HOST_WORKER", 1)
         cmd = [
             'gunicorn', 'smartdoc.wsgi:application',
             '-b', bind,
             '-k', 'gthread',
             '--threads', '200',
-            '-w', "1",
+            '-w', str(worker),
             '--max-requests', '10240',
             '--max-requests-jitter', '2048',
             '--access-logformat', log_format,

apps/common/util/common.py

@@ -11,6 +11,7 @@ import importlib
 import io
 import mimetypes
 import pickle
+import random
 import re
 import shutil
 from functools import reduce
@@ -297,3 +298,14 @@ def markdown_to_plain_text(md: str) -> str:
     # 去除首尾空格
     text = text.strip()
     return text
+
+
+SAFE_CHAR_SET = (
+        [chr(i) for i in range(65, 91) if chr(i) not in {'I', 'O'}] +  # 大写字母 A-H, J-N, P-Z
+        [chr(i) for i in range(97, 123) if chr(i) not in {'i', 'l', 'o'}] +  # 小写字母 a-h, j-n, p-z
+        [str(i) for i in range(10) if str(i) not in {'0', '1', '7'}]  # 数字 2-6, 8-9
+)
+
+
+def get_random_chars(number=4):
+    return ''.join(random.choices(SAFE_CHAR_SET, k=number))

apps/common/util/function_code.py

@@ -7,13 +7,12 @@
     @desc:
 """
 import os
+import pickle
 import subprocess
 import sys
 import uuid
 from textwrap import dedent
 
-from diskcache import Cache
-
 from smartdoc.const import BASE_DIR
 from smartdoc.const import PROJECT_DIR
 
@@ -37,6 +36,8 @@ class FunctionExecutor:
         old_mask = os.umask(0o077)
         try:
             os.makedirs(self.sandbox_path, 0o700, exist_ok=True)
+            os.makedirs(os.path.join(self.sandbox_path, 'execute'), 0o700, exist_ok=True)
+            os.makedirs(os.path.join(self.sandbox_path, 'result'), 0o700, exist_ok=True)
         finally:
             os.umask(old_mask)
 
@@ -44,10 +45,11 @@ class FunctionExecutor:
         _id = str(uuid.uuid1())
         success = '{"code":200,"msg":"成功","data":exec_result}'
         err = '{"code":500,"msg":str(e),"data":None}'
-        path = r'' + self.sandbox_path + ''
+        result_path = f'{self.sandbox_path}/result/{_id}.result'
         _exec_code = f"""
 try:
     import os
+    import pickle
     env = dict(os.environ)
     for key in list(env.keys()):
         if key in os.environ and (key.startswith('MAXKB') or key.startswith('POSTGRES') or key.startswith('PG')):
@@ -60,13 +62,11 @@ try:
     for local in locals_v:
         globals_v[local] = locals_v[local]
     exec_result=f(**keywords)
-    from diskcache import Cache
+    with open({result_path!a}, 'wb') as file:
-    cache = Cache({path!a})
+        file.write(pickle.dumps({success}))
-    cache.set({_id!a},{success})
 except Exception as e:
-    from diskcache import Cache
+    with open({result_path!a}, 'wb') as file:
-    cache = Cache({path!a})
+        file.write(pickle.dumps({err}))
-    cache.set({_id!a},{err})
 """
         if self.sandbox:
             subprocess_result = self._exec_sandbox(_exec_code, _id)
@@ -74,18 +74,18 @@ except Exception as e:
             subprocess_result = self._exec(_exec_code)
         if subprocess_result.returncode == 1:
             raise Exception(subprocess_result.stderr)
-        cache = Cache(self.sandbox_path)
+        with open(result_path, 'rb') as file:
-        result = cache.get(_id)
+            result = pickle.loads(file.read())
-        cache.delete(_id)
+        os.remove(result_path)
         if result.get('code') == 200:
             return result.get('data')
         raise Exception(result.get('msg'))
 
     def _exec_sandbox(self, _code, _id):
-        exec_python_file = f'{self.sandbox_path}/{_id}.py'
+        exec_python_file = f'{self.sandbox_path}/execute/{_id}.py'
         with open(exec_python_file, 'w') as file:
             file.write(_code)
-            os.system(f"chown {self.user}:{self.user} {exec_python_file}")
+            os.system(f"chown {self.user}:root {exec_python_file}")
         kwargs = {'cwd': BASE_DIR}
         subprocess_result = subprocess.run(
             ['su', '-s', python_directory, '-c', "exec(open('" + exec_python_file + "').read())", self.user],

apps/common/util/rsa_util.py

@@ -40,15 +40,12 @@ def generate():
 def get_key_pair():
     rsa_value = rsa_cache.get(cache_key)
     if rsa_value is None:
-        lock.acquire()
+        with lock:
-        rsa_value = rsa_cache.get(cache_key)
+            rsa_value = rsa_cache.get(cache_key)
-        if rsa_value is not None:
+            if rsa_value is not None:
-            return rsa_value
+                return rsa_value
-        try:
             rsa_value = get_key_pair_by_sql()
             rsa_cache.set(cache_key, rsa_value)
-        finally:
-            lock.release()
     return rsa_value
 
 

apps/dataset/serializers/document_serializers.py

@@ -23,6 +23,8 @@ from django.db import transaction, models
 from django.db.models import QuerySet, Count
 from django.db.models.functions import Substr, Reverse
 from django.http import HttpResponse
+from django.utils.translation import get_language
+from django.utils.translation import gettext_lazy as _, gettext, to_locale
 from drf_yasg import openapi
 from openpyxl.cell.cell import ILLEGAL_CHARACTERS_RE
 from rest_framework import serializers
@@ -64,8 +66,6 @@ from embedding.task.embedding import embedding_by_document, delete_embedding_by_
     embedding_by_document_list
 from setting.models import Model
 from smartdoc.conf import PROJECT_DIR
-from django.utils.translation import gettext_lazy as _, gettext, to_locale
-from django.utils.translation import get_language
 
 parse_qa_handle_list = [XlsParseQAHandle(), CsvParseQAHandle(), XlsxParseQAHandle(), ZipParseQAHandle()]
 parse_table_handle_list = [CsvSplitTableHandle(), XlsSplitTableHandle(), XlsxSplitTableHandle()]
@@ -661,6 +661,8 @@ class DocumentSerializers(ApiMixin, serializers.Serializer):
                         cell = worksheet.cell(row=row_idx + 1, column=col_idx + 1)
                         if isinstance(col, str):
                             col = re.sub(ILLEGAL_CHARACTERS_RE, '', col)
+                            if col.startswith(('=', '+', '-', '@')):
+                                col = '\ufeff' + col
                         cell.value = col
                     # 创建HttpResponse对象返回Excel文件
             return workbook

apps/dataset/serializers/file_serializers.py

@@ -28,6 +28,9 @@ mime_types = {"html": "text/html", "htm": "text/html", "shtml": "text/html", "cs
               "woff2": "font/woff2", "jar": "application/java-archive", "war": "application/java-archive",
               "ear": "application/java-archive", "json": "application/json", "hqx": "application/mac-binhex40",
               "doc": "application/msword", "pdf": "application/pdf", "ps": "application/postscript",
+              "docx": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
+              "xlsx": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
+              "pptx": "application/vnd.openxmlformats-officedocument.presentationml.presentation",
               "eps": "application/postscript", "ai": "application/postscript", "rtf": "application/rtf",
               "m3u8": "application/vnd.apple.mpegurl", "kml": "application/vnd.google-earth.kml+xml",
               "kmz": "application/vnd.google-earth.kmz", "xls": "application/vnd.ms-excel",
@@ -87,4 +90,4 @@ class FileSerializer(serializers.Serializer):
                                                                           'Content-Disposition': 'attachment; filename="{}"'.format(
                                                                               file.file_name)})
             return HttpResponse(file.get_byte(), status=200,
-                                headers={'Content-Type': mime_types.get(file.file_name.split(".")[-1], 'text/plain')})
+                                headers={'Content-Type': mime_types.get(file_type, 'text/plain')})

apps/dataset/sql/update_document_char_length.sql

@@ -2,6 +2,7 @@ UPDATE "document"
 SET "char_length" = ( SELECT CASE WHEN
 		"sum" ( "char_length" ( "content" ) ) IS NULL THEN
 			0 ELSE "sum" ( "char_length" ( "content" ) )
-		END FROM paragraph WHERE "document_id" = %s )
+		END FROM paragraph WHERE "document_id" = %s ),
+    "update_time" = CURRENT_TIMESTAMP
 WHERE
 	"id" = %s

apps/dataset/views/dataset.py

@@ -181,6 +181,7 @@ class Dataset(APIView):
         @swagger_auto_schema(operation_summary=_('Generate related'), operation_id=_('Generate related'),
                              manual_parameters=DataSetSerializers.Operate.get_request_params_api(),
                              request_body=GenerateRelatedSerializer.get_request_body_api(),
+                             responses=result.get_default_response(),
                              tags=[_('Knowledge Base')]
                              )
         @log(menu='document', operate="Generate related documents",

apps/function_lib/swagger_api/function_lib_api.py

@@ -195,6 +195,53 @@ class FunctionLibApi(ApiMixin):
                 }
             )
 
+        @staticmethod
+        def get_response_body_api():
+            return openapi.Schema(
+                type=openapi.TYPE_OBJECT,
+                required=['id', 'name', 'code', 'input_field_list', 'permission_type'],
+                properties={
+                    'id': openapi.Schema(type=openapi.TYPE_STRING, title="", description=_('ID')),
+
+                    'name': openapi.Schema(type=openapi.TYPE_STRING, title=_('function name'),
+                                           description=_('function name')),
+                    'desc': openapi.Schema(type=openapi.TYPE_STRING, title=_('function description'),
+                                           description=_('function description')),
+                    'code': openapi.Schema(type=openapi.TYPE_STRING, title=_('function content'),
+                                           description=_('function content')),
+                    'permission_type': openapi.Schema(type=openapi.TYPE_STRING, title=_('permission'),
+                                                      description=_('permission')),
+                    'is_active': openapi.Schema(type=openapi.TYPE_BOOLEAN, title=_('Is active'),
+                                                description=_('Is active')),
+                    'input_field_list': openapi.Schema(type=openapi.TYPE_ARRAY,
+                                                       description=_('Input variable list'),
+                                                       items=openapi.Schema(type=openapi.TYPE_OBJECT,
+                                                                            required=['name', 'is_required', 'source'],
+                                                                            properties={
+                                                                                'name': openapi.Schema(
+                                                                                    type=openapi.TYPE_STRING,
+                                                                                    title=_('variable name'),
+                                                                                    description=_('variable name')),
+                                                                                'is_required': openapi.Schema(
+                                                                                    type=openapi.TYPE_BOOLEAN,
+                                                                                    title=_('required'),
+                                                                                    description=_('required')),
+                                                                                'type': openapi.Schema(
+                                                                                    type=openapi.TYPE_STRING,
+                                                                                    title=_('type'),
+                                                                                    description=_(
+                                                                                        'Field type string|int|dict|array|float')
+                                                                                ),
+                                                                                'source': openapi.Schema(
+                                                                                    type=openapi.TYPE_STRING,
+                                                                                    title=_('source'),
+                                                                                    description=_(
+                                                                                        'The source only supports custom|reference')),
+
+                                                                            }))
+                }
+            )
+
     class Export(ApiMixin):
         @staticmethod
         def get_request_params_api():

