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Code Issues Pull Requests Packages Projects Releases Wiki Activity

- update LangchainJS version 

- add types & interfaces

- small ui bug fix

- update marketplace files
This commit is contained in:
Henry 2023-04-13 18:32:00 +01:00
parent 02d8284f58
commit 9281b57ef1
47 changed files with 1178 additions and 1141 deletions
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2
.github/workflows/main.yml vendored
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@ -17,7 +17,7 @@ jobs:
strategy:
matrix:
platform: [ubuntu-latest]
node-version: [14.x, 16.x]
node-version: [18.15.0]
runs-on: ${{ matrix.platform }}
steps:

20
packages/components/nodes/agents/ConversationalAgent/ConversationalAgent.ts
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@ -1,4 +1,9 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { initializeAgentExecutor, AgentExecutor } from 'langchain/agents'
import { Tool } from 'langchain/tools'
import { BaseChatModel } from 'langchain/chat_models/base'
import { BaseChatMemory } from 'langchain/memory'
import { getBaseClasses } from '../../../src/utils'
class ConversationalAgent_Agents implements INode {
label: string
@ -17,6 +22,7 @@ class ConversationalAgent_Agents implements INode {
this.category = 'Agents'
this.icon = 'agent.svg'
this.description = 'Conversational agent for a chat model. It will utilize chat specific prompts'
this.baseClasses = [this.type, ...getBaseClasses(AgentExecutor)]
this.inputs = [
{
label: 'Allowed Tools',
@ -37,16 +43,10 @@ class ConversationalAgent_Agents implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
return ['AgentExecutor']
}
async init(nodeData: INodeData): Promise<any> {
const { initializeAgentExecutor } = await import('langchain/agents')
const model = nodeData.inputs?.model
const tools = nodeData.inputs?.tools
const memory = nodeData.inputs?.memory
const model = nodeData.inputs?.model as BaseChatModel
const tools = nodeData.inputs?.tools as Tool[]
const memory = nodeData.inputs?.memory as BaseChatMemory
const executor = await initializeAgentExecutor(tools, model, 'chat-conversational-react-description', true)
executor.memory = memory
@ -54,7 +54,7 @@ class ConversationalAgent_Agents implements INode {
}
async run(nodeData: INodeData, input: string): Promise<string> {
const executor = nodeData.instance
const executor = nodeData.instance as AgentExecutor
const result = await executor.call({ input })
return result?.output

26
packages/components/nodes/agents/MRLKAgentChat/MRLKAgentChat.ts → packages/components/nodes/agents/MRKLAgentChat/MRKLAgentChat.ts
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@ -1,6 +1,10 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { initializeAgentExecutor, AgentExecutor } from 'langchain/agents'
import { Tool } from 'langchain/tools'
import { BaseChatModel } from 'langchain/chat_models/base'
import { getBaseClasses } from '../../../src/utils'
class MRLKAgentChat_Agents implements INode {
class MRKLAgentChat_Agents implements INode {
label: string
name: string
description: string
@ -11,12 +15,13 @@ class MRLKAgentChat_Agents implements INode {
inputs: INodeParams[]
constructor() {
this.label = 'MRLK Agent for Chat Models'
this.name = 'mrlkAgentChat'
this.label = 'MRKL Agent for Chat Models'
this.name = 'mrklAgentChat'
this.type = 'AgentExecutor'
this.category = 'Agents'
this.icon = 'agent.svg'
this.description = 'Agent that uses the ReAct Framework to decide what action to take, optimized to be used with Chat Models'
this.baseClasses = [this.type, ...getBaseClasses(AgentExecutor)]
this.inputs = [
{
label: 'Allowed Tools',
@ -32,27 +37,20 @@ class MRLKAgentChat_Agents implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
return ['AgentExecutor']
}
async init(nodeData: INodeData): Promise<any> {
const { initializeAgentExecutor } = await import('langchain/agents')
const model = nodeData.inputs?.model
const tools = nodeData.inputs?.tools
const model = nodeData.inputs?.model as BaseChatModel
const tools = nodeData.inputs?.tools as Tool[]
const executor = await initializeAgentExecutor(tools, model, 'chat-zero-shot-react-description', true)
return executor
}
async run(nodeData: INodeData, input: string): Promise<string> {
const executor = nodeData.instance
const executor = nodeData.instance as AgentExecutor
const result = await executor.call({ input })
return result?.output
}
}
module.exports = { nodeClass: MRLKAgentChat_Agents }
module.exports = { nodeClass: MRKLAgentChat_Agents }

0
packages/components/nodes/agents/MRLKAgentChat/agent.svg → packages/components/nodes/agents/MRKLAgentChat/agent.svg
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28
packages/components/nodes/agents/MRLKAgentLLM/MRLKAgentLLM.ts → packages/components/nodes/agents/MRKLAgentLLM/MRKLAgentLLM.ts
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@ -1,6 +1,10 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { initializeAgentExecutor, AgentExecutor } from 'langchain/agents'
import { Tool } from 'langchain/tools'
import { BaseLLM } from 'langchain/llms/base'
import { getBaseClasses } from '../../../src/utils'
class MRLKAgentLLM_Agents implements INode {
class MRKLAgentLLM_Agents implements INode {
label: string
name: string
description: string
@ -11,12 +15,13 @@ class MRLKAgentLLM_Agents implements INode {
inputs: INodeParams[]
constructor() {
this.label = 'MRLK Agent for LLMs'
this.name = 'mrlkAgentLLM'
this.label = 'MRKL Agent for LLMs'
this.name = 'mrklAgentLLM'
this.type = 'AgentExecutor'
this.category = 'Agents'
this.icon = 'agent.svg'
this.description = 'Agent that uses the ReAct Framework to decide what action to take, optimized to be used with LLMs'
this.baseClasses = [this.type, ...getBaseClasses(AgentExecutor)]
this.inputs = [
{
label: 'Allowed Tools',
@ -27,32 +32,25 @@ class MRLKAgentLLM_Agents implements INode {
{
label: 'LLM Model',
name: 'model',
type: 'BaseLanguageModel'
type: 'BaseLLM'
}
]
}
async getBaseClasses(): Promise<string[]> {
return ['AgentExecutor']
}
async init(nodeData: INodeData): Promise<any> {
const { initializeAgentExecutor } = await import('langchain/agents')
const model = nodeData.inputs?.model
const tools = nodeData.inputs?.tools
const model = nodeData.inputs?.model as BaseLLM
const tools = nodeData.inputs?.tools as Tool[]
const executor = await initializeAgentExecutor(tools, model, 'zero-shot-react-description', true)
return executor
}
async run(nodeData: INodeData, input: string): Promise<string> {
const executor = nodeData.instance
const executor = nodeData.instance as AgentExecutor
const result = await executor.call({ input })
return result?.output
}
}
module.exports = { nodeClass: MRLKAgentLLM_Agents }
module.exports = { nodeClass: MRKLAgentLLM_Agents }

