Merge branch 'main' into main

packages/components/.env.example

@@ -1 +0,0 @@
-DEBUG=true

packages/components/README.md

@@ -12,14 +12,6 @@ Install:
 npm i flowise-components
 ```
 
-## Debug
-
-To view all the logs, create an `.env` file and add:
-
-```
-DEBUG=true
-```
-
 ## License
 
 Source code in this repository is made available under the [MIT License](https://github.com/FlowiseAI/Flowise/blob/master/LICENSE.md).

packages/components/credentials/AirtableApi.credential.ts

@@ -0,0 +1,27 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class AirtableApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Airtable API'
+        this.name = 'airtableApi'
+        this.version = 1.0
+        this.description =
+            'Refer to <a target="_blank" href="https://support.airtable.com/docs/creating-and-using-api-keys-and-access-tokens">official guide</a> on how to get accessToken on Airtable'
+        this.inputs = [
+            {
+                label: 'Access Token',
+                name: 'accessToken',
+                type: 'password',
+                placeholder: '<AIRTABLE_ACCESS_TOKEN>'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: AirtableApi }

packages/components/credentials/AnthropicApi.credential.ts

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

packages/components/credentials/AzureOpenAIApi.credential.ts

@@ -0,0 +1,47 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class AzureOpenAIApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Azure OpenAI API'
+        this.name = 'azureOpenAIApi'
+        this.version = 1.0
+        this.description =
+            'Refer to <a target="_blank" href="https://azure.microsoft.com/en-us/products/cognitive-services/openai-service">official guide</a> of how to use Azure OpenAI service'
+        this.inputs = [
+            {
+                label: 'Azure OpenAI Api Key',
+                name: 'azureOpenAIApiKey',
+                type: 'password',
+                description: `Refer to <a target="_blank" href="https://learn.microsoft.com/en-us/azure/cognitive-services/openai/quickstart?tabs=command-line&pivots=rest-api#set-up">official guide</a> on how to create API key on Azure OpenAI`
+            },
+            {
+                label: 'Azure OpenAI Api Instance Name',
+                name: 'azureOpenAIApiInstanceName',
+                type: 'string',
+                placeholder: 'YOUR-INSTANCE-NAME'
+            },
+            {
+                label: 'Azure OpenAI Api Deployment Name',
+                name: 'azureOpenAIApiDeploymentName',
+                type: 'string',
+                placeholder: 'YOUR-DEPLOYMENT-NAME'
+            },
+            {
+                label: 'Azure OpenAI Api Version',
+                name: 'azureOpenAIApiVersion',
+                type: 'string',
+                placeholder: '2023-06-01-preview',
+                description:
+                    'Description of Supported API Versions. Please refer <a target="_blank" href="https://learn.microsoft.com/en-us/azure/cognitive-services/openai/reference#chat-completions">examples</a>'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: AzureOpenAIApi }

packages/components/credentials/BraveSearchApi.credential.ts

@@ -0,0 +1,24 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class BraveSearchApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Brave Search API'
+        this.name = 'braveSearchApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'BraveSearch Api Key',
+                name: 'braveApiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: BraveSearchApi }

packages/components/credentials/CohereApi.credential.ts

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

packages/components/credentials/ConfluenceApi.credential.ts

@@ -0,0 +1,33 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class ConfluenceApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Confluence API'
+        this.name = 'confluenceApi'
+        this.version = 1.0
+        this.description =
+            'Refer to <a target="_blank" href="https://support.atlassian.com/confluence-cloud/docs/manage-oauth-access-tokens/">official guide</a> on how to get accessToken on Confluence'
+        this.inputs = [
+            {
+                label: 'Access Token',
+                name: 'accessToken',
+                type: 'password',
+                placeholder: '<CONFLUENCE_ACCESS_TOKEN>'
+            },
+            {
+                label: 'Username',
+                name: 'username',
+                type: 'string',
+                placeholder: '<CONFLUENCE_USERNAME>'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: ConfluenceApi }

packages/components/credentials/DynamodbMemoryApi.credential.ts

@@ -0,0 +1,29 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class DynamodbMemoryApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'DynamodbMemory API'
+        this.name = 'dynamodbMemoryApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'Access Key',
+                name: 'accessKey',
+                type: 'password'
+            },
+            {
+                label: 'Secret Access Key',
+                name: 'secretAccessKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: DynamodbMemoryApi }

packages/components/credentials/FigmaApi.credential.ts

@@ -0,0 +1,27 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class FigmaApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Figma API'
+        this.name = 'figmaApi'
+        this.version = 1.0
+        this.description =
+            'Refer to <a target="_blank" href="https://www.figma.com/developers/api#access-tokens">official guide</a> on how to get accessToken on Figma'
+        this.inputs = [
+            {
+                label: 'Access Token',
+                name: 'accessToken',
+                type: 'password',
+                placeholder: '<FIGMA_ACCESS_TOKEN>'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: FigmaApi }

packages/components/credentials/GithubApi.credential.ts

@@ -0,0 +1,27 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class GithubApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Github API'
+        this.name = 'githubApi'
+        this.version = 1.0
+        this.description =
+            'Refer to <a target="_blank" href="https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens">official guide</a> on how to get accessToken on Github'
+        this.inputs = [
+            {
+                label: 'Access Token',
+                name: 'accessToken',
+                type: 'password',
+                placeholder: '<GITHUB_ACCESS_TOKEN>'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: GithubApi }

packages/components/credentials/GoogleSearchApi.credential.ts

@@ -0,0 +1,31 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class GoogleSearchApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Google Custom Search API'
+        this.name = 'googleCustomSearchApi'
+        this.version = 1.0
+        this.description =
+            'Please refer to the <a target="_blank" href="https://console.cloud.google.com/apis/credentials">Google Cloud Console</a> for instructions on how to create an API key, and visit the <a target="_blank" href="https://programmablesearchengine.google.com/controlpanel/create">Search Engine Creation page</a> to learn how to generate your Search Engine ID.'
+        this.inputs = [
+            {
+                label: 'Google Custom Search Api Key',
+                name: 'googleCustomSearchApiKey',
+                type: 'password'
+            },
+            {
+                label: 'Programmable Search Engine ID',
+                name: 'googleCustomSearchApiId',
+                type: 'string'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: GoogleSearchApi }

packages/components/credentials/HuggingFaceApi.credential.ts

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

packages/components/credentials/MotorheadMemoryApi.credential.ts

@@ -0,0 +1,31 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class MotorheadMemoryApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Motorhead Memory API'
+        this.name = 'motorheadMemoryApi'
+        this.version = 1.0
+        this.description =
+            'Refer to <a target="_blank" href="https://docs.getmetal.io/misc-get-keys">official guide</a> on how to create API key and Client ID on Motorhead Memory'
+        this.inputs = [
+            {
+                label: 'Client ID',
+                name: 'clientId',
+                type: 'string'
+            },
+            {
+                label: 'API Key',
+                name: 'apiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: MotorheadMemoryApi }

packages/components/credentials/NotionApi.credential.ts

@@ -0,0 +1,26 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class NotionApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Notion API'
+        this.name = 'notionApi'
+        this.version = 1.0
+        this.description =
+            'You can find integration token <a target="_blank" href="https://developers.notion.com/docs/create-a-notion-integration#step-1-create-an-integration">here</a>'
+        this.inputs = [
+            {
+                label: 'Notion Integration Token',
+                name: 'notionIntegrationToken',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: NotionApi }

packages/components/credentials/OpenAIApi.credential.ts

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

packages/components/credentials/OpenAPIAuth.credential.ts

@@ -0,0 +1,25 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class OpenAPIAuth implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'OpenAPI Auth Token'
+        this.name = 'openAPIAuth'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'OpenAPI Token',
+                name: 'openAPIToken',
+                type: 'password',
+                description: 'Auth Token. For example: Bearer <TOKEN>'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: OpenAPIAuth }

packages/components/credentials/PineconeApi.credential.ts

@@ -0,0 +1,29 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class PineconeApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Pinecone API'
+        this.name = 'pineconeApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'Pinecone Api Key',
+                name: 'pineconeApiKey',
+                type: 'password'
+            },
+            {
+                label: 'Pinecone Environment',
+                name: 'pineconeEnv',
+                type: 'string'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: PineconeApi }

packages/components/credentials/QdrantApi.credential.ts

@@ -0,0 +1,24 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class QdrantApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Qdrant API'
+        this.name = 'qdrantApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'Qdrant API Key',
+                name: 'qdrantApiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: QdrantApi }

packages/components/credentials/ReplicateApi.credential.ts

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

packages/components/credentials/SerpApi.credential.ts

@@ -0,0 +1,24 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class SerpApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Serp API'
+        this.name = 'serpApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'Serp Api Key',
+                name: 'serpApiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: SerpApi }

packages/components/credentials/SerperApi.credential.ts

@@ -0,0 +1,24 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class SerperApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Serper API'
+        this.name = 'serperApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'Serper Api Key',
+                name: 'serperApiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: SerperApi }

packages/components/credentials/SingleStoreApi.credential.ts

@@ -0,0 +1,31 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class SingleStoreApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'SingleStore API'
+        this.name = 'singleStoreApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'User',
+                name: 'user',
+                type: 'string',
+                placeholder: '<SINGLESTORE_USERNAME>'
+            },
+            {
+                label: 'Password',
+                name: 'password',
+                type: 'password',
+                placeholder: '<SINGLESTORE_PASSWORD>'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: SingleStoreApi }

packages/components/credentials/SupabaseApi.credential.ts

@@ -0,0 +1,24 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class SupabaseApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Supabase API'
+        this.name = 'supabaseApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'Supabase API Key',
+                name: 'supabaseApiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: SupabaseApi }

packages/components/credentials/VectaraApi.credential.ts

@@ -0,0 +1,34 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class VectaraAPI implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Vectara API'
+        this.name = 'vectaraApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'Vectara Customer ID',
+                name: 'customerID',
+                type: 'string'
+            },
+            {
+                label: 'Vectara Corpus ID',
+                name: 'corpusID',
+                type: 'string'
+            },
+            {
+                label: 'Vectara API Key',
+                name: 'apiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: VectaraAPI }

packages/components/credentials/WeaviateApi.credential.ts

@@ -0,0 +1,24 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class WeaviateApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Weaviate API'
+        this.name = 'weaviateApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'Weaviate API Key',
+                name: 'weaviateApiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: WeaviateApi }

packages/components/credentials/ZapierNLAApi.credential.ts

@@ -0,0 +1,24 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class ZapierNLAApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Zapier NLA API'
+        this.name = 'zapierNLAApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'Zapier NLA Api Key',
+                name: 'zapierNLAApiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: ZapierNLAApi }

packages/components/credentials/ZepMemoryApi.credential.ts

@@ -0,0 +1,26 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class ZepMemoryApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Zep Memory API'
+        this.name = 'zepMemoryApi'
+        this.version = 1.0
+        this.description =
+            'Refer to <a target="_blank" href="https://docs.getzep.com/deployment/auth/">official guide</a> on how to create API key on Zep'
+        this.inputs = [
+            {
+                label: 'API Key',
+                name: 'apiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: ZepMemoryApi }

packages/components/nodes/agents/AirtableAgent/AirtableAgent.ts

@@ -0,0 +1,232 @@
+import { ICommonObject, INode, INodeData, INodeParams, PromptTemplate } from '../../../src/Interface'
+import { AgentExecutor } from 'langchain/agents'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+import { LoadPyodide, finalSystemPrompt, systemPrompt } from './core'
+import { LLMChain } from 'langchain/chains'
+import { BaseLanguageModel } from 'langchain/base_language'
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
+import axios from 'axios'
+
+class Airtable_Agents implements INode {
+    label: string
+    name: string
+    version: number
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    credential: INodeParams
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Airtable Agent'
+        this.name = 'airtableAgent'
+        this.version = 1.0
+        this.type = 'AgentExecutor'
+        this.category = 'Agents'
+        this.icon = 'airtable.svg'
+        this.description = 'Agent used to to answer queries on Airtable table'
+        this.baseClasses = [this.type, ...getBaseClasses(AgentExecutor)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['airtableApi']
+        }
+        this.inputs = [
+            {
+                label: 'Language Model',
+                name: 'model',
+                type: 'BaseLanguageModel'
+            },
+            {
+                label: 'Base Id',
+                name: 'baseId',
+                type: 'string',
+                placeholder: 'app11RobdGoX0YNsC',
+                description:
+                    'If your table URL looks like: https://airtable.com/app11RobdGoX0YNsC/tblJdmvbrgizbYICO/viw9UrP77Id0CE4ee, app11RovdGoX0YNsC is the base id'
+            },
+            {
+                label: 'Table Id',
+                name: 'tableId',
+                type: 'string',
+                placeholder: 'tblJdmvbrgizbYICO',
+                description:
+                    'If your table URL looks like: https://airtable.com/app11RobdGoX0YNsC/tblJdmvbrgizbYICO/viw9UrP77Id0CE4ee, tblJdmvbrgizbYICO is the table id'
+            },
+            {
+                label: 'Return All',
+                name: 'returnAll',
+                type: 'boolean',
+                default: true,
+                additionalParams: true,
+                description: 'If all results should be returned or only up to a given limit'
+            },
+            {
+                label: 'Limit',
+                name: 'limit',
+                type: 'number',
+                default: 100,
+                additionalParams: true,
+                description: 'Number of results to return'
+            }
+        ]
+    }
+
+    async init(): Promise<any> {
+        // Not used
+        return undefined
+    }
+
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+        const model = nodeData.inputs?.model as BaseLanguageModel
+        const baseId = nodeData.inputs?.baseId as string
+        const tableId = nodeData.inputs?.tableId as string
+        const returnAll = nodeData.inputs?.returnAll as boolean
+        const limit = nodeData.inputs?.limit as string
+
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const accessToken = getCredentialParam('accessToken', credentialData, nodeData)
+
+        let airtableData: ICommonObject[] = []
+
+        if (returnAll) {
+            airtableData = await loadAll(baseId, tableId, accessToken)
+        } else {
+            airtableData = await loadLimit(limit ? parseInt(limit, 10) : 100, baseId, tableId, accessToken)
+        }
+
+        let base64String = Buffer.from(JSON.stringify(airtableData)).toString('base64')
+
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
+        const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
+
+        const pyodide = await LoadPyodide()
+
+        // First load the csv file and get the dataframe dictionary of column types
+        // For example using titanic.csv: {'PassengerId': 'int64', 'Survived': 'int64', 'Pclass': 'int64', 'Name': 'object', 'Sex': 'object', 'Age': 'float64', 'SibSp': 'int64', 'Parch': 'int64', 'Ticket': 'object', 'Fare': 'float64', 'Cabin': 'object', 'Embarked': 'object'}
+        let dataframeColDict = ''
+        try {
+            const code = `import pandas as pd
+import base64
+import json
+
+base64_string = "${base64String}"
+
+decoded_data = base64.b64decode(base64_string)
+
+json_data = json.loads(decoded_data)
+
+df = pd.DataFrame(json_data)
+my_dict = df.dtypes.astype(str).to_dict()
+print(my_dict)
+json.dumps(my_dict)`
+            dataframeColDict = await pyodide.runPythonAsync(code)
+        } catch (error) {
+            throw new Error(error)
+        }
+
+        // Then tell GPT to come out with ONLY python code
+        // For example: len(df), df[df['SibSp'] > 3]['PassengerId'].count()
+        let pythonCode = ''
+        if (dataframeColDict) {
+            const chain = new LLMChain({
+                llm: model,
+                prompt: PromptTemplate.fromTemplate(systemPrompt),
+                verbose: process.env.DEBUG === 'true' ? true : false
+            })
+            const inputs = {
+                dict: dataframeColDict,
+                question: input
+            }
+            const res = await chain.call(inputs, [loggerHandler])
+            pythonCode = res?.text
+        }
+
+        // Then run the code using Pyodide
+        let finalResult = ''
+        if (pythonCode) {
+            try {
+                const code = `import pandas as pd\n${pythonCode}`
+                finalResult = await pyodide.runPythonAsync(code)
+            } catch (error) {
+                throw new Error(`Sorry, I'm unable to find answer for question: "${input}" using follwoing code: "${pythonCode}"`)
+            }
+        }
+
+        // Finally, return a complete answer
+        if (finalResult) {
+            const chain = new LLMChain({
+                llm: model,
+                prompt: PromptTemplate.fromTemplate(finalSystemPrompt),
+                verbose: process.env.DEBUG === 'true' ? true : false
+            })
+            const inputs = {
+                question: input,
+                answer: finalResult
+            }
+
+            if (options.socketIO && options.socketIOClientId) {
+                const result = await chain.call(inputs, [loggerHandler, handler])
+                return result?.text
+            } else {
+                const result = await chain.call(inputs, [loggerHandler])
+                return result?.text
+            }
+        }
+
+        return pythonCode
+    }
+}
+
+interface AirtableLoaderResponse {
+    records: AirtableLoaderPage[]
+    offset?: string
+}
+
+interface AirtableLoaderPage {
+    id: string
+    createdTime: string
+    fields: ICommonObject
+}
+
+const fetchAirtableData = async (url: string, params: ICommonObject, accessToken: string): Promise<AirtableLoaderResponse> => {
+    try {
+        const headers = {
+            Authorization: `Bearer ${accessToken}`,
+            'Content-Type': 'application/json',
+            Accept: 'application/json'
+        }
+        const response = await axios.get(url, { params, headers })
+        return response.data
+    } catch (error) {
+        throw new Error(`Failed to fetch ${url} from Airtable: ${error}`)
+    }
+}
+
+const loadAll = async (baseId: string, tableId: string, accessToken: string): Promise<ICommonObject[]> => {
+    const params: ICommonObject = { pageSize: 100 }
+    let data: AirtableLoaderResponse
+    let returnPages: AirtableLoaderPage[] = []
+
+    do {
+        data = await fetchAirtableData(`https://api.airtable.com/v0/${baseId}/${tableId}`, params, accessToken)
+        returnPages.push.apply(returnPages, data.records)
+        params.offset = data.offset
+    } while (data.offset !== undefined)
+
+    return data.records.map((page) => page.fields)
+}
+
+const loadLimit = async (limit: number, baseId: string, tableId: string, accessToken: string): Promise<ICommonObject[]> => {
+    const params = { maxRecords: limit }
+    const data = await fetchAirtableData(`https://api.airtable.com/v0/${baseId}/${tableId}`, params, accessToken)
+    if (data.records.length === 0) {
+        return []
+    }
+    return data.records.map((page) => page.fields)
+}
+
+module.exports = { nodeClass: Airtable_Agents }

packages/components/nodes/agents/AirtableAgent/airtable.svg

@@ -0,0 +1,9 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<svg width="256px" height="215px" viewBox="0 0 256 215" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" preserveAspectRatio="xMidYMid">
+	<g>
+		<path d="M114.25873,2.70101695 L18.8604023,42.1756384 C13.5552723,44.3711638 13.6102328,51.9065311 18.9486282,54.0225085 L114.746142,92.0117514 C123.163769,95.3498757 132.537419,95.3498757 140.9536,92.0117514 L236.75256,54.0225085 C242.08951,51.9065311 242.145916,44.3711638 236.83934,42.1756384 L141.442459,2.70101695 C132.738459,-0.900338983 122.961284,-0.900338983 114.25873,2.70101695" fill="#FFBF00"></path>
+		<path d="M136.349071,112.756863 L136.349071,207.659101 C136.349071,212.173089 140.900664,215.263892 145.096461,213.600615 L251.844122,172.166219 C254.281184,171.200072 255.879376,168.845451 255.879376,166.224705 L255.879376,71.3224678 C255.879376,66.8084791 251.327783,63.7176768 247.131986,65.3809537 L140.384325,106.815349 C137.94871,107.781496 136.349071,110.136118 136.349071,112.756863" fill="#26B5F8"></path>
+		<path d="M111.422771,117.65355 L79.742409,132.949912 L76.5257763,134.504714 L9.65047684,166.548104 C5.4112904,168.593211 0.000578531073,165.503855 0.000578531073,160.794612 L0.000578531073,71.7210757 C0.000578531073,70.0173017 0.874160452,68.5463864 2.04568588,67.4384994 C2.53454463,66.9481944 3.08848814,66.5446689 3.66412655,66.2250305 C5.26231864,65.2661153 7.54173107,65.0101153 9.47981017,65.7766689 L110.890522,105.957098 C116.045234,108.002206 116.450206,115.225166 111.422771,117.65355" fill="#ED3049"></path>
+		<path d="M111.422771,117.65355 L79.742409,132.949912 L2.04568588,67.4384994 C2.53454463,66.9481944 3.08848814,66.5446689 3.66412655,66.2250305 C5.26231864,65.2661153 7.54173107,65.0101153 9.47981017,65.7766689 L110.890522,105.957098 C116.045234,108.002206 116.450206,115.225166 111.422771,117.65355" fill-opacity="0.25" fill="#000000"></path>
+	</g>
+</svg>

packages/components/nodes/agents/AirtableAgent/core.ts

@@ -0,0 +1,29 @@
+import type { PyodideInterface } from 'pyodide'
+import * as path from 'path'
+import { getUserHome } from '../../../src/utils'
+
+let pyodideInstance: PyodideInterface | undefined
+
+export async function LoadPyodide(): Promise<PyodideInterface> {
+    if (pyodideInstance === undefined) {
+        const { loadPyodide } = await import('pyodide')
+        const obj: any = { packageCacheDir: path.join(getUserHome(), '.flowise', 'pyodideCacheDir') }
+        pyodideInstance = await loadPyodide(obj)
+        await pyodideInstance.loadPackage(['pandas', 'numpy'])
+    }
+
+    return pyodideInstance
+}
+
+export const systemPrompt = `You are working with a pandas dataframe in Python. The name of the dataframe is df.
