feat: add LMStudio

packages/components/credentials/LmStudioApi.credential.ts

@@ -0,0 +1,28 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class LMStudioApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'LM Studio API'
+        this.name = 'lmStudioApi'
+        this.version = 1.0
+        this.description =
+            'Refer to <a target="_blank" href="https://lmstudio.ai/docs/developer/core/authentication">official guide</a> on how to get access token on LmStudio'
+
+        this.inputs = [
+            {
+                label: 'LM Studio Api Key',
+                name: 'lmStudioApiKey',
+                type: 'password',
+                placeholder: '<LM_STUDIO_ACCESS_TOKEN>'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: LMStudioApi }

packages/components/nodes/chatmodels/ChatLmStudio/ChatLmStudio.ts

@@ -0,0 +1,149 @@
+import { ChatOpenAI as LangchainChatLmStudio, ChatOpenAIFields as ChatLmStudioFields } from '@langchain/openai'
+import { BaseCache } from '@langchain/core/caches'
+import { ICommonObject, IMultiModalOption, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+import { FlowiseChatLmStudio } from './FlowiseChatLmStudio'
+
+class ChatLmStudio_ChatModels 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 = 'LMStudio'
+        this.name = 'chatLmStudio'
+        this.version = 3.0
+        this.type = 'ChatLmStudio'
+        this.icon = 'lmstudio.png'
+        this.category = 'Chat Models'
+        this.description = 'Use local LLMs using LmStudio'
+        this.baseClasses = [this.type, 'BaseChatModel', ...getBaseClasses(LangchainChatLmStudio)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['lmStudioApi'],
+            optional: true
+        }
+        this.inputs = [
+            {
+                label: 'Cache',
+                name: 'cache',
+                type: 'BaseCache',
+                optional: true
+            },
+            {
+                label: 'Base URL',
+                name: 'baseURL',
+                type: 'string',
+                placeholder: 'http://localhost:1234/v1'
+            },
+            {
+                label: 'Model Name',
+                name: 'modelName',
+                type: 'string',
+                placeholder: 'gpt4all-lora-quantized.bin'
+            },
+            {
+                label: 'Temperature',
+                name: 'temperature',
+                type: 'number',
+                step: 0.1,
+                default: 0.9,
+                optional: true
+            },
+            {
+                label: 'Allow Image Uploads',
+                name: 'allowImageUploads',
+                type: 'boolean',
+                description:
+                    'Allow image input. Refer to the <a href="https://docs.flowiseai.com/using-flowise/uploads#image" target="_blank">docs</a> for more details.',
+                default: false,
+                optional: true
+            },
+            {
+                label: 'Streaming',
+                name: 'streaming',
+                type: 'boolean',
+                default: true,
+                optional: true,
+                additionalParams: true
+            },
+            {
+                label: 'Max Tokens',
+                name: 'maxTokens',
+                type: 'number',
+                step: 1,
+                optional: true,
+                additionalParams: true
+            },
+            {
+                label: 'Top Probability',
+                name: 'topP',
+                type: 'number',
+                step: 0.1,
+                optional: true,
+                additionalParams: true
+            },
+            {
+                label: 'Timeout',
+                name: 'timeout',
+                type: 'number',
+                step: 1,
+                optional: true,
+                additionalParams: true
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
+        const temperature = nodeData.inputs?.temperature as string
+        const modelName = nodeData.inputs?.modelName as string
+        const maxTokens = nodeData.inputs?.maxTokens as string
+        const topP = nodeData.inputs?.topP as string
+        const timeout = nodeData.inputs?.timeout as string
+        const baseURL = nodeData.inputs?.baseURL as string
+        const streaming = nodeData.inputs?.streaming as boolean
+        const allowImageUploads = nodeData.inputs?.allowImageUploads as boolean
+
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const lmStudioApiKey = getCredentialParam('lmStudioApiKey', credentialData, nodeData)
+
+        const cache = nodeData.inputs?.cache as BaseCache
+
+        const obj: ChatLmStudioFields = {
+            modelName,
+            streaming: streaming ?? true,
+            configuration: {
+                baseURL,
+                apiKey: lmStudioApiKey
+            }
+        }
+
+        if (temperature) obj.temperature = parseFloat(temperature)
+        if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
+        if (topP) obj.topP = parseFloat(topP)
+        if (timeout) obj.timeout = parseInt(timeout, 10)
+        if (cache) obj.cache = cache
+
+        const multiModalOption: IMultiModalOption = {
+            image: {
+                allowImageUploads: allowImageUploads ?? false
+            }
+        }
+
+        const model = new FlowiseChatLmStudio(nodeData.id, obj)
+        model.setMultiModalOption(multiModalOption)
+
+        return model
+    }
+}
+
+module.exports = { nodeClass: ChatLmStudio_ChatModels }

