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b/zh_CN/.gitbook/assets/image (4) (1).png index 1592de4..c2fb745 100644 Binary files a/zh_CN/.gitbook/assets/image (4) (1).png and b/zh_CN/.gitbook/assets/image (4) (1).png differ diff --git a/zh_CN/.gitbook/assets/image (4).png b/zh_CN/.gitbook/assets/image (4).png index c2fb745..aab0a24 100644 Binary files a/zh_CN/.gitbook/assets/image (4).png and b/zh_CN/.gitbook/assets/image (4).png differ diff --git a/zh_CN/.gitbook/assets/image.png b/zh_CN/.gitbook/assets/image.png index aab0a24..fecf1d7 100644 Binary files a/zh_CN/.gitbook/assets/image.png and b/zh_CN/.gitbook/assets/image.png differ diff --git a/zh_CN/guides/application-design/agent.md b/zh_CN/guides/application-design/agent.md index 09bcd31..00d3dd2 100644 --- a/zh_CN/guides/application-design/agent.md +++ b/zh_CN/guides/application-design/agent.md @@ -8,11 +8,11 @@ 为了方便快速上手使用，您可以在“探索”中找到智能助手的应用模板，添加到自己的工作区，或者在此基础上进行自定义。在全新的 Dify 工作室中，你也可以从零编排一个专属于你自己的智能助手，帮助你完成财务报表分析、撰写报告、Logo 设计、旅程规划等任务。 -

探索-智能助手应用模板

+

探索-智能助手应用模板

在“工作室-助手型应用”内选择智能助手即可开始编排。 -

工作室-构建智能助手

+

工作室-构建智能助手

选择智能助手的推理模型，智能助手的任务完成能力取决于模型推理能力，我们建议在使用智能助手时选择推理能力更强的模型系列如 gpt-4 以获得更稳定的任务完成效果。 @@ -20,7 +20,7 @@ 你可以在“提示词”中编写智能助手的指令，为了能够达到更优的预期效果，你可以在指令中明确它的任务目标、工作流程、资源和限制等。 -

编排智能助手的指令提示词

+

编排智能助手的指令提示词

### 添加助手需要的工具 @@ -30,7 +30,7 @@ 你可以直接使用 Dify 生态提供的第一方内置工具，或者轻松导入自定义的 API 工具（目前支持 OpenAPI / Swagger 和 OpenAI Plugin 规范）。 -

添加助手需要的工具

+

添加助手需要的工具

工具使用户可以在 Dify 上创建更强大的 AI 应用，如你可以为智能助理型应用（Agent）编排合适的工具，它可以通过任务推理、步骤拆解、调用工具完成复杂任务。另外工具也可以方便将你的应用与其他系统或服务连接，与外部环境交互，如代码执行、对专属信息源的访问等。 @@ -48,7 +48,7 @@ 您可以为智能助手配置一套会话开场白和开场问题，配置的对话开场白将在每次用户初次对话中展示助手可以完成什么样的任务，以及可以提出的问题示例。 -

配置会话开场白和开场问题

+

配置会话开场白和开场问题

### 调试与预览 diff --git a/zh_CN/guides/biao-zhu/annotation-reply.md b/zh_CN/guides/biao-zhu/annotation-reply.md index becc2af..19bed12 100644 --- a/zh_CN/guides/biao-zhu/annotation-reply.md +++ b/zh_CN/guides/biao-zhu/annotation-reply.md @@ -53,7 +53,7 @@ 通过进入“应用构建->日志与标注->标注”开启标注回复开关： -

日志与标注中开启标注回复

+

日志与标注中开启标注回复

### 在标注后台设置标注回复参数 @@ -63,7 +63,7 @@ **Embedding 模型**：用于对标注文本进行向量化，切换模型时会重新生成嵌入。 -

设置标注回复参数

+

设置标注回复参数

### 批量导入标注问答对 diff --git a/zh_CN/guides/knowledge-base/integrate_knowledge_within_application.md b/zh_CN/guides/knowledge-base/integrate_knowledge_within_application.md index c6cca89..748876e 100644 --- a/zh_CN/guides/knowledge-base/integrate_knowledge_within_application.md +++ b/zh_CN/guides/knowledge-base/integrate_knowledge_within_application.md @@ -93,7 +93,7 @@ Dify 目前已支持 Cohere Rerank 模型，通过进入“模型供应商-> Coh 通过进入“数据集->创建数据集->检索设置”页面并在添加 Rerank 设置。除了在创建数据集可以设置 Rerank ，你也可以在已创建的数据集设置内更改 Rerank 配置，在应用编排的数据集召回模式设置中更改 Rerank 配置。 -