apps/function_lib/views/function_lib_views.py

@@ -44,6 +44,7 @@ class FunctionLibView(APIView):
     @swagger_auto_schema(operation_summary=_('Create function'),
                          operation_id=_('Create function'),
                          request_body=FunctionLibApi.Create.get_request_body_api(),
+                         responses=result.get_api_response(FunctionLibApi.Create.get_response_body_api()),
                          tags=[_('Function')])
     @has_permissions(RoleConstants.ADMIN, RoleConstants.USER)
     @log(menu='Function', operate="Create function",
@@ -58,6 +59,7 @@ class FunctionLibView(APIView):
         @swagger_auto_schema(operation_summary=_('Debug function'),
                              operation_id=_('Debug function'),
                              request_body=FunctionLibApi.Debug.get_request_body_api(),
+                             responses=result.get_default_response(),
                              tags=[_('Function')])
         @has_permissions(RoleConstants.ADMIN, RoleConstants.USER)
         def post(self, request: Request):
@@ -72,6 +74,7 @@ class FunctionLibView(APIView):
         @swagger_auto_schema(operation_summary=_('Update function'),
                              operation_id=_('Update function'),
                              request_body=FunctionLibApi.Edit.get_request_body_api(),
+                             responses=result.get_api_response(FunctionLibApi.Edit.get_request_body_api()),
                              tags=[_('Function')])
         @has_permissions(RoleConstants.ADMIN, RoleConstants.USER)
         @log(menu='Function', operate="Update function",
@@ -84,6 +87,7 @@ class FunctionLibView(APIView):
         @action(methods=['DELETE'], detail=False)
         @swagger_auto_schema(operation_summary=_('Delete function'),
                              operation_id=_('Delete function'),
+                             responses=result.get_default_response(),
                              tags=[_('Function')])
         @has_permissions(RoleConstants.ADMIN, RoleConstants.USER)
         @log(menu='Function', operate="Delete function",

apps/function_lib/views/py_lint.py

@@ -26,6 +26,7 @@ class PyLintView(APIView):
     @swagger_auto_schema(operation_summary=_('Check code'),
                          operation_id=_('Check code'),
                          request_body=PyLintApi.get_request_body_api(),
+                         responses=result.get_api_response(PyLintApi.get_request_body_api()),
                          tags=[_('Function')])
     @has_permissions(RoleConstants.ADMIN, RoleConstants.USER)
     def post(self, request: Request):

apps/locales/en_US/LC_MESSAGES/django.po

@@ -7491,3 +7491,12 @@ msgstr ""
 
 msgid "Generate related"
 msgstr ""
+
+msgid "Obtain graphical captcha"
+msgstr ""
+
+msgid "Captcha code error or expiration"
+msgstr ""
+
+msgid "captcha"
+msgstr ""

apps/locales/zh_CN/LC_MESSAGES/django.po

@@ -4536,7 +4536,7 @@ msgstr "修改知识库信息"
 #: community/apps/dataset/views/document.py:463
 #: community/apps/dataset/views/document.py:464
 msgid "Get the knowledge base paginated list"
-msgstr "获取知识库分页列表"
+msgstr "获取知识库文档分页列表"
 
 #: community/apps/dataset/views/document.py:31
 #: community/apps/dataset/views/document.py:32
@@ -7654,3 +7654,12 @@ msgstr "字段: {name} 未设置值"
 
 msgid "Generate related"
 msgstr "生成问题"
+
+msgid "Obtain graphical captcha"
+msgstr "获取图形验证码"
+
+msgid "Captcha code error or expiration"
+msgstr "验证码错误或过期"
+
+msgid "captcha"
+msgstr "验证码"

apps/locales/zh_Hant/LC_MESSAGES/django.po

@@ -4545,7 +4545,7 @@ msgstr "修改知識庫信息"
 #: community/apps/dataset/views/document.py:463
 #: community/apps/dataset/views/document.py:464
 msgid "Get the knowledge base paginated list"
-msgstr "獲取知識庫分頁列表"
+msgstr "獲取知識庫文档分頁列表"
 
 #: community/apps/dataset/views/document.py:31
 #: community/apps/dataset/views/document.py:32
@@ -7664,3 +7664,12 @@ msgstr "欄位: {name} 未設定值"
 
 msgid "Generate related"
 msgstr "生成問題"
+
+msgid "Obtain graphical captcha"
+msgstr "獲取圖形驗證碼"
+
+msgid "Captcha code error or expiration"
+msgstr "驗證碼錯誤或過期"
+
+msgid "captcha"
+msgstr "驗證碼"

apps/setting/models_provider/base_model_provider.py

@@ -106,7 +106,10 @@ class MaxKBBaseModel(ABC):
         optional_params = {}
         for key, value in model_kwargs.items():
             if key not in ['model_id', 'use_local', 'streaming', 'show_ref_label']:
-                optional_params[key] = value
+                if key == 'extra_body' and isinstance(value, dict):
+                    optional_params = {**optional_params, **value}
+                else:
+                    optional_params[key] = value
         return optional_params
 
 

apps/setting/models_provider/constants/model_provider_constants.py

@@ -19,6 +19,8 @@ from setting.models_provider.impl.kimi_model_provider.kimi_model_provider import
 from setting.models_provider.impl.ollama_model_provider.ollama_model_provider import OllamaModelProvider
 from setting.models_provider.impl.openai_model_provider.openai_model_provider import OpenAIModelProvider
 from setting.models_provider.impl.qwen_model_provider.qwen_model_provider import QwenModelProvider
+from setting.models_provider.impl.regolo_model_provider.regolo_model_provider import \
+    RegoloModelProvider
 from setting.models_provider.impl.siliconCloud_model_provider.siliconCloud_model_provider import \
     SiliconCloudModelProvider
 from setting.models_provider.impl.tencent_cloud_model_provider.tencent_cloud_model_provider import \
@@ -55,3 +57,4 @@ class ModelProvideConstants(Enum):
     aliyun_bai_lian_model_provider = AliyunBaiLianModelProvider()
     model_anthropic_provider = AnthropicModelProvider()
     model_siliconCloud_provider = SiliconCloudModelProvider()
+    model_regolo_provider = RegoloModelProvider()

apps/setting/models_provider/impl/aliyun_bai_lian_model_provider/aliyun_bai_lian_model_provider.py

@@ -51,6 +51,23 @@ model_info_list = [ModelInfo('gte-rerank',
                              _("Universal text vector is Tongyi Lab's multi-language text unified vector model based on the LLM base. It provides high-level vector services for multiple mainstream languages around the world and helps developers quickly convert text data into high-quality vector data."),
                              ModelTypeConst.EMBEDDING, aliyun_bai_lian_embedding_model_credential,
                              AliyunBaiLianEmbedding),
+                   ModelInfo('qwen3-0.6b', '', ModelTypeConst.LLM, aliyun_bai_lian_llm_model_credential,
+                             BaiLianChatModel),
+                   ModelInfo('qwen3-1.7b', '', ModelTypeConst.LLM, aliyun_bai_lian_llm_model_credential,
+                             BaiLianChatModel),
+                   ModelInfo('qwen3-4b', '', ModelTypeConst.LLM, aliyun_bai_lian_llm_model_credential,
+                             BaiLianChatModel),
+                   ModelInfo('qwen3-8b', '', ModelTypeConst.LLM, aliyun_bai_lian_llm_model_credential,
+                             BaiLianChatModel),
+                   ModelInfo('qwen3-14b', '', ModelTypeConst.LLM, aliyun_bai_lian_llm_model_credential,
+                             BaiLianChatModel),
+                   ModelInfo('qwen3-32b', '', ModelTypeConst.LLM, aliyun_bai_lian_llm_model_credential,
+                             BaiLianChatModel),
+                   ModelInfo('qwen3-30b-a3b', '', ModelTypeConst.LLM, aliyun_bai_lian_llm_model_credential,
+                             BaiLianChatModel),
+                   ModelInfo('qwen3-235b-a22b', '', ModelTypeConst.LLM, aliyun_bai_lian_llm_model_credential,
+                             BaiLianChatModel),
+
                    ModelInfo('qwen-turbo', '', ModelTypeConst.LLM, aliyun_bai_lian_llm_model_credential,
                              BaiLianChatModel),
                    ModelInfo('qwen-plus', '', ModelTypeConst.LLM, aliyun_bai_lian_llm_model_credential,

apps/setting/models_provider/impl/aliyun_bai_lian_model_provider/credential/llm.py

@@ -30,6 +30,29 @@ class BaiLianLLMModelParams(BaseForm):
         precision=0)
 
 
+class BaiLianLLMStreamModelParams(BaseForm):
+    temperature = forms.SliderField(TooltipLabel(_('Temperature'),
+                                                 _('Higher values make the output more random, while lower values make it more focused and deterministic')),
+                                    required=True, default_value=0.7,
+                                    _min=0.1,
+                                    _max=1.0,
+                                    _step=0.01,
+                                    precision=2)
+
+    max_tokens = forms.SliderField(
+        TooltipLabel(_('Output the maximum Tokens'),
+                     _('Specify the maximum number of tokens that the model can generate')),
+        required=True, default_value=800,
+        _min=1,
+        _max=100000,
+        _step=1,
+        precision=0)
+
+    stream = forms.SwitchField(label=TooltipLabel(_('Is the answer in streaming mode'),
+                                                  _('Is the answer in streaming mode')),
+                               required=True, default_value=True)
+
+
 class BaiLianLLMModelCredential(BaseForm, BaseModelCredential):
 
     def is_valid(self, model_type: str, model_name, model_credential: Dict[str, object], model_params, provider,
@@ -47,7 +70,11 @@ class BaiLianLLMModelCredential(BaseForm, BaseModelCredential):
                     return False
         try:
             model = provider.get_model(model_type, model_name, model_credential, **model_params)
-            model.invoke([HumanMessage(content=gettext('Hello'))])
+            if model_params.get('stream'):
+                for res in model.stream([HumanMessage(content=gettext('Hello'))]):
+                    pass
+            else:
+                model.invoke([HumanMessage(content=gettext('Hello'))])
         except Exception as e:
             traceback.print_exc()
             if isinstance(e, AppApiException):
@@ -68,4 +95,6 @@ class BaiLianLLMModelCredential(BaseForm, BaseModelCredential):
     api_key = forms.PasswordInputField('API Key', required=True)
 
     def get_model_params_setting_form(self, model_name):
+        if 'qwen3' in model_name:
+            return BaiLianLLMStreamModelParams()
         return BaiLianLLMModelParams()

apps/setting/models_provider/impl/aliyun_bai_lian_model_provider/model/image.py

@@ -15,9 +15,8 @@ class QwenVLChatModel(MaxKBBaseModel, BaseChatOpenAI):
             model_name=model_name,
             openai_api_key=model_credential.get('api_key'),
             openai_api_base='https://dashscope.aliyuncs.com/compatible-mode/v1',
-            # stream_options={"include_usage": True},
             streaming=True,
             stream_usage=True,
-            **optional_params,
+            extra_body=optional_params
         )
         return chat_tong_yi

apps/setting/models_provider/impl/aliyun_bai_lian_model_provider/model/llm.py

@@ -20,5 +20,5 @@ class BaiLianChatModel(MaxKBBaseModel, BaseChatOpenAI):
             model=model_name,
             openai_api_base=model_credential.get('api_base'),
             openai_api_key=model_credential.get('api_key'),
-            **optional_params
+            extra_body=optional_params
         )

apps/setting/models_provider/impl/aws_bedrock_model_provider/model/llm.py

@@ -1,10 +1,12 @@
 import os
 import re
-from typing import Dict
+from typing import Dict, List
 
 from botocore.config import Config
 from langchain_community.chat_models import BedrockChat
+from langchain_core.messages import BaseMessage, get_buffer_string
 