0
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19
packages/components/nodes/chains/ConversationalRetrievalQAChain/ConversationalRetrievalQAChain.ts
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@ -1,5 +1,8 @@
import { ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { ConversationalRetrievalQAChain } from 'langchain/chains'
import { BaseLLM } from 'langchain/llms/base'
import { BaseRetriever } from 'langchain/schema'
class ConversationalRetrievalQAChain_Chains implements INode {
label: string
@ -18,11 +21,12 @@ class ConversationalRetrievalQAChain_Chains implements INode {
this.icon = 'chain.svg'
this.category = 'Chains'
this.description = 'Document QA - built on RetrievalQAChain to provide a chat history component'
this.baseClasses = [this.type, ...getBaseClasses(ConversationalRetrievalQAChain)]
this.inputs = [
{
label: 'LLM',
name: 'llm',
type: 'BaseLanguageModel'
type: 'BaseLLM'
},
{
label: 'Vector Store Retriever',
@ -32,23 +36,16 @@ class ConversationalRetrievalQAChain_Chains implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
const { ConversationalRetrievalQAChain } = await import('langchain/chains')
return getBaseClasses(ConversationalRetrievalQAChain)
}
async init(nodeData: INodeData): Promise<any> {
const { ConversationalRetrievalQAChain } = await import('langchain/chains')
const llm = nodeData.inputs?.llm
const vectorStoreRetriever = nodeData.inputs?.vectorStoreRetriever
const llm = nodeData.inputs?.llm as BaseLLM
const vectorStoreRetriever = nodeData.inputs?.vectorStoreRetriever as BaseRetriever
const chain = ConversationalRetrievalQAChain.fromLLM(llm, vectorStoreRetriever)
return chain
}
async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
const chain = nodeData.instance
const chain = nodeData.instance as ConversationalRetrievalQAChain
let chatHistory = ''
if (options && options.chatHistory) {

35
packages/components/nodes/chains/LLMChain/LLMChain.ts
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@ -1,5 +1,8 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { LLMChain } from 'langchain/chains'
import { BaseLanguageModel } from 'langchain/base_language'
import { BasePromptTemplate } from 'langchain/prompts'
class LLMChain_Chains implements INode {
label: string
@ -18,10 +21,11 @@ class LLMChain_Chains implements INode {
this.icon = 'chain.svg'
this.category = 'Chains'
this.description = 'Chain to run queries against LLMs'
this.baseClasses = [this.type, ...getBaseClasses(LLMChain)]
this.inputs = [
{
label: 'LLM',
name: 'llm',
label: 'Language Model',
name: 'model',
type: 'BaseLanguageModel'
},
{
@ -43,24 +47,17 @@ class LLMChain_Chains implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
const { LLMChain } = await import('langchain/chains')
return getBaseClasses(LLMChain)
}
async init(nodeData: INodeData): Promise<any> {
const { LLMChain } = await import('langchain/chains')
const model = nodeData.inputs?.model as BaseLanguageModel
const prompt = nodeData.inputs?.prompt as BasePromptTemplate
const llm = nodeData.inputs?.llm
const prompt = nodeData.inputs?.prompt
const chain = new LLMChain({ llm, prompt })
const chain = new LLMChain({ llm: model, prompt })
return chain
}
async run(nodeData: INodeData, input: string): Promise<string> {
const inputVariables = nodeData.instance.prompt.inputVariables // ["product"]
const chain = nodeData.instance
const inputVariables = nodeData.instance.prompt.inputVariables as string[] // ["product"]
const chain = nodeData.instance as LLMChain
if (inputVariables.length === 1) {
const res = await chain.run(input)
@ -71,7 +68,7 @@ class LLMChain_Chains implements INode {
const promptValues = JSON.parse(promptValuesStr.replace(/\s/g, ''))
let seen = []
let seen: string[] = []
for (const variable of inputVariables) {
seen.push(variable)
@ -81,13 +78,17 @@ class LLMChain_Chains implements INode {
}
if (seen.length === 1) {
const lastValue = seen.pop()
if (!lastValue) throw new Error('Please provide Prompt Values')
const options = {
...promptValues,
[seen.pop()]: input
[lastValue]: input
}
const res = await chain.call(options)
return res?.text
} else throw new Error('Please provide Prompt Values')
} else {
throw new Error('Please provide Prompt Values')
}
} else {
const res = await chain.run(input)
return res

18
packages/components/nodes/chains/RetrievalQAChain/RetrievalQAChain.ts
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@ -1,4 +1,8 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { RetrievalQAChain } from 'langchain/chains'
import { BaseLLM } from 'langchain/llms/base'
import { BaseRetriever } from 'langchain/schema'
import { getBaseClasses } from '../../../src/utils'
class RetrievalQAChain_Chains implements INode {
label: string
@ -17,11 +21,12 @@ class RetrievalQAChain_Chains implements INode {
this.icon = 'chain.svg'
this.category = 'Chains'
this.description = 'QA chain to answer a question based on the retrieved documents'
this.baseClasses = [this.type, ...getBaseClasses(RetrievalQAChain)]
this.inputs = [
{
label: 'LLM',
name: 'llm',
type: 'BaseLanguageModel'
type: 'BaseLLM'
},
{
label: 'Vector Store Retriever',
@ -31,21 +36,16 @@ class RetrievalQAChain_Chains implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
return ['BaseChain']
}
async init(nodeData: INodeData): Promise<any> {
const { RetrievalQAChain } = await import('langchain/chains')
const llm = nodeData.inputs?.llm
const vectorStoreRetriever = nodeData.inputs?.vectorStoreRetriever
const llm = nodeData.inputs?.llm as BaseLLM
const vectorStoreRetriever = nodeData.inputs?.vectorStoreRetriever as BaseRetriever
const chain = RetrievalQAChain.fromLLM(llm, vectorStoreRetriever)
return chain
}
async run(nodeData: INodeData, input: string): Promise<string> {
const chain = nodeData.instance
const chain = nodeData.instance as RetrievalQAChain
const obj = {
query: input
}