+
+The columns and data types of a dataframe are given below as a Python dictionary with keys showing column names and values showing the data types.
+{dict}
+
+I will ask question, and you will output the Python code using pandas dataframe to answer my question. Do not provide any explanations. Do not respond with anything except the output of the code.
+
+Question: {question}
+Output Code:`
+
+export const finalSystemPrompt = `You are given the question: {question}. You have an answer to the question: {answer}. Rephrase the answer into a standalone answer.
+Standalone Answer:`

packages/components/nodes/agents/AutoGPT/AutoGPT.ts

@@ -8,6 +8,7 @@ import { flatten } from 'lodash'
 class AutoGPT_Agents implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -18,6 +19,7 @@ class AutoGPT_Agents implements INode {
     constructor() {
         this.label = 'AutoGPT'
         this.name = 'autoGPT'
+        this.version = 1.0
         this.type = 'AutoGPT'
         this.category = 'Agents'
         this.icon = 'autogpt.png'
@@ -90,7 +92,6 @@ class AutoGPT_Agents implements INode {
             const res = await executor.run([input])
             return res || 'I have completed all my tasks.'
         } catch (e) {
-            console.error(e)
             throw new Error(e)
         }
     }

packages/components/nodes/agents/BabyAGI/BabyAGI.ts

@@ -6,6 +6,7 @@ import { VectorStore } from 'langchain/vectorstores'
 class BabyAGI_Agents implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -16,6 +17,7 @@ class BabyAGI_Agents implements INode {
     constructor() {
         this.label = 'BabyAGI'
         this.name = 'babyAGI'
+        this.version = 1.0
         this.type = 'BabyAGI'
         this.category = 'Agents'
         this.icon = 'babyagi.jpg'

packages/components/nodes/agents/CSVAgent/CSVAgent.ts

@@ -0,0 +1,151 @@
+import { ICommonObject, INode, INodeData, INodeParams, PromptTemplate } from '../../../src/Interface'
+import { AgentExecutor } from 'langchain/agents'
+import { getBaseClasses } from '../../../src/utils'
+import { LoadPyodide, finalSystemPrompt, systemPrompt } from './core'
+import { LLMChain } from 'langchain/chains'
+import { BaseLanguageModel } from 'langchain/base_language'
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
+
+class CSV_Agents implements INode {
+    label: string
+    name: string
+    version: number
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'CSV Agent'
+        this.name = 'csvAgent'
+        this.version = 1.0
+        this.type = 'AgentExecutor'
+        this.category = 'Agents'
+        this.icon = 'csvagent.png'
+        this.description = 'Agent used to to answer queries on CSV data'
+        this.baseClasses = [this.type, ...getBaseClasses(AgentExecutor)]
+        this.inputs = [
+            {
+                label: 'Csv File',
+                name: 'csvFile',
+                type: 'file',
+                fileType: '.csv'
+            },
+            {
+                label: 'Language Model',
+                name: 'model',
+                type: 'BaseLanguageModel'
+            }
+        ]
+    }
+
+    async init(): Promise<any> {
+        // Not used
+        return undefined
+    }
+
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+        const csvFileBase64 = nodeData.inputs?.csvFile as string
+        const model = nodeData.inputs?.model as BaseLanguageModel
+
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
+        const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
+
+        let files: string[] = []
+
+        if (csvFileBase64.startsWith('[') && csvFileBase64.endsWith(']')) {
+            files = JSON.parse(csvFileBase64)
+        } else {
+            files = [csvFileBase64]
+        }
+
+        let base64String = ''
+
+        for (const file of files) {
+            const splitDataURI = file.split(',')
+            splitDataURI.pop()
+            base64String = splitDataURI.pop() ?? ''
+        }
+
+        const pyodide = await LoadPyodide()
+
+        // First load the csv file and get the dataframe dictionary of column types
+        // For example using titanic.csv: {'PassengerId': 'int64', 'Survived': 'int64', 'Pclass': 'int64', 'Name': 'object', 'Sex': 'object', 'Age': 'float64', 'SibSp': 'int64', 'Parch': 'int64', 'Ticket': 'object', 'Fare': 'float64', 'Cabin': 'object', 'Embarked': 'object'}
+        let dataframeColDict = ''
+        try {
+            const code = `import pandas as pd
+import base64
+from io import StringIO
+import json
+
+base64_string = "${base64String}"
+
+decoded_data = base64.b64decode(base64_string)
+
+csv_data = StringIO(decoded_data.decode('utf-8'))
+
+df = pd.read_csv(csv_data)
+my_dict = df.dtypes.astype(str).to_dict()
+print(my_dict)
+json.dumps(my_dict)`
+            dataframeColDict = await pyodide.runPythonAsync(code)
+        } catch (error) {
+            throw new Error(error)
+        }
+
+        // Then tell GPT to come out with ONLY python code
+        // For example: len(df), df[df['SibSp'] > 3]['PassengerId'].count()
+        let pythonCode = ''
+        if (dataframeColDict) {
+            const chain = new LLMChain({
+                llm: model,
+                prompt: PromptTemplate.fromTemplate(systemPrompt),
+                verbose: process.env.DEBUG === 'true' ? true : false
+            })
+            const inputs = {
+                dict: dataframeColDict,
+                question: input
+            }
+            const res = await chain.call(inputs, [loggerHandler])
+            pythonCode = res?.text
+        }
+
+        // Then run the code using Pyodide
+        let finalResult = ''
+        if (pythonCode) {
+            try {
+                const code = `import pandas as pd\n${pythonCode}`
+                finalResult = await pyodide.runPythonAsync(code)
+            } catch (error) {
+                throw new Error(`Sorry, I'm unable to find answer for question: "${input}" using follwoing code: "${pythonCode}"`)
+            }
+        }
+
+        // Finally, return a complete answer
+        if (finalResult) {
+            const chain = new LLMChain({
+                llm: model,
+                prompt: PromptTemplate.fromTemplate(finalSystemPrompt),
+                verbose: process.env.DEBUG === 'true' ? true : false
+            })
+            const inputs = {
+                question: input,
+                answer: finalResult
+            }
+
+            if (options.socketIO && options.socketIOClientId) {
+                const result = await chain.call(inputs, [loggerHandler, handler])
+                return result?.text
+            } else {
+                const result = await chain.call(inputs, [loggerHandler])
+                return result?.text
+            }
+        }
+
+        return pythonCode
+    }
+}
+
+module.exports = { nodeClass: CSV_Agents }

packages/components/nodes/agents/CSVAgent/core.ts

@@ -0,0 +1,29 @@
+import type { PyodideInterface } from 'pyodide'
+import * as path from 'path'
+import { getUserHome } from '../../../src/utils'
+
+let pyodideInstance: PyodideInterface | undefined
+
+export async function LoadPyodide(): Promise<PyodideInterface> {
+    if (pyodideInstance === undefined) {
+        const { loadPyodide } = await import('pyodide')
+        const obj: any = { packageCacheDir: path.join(getUserHome(), '.flowise', 'pyodideCacheDir') }
+        pyodideInstance = await loadPyodide(obj)
+        await pyodideInstance.loadPackage(['pandas', 'numpy'])
+    }
+
+    return pyodideInstance
+}
+
+export const systemPrompt = `You are working with a pandas dataframe in Python. The name of the dataframe is df.
+
+The columns and data types of a dataframe are given below as a Python dictionary with keys showing column names and values showing the data types.
+{dict}
+
+I will ask question, and you will output the Python code using pandas dataframe to answer my question. Do not provide any explanations. Do not respond with anything except the output of the code.
+
+Question: {question}
+Output Code:`
+
+export const finalSystemPrompt = `You are given the question: {question}. You have an answer to the question: {answer}. Rephrase the answer into a standalone answer.
+Standalone Answer:`

packages/components/nodes/agents/ConversationalAgent/ConversationalAgent.ts

@@ -3,13 +3,22 @@ import { initializeAgentExecutorWithOptions, AgentExecutor, InitializeAgentExecu
 import { Tool } from 'langchain/tools'
 import { BaseChatMemory, ChatMessageHistory } from 'langchain/memory'
 import { getBaseClasses } from '../../../src/utils'
-import { AIChatMessage, HumanChatMessage } from 'langchain/schema'
+import { AIMessage, HumanMessage } from 'langchain/schema'
 import { BaseLanguageModel } from 'langchain/base_language'
 import { flatten } from 'lodash'
 
+const DEFAULT_PREFIX = `Assistant is a large language model trained by OpenAI.
+
+Assistant is designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a language model, Assistant is able to generate human-like text based on the input it receives, allowing it to engage in natural-sounding conversations and provide responses that are coherent and relevant to the topic at hand.
+
+Assistant is constantly learning and improving, and its capabilities are constantly evolving. It is able to process and understand large amounts of text, and can use this knowledge to provide accurate and informative responses to a wide range of questions. Additionally, Assistant is able to generate its own text based on the input it receives, allowing it to engage in discussions and provide explanations and descriptions on a wide range of topics.
+
+Overall, Assistant is a powerful system that can help with a wide range of tasks and provide valuable insights and information on a wide range of topics. Whether you need help with a specific question or just want to have a conversation about a particular topic, Assistant is here to assist.`
+
 class ConversationalAgent_Agents implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -20,6 +29,7 @@ class ConversationalAgent_Agents implements INode {
     constructor() {
         this.label = 'Conversational Agent'
         this.name = 'conversationalAgent'
+        this.version = 1.0
         this.type = 'AgentExecutor'
         this.category = 'Agents'
         this.icon = 'agent.svg'
@@ -47,14 +57,7 @@ class ConversationalAgent_Agents implements INode {
                 name: 'systemMessage',
                 type: 'string',
                 rows: 4,
-                optional: true,
-                additionalParams: true
-            },
-            {
-                label: 'Human Message',
-                name: 'humanMessage',
-                type: 'string',
-                rows: 4,
+                default: DEFAULT_PREFIX,
                 optional: true,
                 additionalParams: true
             }
@@ -66,7 +69,6 @@ class ConversationalAgent_Agents implements INode {
         let tools = nodeData.inputs?.tools as Tool[]
         tools = flatten(tools)
         const memory = nodeData.inputs?.memory as BaseChatMemory
-        const humanMessage = nodeData.inputs?.humanMessage as string
         const systemMessage = nodeData.inputs?.systemMessage as string
 
         const obj: InitializeAgentExecutorOptions = {
@@ -75,9 +77,6 @@ class ConversationalAgent_Agents implements INode {
         }
 
         const agentArgs: any = {}
-        if (humanMessage) {
-            agentArgs.humanMessage = humanMessage
-        }
         if (systemMessage) {
             agentArgs.systemMessage = systemMessage
         }
@@ -99,9 +98,9 @@ class ConversationalAgent_Agents implements INode {
 
             for (const message of histories) {
                 if (message.type === 'apiMessage') {
-                    chatHistory.push(new AIChatMessage(message.message))
+                    chatHistory.push(new AIMessage(message.message))
                 } else if (message.type === 'userMessage') {
-                    chatHistory.push(new HumanChatMessage(message.message))
+                    chatHistory.push(new HumanMessage(message.message))
                 }
             }
             memory.chatHistory = new ChatMessageHistory(chatHistory)

packages/components/nodes/agents/MRKLAgentChat/MRKLAgentChat.ts

@@ -8,6 +8,7 @@ import { flatten } from 'lodash'
 class MRKLAgentChat_Agents implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -18,6 +19,7 @@ class MRKLAgentChat_Agents implements INode {
     constructor() {
         this.label = 'MRKL Agent for Chat Models'
         this.name = 'mrklAgentChat'
+        this.version = 1.0
         this.type = 'AgentExecutor'
         this.category = 'Agents'
         this.icon = 'agent.svg'

packages/components/nodes/agents/MRKLAgentLLM/MRKLAgentLLM.ts

@@ -8,6 +8,7 @@ import { flatten } from 'lodash'
 class MRKLAgentLLM_Agents implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -18,6 +19,7 @@ class MRKLAgentLLM_Agents implements INode {
     constructor() {
         this.label = 'MRKL Agent for LLMs'
         this.name = 'mrklAgentLLM'
+        this.version = 1.0
         this.type = 'AgentExecutor'
         this.category = 'Agents'
         this.icon = 'agent.svg'

packages/components/nodes/agents/OpenAIFunctionAgent/OpenAIFunctionAgent.ts

@@ -1,14 +1,16 @@
 import { ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { initializeAgentExecutorWithOptions, AgentExecutor } from 'langchain/agents'
-import { CustomChainHandler, getBaseClasses } from '../../../src/utils'
+import { getBaseClasses } from '../../../src/utils'
 import { BaseLanguageModel } from 'langchain/base_language'
 import { flatten } from 'lodash'
 import { BaseChatMemory, ChatMessageHistory } from 'langchain/memory'
-import { AIChatMessage, HumanChatMessage } from 'langchain/schema'
+import { AIMessage, HumanMessage } from 'langchain/schema'
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
 
 class OpenAIFunctionAgent_Agents implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -19,6 +21,7 @@ class OpenAIFunctionAgent_Agents implements INode {
     constructor() {
         this.label = 'OpenAI Function Agent'
         this.name = 'openAIFunctionAgent'
+        this.version = 1.0
         this.type = 'AgentExecutor'
         this.category = 'Agents'
         this.icon = 'openai.png'
@@ -84,21 +87,23 @@ class OpenAIFunctionAgent_Agents implements INode {
 
             for (const message of histories) {
                 if (message.type === 'apiMessage') {
-                    chatHistory.push(new AIChatMessage(message.message))
+                    chatHistory.push(new AIMessage(message.message))
                 } else if (message.type === 'userMessage') {
-                    chatHistory.push(new HumanChatMessage(message.message))
+                    chatHistory.push(new HumanMessage(message.message))
                 }
             }
             memory.chatHistory = new ChatMessageHistory(chatHistory)
             executor.memory = memory
         }
 
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
+
         if (options.socketIO && options.socketIOClientId) {
             const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
-            const result = await executor.run(input, [handler])
+            const result = await executor.run(input, [loggerHandler, handler])
             return result
         } else {
-            const result = await executor.run(input)
+            const result = await executor.run(input, [loggerHandler])
             return result
         }
     }

packages/components/nodes/chains/ApiChain/GETApiChain.ts

@@ -1,8 +1,9 @@
 import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { APIChain } from 'langchain/chains'
-import { CustomChainHandler, getBaseClasses } from '../../../src/utils'
+import { getBaseClasses } from '../../../src/utils'
 import { BaseLanguageModel } from 'langchain/base_language'
 import { PromptTemplate } from 'langchain/prompts'
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
 
 export const API_URL_RAW_PROMPT_TEMPLATE = `You are given the below API Documentation:
 {api_docs}
@@ -18,6 +19,7 @@ export const API_RESPONSE_RAW_PROMPT_TEMPLATE =
 class GETApiChain_Chains implements INode {
     label: string
     name: string
+    version: number
     type: string
     icon: string
     category: string
@@ -28,6 +30,7 @@ class GETApiChain_Chains implements INode {
     constructor() {
         this.label = 'GET API Chain'
         this.name = 'getApiChain'
+        this.version = 1.0
         this.type = 'GETApiChain'
         this.icon = 'apichain.svg'
         this.category = 'Chains'
@@ -95,12 +98,14 @@ class GETApiChain_Chains implements INode {
         const ansPrompt = nodeData.inputs?.ansPrompt as string
 
         const chain = await getAPIChain(apiDocs, model, headers, urlPrompt, ansPrompt)
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
+
         if (options.socketIO && options.socketIOClientId) {
             const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId, 2)
-            const res = await chain.run(input, [handler])
+            const res = await chain.run(input, [loggerHandler, handler])
             return res
         } else {
-            const res = await chain.run(input)
+            const res = await chain.run(input, [loggerHandler])
             return res
         }
     }

packages/components/nodes/chains/ApiChain/OpenAPIChain.ts

@@ -0,0 +1,100 @@
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { APIChain, createOpenAPIChain } from 'langchain/chains'
+import { getBaseClasses } from '../../../src/utils'
+import { ChatOpenAI } from 'langchain/chat_models/openai'
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
+
+class OpenApiChain_Chains implements INode {
+    label: string
+    name: string
+    version: number
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'OpenAPI Chain'
+        this.name = 'openApiChain'
+        this.version = 1.0
+        this.type = 'OpenAPIChain'
+        this.icon = 'openapi.png'
+        this.category = 'Chains'
+        this.description = 'Chain that automatically select and call APIs based only on an OpenAPI spec'
+        this.baseClasses = [this.type, ...getBaseClasses(APIChain)]
+        this.inputs = [
+            {
+                label: 'ChatOpenAI Model',
+                name: 'model',
+                type: 'ChatOpenAI'
+            },
+            {
+                label: 'YAML Link',
+                name: 'yamlLink',
+                type: 'string',
+                placeholder: 'https://api.speak.com/openapi.yaml',
+                description: 'If YAML link is provided, uploaded YAML File will be ignored and YAML link will be used instead'
+            },
+            {
+                label: 'YAML File',
+                name: 'yamlFile',
+                type: 'file',
+                fileType: '.yaml',
+                description: 'If YAML link is provided, uploaded YAML File will be ignored and YAML link will be used instead'
+            },
+            {
+                label: 'Headers',
+                name: 'headers',
+                type: 'json',
+                additionalParams: true,
+                optional: true
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData): Promise<any> {
+        return await initChain(nodeData)
+    }
+
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+        const chain = await initChain(nodeData)
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
+
+        if (options.socketIO && options.socketIOClientId) {
+            const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
+            const res = await chain.run(input, [loggerHandler, handler])
+            return res
+        } else {
+            const res = await chain.run(input, [loggerHandler])
+            return res
+        }
+    }
+}
+
+const initChain = async (nodeData: INodeData) => {
+    const model = nodeData.inputs?.model as ChatOpenAI
+    const headers = nodeData.inputs?.headers as string
+    const yamlLink = nodeData.inputs?.yamlLink as string
+    const yamlFileBase64 = nodeData.inputs?.yamlFile as string
+
+    let yamlString = ''
+
+    if (yamlLink) {
+        yamlString = yamlLink
+    } else {
+        const splitDataURI = yamlFileBase64.split(',')
+        splitDataURI.pop()
+        const bf = Buffer.from(splitDataURI.pop() || '', 'base64')
+        yamlString = bf.toString('utf-8')
+    }
+
+    return await createOpenAPIChain(yamlString, {
+        llm: model,
+        headers: typeof headers === 'object' ? headers : headers ? JSON.parse(headers) : {},
+        verbose: process.env.DEBUG === 'true' ? true : false
+    })
+}
+
+module.exports = { nodeClass: OpenApiChain_Chains }

packages/components/nodes/chains/ApiChain/POSTApiChain.ts

@@ -1,12 +1,14 @@
 import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
-import { CustomChainHandler, getBaseClasses } from '../../../src/utils'
+import { getBaseClasses } from '../../../src/utils'
 import { BaseLanguageModel } from 'langchain/base_language'
 import { PromptTemplate } from 'langchain/prompts'
 import { API_RESPONSE_RAW_PROMPT_TEMPLATE, API_URL_RAW_PROMPT_TEMPLATE, APIChain } from './postCore'
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
 
 class POSTApiChain_Chains implements INode {
     label: string
     name: string
+    version: number
     type: string
     icon: string
     category: string
@@ -17,6 +19,7 @@ class POSTApiChain_Chains implements INode {
     constructor() {
         this.label = 'POST API Chain'
         this.name = 'postApiChain'
+        this.version = 1.0
         this.type = 'POSTApiChain'
         this.icon = 'apichain.svg'
         this.category = 'Chains'
@@ -84,12 +87,14 @@ class POSTApiChain_Chains implements INode {
         const ansPrompt = nodeData.inputs?.ansPrompt as string
 
         const chain = await getAPIChain(apiDocs, model, headers, urlPrompt, ansPrompt)
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
+
         if (options.socketIO && options.socketIOClientId) {
             const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId, 2)
-            const res = await chain.run(input, [handler])
+            const res = await chain.run(input, [loggerHandler, handler])
             return res
         } else {
-            const res = await chain.run(input)
+            const res = await chain.run(input, [loggerHandler])
             return res
         }
     }

packages/components/nodes/chains/ConversationChain/ConversationChain.ts

@@ -1,16 +1,20 @@
 import { ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { ConversationChain } from 'langchain/chains'
-import { CustomChainHandler, getBaseClasses } from '../../../src/utils'
+import { getBaseClasses } from '../../../src/utils'
 import { ChatPromptTemplate, HumanMessagePromptTemplate, MessagesPlaceholder, SystemMessagePromptTemplate } from 'langchain/prompts'
 import { BufferMemory, ChatMessageHistory } from 'langchain/memory'
 import { BaseChatModel } from 'langchain/chat_models/base'
-import { AIChatMessage, HumanChatMessage } from 'langchain/schema'
+import { AIMessage, HumanMessage } from 'langchain/schema'
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
+import { flatten } from 'lodash'
+import { Document } from 'langchain/document'
 
-const systemMessage = `The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.`
+let systemMessage = `The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.`
 
 class ConversationChain_Chains implements INode {
     label: string
     name: string
+    version: number
     type: string
     icon: string
     category: string
@@ -21,6 +25,7 @@ class ConversationChain_Chains implements INode {
     constructor() {
         this.label = 'Conversation Chain'
         this.name = 'conversationChain'
+        this.version = 1.0
         this.type = 'ConversationChain'
         this.icon = 'chain.svg'
         this.category = 'Chains'
@@ -37,6 +42,14 @@ class ConversationChain_Chains implements INode {
                 name: 'memory',
                 type: 'BaseMemory'
             },
+            {
+                label: 'Document',
+                name: 'document',
+                type: 'Document',
+                description: 'Include whole document into the context window',
+                optional: true,
+                list: true
+            },
             {
                 label: 'System Message',
                 name: 'systemMessagePrompt',
@@ -53,6 +66,23 @@ class ConversationChain_Chains implements INode {
         const model = nodeData.inputs?.model as BaseChatModel
         const memory = nodeData.inputs?.memory as BufferMemory
         const prompt = nodeData.inputs?.systemMessagePrompt as string
+        const docs = nodeData.inputs?.document as Document[]
+
+        const flattenDocs = docs && docs.length ? flatten(docs) : []
+        const finalDocs = []
+        for (let i = 0; i < flattenDocs.length; i += 1) {
+            finalDocs.push(new Document(flattenDocs[i]))
+        }
+
+        let finalText = ''
+        for (let i = 0; i < finalDocs.length; i += 1) {
+            finalText += finalDocs[i].pageContent
+        }
+
+        const replaceChar: string[] = ['{', '}']
+        for (const char of replaceChar) finalText = finalText.replaceAll(char, '')
+
+        if (finalText) systemMessage = `${systemMessage}\nThe AI has the following context:\n${finalText}`
 
         const obj: any = {
             llm: model,
@@ -81,21 +111,23 @@ class ConversationChain_Chains implements INode {
 
             for (const message of histories) {
                 if (message.type === 'apiMessage') {
-                    chatHistory.push(new AIChatMessage(message.message))
+                    chatHistory.push(new AIMessage(message.message))
                 } else if (message.type === 'userMessage') {
-                    chatHistory.push(new HumanChatMessage(message.message))
+                    chatHistory.push(new HumanMessage(message.message))
                 }
             }
             memory.chatHistory = new ChatMessageHistory(chatHistory)
             chain.memory = memory
         }
 
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
+
         if (options.socketIO && options.socketIOClientId) {
             const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
-            const res = await chain.call({ input }, [handler])
+            const res = await chain.call({ input }, [loggerHandler, handler])
             return res?.response
         } else {
-            const res = await chain.call({ input })
+            const res = await chain.call({ input }, [loggerHandler])
             return res?.response
         }
     }

packages/components/nodes/chains/ConversationalRetrievalQAChain/ConversationalRetrievalQAChain.ts

@@ -1,28 +1,26 @@
 import { BaseLanguageModel } from 'langchain/base_language'
 import { ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface'
-import { CustomChainHandler, getBaseClasses } from '../../../src/utils'
-import { ConversationalRetrievalQAChain } from 'langchain/chains'
-import { AIChatMessage, BaseRetriever, HumanChatMessage } from 'langchain/schema'
-import { BaseChatMemory, BufferMemory, ChatMessageHistory } from 'langchain/memory'
+import { getBaseClasses } from '../../../src/utils'
+import { ConversationalRetrievalQAChain, QAChainParams } from 'langchain/chains'
+import { AIMessage, HumanMessage } from 'langchain/schema'
+import { BaseRetriever } from 'langchain/schema/retriever'
+import { BaseChatMemory, BufferMemory, ChatMessageHistory, BufferMemoryInput } from 'langchain/memory'
 import { PromptTemplate } from 'langchain/prompts'
-
-const default_qa_template = `Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.