数据集检索模式中设置 Rerank 模型

+

数据集检索模式中设置 Rerank 模型

**TopK**：用于设置 Rerank 后返回相关文档的数量。 @@ -101,4 +101,4 @@ Dify 目前已支持 Cohere Rerank 模型，通过进入“模型供应商-> Coh 通过进入“提示词编排->上下文->设置”页面中设置为多路召回模式时需开启 Rerank 模型。 -

数据集多路召回模式中设置 Rerank 模型

+

数据集多路召回模式中设置 Rerank 模型

diff --git a/zh_CN/guides/knowledge-base/knowledge_and_documents_maintenance.md b/zh_CN/guides/knowledge-base/knowledge_and_documents_maintenance.md index b786207..831a32e 100644 --- a/zh_CN/guides/knowledge-base/knowledge_and_documents_maintenance.md +++ b/zh_CN/guides/knowledge-base/knowledge_and_documents_maintenance.md @@ -4,7 +4,7 @@ 知识库内已上传的每个文档都会以文本分段（Chunks）的形式进行存储，你可以在分段列表内查看每一个分段的具体文本内容。 -

查看已上传的文档分段

+

查看已上传的文档分段

*** @@ -34,11 +34,11 @@ 在分段列表内点击 「 添加分段 」 ，可以在文档内自行添加一个或批量添加多个自定义分段。 -
+
批量添加分段时，你需要先下载 CSV 格式的分段上传模板，并按照模板格式在 Excel 内编辑所有的分段内容，再将 CSV 文件保存后上传。 -

批量添加自定义分段

+

批量添加自定义分段

*** diff --git a/zh_CN/guides/knowledge-base/retrieval_test_and_citation.md b/zh_CN/guides/knowledge-base/retrieval_test_and_citation.md index ba1ecb2..6f285b5 100644 --- a/zh_CN/guides/knowledge-base/retrieval_test_and_citation.md +++ b/zh_CN/guides/knowledge-base/retrieval_test_and_citation.md @@ -4,11 +4,11 @@ Dify 知识库内提供了文本召回测试的功能，用于调试不同检索方式及参数配置下的召回效果。你可以在 **源文本** 输入框输入常见的用户问题，点击 **测试** 并在右侧的 **召回段落** 查看召回结果。在 **最近查询** 内可以查看到历史的查询记录；若知识库已关联至应用内，由应用内触发的知识库查询也可以在此查看记录。 -

召回测试

+

召回测试

点击源文本输入框右上角的图标可以更换当前知识库的检索方式和具体参数，**保存之后仅在召回测试的调试过程中生效**。在召回测试完成调试并确认更改知识库的检索参数时，需要在 [知识库设置 > 检索设置](retrieval\_test\_and\_citation.md#zhi-shi-ku-she-zhi) 中进行更改。 -

召回测试-检索设置

+

召回测试-检索设置

**召回测试建议步骤：** @@ -27,8 +27,8 @@ Dify 知识库内提供了文本召回测试的功能，用于调试不同检索 在应用内测试知识库效果时，你可以进入 **工作室 -- 添加功能 -- 引用归属**，打开引用归属功能。 -

打开引用与归属功能

+

打开引用与归属功能

开启功能后，当大语言模型回复问题时引用来自知识库的内容时，可以在回复内容下面查看到具体的引用段落信息，包括**原始分段文本、分段序号、匹配度**等。点击引用分段上方的 **跳转至知识库 ，**可以快捷访问该分段所在的知识库分段列表，方便开发者进行调试编辑。 -

