acedatacloud-dev · Oct 6, 2026 · Oct 6, 2026 · Oct 6, 2026 · Oct 6, 2026
diff --git a/docs.json b/docs.json
@@ -70,6 +70,16 @@
                   "zh-Hans/concepts/async-tasks"
                 ]
               },
+              {
+                "group": "生态集成",
+                "icon": "puzzle-piece",
+                "pages": [
+                  "zh-Hans/integrations/n8n",
+                  "zh-Hans/integrations/dify",
+                  "zh-Hans/integrations/gitlab-ci",
+                  "zh-Hans/integrations/open-webui"
+                ]
+              },
               {
                 "group": "AI 聊天",
                 "icon": "comments",
@@ -812,6 +822,16 @@
                   "en/concepts/async-tasks"
                 ]
               },
+              {
+                "group": "Integrations",
+                "icon": "puzzle-piece",
+                "pages": [
+                  "en/integrations/n8n",
+                  "en/integrations/dify",
+                  "en/integrations/gitlab-ci",
+                  "en/integrations/open-webui"
+                ]
+              },
               {
                 "group": "AI Chat",
                 "icon": "comments",

diff --git a/en/integrations/dify.mdx b/en/integrations/dify.mdx
@@ -0,0 +1,29 @@
+---
+title: "Use AceDataCloud models in Dify"
+description: "Configure an OpenAI API-compatible model provider in Dify."
+---
+
+Dify's OpenAI API-compatible model provider can call AceDataCloud chat models. You can configure a model in Dify without installing an AceDataCloud plugin.
+
+## Configure the model
+
+1. Create an [AceDataCloud API token](https://platform.acedata.cloud/console/applications).
+2. In Dify, open **Settings → Model Provider** and install [OpenAI-API-compatible](https://marketplace.dify.ai/plugin/langgenius/openai_api_compatible) from the Marketplace if it is not already installed.
+3. Add a chat model using these values:
+
+| Field | Value |
+| --- | --- |
+| API Base URL | `https://api.acedata.cloud/v1` |
+| API key | Your AceDataCloud token |
+| Model name | `gpt-5.5`, or another [supported chat model](https://platform.acedata.cloud/documents/openai-chat-completions) |
+| Model type | LLM |
+| Completion mode | Chat |
+| API type | Chat Completions API |
+
+4. Save and test the model, then select it in a Dify **LLM** node.
+
+The Base URL ends in `/v1`. Do not add `/chat/completions`; Dify adds the operation path. The older `/openai/v1` URL does not serve this endpoint.
+
+Each test or workflow run uses your AceDataCloud balance. Check the model's current price and Dify's retry settings before publishing a workflow. Keep the API key in Dify's provider credential settings, never in a prompt or workflow export.
+
+For the request and response schema, see [Chat Completions](/en/guides/openai/openai_chat_completions).
diff --git a/en/integrations/gitlab-ci.mdx b/en/integrations/gitlab-ci.mdx
@@ -0,0 +1,19 @@
+---
+title: "Call AceDataCloud from GitLab CI"
+description: "Run a manual pipeline job that summarizes a commit title with a chat model."
+---
+
+Use a GitLab CI job to call the AceDataCloud Chat Completions API. The [sample pipeline](https://raw.githubusercontent.com/AceDataCloud/Docs/main/examples/gitlab/acedatacloud-chat.gitlab-ci.yml) summarizes the latest commit title and saves the result as a short-lived artifact. The job is manual and runs only on the default branch.
+
+## Set up the job
+
+1. Create an [AceDataCloud API token](https://platform.acedata.cloud/console/applications).
+2. In your GitLab project, open **Settings → CI/CD → Variables**. Add `ACEDATACLOUD_API_TOKEN` as a masked and hidden variable. Protect the variable and the default branch.
+3. Copy the [sample pipeline YAML](https://raw.githubusercontent.com/AceDataCloud/Docs/main/examples/gitlab/acedatacloud-chat.gitlab-ci.yml) into your `.gitlab-ci.yml`. If your pipeline already has `stages`, add `report` to that list and copy only the job.
+4. Run a pipeline on the default branch, start the manual **acedatacloud_commit_summary** job, and download `summary.txt` from its artifacts.