-
-{context}
-
-Question: {question}
-Helpful Answer:`
-
-const qa_template = `Use the following pieces of context to answer the question at the end.
-
-{context}
-
-Question: {question}
-Helpful Answer:`
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
+import {
+    default_map_reduce_template,
+    default_qa_template,
+    qa_template,
+    map_reduce_template,
+    CUSTOM_QUESTION_GENERATOR_CHAIN_PROMPT,
+    refine_question_template,
+    refine_template
+} from './prompts'
 
 class ConversationalRetrievalQAChain_Chains implements INode {
     label: string
     name: string
+    version: number
     type: string
     icon: string
     category: string
@@ -33,6 +31,7 @@ class ConversationalRetrievalQAChain_Chains implements INode {
     constructor() {
         this.label = 'Conversational Retrieval QA Chain'
         this.name = 'conversationalRetrievalQAChain'
+        this.version = 1.0
         this.type = 'ConversationalRetrievalQAChain'
         this.icon = 'chain.svg'
         this.category = 'Chains'
@@ -49,6 +48,13 @@ class ConversationalRetrievalQAChain_Chains implements INode {
                 name: 'vectorStoreRetriever',
                 type: 'BaseRetriever'
             },
+            {
+                label: 'Memory',
+                name: 'memory',
+                type: 'BaseMemory',
+                optional: true,
+                description: 'If left empty, a default BufferMemory will be used'
+            },
             {
                 label: 'Return Source Documents',
                 name: 'returnSourceDocuments',
@@ -99,22 +105,59 @@ class ConversationalRetrievalQAChain_Chains implements INode {
         const systemMessagePrompt = nodeData.inputs?.systemMessagePrompt as string
         const returnSourceDocuments = nodeData.inputs?.returnSourceDocuments as boolean
         const chainOption = nodeData.inputs?.chainOption as string
+        const memory = nodeData.inputs?.memory
 
         const obj: any = {
             verbose: process.env.DEBUG === 'true' ? true : false,
-            qaChainOptions: {
-                type: 'stuff',
-                prompt: PromptTemplate.fromTemplate(systemMessagePrompt ? `${systemMessagePrompt}\n${qa_template}` : default_qa_template)
-            },
-            memory: new BufferMemory({
-                memoryKey: 'chat_history',
-                inputKey: 'question',
-                outputKey: 'text',
-                returnMessages: true
-            })
+            questionGeneratorChainOptions: {
+                template: CUSTOM_QUESTION_GENERATOR_CHAIN_PROMPT
+            }
         }
         if (returnSourceDocuments) obj.returnSourceDocuments = returnSourceDocuments
-        if (chainOption) obj.qaChainOptions = { ...obj.qaChainOptions, type: chainOption }
+        if (chainOption === 'map_reduce') {
+            obj.qaChainOptions = {
+                type: 'map_reduce',
+                combinePrompt: PromptTemplate.fromTemplate(
+                    systemMessagePrompt ? `${systemMessagePrompt}\n${map_reduce_template}` : default_map_reduce_template
+                )
+            } as QAChainParams
+        } else if (chainOption === 'refine') {
+            const qprompt = new PromptTemplate({
+                inputVariables: ['context', 'question'],
+                template: refine_question_template(systemMessagePrompt)
+            })
+            const rprompt = new PromptTemplate({
+                inputVariables: ['context', 'question', 'existing_answer'],
+                template: refine_template
+            })
+            obj.qaChainOptions = {
+                type: 'refine',
+                questionPrompt: qprompt,
+                refinePrompt: rprompt
+            } as QAChainParams
+        } else {
+            obj.qaChainOptions = {
+                type: 'stuff',
+                prompt: PromptTemplate.fromTemplate(systemMessagePrompt ? `${systemMessagePrompt}\n${qa_template}` : default_qa_template)
+            } as QAChainParams
+        }
+
+        if (memory) {
+            memory.inputKey = 'question'
+            memory.memoryKey = 'chat_history'
+            if (chainOption === 'refine') memory.outputKey = 'output_text'
+            else memory.outputKey = 'text'
+            obj.memory = memory
+        } else {
+            const fields: BufferMemoryInput = {
+                memoryKey: 'chat_history',
+                inputKey: 'question',
+                returnMessages: true
+            }
+            if (chainOption === 'refine') fields.outputKey = 'output_text'
+            else fields.outputKey = 'text'
+            obj.memory = new BufferMemory(fields)
+        }
 
         const chain = ConversationalRetrievalQAChain.fromLLM(model, vectorStoreRetriever, obj)
         return chain
@@ -123,6 +166,9 @@ class ConversationalRetrievalQAChain_Chains implements INode {
     async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | ICommonObject> {
         const chain = nodeData.instance as ConversationalRetrievalQAChain
         const returnSourceDocuments = nodeData.inputs?.returnSourceDocuments as boolean
+        const memory = nodeData.inputs?.memory
+        const chainOption = nodeData.inputs?.chainOption as string
+
         let model = nodeData.inputs?.model
 
         // Temporary fix: https://github.com/hwchase17/langchainjs/issues/754
@@ -131,29 +177,46 @@ class ConversationalRetrievalQAChain_Chains implements INode {
 
         const obj = { question: input }
 
-        if (chain.memory && options && options.chatHistory) {
+        // If external memory like Zep, Redis is being used, ignore below
+        if (!memory && chain.memory && options && options.chatHistory) {
             const chatHistory = []
             const histories: IMessage[] = options.chatHistory
             const memory = chain.memory as BaseChatMemory
 
             for (const message of histories) {
                 if (message.type === 'apiMessage') {
-                    chatHistory.push(new AIChatMessage(message.message))
+                    chatHistory.push(new AIMessage(message.message))
                 } else if (message.type === 'userMessage') {
-                    chatHistory.push(new HumanChatMessage(message.message))
+                    chatHistory.push(new HumanMessage(message.message))
                 }
             }
             memory.chatHistory = new ChatMessageHistory(chatHistory)
             chain.memory = memory
         }
 
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
+
         if (options.socketIO && options.socketIOClientId) {
-            const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId, undefined, returnSourceDocuments)
-            const res = await chain.call(obj, [handler])
+            const handler = new CustomChainHandler(
+                options.socketIO,
+                options.socketIOClientId,
+                chainOption === 'refine' ? 4 : undefined,
+                returnSourceDocuments
+            )
+            const res = await chain.call(obj, [loggerHandler, handler])
+            if (chainOption === 'refine') {
+                if (res.output_text && res.sourceDocuments) {
+                    return {
+                        text: res.output_text,
+                        sourceDocuments: res.sourceDocuments
+                    }
+                }
+                return res?.output_text
+            }
             if (res.text && res.sourceDocuments) return res
             return res?.text
         } else {
-            const res = await chain.call(obj)
+            const res = await chain.call(obj, [loggerHandler])
             if (res.text && res.sourceDocuments) return res
             return res?.text
         }

packages/components/nodes/chains/ConversationalRetrievalQAChain/prompts.ts

@@ -0,0 +1,64 @@
+export const default_qa_template = `Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.
+
+{context}
+
+Question: {question}
+Helpful Answer:`
+
+export const qa_template = `Use the following pieces of context to answer the question at the end.
+
+{context}
+
+Question: {question}
+Helpful Answer:`
+
+export const default_map_reduce_template = `Given the following extracted parts of a long document and a question, create a final answer. 
+If you don't know the answer, just say that you don't know. Don't try to make up an answer.
+
+{summaries}
+
+Question: {question}
+Helpful Answer:`
+
+export const map_reduce_template = `Given the following extracted parts of a long document and a question, create a final answer. 
+
+{summaries}
+
+Question: {question}
+Helpful Answer:`
+
+export const refine_question_template = (sysPrompt?: string) => {
+    let returnPrompt = ''
+    if (sysPrompt)
+        returnPrompt = `Context information is below. 
+---------------------
+{context}
+---------------------
+Given the context information and not prior knowledge, ${sysPrompt}
+Answer the question: {question}.
+Answer:`
+    if (!sysPrompt)
+        returnPrompt = `Context information is below. 
+---------------------
+{context}
+---------------------
+Given the context information and not prior knowledge, answer the question: {question}.
+Answer:`
+    return returnPrompt
+}
+
+export const refine_template = `The original question is as follows: {question}
+We have provided an existing answer: {existing_answer}
+We have the opportunity to refine the existing answer (only if needed) with some more context below.
+------------
+{context}
+------------
+Given the new context, refine the original answer to better answer the question. 
+If you can't find answer from the context, return the original answer.`
+
+export const CUSTOM_QUESTION_GENERATOR_CHAIN_PROMPT = `Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question, answer in the same language as the follow up question. include it in the standalone question.
+
+Chat History:
+{chat_history}
+Follow Up Input: {question}
+Standalone question:`

packages/components/nodes/chains/LLMChain/LLMChain.ts

@@ -1,11 +1,13 @@
 import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
-import { CustomChainHandler, getBaseClasses } from '../../../src/utils'
+import { getBaseClasses, handleEscapeCharacters } from '../../../src/utils'
 import { LLMChain } from 'langchain/chains'
 import { BaseLanguageModel } from 'langchain/base_language'
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
 
 class LLMChain_Chains implements INode {
     label: string
     name: string
+    version: number
     type: string
     icon: string
     category: string
@@ -17,6 +19,7 @@ class LLMChain_Chains implements INode {
     constructor() {
         this.label = 'LLM Chain'
         this.name = 'llmChain'
+        this.version = 1.0
         this.type = 'LLMChain'
         this.icon = 'chain.svg'
         this.category = 'Chains'
@@ -50,12 +53,12 @@ class LLMChain_Chains implements INode {
             {
                 label: 'Output Prediction',
                 name: 'outputPrediction',
-                baseClasses: ['string']
+                baseClasses: ['string', 'json']
             }
         ]
     }
 
-    async init(nodeData: INodeData, input: string): Promise<any> {
+    async init(nodeData: INodeData, input: string, options: ICommonObject): Promise<any> {
         const model = nodeData.inputs?.model as BaseLanguageModel
         const prompt = nodeData.inputs?.prompt
         const output = nodeData.outputs?.output as string
@@ -67,12 +70,17 @@ class LLMChain_Chains implements INode {
         } else if (output === 'outputPrediction') {
             const chain = new LLMChain({ llm: model, prompt, verbose: process.env.DEBUG === 'true' ? true : false })
             const inputVariables = chain.prompt.inputVariables as string[] // ["product"]
-            const res = await runPrediction(inputVariables, chain, input, promptValues)
+            const res = await runPrediction(inputVariables, chain, input, promptValues, options)
             // eslint-disable-next-line no-console
             console.log('\x1b[92m\x1b[1m\n*****OUTPUT PREDICTION*****\n\x1b[0m\x1b[0m')
             // eslint-disable-next-line no-console
             console.log(res)
-            return res
+            /**
+             * Apply string transformation to convert special chars:
+             * FROM: hello i am ben\n\n\thow are you?
+             * TO: hello i am benFLOWISE_NEWLINEFLOWISE_NEWLINEFLOWISE_TABhow are you?
+             */
+            return handleEscapeCharacters(res, false)
         }
     }
 
@@ -80,10 +88,7 @@ class LLMChain_Chains implements INode {
         const inputVariables = nodeData.instance.prompt.inputVariables as string[] // ["product"]
         const chain = nodeData.instance as LLMChain
         const promptValues = nodeData.inputs?.prompt.promptValues as ICommonObject
-
-        const res = options.socketIO
-            ? await runPrediction(inputVariables, chain, input, promptValues, true, options.socketIO, options.socketIOClientId)
-            : await runPrediction(inputVariables, chain, input, promptValues)
+        const res = await runPrediction(inputVariables, chain, input, promptValues, options)
         // eslint-disable-next-line no-console
         console.log('\x1b[93m\x1b[1m\n*****FINAL RESULT*****\n\x1b[0m\x1b[0m')
         // eslint-disable-next-line no-console
@@ -96,21 +101,22 @@ const runPrediction = async (
     inputVariables: string[],
     chain: LLMChain,
     input: string,
-    promptValues: ICommonObject,
-    isStreaming?: boolean,
-    socketIO?: any,
-    socketIOClientId = ''
+    promptValuesRaw: ICommonObject,
+    options: ICommonObject
 ) => {
-    if (inputVariables.length === 1) {
-        if (isStreaming) {
-            const handler = new CustomChainHandler(socketIO, socketIOClientId)
-            const res = await chain.run(input, [handler])
-            return res
-        } else {
-            const res = await chain.run(input)
-            return res
-        }
-    } else if (inputVariables.length > 1) {
+    const loggerHandler = new ConsoleCallbackHandler(options.logger)
+    const isStreaming = options.socketIO && options.socketIOClientId
+    const socketIO = isStreaming ? options.socketIO : undefined
+    const socketIOClientId = isStreaming ? options.socketIOClientId : ''
+
+    /**
+     * Apply string transformation to reverse converted special chars:
+     * FROM: { "value": "hello i am benFLOWISE_NEWLINEFLOWISE_NEWLINEFLOWISE_TABhow are you?" }
+     * TO: { "value": "hello i am ben\n\n\thow are you?" }
+     */
+    const promptValues = handleEscapeCharacters(promptValuesRaw, true)
+
+    if (promptValues && inputVariables.length > 0) {
         let seen: string[] = []
 
         for (const variable of inputVariables) {
@@ -122,15 +128,13 @@ const runPrediction = async (
 
         if (seen.length === 0) {
             // All inputVariables have fixed values specified
-            const options = {
-                ...promptValues
-            }
+            const options = { ...promptValues }
             if (isStreaming) {
                 const handler = new CustomChainHandler(socketIO, socketIOClientId)
-                const res = await chain.call(options, [handler])
+                const res = await chain.call(options, [loggerHandler, handler])
                 return res?.text
             } else {
-                const res = await chain.call(options)
+                const res = await chain.call(options, [loggerHandler])
                 return res?.text
             }
         } else if (seen.length === 1) {
@@ -143,10 +147,10 @@ const runPrediction = async (
             }
             if (isStreaming) {
                 const handler = new CustomChainHandler(socketIO, socketIOClientId)
-                const res = await chain.call(options, [handler])
+                const res = await chain.call(options, [loggerHandler, handler])
                 return res?.text
             } else {
-                const res = await chain.call(options)
+                const res = await chain.call(options, [loggerHandler])
                 return res?.text
             }
         } else {
@@ -155,10 +159,10 @@ const runPrediction = async (
     } else {
         if (isStreaming) {
             const handler = new CustomChainHandler(socketIO, socketIOClientId)
-            const res = await chain.run(input, [handler])
+            const res = await chain.run(input, [loggerHandler, handler])
             return res
         } else {
-            const res = await chain.run(input)
+            const res = await chain.run(input, [loggerHandler])
             return res
         }
     }

packages/components/nodes/chains/MultiPromptChain/MultiPromptChain.ts

@@ -1,11 +1,13 @@
 import { BaseLanguageModel } from 'langchain/base_language'
 import { ICommonObject, INode, INodeData, INodeParams, PromptRetriever } from '../../../src/Interface'
-import { CustomChainHandler, getBaseClasses } from '../../../src/utils'
+import { getBaseClasses } from '../../../src/utils'
 import { MultiPromptChain } from 'langchain/chains'
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
 
 class MultiPromptChain_Chains implements INode {
     label: string
     name: string
+    version: number
     type: string
     icon: string
     category: string
@@ -16,6 +18,7 @@ class MultiPromptChain_Chains implements INode {
     constructor() {
         this.label = 'Multi Prompt Chain'
         this.name = 'multiPromptChain'
+        this.version = 1.0
         this.type = 'MultiPromptChain'
         this.icon = 'chain.svg'
         this.category = 'Chains'
@@ -63,12 +66,14 @@ class MultiPromptChain_Chains implements INode {
         const chain = nodeData.instance as MultiPromptChain
         const obj = { input }
 
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
+
         if (options.socketIO && options.socketIOClientId) {
             const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId, 2)
-            const res = await chain.call(obj, [handler])
+            const res = await chain.call(obj, [loggerHandler, handler])
             return res?.text
         } else {
-            const res = await chain.call(obj)
+            const res = await chain.call(obj, [loggerHandler])
             return res?.text
         }
     }

packages/components/nodes/chains/MultiRetrievalQAChain/MultiRetrievalQAChain.ts

@@ -1,11 +1,13 @@
 import { BaseLanguageModel } from 'langchain/base_language'
 import { ICommonObject, INode, INodeData, INodeParams, VectorStoreRetriever } from '../../../src/Interface'
-import { CustomChainHandler, getBaseClasses } from '../../../src/utils'
+import { getBaseClasses } from '../../../src/utils'
 import { MultiRetrievalQAChain } from 'langchain/chains'
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
 
 class MultiRetrievalQAChain_Chains implements INode {
     label: string
     name: string
+    version: number
     type: string
     icon: string
     category: string
@@ -16,6 +18,7 @@ class MultiRetrievalQAChain_Chains implements INode {
     constructor() {
         this.label = 'Multi Retrieval QA Chain'
         this.name = 'multiRetrievalQAChain'
+        this.version = 1.0
         this.type = 'MultiRetrievalQAChain'
         this.icon = 'chain.svg'
         this.category = 'Chains'
@@ -71,14 +74,15 @@ class MultiRetrievalQAChain_Chains implements INode {
         const returnSourceDocuments = nodeData.inputs?.returnSourceDocuments as boolean
 
         const obj = { input }
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
 
         if (options.socketIO && options.socketIOClientId) {
             const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId, 2, returnSourceDocuments)
-            const res = await chain.call(obj, [handler])
+            const res = await chain.call(obj, [loggerHandler, handler])
             if (res.text && res.sourceDocuments) return res
             return res?.text
         } else {
-            const res = await chain.call(obj)
+            const res = await chain.call(obj, [loggerHandler])
             if (res.text && res.sourceDocuments) return res
             return res?.text
         }

packages/components/nodes/chains/RetrievalQAChain/RetrievalQAChain.ts

@@ -1,12 +1,14 @@
 import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { RetrievalQAChain } from 'langchain/chains'
-import { BaseRetriever } from 'langchain/schema'
-import { CustomChainHandler, getBaseClasses } from '../../../src/utils'
+import { BaseRetriever } from 'langchain/schema/retriever'
+import { getBaseClasses } from '../../../src/utils'
 import { BaseLanguageModel } from 'langchain/base_language'
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
 
 class RetrievalQAChain_Chains implements INode {
     label: string
     name: string
+    version: number
     type: string
     icon: string
     category: string
@@ -17,6 +19,7 @@ class RetrievalQAChain_Chains implements INode {
     constructor() {
         this.label = 'Retrieval QA Chain'
         this.name = 'retrievalQAChain'
+        this.version = 1.0
         this.type = 'RetrievalQAChain'
         this.icon = 'chain.svg'
         this.category = 'Chains'
@@ -49,13 +52,14 @@ class RetrievalQAChain_Chains implements INode {
         const obj = {
             query: input
         }
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
 
         if (options.socketIO && options.socketIOClientId) {
             const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
-            const res = await chain.call(obj, [handler])
+            const res = await chain.call(obj, [loggerHandler, handler])
             return res?.text
         } else {
-            const res = await chain.call(obj)
+            const res = await chain.call(obj, [loggerHandler])
             return res?.text
         }
     }

packages/components/nodes/chains/SqlDatabaseChain/SqlDatabaseChain.ts

@@ -1,13 +1,15 @@
 import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
-import { SqlDatabaseChain, SqlDatabaseChainInput } from 'langchain/chains'
-import { CustomChainHandler, getBaseClasses } from '../../../src/utils'
