refactor: nodejs sdk (#30036)

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>

sdks/nodejs-client/README.md

@@ -13,54 +13,92 @@ npm install dify-client
 After installing the SDK, you can use it in your project like this:
 
 ```js
-import { DifyClient, ChatClient, CompletionClient } from 'dify-client'
+import {
+  DifyClient,
+  ChatClient,
+  CompletionClient,
+  WorkflowClient,
+  KnowledgeBaseClient,
+  WorkspaceClient
+} from 'dify-client'
 
-const API_KEY = 'your-api-key-here'
-const user = `random-user-id`
+const API_KEY = 'your-app-api-key'
+const DATASET_API_KEY = 'your-dataset-api-key'
+const user = 'random-user-id'
 const query = 'Please tell me a short story in 10 words or less.'
-const remote_url_files = [{
-    type: 'image',
-    transfer_method: 'remote_url',
-    url: 'your_url_address'
-}]
 
-// Create a completion client
-const completionClient = new CompletionClient(API_KEY)
-// Create a completion message
-completionClient.createCompletionMessage({'query': query}, user)
-// Create a completion message with vision model
-completionClient.createCompletionMessage({'query': 'Describe the picture.'}, user, false, remote_url_files)
-
-// Create a chat client
 const chatClient = new ChatClient(API_KEY)
-// Create a chat message in stream mode
-const response = await chatClient.createChatMessage({}, query, user, true, null)
-const stream = response.data;
-stream.on('data', data => {
-    console.log(data);
-});
-stream.on('end', () => {
-    console.log('stream done');
-});
-// Create a chat message with vision model
-chatClient.createChatMessage({}, 'Describe the picture.', user, false, null, remote_url_files)
-// Fetch conversations
-chatClient.getConversations(user)
-// Fetch conversation messages
-chatClient.getConversationMessages(conversationId, user)
-// Rename conversation
-chatClient.renameConversation(conversationId, name, user)
-
-
+const completionClient = new CompletionClient(API_KEY)
+const workflowClient = new WorkflowClient(API_KEY)
+const kbClient = new KnowledgeBaseClient(DATASET_API_KEY)
+const workspaceClient = new WorkspaceClient(DATASET_API_KEY)
 const client = new DifyClient(API_KEY)
-// Fetch application parameters
-client.getApplicationParameters(user)
-// Provide feedback for a message
-client.messageFeedback(messageId, rating, user)
+
+// App core
+await client.getApplicationParameters(user)
+await client.messageFeedback('message-id', 'like', user)
+
+// Completion (blocking)
+await completionClient.createCompletionMessage({
+  inputs: { query },
+  user,
+  response_mode: 'blocking'
+})
+
+// Chat (streaming)
+const stream = await chatClient.createChatMessage({
+  inputs: {},
+  query,
+  user,
+  response_mode: 'streaming'
+})
+for await (const event of stream) {
+  console.log(event.event, event.data)
+}
+
+// Chatflow (advanced chat via workflow_id)
+await chatClient.createChatMessage({
+  inputs: {},
+  query,
+  user,
+  workflow_id: 'workflow-id',
+  response_mode: 'blocking'
+})
+
+// Workflow run (blocking or streaming)
+await workflowClient.run({
+  inputs: { query },
+  user,
+  response_mode: 'blocking'
+})
+
+// Knowledge base (dataset token required)
+await kbClient.listDatasets({ page: 1, limit: 20 })
+await kbClient.createDataset({ name: 'KB', indexing_technique: 'economy' })
+
+// RAG pipeline (may require service API route registration)
+const pipelineStream = await kbClient.runPipeline('dataset-id', {
+  inputs: {},
+  datasource_type: 'online_document',
+  datasource_info_list: [],
+  start_node_id: 'start-node-id',
+  is_published: true,
+  response_mode: 'streaming'
+})
+for await (const event of pipelineStream) {
+  console.log(event.data)
+}
+
+// Workspace models (dataset token required)
+await workspaceClient.getModelsByType('text-embedding')
 
 ```
 
-Replace 'your-api-key-here' with your actual Dify API key.Replace 'your-app-id-here' with your actual Dify APP ID.
+Notes:
+
+- App endpoints use an app API token; knowledge base and workspace endpoints use a dataset API token.
+- Chat/completion require a stable `user` identifier in the request payload.
+- For streaming responses, iterate the returned AsyncIterable. Use `stream.toText()` to collect text.
 
 ## License