+
+The job sends `CI_COMMIT_TITLE` to AceDataCloud. Do not send confidential commit text unless your project's data policy allows it. Each manual run makes one billable API request; check the model's current price before enabling other triggers. The token stays in GitLab's CI/CD variable store and is not written to the artifact.
+
+To summarize a different input, change the `jq --arg title` line and the prompt in the sample. Keep the token in the CI/CD variable and encode user-controlled text with `jq --arg`, not shell string interpolation inside JSON. The request schema is documented in [Chat Completions](/en/guides/openai/openai_chat_completions).
+
+This is a copyable CI example. Publishing a reusable component to the [GitLab CI/CD Catalog](https://docs.gitlab.com/ci/components/) requires a GitLab-hosted component project and a release.
diff --git a/en/integrations/n8n.mdx b/en/integrations/n8n.mdx
@@ -0,0 +1,22 @@
+---
+title: "Use AceDataCloud in n8n"
+description: "Import a chat workflow and connect it to your AceDataCloud API token."
+---
+
+Use n8n's HTTP Request node to call AceDataCloud. The [sample workflow](https://raw.githubusercontent.com/AceDataCloud/Docs/main/examples/n8n/acedatacloud-chat.json) sends a prompt to the Chat Completions API and returns the response and token usage. It uses only built-in n8n nodes.
+
+## Import the workflow
+
+1. Create an [AceDataCloud API token](https://platform.acedata.cloud/console/applications).
+2. In n8n, create a workflow and choose **Import from URL**. Paste the [sample workflow URL](https://raw.githubusercontent.com/AceDataCloud/Docs/main/examples/n8n/acedatacloud-chat.json). You can also download the JSON file and choose **Import from File**.
+3. Open **AceDataCloud chat**. Under **Authentication → Generic Credential Type**, select **Bearer Auth** and create a credential containing your AceDataCloud token. Paste only the token; n8n adds the `Bearer ` prefix. Save the credential and select it in this node.
+4. In **Set prompt and model**, replace the sample prompt and choose a [supported chat model](https://platform.acedata.cloud/documents/openai-chat-completions).
+5. Select **Execute workflow**. The HTTP Request output contains `choices[0].message.content` and `usage`.
+
+Keep the token in the n8n credential. Do not put it in the workflow JSON or a Set node. Each execution calls a billable API; review the model's current price before activating a schedule or webhook.
+
+## Customize the flow
+
+Replace the manual trigger with your own trigger. Map its text to `prompt` in **Set prompt and model**. The HTTP Request node sends a non-streaming `POST` to `https://api.acedata.cloud/v1/chat/completions`; n8n can then pass the result to another node. For the request and response schema, see [Chat Completions](/en/guides/openai/openai_chat_completions).
+
+If the request fails, check the node's selected credential, whether the token was pasted without a `Bearer ` prefix, the model name, and your available balance. An authentication or billing error should be fixed before rerunning the workflow.
diff --git a/en/integrations/open-webui.mdx b/en/integrations/open-webui.mdx
@@ -0,0 +1,17 @@
+---
+title: "Use AceDataCloud in Open WebUI"
+description: "Connect an AceDataCloud chat model through Open WebUI's OpenAI-compatible provider."
+---
+
+Open WebUI supports OpenAI-compatible Chat Completions endpoints. Connect it directly to AceDataCloud; no custom Pipe or provider module is needed.
+
+## Add the connection
+
+1. Create an [AceDataCloud API token](https://platform.acedata.cloud/console/applications).
+2. In Open WebUI, open **Settings → Admin → Connections**. Under **Manage OpenAI API Connections**, choose **Add Connection**.
+3. Enter `https://api.acedata.cloud/v1` as the URL and your AceDataCloud token as the API key.
+4. Add `gpt-5.5` to **Model IDs** if it is not discovered automatically. Save the connection, select that model in a new chat, and send a short prompt.
+
+Open WebUI's **Verify Connection** calls `/models`; a failed discovery check is not proof that Chat Completions failed. If it fails, add the model ID manually and test an actual chat request. AceDataCloud's `/v1/models` and `/v1/chat/completions` routes accept the same Bearer token. Use only models listed in the [current catalog](https://platform.acedata.cloud/documents/openai-chat-completions).