+from common.config.tokenizer_manage_config import TokenizerManage
 from setting.models_provider.base_model_provider import MaxKBBaseModel
 
 
@@ -72,6 +74,20 @@ class BedrockModel(MaxKBBaseModel, BedrockChat):
             config=config
         )
 
+    def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:
+        try:
+            return super().get_num_tokens_from_messages(messages)
+        except Exception as e:
+            tokenizer = TokenizerManage.get_tokenizer()
+            return sum([len(tokenizer.encode(get_buffer_string([m]))) for m in messages])
+
+    def get_num_tokens(self, text: str) -> int:
+        try:
+            return super().get_num_tokens(text)
+        except Exception as e:
+            tokenizer = TokenizerManage.get_tokenizer()
+            return len(tokenizer.encode(text))
+
 
 def _update_aws_credentials(profile_name, access_key_id, secret_access_key):
     credentials_path = os.path.join(os.path.expanduser("~"), ".aws", "credentials")

apps/setting/models_provider/impl/base_chat_open_ai.py

@@ -1,15 +1,16 @@
 # coding=utf-8
-import warnings
+from typing import Dict, Optional, Any, Iterator, cast, Union, Sequence, Callable, Mapping
-from typing import List, Dict, Optional, Any, Iterator, cast, Type, Union
 
-import openai
-from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models import LanguageModelInput
-from langchain_core.messages import BaseMessage, get_buffer_string, BaseMessageChunk, AIMessageChunk
+from langchain_core.messages import BaseMessage, get_buffer_string, BaseMessageChunk, HumanMessageChunk, AIMessageChunk, \
-from langchain_core.outputs import ChatGenerationChunk, ChatGeneration
+    SystemMessageChunk, FunctionMessageChunk, ChatMessageChunk
+from langchain_core.messages.ai import UsageMetadata
+from langchain_core.messages.tool import tool_call_chunk, ToolMessageChunk
+from langchain_core.outputs import ChatGenerationChunk
 from langchain_core.runnables import RunnableConfig, ensure_config
-from langchain_core.utils.pydantic import is_basemodel_subclass
+from langchain_core.tools import BaseTool
 from langchain_openai import ChatOpenAI
+from langchain_openai.chat_models.base import _create_usage_metadata
 
 from common.config.tokenizer_manage_config import TokenizerManage
 
@@ -19,6 +20,65 @@ def custom_get_token_ids(text: str):
     return tokenizer.encode(text)
 
 
+def _convert_delta_to_message_chunk(
+        _dict: Mapping[str, Any], default_class: type[BaseMessageChunk]
+) -> BaseMessageChunk:
+    id_ = _dict.get("id")
+    role = cast(str, _dict.get("role"))
+    content = cast(str, _dict.get("content") or "")
+    additional_kwargs: dict = {}
+    if 'reasoning_content' in _dict:
+        additional_kwargs['reasoning_content'] = _dict.get('reasoning_content')
+    if _dict.get("function_call"):
+        function_call = dict(_dict["function_call"])
+        if "name" in function_call and function_call["name"] is None:
+            function_call["name"] = ""
+        additional_kwargs["function_call"] = function_call
+    tool_call_chunks = []
+    if raw_tool_calls := _dict.get("tool_calls"):
+        additional_kwargs["tool_calls"] = raw_tool_calls
+        try:
+            tool_call_chunks = [
+                tool_call_chunk(
+                    name=rtc["function"].get("name"),
+                    args=rtc["function"].get("arguments"),
+                    id=rtc.get("id"),
+                    index=rtc["index"],
+                )
+                for rtc in raw_tool_calls
+            ]
+        except KeyError:
+            pass
+
+    if role == "user" or default_class == HumanMessageChunk:
+        return HumanMessageChunk(content=content, id=id_)
+    elif role == "assistant" or default_class == AIMessageChunk:
+        return AIMessageChunk(
+            content=content,
+            additional_kwargs=additional_kwargs,
+            id=id_,
+            tool_call_chunks=tool_call_chunks,  # type: ignore[arg-type]
+        )
+    elif role in ("system", "developer") or default_class == SystemMessageChunk:
+        if role == "developer":
+            additional_kwargs = {"__openai_role__": "developer"}
+        else:
+            additional_kwargs = {}
+        return SystemMessageChunk(
+            content=content, id=id_, additional_kwargs=additional_kwargs
+        )
+    elif role == "function" or default_class == FunctionMessageChunk:
+        return FunctionMessageChunk(content=content, name=_dict["name"], id=id_)
+    elif role == "tool" or default_class == ToolMessageChunk:
+        return ToolMessageChunk(
+            content=content, tool_call_id=_dict["tool_call_id"], id=id_
+        )
+    elif role or default_class == ChatMessageChunk:
+        return ChatMessageChunk(content=content, role=role, id=id_)
+    else:
+        return default_class(content=content, id=id_)  # type: ignore
+
+
 class BaseChatOpenAI(ChatOpenAI):
     usage_metadata: dict = {}
     custom_get_token_ids = custom_get_token_ids
@@ -26,7 +86,13 @@ class BaseChatOpenAI(ChatOpenAI):
     def get_last_generation_info(self) -> Optional[Dict[str, Any]]:
         return self.usage_metadata
 
-    def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:
+    def get_num_tokens_from_messages(
+            self,
+            messages: list[BaseMessage],
+            tools: Optional[
+                Sequence[Union[dict[str, Any], type, Callable, BaseTool]]
+            ] = None,
+    ) -> int:
         if self.usage_metadata is None or self.usage_metadata == {}:
             try:
                 return super().get_num_tokens_from_messages(messages)
@@ -44,114 +110,77 @@ class BaseChatOpenAI(ChatOpenAI):
                 return len(tokenizer.encode(text))
         return self.get_last_generation_info().get('output_tokens', 0)
 
-    def _stream(
+    def _stream(self, *args: Any, **kwargs: Any) -> Iterator[ChatGenerationChunk]:
+        kwargs['stream_usage'] = True
+        for chunk in super()._stream(*args, **kwargs):
+            if chunk.message.usage_metadata is not None:
+                self.usage_metadata = chunk.message.usage_metadata
+            yield chunk
+
+    def _convert_chunk_to_generation_chunk(
             self,
-            messages: List[BaseMessage],
+            chunk: dict,
-            stop: Optional[List[str]] = None,
+            default_chunk_class: type,
-            run_manager: Optional[CallbackManagerForLLMRun] = None,
+            base_generation_info: Optional[dict],
-            **kwargs: Any,
+    ) -> Optional[ChatGenerationChunk]:
-    ) -> Iterator[ChatGenerationChunk]:
+        if chunk.get("type") == "content.delta":  # from beta.chat.completions.stream
-        kwargs["stream"] = True
+            return None
-        kwargs["stream_options"] = {"include_usage": True}
+        token_usage = chunk.get("usage")
-        """Set default stream_options."""
+        choices = (
-        stream_usage = self._should_stream_usage(kwargs.get('stream_usage'), **kwargs)
+                chunk.get("choices", [])
-        # Note: stream_options is not a valid parameter for Azure OpenAI.
+                # from beta.chat.completions.stream
-        # To support users proxying Azure through ChatOpenAI, here we only specify
+                or chunk.get("chunk", {}).get("choices", [])
-        # stream_options if include_usage is set to True.
+        )
-        # See https://learn.microsoft.com/en-us/azure/ai-services/openai/whats-new
-        # for release notes.
-        if stream_usage:
-            kwargs["stream_options"] = {"include_usage": stream_usage}
 
-        payload = self._get_request_payload(messages, stop=stop, **kwargs)
+        usage_metadata: Optional[UsageMetadata] = (
-        default_chunk_class: Type[BaseMessageChunk] = AIMessageChunk
+            _create_usage_metadata(token_usage) if token_usage and token_usage.get("prompt_tokens") else None
-        base_generation_info = {}
+        )
-
+        if len(choices) == 0:
-        if "response_format" in payload and is_basemodel_subclass(
+            # logprobs is implicitly None
-                payload["response_format"]
+            generation_chunk = ChatGenerationChunk(
-        ):
+                message=default_chunk_class(content="", usage_metadata=usage_metadata)
-            # TODO: Add support for streaming with Pydantic response_format.
-            warnings.warn("Streaming with Pydantic response_format not yet supported.")
-            chat_result = self._generate(
-                messages, stop, run_manager=run_manager, **kwargs
             )
-            msg = chat_result.generations[0].message
+            return generation_chunk
-            yield ChatGenerationChunk(
-                message=AIMessageChunk(
-                    **msg.dict(exclude={"type", "additional_kwargs"}),
-                    # preserve the "parsed" Pydantic object without converting to dict
-                    additional_kwargs=msg.additional_kwargs,
-                ),
-                generation_info=chat_result.generations[0].generation_info,
-            )
-            return
-        if self.include_response_headers:
-            raw_response = self.client.with_raw_response.create(**payload)
-            response = raw_response.parse()
-            base_generation_info = {"headers": dict(raw_response.headers)}
-        else:
-            response = self.client.create(**payload)
-        with response:
-            is_first_chunk = True
-            for chunk in response:
-                if not isinstance(chunk, dict):
-                    chunk = chunk.model_dump()
 
-                generation_chunk = super()._convert_chunk_to_generation_chunk(
+        choice = choices[0]
-                    chunk,
+        if choice["delta"] is None:
-                    default_chunk_class,
+            return None
-                    base_generation_info if is_first_chunk else {},
-                )
-                if generation_chunk is None:
-                    continue
 