查看回复内容的引用信息

+

查看回复内容的引用信息

diff --git a/zh_CN/guides/knowledge-base/sync-from-notion.md b/zh_CN/guides/knowledge-base/sync-from-notion.md index 1667229..794c431 100644 --- a/zh_CN/guides/knowledge-base/sync-from-notion.md +++ b/zh_CN/guides/knowledge-base/sync-from-notion.md @@ -37,11 +37,11 @@ Notion集成分为**内部集成**（internal integration）和**外部集成** 点击“**New integration**”按钮，类型默认是 **Internal**（不可修改），选择关联的空间，输入集成名称并上传 logo 后，点击“Submit”，集成创建成功。 -
+
创建集成后，您可以根据需要在 Capabilities 选项卡下更新其设置，并在 Secrets 下点击 “Show” 按钮然后复制 Secrets。 -
+
复制后回到 Dify 源代码下，在 **.env** 文件里配置相关环境变量，环境变量如下： diff --git a/zh_CN/guides/model-configuration/README.md b/zh_CN/guides/model-configuration/README.md index 580cf90..036724c 100644 --- a/zh_CN/guides/model-configuration/README.md +++ b/zh_CN/guides/model-configuration/README.md @@ -35,7 +35,7 @@ Dify 目前已支持主流的模型供应商，例如 OpenAI 的 GPT 系列、An Dify 在需要模型时，会根据使用场景来选择设置过的默认模型。在 `设置 > 模型供应商` 中设置默认模型。 -
+
### 接入模型设置 diff --git a/zh_CN/guides/model-configuration/replicate.md b/zh_CN/guides/model-configuration/replicate.md index aa89d3e..1c9ea24 100644 --- a/zh_CN/guides/model-configuration/replicate.md +++ b/zh_CN/guides/model-configuration/replicate.md @@ -9,7 +9,7 @@ Dify 支持接入 Replicate 上的 [Language models](https://replicate.com/colle 3. 挑选模型。在 [Language models](https://replicate.com/collections/language-models) 和 [Embedding models](https://replicate.com/collections/embedding-models) 下挑选模型。 4. 在 Dify 的 `设置 > 模型供应商 > Replicate` 中添加模型。 -
+
API key 为第 2 步中设置的 API Key。Model Name 和 Model Version 可以在模型详情页中找到： diff --git a/zh_CN/guides/workflow/node/answer.md b/zh_CN/guides/workflow/node/answer.md index ac3f076..0dcf555 100644 --- a/zh_CN/guides/workflow/node/answer.md +++ b/zh_CN/guides/workflow/node/answer.md @@ -14,8 +14,8 @@ 示例2：输出图片+LLM回复 -
+
-
+
提示：直接回复节点可以不作为最终的输出节点，作为流程过程节点时，可以在中间步骤流式输出结果。 diff --git a/zh_CN/guides/workflow/node/ifelse.md b/zh_CN/guides/workflow/node/ifelse.md index cc86152..71c355f 100644 --- a/zh_CN/guides/workflow/node/ifelse.md +++ b/zh_CN/guides/workflow/node/ifelse.md @@ -25,7 +25,7 @@ ### 场景 -
+
以上图**文本总结工作流**为例 @@ -37,4 +37,4 @@ 涉及复杂的条件判断时，可以设置多重条件判断，在条件之间设置 **AND** 或者 **OR**，即在条件之间取**交集**或者**并集**。 -

多重条件判断

+

多重条件判断

diff --git a/zh_CN/guides/workflow/node/knowledge_retrieval.md b/zh_CN/guides/workflow/node/knowledge_retrieval.md index d42238f..b561ddf 100644 --- a/zh_CN/guides/workflow/node/knowledge_retrieval.md +++ b/zh_CN/guides/workflow/node/knowledge_retrieval.md @@ -18,7 +18,7 @@ ### 3 如何配置 -

知识检索配置

+

知识检索配置

**配置流程：** @@ -43,6 +43,6 @@ 当用户提问时，若在知识检索中召回了相关文本，文本内容会作为上下文变量中的值填入提示词，提供 LLM 回复问题；若未在知识库检索中召回相关的文本，上下文变量值为空，LLM 则会直接回复用户问题。 -

配置下游 LLM 节点

+

配置下游 LLM 节点

该变量除了可以作为 LLM 回复问题时的提示词上下文作为外部知识参考引用，另外由于其数据结构中包含了分段引用信息，同时可以支持应用端的 [**引用与归属**](../../knowledge-base/retrieval\_test\_and\_citation.md#id-2-yin-yong-yu-gui-shu) 功能。 diff --git a/zh_CN/guides/workflow/node/llm.md b/zh_CN/guides/workflow/node/llm.md index c132497..a9a5c8e 100644 --- a/zh_CN/guides/workflow/node/llm.md +++ b/zh_CN/guides/workflow/node/llm.md @@ -4,7 +4,7 @@ 调用大语言模型回答问题或者对自然语言进行处理。 -