+import { SqlDatabaseChain, SqlDatabaseChainInput } from 'langchain/chains/sql_db'
+import { getBaseClasses } from '../../../src/utils'
 import { DataSource } from 'typeorm'
 import { SqlDatabase } from 'langchain/sql_db'
 import { BaseLanguageModel } from 'langchain/base_language'
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
 
 class SqlDatabaseChain_Chains implements INode {
     label: string
     name: string
+    version: number
     type: string
     icon: string
     category: string
@@ -18,6 +20,7 @@ class SqlDatabaseChain_Chains implements INode {
     constructor() {
         this.label = 'Sql Database Chain'
         this.name = 'sqlDatabaseChain'
+        this.version = 1.0
         this.type = 'SqlDatabaseChain'
         this.icon = 'sqlchain.svg'
         this.category = 'Chains'
@@ -65,12 +68,14 @@ class SqlDatabaseChain_Chains implements INode {
         const dbFilePath = nodeData.inputs?.dbFilePath
 
         const chain = await getSQLDBChain(databaseType, dbFilePath, model)
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
+
         if (options.socketIO && options.socketIOClientId) {
-            const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
-            const res = await chain.run(input, [handler])
+            const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId, 2)
+            const res = await chain.run(input, [loggerHandler, handler])
             return res
         } else {
-            const res = await chain.run(input)
+            const res = await chain.run(input, [loggerHandler])
             return res
         }
     }

packages/components/nodes/chains/VectorDBQAChain/VectorDBQAChain.ts

@@ -1,12 +1,14 @@
 import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
-import { CustomChainHandler, getBaseClasses } from '../../../src/utils'
+import { getBaseClasses } from '../../../src/utils'
 import { VectorDBQAChain } from 'langchain/chains'
 import { BaseLanguageModel } from 'langchain/base_language'
 import { VectorStore } from 'langchain/vectorstores'
+import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler'
 
 class VectorDBQAChain_Chains implements INode {
     label: string
     name: string
+    version: number
     type: string
     icon: string
     category: string
@@ -17,6 +19,7 @@ class VectorDBQAChain_Chains implements INode {
     constructor() {
         this.label = 'VectorDB QA Chain'
         this.name = 'vectorDBQAChain'
+        this.version = 1.0
         this.type = 'VectorDBQAChain'
         this.icon = 'chain.svg'
         this.category = 'Chains'
@@ -53,12 +56,14 @@ class VectorDBQAChain_Chains implements INode {
             query: input
         }
 
+        const loggerHandler = new ConsoleCallbackHandler(options.logger)
+
         if (options.socketIO && options.socketIOClientId) {
             const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
-            const res = await chain.call(obj, [handler])
+            const res = await chain.call(obj, [loggerHandler, handler])
             return res?.text
         } else {
-            const res = await chain.call(obj)
+            const res = await chain.call(obj, [loggerHandler])
             return res?.text
         }
     }

packages/components/nodes/chatmodels/AzureChatOpenAI/Azure.svg

@@ -1,5 +1 @@
-<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-brand-azure" width="24" height="24" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round">
-   <path stroke="none" d="M0 0h24v24H0z" fill="none"></path>
-   <path d="M6 7.5l-4 9.5h4l6 -15z"></path>
-   <path d="M22 20l-7 -15l-3 7l4 5l-8 3z"></path>
-</svg>
+<svg xmlns="http://www.w3.org/2000/svg"  viewBox="0 0 48 48" width="96px" height="96px"><path fill="#035bda" d="M46 40L29.317 10.852 22.808 23.96 34.267 37.24 13 39.655zM13.092 18.182L2 36.896 11.442 35.947 28.033 5.678z"/></svg>

packages/components/nodes/chatmodels/AzureChatOpenAI/AzureChatOpenAI.ts

@@ -1,32 +1,36 @@
 import { OpenAIBaseInput } from 'langchain/dist/types/openai-types'
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { getBaseClasses } from '../../../src/utils'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
 import { AzureOpenAIInput, ChatOpenAI } from 'langchain/chat_models/openai'
 
 class AzureChatOpenAI_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 = 'Azure ChatOpenAI'
         this.name = 'azureChatOpenAI'
+        this.version = 1.0
         this.type = 'AzureChatOpenAI'
         this.icon = 'Azure.svg'
         this.category = 'Chat Models'
         this.description = 'Wrapper around Azure OpenAI large language models that use the Chat endpoint'
         this.baseClasses = [this.type, ...getBaseClasses(ChatOpenAI)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['azureOpenAIApi']
+        }
         this.inputs = [
-            {
-                label: 'Azure OpenAI Api Key',
-                name: 'azureOpenAIApiKey',
-                type: 'password'
-            },
             {
                 label: 'Model Name',
                 name: 'modelName',
@@ -43,6 +47,10 @@ class AzureChatOpenAI_ChatModels implements INode {
                     {
                         label: 'gpt-35-turbo',
                         name: 'gpt-35-turbo'
+                    },
+                    {
+                        label: 'gpt-35-turbo-16k',
+                        name: 'gpt-35-turbo-16k'
                     }
                 ],
                 default: 'gpt-35-turbo',
@@ -52,37 +60,15 @@ class AzureChatOpenAI_ChatModels implements INode {
                 label: 'Temperature',
                 name: 'temperature',
                 type: 'number',
+                step: 0.1,
                 default: 0.9,
                 optional: true
             },
-            {
-                label: 'Azure OpenAI Api Instance Name',
-                name: 'azureOpenAIApiInstanceName',
-                type: 'string',
-                placeholder: 'YOUR-INSTANCE-NAME'
-            },
-            {
-                label: 'Azure OpenAI Api Deployment Name',
-                name: 'azureOpenAIApiDeploymentName',
-                type: 'string',
-                placeholder: 'YOUR-DEPLOYMENT-NAME'
-            },
-            {
-                label: 'Azure OpenAI Api Version',
-                name: 'azureOpenAIApiVersion',
-                type: 'options',
-                options: [
-                    {
-                        label: '2023-03-15-preview',
-                        name: '2023-03-15-preview'
-                    }
-                ],
-                default: '2023-03-15-preview'
-            },
             {
                 label: 'Max Tokens',
                 name: 'maxTokens',
                 type: 'number',
+                step: 1,
                 optional: true,
                 additionalParams: true
             },
@@ -90,6 +76,7 @@ class AzureChatOpenAI_ChatModels implements INode {
                 label: 'Frequency Penalty',
                 name: 'frequencyPenalty',
                 type: 'number',
+                step: 0.1,
                 optional: true,
                 additionalParams: true
             },
@@ -97,6 +84,7 @@ class AzureChatOpenAI_ChatModels implements INode {
                 label: 'Presence Penalty',
                 name: 'presencePenalty',
                 type: 'number',
+                step: 0.1,
                 optional: true,
                 additionalParams: true
             },
@@ -104,27 +92,30 @@ class AzureChatOpenAI_ChatModels implements INode {
                 label: 'Timeout',
                 name: 'timeout',
                 type: 'number',
+                step: 1,
                 optional: true,
                 additionalParams: true
             }
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
-        const azureOpenAIApiKey = nodeData.inputs?.azureOpenAIApiKey as string
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const modelName = nodeData.inputs?.modelName as string
         const temperature = nodeData.inputs?.temperature as string
-        const azureOpenAIApiInstanceName = nodeData.inputs?.azureOpenAIApiInstanceName as string
-        const azureOpenAIApiDeploymentName = nodeData.inputs?.azureOpenAIApiDeploymentName as string
-        const azureOpenAIApiVersion = nodeData.inputs?.azureOpenAIApiVersion as string
         const maxTokens = nodeData.inputs?.maxTokens as string
         const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
         const presencePenalty = nodeData.inputs?.presencePenalty as string
         const timeout = nodeData.inputs?.timeout as string
         const streaming = nodeData.inputs?.streaming as boolean
 
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const azureOpenAIApiKey = getCredentialParam('azureOpenAIApiKey', credentialData, nodeData)
+        const azureOpenAIApiInstanceName = getCredentialParam('azureOpenAIApiInstanceName', credentialData, nodeData)
+        const azureOpenAIApiDeploymentName = getCredentialParam('azureOpenAIApiDeploymentName', credentialData, nodeData)
+        const azureOpenAIApiVersion = getCredentialParam('azureOpenAIApiVersion', credentialData, nodeData)
+
         const obj: Partial<AzureOpenAIInput> & Partial<OpenAIBaseInput> = {
-            temperature: parseInt(temperature, 10),
+            temperature: parseFloat(temperature),
             modelName,
             azureOpenAIApiKey,
             azureOpenAIApiInstanceName,
@@ -134,8 +125,8 @@ class AzureChatOpenAI_ChatModels implements INode {
         }
 
         if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
-        if (frequencyPenalty) obj.frequencyPenalty = parseInt(frequencyPenalty, 10)
-        if (presencePenalty) obj.presencePenalty = parseInt(presencePenalty, 10)
+        if (frequencyPenalty) obj.frequencyPenalty = parseFloat(frequencyPenalty)
+        if (presencePenalty) obj.presencePenalty = parseFloat(presencePenalty)
         if (timeout) obj.timeout = parseInt(timeout, 10)
 
         const model = new ChatOpenAI(obj)

packages/components/nodes/chatmodels/ChatAnthropic/ChatAnthropic.ts

@@ -1,36 +1,50 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { getBaseClasses } from '../../../src/utils'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
 import { AnthropicInput, ChatAnthropic } from 'langchain/chat_models/anthropic'
 
 class ChatAnthropic_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 = 'ChatAnthropic'
         this.name = 'chatAnthropic'
+        this.version = 1.0
         this.type = 'ChatAnthropic'
         this.icon = 'chatAnthropic.png'
         this.category = 'Chat Models'
         this.description = 'Wrapper around ChatAnthropic large language models that use the Chat endpoint'
         this.baseClasses = [this.type, ...getBaseClasses(ChatAnthropic)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['anthropicApi']
+        }
         this.inputs = [
-            {
-                label: 'ChatAnthropic Api Key',
-                name: 'anthropicApiKey',
-                type: 'password'
-            },
             {
                 label: 'Model Name',
                 name: 'modelName',
                 type: 'options',
                 options: [
+                    {
+                        label: 'claude-2',
+                        name: 'claude-2',
+                        description: 'Claude 2 latest major version, automatically get updates to the model as they are released'
+                    },
+                    {
+                        label: 'claude-instant-1',
+                        name: 'claude-instant-1',
+                        description: 'Claude Instant latest major version, automatically get updates to the model as they are released'
+                    },
                     {
                         label: 'claude-v1',
                         name: 'claude-v1'
@@ -76,13 +90,14 @@ class ChatAnthropic_ChatModels implements INode {
                         name: 'claude-instant-v1.1-100k'
                     }
                 ],
-                default: 'claude-v1',
+                default: 'claude-2',
                 optional: true
             },
             {
                 label: 'Temperature',
                 name: 'temperature',
                 type: 'number',
+                step: 0.1,
                 default: 0.9,
                 optional: true
             },
@@ -90,6 +105,7 @@ class ChatAnthropic_ChatModels implements INode {
                 label: 'Max Tokens',
                 name: 'maxTokensToSample',
                 type: 'number',
+                step: 1,
                 optional: true,
                 additionalParams: true
             },
@@ -97,6 +113,7 @@ class ChatAnthropic_ChatModels implements INode {
                 label: 'Top P',
                 name: 'topP',
                 type: 'number',
+                step: 0.1,
                 optional: true,
                 additionalParams: true
             },
@@ -104,31 +121,34 @@ class ChatAnthropic_ChatModels implements INode {
                 label: 'Top K',
                 name: 'topK',
                 type: 'number',
+                step: 0.1,
                 optional: true,
                 additionalParams: true
             }
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const temperature = nodeData.inputs?.temperature as string
         const modelName = nodeData.inputs?.modelName as string
-        const anthropicApiKey = nodeData.inputs?.anthropicApiKey as string
         const maxTokensToSample = nodeData.inputs?.maxTokensToSample as string
         const topP = nodeData.inputs?.topP as string
         const topK = nodeData.inputs?.topK as string
         const streaming = nodeData.inputs?.streaming as boolean
 
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const anthropicApiKey = getCredentialParam('anthropicApiKey', credentialData, nodeData)
+
         const obj: Partial<AnthropicInput> & { anthropicApiKey?: string } = {
-            temperature: parseInt(temperature, 10),
+            temperature: parseFloat(temperature),
             modelName,
             anthropicApiKey,
             streaming: streaming ?? true
         }
 
         if (maxTokensToSample) obj.maxTokensToSample = parseInt(maxTokensToSample, 10)
-        if (topP) obj.topP = parseInt(topP, 10)
-        if (topK) obj.topK = parseInt(topK, 10)
+        if (topP) obj.topP = parseFloat(topP)
+        if (topK) obj.topK = parseFloat(topK)
 
         const model = new ChatAnthropic(obj)
         return model

packages/components/nodes/chatmodels/ChatHuggingFace/ChatHuggingFace.ts

@@ -1,41 +1,56 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { getBaseClasses } from '../../../src/utils'
-import { HFInput, HuggingFaceInference } from 'langchain/llms/hf'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+import { HFInput, HuggingFaceInference } from './core'
 
 class ChatHuggingFace_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 = 'ChatHuggingFace'
         this.name = 'chatHuggingFace'
+        this.version = 1.0
         this.type = 'ChatHuggingFace'
         this.icon = 'huggingface.png'
         this.category = 'Chat Models'
         this.description = 'Wrapper around HuggingFace large language models'
         this.baseClasses = [this.type, 'BaseChatModel', ...getBaseClasses(HuggingFaceInference)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['huggingFaceApi']
+        }
         this.inputs = [
             {
                 label: 'Model',
                 name: 'model',
                 type: 'string',
-                placeholder: 'gpt2'
+                description: 'If using own inference endpoint, leave this blank',
+                placeholder: 'gpt2',
+                optional: true
             },
             {
-                label: 'HuggingFace Api Key',
-                name: 'apiKey',
-                type: 'password'
+                label: 'Endpoint',
+                name: 'endpoint',
+                type: 'string',
+                placeholder: 'https://xyz.eu-west-1.aws.endpoints.huggingface.cloud/gpt2',
+                description: 'Using your own inference endpoint',
+                optional: true
             },
             {
                 label: 'Temperature',
                 name: 'temperature',
                 type: 'number',
+                step: 0.1,
                 description: 'Temperature parameter may not apply to certain model. Please check available model parameters',
                 optional: true,
                 additionalParams: true
@@ -44,6 +59,7 @@ class ChatHuggingFace_ChatModels implements INode {
                 label: 'Max Tokens',
                 name: 'maxTokens',
                 type: 'number',
+                step: 1,
                 description: 'Max Tokens parameter may not apply to certain model. Please check available model parameters',
                 optional: true,
                 additionalParams: true
@@ -52,6 +68,7 @@ class ChatHuggingFace_ChatModels implements INode {
                 label: 'Top Probability',
                 name: 'topP',
                 type: 'number',
+                step: 0.1,
                 description: 'Top Probability parameter may not apply to certain model. Please check available model parameters',
                 optional: true,
                 additionalParams: true
@@ -60,6 +77,7 @@ class ChatHuggingFace_ChatModels implements INode {
                 label: 'Top K',
                 name: 'hfTopK',
                 type: 'number',
+                step: 0.1,
                 description: 'Top K parameter may not apply to certain model. Please check available model parameters',
                 optional: true,
                 additionalParams: true
@@ -68,6 +86,7 @@ class ChatHuggingFace_ChatModels implements INode {
                 label: 'Frequency Penalty',
                 name: 'frequencyPenalty',
                 type: 'number',
+                step: 0.1,
                 description: 'Frequency Penalty parameter may not apply to certain model. Please check available model parameters',
                 optional: true,
                 additionalParams: true
@@ -75,25 +94,29 @@ class ChatHuggingFace_ChatModels implements INode {
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const model = nodeData.inputs?.model as string
-        const apiKey = nodeData.inputs?.apiKey as string
         const temperature = nodeData.inputs?.temperature as string
         const maxTokens = nodeData.inputs?.maxTokens as string
         const topP = nodeData.inputs?.topP as string
         const hfTopK = nodeData.inputs?.hfTopK as string
         const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
+        const endpoint = nodeData.inputs?.endpoint as string
+
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const huggingFaceApiKey = getCredentialParam('huggingFaceApiKey', credentialData, nodeData)
 
         const obj: Partial<HFInput> = {
             model,
-            apiKey
+            apiKey: huggingFaceApiKey
         }
 
-        if (temperature) obj.temperature = parseInt(temperature, 10)
+        if (temperature) obj.temperature = parseFloat(temperature)
         if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
-        if (topP) obj.topP = parseInt(topP, 10)
-        if (hfTopK) obj.topK = parseInt(hfTopK, 10)
-        if (frequencyPenalty) obj.frequencyPenalty = parseInt(frequencyPenalty, 10)
+        if (topP) obj.topP = parseFloat(topP)
+        if (hfTopK) obj.topK = parseFloat(hfTopK)
+        if (frequencyPenalty) obj.frequencyPenalty = parseFloat(frequencyPenalty)
+        if (endpoint) obj.endpoint = endpoint
 
         const huggingFace = new HuggingFaceInference(obj)
         return huggingFace

packages/components/nodes/chatmodels/ChatHuggingFace/core.ts

@@ -0,0 +1,113 @@
+import { getEnvironmentVariable } from '../../../src/utils'
+import { LLM, BaseLLMParams } from 'langchain/llms/base'
+
+export interface HFInput {
+    /** Model to use */
+    model: string
+
+    /** Sampling temperature to use */
+    temperature?: number
+
+    /**
+     * Maximum number of tokens to generate in the completion.
+     */
+    maxTokens?: number
+
+    /** Total probability mass of tokens to consider at each step */
+    topP?: number
+
+    /** Integer to define the top tokens considered within the sample operation to create new text. */
+    topK?: number
+
+    /** Penalizes repeated tokens according to frequency */
+    frequencyPenalty?: number
+
+    /** API key to use. */
+    apiKey?: string
+
+    /** Private endpoint to use. */
+    endpoint?: string
+}
+
+export class HuggingFaceInference extends LLM implements HFInput {
+    get lc_secrets(): { [key: string]: string } | undefined {
+        return {
+            apiKey: 'HUGGINGFACEHUB_API_KEY'
+        }
+    }
+
+    model = 'gpt2'
+
+    temperature: number | undefined = undefined
+
+    maxTokens: number | undefined = undefined
+
+    topP: number | undefined = undefined
+
+    topK: number | undefined = undefined
+
+    frequencyPenalty: number | undefined = undefined
+
+    apiKey: string | undefined = undefined
+
+    endpoint: string | undefined = undefined
+
+    constructor(fields?: Partial<HFInput> & BaseLLMParams) {
+        super(fields ?? {})
+
+        this.model = fields?.model ?? this.model
+        this.temperature = fields?.temperature ?? this.temperature
+        this.maxTokens = fields?.maxTokens ?? this.maxTokens
+        this.topP = fields?.topP ?? this.topP
+        this.topK = fields?.topK ?? this.topK
+        this.frequencyPenalty = fields?.frequencyPenalty ?? this.frequencyPenalty
+        this.endpoint = fields?.endpoint ?? ''
+        this.apiKey = fields?.apiKey ?? getEnvironmentVariable('HUGGINGFACEHUB_API_KEY')
+        if (!this.apiKey) {
+            throw new Error(
+                'Please set an API key for HuggingFace Hub in the environment variable HUGGINGFACEHUB_API_KEY or in the apiKey field of the HuggingFaceInference constructor.'