-                # custom code
+        message_chunk = _convert_delta_to_message_chunk(
-                if len(chunk['choices']) > 0 and 'reasoning_content' in chunk['choices'][0]['delta']:
+            choice["delta"], default_chunk_class
-                    generation_chunk.message.additional_kwargs["reasoning_content"] = chunk['choices'][0]['delta'][
+        )
-                        'reasoning_content']
+        generation_info = {**base_generation_info} if base_generation_info else {}
 
-                default_chunk_class = generation_chunk.message.__class__
+        if finish_reason := choice.get("finish_reason"):
-                logprobs = (generation_chunk.generation_info or {}).get("logprobs")
+            generation_info["finish_reason"] = finish_reason
-                if run_manager:
+            if model_name := chunk.get("model"):
-                    run_manager.on_llm_new_token(
+                generation_info["model_name"] = model_name
-                        generation_chunk.text, chunk=generation_chunk, logprobs=logprobs
+            if system_fingerprint := chunk.get("system_fingerprint"):
-                    )
+                generation_info["system_fingerprint"] = system_fingerprint
-                is_first_chunk = False
-                # custom code
-                if generation_chunk.message.usage_metadata is not None:
-                    self.usage_metadata = generation_chunk.message.usage_metadata
-                yield generation_chunk
 
-    def _create_chat_result(self,
+        logprobs = choice.get("logprobs")
-                            response: Union[dict, openai.BaseModel],
+        if logprobs:
-                            generation_info: Optional[Dict] = None):
+            generation_info["logprobs"] = logprobs
-        result = super()._create_chat_result(response, generation_info)
+
-        try:
+        if usage_metadata and isinstance(message_chunk, AIMessageChunk):
-            reasoning_content = ''
+            message_chunk.usage_metadata = usage_metadata
-            reasoning_content_enable = False
+
-            for res in response.choices:
+        generation_chunk = ChatGenerationChunk(
-                if 'reasoning_content' in res.message.model_extra:
+            message=message_chunk, generation_info=generation_info or None
-                    reasoning_content_enable = True
+        )
-                    _reasoning_content = res.message.model_extra.get('reasoning_content')
+        return generation_chunk
-                    if _reasoning_content is not None:
-                        reasoning_content += _reasoning_content
-            if reasoning_content_enable:
-                result.llm_output['reasoning_content'] = reasoning_content
-        except Exception as e:
-            pass
-        return result
 
     def invoke(
             self,
             input: LanguageModelInput,
             config: Optional[RunnableConfig] = None,
             *,
-            stop: Optional[List[str]] = None,
+            stop: Optional[list[str]] = None,
             **kwargs: Any,
     ) -> BaseMessage:
         config = ensure_config(config)
         chat_result = cast(
-            ChatGeneration,
+            "ChatGeneration",
             self.generate_prompt(
                 [self._convert_input(input)],
                 stop=stop,
@@ -162,7 +191,9 @@ class BaseChatOpenAI(ChatOpenAI):
                 run_id=config.pop("run_id", None),
                 **kwargs,
             ).generations[0][0],
+
         ).message
+
         self.usage_metadata = chat_result.response_metadata[
             'token_usage'] if 'token_usage' in chat_result.response_metadata else chat_result.usage_metadata
         return chat_result

apps/setting/models_provider/impl/deepseek_model_provider/model/llm.py

@@ -26,6 +26,6 @@ class DeepSeekChatModel(MaxKBBaseModel, BaseChatOpenAI):
             model=model_name,
             openai_api_base='https://api.deepseek.com',
             openai_api_key=model_credential.get('api_key'),
-            **optional_params
+            extra_body=optional_params
         )
         return deepseek_chat_open_ai

apps/setting/models_provider/impl/gemini_model_provider/model/llm.py

@@ -13,7 +13,7 @@ from google.ai.generativelanguage_v1beta.types import (
     Tool as GoogleTool,
 )
 from langchain_core.callbacks import CallbackManagerForLLMRun
-from langchain_core.messages import BaseMessage
+from langchain_core.messages import BaseMessage, get_buffer_string
 from langchain_core.outputs import ChatGenerationChunk
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_google_genai._function_utils import _ToolConfigDict, _ToolDict
@@ -22,6 +22,8 @@ from langchain_google_genai.chat_models import _chat_with_retry, _response_to_re
 from langchain_google_genai._common import (
     SafetySettingDict,
 )
+
+from common.config.tokenizer_manage_config import TokenizerManage
 from setting.models_provider.base_model_provider import MaxKBBaseModel
 
 
@@ -46,10 +48,18 @@ class GeminiChatModel(MaxKBBaseModel, ChatGoogleGenerativeAI):
         return self.__dict__.get('_last_generation_info')
 
     def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:
-        return self.get_last_generation_info().get('input_tokens', 0)
+        try:
+            return self.get_last_generation_info().get('input_tokens', 0)
+        except Exception as e:
+            tokenizer = TokenizerManage.get_tokenizer()
+            return sum([len(tokenizer.encode(get_buffer_string([m]))) for m in messages])
 
     def get_num_tokens(self, text: str) -> int:
-        return self.get_last_generation_info().get('output_tokens', 0)
+        try:
+            return self.get_last_generation_info().get('output_tokens', 0)
+        except Exception as e:
+            tokenizer = TokenizerManage.get_tokenizer()
+            return len(tokenizer.encode(text))
 
     def _stream(
             self,

apps/setting/models_provider/impl/kimi_model_provider/model/llm.py

@@ -21,11 +21,10 @@ class KimiChatModel(MaxKBBaseModel, BaseChatOpenAI):
     @staticmethod
     def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
         optional_params = MaxKBBaseModel.filter_optional_params(model_kwargs)
-
         kimi_chat_open_ai = KimiChatModel(
             openai_api_base=model_credential['api_base'],
             openai_api_key=model_credential['api_key'],
             model_name=model_name,
-            **optional_params
+            extra_body=optional_params,
         )
         return kimi_chat_open_ai

apps/setting/models_provider/impl/ollama_model_provider/credential/llm.py

@@ -25,7 +25,7 @@ class OllamaLLMModelParams(BaseForm):
                                     _step=0.01,
                                     precision=2)
 
-    max_tokens = forms.SliderField(
+    num_predict = forms.SliderField(
         TooltipLabel(_('Output the maximum Tokens'),
                      _('Specify the maximum number of tokens that the model can generate')),
         required=True, default_value=1024,

apps/setting/models_provider/impl/ollama_model_provider/model/image.py

@@ -28,5 +28,5 @@ class OllamaImage(MaxKBBaseModel, BaseChatOpenAI):
             # stream_options={"include_usage": True},
             streaming=True,
             stream_usage=True,
-            **optional_params,
+            extra_body=optional_params
         )

apps/setting/models_provider/impl/openai_model_provider/model/image.py

@@ -16,5 +16,5 @@ class OpenAIImage(MaxKBBaseModel, BaseChatOpenAI):
             # stream_options={"include_usage": True},
             streaming=True,
             stream_usage=True,
-            **optional_params,
+            extra_body=optional_params
         )

apps/setting/models_provider/impl/openai_model_provider/model/llm.py

@@ -9,7 +9,6 @@
 from typing import List, Dict
 
 from langchain_core.messages import BaseMessage, get_buffer_string
-from langchain_openai.chat_models import ChatOpenAI
 
 from common.config.tokenizer_manage_config import TokenizerManage
 from setting.models_provider.base_model_provider import MaxKBBaseModel
@@ -35,9 +34,9 @@ class OpenAIChatModel(MaxKBBaseModel, BaseChatOpenAI):
             streaming = False
         azure_chat_open_ai = OpenAIChatModel(
             model=model_name,
-            openai_api_base=model_credential.get('api_base'),
+            base_url=model_credential.get('api_base'),
-            openai_api_key=model_credential.get('api_key'),
+            api_key=model_credential.get('api_key'),
-            **optional_params,
+            extra_body=optional_params,
             streaming=streaming,
             custom_get_token_ids=custom_get_token_ids
         )

apps/setting/models_provider/impl/qwen_model_provider/model/image.py

@@ -18,9 +18,8 @@ class QwenVLChatModel(MaxKBBaseModel, BaseChatOpenAI):
             model_name=model_name,
             openai_api_key=model_credential.get('api_key'),
             openai_api_base='https://dashscope.aliyuncs.com/compatible-mode/v1',
-            # stream_options={"include_usage": True},
             streaming=True,
             stream_usage=True,
-            **optional_params,
+            extra_body=optional_params
         )
         return chat_tong_yi

apps/setting/models_provider/impl/qwen_model_provider/model/llm.py

@@ -26,6 +26,6 @@ class QwenChatModel(MaxKBBaseModel, BaseChatOpenAI):
             openai_api_base='https://dashscope.aliyuncs.com/compatible-mode/v1',
             streaming=True,
             stream_usage=True,
-            **optional_params,
+            extra_body=optional_params
         )
         return chat_tong_yi

apps/setting/models_provider/impl/regolo_model_provider/__init__.py

@@ -0,0 +1,8 @@
+# coding=utf-8
+"""
+    @project: maxkb
+    @Author：虎
+    @file： __init__.py.py
+    @date：2024/3/28 16:25
+    @desc:
+"""

apps/setting/models_provider/impl/regolo_model_provider/credential/embedding.py

@@ -0,0 +1,52 @@
+# coding=utf-8
+"""
+    @project: MaxKB
+    @Author：虎
+    @file： embedding.py
+    @date：2024/7/12 16:45
+    @desc:
+"""
+import traceback
+from typing import Dict
+
+from django.utils.translation import gettext as _
+
+from common import forms
+from common.exception.app_exception import AppApiException
+from common.forms import BaseForm
+from setting.models_provider.base_model_provider import BaseModelCredential, ValidCode
+
+
+class RegoloEmbeddingCredential(BaseForm, BaseModelCredential):
+    def is_valid(self, model_type: str, model_name, model_credential: Dict[str, object], model_params, provider,
+                 raise_exception=True):
+        model_type_list = provider.get_model_type_list()
+        if not any(list(filter(lambda mt: mt.get('value') == model_type, model_type_list))):
+            raise AppApiException(ValidCode.valid_error.value,
+                                  _('{model_type} Model type is not supported').format(model_type=model_type))
+
+        for key in ['api_key']:
+            if key not in model_credential:
+                if raise_exception:
+                    raise AppApiException(ValidCode.valid_error.value, _('{key}  is required').format(key=key))
+                else:
+                    return False
+        try:
+            model = provider.get_model(model_type, model_name, model_credential)
+            model.embed_query(_('Hello'))
+        except Exception as e:
+            traceback.print_exc()
+            if isinstance(e, AppApiException):
+                raise e
+            if raise_exception:
+                raise AppApiException(ValidCode.valid_error.value,
+                                      _('Verification failed, please check whether the parameters are correct: {error}').format(
+                                          error=str(e)))
+            else:
+                return False
+        return True
+
+    def encryption_dict(self, model: Dict[str, object]):
+        return {**model, 'api_key': super().encryption(model.get('api_key', ''))}
+
+    api_key = forms.PasswordInputField('API Key', required=True)

