feat(components): add Baidu Qianfan embeddings node

packages/components/models.json

@@ -2183,6 +2183,27 @@
                 }
             ]
         },
+        {
+            "name": "baiduQianfanEmbeddings",
+            "models": [
+                {
+                    "label": "Embedding-V1",
+                    "name": "Embedding-V1"
+                },
+                {
+                    "label": "bge-large-zh",
+                    "name": "bge-large-zh"
+                },
+                {
+                    "label": "bge-large-en",
+                    "name": "bge-large-en"
+                },
+                {
+                    "label": "tao-8k",
+                    "name": "tao-8k"
+                }
+            ]
+        },
         {
             "name": "mistralAIEmbeddings",
             "models": [

packages/components/nodes/embeddings/BaiduQianfanEmbedding/BaiduQianfanEmbedding.test.ts

@@ -0,0 +1,96 @@
+jest.mock('@langchain/baidu-qianfan', () => ({
+    BaiduQianfanEmbeddings: jest.fn().mockImplementation((fields) => ({ fields }))
+}))
+
+jest.mock('../../../src/utils', () => ({
+    getBaseClasses: jest.fn().mockReturnValue(['Embeddings']),
+    getCredentialData: jest.fn(),
+    getCredentialParam: jest.fn()
+}))
+
+jest.mock('../../../src/modelLoader', () => ({
+    MODEL_TYPE: { EMBEDDING: 'embedding' },
+    getModels: jest.fn()
+}))
+
+import { getCredentialData, getCredentialParam } from '../../../src/utils'
+import { getModels } from '../../../src/modelLoader'
+
+const { nodeClass: BaiduQianfanEmbedding } = require('./BaiduQianfanEmbedding')
+
+describe('BaiduQianfanEmbedding', () => {
+    beforeEach(() => {
+        jest.clearAllMocks()
+    })
+
+    it('loads embedding model options from the shared model loader', async () => {
+        ;(getModels as jest.Mock).mockResolvedValue([{ label: 'Embedding-V1', name: 'Embedding-V1' }])
+
+        const node = new BaiduQianfanEmbedding()
+        const models = await node.loadMethods.listModels()
+
+        expect(getModels).toHaveBeenCalledWith('embedding', 'baiduQianfanEmbeddings')
+        expect(models).toEqual([{ label: 'Embedding-V1', name: 'Embedding-V1' }])
+    })
+
+    it('maps credential, custom model names, and optional embedding parameters into BaiduQianfanEmbeddings', async () => {
+        ;(getCredentialData as jest.Mock).mockResolvedValue({
+            qianfanAccessKey: 'access-key',
+            qianfanSecretKey: 'secret-key'
+        })
+        ;(getCredentialParam as jest.Mock).mockImplementation((key, credentialData) => credentialData[key])
+
+        const node = new BaiduQianfanEmbedding()
+        const model = await node.init(
+            {
+                credential: 'cred-1',
+                inputs: {
+                    modelName: 'bge-large-zh',
+                    customModelName: 'Qwen3-Embedding-4B',
+                    stripNewLines: true,
+                    batchSize: '8',
+                    timeout: '15000'
+                }
+            },
+            '',
+            {}
+        )
+
+        expect(model.fields).toMatchObject({
+            modelName: 'Qwen3-Embedding-4B',
+            qianfanAccessKey: 'access-key',
+            qianfanSecretKey: 'secret-key',
+            stripNewLines: true,
+            batchSize: 8,
+            timeout: 15000
+        })
+    })
+
+    it('preserves explicit zero values for numeric parameters', async () => {
+        ;(getCredentialData as jest.Mock).mockResolvedValue({
+            qianfanAccessKey: 'access-key',
+            qianfanSecretKey: 'secret-key'
+        })
+        ;(getCredentialParam as jest.Mock).mockImplementation((key, credentialData) => credentialData[key])
+
+        const node = new BaiduQianfanEmbedding()
+        const model = await node.init(
+            {
+                credential: 'cred-1',
+                inputs: {
+                    modelName: 'Embedding-V1',
+                    batchSize: '0',
+                    timeout: '0'
+                }
+            },
+            '',
+            {}
+        )
+
+        expect(model.fields).toMatchObject({
+            modelName: 'Embedding-V1',
+            batchSize: 0,
+            timeout: 0
+        })
+    })
+})

packages/components/nodes/embeddings/BaiduQianfanEmbedding/BaiduQianfanEmbedding.ts