+            )
+        }
+    }
+
+    _llmType() {
+        return 'hf'
+    }
+
+    /** @ignore */
+    async _call(prompt: string, options: this['ParsedCallOptions']): Promise<string> {
+        const { HfInference } = await HuggingFaceInference.imports()
+        const hf = new HfInference(this.apiKey)
+        const obj: any = {
+            parameters: {
+                // make it behave similar to openai, returning only the generated text
+                return_full_text: false,
+                temperature: this.temperature,
+                max_new_tokens: this.maxTokens,
+                top_p: this.topP,
+                top_k: this.topK,
+                repetition_penalty: this.frequencyPenalty
+            },
+            inputs: prompt
+        }
+        if (this.endpoint) {
+            hf.endpoint(this.endpoint)
+        } else {
+            obj.model = this.model
+        }
+        const res = await this.caller.callWithOptions({ signal: options.signal }, hf.textGeneration.bind(hf), obj)
+        return res.generated_text
+    }
+
+    /** @ignore */
+    static async imports(): Promise<{
+        HfInference: typeof import('@huggingface/inference').HfInference
+    }> {
+        try {
+            const { HfInference } = await import('@huggingface/inference')
+            return { HfInference }
+        } catch (e) {
+            throw new Error('Please install huggingface as a dependency with, e.g. `yarn add @huggingface/inference`')
+        }
+    }
+}

packages/components/nodes/chatmodels/ChatLocalAI/ChatLocalAI.ts

@@ -6,6 +6,7 @@ import { OpenAIChatInput } from 'langchain/chat_models/openai'
 class ChatLocalAI_ChatModels implements INode {
     label: string
     name: string
+    version: number
     type: string
     icon: string
     category: string
@@ -16,6 +17,7 @@ class ChatLocalAI_ChatModels implements INode {
     constructor() {
         this.label = 'ChatLocalAI'
         this.name = 'chatLocalAI'
+        this.version = 1.0
         this.type = 'ChatLocalAI'
         this.icon = 'localai.png'
         this.category = 'Chat Models'
@@ -38,6 +40,7 @@ class ChatLocalAI_ChatModels implements INode {
                 label: 'Temperature',
                 name: 'temperature',
                 type: 'number',
+                step: 0.1,
                 default: 0.9,
                 optional: true
             },
@@ -45,6 +48,7 @@ class ChatLocalAI_ChatModels implements INode {
                 label: 'Max Tokens',
                 name: 'maxTokens',
                 type: 'number',
+                step: 1,
                 optional: true,
                 additionalParams: true
             },
@@ -52,6 +56,7 @@ class ChatLocalAI_ChatModels implements INode {
                 label: 'Top Probability',
                 name: 'topP',
                 type: 'number',
+                step: 0.1,
                 optional: true,
                 additionalParams: true
             },
@@ -59,6 +64,7 @@ class ChatLocalAI_ChatModels implements INode {
                 label: 'Timeout',
                 name: 'timeout',
                 type: 'number',
+                step: 1,
                 optional: true,
                 additionalParams: true
             }
@@ -74,13 +80,13 @@ class ChatLocalAI_ChatModels implements INode {
         const basePath = nodeData.inputs?.basePath as string
 
         const obj: Partial<OpenAIChatInput> & { openAIApiKey?: string } = {
-            temperature: parseInt(temperature, 10),
+            temperature: parseFloat(temperature),
             modelName,
             openAIApiKey: 'sk-'
         }
 
         if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
-        if (topP) obj.topP = parseInt(topP, 10)
+        if (topP) obj.topP = parseFloat(topP)
         if (timeout) obj.timeout = parseInt(timeout, 10)
 
         const model = new OpenAIChat(obj, { basePath })

packages/components/nodes/chatmodels/ChatOpenAI/ChatOpenAI.ts

@@ -1,31 +1,35 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { getBaseClasses } from '../../../src/utils'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
 import { ChatOpenAI, OpenAIChatInput } from 'langchain/chat_models/openai'
 
 class ChatOpenAI_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 = 'ChatOpenAI'
         this.name = 'chatOpenAI'
+        this.version = 1.0
         this.type = 'ChatOpenAI'
         this.icon = 'openai.png'
         this.category = 'Chat Models'
         this.description = 'Wrapper around OpenAI large language models that use the Chat endpoint'
         this.baseClasses = [this.type, ...getBaseClasses(ChatOpenAI)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['openAIApi']
+        }
         this.inputs = [
-            {
-                label: 'OpenAI Api Key',
-                name: 'openAIApiKey',
-                type: 'password'
-            },
             {
                 label: 'Model Name',
                 name: 'modelName',
@@ -71,6 +75,7 @@ class ChatOpenAI_ChatModels implements INode {
                 label: 'Temperature',
                 name: 'temperature',
                 type: 'number',
+                step: 0.1,
                 default: 0.9,
                 optional: true
             },
@@ -78,6 +83,7 @@ class ChatOpenAI_ChatModels implements INode {
                 label: 'Max Tokens',
                 name: 'maxTokens',
                 type: 'number',
+                step: 1,
                 optional: true,
                 additionalParams: true
             },
@@ -85,6 +91,7 @@ class ChatOpenAI_ChatModels implements INode {
                 label: 'Top Probability',
                 name: 'topP',
                 type: 'number',
+                step: 0.1,
                 optional: true,
                 additionalParams: true
             },
@@ -92,6 +99,7 @@ class ChatOpenAI_ChatModels implements INode {
                 label: 'Frequency Penalty',
                 name: 'frequencyPenalty',
                 type: 'number',
+                step: 0.1,
                 optional: true,
                 additionalParams: true
             },
@@ -99,6 +107,7 @@ class ChatOpenAI_ChatModels implements INode {
                 label: 'Presence Penalty',
                 name: 'presencePenalty',
                 type: 'number',
+                step: 0.1,
                 optional: true,
                 additionalParams: true
             },
@@ -106,6 +115,7 @@ class ChatOpenAI_ChatModels implements INode {
                 label: 'Timeout',
                 name: 'timeout',
                 type: 'number',
+                step: 1,
                 optional: true,
                 additionalParams: true
             },
@@ -119,10 +129,9 @@ class ChatOpenAI_ChatModels implements INode {
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const temperature = nodeData.inputs?.temperature as string
         const modelName = nodeData.inputs?.modelName as string
-        const openAIApiKey = nodeData.inputs?.openAIApiKey as string
         const maxTokens = nodeData.inputs?.maxTokens as string
         const topP = nodeData.inputs?.topP as string
         const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
@@ -131,17 +140,20 @@ class ChatOpenAI_ChatModels implements INode {
         const streaming = nodeData.inputs?.streaming as boolean
         const basePath = nodeData.inputs?.basepath as string
 
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, nodeData)
+
         const obj: Partial<OpenAIChatInput> & { openAIApiKey?: string } = {
-            temperature: parseInt(temperature, 10),
+            temperature: parseFloat(temperature),
             modelName,
             openAIApiKey,
             streaming: streaming ?? true
         }
 
         if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
-        if (topP) obj.topP = parseInt(topP, 10)
-        if (frequencyPenalty) obj.frequencyPenalty = parseInt(frequencyPenalty, 10)
-        if (presencePenalty) obj.presencePenalty = parseInt(presencePenalty, 10)
+        if (topP) obj.topP = parseFloat(topP)
+        if (frequencyPenalty) obj.frequencyPenalty = parseFloat(frequencyPenalty)
+        if (presencePenalty) obj.presencePenalty = parseFloat(presencePenalty)
         if (timeout) obj.timeout = parseInt(timeout, 10)
 
         const model = new ChatOpenAI(obj, {

packages/components/nodes/documentloaders/API/APILoader.ts

@@ -0,0 +1,200 @@
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { TextSplitter } from 'langchain/text_splitter'
+import { BaseDocumentLoader } from 'langchain/document_loaders/base'
+import { Document } from 'langchain/document'
+import axios, { AxiosRequestConfig } from 'axios'
+
+class API_DocumentLoaders implements INode {
+    label: string
+    name: string
+    version: number
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    inputs?: INodeParams[]
+
+    constructor() {
+        this.label = 'API Loader'
+        this.name = 'apiLoader'
+        this.version = 1.0
+        this.type = 'Document'
+        this.icon = 'api-loader.png'
+        this.category = 'Document Loaders'
+        this.description = `Load data from an API`
+        this.baseClasses = [this.type]
+        this.inputs = [
+            {
+                label: 'Text Splitter',
+                name: 'textSplitter',
+                type: 'TextSplitter',
+                optional: true
+            },
+            {
+                label: 'Method',
+                name: 'method',
+                type: 'options',
+                options: [
+                    {
+                        label: 'GET',
+                        name: 'GET'
+                    },
+                    {
+                        label: 'POST',
+                        name: 'POST'
+                    }
+                ]
+            },
+            {
+                label: 'URL',
+                name: 'url',
+                type: 'string'
+            },
+            {
+                label: 'Headers',
+                name: 'headers',
+                type: 'json',
+                additionalParams: true,
+                optional: true
+            },
+            {
+                label: 'Body',
+                name: 'body',
+                type: 'json',
+                description:
+                    'JSON body for the POST request. If not specified, agent will try to figure out itself from AIPlugin if provided',
+                additionalParams: true,
+                optional: true
+            }
+        ]
+    }
+    async init(nodeData: INodeData): Promise<any> {
+        const headers = nodeData.inputs?.headers as string
+        const url = nodeData.inputs?.url as string
+        const body = nodeData.inputs?.body as string
+        const method = nodeData.inputs?.method as string
+        const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
+        const metadata = nodeData.inputs?.metadata
+
+        const options: ApiLoaderParams = {
+            url,
+            method
+        }
+
+        if (headers) {
+            const parsedHeaders = typeof headers === 'object' ? headers : JSON.parse(headers)
+            options.headers = parsedHeaders
+        }
+
+        if (body) {
+            const parsedBody = typeof body === 'object' ? body : JSON.parse(body)
+            options.body = parsedBody
+        }
+
+        const loader = new ApiLoader(options)
+
+        let docs = []
+
+        if (textSplitter) {
+            docs = await loader.loadAndSplit(textSplitter)
+        } else {
+            docs = await loader.load()
+        }
+
+        if (metadata) {
+            const parsedMetadata = typeof metadata === 'object' ? metadata : JSON.parse(metadata)
+            let finaldocs = []
+            for (const doc of docs) {
+                const newdoc = {
+                    ...doc,
+                    metadata: {
+                        ...doc.metadata,
+                        ...parsedMetadata
+                    }
+                }
+                finaldocs.push(newdoc)
+            }
+            return finaldocs
+        }
+
+        return docs
+    }
+}
+
+interface ApiLoaderParams {
+    url: string
+    method: string
+    headers?: ICommonObject
+    body?: ICommonObject
+}
+
+class ApiLoader extends BaseDocumentLoader {
+    public readonly url: string
+
+    public readonly headers?: ICommonObject
+
+    public readonly body?: ICommonObject
+
+    public readonly method: string
+
+    constructor({ url, headers, body, method }: ApiLoaderParams) {
+        super()
+        this.url = url
+        this.headers = headers
+        this.body = body
+        this.method = method
+    }
+
+    public async load(): Promise<Document[]> {
+        if (this.method === 'POST') {
+            return this.executePostRequest(this.url, this.headers, this.body)
+        } else {
+            return this.executeGetRequest(this.url, this.headers)
+        }
+    }
+
+    protected async executeGetRequest(url: string, headers?: ICommonObject): Promise<Document[]> {
+        try {
+            const config: AxiosRequestConfig = {}
+            if (headers) {
+                config.headers = headers
+            }
+            const response = await axios.get(url, config)
+            const responseJsonString = JSON.stringify(response.data, null, 2)
+            const doc = new Document({
+                pageContent: responseJsonString,
+                metadata: {
+                    url
+                }
+            })
+            return [doc]
+        } catch (error) {
+            throw new Error(`Failed to fetch ${url}: ${error}`)
+        }
+    }
+
+    protected async executePostRequest(url: string, headers?: ICommonObject, body?: ICommonObject): Promise<Document[]> {
+        try {
+            const config: AxiosRequestConfig = {}
+            if (headers) {
+                config.headers = headers
+            }
+            const response = await axios.post(url, body ?? {}, config)
+            const responseJsonString = JSON.stringify(response.data, null, 2)
+            const doc = new Document({
+                pageContent: responseJsonString,
+                metadata: {
+                    url
+                }
+            })
+            return [doc]
+        } catch (error) {
+            throw new Error(`Failed to post ${url}: ${error}`)
+        }
+    }
+}
+
+module.exports = {
+    nodeClass: API_DocumentLoaders
+}

packages/components/nodes/documentloaders/Airtable/Airtable.ts

@@ -0,0 +1,230 @@
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { TextSplitter } from 'langchain/text_splitter'
+import { BaseDocumentLoader } from 'langchain/document_loaders/base'
+import { Document } from 'langchain/document'
+import axios from 'axios'
+import { getCredentialData, getCredentialParam } from '../../../src/utils'
+
+class Airtable_DocumentLoaders implements INode {
+    label: string
+    name: string
+    version: number
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    credential: INodeParams
+    inputs?: INodeParams[]
+
+    constructor() {
+        this.label = 'Airtable'
+        this.name = 'airtable'
+        this.version = 1.0
+        this.type = 'Document'
+        this.icon = 'airtable.svg'
+        this.category = 'Document Loaders'
+        this.description = `Load data from Airtable table`
+        this.baseClasses = [this.type]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['airtableApi']
+        }
+        this.inputs = [
+            {
+                label: 'Text Splitter',
+                name: 'textSplitter',
+                type: 'TextSplitter',
+                optional: true
+            },
+            {
+                label: 'Base Id',
+                name: 'baseId',
+                type: 'string',
+                placeholder: 'app11RobdGoX0YNsC',
+                description:
+                    'If your table URL looks like: https://airtable.com/app11RobdGoX0YNsC/tblJdmvbrgizbYICO/viw9UrP77Id0CE4ee, app11RovdGoX0YNsC is the base id'
+            },
+            {
+                label: 'Table Id',
+                name: 'tableId',
+                type: 'string',
+                placeholder: 'tblJdmvbrgizbYICO',
+                description:
+                    'If your table URL looks like: https://airtable.com/app11RobdGoX0YNsC/tblJdmvbrgizbYICO/viw9UrP77Id0CE4ee, tblJdmvbrgizbYICO is the table id'
+            },
+            {
+                label: 'Return All',
+                name: 'returnAll',
+                type: 'boolean',
+                default: true,
+                additionalParams: true,
+                description: 'If all results should be returned or only up to a given limit'
+            },
+            {
+                label: 'Limit',
+                name: 'limit',
+                type: 'number',
+                default: 100,
+                additionalParams: true,
+                description: 'Number of results to return'
+            },
+            {
+                label: 'Metadata',
+                name: 'metadata',
+                type: 'json',
+                optional: true,
+                additionalParams: true
+            }
+        ]
+    }
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
+        const baseId = nodeData.inputs?.baseId as string
+        const tableId = nodeData.inputs?.tableId as string
+        const returnAll = nodeData.inputs?.returnAll as boolean
+        const limit = nodeData.inputs?.limit as string
+        const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
+        const metadata = nodeData.inputs?.metadata
+
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const accessToken = getCredentialParam('accessToken', credentialData, nodeData)
+
+        const airtableOptions: AirtableLoaderParams = {
+            baseId,
+            tableId,
+            returnAll,
+            accessToken,
+            limit: limit ? parseInt(limit, 10) : 100
+        }
+
+        const loader = new AirtableLoader(airtableOptions)
+
+        let docs = []
+
+        if (textSplitter) {
+            docs = await loader.loadAndSplit(textSplitter)
+        } else {
+            docs = await loader.load()
+        }
+
+        if (metadata) {
+            const parsedMetadata = typeof metadata === 'object' ? metadata : JSON.parse(metadata)
+            let finaldocs = []
+            for (const doc of docs) {
+                const newdoc = {
+                    ...doc,
+                    metadata: {
+                        ...doc.metadata,
+                        ...parsedMetadata
+                    }
+                }
+                finaldocs.push(newdoc)
+            }
+            return finaldocs
+        }
+
+        return docs
+    }
+}
+
+interface AirtableLoaderParams {
+    baseId: string
+    tableId: string
+    accessToken: string
+    limit?: number
+    returnAll?: boolean
+}
+
+interface AirtableLoaderResponse {
+    records: AirtableLoaderPage[]
+    offset?: string
+}
+
+interface AirtableLoaderPage {
+    id: string
+    createdTime: string
+    fields: ICommonObject
+}
+
+class AirtableLoader extends BaseDocumentLoader {
+    public readonly baseId: string
+
+    public readonly tableId: string
+
+    public readonly accessToken: string
+
+    public readonly limit: number
+
+    public readonly returnAll: boolean
+
+    constructor({ baseId, tableId, accessToken, limit = 100, returnAll = false }: AirtableLoaderParams) {
+        super()
+        this.baseId = baseId
+        this.tableId = tableId
+        this.accessToken = accessToken
+        this.limit = limit
+        this.returnAll = returnAll
+    }
+
+    public async load(): Promise<Document[]> {
+        if (this.returnAll) {
+            return this.loadAll()
+        }
+        return this.loadLimit()
+    }
+
+    protected async fetchAirtableData(url: string, params: ICommonObject): Promise<AirtableLoaderResponse> {
+        try {
+            const headers = {
+                Authorization: `Bearer ${this.accessToken}`,
+                'Content-Type': 'application/json',
+                Accept: 'application/json'
+            }
+            const response = await axios.get(url, { params, headers })
+            return response.data
+        } catch (error) {
+            throw new Error(`Failed to fetch ${url} from Airtable: ${error}`)
+        }
+    }
+
+    private createDocumentFromPage(page: AirtableLoaderPage): Document {
+        // Generate the URL
+        const pageUrl = `https://api.airtable.com/v0/${this.baseId}/${this.tableId}/${page.id}`
+
+        // Return a langchain document
+        return new Document({
+            pageContent: JSON.stringify(page.fields, null, 2),
+            metadata: {
+                url: pageUrl
+            }
+        })
+    }
+
+    private async loadLimit(): Promise<Document[]> {
+        const params = { maxRecords: this.limit }
+        const data = await this.fetchAirtableData(`https://api.airtable.com/v0/${this.baseId}/${this.tableId}`, params)
+        if (data.records.length === 0) {
+            return []
+        }
+        return data.records.map((page) => this.createDocumentFromPage(page))
+    }
+
+    private async loadAll(): Promise<Document[]> {
+        const params: ICommonObject = { pageSize: 100 }
+        let data: AirtableLoaderResponse
+        let returnPages: AirtableLoaderPage[] = []
+
+        do {
+            data = await this.fetchAirtableData(`https://api.airtable.com/v0/${this.baseId}/${this.tableId}`, params)
+            returnPages.push.apply(returnPages, data.records)
+            params.offset = data.offset
+        } while (data.offset !== undefined)
+        return returnPages.map((page) => this.createDocumentFromPage(page))
+    }
+}
+
+module.exports = {
+    nodeClass: Airtable_DocumentLoaders
+}

packages/components/nodes/documentloaders/Airtable/airtable.svg

@@ -0,0 +1,9 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<svg width="256px" height="215px" viewBox="0 0 256 215" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" preserveAspectRatio="xMidYMid">
+	<g>
+		<path d="M114.25873,2.70101695 L18.8604023,42.1756384 C13.5552723,44.3711638 13.6102328,51.9065311 18.9486282,54.0225085 L114.746142,92.0117514 C123.163769,95.3498757 132.537419,95.3498757 140.9536,92.0117514 L236.75256,54.0225085 C242.08951,51.9065311 242.145916,44.3711638 236.83934,42.1756384 L141.442459,2.70101695 C132.738459,-0.900338983 122.961284,-0.900338983 114.25873,2.70101695" fill="#FFBF00"></path>
+		<path d="M136.349071,112.756863 L136.349071,207.659101 C136.349071,212.173089 140.900664,215.263892 145.096461,213.600615 L251.844122,172.166219 C254.281184,171.200072 255.879376,168.845451 255.879376,166.224705 L255.879376,71.3224678 C255.879376,66.8084791 251.327783,63.7176768 247.131986,65.3809537 L140.384325,106.815349 C137.94871,107.781496 136.349071,110.136118 136.349071,112.756863" fill="#26B5F8"></path>
+		<path d="M111.422771,117.65355 L79.742409,132.949912 L76.5257763,134.504714 L9.65047684,166.548104 C5.4112904,168.593211 0.000578531073,165.503855 0.000578531073,160.794612 L0.000578531073,71.7210757 C0.000578531073,70.0173017 0.874160452,68.5463864 2.04568588,67.4384994 C2.53454463,66.9481944 3.08848814,66.5446689 3.66412655,66.2250305 C5.26231864,65.2661153 7.54173107,65.0101153 9.47981017,65.7766689 L110.890522,105.957098 C116.045234,108.002206 116.450206,115.225166 111.422771,117.65355" fill="#ED3049"></path>
+		<path d="M111.422771,117.65355 L79.742409,132.949912 L2.04568588,67.4384994 C2.53454463,66.9481944 3.08848814,66.5446689 3.66412655,66.2250305 C5.26231864,65.2661153 7.54173107,65.0101153 9.47981017,65.7766689 L110.890522,105.957098 C116.045234,108.002206 116.450206,115.225166 111.422771,117.65355" fill-opacity="0.25" fill="#000000"></path>
+	</g>
+</svg>

packages/components/nodes/documentloaders/Cheerio/Cheerio.ts

@@ -2,11 +2,12 @@ import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { TextSplitter } from 'langchain/text_splitter'
 import { CheerioWebBaseLoader } from 'langchain/document_loaders/web/cheerio'
 import { test } from 'linkifyjs'
-import { getAvailableURLs } from '../../../src'
+import { webCrawl, xmlScrape } from '../../../src'
 
 class Cheerio_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -17,6 +18,7 @@ class Cheerio_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Cheerio Web Scraper'
         this.name = 'cheerioWebScraper'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'cheerio.svg'
         this.category = 'Document Loaders'
@@ -35,19 +37,34 @@ class Cheerio_DocumentLoaders implements INode {
                 optional: true
             },
             {
-                label: 'Web Scrap for Relative Links',
