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index 0fa44bb..7b3e9f4 100644
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diff --git a/zh_CN/.gitbook/assets/image (9).png b/zh_CN/.gitbook/assets/image (9).png
index 7b3e9f4..6bc95ab 100644
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diff --git a/zh_CN/guides/application-publishing/developing-with-apis.md b/zh_CN/guides/application-publishing/developing-with-apis.md
index a3526a1..1d87db8 100644
--- a/zh_CN/guides/application-publishing/developing-with-apis.md
+++ b/zh_CN/guides/application-publishing/developing-with-apis.md
@@ -15,7 +15,7 @@ Dify 基于“**后端即服务**”理念为所有应用提供了 API,为 AI
选择一个应用,在应用(Apps)左侧导航中可以找到**访问 API(API Access)**。在该页面中你可以查看 Dify 提供的 API 文档,并管理可访问 API 的凭据。
-
访问 API
+.png)
访问 API
例如你是一个咨询公司的开发部分,你可以基于公司的私有数据库提供 AI 能力给终端用户或开发者,但开发者无法掌握你的数据和 AI 逻辑设计,从而使得服务可以安全、可持续的交付并满足商业目的。
diff --git a/zh_CN/guides/application_orchestrate/agent.md b/zh_CN/guides/application_orchestrate/agent.md
index e3e7372..a03f2ee 100644
--- a/zh_CN/guides/application_orchestrate/agent.md
+++ b/zh_CN/guides/application_orchestrate/agent.md
@@ -8,19 +8,19 @@
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。
- (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
探索-智能助手应用模板
+ (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
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。
- (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
工作室-构建智能助手
+ (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
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。
- (1) (1).png)
选择智能助手的推理模型
+ (1) (1) (1).png)
选择智能助手的推理模型
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。
- (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
编排智能助手的指令提示词
+ (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
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)。
- (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
添加助手需要的工具
+ (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
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。
@@ -40,22 +40,22 @@
在 Agent 配置中,你可以修改助手的迭代次数限制。
-.png)
Function Calling 模式
+ (1).png)
Function Calling 模式
-.png)
ReAct 模式
+ (1).png)
ReAct 模式
### 配置对话开场白
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。
- (1) (1) (1) (1) (1) (1).png)
配置会话开场白和开场问题
+ (1) (1) (1) (1) (1) (1) (1).png)
配置会话开场白和开场问题
### 调试与预览
编排完智能助手之后,你可以在发布成应用之前进行调试与预览,查看助手的任务完成效果。
- (1).png)
调试与预览
+ (1) (1).png)
调试与预览
### 应用发布
- (1).png)
应用发布为 Webapp
+ (1) (1).png)
应用发布为 Webapp
diff --git a/zh_CN/guides/application_orchestrate/conversation-application.md b/zh_CN/guides/application_orchestrate/conversation-application.md
index 798c702..bd111fb 100644
--- a/zh_CN/guides/application_orchestrate/conversation-application.md
+++ b/zh_CN/guides/application_orchestrate/conversation-application.md
@@ -22,7 +22,7 @@
应用成功后会自动跳转到应用概览页。点击左侧菜单 **编排** 来编排应用。
-.png)
应用编排
+ (1).png)
应用编排
**填写提示词**
diff --git a/zh_CN/guides/biao-zhu/annotation-reply.md b/zh_CN/guides/biao-zhu/annotation-reply.md
index 449ca73..3b58acd 100644
--- a/zh_CN/guides/biao-zhu/annotation-reply.md
+++ b/zh_CN/guides/biao-zhu/annotation-reply.md
@@ -23,7 +23,7 @@
通过进入“应用构建->添加功能”开启标注回复开关:
- (1).png)
提示词编排中开启标注回复