LLM 节点

+

LLM 节点

*** diff --git a/zh_CN/guides/workflow/node/parameter_extractor.md b/zh_CN/guides/workflow/node/parameter_extractor.md index 2b169eb..a34ed00 100644 --- a/zh_CN/guides/workflow/node/parameter_extractor.md +++ b/zh_CN/guides/workflow/node/parameter_extractor.md @@ -1,3 +1,58 @@ # 参数提取 🚧 维护中 + +### 1 定义 + +利用 LLM 从自然语言推理并提取结构化参数，用于后置的工具调用或 HTTP 请求。 + +*** + +### 2 场景 + +1. **从自然语言中提供工具所需的关键参数提取**，如构建一个简单的对话式 Arxiv 论文检索应用。 + +在该示例中：Arxiv 论文检索工具的输入参数要求为 **论文作者** 或 **论文编号**，参数提取器从问题“这篇论文中讲了什么内容：2405.10739”中提取出论文编号 2405.10739，并作为工具参数进行精确查询。 + +
+ +2. **将文本转换为结构化数据**，如长故事迭代生成应用中，作为[迭代节点](iteration.md)的前置步骤，将文本格式的章节内容转换为数组格式，方便迭代节点进行多轮生成处理。 + +
+ +3. **提取结构化数据并使用** [**HTTP 请求**](http\_request.md) ，可请求任意可访问的 URL ，适用于获取外部检索结果、webhook、生成图片等情景。 + +*** + +### 3 如何配置 + +
+ +**配置步骤** + +1. 选择输入变量，一般为用于提取参数的变量输入 +2. 选择模型，参数提取器的提取依靠的是 LLM 的推理和结构化生成能力 +3. 定义提取参数，可以手动添加编辑，也可以从已有工具中直接导入 +4. 编写指令，在提取复杂的参数时，编写示例可以帮助 LLM 提升生成的效果和稳定性 + +**高级设置** + +**推理模式** + +部分模型同时支持两种推理模式，通过函数/工具调用或是纯提示词的方式实现参数提取，在指令遵循能力上有所差别。例如某些模型在函数调用效果欠佳的情况下可以切换成提示词推理。 + +* Function Call/Tool Call +* Prompt + +**记忆** + +开启记忆后问题分类器的每次输入将包含对话中的聊天历史，以帮助 LLM 理解上文，提高对话交互中的问题理解能力。 + +**输出变量** + +* 提取定义的变量 +* 节点内置变量 + +`__is_success Number 提取是否成功` 成功时值为 1，失败时值为 0。 + +`__reason String` 提取错误原因 diff --git a/zh_CN/guides/workflow/node/question_classifier.md b/zh_CN/guides/workflow/node/question_classifier.md index 98c90fe..46de871 100644 --- a/zh_CN/guides/workflow/node/question_classifier.md +++ b/zh_CN/guides/workflow/node/question_classifier.md @@ -14,7 +14,7 @@ 下图为产品客服场景的示例工作流模板： -
+
在该场景中我们设置了 3 个分类标签/描述： @@ -32,7 +32,7 @@ ### 3 如何配置 -
+
**配置步骤：** diff --git a/zh_CN/learn-more/extended-reading/retrieval-augment/rerank.md b/zh_CN/learn-more/extended-reading/retrieval-augment/rerank.md index 61353f8..3b57e0e 100644 --- a/zh_CN/learn-more/extended-reading/retrieval-augment/rerank.md +++ b/zh_CN/learn-more/extended-reading/retrieval-augment/rerank.md @@ -38,7 +38,7 @@ Dify 目前已支持 Cohere Rerank 模型，通过进入“模型供应商-> Coh 通过进入“数据集->创建数据集->检索设置”页面并在添加 Rerank 设置。除了在创建数据集可以设置 Rerank ，你也可以在已创建的数据集设置内更改 Rerank 配置，在应用编排的数据集召回模式设置中更改 Rerank 配置。 -

数据集检索模式中设置 Rerank 模型

+

数据集检索模式中设置 Rerank 模型

\*\*TopK：\*\*用于设置 Rerank 后返回相关文档的数量。 @@ -50,4 +50,4 @@ Dify 目前已支持 Cohere Rerank 模型，通过进入“模型供应商-> Coh 关于多路召回模式的说明：🔗 -

数据集多路召回模式中设置 Rerank 模型

+

数据集多路召回模式中设置 Rerank 模型

diff --git a/zh_CN/learn-more/extended-reading/retrieval-augment/retrieval.md b/zh_CN/learn-more/extended-reading/retrieval-augment/retrieval.md index 6fddfc5..23d4e36 100644 --- a/zh_CN/learn-more/extended-reading/retrieval-augment/retrieval.md +++ b/zh_CN/learn-more/extended-reading/retrieval-augment/retrieval.md @@ -26,7 +26,7 @@ 以下是多路召回模式的技术流程图： -

多路召回

+

多路召回

由于多路召回模式不依赖于模型的推理能力或数据集描述，该模式在多数据集检索时能够获得质量更高的召回效果，除此之外加入 Rerank 步骤也能有效改进文档召回效果。因此，当创建的知识库问答应用关联了多个数据集时，我们更推荐将召回模式配置为多路召回。\ \ diff --git a/zh_CN/learn-more/faq/llms-use-faq.md b/zh_CN/learn-more/faq/llms-use-faq.md index 1383dbd..59e9d8b 100644 --- a/zh_CN/learn-more/faq/llms-use-faq.md +++ b/zh_CN/learn-more/faq/llms-use-faq.md @@ -125,7 +125,7 @@ Query or prefix prompt is too long, you can reduce the preix prompt, or shrink t 如下方表格示例，仅需保留第二行的表头，首行（表格1）为多余表头，需删掉。 -
+
### 20 买了 ChatGPT plus，为什么在 dify 里还不能使用 GPT4？