-                name: 'webScrap',
-                type: 'boolean',
+                label: 'Get Relative Links Method',
+                name: 'relativeLinksMethod',
+                type: 'options',
+                description: 'Select a method to retrieve relative links',
+                options: [
+                    {
+                        label: 'Web Crawl',
+                        name: 'webCrawl',
+                        description: 'Crawl relative links from HTML URL'
+                    },
+                    {
+                        label: 'Scrape XML Sitemap',
+                        name: 'scrapeXMLSitemap',
+                        description: 'Scrape relative links from XML sitemap URL'
+                    }
+                ],
                 optional: true,
                 additionalParams: true
             },
             {
-                label: 'Web Scrap Links Limit',
+                label: 'Get Relative Links Limit',
                 name: 'limit',
                 type: 'number',
-                default: 10,
                 optional: true,
-                additionalParams: true
+                additionalParams: true,
+                description:
+                    'Only used when "Get Relative Links Method" is selected. Set 0 to retrieve all relative links, default limit is 10.',
+                warning: `Retreiving all links might take long time, and all links will be upserted again if the flow's state changed (eg: different URL, chunk size, etc)`
             },
             {
                 label: 'Metadata',
@@ -62,7 +79,7 @@ class Cheerio_DocumentLoaders implements INode {
     async init(nodeData: INodeData): Promise<any> {
         const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
         const metadata = nodeData.inputs?.metadata
-        const webScrap = nodeData.inputs?.webScrap as boolean
+        const relativeLinksMethod = nodeData.inputs?.relativeLinksMethod as string
         let limit = nodeData.inputs?.limit as string
 
         let url = nodeData.inputs?.url as string
@@ -71,25 +88,34 @@ class Cheerio_DocumentLoaders implements INode {
             throw new Error('Invalid URL')
         }
 
-        const cheerioLoader = async (url: string): Promise<any> => {
-            let docs = []
-            const loader = new CheerioWebBaseLoader(url)
-            if (textSplitter) {
-                docs = await loader.loadAndSplit(textSplitter)
-            } else {
-                docs = await loader.load()
+        async function cheerioLoader(url: string): Promise<any> {
+            try {
+                let docs = []
+                const loader = new CheerioWebBaseLoader(url)
+                if (textSplitter) {
+                    docs = await loader.loadAndSplit(textSplitter)
+                } else {
+                    docs = await loader.load()
+                }
+                return docs
+            } catch (err) {
+                if (process.env.DEBUG === 'true') console.error(`error in CheerioWebBaseLoader: ${err.message}, on page: ${url}`)
             }
-            return docs
         }
 
-        let availableUrls: string[]
         let docs = []
-        if (webScrap) {
+        if (relativeLinksMethod) {
+            if (process.env.DEBUG === 'true') console.info(`Start ${relativeLinksMethod}`)
             if (!limit) limit = '10'
-            availableUrls = await getAvailableURLs(url, parseInt(limit))
-            for (let i = 0; i < availableUrls.length; i++) {
-                docs.push(...(await cheerioLoader(availableUrls[i])))
+            else if (parseInt(limit) < 0) throw new Error('Limit cannot be less than 0')
+            const pages: string[] =
+                relativeLinksMethod === 'webCrawl' ? await webCrawl(url, parseInt(limit)) : await xmlScrape(url, parseInt(limit))
+            if (process.env.DEBUG === 'true') console.info(`pages: ${JSON.stringify(pages)}, length: ${pages.length}`)
+            if (!pages || pages.length === 0) throw new Error('No relative links found')
+            for (const page of pages) {
+                docs.push(...(await cheerioLoader(page)))
             }
+            if (process.env.DEBUG === 'true') console.info(`Finish ${relativeLinksMethod}`)
         } else {
             docs = await cheerioLoader(url)
         }

packages/components/nodes/documentloaders/Confluence/Confluence.ts

@@ -1,25 +1,35 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { TextSplitter } from 'langchain/text_splitter'
 import { ConfluencePagesLoader, ConfluencePagesLoaderParams } from 'langchain/document_loaders/web/confluence'
+import { getCredentialData, getCredentialParam } from '../../../src'
 
 class Confluence_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
     category: string
     baseClasses: string[]
+    credential: INodeParams
     inputs: INodeParams[]
 
     constructor() {
         this.label = 'Confluence'
         this.name = 'confluence'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'confluence.png'
         this.category = 'Document Loaders'
         this.description = `Load data from a Confluence Document`
         this.baseClasses = [this.type]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['confluenceApi']
+        }
         this.inputs = [
             {
                 label: 'Text Splitter',
@@ -27,18 +37,6 @@ class Confluence_DocumentLoaders implements INode {
                 type: 'TextSplitter',
                 optional: true
             },
-            {
-                label: 'Username',
-                name: 'username',
-                type: 'string',
-                placeholder: '<CONFLUENCE_USERNAME>'
-            },
-            {
-                label: 'Access Token',
-                name: 'accessToken',
-                type: 'password',
-                placeholder: '<CONFLUENCE_ACCESS_TOKEN>'
-            },
             {
                 label: 'Base URL',
                 name: 'baseUrl',
@@ -49,7 +47,9 @@ class Confluence_DocumentLoaders implements INode {
                 label: 'Space Key',
                 name: 'spaceKey',
                 type: 'string',
-                placeholder: '~EXAMPLE362906de5d343d49dcdbae5dEXAMPLE'
+                placeholder: '~EXAMPLE362906de5d343d49dcdbae5dEXAMPLE',
+                description:
+                    'Refer to <a target="_blank" href="https://community.atlassian.com/t5/Confluence-questions/How-to-find-the-key-for-a-space/qaq-p/864760">official guide</a> on how to get Confluence Space Key'
             },
             {
                 label: 'Limit',
@@ -68,16 +68,18 @@ class Confluence_DocumentLoaders implements INode {
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
-        const username = nodeData.inputs?.username as string
-        const accessToken = nodeData.inputs?.accessToken as string
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const spaceKey = nodeData.inputs?.spaceKey as string
         const baseUrl = nodeData.inputs?.baseUrl as string
         const limit = nodeData.inputs?.limit as number
         const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
         const metadata = nodeData.inputs?.metadata
 
-        const options: ConfluencePagesLoaderParams = {
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const accessToken = getCredentialParam('accessToken', credentialData, nodeData)
+        const username = getCredentialParam('username', credentialData, nodeData)
+
+        const confluenceOptions: ConfluencePagesLoaderParams = {
             username,
             accessToken,
             baseUrl,
@@ -85,7 +87,7 @@ class Confluence_DocumentLoaders implements INode {
             limit
         }
 
-        const loader = new ConfluencePagesLoader(options)
+        const loader = new ConfluencePagesLoader(confluenceOptions)
 
         let docs = []
 

packages/components/nodes/documentloaders/Csv/Csv.ts

@@ -5,6 +5,7 @@ import { CSVLoader } from 'langchain/document_loaders/fs/csv'
 class Csv_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -15,6 +16,7 @@ class Csv_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Csv File'
         this.name = 'csvFile'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'Csv.png'
         this.category = 'Document Loaders'

packages/components/nodes/documentloaders/Docx/Docx.ts

@@ -5,6 +5,7 @@ import { DocxLoader } from 'langchain/document_loaders/fs/docx'
 class Docx_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -15,6 +16,7 @@ class Docx_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Docx File'
         this.name = 'docxFile'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'Docx.png'
         this.category = 'Document Loaders'

packages/components/nodes/documentloaders/Figma/Figma.ts

@@ -1,42 +1,50 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getCredentialData, getCredentialParam } from '../../../src'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { FigmaFileLoader, FigmaLoaderParams } from 'langchain/document_loaders/web/figma'
 
 class Figma_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
     category: string
     baseClasses: string[]
+    credential: INodeParams
     inputs: INodeParams[]
 
     constructor() {
         this.label = 'Figma'
         this.name = 'figma'
+        this.version = 1.0
         this.type = 'Document'
-        this.icon = 'figma.png'
+        this.icon = 'figma.svg'
         this.category = 'Document Loaders'
         this.description = 'Load data from a Figma file'
         this.baseClasses = [this.type]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['figmaApi']
+        }
         this.inputs = [
-            {
-                label: 'Access Token',
-                name: 'accessToken',
-                type: 'password',
-                placeholder: '<FIGMA_ACCESS_TOKEN>'
-            },
             {
                 label: 'File Key',
                 name: 'fileKey',
                 type: 'string',
-                placeholder: 'key'
+                placeholder: 'key',
+                description:
+                    'The file key can be read from any Figma file URL: https://www.figma.com/file/:key/:title. For example, in https://www.figma.com/file/12345/Website, the file key is 12345'
             },
             {
                 label: 'Node IDs',
                 name: 'nodeIds',
                 type: 'string',
-                placeholder: '0, 1, 2'
+                placeholder: '0, 1, 2',
+                description:
+                    'A list of Node IDs, seperated by comma. Refer to <a target="_blank" href="https://www.figma.com/community/plugin/758276196886757462/Node-Inspector">official guide</a> on how to get Node IDs'
             },
             {
                 label: 'Recursive',
@@ -60,18 +68,20 @@ class Figma_DocumentLoaders implements INode {
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
-        const accessToken = nodeData.inputs?.accessToken as string
-        const nodeIds = (nodeData.inputs?.nodeIds as string)?.split(',') || []
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
+        const nodeIds = (nodeData.inputs?.nodeIds as string)?.trim().split(',') || []
         const fileKey = nodeData.inputs?.fileKey as string
 
-        const options: FigmaLoaderParams = {
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const accessToken = getCredentialParam('accessToken', credentialData, nodeData)
+
+        const figmaOptions: FigmaLoaderParams = {
             accessToken,
             nodeIds,
             fileKey
         }
 
-        const loader = new FigmaFileLoader(options)
+        const loader = new FigmaFileLoader(figmaOptions)
         const docs = await loader.load()
 
         return docs

packages/components/nodes/documentloaders/Figma/figma.svg

@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg"  viewBox="0 0 48 48" width="96px" height="96px"><path fill="#e64a19" d="M26,17h-8c-3.866,0-7-3.134-7-7v0c0-3.866,3.134-7,7-7h8V17z"/><path fill="#7c4dff" d="M25,31h-7c-3.866,0-7-3.134-7-7v0c0-3.866,3.134-7,7-7h7V31z"/><path fill="#66bb6a" d="M18,45L18,45c-3.866,0-7-3.134-7-7v0c0-3.866,3.134-7,7-7h7v7C25,41.866,21.866,45,18,45z"/><path fill="#ff7043" d="M32,17h-7V3h7c3.866,0,7,3.134,7,7v0C39,13.866,35.866,17,32,17z"/><circle cx="32" cy="24" r="7" fill="#29b6f6"/></svg>

packages/components/nodes/documentloaders/Folder/Folder.ts

@@ -10,6 +10,7 @@ import { DocxLoader } from 'langchain/document_loaders/fs/docx'
 class Folder_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -20,6 +21,7 @@ class Folder_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Folder with Files'
         this.name = 'folderFiles'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'folder.svg'
         this.category = 'Document Loaders'

packages/components/nodes/documentloaders/Gitbook/Gitbook.ts

@@ -0,0 +1,84 @@
+import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { TextSplitter } from 'langchain/text_splitter'
+import { GitbookLoader } from 'langchain/document_loaders/web/gitbook'
+
+class Gitbook_DocumentLoaders implements INode {
+    label: string
+    name: string
+    version: number
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    inputs?: INodeParams[]
+
+    constructor() {
+        this.label = 'GitBook'
+        this.name = 'gitbook'
+        this.version = 1.0
+        this.type = 'Document'
+        this.icon = 'gitbook.svg'
+        this.category = 'Document Loaders'
+        this.description = `Load data from GitBook`
+        this.baseClasses = [this.type]
+        this.inputs = [
+            {
+                label: 'Web Path',
+                name: 'webPath',
+                type: 'string',
+                placeholder: 'https://docs.gitbook.com/product-tour/navigation',
+                description: 'If want to load all paths from the GitBook provide only root path e.g.https://docs.gitbook.com/ '
+            },
+            {
+                label: 'Should Load All Paths',
+                name: 'shouldLoadAllPaths',
+                type: 'boolean',
+                description: 'Load from all paths in a given GitBook',
+                optional: true
+            },
+            {
+                label: 'Text Splitter',
+                name: 'textSplitter',
+                type: 'TextSplitter',
+                optional: true
+            },
+            {
+                label: 'Metadata',
+                name: 'metadata',
+                type: 'json',
+                optional: true,
+                additionalParams: true
+            }
+        ]
+    }
+    async init(nodeData: INodeData): Promise<any> {
+        const webPath = nodeData.inputs?.webPath as string
+        const shouldLoadAllPaths = nodeData.inputs?.shouldLoadAllPaths as boolean
+        const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
+        const metadata = nodeData.inputs?.metadata
+
+        const loader = shouldLoadAllPaths ? new GitbookLoader(webPath, { shouldLoadAllPaths }) : new GitbookLoader(webPath)
+
+        const docs = textSplitter ? await loader.loadAndSplit() : await loader.load()
+
+        if (metadata) {
+            const parsedMetadata = typeof metadata === 'object' ? metadata : JSON.parse(metadata)
+            return docs.map((doc) => {
+                return {
+                    ...doc,
+                    metadata: {
+                        ...doc.metadata,
+                        ...parsedMetadata
+                    }
+                }
+            })
+        }
+
+        return docs
+    }
+}
+
+module.exports = {
+    nodeClass: Gitbook_DocumentLoaders
+}

packages/components/nodes/documentloaders/Gitbook/gitbook.svg

@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" width="64" height="64"><switch><g><path d="M28.8 47.4c1 0 1.9.8 1.9 1.9 0 1-.8 1.9-1.9 1.9-1 0-1.9-.8-1.9-1.9 0-1.1.9-1.9 1.9-1.9m29.4-11.6c-1 0-1.9-.8-1.9-1.9 0-1 .8-1.9 1.9-1.9 1 0 1.9.8 1.9 1.9 0 1-.9 1.9-1.9 1.9m0-7.7c-3.2 0-5.8 2.6-5.8 5.8 0 .6.1 1.2.3 1.8L33.6 45.9c-1.1-1.6-2.9-2.5-4.8-2.5-2.2 0-4.2 1.3-5.2 3.2l-17.2-9c-1.8-1-3.2-3.9-3-6.7.1-1.4.6-2.5 1.3-2.9.5-.3 1-.2 1.7.1l.1.1c4.6 2.4 19.5 10.2 20.1 10.5 1 .4 1.5.6 3.2-.2l30.8-16c.5-.2 1-.6 1-1.3 0-.9-.9-1.3-.9-1.3-1.8-.8-4.5-2.1-7.1-3.3C48 14 41.6 11 38.8 9.5c-2.4-1.3-4.4-.2-4.7 0l-.7.3C20.7 16.2 3.9 24.5 2.9 25.1c-1.7 1-2.8 3.1-2.9 5.7-.2 4.1 1.9 8.4 4.9 9.9l18.2 9.4c.4 2.8 2.9 5 5.7 5 3.2 0 5.7-2.5 5.8-5.7l20-10.8c1 .8 2.3 1.2 3.6 1.2 3.2 0 5.8-2.6 5.8-5.8 0-3.3-2.6-5.9-5.8-5.9" fill="#4285fd"/></g></switch></svg>

packages/components/nodes/documentloaders/Github/Github.ts

@@ -1,25 +1,37 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { TextSplitter } from 'langchain/text_splitter'
 import { GithubRepoLoader, GithubRepoLoaderParams } from 'langchain/document_loaders/web/github'
+import { getCredentialData, getCredentialParam } from '../../../src'
 
 class Github_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
     category: string
     baseClasses: string[]
+    credential: INodeParams
     inputs: INodeParams[]
 
     constructor() {
         this.label = 'Github'
         this.name = 'github'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'github.png'
         this.category = 'Document Loaders'
         this.description = `Load data from a GitHub repository`
         this.baseClasses = [this.type]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            description: 'Only needed when accessing private repo',
+            optional: true,
+            credentialNames: ['githubApi']
+        }
         this.inputs = [
             {
                 label: 'Repo Link',
@@ -33,13 +45,6 @@ class Github_DocumentLoaders implements INode {
                 type: 'string',
                 default: 'main'
             },
-            {
-                label: 'Access Token',
-                name: 'accessToken',
-                type: 'password',
-                placeholder: '<GITHUB_ACCESS_TOKEN>',
-                optional: true
-            },
             {
                 label: 'Recursive',
                 name: 'recursive',
@@ -62,23 +67,25 @@ class Github_DocumentLoaders implements INode {
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const repoLink = nodeData.inputs?.repoLink as string
         const branch = nodeData.inputs?.branch as string
         const recursive = nodeData.inputs?.recursive as boolean
-        const accessToken = nodeData.inputs?.accessToken as string
         const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
         const metadata = nodeData.inputs?.metadata
 
-        const options: GithubRepoLoaderParams = {
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const accessToken = getCredentialParam('accessToken', credentialData, nodeData)
+
+        const githubOptions: GithubRepoLoaderParams = {
             branch,
             recursive,
             unknown: 'warn'
         }
 
-        if (accessToken) options.accessToken = accessToken
+        if (accessToken) githubOptions.accessToken = accessToken
 
-        const loader = new GithubRepoLoader(repoLink, options)
+        const loader = new GithubRepoLoader(repoLink, githubOptions)
         const docs = textSplitter ? await loader.loadAndSplit(textSplitter) : await loader.load()
 
         if (metadata) {

packages/components/nodes/documentloaders/Json/Json.ts

@@ -5,6 +5,7 @@ import { JSONLoader } from 'langchain/document_loaders/fs/json'
 class Json_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -15,6 +16,7 @@ class Json_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Json File'
         this.name = 'jsonFile'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'json.svg'
         this.category = 'Document Loaders'

packages/components/nodes/documentloaders/Jsonlines/Jsonlines.ts

@@ -5,6 +5,7 @@ import { JSONLinesLoader } from 'langchain/document_loaders/fs/json'
 class Jsonlines_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -15,6 +16,7 @@ class Jsonlines_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Json Lines File'
         this.name = 'jsonlinesFile'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'jsonlines.svg'
         this.category = 'Document Loaders'

packages/components/nodes/documentloaders/Notion/NotionDB.ts

@@ -1,25 +1,35 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { TextSplitter } from 'langchain/text_splitter'
-import { NotionDBLoader, NotionDBLoaderParams } from 'langchain/document_loaders/web/notiondb'
+import { NotionAPILoader, NotionAPILoaderOptions } from 'langchain/document_loaders/web/notionapi'
+import { getCredentialData, getCredentialParam } from '../../../src'
 
 class NotionDB_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
     category: string
     baseClasses: string[]
+    credential: INodeParams
     inputs: INodeParams[]
 
     constructor() {
         this.label = 'Notion Database'
         this.name = 'notionDB'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'notion.png'
         this.category = 'Document Loaders'
-        this.description = 'Load data from Notion Database ID'
+        this.description = 'Load data from Notion Database (each row is a separate document with all properties as metadata)'
         this.baseClasses = [this.type]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['notionApi']
+        }
         this.inputs = [
             {
                 label: 'Text Splitter',
@@ -31,21 +41,7 @@ class NotionDB_DocumentLoaders implements INode {
                 label: 'Notion Database Id',
                 name: 'databaseId',
                 type: 'string',
-                description:
-                    'If your URL looks like - https://www.notion.so/<long_hash_1>?v=<long_hash_2>, then <long_hash_1> is the database ID'
-            },
-            {
-                label: 'Notion Integration Token',
-                name: 'notionIntegrationToken',
-                type: 'password',
-                description:
-                    'You can find integration token <a target="_blank" href="https://developers.notion.com/docs/create-a-notion-integration#step-1-create-an-integration">here</a>'
-            },
-            {
-                label: 'Page Size Limit',
-                name: 'pageSizeLimit',
-                type: 'number',
-                default: 10
+                description: 'If your URL looks like - https://www.notion.so/abcdefh?v=long_hash_2, then abcdefh is the database ID'
             },
             {
                 label: 'Metadata',
@@ -57,19 +53,22 @@ class NotionDB_DocumentLoaders implements INode {
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
         const databaseId = nodeData.inputs?.databaseId as string
-        const notionIntegrationToken = nodeData.inputs?.notionIntegrationToken as string
-        const pageSizeLimit = nodeData.inputs?.pageSizeLimit as string
         const metadata = nodeData.inputs?.metadata
 
-        const obj: NotionDBLoaderParams = {
-            pageSizeLimit: pageSizeLimit ? parseInt(pageSizeLimit, 10) : 10,
-            databaseId,
-            notionIntegrationToken
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const notionIntegrationToken = getCredentialParam('notionIntegrationToken', credentialData, nodeData)
+
+        const obj: NotionAPILoaderOptions = {
+            clientOptions: {
+                auth: notionIntegrationToken
+            },
+            id: databaseId,
+            type: 'database'
         }
-        const loader = new NotionDBLoader(obj)
+        const loader = new NotionAPILoader(obj)
 
         let docs = []
         if (textSplitter) {

packages/components/nodes/documentloaders/Notion/NotionFolder.ts

@@ -5,6 +5,7 @@ import { NotionLoader } from 'langchain/document_loaders/fs/notion'
 class NotionFolder_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -15,6 +16,7 @@ class NotionFolder_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Notion Folder'
         this.name = 'notionFolder'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'notion.png'
         this.category = 'Document Loaders'

packages/components/nodes/documentloaders/Notion/NotionPage.ts

@@ -0,0 +1,101 @@
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { TextSplitter } from 'langchain/text_splitter'
+import { NotionAPILoader, NotionAPILoaderOptions } from 'langchain/document_loaders/web/notionapi'
+import { getCredentialData, getCredentialParam } from '../../../src'
+
+class NotionPage_DocumentLoaders implements INode {
+    label: string
+    name: string
+    version: number
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    credential: INodeParams
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Notion Page'
+        this.name = 'notionPage'