+ (1) (1).png)
提示词编排中开启标注回复
开启时需要先设置标注回复的参数,可设置参数包括:Score 阈值 和 Embedding 模型
@@ -33,27 +33,27 @@
点击保存并启用时,该设置会立即生效,系统将对所有已保存的标注利用 Embedding 模型生成嵌入保存。
- (1).png)
标注回复参数设置
+ (1) (1).png)
标注回复参数设置
### 在会话调试页添加标注
你可以在调试与预览页面直接在模型回复信息上添加或编辑标注。
- (1).png)
添加标注回复
+ (1) (1).png)
添加标注回复
编辑成你需要的高质量回复并保存。
- (1).png)
编辑标注回复
+ (1) (1).png)
编辑标注回复
再次输入同样的用户问题,系统将使用已保存的标注直接回复用户问题。
-.png)
通过已保存的标注回复用户问题
+ (1).png)
通过已保存的标注回复用户问题
### 日志与标注中开启标注回复
通过进入“应用构建->日志与标注->标注”开启标注回复开关:
- (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
日志与标注中开启标注回复
+ (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
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
@@ -63,22 +63,22 @@
**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。
- (1) (1) (1) (1) (1) (1) (1) (1).png)
设置标注回复参数
+ (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
设置标注回复参数
### 批量导入标注问答对
在批量导入功能内,你可以下载标注导入模板,按模版格式编辑标注问答对,编辑好后在此批量导入。
- (1) (1) (1).png)
批量导入标注问答对
+ (1) (1) (1) (1).png)
批量导入标注问答对
### 批量导出标注问答对
通过标注批量导出功能,你可以一次性导出系统内已保存的所有标注问答对。
- (1) (1) (1).png)
批量导出标注问答对
+ (1) (1) (1) (1).png)
批量导出标注问答对
### 查看标注回复命中历史
在标注命中历史功能内,你可以查看所有命中该条标注的编辑历史、命中的用户问题、回复答案、命中来源、匹配相似分数、命中时间等信息,你可以根据这些系统信息持续改进你的标注内容。
- (1) (1).png)
查看标注回复命中历史
+ (1) (1) (1).png)
查看标注回复命中历史
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 4cf8ad2..9d06213 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。
- (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
数据集检索模式中设置 Rerank 模型
+ (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
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。
- (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
数据集多路召回模式中设置 Rerank 模型
+ (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
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 47f858c..dc01fef 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。
- (1) (1) (1) (1) (1) (1) (1).png)
查看已上传的文档分段
+ (1) (1) (1) (1) (1) (1) (1) (1).png)
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。
- (1) (1) (1) (1) (1).png)
批量添加自定义分段
+ (1) (1) (1) (1) (1) (1).png)
批量添加自定义分段
***
@@ -46,7 +46,7 @@
在分段列表内,你可以对已添加的分段内容直接进行编辑修改。包括分段的文本内容和关键词。
- (1).png)
编辑文档分段
+ (1) (1).png)
编辑文档分段
***
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 062c6ad..0106d11 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。
- (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
召回测试
+ (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
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。
- (1) (1) (1) (1) (1) (1) (1) (1).png)
召回测试-检索设置
+ (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
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。
- (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
打开引用与归属功能
+ (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
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。
- (1) (1) (1) (1) (1) (1) (1).png)
查看回复内容的引用信息
+ (1) (1) (1) (1) (1) (1) (1) (1).png)
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 6bce516..9f5af64 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:
@@ -53,11 +53,11 @@ Notion集成分为**内部集成**(internal integration)和**外部集成**
**需要将 internal 集成升级为 public 集成**,导航到集成的 Distribution 页面,然后切换开关以公开集成。将开关切换到公共设置,您需要在下面的 Organization Information 表单中填写其他信息,包括您的公司名称、网站和重定向 URL 等信息,然后点击“Submit”按钮。
-