apps/setting/models_provider/impl/regolo_model_provider/credential/image.py

@@ -0,0 +1,74 @@
+# coding=utf-8
+import base64
+import os
+import traceback
+from typing import Dict
+
+from langchain_core.messages import HumanMessage
+
+from common import forms
+from common.exception.app_exception import AppApiException
+from common.forms import BaseForm, TooltipLabel
+from setting.models_provider.base_model_provider import BaseModelCredential, ValidCode
+from django.utils.translation import gettext_lazy as _, gettext
+
+
+class RegoloImageModelParams(BaseForm):
+    temperature = forms.SliderField(TooltipLabel(_('Temperature'),
+                                                 _('Higher values make the output more random, while lower values make it more focused and deterministic')),
+                                    required=True, default_value=0.7,
+                                    _min=0.1,
+                                    _max=1.0,
+                                    _step=0.01,
+                                    precision=2)
+
+    max_tokens = forms.SliderField(
+        TooltipLabel(_('Output the maximum Tokens'),
+                     _('Specify the maximum number of tokens that the model can generate')),
+        required=True, default_value=800,
+        _min=1,
+        _max=100000,
+        _step=1,
+        precision=0)
+
+
+class RegoloImageModelCredential(BaseForm, BaseModelCredential):
+    api_base = forms.TextInputField('API URL', required=True)
+    api_key = forms.PasswordInputField('API Key', required=True)
+
+    def is_valid(self, model_type: str, model_name, model_credential: Dict[str, object], model_params, provider,
+                 raise_exception=False):
+        model_type_list = provider.get_model_type_list()
+        if not any(list(filter(lambda mt: mt.get('value') == model_type, model_type_list))):
+            raise AppApiException(ValidCode.valid_error.value,
+                                  gettext('{model_type} Model type is not supported').format(model_type=model_type))
+
+        for key in ['api_key']:
+            if key not in model_credential:
+                if raise_exception:
+                    raise AppApiException(ValidCode.valid_error.value, gettext('{key}  is required').format(key=key))
+                else:
+                    return False
+        try:
+            model = provider.get_model(model_type, model_name, model_credential, **model_params)
+            res = model.stream([HumanMessage(content=[{"type": "text", "text": gettext('Hello')}])])
+            for chunk in res:
+                print(chunk)
+        except Exception as e:
+            traceback.print_exc()
+            if isinstance(e, AppApiException):
+                raise e
+            if raise_exception:
+                raise AppApiException(ValidCode.valid_error.value,
+                                      gettext(
+                                          'Verification failed, please check whether the parameters are correct: {error}').format(
+                                          error=str(e)))
+            else:
+                return False
+        return True
+
+    def encryption_dict(self, model: Dict[str, object]):
+        return {**model, 'api_key': super().encryption(model.get('api_key', ''))}
+
+    def get_model_params_setting_form(self, model_name):
+        return RegoloImageModelParams()

apps/setting/models_provider/impl/regolo_model_provider/credential/llm.py

@@ -0,0 +1,78 @@
+# coding=utf-8
+"""
+    @project: MaxKB
+    @Author：虎
+    @file： llm.py
+    @date：2024/7/11 18:32
+    @desc:
+"""
+import traceback
+from typing import Dict
+
+from django.utils.translation import gettext_lazy as _, gettext
+from langchain_core.messages import HumanMessage
+
+from common import forms
+from common.exception.app_exception import AppApiException
+from common.forms import BaseForm, TooltipLabel
+from setting.models_provider.base_model_provider import BaseModelCredential, ValidCode
+
+
+class RegoloLLMModelParams(BaseForm):
+    temperature = forms.SliderField(TooltipLabel(_('Temperature'),
+                                                 _('Higher values make the output more random, while lower values make it more focused and deterministic')),
+                                    required=True, default_value=0.7,
+                                    _min=0.1,
+                                    _max=1.0,
+                                    _step=0.01,
+                                    precision=2)
+
+    max_tokens = forms.SliderField(
+        TooltipLabel(_('Output the maximum Tokens'),
+                     _('Specify the maximum number of tokens that the model can generate')),
+        required=True, default_value=800,
+        _min=1,
+        _max=100000,
+        _step=1,
+        precision=0)
+
+
+class RegoloLLMModelCredential(BaseForm, BaseModelCredential):
+
+    def is_valid(self, model_type: str, model_name, model_credential: Dict[str, object], model_params, provider,
+                 raise_exception=False):
+        model_type_list = provider.get_model_type_list()
+        if not any(list(filter(lambda mt: mt.get('value') == model_type, model_type_list))):
+            raise AppApiException(ValidCode.valid_error.value,
+                                  gettext('{model_type} Model type is not supported').format(model_type=model_type))
+
+        for key in ['api_key']:
+            if key not in model_credential:
+                if raise_exception:
+                    raise AppApiException(ValidCode.valid_error.value, gettext('{key}  is required').format(key=key))
+                else:
+                    return False
+        try:
+
+            model = provider.get_model(model_type, model_name, model_credential, **model_params)
+            model.invoke([HumanMessage(content=gettext('Hello'))])
+        except Exception as e:
+            traceback.print_exc()
+            if isinstance(e, AppApiException):
+                raise e
+            if raise_exception:
+                raise AppApiException(ValidCode.valid_error.value,
+                                      gettext(
+                                          'Verification failed, please check whether the parameters are correct: {error}').format(
+                                          error=str(e)))
+            else:
+                return False
+        return True
+
+    def encryption_dict(self, model: Dict[str, object]):
+        return {**model, 'api_key': super().encryption(model.get('api_key', ''))}
+
+    api_key = forms.PasswordInputField('API Key', required=True)
+
+    def get_model_params_setting_form(self, model_name):
+        return RegoloLLMModelParams()

apps/setting/models_provider/impl/regolo_model_provider/credential/tti.py

@@ -0,0 +1,89 @@
+# coding=utf-8
+import traceback
+from typing import Dict
+
+from django.utils.translation import gettext_lazy as _, gettext
+
+from common import forms
+from common.exception.app_exception import AppApiException
+from common.forms import BaseForm, TooltipLabel
+from setting.models_provider.base_model_provider import BaseModelCredential, ValidCode
+
+
+class RegoloTTIModelParams(BaseForm):
+    size = forms.SingleSelect(
+        TooltipLabel(_('Image size'),
+                     _('The image generation endpoint allows you to create raw images based on text prompts. ')),
+        required=True,
+        default_value='1024x1024',
+        option_list=[
+            {'value': '1024x1024', 'label': '1024x1024'},
+            {'value': '1024x1792', 'label': '1024x1792'},
+            {'value': '1792x1024', 'label': '1792x1024'},
+        ],
+        text_field='label',
+        value_field='value'
+    )
+
+    quality = forms.SingleSelect(
+        TooltipLabel(_('Picture quality'), _('''       
+By default, images are produced in standard quality.
+        ''')),
+        required=True,
+        default_value='standard',
+        option_list=[
+            {'value': 'standard', 'label': 'standard'},
+            {'value': 'hd', 'label': 'hd'},
+        ],
+        text_field='label',
+        value_field='value'
+    )
+
+    n = forms.SliderField(
+        TooltipLabel(_('Number of pictures'),
+                     _('1 as default')),
+        required=True, default_value=1,
+        _min=1,
+        _max=10,
+        _step=1,
+        precision=0)
+
+
+class RegoloTextToImageModelCredential(BaseForm, BaseModelCredential):
+    api_key = forms.PasswordInputField('API Key', required=True)
+
+    def is_valid(self, model_type: str, model_name, model_credential: Dict[str, object], model_params, provider,
+                 raise_exception=False):
+        model_type_list = provider.get_model_type_list()
+        if not any(list(filter(lambda mt: mt.get('value') == model_type, model_type_list))):
+            raise AppApiException(ValidCode.valid_error.value,
+                                  gettext('{model_type} Model type is not supported').format(model_type=model_type))
+
+        for key in ['api_key']:
+            if key not in model_credential:
+                if raise_exception:
+                    raise AppApiException(ValidCode.valid_error.value, gettext('{key}  is required').format(key=key))
+                else:
+                    return False
+        try:
+            model = provider.get_model(model_type, model_name, model_credential, **model_params)
+            res = model.check_auth()
+            print(res)
+        except Exception as e:
+            traceback.print_exc()
+            if isinstance(e, AppApiException):
+                raise e
+            if raise_exception:
+                raise AppApiException(ValidCode.valid_error.value,
+                                      gettext(
+                                          'Verification failed, please check whether the parameters are correct: {error}').format(
+                                          error=str(e)))
+            else:
+                return False
+        return True
+
+    def encryption_dict(self, model: Dict[str, object]):
+        return {**model, 'api_key': super().encryption(model.get('api_key', ''))}
+
+    def get_model_params_setting_form(self, model_name):
+        return RegoloTTIModelParams()