21
packages/components/nodes/chatmodels/ChatOpenAI/ChatOpenAI.ts
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@ -1,5 +1,6 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { ChatOpenAI } from 'langchain/chat_models/openai'
class ChatOpenAI_ChatModels implements INode {
label: string
@ -18,6 +19,7 @@ class ChatOpenAI_ChatModels implements INode {
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.inputs = [
{
label: 'OpenAI Api Key',
@ -29,6 +31,18 @@ class ChatOpenAI_ChatModels implements INode {
name: 'modelName',
type: 'options',
options: [
{
label: 'gpt-4',
name: 'gpt-4'
},
{
label: 'gpt-4-0314',
name: 'gpt-4-0314'
},
{
label: 'gpt-4-32k-0314',
name: 'gpt-4-32k-0314'
},
{
label: 'gpt-3.5-turbo',
name: 'gpt-3.5-turbo'
@ -51,14 +65,7 @@ class ChatOpenAI_ChatModels implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
const { ChatOpenAI } = await import('langchain/chat_models')
return getBaseClasses(ChatOpenAI)
}
async init(nodeData: INodeData): Promise<any> {
const { ChatOpenAI } = await import('langchain/chat_models')
const temperature = nodeData.inputs?.temperature as string
const modelName = nodeData.inputs?.modelName as string
const openAIApiKey = nodeData.inputs?.openAIApiKey as string

17
packages/components/nodes/documentloaders/Github/Github.ts
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@ -1,4 +1,6 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { TextSplitter } from 'langchain/text_splitter'
import { GithubRepoLoader, GithubRepoLoaderParams } from 'langchain/document_loaders/web/github'
class Github_DocumentLoaders implements INode {
label: string
@ -13,10 +15,11 @@ class Github_DocumentLoaders implements INode {
constructor() {
this.label = 'Github'
this.name = 'github'
this.type = 'Github'
this.type = 'Document'
this.icon = 'github.png'
this.category = 'Document Loaders'
this.description = `Load data from a GitHub repository`
this.baseClasses = [this.type]
this.inputs = [
{
label: 'Repo Link',
@ -46,23 +49,17 @@ class Github_DocumentLoaders implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
return ['Document']
}
async init(nodeData: INodeData): Promise<any> {
const { GithubRepoLoader } = await import('langchain/document_loaders')
const repoLink = nodeData.inputs?.repoLink as string
const branch = nodeData.inputs?.branch as string
const accessToken = nodeData.inputs?.accessToken as string
const textSplitter = nodeData.inputs?.textSplitter
const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
const options = {
const options: GithubRepoLoaderParams = {
branch,
recursive: false,
unknown: 'warn'
} as any
}
if (accessToken) options.accessToken = accessToken

13
packages/components/nodes/documentloaders/Pdf/Pdf.ts
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@ -1,4 +1,6 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { TextSplitter } from 'langchain/text_splitter'
import { PDFLoader } from 'langchain/document_loaders/fs/pdf'
class Pdf_DocumentLoaders implements INode {
label: string
@ -13,10 +15,11 @@ class Pdf_DocumentLoaders implements INode {
constructor() {
this.label = 'Pdf File'
this.name = 'pdfFile'
this.type = 'PDF'
this.type = 'Document'
this.icon = 'pdf.svg'
this.category = 'Document Loaders'
this.description = `Load data from PDF files`
this.baseClasses = [this.type]
this.inputs = [
{
label: 'Pdf File',
@ -49,14 +52,8 @@ class Pdf_DocumentLoaders implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
return ['Document']
}
async init(nodeData: INodeData): Promise<any> {
const { PDFLoader } = await import('langchain/document_loaders')
const textSplitter = nodeData.inputs?.textSplitter
const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
const pdfFileBase64 = nodeData.inputs?.pdfFile as string
const usage = nodeData.inputs?.usage as string

12
packages/components/nodes/documentloaders/Text/Text.ts
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@ -1,4 +1,6 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { TextSplitter } from 'langchain/text_splitter'
import { TextLoader } from 'langchain/document_loaders/fs/text'
class Text_DocumentLoaders implements INode {
label: string
@ -13,10 +15,11 @@ class Text_DocumentLoaders implements INode {
constructor() {
this.label = 'Text File'
this.name = 'textFile'
this.type = 'Text'
this.type = 'Document'
this.icon = 'textFile.svg'
this.category = 'Document Loaders'
this.description = `Load data from text files`
this.baseClasses = [this.type]
this.inputs = [
{
label: 'Txt File',
@ -33,13 +36,8 @@ class Text_DocumentLoaders implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
return ['Document']
}
async init(nodeData: INodeData): Promise<any> {
const { TextLoader } = await import('langchain/document_loaders')
const textSplitter = nodeData.inputs?.textSplitter
const textSplitter = nodeData.inputs?.textSplitter as TextSplitter
const txtFileBase64 = nodeData.inputs?.txtFile as string
const splitDataURI = txtFileBase64.split(',')
splitDataURI.pop()

8
packages/components/nodes/embeddings/OpenAIEmbedding/OpenAIEmbedding.ts
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@ -1,5 +1,6 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { OpenAIEmbeddings } from 'langchain/embeddings/openai'
class OpenAIEmbedding_Embeddings implements INode {
label: string
@ -18,6 +19,7 @@ class OpenAIEmbedding_Embeddings implements INode {
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.inputs = [
{
label: 'OpenAI Api Key',
@ -27,13 +29,7 @@ class OpenAIEmbedding_Embeddings implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
const { OpenAIEmbeddings } = await import('langchain/embeddings')
return getBaseClasses(OpenAIEmbeddings)
}
async init(nodeData: INodeData): Promise<any> {
const { OpenAIEmbeddings } = await import('langchain/embeddings')
const openAIApiKey = nodeData.inputs?.openAIApiKey as string
const model = new OpenAIEmbeddings({ openAIApiKey })

11
packages/components/nodes/llms/HuggingFaceInference/HuggingFaceInference.ts
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@ -1,5 +1,6 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { HuggingFaceInference } from 'langchain/llms/hf'
class HuggingFaceInference_LLMs implements INode {
label: string
@ -17,7 +18,8 @@ class HuggingFaceInference_LLMs implements INode {
this.type = 'HuggingFaceInference'
this.icon = 'huggingface.png'
this.category = 'LLMs'
this.description = 'Wrapper around OpenAI large language models'
this.description = 'Wrapper around HuggingFace large language models'
this.baseClasses = [this.type, ...getBaseClasses(HuggingFaceInference)]
this.inputs = [
{
label: 'Model',
@ -42,14 +44,7 @@ class HuggingFaceInference_LLMs implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
const { HuggingFaceInference } = await import('langchain/llms')
return getBaseClasses(HuggingFaceInference)
}
async init(nodeData: INodeData): Promise<any> {
const { HuggingFaceInference } = await import('langchain/llms')
const temperature = nodeData.inputs?.temperature as string
const model = nodeData.inputs?.model as string