+
+Keep the token in Open WebUI's connection settings. Each test prompt can incur API charges; check the model's current price. For protocol details, see [Chat Completions](/en/guides/openai/openai_chat_completions) and the [Open WebUI provider guide](https://docs.openwebui.com/getting-started/quick-start/connect-a-provider/starting-with-openai-compatible/).
diff --git a/examples/gitlab/acedatacloud-chat.gitlab-ci.yml b/examples/gitlab/acedatacloud-chat.gitlab-ci.yml
@@ -0,0 +1,34 @@
+stages:
+  - report
+
+acedatacloud_commit_summary:
+  stage: report
+  image: alpine:3.23
+  variables:
+    GIT_STRATEGY: none
+  rules:
+    - if: '$CI_COMMIT_BRANCH == $CI_DEFAULT_BRANCH'
+      when: manual
+      allow_failure: true
+    - when: never
+  before_script:
+    - apk add --no-cache curl jq
+  script:
+    - |
+      set -eu
+      : "${ACEDATACLOUD_API_TOKEN:?Set a masked CI/CD variable}"
+      jq -n --arg title "$CI_COMMIT_TITLE" '{
+        model: "gpt-5.5",
+        messages: [{role: "user", content: ("Summarize this commit title in one sentence: " + $title)}],
+        stream: false
+      }' > request.json
+      curl --fail-with-body --silent --show-error --retry 0 \
+        -H "Authorization: Bearer $ACEDATACLOUD_API_TOKEN" \
+        -H "Content-Type: application/json" \
+        --data @request.json \
+        https://api.acedata.cloud/v1/chat/completions > response.json
+      jq -er '.choices[0].message.content | select(type == "string" and length > 0)' response.json > summary.txt
+  artifacts:
+    paths:
+      - summary.txt
+    expire_in: 1 day
diff --git a/examples/n8n/acedatacloud-chat.json b/examples/n8n/acedatacloud-chat.json
@@ -0,0 +1,78 @@
+{
+  "name": "AceDataCloud: run a chat prompt",
+  "nodes": [
+    {
+      "parameters": {},
+      "id": "e8b9d998-a119-426b-aa8a-47f71848f5a1",
+      "name": "When clicking Execute workflow",
+      "type": "n8n-nodes-base.manualTrigger",
+      "typeVersion": 1,
+      "position": [240, 300]
+    },
+    {
+      "parameters": {
+        "assignments": {
+          "assignments": [
+            {
+              "id": "aa1895bb-3ab4-4517-acfd-c28e7eb7e0c2",
+              "name": "prompt",
+              "value": "Summarize why automation matters in one sentence.",
+              "type": "string"
+            },
+            {
+              "id": "925408cb-5050-48da-a889-fd9e2ed2e45a",
+              "name": "model",
+              "value": "gpt-5.5",
+              "type": "string"
+            }
+          ]
+        },
+        "options": {}
+      },
+      "id": "0aed7632-a0df-47a9-924d-8850b1613260",
+      "name": "Set prompt and model",
+      "type": "n8n-nodes-base.set",
+      "typeVersion": 3.4,
+      "position": [460, 300]
+    },
+    {
+      "parameters": {
+        "method": "POST",
+        "url": "https://api.acedata.cloud/v1/chat/completions",
+        "authentication": "genericCredentialType",
+        "genericAuthType": "httpBearerAuth",
+        "sendBody": true,
+        "contentType": "json",