apps/setting/models_provider/impl/regolo_model_provider/icon/regolo_icon_svg

@@ -0,0 +1,64 @@
+<?xml version="1.0" encoding="UTF-8" standalone="no"?>
+<svg
+   id="Livello_2"
+   data-name="Livello 2"
+   viewBox="0 0 104.4 104.38"
+   version="1.1"
+   sodipodi:docname="Regolo_logo_positive.svg"
+   width="100%" height="100%"
+   inkscape:version="1.4 (e7c3feb100, 2024-10-09)"
+   xmlns:inkscape="http://www.inkscape.org/namespaces/inkscape"
+   xmlns:sodipodi="http://sodipodi.sourceforge.net/DTD/sodipodi-0.dtd"
+   xmlns="http://www.w3.org/2000/svg"
+   xmlns:svg="http://www.w3.org/2000/svg">
+  <sodipodi:namedview
+     id="namedview13"
+     pagecolor="#ffffff"
+     bordercolor="#666666"
+     borderopacity="1.0"
+     inkscape:showpageshadow="2"
+     inkscape:pageopacity="0.0"
+     inkscape:pagecheckerboard="0"
+     inkscape:deskcolor="#d1d1d1"
+     inkscape:zoom="2.1335227"
+     inkscape:cx="119.05193"
+     inkscape:cy="48.511318"
+     inkscape:window-width="1920"
+     inkscape:window-height="1025"
+     inkscape:window-x="0"
+     inkscape:window-y="0"
+     inkscape:window-maximized="1"
+     inkscape:current-layer="g13" />
+  <defs
+     id="defs1">
+    <style
+       id="style1">
+      .cls-1 {
+        fill: #303030;
+      }
+
+      .cls-2 {
+        fill: #59e389;
+      }
+    </style>
+  </defs>
+  <g
+     id="Grafica"
+     transform="translate(0,-40.87)">
+    <g
+       id="g13">
+      <path
+         class="cls-1"
+         d="m 104.39,105.96 v 36.18 c 0,0.32 -0.05,0.62 -0.14,0.91 -0.39,1.27 -1.58,2.2 -2.99,2.2 H 65.08 c -1.73,0 -3.13,-1.41 -3.13,-3.13 V 113.4 c 0,-0.15 0,-0.29 0,-0.44 v -7 c 0,-1.73 1.4,-3.13 3.13,-3.13 h 36.19 c 1.5,0 2.77,1.07 3.06,2.5 0.05,0.21 0.07,0.41 0.07,0.63 z"
+         id="path1" />
+      <path
+         class="cls-1"
+         d="m 104.39,105.96 v 36.18 c 0,0.32 -0.05,0.62 -0.14,0.91 -0.39,1.27 -1.58,2.2 -2.99,2.2 H 65.08 c -1.73,0 -3.13,-1.41 -3.13,-3.13 V 113.4 c 0,-0.15 0,-0.29 0,-0.44 v -7 c 0,-1.73 1.4,-3.13 3.13,-3.13 h 36.19 c 1.5,0 2.77,1.07 3.06,2.5 0.05,0.21 0.07,0.41 0.07,0.63 z"
+         id="path2" />
+      <path
+         class="cls-2"
+         d="M 101.27,40.88 H 65.09 c -1.73,0 -3.13,1.4 -3.13,3.13 v 28.71 c 0,4.71 -1.88,9.23 -5.2,12.56 L 44.42,97.61 c -3.32,3.33 -7.85,5.2 -12.55,5.2 H 18.98 c -2.21,0 -3.99,-1.79 -3.99,-3.99 V 87.29 c 0,-2.21 1.79,-3.99 3.99,-3.99 h 20.34 c 1.41,0 2.59,-0.93 2.99,-2.2 0.09,-0.29 0.14,-0.59 0.14,-0.91 V 44 c 0,-0.22 -0.02,-0.42 -0.07,-0.63 -0.29,-1.43 -1.56,-2.5 -3.06,-2.5 H 3.13 C 1.4,40.87 0,42.27 0,44 v 7 c 0,0.15 0,0.29 0,0.44 v 28.72 c 0,1.72 1.41,3.13 3.13,3.13 h 3.16 c 2.21,0 3.99,1.79 3.99,3.99 v 11.53 c 0,2.21 -1.79,3.99 -3.99,3.99 H 3.15 c -1.73,0 -3.13,1.4 -3.13,3.13 v 36.19 c 0,1.72 1.41,3.13 3.13,3.13 h 36.19 c 1.73,0 3.13,-1.41 3.13,-3.13 V 113.4 c 0,-4.7 1.87,-9.23 5.2,-12.55 L 60,88.51 c 3.33,-3.32 7.85,-5.2 12.56,-5.2 h 28.71 c 1.73,0 3.13,-1.4 3.13,-3.13 V 44 c 0,-1.73 -1.4,-3.13 -3.13,-3.13 z"
+         id="path3" />
+    </g>
+  </g>
+</svg>

apps/setting/models_provider/impl/regolo_model_provider/model/embedding.py

@@ -0,0 +1,23 @@
+# coding=utf-8
+"""
+    @project: MaxKB
+    @Author：虎
+    @file： embedding.py
+    @date：2024/7/12 17:44
+    @desc:
+"""
+from typing import Dict
+
+from langchain_community.embeddings import OpenAIEmbeddings
+
+from setting.models_provider.base_model_provider import MaxKBBaseModel
+
+
+class RegoloEmbeddingModel(MaxKBBaseModel, OpenAIEmbeddings):
+    @staticmethod
+    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
+        return RegoloEmbeddingModel(
+            api_key=model_credential.get('api_key'),
+            model=model_name,
+            openai_api_base="https://api.regolo.ai/v1",
+        )

apps/setting/models_provider/impl/regolo_model_provider/model/image.py

@@ -0,0 +1,19 @@
+from typing import Dict
+
+from setting.models_provider.base_model_provider import MaxKBBaseModel
+from setting.models_provider.impl.base_chat_open_ai import BaseChatOpenAI
+
+
+class RegoloImage(MaxKBBaseModel, BaseChatOpenAI):
+
+    @staticmethod
+    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
+        optional_params = MaxKBBaseModel.filter_optional_params(model_kwargs)
+        return RegoloImage(
+            model_name=model_name,
+            openai_api_base="https://api.regolo.ai/v1",
+            openai_api_key=model_credential.get('api_key'),
+            streaming=True,
+            stream_usage=True,
+            extra_body=optional_params
+        )

apps/setting/models_provider/impl/regolo_model_provider/model/llm.py

@@ -0,0 +1,38 @@
+# coding=utf-8
+"""
+    @project: maxkb
+    @Author：虎
+    @file： llm.py
+    @date：2024/4/18 15:28
+    @desc:
+"""
+from typing import List, Dict
+
+from langchain_core.messages import BaseMessage, get_buffer_string
+from langchain_openai.chat_models import ChatOpenAI
+
+from common.config.tokenizer_manage_config import TokenizerManage
+from setting.models_provider.base_model_provider import MaxKBBaseModel
+from setting.models_provider.impl.base_chat_open_ai import BaseChatOpenAI
+
+
+def custom_get_token_ids(text: str):
+    tokenizer = TokenizerManage.get_tokenizer()
+    return tokenizer.encode(text)
+
+
+class RegoloChatModel(MaxKBBaseModel, BaseChatOpenAI):
+
+    @staticmethod
+    def is_cache_model():
+        return False
+
+    @staticmethod
+    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
+        optional_params = MaxKBBaseModel.filter_optional_params(model_kwargs)
+        return RegoloChatModel(
+            model=model_name,
+            openai_api_base="https://api.regolo.ai/v1",
+            openai_api_key=model_credential.get('api_key'),
+            extra_body=optional_params
+        )

apps/setting/models_provider/impl/regolo_model_provider/model/tti.py

@@ -0,0 +1,58 @@
+from typing import Dict
+
+from openai import OpenAI
+
+from common.config.tokenizer_manage_config import TokenizerManage
+from setting.models_provider.base_model_provider import MaxKBBaseModel
+from setting.models_provider.impl.base_tti import BaseTextToImage
+
+
+def custom_get_token_ids(text: str):
+    tokenizer = TokenizerManage.get_tokenizer()
+    return tokenizer.encode(text)
+
+
+class RegoloTextToImage(MaxKBBaseModel, BaseTextToImage):
+    api_base: str
+    api_key: str
+    model: str
+    params: dict
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.api_key = kwargs.get('api_key')
+        self.api_base = "https://api.regolo.ai/v1"
+        self.model = kwargs.get('model')
+        self.params = kwargs.get('params')
+
+    @staticmethod
+    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
+        optional_params = {'params': {'size': '1024x1024', 'quality': 'standard', 'n': 1}}
+        for key, value in model_kwargs.items():
+            if key not in ['model_id', 'use_local', 'streaming']:
+                optional_params['params'][key] = value
+        return RegoloTextToImage(
+            model=model_name,
+            api_base="https://api.regolo.ai/v1",
+            api_key=model_credential.get('api_key'),
+            **optional_params,
+        )
+
+    def is_cache_model(self):
+        return False
+
+    def check_auth(self):
+        chat = OpenAI(api_key=self.api_key, base_url=self.api_base)
+        response_list = chat.models.with_raw_response.list()
+
+        # self.generate_image('生成一个小猫图片')
+
+    def generate_image(self, prompt: str, negative_prompt: str = None):
+        chat = OpenAI(api_key=self.api_key, base_url=self.api_base)
+        res = chat.images.generate(model=self.model, prompt=prompt, **self.params)
+        file_urls = []
+        for content in res.data:
+            url = content.url
+            file_urls.append(url)
+
+        return file_urls

apps/setting/models_provider/impl/regolo_model_provider/regolo_model_provider.py

@@ -0,0 +1,89 @@
+# coding=utf-8
+"""
+    @project: maxkb
+    @Author：虎
+    @file： openai_model_provider.py
+    @date：2024/3/28 16:26
+    @desc:
+"""
+import os
+
+from common.util.file_util import get_file_content
+from setting.models_provider.base_model_provider import IModelProvider, ModelProvideInfo, ModelInfo, \
+    ModelTypeConst, ModelInfoManage
+from setting.models_provider.impl.regolo_model_provider.credential.embedding import \
+    RegoloEmbeddingCredential
+from setting.models_provider.impl.regolo_model_provider.credential.llm import RegoloLLMModelCredential
+from setting.models_provider.impl.regolo_model_provider.credential.tti import \
+    RegoloTextToImageModelCredential
+from setting.models_provider.impl.regolo_model_provider.model.embedding import RegoloEmbeddingModel
+from setting.models_provider.impl.regolo_model_provider.model.llm import RegoloChatModel
+from setting.models_provider.impl.regolo_model_provider.model.tti import RegoloTextToImage
+from smartdoc.conf import PROJECT_DIR
+from django.utils.translation import gettext as _
+
+openai_llm_model_credential = RegoloLLMModelCredential()
+openai_tti_model_credential = RegoloTextToImageModelCredential()
+model_info_list = [
+    ModelInfo('Phi-4', '', ModelTypeConst.LLM,
+              openai_llm_model_credential, RegoloChatModel
+              ),
+    ModelInfo('DeepSeek-R1-Distill-Qwen-32B', '', ModelTypeConst.LLM,
+              openai_llm_model_credential,
+              RegoloChatModel),
+    ModelInfo('maestrale-chat-v0.4-beta', '',
+              ModelTypeConst.LLM, openai_llm_model_credential,
+              RegoloChatModel),
+    ModelInfo('Llama-3.3-70B-Instruct',
+              '',
+              ModelTypeConst.LLM, openai_llm_model_credential,
+              RegoloChatModel),
+    ModelInfo('Llama-3.1-8B-Instruct',
+              '',
+              ModelTypeConst.LLM, openai_llm_model_credential,
+              RegoloChatModel),
+    ModelInfo('DeepSeek-Coder-6.7B-Instruct', '',
+              ModelTypeConst.LLM, openai_llm_model_credential,
+              RegoloChatModel)
+]
+open_ai_embedding_credential = RegoloEmbeddingCredential()
+model_info_embedding_list = [
+    ModelInfo('gte-Qwen2', '',
+              ModelTypeConst.EMBEDDING, open_ai_embedding_credential,
+              RegoloEmbeddingModel),
+]
+
+model_info_tti_list = [
+    ModelInfo('FLUX.1-dev', '',
+              ModelTypeConst.TTI, openai_tti_model_credential,
+              RegoloTextToImage),
+    ModelInfo('sdxl-turbo', '',
+              ModelTypeConst.TTI, openai_tti_model_credential,
+              RegoloTextToImage),
+]
+model_info_manage = (
+    ModelInfoManage.builder()
+    .append_model_info_list(model_info_list)
+    .append_default_model_info(
+        ModelInfo('gpt-3.5-turbo', _('The latest gpt-3.5-turbo, updated with OpenAI adjustments'), ModelTypeConst.LLM,
+                  openai_llm_model_credential, RegoloChatModel
+                  ))
+    .append_model_info_list(model_info_embedding_list)
+    .append_default_model_info(model_info_embedding_list[0])
+    .append_model_info_list(model_info_tti_list)
+    .append_default_model_info(model_info_tti_list[0])
+
+    .build()
+)
+
+
+class RegoloModelProvider(IModelProvider):
+
+    def get_model_info_manage(self):
+        return model_info_manage
+
+    def get_model_provide_info(self):
+        return ModelProvideInfo(provider='model_regolo_provider', name='Regolo', icon=get_file_content(
+            os.path.join(PROJECT_DIR, "apps", "setting", 'models_provider', 'impl', 'regolo_model_provider',
+                         'icon',
+                         'regolo_icon_svg')))