+        this.version = 1.0
+        this.type = 'Document'
+        this.icon = 'notion.png'
+        this.category = 'Document Loaders'
+        this.description = 'Load data from Notion Page (including child pages all as separate documents)'
+        this.baseClasses = [this.type]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['notionApi']
+        }
+        this.inputs = [
+            {
+                label: 'Text Splitter',
+                name: 'textSplitter',
+                type: 'TextSplitter',
+                optional: true
+            },
+            {
+                label: 'Notion Page Id',
+                name: 'pageId',
+                type: 'string',
+                description:
+                    'The last The 32 char hex in the url path. For example: https://www.notion.so/skarard/LangChain-Notion-API-b34ca03f219c4420a6046fc4bdfdf7b4, b34ca03f219c4420a6046fc4bdfdf7b4 is the Page ID'
+            },
+            {
+                label: 'Metadata',
+                name: 'metadata',
+                type: 'json',
+                optional: true,
+                additionalParams: true
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
+        const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
+        const pageId = nodeData.inputs?.pageId as string
+        const metadata = nodeData.inputs?.metadata
+
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const notionIntegrationToken = getCredentialParam('notionIntegrationToken', credentialData, nodeData)
+
+        const obj: NotionAPILoaderOptions = {
+            clientOptions: {
+                auth: notionIntegrationToken
+            },
+            id: pageId,
+            type: 'page'
+        }
+        const loader = new NotionAPILoader(obj)
+
+        let docs = []
+        if (textSplitter) {
+            docs = await loader.loadAndSplit(textSplitter)
+        } else {
+            docs = await loader.load()
+        }
+
+        if (metadata) {
+            const parsedMetadata = typeof metadata === 'object' ? metadata : JSON.parse(metadata)
+            let finaldocs = []
+            for (const doc of docs) {
+                const newdoc = {
+                    ...doc,
+                    metadata: {
+                        ...doc.metadata,
+                        ...parsedMetadata
+                    }
+                }
+                finaldocs.push(newdoc)
+            }
+            return finaldocs
+        }
+
+        return docs
+    }
+}
+
+module.exports = { nodeClass: NotionPage_DocumentLoaders }

packages/components/nodes/documentloaders/Pdf/Pdf.ts

@@ -5,6 +5,7 @@ import { PDFLoader } from 'langchain/document_loaders/fs/pdf'
 class Pdf_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -15,6 +16,7 @@ class Pdf_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Pdf File'
         this.name = 'pdfFile'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'pdf.svg'
         this.category = 'Document Loaders'

packages/components/nodes/documentloaders/Playwright/Playwright.ts

@@ -2,11 +2,12 @@ import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { TextSplitter } from 'langchain/text_splitter'
 import { PlaywrightWebBaseLoader } from 'langchain/document_loaders/web/playwright'
 import { test } from 'linkifyjs'
-import { getAvailableURLs } from '../../../src'
+import { webCrawl, xmlScrape } from '../../../src'
 
 class Playwright_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -17,6 +18,7 @@ class Playwright_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Playwright Web Scraper'
         this.name = 'playwrightWebScraper'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'playwright.svg'
         this.category = 'Document Loaders'
@@ -35,19 +37,34 @@ class Playwright_DocumentLoaders implements INode {
                 optional: true
             },
             {
-                label: 'Web Scrap for Relative Links',
-                name: 'webScrap',
-                type: 'boolean',
+                label: 'Get Relative Links Method',
+                name: 'relativeLinksMethod',
+                type: 'options',
+                description: 'Select a method to retrieve relative links',
+                options: [
+                    {
+                        label: 'Web Crawl',
+                        name: 'webCrawl',
+                        description: 'Crawl relative links from HTML URL'
+                    },
+                    {
+                        label: 'Scrape XML Sitemap',
+                        name: 'scrapeXMLSitemap',
+                        description: 'Scrape relative links from XML sitemap URL'
+                    }
+                ],
                 optional: true,
                 additionalParams: true
             },
             {
-                label: 'Web Scrap Links Limit',
+                label: 'Get Relative Links Limit',
                 name: 'limit',
                 type: 'number',
-                default: 10,
                 optional: true,
-                additionalParams: true
+                additionalParams: true,
+                description:
+                    'Only used when "Get Relative Links Method" is selected. Set 0 to retrieve all relative links, default limit is 10.',
+                warning: `Retreiving all links might take long time, and all links will be upserted again if the flow's state changed (eg: different URL, chunk size, etc)`
             },
             {
                 label: 'Metadata',
@@ -62,7 +79,7 @@ class Playwright_DocumentLoaders implements INode {
     async init(nodeData: INodeData): Promise<any> {
         const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
         const metadata = nodeData.inputs?.metadata
-        const webScrap = nodeData.inputs?.webScrap as boolean
+        const relativeLinksMethod = nodeData.inputs?.relativeLinksMethod as string
         let limit = nodeData.inputs?.limit as string
 
         let url = nodeData.inputs?.url as string
@@ -71,25 +88,34 @@ class Playwright_DocumentLoaders implements INode {
             throw new Error('Invalid URL')
         }
 
-        const playwrightLoader = async (url: string): Promise<any> => {
-            let docs = []
-            const loader = new PlaywrightWebBaseLoader(url)
-            if (textSplitter) {
-                docs = await loader.loadAndSplit(textSplitter)
-            } else {
-                docs = await loader.load()
+        async function playwrightLoader(url: string): Promise<any> {
+            try {
+                let docs = []
+                const loader = new PlaywrightWebBaseLoader(url)
+                if (textSplitter) {
+                    docs = await loader.loadAndSplit(textSplitter)
+                } else {
+                    docs = await loader.load()
+                }
+                return docs
+            } catch (err) {
+                if (process.env.DEBUG === 'true') console.error(`error in PlaywrightWebBaseLoader: ${err.message}, on page: ${url}`)
             }
-            return docs
         }
 
-        let availableUrls: string[]
         let docs = []
-        if (webScrap) {
+        if (relativeLinksMethod) {
+            if (process.env.DEBUG === 'true') console.info(`Start ${relativeLinksMethod}`)
             if (!limit) limit = '10'
-            availableUrls = await getAvailableURLs(url, parseInt(limit))
-            for (let i = 0; i < availableUrls.length; i++) {
-                docs.push(...(await playwrightLoader(availableUrls[i])))
+            else if (parseInt(limit) < 0) throw new Error('Limit cannot be less than 0')
+            const pages: string[] =
+                relativeLinksMethod === 'webCrawl' ? await webCrawl(url, parseInt(limit)) : await xmlScrape(url, parseInt(limit))
+            if (process.env.DEBUG === 'true') console.info(`pages: ${JSON.stringify(pages)}, length: ${pages.length}`)
+            if (!pages || pages.length === 0) throw new Error('No relative links found')
+            for (const page of pages) {
+                docs.push(...(await playwrightLoader(page)))
             }
+            if (process.env.DEBUG === 'true') console.info(`Finish ${relativeLinksMethod}`)
         } else {
             docs = await playwrightLoader(url)
         }

packages/components/nodes/documentloaders/Puppeteer/Puppeteer.ts

@@ -2,11 +2,12 @@ import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { TextSplitter } from 'langchain/text_splitter'
 import { PuppeteerWebBaseLoader } from 'langchain/document_loaders/web/puppeteer'
 import { test } from 'linkifyjs'
-import { getAvailableURLs } from '../../../src'
+import { webCrawl, xmlScrape } from '../../../src'
 
 class Puppeteer_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -17,6 +18,7 @@ class Puppeteer_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Puppeteer Web Scraper'
         this.name = 'puppeteerWebScraper'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'puppeteer.svg'
         this.category = 'Document Loaders'
@@ -35,19 +37,34 @@ class Puppeteer_DocumentLoaders implements INode {
                 optional: true
             },
             {
-                label: 'Web Scrape for Relative Links',
-                name: 'webScrape',
-                type: 'boolean',
+                label: 'Get Relative Links Method',
+                name: 'relativeLinksMethod',
+                type: 'options',
+                description: 'Select a method to retrieve relative links',
+                options: [
+                    {
+                        label: 'Web Crawl',
+                        name: 'webCrawl',
+                        description: 'Crawl relative links from HTML URL'
+                    },
+                    {
+                        label: 'Scrape XML Sitemap',
+                        name: 'scrapeXMLSitemap',
+                        description: 'Scrape relative links from XML sitemap URL'
+                    }
+                ],
                 optional: true,
                 additionalParams: true
             },
             {
-                label: 'Web Scrape Links Limit',
+                label: 'Get Relative Links Limit',
                 name: 'limit',
                 type: 'number',
-                default: 10,
                 optional: true,
-                additionalParams: true
+                additionalParams: true,
+                description:
+                    'Only used when "Get Relative Links Method" is selected. Set 0 to retrieve all relative links, default limit is 10.',
+                warning: `Retreiving all links might take long time, and all links will be upserted again if the flow's state changed (eg: different URL, chunk size, etc)`
             },
             {
                 label: 'Metadata',
@@ -62,7 +79,7 @@ class Puppeteer_DocumentLoaders implements INode {
     async init(nodeData: INodeData): Promise<any> {
         const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
         const metadata = nodeData.inputs?.metadata
-        const webScrape = nodeData.inputs?.webScrape as boolean
+        const relativeLinksMethod = nodeData.inputs?.relativeLinksMethod as string
         let limit = nodeData.inputs?.limit as string
 
         let url = nodeData.inputs?.url as string
@@ -71,30 +88,39 @@ class Puppeteer_DocumentLoaders implements INode {
             throw new Error('Invalid URL')
         }
 
-        const puppeteerLoader = async (url: string): Promise<any> => {
-            let docs = []
-            const loader = new PuppeteerWebBaseLoader(url)
-            if (textSplitter) {
-                docs = await loader.loadAndSplit(textSplitter)
-            } else {
-                docs = await loader.load()
+        async function puppeteerLoader(url: string): Promise<any> {
+            try {
+                let docs = []
+                const loader = new PuppeteerWebBaseLoader(url, {
+                    launchOptions: {
+                        args: ['--no-sandbox'],
+                        headless: 'new'
+                    }
+                })
+                if (textSplitter) {
+                    docs = await loader.loadAndSplit(textSplitter)
+                } else {
+                    docs = await loader.load()
+                }
+                return docs
+            } catch (err) {
+                if (process.env.DEBUG === 'true') console.error(`error in PuppeteerWebBaseLoader: ${err.message}, on page: ${url}`)
             }
-            return docs
         }
 
-        let availableUrls: string[]
         let docs = []
-        if (webScrape) {
+        if (relativeLinksMethod) {
+            if (process.env.DEBUG === 'true') console.info(`Start ${relativeLinksMethod}`)
             if (!limit) limit = '10'
-            availableUrls = await getAvailableURLs(url, parseInt(limit))
-            for (let i = 0; i < availableUrls.length; i++) {
-                try {
-                    docs.push(...(await puppeteerLoader(availableUrls[i])))
-                } catch (error) {
-                    console.error('Error loading url with puppeteer. URL: ', availableUrls[i], 'Error: ', error)
-                    continue
-                }
+            else if (parseInt(limit) < 0) throw new Error('Limit cannot be less than 0')
+            const pages: string[] =
+                relativeLinksMethod === 'webCrawl' ? await webCrawl(url, parseInt(limit)) : await xmlScrape(url, parseInt(limit))
+            if (process.env.DEBUG === 'true') console.info(`pages: ${JSON.stringify(pages)}, length: ${pages.length}`)
+            if (!pages || pages.length === 0) throw new Error('No relative links found')
+            for (const page of pages) {
+                docs.push(...(await puppeteerLoader(page)))
             }
+            if (process.env.DEBUG === 'true') console.info(`Finish ${relativeLinksMethod}`)
         } else {
             docs = await puppeteerLoader(url)
         }

packages/components/nodes/documentloaders/Subtitles/Subtitles.ts

@@ -5,6 +5,7 @@ import { SRTLoader } from 'langchain/document_loaders/fs/srt'
 class Subtitles_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -15,6 +16,7 @@ class Subtitles_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Subtitles File'
         this.name = 'subtitlesFile'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'subtitlesFile.svg'
         this.category = 'Document Loaders'

packages/components/nodes/documentloaders/Text/Text.ts

@@ -5,6 +5,7 @@ import { TextLoader } from 'langchain/document_loaders/fs/text'
 class Text_DocumentLoaders implements INode {
     label: string
     name: string
+    version: number
     description: string
     type: string
     icon: string
@@ -15,6 +16,7 @@ class Text_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Text File'
         this.name = 'textFile'
+        this.version = 1.0
         this.type = 'Document'
         this.icon = 'textFile.svg'
         this.category = 'Document Loaders'

packages/components/nodes/embeddings/AzureOpenAIEmbedding/Azure.svg

@@ -1,5 +1 @@
-<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-brand-azure" width="24" height="24" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round">
-   <path stroke="none" d="M0 0h24v24H0z" fill="none"></path>
-   <path d="M6 7.5l-4 9.5h4l6 -15z"></path>
-   <path d="M22 20l-7 -15l-3 7l4 5l-8 3z"></path>
-</svg>
+<svg xmlns="http://www.w3.org/2000/svg"  viewBox="0 0 48 48" width="96px" height="96px"><path fill="#035bda" d="M46 40L29.317 10.852 22.808 23.96 34.267 37.24 13 39.655zM13.092 18.182L2 36.896 11.442 35.947 28.033 5.678z"/></svg>

packages/components/nodes/embeddings/AzureOpenAIEmbedding/AzureOpenAIEmbedding.ts

@@ -1,52 +1,36 @@
 import { AzureOpenAIInput } from 'langchain/chat_models/openai'
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { getBaseClasses } from '../../../src/utils'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
 import { OpenAIEmbeddings, OpenAIEmbeddingsParams } from 'langchain/embeddings/openai'
 
 class AzureOpenAIEmbedding_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 = 'Azure OpenAI Embeddings'
         this.name = 'azureOpenAIEmbeddings'
+        this.version = 1.0
         this.type = 'AzureOpenAIEmbeddings'
         this.icon = 'Azure.svg'
         this.category = 'Embeddings'
         this.description = 'Azure OpenAI API to generate embeddings for a given text'
         this.baseClasses = [this.type, ...getBaseClasses(OpenAIEmbeddings)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['azureOpenAIApi']
+        }
         this.inputs = [
-            {
-                label: 'Azure OpenAI Api Key',
-                name: 'azureOpenAIApiKey',
-                type: 'password'
-            },
-            {
-                label: 'Azure OpenAI Api Instance Name',
-                name: 'azureOpenAIApiInstanceName',
-                type: 'string',
-                placeholder: 'YOUR-INSTANCE-NAME'
-            },
-            {
-                label: 'Azure OpenAI Api Deployment Name',
-                name: 'azureOpenAIApiDeploymentName',
-                type: 'string',
-                placeholder: 'YOUR-DEPLOYMENT-NAME'
-            },
-            {
-                label: 'Azure OpenAI Api Version',
-                name: 'azureOpenAIApiVersion',
-                type: 'string',
-                placeholder: 'YOUR-API-VERSION',
-                description:
-                    'Description of Supported API Versions. Please refer <a target="_blank" href="https://learn.microsoft.com/en-us/azure/cognitive-services/openai/reference#embeddings">examples</a>'
-            },
             {
                 label: 'Batch Size',
                 name: 'batchSize',
@@ -65,14 +49,16 @@ class AzureOpenAIEmbedding_Embeddings implements INode {
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
-        const azureOpenAIApiKey = nodeData.inputs?.azureOpenAIApiKey as string
-        const azureOpenAIApiInstanceName = nodeData.inputs?.azureOpenAIApiInstanceName as string
-        const azureOpenAIApiDeploymentName = nodeData.inputs?.azureOpenAIApiDeploymentName as string
-        const azureOpenAIApiVersion = nodeData.inputs?.azureOpenAIApiVersion as string
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const batchSize = nodeData.inputs?.batchSize as string
         const timeout = nodeData.inputs?.timeout as string
 
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const azureOpenAIApiKey = getCredentialParam('azureOpenAIApiKey', credentialData, nodeData)
+        const azureOpenAIApiInstanceName = getCredentialParam('azureOpenAIApiInstanceName', credentialData, nodeData)
+        const azureOpenAIApiDeploymentName = getCredentialParam('azureOpenAIApiDeploymentName', credentialData, nodeData)
+        const azureOpenAIApiVersion = getCredentialParam('azureOpenAIApiVersion', credentialData, nodeData)
+
         const obj: Partial<OpenAIEmbeddingsParams> & Partial<AzureOpenAIInput> = {
             azureOpenAIApiKey,
             azureOpenAIApiInstanceName,

packages/components/nodes/embeddings/CohereEmbedding/CohereEmbedding.ts

@@ -1,31 +1,35 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { getBaseClasses } from '../../../src/utils'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
 import { CohereEmbeddings, CohereEmbeddingsParams } from 'langchain/embeddings/cohere'
 
 class CohereEmbedding_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 = 'Cohere Embeddings'
         this.name = 'cohereEmbeddings'
+        this.version = 1.0
         this.type = 'CohereEmbeddings'
         this.icon = 'cohere.png'
         this.category = 'Embeddings'
         this.description = 'Cohere API to generate embeddings for a given text'
         this.baseClasses = [this.type, ...getBaseClasses(CohereEmbeddings)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['cohereApi']
+        }
         this.inputs = [
-            {
-                label: 'Cohere API Key',
-                name: 'cohereApiKey',
-                type: 'password'
-            },
             {
                 label: 'Model Name',
                 name: 'modelName',
@@ -50,12 +54,14 @@ class CohereEmbedding_Embeddings implements INode {
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
-        const apiKey = nodeData.inputs?.cohereApiKey as string
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const modelName = nodeData.inputs?.modelName as string
 
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const cohereApiKey = getCredentialParam('cohereApiKey', credentialData, nodeData)
+
         const obj: Partial<CohereEmbeddingsParams> & { apiKey?: string } = {
-            apiKey
+            apiKey: cohereApiKey
         }
 
         if (modelName) obj.modelName = modelName

packages/components/nodes/embeddings/HuggingFaceInferenceEmbedding/HuggingFaceInferenceEmbedding.ts

@@ -1,49 +1,67 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { getBaseClasses } from '../../../src/utils'
-import { HuggingFaceInferenceEmbeddings, HuggingFaceInferenceEmbeddingsParams } from 'langchain/embeddings/hf'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+import { HuggingFaceInferenceEmbeddings, HuggingFaceInferenceEmbeddingsParams } from './core'
 
 class HuggingFaceInferenceEmbedding_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 = 'HuggingFace Inference Embeddings'
         this.name = 'huggingFaceInferenceEmbeddings'
+        this.version = 1.0
         this.type = 'HuggingFaceInferenceEmbeddings'
         this.icon = 'huggingface.png'
         this.category = 'Embeddings'
         this.description = 'HuggingFace Inference API to generate embeddings for a given text'
         this.baseClasses = [this.type, ...getBaseClasses(HuggingFaceInferenceEmbeddings)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['huggingFaceApi']
+        }
         this.inputs = [
-            {
-                label: 'HuggingFace Api Key',
-                name: 'apiKey',
-                type: 'password'
-            },
             {
                 label: 'Model',
                 name: 'modelName',
                 type: 'string',
+                description: 'If using own inference endpoint, leave this blank',
+                placeholder: 'sentence-transformers/distilbert-base-nli-mean-tokens',
+                optional: true
+            },
+            {
+                label: 'Endpoint',
+                name: 'endpoint',
+                type: 'string',
+                placeholder: 'https://xyz.eu-west-1.aws.endpoints.huggingface.cloud/sentence-transformers/all-MiniLM-L6-v2',
+                description: 'Using your own inference endpoint',
                 optional: true
             }
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
-        const apiKey = nodeData.inputs?.apiKey as string
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const modelName = nodeData.inputs?.modelName as string
+        const endpoint = nodeData.inputs?.endpoint as string
+
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const huggingFaceApiKey = getCredentialParam('huggingFaceApiKey', credentialData, nodeData)
 
         const obj: Partial<HuggingFaceInferenceEmbeddingsParams> = {
-            apiKey
+            apiKey: huggingFaceApiKey
         }
 
         if (modelName) obj.model = modelName
+        if (endpoint) obj.endpoint = endpoint
 
         const model = new HuggingFaceInferenceEmbeddings(obj)
         return model

packages/components/nodes/embeddings/HuggingFaceInferenceEmbedding/core.ts

@@ -0,0 +1,55 @@
+import { HfInference } from '@huggingface/inference'
+import { Embeddings, EmbeddingsParams } from 'langchain/embeddings/base'
+import { getEnvironmentVariable } from '../../../src/utils'
+
+export interface HuggingFaceInferenceEmbeddingsParams extends EmbeddingsParams {
+    apiKey?: string
+    model?: string
+    endpoint?: string
+}
+
+export class HuggingFaceInferenceEmbeddings extends Embeddings implements HuggingFaceInferenceEmbeddingsParams {
+    apiKey?: string
+
+    endpoint?: string
+
+    model: string
+
+    client: HfInference
+
+    constructor(fields?: HuggingFaceInferenceEmbeddingsParams) {
+        super(fields ?? {})
+
+        this.model = fields?.model ?? 'sentence-transformers/distilbert-base-nli-mean-tokens'
+        this.apiKey = fields?.apiKey ?? getEnvironmentVariable('HUGGINGFACEHUB_API_KEY')
+        this.endpoint = fields?.endpoint ?? ''
+        this.client = new HfInference(this.apiKey)
+        if (this.endpoint) this.client.endpoint(this.endpoint)
+    }
+
+    async _embed(texts: string[]): Promise<number[][]> {
+        // replace newlines, which can negatively affect performance.