9
packages/components/nodes/llms/OpenAI/OpenAI.ts
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@ -1,5 +1,6 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { OpenAI } from 'langchain/llms/openai'
class OpenAI_LLMs implements INode {
label: string
@ -18,6 +19,7 @@ class OpenAI_LLMs implements INode {
this.icon = 'openai.png'
this.category = 'LLMs'
this.description = 'Wrapper around OpenAI large language models'
this.baseClasses = [this.type, ...getBaseClasses(OpenAI)]
this.inputs = [
{
label: 'OpenAI Api Key',
@ -59,14 +61,7 @@ class OpenAI_LLMs implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
const { OpenAI } = await import('langchain/llms')
return getBaseClasses(OpenAI)
}
async init(nodeData: INodeData): Promise<any> {
const { OpenAI } = await import('langchain/llms')
const temperature = nodeData.inputs?.temperature as string
const modelName = nodeData.inputs?.modelName as string
const openAIApiKey = nodeData.inputs?.openAIApiKey as string

10
packages/components/nodes/memory/BufferMemory/BufferMemory.ts
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@ -1,5 +1,6 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { BufferMemory } from 'langchain/memory'
class BufferMemory_Memory implements INode {
label: string
@ -17,7 +18,8 @@ class BufferMemory_Memory implements INode {
this.type = 'BufferMemory'
this.icon = 'memory.svg'
this.category = 'Memory'
this.description = 'Perform calculations on response'
this.description = 'Remembers previous conversational back and forths directly'
this.baseClasses = [this.type, ...getBaseClasses(BufferMemory)]
this.inputs = [
{
label: 'Memory Key',
@ -34,13 +36,7 @@ class BufferMemory_Memory implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
const { BufferMemory } = await import('langchain/memory')
return getBaseClasses(BufferMemory)
}
async init(nodeData: INodeData): Promise<any> {
const { BufferMemory } = await import('langchain/memory')
const memoryKey = nodeData.inputs?.memoryKey as string
const inputKey = nodeData.inputs?.inputKey as string
return new BufferMemory({

8
packages/components/nodes/prompts/ChatPromptTemplate/ChatPromptTemplate.ts
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@ -1,5 +1,6 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate } from 'langchain/prompts'
class ChatPromptTemplate_Prompts implements INode {
label: string
@ -18,6 +19,7 @@ class ChatPromptTemplate_Prompts implements INode {
this.icon = 'prompt.svg'
this.category = 'Prompts'
this.description = 'Schema to represent a chat prompt'
this.baseClasses = [this.type, ...getBaseClasses(ChatPromptTemplate)]
this.inputs = [
{
label: 'System Message',
@ -36,13 +38,7 @@ class ChatPromptTemplate_Prompts implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
const { ChatPromptTemplate } = await import('langchain/prompts')
return getBaseClasses(ChatPromptTemplate)
}
async init(nodeData: INodeData): Promise<any> {
const { ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate } = await import('langchain/prompts')
const systemMessagePrompt = nodeData.inputs?.systemMessagePrompt as string
const humanMessagePrompt = nodeData.inputs?.humanMessagePrompt as string

25
packages/components/nodes/prompts/FewShotPromptTemplate/FewShotPromptTemplate.ts
View File

@ -1,5 +1,8 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getInputVariables } from '../../../src/utils'
import { FewShotPromptTemplate, FewShotPromptTemplateInput, PromptTemplate } from 'langchain/prompts'
import { Example } from 'langchain/schema'
import { TemplateFormat } from 'langchain/dist/prompts/template'
class FewShotPromptTemplate_Prompts implements INode {
label: string
@ -18,6 +21,7 @@ class FewShotPromptTemplate_Prompts implements INode {
this.icon = 'prompt.svg'
this.category = 'Prompts'
this.description = 'Prompt template you can build with examples'
this.baseClasses = [this.type, ...getBaseClasses(FewShotPromptTemplate)]
this.inputs = [
{
label: 'Examples',
@ -32,7 +36,7 @@ class FewShotPromptTemplate_Prompts implements INode {
{
label: 'Example Prompt',
name: 'examplePrompt',
type: 'BasePromptTemplate'
type: 'PromptTemplate'
},
{
label: 'Prefix',
@ -73,27 +77,19 @@ class FewShotPromptTemplate_Prompts implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
const { FewShotPromptTemplate } = await import('langchain/prompts')
return getBaseClasses(FewShotPromptTemplate)
}
async init(nodeData: INodeData): Promise<any> {
const { FewShotPromptTemplate } = await import('langchain/prompts')
const examplesStr = nodeData.inputs?.examples as string
const prefix = nodeData.inputs?.prefix as string
const suffix = nodeData.inputs?.suffix as string
const exampleSeparator = nodeData.inputs?.exampleSeparator as string
const templateFormat = nodeData.inputs?.templateFormat
const examplePrompt = nodeData.inputs?.examplePrompt
const templateFormat = nodeData.inputs?.templateFormat as TemplateFormat
const examplePrompt = nodeData.inputs?.examplePrompt as PromptTemplate
const inputVariables = getInputVariables(suffix)
const examples = JSON.parse(examplesStr.replace(/\s/g, ''))
const examples: Example[] = JSON.parse(examplesStr.replace(/\s/g, ''))
try {
const prompt = new FewShotPromptTemplate({
const obj: FewShotPromptTemplateInput = {
examples,
examplePrompt,
prefix,
@ -101,7 +97,8 @@ class FewShotPromptTemplate_Prompts implements INode {
inputVariables,
exampleSeparator,
templateFormat
})
}
const prompt = new FewShotPromptTemplate(obj)
return prompt
} catch (e) {
throw new Error(e)

11
packages/components/nodes/prompts/PromptTemplate/PromptTemplate.ts
View File

@ -1,5 +1,6 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getInputVariables } from '../../../src/utils'
import { PromptTemplate, PromptTemplateInput } from 'langchain/prompts'
class PromptTemplate_Prompts implements INode {
label: string
@ -18,6 +19,7 @@ class PromptTemplate_Prompts implements INode {
this.icon = 'prompt.svg'
this.category = 'Prompts'
this.description = 'Schema to represent a basic prompt for an LLM'
this.baseClasses = [this.type, ...getBaseClasses(PromptTemplate)]
this.inputs = [
{
label: 'Template',
@ -29,19 +31,12 @@ class PromptTemplate_Prompts implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
const { PromptTemplate } = await import('langchain/prompts')
return getBaseClasses(PromptTemplate)
}
async init(nodeData: INodeData): Promise<any> {
const { PromptTemplate } = await import('langchain/prompts')
const template = nodeData.inputs?.template as string
const inputVariables = getInputVariables(template)
try {
const options = {
const options: PromptTemplateInput = {
template,
inputVariables
}

10
packages/components/nodes/textsplitters/RecursiveCharacterTextSplitter/RecursiveCharacterTextSplitter.ts
View File

