feat(embeddings): add LM Studio embeddings node

packages/components/credentials/LMStudioApi.credential.ts

@@ -0,0 +1,23 @@
+import { INodeCredential, INodeParams } from '../src/Interface'
+
+class LMStudioApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'LM Studio API'
+        this.name = 'lmStudioApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'LM Studio API Key',
+                name: 'lmStudioApiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: LMStudioApi }

packages/components/nodes/embeddings/LMStudioEmbedding/LMStudioEmbedding.ts

@@ -0,0 +1,126 @@
+import { ClientOptions, OpenAIEmbeddings, OpenAIEmbeddingsParams } from '@langchain/openai'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+
+const parseOptionalInt = (value?: string | number): number | undefined => {
+    if (value === undefined || value === null || value === '') return undefined
+
+    const parsedValue = Number.parseInt(String(value), 10)
+    return Number.isNaN(parsedValue) ? undefined : parsedValue
+}
+
+class LMStudioEmbedding_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 = 'LM Studio Embeddings'
+        this.name = 'lmStudioEmbeddings'
+        this.version = 1.0
+        this.type = 'LMStudioEmbeddings'
+        this.icon = 'lmstudio.svg'
+        this.category = 'Embeddings'
+        this.description = "Generate embeddings using LM Studio's OpenAI-compatible API"
+        this.baseClasses = [this.type, ...getBaseClasses(OpenAIEmbeddings)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['lmStudioApi'],
+            optional: true
+        }
+        this.inputs = [
+            {
+                label: 'Base URL',
+                name: 'baseUrl',
+                type: 'string',
+                default: 'http://localhost:1234/v1'
+            },
+            {
+                label: 'Model Name',
+                name: 'modelName',
+                type: 'string',
+                default: 'text-embedding-nomic-embed-text-v1.5'
+            },
+            {
+                label: 'Strip New Lines',
+                name: 'stripNewLines',
+                type: 'boolean',
+                optional: true,
+                additionalParams: true
+            },
+            {
+                label: 'Batch Size',
+                name: 'batchSize',
+                type: 'number',
+                optional: true,
+                additionalParams: true
+            },
+            {
+                label: 'Timeout',
+                name: 'timeout',
+                type: 'number',
+                optional: true,
+                additionalParams: true
+            },
+            {
+                label: 'Dimensions',
+                name: 'dimensions',
+                type: 'number',
+                optional: true,
+                additionalParams: true
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
+        const baseUrl = nodeData.inputs?.baseUrl as string
+        const modelName = nodeData.inputs?.modelName as string
+        const stripNewLines = nodeData.inputs?.stripNewLines as boolean
+        const batchSize = nodeData.inputs?.batchSize as string | number
+        const timeout = nodeData.inputs?.timeout as string | number
+        const dimensions = nodeData.inputs?.dimensions as string | number
+
+        if (nodeData.inputs?.credentialId) {
+            nodeData.credential = nodeData.inputs?.credentialId
+        }
+
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const lmStudioApiKey = getCredentialParam('lmStudioApiKey', credentialData, nodeData)
+
+        const obj: Partial<OpenAIEmbeddingsParams> & { openAIApiKey?: string; configuration?: ClientOptions } = {
+            modelName,
+            openAIApiKey: 'sk-'
+        }
+
+        if (lmStudioApiKey) obj.openAIApiKey = lmStudioApiKey
+        if (stripNewLines !== undefined) obj.stripNewLines = stripNewLines
+
+        const parsedBatchSize = parseOptionalInt(batchSize)
+        const parsedTimeout = parseOptionalInt(timeout)
+        const parsedDimensions = parseOptionalInt(dimensions)
+
+        if (parsedBatchSize !== undefined) obj.batchSize = parsedBatchSize
+        if (parsedTimeout !== undefined) obj.timeout = parsedTimeout
+        if (parsedDimensions !== undefined) obj.dimensions = parsedDimensions
+
+        if (baseUrl) {
+            obj.configuration = {
+                baseURL: baseUrl
+            }
+        }
+
+        const model = new OpenAIEmbeddings(obj)
+        return model
+    }
+}
+
+module.exports = { nodeClass: LMStudioEmbedding_Embeddings }