+        const clean = texts.map((text) => text.replace(/\n/g, ' '))
+        const hf = new HfInference(this.apiKey)
+        const obj: any = {
+            inputs: clean
+        }
+        if (this.endpoint) {
+            hf.endpoint(this.endpoint)
+        } else {
+            obj.model = this.model
+        }
+
+        const res = await this.caller.callWithOptions({}, hf.featureExtraction.bind(hf), obj)
+        return res as number[][]
+    }
+
+    async embedQuery(document: string): Promise<number[]> {
+        const res = await this._embed([document])
+        return res[0]
+    }
+
+    async embedDocuments(documents: string[]): Promise<number[][]> {
+        return this._embed(documents)
+    }
+}

packages/components/nodes/embeddings/LocalAIEmbedding/LocalAIEmbedding.ts

@@ -4,6 +4,7 @@ import { OpenAIEmbeddings, OpenAIEmbeddingsParams } from 'langchain/embeddings/o
 class LocalAIEmbedding_Embeddings implements INode {
     label: string
     name: string
+    version: number
     type: string
     icon: string
     category: string
@@ -14,6 +15,7 @@ class LocalAIEmbedding_Embeddings implements INode {
     constructor() {
         this.label = 'LocalAI Embeddings'
         this.name = 'localAIEmbeddings'
+        this.version = 1.0
         this.type = 'LocalAI Embeddings'
         this.icon = 'localai.png'
         this.category = 'Embeddings'

packages/components/nodes/embeddings/OpenAIEmbedding/OpenAIEmbedding.ts

@@ -1,31 +1,35 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { getBaseClasses } from '../../../src/utils'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
 import { OpenAIEmbeddings, OpenAIEmbeddingsParams } from 'langchain/embeddings/openai'
 
 class OpenAIEmbedding_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 = 'OpenAI Embeddings'
         this.name = 'openAIEmbeddings'
+        this.version = 1.0
         this.type = 'OpenAIEmbeddings'
         this.icon = 'openai.png'
         this.category = 'Embeddings'
         this.description = 'OpenAI API to generate embeddings for a given text'
         this.baseClasses = [this.type, ...getBaseClasses(OpenAIEmbeddings)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['openAIApi']
+        }
         this.inputs = [
-            {
-                label: 'OpenAI Api Key',
-                name: 'openAIApiKey',
-                type: 'password'
-            },
             {
                 label: 'Strip New Lines',
                 name: 'stripNewLines',
@@ -57,13 +61,15 @@ class OpenAIEmbedding_Embeddings implements INode {
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
-        const openAIApiKey = nodeData.inputs?.openAIApiKey as string
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const stripNewLines = nodeData.inputs?.stripNewLines as boolean
         const batchSize = nodeData.inputs?.batchSize as string
         const timeout = nodeData.inputs?.timeout as string
         const basePath = nodeData.inputs?.basepath as string
 
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, nodeData)
+
         const obj: Partial<OpenAIEmbeddingsParams> & { openAIApiKey?: string } = {
             openAIApiKey
         }

packages/components/nodes/llms/Azure OpenAI/Azure.svg

@@ -1,5 +1 @@
-<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-brand-azure" width="24" height="24" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round">
-   <path stroke="none" d="M0 0h24v24H0z" fill="none"></path>
-   <path d="M6 7.5l-4 9.5h4l6 -15z"></path>
-   <path d="M22 20l-7 -15l-3 7l4 5l-8 3z"></path>
-</svg>
+<svg xmlns="http://www.w3.org/2000/svg"  viewBox="0 0 48 48" width="96px" height="96px"><path fill="#035bda" d="M46 40L29.317 10.852 22.808 23.96 34.267 37.24 13 39.655zM13.092 18.182L2 36.896 11.442 35.947 28.033 5.678z"/></svg>

packages/components/nodes/llms/Azure OpenAI/AzureOpenAI.ts

@@ -1,31 +1,35 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { getBaseClasses } from '../../../src/utils'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
 import { AzureOpenAIInput, OpenAI, OpenAIInput } from 'langchain/llms/openai'
 
 class AzureOpenAI_LLMs 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 = 'Azure OpenAI'
         this.name = 'azureOpenAI'
+        this.version = 1.0
         this.type = 'AzureOpenAI'
         this.icon = 'Azure.svg'
         this.category = 'LLMs'
         this.description = 'Wrapper around Azure OpenAI large language models'
         this.baseClasses = [this.type, ...getBaseClasses(OpenAI)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['azureOpenAIApi']
+        }
         this.inputs = [
-            {
-                label: 'Azure OpenAI Api Key',
-                name: 'azureOpenAIApiKey',
-                type: 'password'
-            },
             {
                 label: 'Model Name',
                 name: 'modelName',
@@ -87,41 +91,15 @@ class AzureOpenAI_LLMs implements INode {
                 label: 'Temperature',
                 name: 'temperature',
                 type: 'number',
+                step: 0.1,
                 default: 0.9,
                 optional: true
             },
-            {
-                label: 'Azure OpenAI Api Instance Name',
-                name: 'azureOpenAIApiInstanceName',
-                type: 'string',
-                placeholder: 'YOUR-INSTANCE-NAME'
-            },
-            {
-                label: 'Azure OpenAI Api Deployment Name',
-                name: 'azureOpenAIApiDeploymentName',
-                type: 'string',
-                placeholder: 'YOUR-DEPLOYMENT-NAME'
-            },
-            {
-                label: 'Azure OpenAI Api Version',
-                name: 'azureOpenAIApiVersion',
-                type: 'options',
-                options: [
-                    {
-                        label: '2023-03-15-preview',
-                        name: '2023-03-15-preview'
-                    },
-                    {
-                        label: '2022-12-01',
-                        name: '2022-12-01'
-                    }
-                ],
-                default: '2023-03-15-preview'
-            },
             {
                 label: 'Max Tokens',
                 name: 'maxTokens',
                 type: 'number',
+                step: 1,
                 optional: true,
                 additionalParams: true
             },
@@ -129,6 +107,7 @@ class AzureOpenAI_LLMs implements INode {
                 label: 'Top Probability',
                 name: 'topP',
                 type: 'number',
+                step: 0.1,
                 optional: true,
                 additionalParams: true
             },
@@ -136,6 +115,7 @@ class AzureOpenAI_LLMs implements INode {
                 label: 'Best Of',
                 name: 'bestOf',
                 type: 'number',
+                step: 1,
                 optional: true,
                 additionalParams: true
             },
@@ -143,6 +123,7 @@ class AzureOpenAI_LLMs implements INode {
                 label: 'Frequency Penalty',
                 name: 'frequencyPenalty',
                 type: 'number',
+                step: 0.1,
                 optional: true,
                 additionalParams: true
             },
@@ -150,6 +131,7 @@ class AzureOpenAI_LLMs implements INode {
                 label: 'Presence Penalty',
                 name: 'presencePenalty',
                 type: 'number',
+                step: 0.1,
                 optional: true,
                 additionalParams: true
             },
@@ -157,19 +139,16 @@ class AzureOpenAI_LLMs implements INode {
                 label: 'Timeout',
                 name: 'timeout',
                 type: 'number',
+                step: 1,
                 optional: true,
                 additionalParams: true
             }
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
-        const azureOpenAIApiKey = nodeData.inputs?.azureOpenAIApiKey as string
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const temperature = nodeData.inputs?.temperature as string
         const modelName = nodeData.inputs?.modelName as string
-        const azureOpenAIApiInstanceName = nodeData.inputs?.azureOpenAIApiInstanceName as string
-        const azureOpenAIApiDeploymentName = nodeData.inputs?.azureOpenAIApiDeploymentName as string
-        const azureOpenAIApiVersion = nodeData.inputs?.azureOpenAIApiVersion as string
         const maxTokens = nodeData.inputs?.maxTokens as string
         const topP = nodeData.inputs?.topP as string
         const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
@@ -178,8 +157,14 @@ class AzureOpenAI_LLMs implements INode {
         const bestOf = nodeData.inputs?.bestOf as string
         const streaming = nodeData.inputs?.streaming as boolean
 
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const azureOpenAIApiKey = getCredentialParam('azureOpenAIApiKey', credentialData, nodeData)
+        const azureOpenAIApiInstanceName = getCredentialParam('azureOpenAIApiInstanceName', credentialData, nodeData)
+        const azureOpenAIApiDeploymentName = getCredentialParam('azureOpenAIApiDeploymentName', credentialData, nodeData)
+        const azureOpenAIApiVersion = getCredentialParam('azureOpenAIApiVersion', credentialData, nodeData)
+
         const obj: Partial<AzureOpenAIInput> & Partial<OpenAIInput> = {
-            temperature: parseInt(temperature, 10),
+            temperature: parseFloat(temperature),
             modelName,
             azureOpenAIApiKey,
             azureOpenAIApiInstanceName,
@@ -189,9 +174,9 @@ class AzureOpenAI_LLMs implements INode {
         }
 
         if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
-        if (topP) obj.topP = parseInt(topP, 10)
-        if (frequencyPenalty) obj.frequencyPenalty = parseInt(frequencyPenalty, 10)
-        if (presencePenalty) obj.presencePenalty = parseInt(presencePenalty, 10)
+        if (topP) obj.topP = parseFloat(topP)
+        if (frequencyPenalty) obj.frequencyPenalty = parseFloat(frequencyPenalty)
+        if (presencePenalty) obj.presencePenalty = parseFloat(presencePenalty)
         if (timeout) obj.timeout = parseInt(timeout, 10)
         if (bestOf) obj.bestOf = parseInt(bestOf, 10)
 

packages/components/nodes/llms/Cohere/Cohere.ts

@@ -1,31 +1,35 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { getBaseClasses } from '../../../src/utils'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
 import { Cohere, CohereInput } from './core'
 
 class Cohere_LLMs 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 = 'Cohere'
         this.name = 'cohere'
+        this.version = 1.0
         this.type = 'Cohere'
         this.icon = 'cohere.png'
         this.category = 'LLMs'
         this.description = 'Wrapper around Cohere large language models'
         this.baseClasses = [this.type, ...getBaseClasses(Cohere)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['cohereApi']
+        }
         this.inputs = [
-            {
-                label: 'Cohere Api Key',
-                name: 'cohereApiKey',
-                type: 'password'
-            },
             {
                 label: 'Model Name',
                 name: 'modelName',
@@ -63,6 +67,7 @@ class Cohere_LLMs implements INode {
                 label: 'Temperature',
                 name: 'temperature',
                 type: 'number',
+                step: 0.1,
                 default: 0.7,
                 optional: true
             },
@@ -70,24 +75,27 @@ class Cohere_LLMs implements INode {
                 label: 'Max Tokens',
                 name: 'maxTokens',
                 type: 'number',
+                step: 1,
                 optional: true
             }
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const temperature = nodeData.inputs?.temperature as string
         const modelName = nodeData.inputs?.modelName as string
-        const apiKey = nodeData.inputs?.cohereApiKey as string
         const maxTokens = nodeData.inputs?.maxTokens as string
 
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const cohereApiKey = getCredentialParam('cohereApiKey', credentialData, nodeData)
+
         const obj: CohereInput = {
-            apiKey
+            apiKey: cohereApiKey
         }
 
         if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
         if (modelName) obj.model = modelName
-        if (temperature) obj.temperature = parseInt(temperature, 10)
+        if (temperature) obj.temperature = parseFloat(temperature)
 
         const model = new Cohere(obj)
         return model

packages/components/nodes/llms/HuggingFaceInference/HuggingFaceInference.ts

@@ -1,41 +1,56 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { getBaseClasses } from '../../../src/utils'
-import { HFInput, HuggingFaceInference } from 'langchain/llms/hf'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+import { HFInput, HuggingFaceInference } from './core'
 
 class HuggingFaceInference_LLMs 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 = 'HuggingFace Inference'
         this.name = 'huggingFaceInference_LLMs'
+        this.version = 1.0
         this.type = 'HuggingFaceInference'
         this.icon = 'huggingface.png'
         this.category = 'LLMs'
         this.description = 'Wrapper around HuggingFace large language models'
         this.baseClasses = [this.type, ...getBaseClasses(HuggingFaceInference)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['huggingFaceApi']
+        }
         this.inputs = [
             {
                 label: 'Model',
                 name: 'model',
                 type: 'string',
-                placeholder: 'gpt2'
+                description: 'If using own inference endpoint, leave this blank',
+                placeholder: 'gpt2',
+                optional: true
             },
             {
-                label: 'HuggingFace Api Key',
-                name: 'apiKey',
-                type: 'password'
+                label: 'Endpoint',
+                name: 'endpoint',
+                type: 'string',
+                placeholder: 'https://xyz.eu-west-1.aws.endpoints.huggingface.cloud/gpt2',
+                description: 'Using your own inference endpoint',
+                optional: true
             },
             {
                 label: 'Temperature',
                 name: 'temperature',
                 type: 'number',
+                step: 0.1,
                 description: 'Temperature parameter may not apply to certain model. Please check available model parameters',
                 optional: true,
                 additionalParams: true
@@ -44,6 +59,7 @@ class HuggingFaceInference_LLMs implements INode {
                 label: 'Max Tokens',
                 name: 'maxTokens',
                 type: 'number',
+                step: 1,
                 description: 'Max Tokens parameter may not apply to certain model. Please check available model parameters',
                 optional: true,
                 additionalParams: true
@@ -52,6 +68,7 @@ class HuggingFaceInference_LLMs implements INode {
                 label: 'Top Probability',
                 name: 'topP',
                 type: 'number',
+                step: 0.1,
                 description: 'Top Probability parameter may not apply to certain model. Please check available model parameters',
                 optional: true,
                 additionalParams: true
@@ -60,6 +77,7 @@ class HuggingFaceInference_LLMs implements INode {
                 label: 'Top K',
                 name: 'hfTopK',
                 type: 'number',
+                step: 0.1,
                 description: 'Top K parameter may not apply to certain model. Please check available model parameters',
                 optional: true,
                 additionalParams: true
@@ -68,6 +86,7 @@ class HuggingFaceInference_LLMs implements INode {
                 label: 'Frequency Penalty',
                 name: 'frequencyPenalty',
                 type: 'number',
+                step: 0.1,
                 description: 'Frequency Penalty parameter may not apply to certain model. Please check available model parameters',
                 optional: true,
                 additionalParams: true
@@ -75,25 +94,29 @@ class HuggingFaceInference_LLMs implements INode {
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const model = nodeData.inputs?.model as string
-        const apiKey = nodeData.inputs?.apiKey as string
         const temperature = nodeData.inputs?.temperature as string
         const maxTokens = nodeData.inputs?.maxTokens as string
         const topP = nodeData.inputs?.topP as string
         const hfTopK = nodeData.inputs?.hfTopK as string
         const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
+        const endpoint = nodeData.inputs?.endpoint as string
+
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const huggingFaceApiKey = getCredentialParam('huggingFaceApiKey', credentialData, nodeData)
 
         const obj: Partial<HFInput> = {
             model,
-            apiKey
+            apiKey: huggingFaceApiKey
         }
 
-        if (temperature) obj.temperature = parseInt(temperature, 10)
+        if (temperature) obj.temperature = parseFloat(temperature)
         if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
-        if (topP) obj.topP = parseInt(topP, 10)
-        if (hfTopK) obj.topK = parseInt(hfTopK, 10)
-        if (frequencyPenalty) obj.frequencyPenalty = parseInt(frequencyPenalty, 10)
+        if (topP) obj.topP = parseFloat(topP)
+        if (hfTopK) obj.topK = parseFloat(hfTopK)
+        if (frequencyPenalty) obj.frequencyPenalty = parseFloat(frequencyPenalty)
+        if (endpoint) obj.endpoint = endpoint
 
         const huggingFace = new HuggingFaceInference(obj)
         return huggingFace

packages/components/nodes/llms/HuggingFaceInference/core.ts

@@ -0,0 +1,113 @@
+import { getEnvironmentVariable } from '../../../src/utils'
+import { LLM, BaseLLMParams } from 'langchain/llms/base'
+
+export interface HFInput {
+    /** Model to use */
+    model: string
+
+    /** Sampling temperature to use */
+    temperature?: number
+
+    /**
+     * Maximum number of tokens to generate in the completion.
+     */
+    maxTokens?: number
+
+    /** Total probability mass of tokens to consider at each step */
+    topP?: number
+
+    /** Integer to define the top tokens considered within the sample operation to create new text. */
+    topK?: number
+
+    /** Penalizes repeated tokens according to frequency */
+    frequencyPenalty?: number
+
+    /** API key to use. */
+    apiKey?: string
+
+    /** Private endpoint to use. */
+    endpoint?: string
+}
+
+export class HuggingFaceInference extends LLM implements HFInput {
+    get lc_secrets(): { [key: string]: string } | undefined {
+        return {
+            apiKey: 'HUGGINGFACEHUB_API_KEY'
+        }
+    }
+
+    model = 'gpt2'
+
+    temperature: number | undefined = undefined
+
+    maxTokens: number | undefined = undefined
+
+    topP: number | undefined = undefined
+
+    topK: number | undefined = undefined
+
+    frequencyPenalty: number | undefined = undefined
+
+    apiKey: string | undefined = undefined
+
+    endpoint: string | undefined = undefined
+
+    constructor(fields?: Partial<HFInput> & BaseLLMParams) {
+        super(fields ?? {})
+
+        this.model = fields?.model ?? this.model
+        this.temperature = fields?.temperature ?? this.temperature
+        this.maxTokens = fields?.maxTokens ?? this.maxTokens
+        this.topP = fields?.topP ?? this.topP
+        this.topK = fields?.topK ?? this.topK
+        this.frequencyPenalty = fields?.frequencyPenalty ?? this.frequencyPenalty
+        this.endpoint = fields?.endpoint ?? ''
+        this.apiKey = fields?.apiKey ?? getEnvironmentVariable('HUGGINGFACEHUB_API_KEY')
+        if (!this.apiKey) {
+            throw new Error(
+                'Please set an API key for HuggingFace Hub in the environment variable HUGGINGFACEHUB_API_KEY or in the apiKey field of the HuggingFaceInference constructor.'
+            )
+        }
+    }
+
+    _llmType() {
+        return 'hf'
+    }
+
+    /** @ignore */
+    async _call(prompt: string, options: this['ParsedCallOptions']): Promise<string> {
+        const { HfInference } = await HuggingFaceInference.imports()
+        const hf = new HfInference(this.apiKey)
+        const obj: any = {
+            parameters: {
+                // make it behave similar to openai, returning only the generated text
+                return_full_text: false,
+                temperature: this.temperature,
+                max_new_tokens: this.maxTokens,
+                top_p: this.topP,
+                top_k: this.topK,
+                repetition_penalty: this.frequencyPenalty
+            },
+            inputs: prompt
+        }
+        if (this.endpoint) {
+            hf.endpoint(this.endpoint)
+        } else {
+            obj.model = this.model
+        }
+        const res = await this.caller.callWithOptions({ signal: options.signal }, hf.textGeneration.bind(hf), obj)
+        return res.generated_text
+    }
+
+    /** @ignore */
+    static async imports(): Promise<{
+        HfInference: typeof import('@huggingface/inference').HfInference
+    }> {
+        try {
+            const { HfInference } = await import('@huggingface/inference')
+            return { HfInference }
+        } catch (e) {
+            throw new Error('Please install huggingface as a dependency with, e.g. `yarn add @huggingface/inference`')
+        }
+    }
+}

packages/components/nodes/llms/OpenAI/OpenAI.ts

@@ -1,31 +1,35 @@
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { getBaseClasses } from '../../../src/utils'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
 import { OpenAI, OpenAIInput } from 'langchain/llms/openai'
 
 class OpenAI_LLMs 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 = 'OpenAI'
         this.name = 'openAI'
+        this.version = 1.0
         this.type = 'OpenAI'
         this.icon = 'openai.png'
         this.category = 'LLMs'
         this.description = 'Wrapper around OpenAI large language models'
         this.baseClasses = [this.type, ...getBaseClasses(OpenAI)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['openAIApi']
+        }
         this.inputs = [
-            {
-                label: 'OpenAI Api Key',
-                name: 'openAIApiKey',
-                type: 'password'
-            },
             {
                 label: 'Model Name',
                 name: 'modelName',
@@ -55,6 +59,7 @@ class OpenAI_LLMs implements INode {
                 label: 'Temperature',
                 name: 'temperature',
                 type: 'number',
+                step: 0.1,
                 default: 0.7,
                 optional: true
             },
@@ -62,6 +67,7 @@ class OpenAI_LLMs implements INode {
                 label: 'Max Tokens',
                 name: 'maxTokens',
                 type: 'number',
+                step: 1,
                 optional: true,
                 additionalParams: true
             },
@@ -69,6 +75,7 @@ class OpenAI_LLMs implements INode {
                 label: 'Top Probability',
                 name: 'topP',
                 type: 'number',
+                step: 0.1,
                 optional: true,
                 additionalParams: true
             },
@@ -76,6 +83,7 @@ class OpenAI_LLMs implements INode {
                 label: 'Best Of',
                 name: 'bestOf',
                 type: 'number',
+                step: 1,
                 optional: true,
                 additionalParams: true
             },
@@ -83,6 +91,7 @@ class OpenAI_LLMs implements INode {
                 label: 'Frequency Penalty',
                 name: 'frequencyPenalty',
                 type: 'number',
+                step: 0.1,
                 optional: true,
                 additionalParams: true
             },
@@ -90,6 +99,7 @@ class OpenAI_LLMs implements INode {
                 label: 'Presence Penalty',
                 name: 'presencePenalty',
                 type: 'number',
+                step: 0.1,
                 optional: true,
                 additionalParams: true
             },
@@ -97,6 +107,7 @@ class OpenAI_LLMs implements INode {
                 label: 'Batch Size',
                 name: 'batchSize',
                 type: 'number',
+                step: 1,
                 optional: true,
                 additionalParams: true
             },
@@ -104,6 +115,7 @@ class OpenAI_LLMs implements INode {
                 label: 'Timeout',
                 name: 'timeout',
                 type: 'number',
+                step: 1,
                 optional: true,
                 additionalParams: true
             },
@@ -117,10 +129,9 @@ class OpenAI_LLMs implements INode {
         ]
     }
 
-    async init(nodeData: INodeData): Promise<any> {
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const temperature = nodeData.inputs?.temperature as string
         const modelName = nodeData.inputs?.modelName as string
-        const openAIApiKey = nodeData.inputs?.openAIApiKey as string
         const maxTokens = nodeData.inputs?.maxTokens as string
         const topP = nodeData.inputs?.topP as string
         const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
@@ -131,17 +142,20 @@ class OpenAI_LLMs implements INode {
         const streaming = nodeData.inputs?.streaming as boolean
         const basePath = nodeData.inputs?.basepath as string
 
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, nodeData)
+
         const obj: Partial<OpenAIInput> & { openAIApiKey?: string } = {
-            temperature: parseInt(temperature, 10),
+            temperature: parseFloat(temperature),
             modelName,
             openAIApiKey,
             streaming: streaming ?? true
         }
 
         if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
-        if (topP) obj.topP = parseInt(topP, 10)
-        if (frequencyPenalty) obj.frequencyPenalty = parseInt(frequencyPenalty, 10)
-        if (presencePenalty) obj.presencePenalty = parseInt(presencePenalty, 10)
+        if (topP) obj.topP = parseFloat(topP)
+        if (frequencyPenalty) obj.frequencyPenalty = parseFloat(frequencyPenalty)
+        if (presencePenalty) obj.presencePenalty = parseFloat(presencePenalty)
         if (timeout) obj.timeout = parseInt(timeout, 10)
         if (batchSize) obj.batchSize = parseInt(batchSize, 10)
         if (bestOf) obj.bestOf = parseInt(bestOf, 10)