@ -1,5 +1,6 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { RecursiveCharacterTextSplitter, RecursiveCharacterTextSplitterParams } from 'langchain/text_splitter'
class RecursiveCharacterTextSplitter_TextSplitters implements INode {
label: string
@ -18,6 +19,7 @@ class RecursiveCharacterTextSplitter_TextSplitters implements INode {
this.icon = 'textsplitter.svg'
this.category = 'Text Splitters'
this.description = `Split documents recursively by different characters - starting with "\n\n", then "\n", then " "`
this.baseClasses = [this.type, ...getBaseClasses(RecursiveCharacterTextSplitter)]
this.inputs = [
{
label: 'Chunk Size',
@ -35,17 +37,11 @@ class RecursiveCharacterTextSplitter_TextSplitters implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
const { RecursiveCharacterTextSplitter } = await import('langchain/text_splitter')
return getBaseClasses(RecursiveCharacterTextSplitter)
}
async init(nodeData: INodeData): Promise<any> {
const { RecursiveCharacterTextSplitter } = await import('langchain/text_splitter')
const chunkSize = nodeData.inputs?.chunkSize as string
const chunkOverlap = nodeData.inputs?.chunkOverlap as string
const obj = {} as any
const obj = {} as RecursiveCharacterTextSplitterParams
if (chunkSize) obj.chunkSize = parseInt(chunkSize, 10)
if (chunkOverlap) obj.chunkOverlap = parseInt(chunkOverlap, 10)

12
packages/components/nodes/tools/Calculator/Calculator.ts
View File

@ -1,7 +1,8 @@
import { INode } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { Calculator } from 'langchain/tools/calculator'
class Calculator implements INode {
class Calculator_Tools implements INode {
label: string
name: string
description: string
@ -17,17 +18,12 @@ class Calculator implements INode {
this.icon = 'calculator.svg'
this.category = 'Tools'
this.description = 'Perform calculations on response'
}
async getBaseClasses(): Promise<string[]> {
const { Calculator } = await import('langchain/tools')
return getBaseClasses(Calculator)
this.baseClasses = [this.type, ...getBaseClasses(Calculator)]
}
async init(): Promise<any> {
const { Calculator } = await import('langchain/tools')
return new Calculator()
}
}
module.exports = { nodeClass: Calculator }
module.exports = { nodeClass: Calculator_Tools }

29
packages/components/nodes/tools/RequestsGet/RequestsGet.ts Normal file
View File

@ -0,0 +1,29 @@
import { INode } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { RequestsGetTool } from 'langchain/tools'
class RequestsGet_Tools implements INode {
label: string
name: string
description: string
type: string
icon: string
category: string
baseClasses: string[]
constructor() {
this.label = 'Requests Get'
this.name = 'requestsGet'
this.type = 'RequestsGet'
this.icon = 'requestsget.svg'
this.category = 'Tools'
this.description = 'Execute HTTP GET requests'
this.baseClasses = [this.type, ...getBaseClasses(RequestsGetTool)]
}
async init(): Promise<any> {
return new RequestsGetTool()
}
}
module.exports = { nodeClass: RequestsGet_Tools }

8
packages/components/nodes/tools/RequestsGet/requestsget.svg Normal file
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@ -0,0 +1,8 @@
<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-http-get" 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="M7 8h-2a2 2 0 0 0 -2 2v4a2 2 0 0 0 2 2h2v-4h-1"></path>
<path d="M14 8h-4v8h4"></path>
<path d="M10 12h2.5"></path>
<path d="M17 8h4"></path>
<path d="M19 8v8"></path>
</svg>
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29
packages/components/nodes/tools/RequestsPost/RequestsPost.ts Normal file
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@ -0,0 +1,29 @@
import { INode } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { RequestsPostTool } from 'langchain/tools'
class RequestsPost_Tools implements INode {
label: string
name: string
description: string
type: string
icon: string
category: string
baseClasses: string[]
constructor() {
this.label = 'Requests Post'
this.name = 'requestsPost'
this.type = 'RequestsPost'
this.icon = 'requestspost.svg'
this.category = 'Tools'
this.description = 'Execute HTTP POST requests'
this.baseClasses = [this.type, ...getBaseClasses(RequestsPostTool)]
}
async init(): Promise<any> {
return new RequestsPostTool()
}
}
module.exports = { nodeClass: RequestsPost_Tools }

6
packages/components/nodes/tools/RequestsPost/requestspost.svg Normal file
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@ -0,0 +1,6 @@
<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-http-post" 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="M3 12h2a2 2 0 1 0 0 -4h-2v8"></path>
<path d="M12 8a2 2 0 0 1 2 2v4a2 2 0 1 1 -4 0v-4a2 2 0 0 1 2 -2z"></path>
<path d="M17 15a1 1 0 0 0 1 1h2a1 1 0 0 0 1 -1v-2a1 1 0 0 0 -1 -1h-2a1 1 0 0 1 -1 -1v-2a1 1 0 0 1 1 -1h2a1 1 0 0 1 1 1"></path>
</svg>
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12
packages/components/nodes/tools/SerpAPI/SerpAPI.ts
View File

@ -1,7 +1,8 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { SerpAPI } from 'langchain/tools'
class SerpAPI implements INode {
class SerpAPI_Tools implements INode {
label: string
name: string
description: string
@ -25,18 +26,13 @@ class SerpAPI implements INode {
type: 'password'
}
]
}
async getBaseClasses(): Promise<string[]> {
const { SerpAPI } = await import('langchain/tools')
return getBaseClasses(SerpAPI)
this.baseClasses = [this.type, ...getBaseClasses(SerpAPI)]
}
async init(nodeData: INodeData): Promise<any> {
const { SerpAPI } = await import('langchain/tools')
const apiKey = nodeData.inputs?.apiKey as string
return new SerpAPI(apiKey)
}
}
module.exports = { nodeClass: SerpAPI }
module.exports = { nodeClass: SerpAPI_Tools }

12
packages/components/nodes/vectorstores/Chroma_Existing/Chroma_Existing.ts
View File

@ -1,4 +1,7 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { Chroma } from 'langchain/vectorstores/chroma'
import { Embeddings } from 'langchain/embeddings/base'
import { getBaseClasses } from '../../../src/utils'
class Chroma_Existing_VectorStores implements INode {
label: string
@ -17,6 +20,7 @@ class Chroma_Existing_VectorStores implements INode {
this.icon = 'chroma.svg'
this.category = 'Vector Stores'
this.description = 'Load existing index from Chroma (i.e: Document has been upserted)'
this.baseClasses = [this.type, ...getBaseClasses(Chroma)]
this.inputs = [
{
label: 'Embeddings',
@ -31,15 +35,9 @@ class Chroma_Existing_VectorStores implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
return ['BaseRetriever']
}
async init(nodeData: INodeData): Promise<any> {
const { Chroma } = await import('langchain/vectorstores')
const collectionName = nodeData.inputs?.collectionName as string
const embeddings = nodeData.inputs?.embeddings
const embeddings = nodeData.inputs?.embeddings as Embeddings
const vectorStore = await Chroma.fromExistingCollection(embeddings, {
collectionName