apps/setting/models_provider/impl/siliconCloud_model_provider/model/image.py

@@ -16,5 +16,5 @@ class SiliconCloudImage(MaxKBBaseModel, BaseChatOpenAI):
             # stream_options={"include_usage": True},
             streaming=True,
             stream_usage=True,
-            **optional_params,
+            extra_body=optional_params
         )

apps/setting/models_provider/impl/siliconCloud_model_provider/model/llm.py

@@ -34,5 +34,5 @@ class SiliconCloudChatModel(MaxKBBaseModel, BaseChatOpenAI):
             model=model_name,
             openai_api_base=model_credential.get('api_base'),
             openai_api_key=model_credential.get('api_key'),
-            **optional_params
+            extra_body=optional_params
         )

apps/setting/models_provider/impl/tencent_cloud_model_provider/model/llm.py

@@ -33,21 +33,7 @@ class TencentCloudChatModel(MaxKBBaseModel, BaseChatOpenAI):
             model=model_name,
             openai_api_base=model_credential.get('api_base'),
             openai_api_key=model_credential.get('api_key'),
-            **optional_params,
+            extra_body=optional_params,
             custom_get_token_ids=custom_get_token_ids
         )
         return azure_chat_open_ai
-
-    def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:
-        try:
-            return super().get_num_tokens_from_messages(messages)
-        except Exception as e:
-            tokenizer = TokenizerManage.get_tokenizer()
-            return sum([len(tokenizer.encode(get_buffer_string([m]))) for m in messages])
-
-    def get_num_tokens(self, text: str) -> int:
-        try:
-            return super().get_num_tokens(text)
-        except Exception as e:
-            tokenizer = TokenizerManage.get_tokenizer()
-            return len(tokenizer.encode(text))

apps/setting/models_provider/impl/tencent_model_provider/model/image.py

@@ -16,5 +16,5 @@ class TencentVision(MaxKBBaseModel, BaseChatOpenAI):
             # stream_options={"include_usage": True},
             streaming=True,
             stream_usage=True,
-            **optional_params,
+            extra_body=optional_params
         )

apps/setting/models_provider/impl/vllm_model_provider/model/image.py

@@ -19,7 +19,7 @@ class VllmImage(MaxKBBaseModel, BaseChatOpenAI):
             # stream_options={"include_usage": True},
             streaming=True,
             stream_usage=True,
-            **optional_params,
+            extra_body=optional_params
         )
 
     def is_cache_model(self):

apps/setting/models_provider/impl/vllm_model_provider/model/llm.py

@@ -1,9 +1,10 @@
 # coding=utf-8
 
-from typing import Dict, List
+from typing import Dict, Optional, Sequence, Union, Any, Callable
 from urllib.parse import urlparse, ParseResult
 
 from langchain_core.messages import BaseMessage, get_buffer_string
+from langchain_core.tools import BaseTool
 
 from common.config.tokenizer_manage_config import TokenizerManage
 from setting.models_provider.base_model_provider import MaxKBBaseModel
@@ -31,13 +32,19 @@ class VllmChatModel(MaxKBBaseModel, BaseChatOpenAI):
             model=model_name,
             openai_api_base=model_credential.get('api_base'),
             openai_api_key=model_credential.get('api_key'),
-            **optional_params,
             streaming=True,
             stream_usage=True,
+            extra_body=optional_params
         )
         return vllm_chat_open_ai
 
-    def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:
+    def get_num_tokens_from_messages(
+            self,
+            messages: list[BaseMessage],
+            tools: Optional[
+                Sequence[Union[dict[str, Any], type, Callable, BaseTool]]
+            ] = None,
+    ) -> int:
         if self.usage_metadata is None or self.usage_metadata == {}:
             tokenizer = TokenizerManage.get_tokenizer()
             return sum([len(tokenizer.encode(get_buffer_string([m]))) for m in messages])

apps/setting/models_provider/impl/volcanic_engine_model_provider/model/image.py

@@ -16,5 +16,5 @@ class VolcanicEngineImage(MaxKBBaseModel, BaseChatOpenAI):
             # stream_options={"include_usage": True},
             streaming=True,
             stream_usage=True,
-            **optional_params,
+            extra_body=optional_params
         )

apps/setting/models_provider/impl/volcanic_engine_model_provider/model/llm.py

@@ -17,5 +17,5 @@ class VolcanicEngineChatModel(MaxKBBaseModel, BaseChatOpenAI):
             model=model_name,
             openai_api_base=model_credential.get('api_base'),
             openai_api_key=model_credential.get('api_key'),
-            **optional_params
+            extra_body=optional_params
         )

apps/setting/models_provider/impl/wenxin_model_provider/credential/llm.py

@@ -27,7 +27,7 @@ class WenxinLLMModelParams(BaseForm):
                                     _step=0.01,
                                     precision=2)
 
-    max_tokens = forms.SliderField(
+    max_output_tokens = forms.SliderField(
         TooltipLabel(_('Output the maximum Tokens'),
                      _('Specify the maximum number of tokens that the model can generate')),
         required=True, default_value=1024,

apps/setting/models_provider/impl/xinference_model_provider/model/image.py

@@ -19,7 +19,7 @@ class XinferenceImage(MaxKBBaseModel, BaseChatOpenAI):
             # stream_options={"include_usage": True},
             streaming=True,
             stream_usage=True,
-            **optional_params,
+            extra_body=optional_params
         )
 
     def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:

apps/setting/models_provider/impl/xinference_model_provider/model/llm.py

@@ -34,7 +34,7 @@ class XinferenceChatModel(MaxKBBaseModel, BaseChatOpenAI):
             model=model_name,
             openai_api_base=base_url,
             openai_api_key=model_credential.get('api_key'),
-            **optional_params
+            extra_body=optional_params
         )
 
     def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:

apps/setting/models_provider/impl/xinference_model_provider/model/reranker.py

@@ -22,6 +22,9 @@ class XInferenceReranker(MaxKBBaseModel, BaseDocumentCompressor):
     """UID of the launched model"""
     api_key: Optional[str]
 
+    @staticmethod
+    def is_cache_model():
+        return False
     @staticmethod
     def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
         return XInferenceReranker(server_url=model_credential.get('server_url'), model_uid=model_name,

apps/setting/models_provider/impl/zhipu_model_provider/model/image.py

@@ -16,5 +16,5 @@ class ZhiPuImage(MaxKBBaseModel, BaseChatOpenAI):
             # stream_options={"include_usage": True},
             streaming=True,
             stream_usage=True,
-            **optional_params,
+            extra_body=optional_params
         )

apps/setting/serializers/team_serializers.py

@@ -171,6 +171,24 @@ class TeamMemberSerializer(ApiMixin, serializers.Serializer):
             }
         )
 
+    @staticmethod
+    def get_response_body_api():
+        return openapi.Schema(
+            type=openapi.TYPE_OBJECT,
+            properties={
+                'id': openapi.Schema(type=openapi.TYPE_STRING, title=_('user id'), description=_('user id')),
+                'username': openapi.Schema(type=openapi.TYPE_STRING, title=_('Username'), description=_('Username')),
+                'email': openapi.Schema(type=openapi.TYPE_STRING, title=_('Email'), description=_('Email')),
+                'role': openapi.Schema(type=openapi.TYPE_STRING, title=_('Role'), description=_('Role')),
+                'is_active': openapi.Schema(type=openapi.TYPE_STRING, title=_('Is active'),
+                                            description=_('Is active')),
+                'team_id': openapi.Schema(type=openapi.TYPE_STRING, title=_('team id'), description=_('team id')),
+                'user_id': openapi.Schema(type=openapi.TYPE_STRING, title=_('user id'), description=_('user id')),
+                'type': openapi.Schema(type=openapi.TYPE_STRING, title=_('member type'),
+                                       description=_('member type manage|member')),
+            }
+        )
+
     @transaction.atomic
     def batch_add_member(self, user_id_list: List[str], with_valid=True):
         """

apps/setting/views/Team.py

@@ -38,6 +38,7 @@ class TeamMember(APIView):
     @swagger_auto_schema(operation_summary=_('Add member'),
                          operation_id=_('Add member'),
                          request_body=TeamMemberSerializer().get_request_body_api(),
+                         responses=result.get_default_response(),
                          tags=[_('Team')])
     @has_permissions(PermissionConstants.TEAM_CREATE)
     @log(menu='Team', operate='Add member',
@@ -53,6 +54,7 @@ class TeamMember(APIView):
         @swagger_auto_schema(operation_summary=_('Add members in batches'),
                              operation_id=_('Add members in batches'),
                              request_body=TeamMemberSerializer.get_bach_request_body_api(),
+                             responses=result.get_api_array_response(TeamMemberSerializer.get_response_body_api()),
                              tags=[_('Team')])
         @has_permissions(PermissionConstants.TEAM_CREATE)
         @log(menu='Team', operate='Add members in batches',
@@ -78,6 +80,7 @@ class TeamMember(APIView):
         @swagger_auto_schema(operation_summary=_('Update team member permissions'),
                              operation_id=_('Update team member permissions'),
                              request_body=UpdateTeamMemberPermissionSerializer().get_request_body_api(),
+                             responses=result.get_default_response(),
                              manual_parameters=TeamMemberSerializer.Operate.get_request_params_api(),
                              tags=[_('Team')]
                              )
@@ -93,6 +96,7 @@ class TeamMember(APIView):
         @swagger_auto_schema(operation_summary=_('Remove member'),
                              operation_id=_('Remove member'),
                              manual_parameters=TeamMemberSerializer.Operate.get_request_params_api(),
+                             responses=result.get_default_response(),
                              tags=[_('Team')]
                              )
         @has_permissions(PermissionConstants.TEAM_DELETE)