+
在集成的设置页面中成功公开集成后,您将能够在密钥选项卡中访问集成的密钥:
-
+
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 61f3993..c3f3748 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/hugging-face.md b/zh_CN/guides/model-configuration/hugging-face.md
index c5ec8cf..64e2a86 100644
--- a/zh_CN/guides/model-configuration/hugging-face.md
+++ b/zh_CN/guides/model-configuration/hugging-face.md
@@ -11,7 +11,7 @@ Dify 支持 Text-Generation 和 Embeddings,以下是与之对应的 Hugging Fa
2. 设置 Hugging Face 的 API key([获取地址](https://huggingface.co/settings/tokens))。
3. 进入 [Hugging Face 模型列表页](https://huggingface.co/models),选择对应的模型类型。
-
+
Dify 支持用两种方式接入 Hugging Face 上的模型:
@@ -24,11 +24,11 @@ Dify 支持用两种方式接入 Hugging Face 上的模型:
模型详情页右侧有包含 Hosted inference API 的 区域才支持 Hosted inference API 。如下图所:
-
+
在模型详情页,可以获得模型的名称。
-
+
#### 2 在 Dify 中使用接入模型
@@ -44,17 +44,17 @@ API Token 为文章开头设置的 API Key。模型名字为上一步获得的
模型详情页右侧的 `Deploy` 按钮下有 Inference Endpoints 选项的模型才支持 Inference Endpoint。如下图所示:
-
+
#### 2 部署模型
点击模型的部署按钮,选择 Inference Endpoint 选项。如果之前没绑过银行卡的,会需要绑卡。按流程走即可。绑过卡后,会出现下面的界面:按需求修改配置,点击左下角的 Create Endpoint 来创建 Inference Endpoint。
-
+
模型部署好后,就可以看到 Endpoint URL。
-
+
#### 3 在 Dify 中使用接入模型
diff --git a/zh_CN/guides/model-configuration/load_balancing.md b/zh_CN/guides/model-configuration/load_balancing.md
index ffad0c8..230db94 100644
--- a/zh_CN/guides/model-configuration/load_balancing.md
+++ b/zh_CN/guides/model-configuration/load_balancing.md
@@ -6,7 +6,7 @@
你可以在 **模型供应商 -- 模型列表 -- 设置模型负载均衡** 打开该功能,并在同一个模型上添加多个凭据 (API key)。
- (1) (1).png)
模型负载均衡
+ (1) (1) (1).png)
模型负载均衡
{% hint style="info" %}
模型负载均衡为付费特性,您可以通过[订阅 SaaS 付费服务](../../getting-started/cloud.md#ding-yue-ji-hua)或者购买企业版来开启该功能。
@@ -14,17 +14,17 @@
默认配置中的 API Key 为初次配置模型供应商时添加的凭据,您需要点击 **增加配置** 添加同一模型的不同 API Key 来正常使用负载均衡功能。
- (1) (1).png)
配置负载均衡
+ (1) (1) (1).png)
配置负载均衡
**需要额外添加至少 1 个模型凭据**即可保存并开启负载均衡。
你也可以将已配置的凭据**临时停用**或者**删除**。
-
+
配置完成后再模型列表内会显示所有已开启负载均衡的模型。
-.png)
开启负载均衡
+ (1).png)
开启负载均衡
{% hint style="info" %}
默认情况下,负载均衡使用 Round-robin 策略。如果触发速率限制,将应用 1 分钟的冷却时间。
@@ -32,4 +32,4 @@
你也可以从 **添加模型** 配置负载均衡,配置流程与上面一致。
-.png)
从添加模型配置负载均衡
+ (1).png)
从添加模型配置负载均衡
diff --git a/zh_CN/guides/model-configuration/replicate.md b/zh_CN/guides/model-configuration/replicate.md
index 3dc3ebb..b883318 100644
--- a/zh_CN/guides/model-configuration/replicate.md
+++ b/zh_CN/guides/model-configuration/replicate.md
@@ -9,8 +9,8 @@ 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/model-configuration/xinference.md b/zh_CN/guides/model-configuration/xinference.md
index 598539b..38113ab 100644
--- a/zh_CN/guides/model-configuration/xinference.md
+++ b/zh_CN/guides/model-configuration/xinference.md
@@ -23,13 +23,13 @@
```
Xinference 默认会在本地启动一个 worker,端点为:`http://127.0.0.1:9997`,端口默认为 `9997`。 默认只可本机访问,可配置 `-H 0.0.0.0`,非本地客户端可任意访问。 如需进一步修改 host 或 port,可查看 xinference 的帮助信息:`xinference-local --help`。
- > 使用 Dify Docker 部署方式的需要注意网络配置,确保 Dify 容器可以访问到 Xinference 的端点,Dify 容器内部无法访问到 localhost,需要使用宿主机 IP 地址。
+ > 使用 Dify Docker 部署方式的需要注意网络配置,确保 Dify 容器可以访问到 Xinference 的端点,Dify 容器内部无法访问到 localhost,需要使用宿主机 IP 地址。
3. 创建并部署模型
进入 `http://127.0.0.1:9997` 选择需要部署的模型和规格进行部署,如下图所示:
-
+