21
packages/components/nodes/vectorstores/Chroma_Upsert/Chroma_Upsert.ts
View File

@ -1,4 +1,8 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { Chroma } from 'langchain/vectorstores/chroma'
import { Embeddings } from 'langchain/embeddings/base'
import { Document } from 'langchain/document'
import { getBaseClasses } from '../../../src/utils'
class ChromaUpsert_VectorStores implements INode {
label: string
@ -17,6 +21,7 @@ class ChromaUpsert_VectorStores implements INode {
this.icon = 'chroma.svg'
this.category = 'Vector Stores'
this.description = 'Upsert documents to Chroma'
this.baseClasses = [this.type, ...getBaseClasses(Chroma)]
this.inputs = [
{
label: 'Document',
@ -36,28 +41,20 @@ class ChromaUpsert_VectorStores implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
return ['BaseRetriever']
}
async init(nodeData: INodeData): Promise<any> {
const { Chroma } = await import('langchain/vectorstores')
const { Document } = await import('langchain/document')
const collectionName = nodeData.inputs?.collectionName as string
const docs = nodeData.inputs?.document
const embeddings = nodeData.inputs?.embeddings
const docs = nodeData.inputs?.document as Document[]
const embeddings = nodeData.inputs?.embeddings as Embeddings
const finalDocs = []
for (let i = 0; i < docs.length; i += 1) {
finalDocs.push(new Document(docs[i]))
}
const result = await Chroma.fromDocuments(finalDocs, embeddings, {
const vectorStore = await Chroma.fromDocuments(finalDocs, embeddings, {
collectionName
})
const retriever = result.asRetriever()
const retriever = vectorStore.asRetriever()
return retriever
}
}

12
packages/components/nodes/vectorstores/Pinecone_Existing/Pinecone_Existing.ts
View File

@ -1,5 +1,8 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { PineconeClient } from '@pinecone-database/pinecone'
import { PineconeStore } from 'langchain/vectorstores/pinecone'
import { Embeddings } from 'langchain/embeddings/base'
import { getBaseClasses } from '../../../src/utils'
class Pinecone_Existing_VectorStores implements INode {
label: string
@ -18,6 +21,7 @@ class Pinecone_Existing_VectorStores implements INode {
this.icon = 'pinecone.png'
this.category = 'Vector Stores'
this.description = 'Load existing index from Pinecone (i.e: Document has been upserted)'
this.baseClasses = [this.type, ...getBaseClasses(PineconeStore)]
this.inputs = [
{
label: 'Embeddings',
@ -42,17 +46,11 @@ class Pinecone_Existing_VectorStores implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
return ['BaseRetriever']
}
async init(nodeData: INodeData): Promise<any> {
const { PineconeStore } = await import('langchain/vectorstores')
const pineconeApiKey = nodeData.inputs?.pineconeApiKey as string
const pineconeEnv = nodeData.inputs?.pineconeEnv as string
const index = nodeData.inputs?.pineconeIndex as string
const embeddings = nodeData.inputs?.embeddings
const embeddings = nodeData.inputs?.embeddings as Embeddings
const client = new PineconeClient()
await client.init({

21
packages/components/nodes/vectorstores/Pinecone_Upsert/Pinecone_Upsert.ts
View File

@ -1,5 +1,9 @@
import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { PineconeClient } from '@pinecone-database/pinecone'
import { PineconeStore } from 'langchain/vectorstores/pinecone'
import { Embeddings } from 'langchain/embeddings/base'
import { Document } from 'langchain/document'
import { getBaseClasses } from '../../../src/utils'
class PineconeUpsert_VectorStores implements INode {
label: string
@ -18,6 +22,7 @@ class PineconeUpsert_VectorStores implements INode {
this.icon = 'pinecone.png'
this.category = 'Vector Stores'
this.description = 'Upsert documents to Pinecone'
this.baseClasses = [this.type, ...getBaseClasses(PineconeStore)]
this.inputs = [
{
label: 'Document',
@ -47,19 +52,12 @@ class PineconeUpsert_VectorStores implements INode {
]
}
async getBaseClasses(): Promise<string[]> {
return ['BaseRetriever']
}
async init(nodeData: INodeData): Promise<any> {
const { PineconeStore } = await import('langchain/vectorstores')
const { Document } = await import('langchain/document')
const pineconeApiKey = nodeData.inputs?.pineconeApiKey as string
const pineconeEnv = nodeData.inputs?.pineconeEnv as string
const index = nodeData.inputs?.pineconeIndex as string
const docs = nodeData.inputs?.document
const embeddings = nodeData.inputs?.embeddings
const docs = nodeData.inputs?.document as Document[]
const embeddings = nodeData.inputs?.embeddings as Embeddings
const client = new PineconeClient()
await client.init({
@ -74,11 +72,10 @@ class PineconeUpsert_VectorStores implements INode {
finalDocs.push(new Document(docs[i]))
}
const result = await PineconeStore.fromDocuments(finalDocs, embeddings, {
const vectorStore = await PineconeStore.fromDocuments(finalDocs, embeddings, {
pineconeIndex
})
const retriever = result.asRetriever()
const retriever = vectorStore.asRetriever()
return retriever
}
}

2
packages/components/package.json
View File

@ -24,7 +24,7 @@
"dotenv": "^16.0.0",
"express": "^4.17.3",
"form-data": "^4.0.0",
"langchain": "^0.0.44",
"langchain": "^0.0.53",
"moment": "^2.29.3",
"node-fetch": "2",
"pdfjs-dist": "^3.5.141",

1
packages/components/src/Interface.ts
View File

@ -75,7 +75,6 @@ export interface INodeProperties {
export interface INode extends INodeProperties {
inputs?: INodeParams[]
getBaseClasses?(): Promise<string[]>
getInstance?(nodeData: INodeData): Promise<string>
run?(nodeData: INodeData, input: string, options?: ICommonObject): Promise<string>
}

3
packages/components/tsconfig.json
View File

@ -14,8 +14,7 @@
"strictPropertyInitialization": false,
"useUnknownInCatchVariables": false,
"declaration": true,
"module": "commonjs",
"moduleResolution": "node16"
"module": "commonjs"
},
"include": ["src", "nodes"]
}