packages/components/nodes/chatmodels/ChatLmStudio/FlowiseChatLmStudio.ts

@@ -0,0 +1,34 @@
+import { ChatOpenAI as LangchainChatLmStudio, ChatOpenAIFields as ChatLmStudioFields } from '@langchain/openai'
+import { IMultiModalOption, IVisionChatModal } from '../../../src'
+
+export class FlowiseChatLmStudio extends LangchainChatLmStudio implements IVisionChatModal {
+    configuredModel: string
+    configuredMaxToken?: number
+    multiModalOption: IMultiModalOption
+    builtInTools: Record<string, any>[] = []
+    id: string
+
+    constructor(id: string, fields?: ChatLmStudioFields) {
+        super(fields)
+        this.id = id
+        this.configuredModel = fields?.modelName ?? ''
+        this.configuredMaxToken = fields?.maxTokens
+    }
+
+    revertToOriginalModel(): void {
+        this.model = this.configuredModel
+        this.maxTokens = this.configuredMaxToken
+    }
+
+    setMultiModalOption(multiModalOption: IMultiModalOption): void {
+        this.multiModalOption = multiModalOption
+    }
+
+    setVisionModel(): void {
+        // pass
+    }
+
+    addBuiltInTools(builtInTool: Record<string, any>): void {
+        this.builtInTools.push(builtInTool)
+    }
+}

packages/components/nodes/embeddings/LMStudioAIEmbedding/LmStudioEmbedding.ts

@@ -0,0 +1,75 @@
+import {
+    ClientOptions,
+    OpenAIEmbeddings as LmStudioEmbeddings,
+    OpenAIEmbeddingsParams as LmStudioEmbeddingsParams
+} from '@langchain/openai'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getCredentialData, getCredentialParam } from '../../../src/utils'
+
+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 = 'LMStudio Embeddings'
+        this.name = 'lmStudioEmbeddings'
+        this.version = 1.0
+        this.type = 'LmStudio Embeddings'
+        this.icon = 'lmstudio.png'
+        this.category = 'Embeddings'
+        this.description = 'Use local embeddings from LMStudio'
+        this.baseClasses = [this.type, 'Embeddings']
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['lmStudioApi'],
+            optional: true
+        }
+        this.inputs = [
+            {
+                label: 'Base URL',
+                name: 'baseURL',
+                type: 'string',
+                placeholder: 'http://localhost:1234/v1'
+            },
+            {
+                label: 'Model Name',
+                name: 'modelName',
+                type: 'string',
+                placeholder: 'text-embedding-ada-002'
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
+        const modelName = nodeData.inputs?.modelName as string
+        const baseURL = nodeData.inputs?.baseURL as string
+
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const lmStudioApiKey = getCredentialParam('lmStudioApiKey', credentialData, nodeData)
+
+        const obj: Partial<LmStudioEmbeddingsParams> & { configuration?: ClientOptions } = {
+            modelName,
+            encodingFormat: 'float',
+            configuration: {
+                apiKey: lmStudioApiKey,
+                baseURL
+            }
+        }
+
+        const model = new LmStudioEmbeddings(obj)
+
+        return model
+    }
+}
+
+module.exports = { nodeClass: LmStudioEmbedding_Embeddings }