+        "specifyBody": "json",
+        "jsonBody": "={{ JSON.stringify({ model: $json.model, messages: [{ role: 'user', content: $json.prompt }], stream: false }) }}",
+        "options": {
+          "timeout": 300000,
+          "redirect": {
+            "redirect": {
+              "followRedirects": false
+            }
+          }
+        }
+      },
+      "id": "534f922e-7b7c-46da-a9ef-51701db9d73b",
+      "name": "AceDataCloud chat",
+      "type": "n8n-nodes-base.httpRequest",
+      "typeVersion": 4.3,
+      "position": [700, 300]
+    }
+  ],
+  "connections": {
+    "When clicking Execute workflow": {
+      "main": [[{"node": "Set prompt and model", "type": "main", "index": 0}]]
+    },
+    "Set prompt and model": {
+      "main": [[{"node": "AceDataCloud chat", "type": "main", "index": 0}]]
+    }
+  },
+  "active": false,
+  "settings": {
+    "executionOrder": "v1"
+  },
+  "pinData": {},
+  "tags": []
+}
diff --git a/zh-Hans/integrations/dify.mdx b/zh-Hans/integrations/dify.mdx
@@ -0,0 +1,29 @@
+---
+title: "在 Dify 中使用 AceDataCloud 模型"
+description: "用 Dify 的 OpenAI API 兼容模型供应商接入 AceDataCloud。"
+---
+
+Dify 的 OpenAI API 兼容模型供应商可以调用 AceDataCloud 聊天模型。配置模型时无需安装 AceDataCloud 专属插件。
+
+## 配置模型
+
+1. [创建 AceDataCloud API Token](https://platform.acedata.cloud/console/applications)。
+2. 在 Dify 中打开 **设置 → 模型供应商**。如果尚未安装，从 Marketplace 安装 [OpenAI-API-compatible](https://marketplace.dify.ai/plugin/langgenius/openai_api_compatible)。
+3. 添加聊天模型，填写：
+
+| 字段 | 值 |
+| --- | --- |
+| API Base URL | `https://api.acedata.cloud/v1` |
+| API Key | 你的 AceDataCloud Token |
+| 模型名称 | `gpt-5.5`，或其他[受支持的聊天模型](https://platform.acedata.cloud/documents/openai-chat-completions) |
+| 模型类型 | LLM |
+| 对话类型 | Chat（对话） |
+| API 类型 | Chat Completions API |
+
+4. 保存并测试模型，然后在 Dify 的 **LLM** 节点中选择它。
+
+Base URL 以 `/v1` 结尾，不要再加 `/chat/completions`；Dify 会自行拼接操作路径。旧的 `/openai/v1` 地址不提供此接口。
+
+每次测试或运行工作流都会产生 AceDataCloud 用量。发布工作流前，检查模型当前价格及 Dify 的重试设置。API Key 只存放在 Dify 的供应商凭据设置中，不要写进提示词或工作流导出文件。
+
+请求和响应结构见 [Chat Completions](/zh-Hans/guides/openai/openai_chat_completions)。
diff --git a/zh-Hans/integrations/gitlab-ci.mdx b/zh-Hans/integrations/gitlab-ci.mdx
@@ -0,0 +1,19 @@
+---
+title: "从 GitLab CI 调用 AceDataCloud"
+description: "用手动流水线任务调用聊天模型，总结提交标题。"
+---
+
+可以在 GitLab CI 任务中调用 AceDataCloud Chat Completions API。[示例流水线](https://raw.githubusercontent.com/AceDataCloud/Docs/main/examples/gitlab/acedatacloud-chat.gitlab-ci.yml)总结最新提交的标题，并将结果保存为短期 Artifact。任务只在默认分支显示，且需要手动启动。
+
+## 配置任务
+
+1. [创建 AceDataCloud API Token](https://platform.acedata.cloud/console/applications)。
+2. 在 GitLab 项目中打开 **Settings → CI/CD → Variables**，添加名为 `ACEDATACLOUD_API_TOKEN` 的变量，设为 masked 和 hidden，并保护该变量及默认分支。
+3. 将[示例流水线 YAML](https://raw.githubusercontent.com/AceDataCloud/Docs/main/examples/gitlab/acedatacloud-chat.gitlab-ci.yml)复制到项目的 `.gitlab-ci.yml`。如果已有 `stages`，将 `report` 加入现有列表，然后只复制示例任务。
+4. 在默认分支运行流水线，手动启动 **acedatacloud_commit_summary** 任务，从 Artifact 下载 `summary.txt`。
+