282
packages/server/marketplaces/Antonym.json
View File

@ -3,11 +3,58 @@
"nodes": [
{
"width": 300,
"height": 885,
"height": 360,
"id": "promptTemplate_0",
"position": {
"x": 294.38456937448433,
"y": 66.5400435451831
},
"type": "customNode",
"data": {
"id": "promptTemplate_0",
"label": "Prompt Template",
"name": "promptTemplate",
"type": "PromptTemplate",
"baseClasses": ["PromptTemplate", "BaseStringPromptTemplate", "BasePromptTemplate"],
"category": "Prompts",
"description": "Schema to represent a basic prompt for an LLM",
"inputParams": [
{
"label": "Template",
"name": "template",
"type": "string",
"rows": 5,
"placeholder": "What is a good name for a company that makes {product}?"
}
],
"inputAnchors": [],
"inputs": {
"template": "Word: {word}\\nAntonym: {antonym}\\n"
},
"outputAnchors": [
{
"id": "promptTemplate_0-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate",
"name": "promptTemplate",
"label": "PromptTemplate",
"type": "PromptTemplate | BaseStringPromptTemplate | BasePromptTemplate"
}
],
"selected": false
},
"selected": false,
"positionAbsolute": {
"x": 294.38456937448433,
"y": 66.5400435451831
},
"dragging": false
},
{
"width": 300,
"height": 886,
"id": "fewShotPromptTemplate_0",
"position": {
"x": 495.78246013667433,
"y": 168.3684510250569
"x": 719.2200337843097,
"y": 67.20405755860693
},
"type": "customNode",
"data": {
@ -15,7 +62,7 @@
"label": "Few Shot Prompt Template",
"name": "fewShotPromptTemplate",
"type": "FewShotPromptTemplate",
"baseClasses": ["BaseStringPromptTemplate", "BasePromptTemplate"],
"baseClasses": ["FewShotPromptTemplate", "BaseStringPromptTemplate", "BasePromptTemplate"],
"category": "Prompts",
"description": "Prompt template you can build with examples",
"inputParams": [
@ -24,7 +71,7 @@
"name": "examples",
"type": "string",
"rows": 5,
"placeholder": "[\n { word: \"happy\", antonym: \"sad\" },\n { word: \"tall\", antonym: \"short\" },\n]"
"placeholder": "[\n { \"word\": \"happy\", \"antonym\": \"sad\" },\n { \"word\": \"tall\", \"antonym\": \"short\" },\n]"
},
{
"label": "Prefix",
@ -67,8 +114,8 @@
{
"label": "Example Prompt",
"name": "examplePrompt",
"type": "BasePromptTemplate",
"id": "fewShotPromptTemplate_0-input-examplePrompt-BasePromptTemplate"
"type": "PromptTemplate",
"id": "fewShotPromptTemplate_0-input-examplePrompt-PromptTemplate"
}
],
"inputs": {
@ -81,128 +128,28 @@
},
"outputAnchors": [
{
"id": "fewShotPromptTemplate_0-output-fewShotPromptTemplate-BaseStringPromptTemplate|BasePromptTemplate",
"id": "fewShotPromptTemplate_0-output-fewShotPromptTemplate-FewShotPromptTemplate|BaseStringPromptTemplate|BasePromptTemplate",
"name": "fewShotPromptTemplate",
"label": "FewShotPromptTemplate",
"type": "BaseStringPromptTemplate | BasePromptTemplate"
"type": "FewShotPromptTemplate | BaseStringPromptTemplate | BasePromptTemplate"
}
],
"selected": false
},
"selected": false,
"positionAbsolute": {
"x": 495.78246013667433,
"y": 168.3684510250569
"x": 719.2200337843097,
"y": 67.20405755860693
},
"dragging": false
},
{
"width": 300,
"height": 359,
"id": "promptTemplate_0",
"position": {
"x": 13.229214123006699,
"y": 171.79555808656028
},
"type": "customNode",
"data": {
"id": "promptTemplate_0",
"label": "Prompt Template",
"name": "promptTemplate",
"type": "PromptTemplate",
"baseClasses": ["BaseStringPromptTemplate", "BasePromptTemplate"],
"category": "Prompts",
"description": "Schema to represent a basic prompt for an LLM",
"inputParams": [
{
"label": "Template",
"name": "template",
"type": "string",
"rows": 5,
"placeholder": "What is a good name for a company that makes {product}?"
}
],
"inputAnchors": [],
"inputs": {
"template": "Word: {word}\\nAntonym: {antonym}\\n"
},
"outputAnchors": [
{
"id": "promptTemplate_0-output-promptTemplate-BaseStringPromptTemplate|BasePromptTemplate",
"name": "promptTemplate",
"label": "PromptTemplate",
"type": "BaseStringPromptTemplate | BasePromptTemplate"
}
],
"selected": false
},
"selected": false,
"positionAbsolute": {
"x": 13.229214123006699,
"y": 171.79555808656028
},
"dragging": false
},
{
"width": 300,
"height": 279,
"id": "llmChain_0",
"position": {
"x": 1237.4411644942688,
"y": 508.82448993622904
},
"type": "customNode",
"data": {
"id": "llmChain_0",
"label": "LLM Chain",
"name": "llmChain",
"type": "LLMChain",
"baseClasses": ["BaseChain"],
"category": "Chains",
"description": "Chain to run queries against LLMs",
"inputParams": [],
"inputAnchors": [
{
"label": "LLM",
"name": "llm",
"type": "BaseLanguageModel",
"id": "llmChain_0-input-llm-BaseLanguageModel"
},
{
"label": "Prompt",
"name": "prompt",
"type": "BasePromptTemplate",
"id": "llmChain_0-input-prompt-BasePromptTemplate"
}
],
"inputs": {
"llm": "{{openAI_0.data.instance}}",
"prompt": "{{fewShotPromptTemplate_0.data.instance}}"
},
"outputAnchors": [
{
"id": "llmChain_0-output-llmChain-BaseChain",
"name": "llmChain",
"label": "LLMChain",
"type": "BaseChain"
}
],
"selected": false
},
"selected": false,
"positionAbsolute": {
"x": 1237.4411644942688,
"y": 508.82448993622904
},
"dragging": false
},
{
"width": 300,
"height": 471,
"height": 472,
"id": "openAI_0",
"position": {
"x": 859.220671981777,
"y": 166.25170842824588
"x": 1089.6434062122398,
"y": 27.515288538129425
},
"type": "customNode",
"data": {
@ -210,7 +157,7 @@
"label": "OpenAI",
"name": "openAI",
"type": "OpenAI",
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106
packages/server/marketplaces/Conversational Agent.json
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212
packages/server/marketplaces/Conversational Retrieval QA Chain.json
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240
packages/server/marketplaces/MRLKAgent.json → packages/server/marketplaces/MRKLAgent.json
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@ -120,28 +29,119 @@
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174
packages/server/marketplaces/Simple LLM Chain.json
View File

@ -3,74 +3,11 @@
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302
packages/server/marketplaces/Translator.json
View File