@@ -0,0 +1,116 @@
+import { BaiduQianfanEmbeddings, BaiduQianfanEmbeddingsParams } from '@langchain/baidu-qianfan'
+import { ICommonObject, INode, INodeData, INodeOptionsValue, INodeParams } from '../../../src/Interface'
+import { MODEL_TYPE, getModels } from '../../../src/modelLoader'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+
+class BaiduQianfanEmbedding_Embeddings implements INode {
+    label: string
+    name: string
+    version: number
+    type: string
+    icon: string
+    category: string
+    description: string
+    baseClasses: string[]
+    credential: INodeParams
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Baidu Qianfan Embedding'
+        this.name = 'baiduQianfanEmbeddings'
+        this.version = 1.0
+        this.type = 'BaiduQianfanEmbeddings'
+        this.icon = 'baiduwenxin.svg'
+        this.category = 'Embeddings'
+        this.description = 'Baidu Qianfan API to generate embeddings for a given text'
+        this.baseClasses = [this.type, ...getBaseClasses(BaiduQianfanEmbeddings)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['baiduQianfanApi']
+        }
+        this.inputs = [
+            {
+                label: 'Model Name',
+                name: 'modelName',
+                type: 'asyncOptions',
+                loadMethod: 'listModels',
+                default: 'Embedding-V1'
+            },
+            {
+                label: 'Custom Model Name',
+                name: 'customModelName',
+                type: 'string',
+                placeholder: 'Qwen3-Embedding-4B',
+                description: 'Custom model name to use. If provided, it will override the selected model.',
+                additionalParams: true,
+                optional: true
+            },
+            {
+                label: 'Strip New Lines',
+                name: 'stripNewLines',
+                type: 'boolean',
+                optional: true,
+                additionalParams: true,
+                description: 'Remove new lines from input text before embedding to reduce token count'
+            },
+            {
+                label: 'Batch Size',
+                name: 'batchSize',
+                type: 'number',
+                optional: true,
+                default: 1,
+                additionalParams: true,
+                description: 'Number of texts sent in each embedding request',
+                warning:
+                    'Qianfan has stricter limits on individual text length. If you encounter a length error, reduce chunk size to 500 and set Batch Size to 1.'
+            },
+            {
+                label: 'Timeout',
+                name: 'timeout',
+                type: 'number',
+                optional: true,
+                additionalParams: true,
+                description: 'Request timeout in milliseconds'
+            }
+        ]
+    }
+
+    //@ts-ignore
+    loadMethods = {
+        async listModels(): Promise<INodeOptionsValue[]> {
+            return await getModels(MODEL_TYPE.EMBEDDING, 'baiduQianfanEmbeddings')
+        }
+    }
+
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
+        const modelName = nodeData.inputs?.modelName as BaiduQianfanEmbeddingsParams['modelName']
+        const customModelName = nodeData.inputs?.customModelName as string
+        const stripNewLines = nodeData.inputs?.stripNewLines as boolean
+        const batchSize = nodeData.inputs?.batchSize as string
+        const timeout = nodeData.inputs?.timeout as string
+
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const qianfanAccessKey = getCredentialParam('qianfanAccessKey', credentialData, nodeData)
+        const qianfanSecretKey = getCredentialParam('qianfanSecretKey', credentialData, nodeData)
+
+        const obj: Partial<BaiduQianfanEmbeddingsParams> & {
+            qianfanAccessKey?: string
+            qianfanSecretKey?: string
+        } = {
+            modelName: (customModelName || modelName) as BaiduQianfanEmbeddingsParams['modelName'],
+            qianfanAccessKey,
+            qianfanSecretKey
+        }
+
+        if (typeof stripNewLines === 'boolean') obj.stripNewLines = stripNewLines
+        if (batchSize !== undefined && batchSize !== null && batchSize !== '') obj.batchSize = parseInt(batchSize, 10)
+        if (timeout !== undefined && timeout !== null && timeout !== '') obj.timeout = parseInt(timeout, 10)
+
+        const model = new BaiduQianfanEmbeddings(obj)
+        return model
+    }
+}
+
+module.exports = { nodeClass: BaiduQianfanEmbedding_Embeddings }