+任务会将 `CI_COMMIT_TITLE` 发送给 AceDataCloud。如果提交标题包含敏感内容，请先确认项目的数据使用规则。每次手动运行产生一次计费 API 请求；更改触发方式前请查看模型当前价格。Token 保留在 GitLab 的 CI/CD 变量中，不会写入 Artifact。
+
+要总结其他输入，可修改示例中的 `jq --arg title` 和提示词。请继续将 Token 放在 CI/CD 变量中，并用 `jq --arg` 编码用户可控文本，不要在 JSON 字符串里直接拼接 shell 变量。请求结构见 [Chat Completions](/zh-Hans/guides/openai/openai_chat_completions)。
+
+这是可复制的 CI 示例。要将可复用组件发布到 [GitLab CI/CD Catalog](https://docs.gitlab.com/ci/components/)，还需要 GitLab 托管的组件项目和 Release。
diff --git a/zh-Hans/integrations/n8n.mdx b/zh-Hans/integrations/n8n.mdx
@@ -0,0 +1,22 @@
+---
+title: "在 n8n 中使用 AceDataCloud"
+description: "导入聊天工作流，用 AceDataCloud API Token 运行。"
+---
+
+使用 n8n 自带的 HTTP Request 节点调用 AceDataCloud。[示例工作流](https://raw.githubusercontent.com/AceDataCloud/Docs/main/examples/n8n/acedatacloud-chat.json)向 Chat Completions API 发送提示词，并返回回复和 Token 用量，无需安装社区节点。
+
+## 导入工作流
+
+1. [创建 AceDataCloud API Token](https://platform.acedata.cloud/console/applications)。
+2. 在 n8n 中新建工作流，选择 **Import from URL**，填入[示例工作流地址](https://raw.githubusercontent.com/AceDataCloud/Docs/main/examples/n8n/acedatacloud-chat.json)。也可以下载 JSON 文件后选择 **Import from File**。
+3. 打开 **AceDataCloud chat** 节点，在 **Authentication → Generic Credential Type** 中选择 **Bearer Auth**，创建凭据并填入 AceDataCloud Token。只需填 Token 本身，n8n 会自动添加 `Bearer ` 前缀。保存后在节点中选中这个凭据。
+4. 在 **Set prompt and model** 节点修改示例提示词，并选择[受支持的聊天模型](https://platform.acedata.cloud/documents/openai-chat-completions)。
+5. 点击 **Execute workflow**。HTTP Request 的输出包含 `choices[0].message.content` 和 `usage`。
+
+请把 Token 只存放在 n8n 凭据中，不要写入工作流 JSON 或 Set 节点。每次运行都会产生 API 用量；启用定时或 Webhook 触发前，请先查看模型当前价格。
+
+## 扩展工作流
+
+可将手动触发器换成自己的触发器，再把输入文本映射到 **Set prompt and model** 中的 `prompt`。HTTP Request 节点向 `https://api.acedata.cloud/v1/chat/completions` 发送非流式 `POST` 请求，后续节点可以直接使用返回结果。请求和响应结构见 [Chat Completions](/zh-Hans/guides/openai/openai_chat_completions)。
+
+请求失败时，检查节点选择的凭据、Token 是否误带 `Bearer ` 前缀、模型名称和可用余额。遇到鉴权或余额错误，先排除原因再重试。
diff --git a/zh-Hans/integrations/open-webui.mdx b/zh-Hans/integrations/open-webui.mdx
@@ -0,0 +1,17 @@
+---
+title: "在 Open WebUI 中使用 AceDataCloud"
+description: "通过 Open WebUI 的 OpenAI 兼容供应商连接 AceDataCloud 聊天模型。"
+---
+
+Open WebUI 支持 OpenAI 兼容的 Chat Completions 接口，可以直接连接 AceDataCloud，无需编写自定义 Pipe 或供应商模块。
+
+## 添加连接
+
+1. [创建 AceDataCloud API Token](https://platform.acedata.cloud/console/applications)。
+2. 在 Open WebUI 中打开 **Settings → Admin → Connections**，在 **Manage OpenAI API Connections** 下选择 **Add Connection**。
+3. URL 填 `https://api.acedata.cloud/v1`，API Key 填 AceDataCloud Token。
+4. 如果没有自动发现模型，在 **Model IDs** 中手动加入 `gpt-5.5`。保存连接，在新对话中选中该模型并发送简短提示词。
+
+Open WebUI 的 **Verify Connection** 会请求 `/models`；模型发现失败不等于 Chat Completions 调用失败。此时可手动添加模型 ID，再用真实聊天请求验证。AceDataCloud 的 `/v1/models` 和 `/v1/chat/completions` 路由均使用 Bearer Token。请以[当前模型目录](https://platform.acedata.cloud/documents/openai-chat-completions)为准。
+
+Token 只存放在 Open WebUI 的连接设置中。测试提示词可能产生 API 用量，请先查看模型当前价格。协议细节见 [Chat Completions](/zh-Hans/guides/openai/openai_chat_completions)和 [Open WebUI 官方指南](https://docs.openwebui.com/getting-started/quick-start/connect-a-provider/starting-with-openai-compatible/)。