由于不同模型在不同硬件平台兼容性不同,请查看 [Xinference 内置模型](https://inference.readthedocs.io/en/latest/models/builtin/index.html) 确定创建的模型是否支持当前硬件平台。
4. 获取模型 UID
diff --git a/zh_CN/guides/monitoring/README.md b/zh_CN/guides/monitoring/README.md
index c58cb39..79a2493 100644
--- a/zh_CN/guides/monitoring/README.md
+++ b/zh_CN/guides/monitoring/README.md
@@ -2,4 +2,4 @@
你可以在 **概览** 内监控、跟踪应用程序在生产环境中的性能,在数据分析仪表盘内分析生产环境中应用的使用成本、延迟、用户反馈、性能等指标,并通过持续调试、迭代不断改进你的应用程序。
-.png)
概览
+ (1).png)
概览
diff --git a/zh_CN/guides/monitoring/analysis.md b/zh_CN/guides/monitoring/analysis.md
index 7654a30..2212363 100644
--- a/zh_CN/guides/monitoring/analysis.md
+++ b/zh_CN/guides/monitoring/analysis.md
@@ -2,7 +2,7 @@
**概览 -- 数据分析** 内显示了用量、活跃用户数和 LLM 调用消耗等,这使你可以持续改进应用运营的效果、活跃度、经济性。我们将逐步提供更多有用的可视化能力,请告诉我们你想要的。
- (1).png)
概览—数据分析
+ (1) (1).png)
概览—数据分析
***
diff --git a/zh_CN/guides/monitoring/integrate_external_ops_tools/integrate_langsmith.md b/zh_CN/guides/monitoring/integrate_external_ops_tools/integrate_langsmith.md
index 0d270c9..301c9f5 100644
--- a/zh_CN/guides/monitoring/integrate_external_ops_tools/integrate_langsmith.md
+++ b/zh_CN/guides/monitoring/integrate_external_ops_tools/integrate_langsmith.md
@@ -1,3 +1,61 @@
# 集成 LangSmith
-🚧 等待维护中
+### 1 什么是 LangSmith
+
+LangSmith 是一个用于构建生产级 LLM 应用程序的平台,它用于开发、协作、测试、部署和监控 LLM 应用程序。
+
+{% hint style="info" %}
+LangSmith 官网介绍:[https://www.langchain.com/langsmith](https://www.langchain.com/langsmith)
+{% endhint %}
+
+***
+
+### 2 如何配置 LangSmith
+
+1. 登录官网注册并登录 LangSmith:[https://www.langchain.com/langsmith](https://www.langchain.com/langsmith)
+2. 在 LangSmith 内创建项目,登录后在主页点击 New Project 创建一个自己的项目,**项目**将用于与 Dify 内的**应用**关联进行数据监测。
+
+
+
+创建完成之后在 Projects 内可以查看到所有已创建的项目。
+
+
+
+3. 创建项目凭据,在左侧边栏内找到项目设置 Setting
+
+.png)
项目设置
+
+点击 Create API Key,创建一个项目凭据。
+
+
+
+选择 **Personal Access Token** ,用于后续的 API 身份校验。
+
+
+
+将创建的 API key 复制保存。
+
+
+
+4. 在 Dify 应用内配置 LangSmith,打开需要监测的应用,在侧边菜单打开**监测**,在页面中选择**配置。**
+
+.png)
配置 LangSmith
+
+
+
+点击配置后,将在 LangSmith 内创建的 **API Key** 和**项目名**粘贴到配置内并保存。
+
+.png)
配置 LangSmith
+
+成功保存后可以在当前页面查看到状态,显示已启动即正在监测。
+
+.png)
查看配置状态
+
+### 3 在 LangSmith 内查看监测数据
+
+配置完成后, Dify 内应用的调试或生产数据可以在 LangSmith 查看监测数据
+
+.png)
在 Dify 内调试数据
+
+.png)
在 LangSmith 内查看监控数据
+
diff --git a/zh_CN/guides/workflow/node/answer.md b/zh_CN/guides/workflow/node/answer.md
index e0c2bbe..ecff355 100644
--- a/zh_CN/guides/workflow/node/answer.md
+++ b/zh_CN/guides/workflow/node/answer.md
@@ -18,9 +18,9 @@
**示例2:**输出图片+LLM回复
-
+
-
+
{% hint style="info" %}
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/http_request.md b/zh_CN/guides/workflow/node/http_request.md
index 2be51fc..ca405a4 100644
--- a/zh_CN/guides/workflow/node/http_request.md
+++ b/zh_CN/guides/workflow/node/http_request.md
@@ -15,7 +15,7 @@
你可以通过配置 HTTP 请求的包括 URL、请求头、查询参数、请求体内容以及认证信息等。
-.png)
HTTP 请求配置
+ (1).png)
HTTP 请求配置
***
@@ -23,6 +23,6 @@
这个节点的一个实用特性是能够根据场景需要,在请求的不同部分动态插入变量。比如在处理客户评价请求时,你可以将用户名或客户ID、评价内容等变量嵌入到请求中,以定制化自动回复信息或获取特定客户信息并发送相关资源至特定的服务器。
- (1).png)
客户评价分类
+ (1) (1).png)
客户评价分类
HTTP 请求的返回值包括响应体、状态码、响应头和文件。值得注意的是,如果响应中包含了文件(目前仅支持图片类型),这个节点能够自动将文件保存下来,供流程后续步骤使用。这样的设计不仅提高了处理效率,也使得处理带有文件的响应变得简单直接。
diff --git a/zh_CN/guides/workflow/node/ifelse.md b/zh_CN/guides/workflow/node/ifelse.md