apps/setting/views/model.py

@@ -31,7 +31,8 @@ class Model(APIView):
     @action(methods=['POST'], detail=False)
     @swagger_auto_schema(operation_summary=_('Create model'),
                          operation_id=_('Create model'),
-                         request_body=ModelCreateApi.get_request_body_api()
+                         request_body=ModelCreateApi.get_request_body_api(),
+                         manual_parameters=result.get_api_response(ModelCreateApi.get_request_body_api())
         , tags=[_('model')])
     @has_permissions(PermissionConstants.MODEL_CREATE)
     @log(menu='model', operate='Create model',
@@ -45,7 +46,8 @@ class Model(APIView):
     @action(methods=['PUT'], detail=False)
     @swagger_auto_schema(operation_summary=_('Download model, trial only with Ollama platform'),
                          operation_id=_('Download model, trial only with Ollama platform'),
-                         request_body=ModelCreateApi.get_request_body_api()
+                         request_body=ModelCreateApi.get_request_body_api(),
+                         responses=result.get_api_response(ModelCreateApi.get_request_body_api())
         , tags=[_('model')])
     @has_permissions(PermissionConstants.MODEL_CREATE)
     def put(self, request: Request):
@@ -123,7 +125,8 @@ class Model(APIView):
         @action(methods=['PUT'], detail=False)
         @swagger_auto_schema(operation_summary=_('Update model'),
                              operation_id=_('Update model'),
-                             request_body=ModelEditApi.get_request_body_api()
+                             request_body=ModelEditApi.get_request_body_api(),
+                             responses=result.get_api_response(ModelEditApi.get_request_body_api())
             , tags=[_('model')])
         @has_permissions(PermissionConstants.MODEL_CREATE)
         @log(menu='model', operate='Update model',
@@ -166,7 +169,8 @@ class Provide(APIView):
         @swagger_auto_schema(operation_summary=_('Call the supplier function to obtain form data'),
                              operation_id=_('Call the supplier function to obtain form data'),
                              manual_parameters=ProvideApi.get_request_params_api(),
-                             request_body=ProvideApi.get_request_body_api()
+                             request_body=ProvideApi.get_request_body_api(),
+                             responses=result.get_api_response(ProvideApi.get_request_body_api())
             , tags=[_('model')])
         @has_permissions(PermissionConstants.MODEL_READ)
         @log(menu='model', operate='Call the supplier function to obtain form data')

apps/smartdoc/conf.py

@@ -93,7 +93,8 @@ class Config(dict):
         'SANDBOX': False,
         'LOCAL_MODEL_HOST': '127.0.0.1',
         'LOCAL_MODEL_PORT': '11636',
-        'LOCAL_MODEL_PROTOCOL': "http"
+        'LOCAL_MODEL_PROTOCOL': "http",
+        'LOCAL_MODEL_HOST_WORKER': 1
 
     }
 
@@ -113,7 +114,8 @@ class Config(dict):
             "ENGINE": self.get('DB_ENGINE'),
             "POOL_OPTIONS": {
                 "POOL_SIZE": 20,
-                "MAX_OVERFLOW": int(self.get('DB_MAX_OVERFLOW'))
+                "MAX_OVERFLOW": int(self.get('DB_MAX_OVERFLOW')),
+                'RECYCLE': 30 * 60
             }
         }
 

apps/smartdoc/settings/base.py

@@ -126,6 +126,10 @@ CACHES = {
     "token_cache": {
         'BACKEND': 'common.cache.file_cache.FileCache',
         'LOCATION': os.path.join(PROJECT_DIR, 'data', 'cache', "token_cache")  # 文件夹路径
+    },
+    'captcha_cache': {
+        'BACKEND': 'common.cache.file_cache.FileCache',
+        'LOCATION': os.path.join(PROJECT_DIR, 'data', 'cache', "captcha_cache")  # 文件夹路径
     }
 }
 

apps/users/serializers/user_serializers.py

@@ -6,18 +6,22 @@
     @date：2023/9/5 16:32
     @desc:
 """
+import base64
 import datetime
 import os
 import random
 import re
 import uuid
 
+from captcha.image import ImageCaptcha
 from django.conf import settings
 from django.core import validators, signing, cache
 from django.core.mail import send_mail
 from django.core.mail.backends.smtp import EmailBackend
 from django.db import transaction
 from django.db.models import Q, QuerySet, Prefetch
+from django.utils.translation import get_language
+from django.utils.translation import gettext_lazy as _, to_locale
 from drf_yasg import openapi
 from rest_framework import serializers
 
@@ -30,7 +34,7 @@ from common.exception.app_exception import AppApiException
 from common.mixins.api_mixin import ApiMixin
 from common.models.db_model_manage import DBModelManage
 from common.response.result import get_api_response
-from common.util.common import valid_license
+from common.util.common import valid_license, get_random_chars
 from common.util.field_message import ErrMessage
 from common.util.lock import lock
 from dataset.models import DataSet, Document, Paragraph, Problem, ProblemParagraphMapping
@@ -39,9 +43,29 @@ from function_lib.models.function import FunctionLib
 from setting.models import Team, SystemSetting, SettingType, Model, TeamMember, TeamMemberPermission
 from smartdoc.conf import PROJECT_DIR
 from users.models.user import User, password_encrypt, get_user_dynamics_permission
-from django.utils.translation import gettext_lazy as _, gettext, to_locale
+
-from django.utils.translation import get_language
 user_cache = cache.caches['user_cache']
+captcha_cache = cache.caches['captcha_cache']
+
+
+class CaptchaSerializer(ApiMixin, serializers.Serializer):
+    @staticmethod
+    def get_response_body_api():
+        return get_api_response(openapi.Schema(
+            type=openapi.TYPE_STRING,
+            title="captcha",
+            default="xxxx",
+            description="captcha"
+        ))
+
+    @staticmethod
+    def generate():
+        chars = get_random_chars()
+        image = ImageCaptcha()
+        data = image.generate(chars)
+        captcha = base64.b64encode(data.getbuffer())
+        captcha_cache.set(f"LOGIN:{chars.lower()}", chars, timeout=5 * 60)
+        return 'data:image/png;base64,' + captcha.decode()
 
 
 class SystemSerializer(ApiMixin, serializers.Serializer):
@@ -71,6 +95,8 @@ class LoginSerializer(ApiMixin, serializers.Serializer):
 
     password = serializers.CharField(required=True, error_messages=ErrMessage.char(_("Password")))
 
+    captcha = serializers.CharField(required=True, error_messages=ErrMessage.char(_("captcha")))
+
     def is_valid(self, *, raise_exception=False):
         """
         校验参数
@@ -78,6 +104,10 @@ class LoginSerializer(ApiMixin, serializers.Serializer):
         :return: User information
         """
         super().is_valid(raise_exception=True)
+        captcha = self.data.get('captcha')
+        captcha_value = captcha_cache.get(f"LOGIN:{captcha.lower()}")
+        if captcha_value is None:
+            raise AppApiException(1005, _("Captcha code error or expiration"))
         username = self.data.get("username")
         password = password_encrypt(self.data.get("password"))
         user = QuerySet(User).filter(Q(username=username,
@@ -109,7 +139,8 @@ class LoginSerializer(ApiMixin, serializers.Serializer):
             required=['username', 'password'],
             properties={
                 'username': openapi.Schema(type=openapi.TYPE_STRING, title=_("Username"), description=_("Username")),
-                'password': openapi.Schema(type=openapi.TYPE_STRING, title=_("Password"), description=_("Password"))
+                'password': openapi.Schema(type=openapi.TYPE_STRING, title=_("Password"), description=_("Password")),
+                'captcha': openapi.Schema(type=openapi.TYPE_STRING, title=_("captcha"), description=_("captcha"))
             }
         )
 

apps/users/urls.py

@@ -6,6 +6,7 @@ app_name = "user"
 urlpatterns = [
     path('profile', views.Profile.as_view()),
     path('user', views.User.as_view(), name="profile"),
+    path('user/captcha', views.CaptchaView.as_view(), name='captcha'),
     path('user/language', views.SwitchUserLanguageView.as_view(), name='language'),
     path('user/list', views.User.Query.as_view()),
     path('user/login', views.Login.as_view(), name='login'),

apps/users/views/user.py

@@ -26,7 +26,7 @@ from smartdoc.settings import JWT_AUTH
 from users.serializers.user_serializers import RegisterSerializer, LoginSerializer, CheckCodeSerializer, \
     RePasswordSerializer, \
     SendEmailSerializer, UserProfile, UserSerializer, UserManageSerializer, UserInstanceSerializer, SystemSerializer, \
-    SwitchLanguageSerializer
+    SwitchLanguageSerializer, CaptchaSerializer
 from users.views.common import get_user_operation_object, get_re_password_details
 
 user_cache = cache.caches['user_cache']
@@ -84,7 +84,7 @@ class SwitchUserLanguageView(APIView):
                                                             description=_("language")),
                              }
                          ),
-                         responses=RePasswordSerializer().get_response_body_api(),
+                         responses=result.get_default_response(),
                          tags=[_("User management")])
     @log(menu='User management', operate='Switch Language',
          get_operation_object=lambda r, k: {'name': r.user.username})
@@ -111,7 +111,7 @@ class ResetCurrentUserPasswordView(APIView):
                                                                description=_("Password"))
                              }
                          ),
-                         responses=RePasswordSerializer().get_response_body_api(),
+                         responses=result.get_default_response(),
                          tags=[_("User management")])
     @log(menu='User management', operate='Modify current user password',
          get_operation_object=lambda r, k: {'name': r.user.username},
@@ -170,6 +170,18 @@ def _get_details(request):
     }
 
 
+class CaptchaView(APIView):
+
+    @action(methods=['GET'], detail=False)
+    @swagger_auto_schema(operation_summary=_("Obtain graphical captcha"),
+                         operation_id=_("Obtain graphical captcha"),
+                         responses=CaptchaSerializer().get_response_body_api(),
+                         security=[],
+                         tags=[_("User management")])
+    def get(self, request: Request):
+        return result.success(CaptchaSerializer().generate())
+
+
 class Login(APIView):
 
     @action(methods=['POST'], detail=False)

installer/Dockerfile

@@ -25,7 +25,7 @@ RUN python3 -m venv /opt/py3 && \
     pip install poetry==1.8.5 --break-system-packages && \
     poetry config virtualenvs.create false && \
     . /opt/py3/bin/activate && \
-    if [ "$(uname -m)" = "x86_64" ]; then sed -i 's/^torch.*/torch = {version = "^2.6.0+cpu", source = "pytorch"}/g' pyproject.toml; fi && \
+    if [ "$(uname -m)" = "x86_64" ]; then sed -i 's/^torch.*/torch = {version = "2.6.0+cpu", source = "pytorch"}/g' pyproject.toml; fi && \
     poetry install && \
     export MAXKB_CONFIG_TYPE=ENV && python3 /opt/maxkb/app/apps/manage.py compilemessages
 
@@ -70,7 +70,8 @@ RUN chmod 755 /opt/maxkb/app/installer/run-maxkb.sh && \
     useradd --no-create-home --home /opt/maxkb/app/sandbox sandbox -g root && \
     chown -R sandbox:root /opt/maxkb/app/sandbox && \
     chmod g-x /usr/local/bin/* /usr/bin/* /bin/* /usr/sbin/* /sbin/* /usr/lib/postgresql/15/bin/* && \
-    chmod g+x /usr/local/bin/python*
+    chmod g+x /usr/local/bin/python* && \
+    find /etc/ -type f ! -path '/etc/resolv.conf' ! -path '/etc/hosts' | xargs chmod g-rx
 
 EXPOSE 8080