@ -4,143 +4,10 @@
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"sourceHandle": "chatPromptTemplate_0-output-chatPromptTemplate-BasePromptTemplate",
"sourceHandle": "chatPromptTemplate_0-output-chatPromptTemplate-ChatPromptTemplate|BaseChatPromptTemplate|BasePromptTemplate",
"target": "llmChain_0",
"targetHandle": "llmChain_0-input-prompt-BasePromptTemplate",
"type": "buttonedge",
"id": "chatPromptTemplate_0-chatPromptTemplate_0-output-chatPromptTemplate-BasePromptTemplate-llmChain_0-llmChain_0-input-prompt-BasePromptTemplate",
"id": "chatPromptTemplate_0-chatPromptTemplate_0-output-chatPromptTemplate-ChatPromptTemplate|BaseChatPromptTemplate|BasePromptTemplate-llmChain_0-llmChain_0-input-prompt-BasePromptTemplate",
"data": {
"label": ""
}

3
packages/server/src/NodesPool.ts
View File

@ -23,9 +23,6 @@ export class NodesPool {
const newNodeInstance = new nodeModule.nodeClass()
newNodeInstance.filePath = file
const baseClasses = await newNodeInstance.getBaseClasses!.call(newNodeInstance)
newNodeInstance.baseClasses = baseClasses
this.componentNodes[newNodeInstance.name] = newNodeInstance
// Replace file icon with absolute path

4
packages/server/src/utils/index.ts
View File

@ -107,7 +107,9 @@ export const getEndingNode = (nodeDependencies: INodeDependencies, graph: INodeD
// Find ending node
let endingNodeId = ''
Object.keys(graph).forEach((nodeId) => {
if (!graph[nodeId].length && nodeDependencies[nodeId] > 0) {
if (Object.keys(nodeDependencies).length === 1) {
endingNodeId = nodeId
} else if (!graph[nodeId].length && nodeDependencies[nodeId] > 0) {
endingNodeId = nodeId
}
})

21
packages/ui/src/views/canvas/NodeInputHandler.js
View File

@ -3,15 +3,21 @@ import { Handle, Position, useUpdateNodeInternals } from 'reactflow'
import { useEffect, useRef, useState, useContext } from 'react'
// material-ui
import { useTheme } from '@mui/material/styles'
import { useTheme, styled } from '@mui/material/styles'
import { Box, Typography, Tooltip } from '@mui/material'
import { tooltipClasses } from '@mui/material/Tooltip'
import { Dropdown } from 'ui-component/dropdown/Dropdown'
import { Input } from 'ui-component/input/Input'
import { File } from 'ui-component/file/File'
import { flowContext } from 'store/context/ReactFlowContext'
import { isValidConnection } from 'utils/genericHelper'
const CustomWidthTooltip = styled(({ className, ...props }) => <Tooltip {...props} classes={{ popper: className }} />)({
[`& .${tooltipClasses.tooltip}`]: {
maxWidth: 500
}
})
// ===========================|| NodeInputHandler ||=========================== //
const NodeInputHandler = ({ inputAnchor, inputParam, data, disabled = false }) => {
@ -36,14 +42,7 @@ const NodeInputHandler = ({ inputAnchor, inputParam, data, disabled = false }) =
<div ref={ref}>
{inputAnchor && (
<>
<Tooltip
placement='left'
title={
<Typography sx={{ color: 'white', p: 1 }} variant='h5'>
{'Type: ' + inputAnchor.type}
</Typography>
}
>
<CustomWidthTooltip placement='left' title={inputAnchor.type}>
<Handle
type='target'
position={Position.Left}
@ -57,7 +56,7 @@ const NodeInputHandler = ({ inputAnchor, inputParam, data, disabled = false }) =
top: position
}}
/>
</Tooltip>
</CustomWidthTooltip>
<Box sx={{ p: 2 }}>
<Typography>
{inputAnchor.label}

20
packages/ui/src/views/canvas/NodeOutputHandler.js
View File

@ -3,11 +3,18 @@ import { Handle, Position, useUpdateNodeInternals } from 'reactflow'
import { useEffect, useRef, useState, useContext } from 'react'
// material-ui
import { useTheme } from '@mui/material/styles'
import { useTheme, styled } from '@mui/material/styles'
import { Box, Typography, Tooltip } from '@mui/material'
import { tooltipClasses } from '@mui/material/Tooltip'
import { flowContext } from 'store/context/ReactFlowContext'
import { isValidConnection } from 'utils/genericHelper'
const CustomWidthTooltip = styled(({ className, ...props }) => <Tooltip {...props} classes={{ popper: className }} />)({
[`& .${tooltipClasses.tooltip}`]: {
maxWidth: 500
}
})
// ===========================|| NodeOutputHandler ||=========================== //
const NodeOutputHandler = ({ outputAnchor, data }) => {
@ -34,14 +41,7 @@ const NodeOutputHandler = ({ outputAnchor, data }) => {
return (
<div ref={ref}>
<Tooltip
placement='right'
title={
<Typography sx={{ color: 'white', p: 1 }} variant='h5'>
{'Type: ' + outputAnchor.type}
</Typography>
}
>
<CustomWidthTooltip placement='right' title={outputAnchor.type}>
<Handle
type='source'
position={Position.Right}
@ -55,7 +55,7 @@ const NodeOutputHandler = ({ outputAnchor, data }) => {
top: position
}}
/>
</Tooltip>
</CustomWidthTooltip>
<Box sx={{ p: 2, textAlign: 'end' }}>
<Typography>{outputAnchor.label}</Typography>
</Box>

10
packages/ui/src/views/chatmessage/ChatMessage.css
View File

@ -1,7 +1,3 @@
.cloudform {
position: relative;
}
.messagelist {
width: 100%;
height: 100%;
@ -113,13 +109,11 @@
position: relative;
flex-direction: column;
padding: 10px;
max-width: 500px;
}
.cloud {
width: '100%';
max-width: 500px;
height: 73vh;
width: 400px;
height: calc(100vh - 260px);
border-radius: 0.5rem;
display: flex;
justify-content: center;

6
packages/ui/src/views/chatmessage/ChatMessage.js
View File

@ -336,13 +336,13 @@ export const ChatMessage = ({ chatflowid }) => {
</div>
<Divider />
<div className='center'>
<div className='cloudform'>
<form onSubmit={handleSubmit}>
<div style={{ width: '100%' }}>
<form style={{ width: '100%' }} onSubmit={handleSubmit}>
<OutlinedInput
inputRef={inputRef}
// eslint-disable-next-line
autoFocus
sx={{ width: '50vh' }}
sx={{ width: '100%' }}
disabled={loading || !chatflowid}
onKeyDown={handleEnter}
id='userInput'