index b871119..859dcf1 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**。
- (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
多重条件判断
+ (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
多重条件判断
diff --git a/zh_CN/guides/workflow/node/iteration.md b/zh_CN/guides/workflow/node/iteration.md
index 3f51e50..275a7a9 100644
--- a/zh_CN/guides/workflow/node/iteration.md
+++ b/zh_CN/guides/workflow/node/iteration.md
@@ -64,7 +64,7 @@
#### **示例 2:长文章迭代生成器(另一种编排方式)**
-
+
* 在 **开始节点** 内输入故事标题和大纲
* 使用 **LLM 节点** 生成文章小标题,以及小标题对应的内容
@@ -138,7 +138,7 @@
**使用代码节点转换**
- (1) (1) (1).png)
代码节点转换
+ (1) (1) (1) (1).png)
代码节点转换
```python
def main(articleSections: list):
@@ -150,7 +150,7 @@ def main(articleSections: list):
**使用模板节点转换**
- (1).png)
模板节点转换
+ (1) (1).png)
模板节点转换
```django
{{ articleSections | join("\n") }}
diff --git a/zh_CN/guides/workflow/node/knowledge_retrieval.md b/zh_CN/guides/workflow/node/knowledge_retrieval.md
index 768b8c6..db010a2 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
- (1) (1) (1) (1).png)
知识检索配置
+ (1) (1) (1) (1) (1).png)
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。
- (1) (1) (1) (1).png)
配置下游 LLM 节点
+ (1) (1) (1) (1) (1).png)
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 0912579..21b07d5 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。
- (1) (1) (1) (1) (1) (1) (1).png)
LLM 节点
+ (1) (1) (1) (1) (1) (1) (1) (1).png)
LLM 节点
***
diff --git a/zh_CN/guides/workflow/node/parameter_extractor.md b/zh_CN/guides/workflow/node/parameter_extractor.md
index 5a46d31..6fd34a0 100644
--- a/zh_CN/guides/workflow/node/parameter_extractor.md
+++ b/zh_CN/guides/workflow/node/parameter_extractor.md
@@ -16,11 +16,11 @@ Dify 工作流内提供了丰富的[工具](../../gong-ju.md)选择,其中大
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。
-.png)
Arxiv 论文检索工具
+ (1).png)
Arxiv 论文检索工具
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。
@@ -28,7 +28,7 @@ Dify 工作流内提供了丰富的[工具](../../gong-ju.md)选择,其中大
### 3 如何配置
-
+
**配置步骤**
diff --git a/zh_CN/guides/workflow/node/question_classifier.md b/zh_CN/guides/workflow/node/question_classifier.md
index 92b93df..ce48dc7 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
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**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 983de32..96fe645 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。
- (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
数据集检索模式中设置 Rerank 模型
+ (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
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:🔗
- (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
数据集多路召回模式中设置 Rerank 模型
+ (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
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 89c40ca..d6e964e 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:
- (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
多路召回
+ (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1).png)
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 2f65f8b..b826d5a 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。
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### 20 买了 ChatGPT plus,为什么在 dify 里还不能使用 GPT4?