102 lines
3.8 KiB
TypeScript
102 lines
3.8 KiB
TypeScript
import { BaseLanguageModel } from '@langchain/core/language_models/base'
|
|
import { VectorStore } from '@langchain/core/vectorstores'
|
|
import { VectorDBQAChain } from 'langchain/chains'
|
|
import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler'
|
|
import { ICommonObject, INode, INodeData, INodeParams, IServerSideEventStreamer } from '../../../src/Interface'
|
|
import { getBaseClasses } from '../../../src/utils'
|
|
import { checkInputs, Moderation } from '../../moderation/Moderation'
|
|
import { formatResponse } from '../../outputparsers/OutputParserHelpers'
|
|
|
|
class VectorDBQAChain_Chains implements INode {
|
|
label: string
|
|
name: string
|
|
version: number
|
|
type: string
|
|
icon: string
|
|
category: string
|
|
baseClasses: string[]
|
|
description: string
|
|
inputs: INodeParams[]
|
|
|
|
constructor() {
|
|
this.label = 'VectorDB QA Chain'
|
|
this.name = 'vectorDBQAChain'
|
|
this.version = 2.0
|
|
this.type = 'VectorDBQAChain'
|
|
this.icon = 'vectordb.svg'
|
|
this.category = 'Chains'
|
|
this.description = 'QA chain for vector databases'
|
|
this.baseClasses = [this.type, ...getBaseClasses(VectorDBQAChain)]
|
|
this.inputs = [
|
|
{
|
|
label: 'Language Model',
|
|
name: 'model',
|
|
type: 'BaseLanguageModel'
|
|
},
|
|
{
|
|
label: 'Vector Store',
|
|
name: 'vectorStore',
|
|
type: 'VectorStore'
|
|
},
|
|
{
|
|
label: 'Input Moderation',
|
|
description: 'Detect text that could generate harmful output and prevent it from being sent to the language model',
|
|
name: 'inputModeration',
|
|
type: 'Moderation',
|
|
optional: true,
|
|
list: true
|
|
}
|
|
]
|
|
}
|
|
|
|
async init(nodeData: INodeData): Promise<any> {
|
|
const model = nodeData.inputs?.model as BaseLanguageModel
|
|
const vectorStore = nodeData.inputs?.vectorStore as VectorStore
|
|
|
|
const chain = VectorDBQAChain.fromLLM(model, vectorStore, {
|
|
k: (vectorStore as any)?.k ?? 4,
|
|
verbose: process.env.DEBUG === 'true' ? true : false
|
|
})
|
|
return chain
|
|
}
|
|
|
|
async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | object> {
|
|
const chain = nodeData.instance as VectorDBQAChain
|
|
const moderations = nodeData.inputs?.inputModeration as Moderation[]
|
|
|
|
const shouldStreamResponse = options.shouldStreamResponse
|
|
const sseStreamer: IServerSideEventStreamer = options.sseStreamer as IServerSideEventStreamer
|
|
const chatId = options.chatId
|
|
|
|
if (moderations && moderations.length > 0) {
|
|
try {
|
|
// Use the output of the moderation chain as input for the VectorDB QA Chain
|
|
input = await checkInputs(moderations, input)
|
|
} catch (e) {
|
|
await new Promise((resolve) => setTimeout(resolve, 500))
|
|
// if (options.shouldStreamResponse) {
|
|
// streamResponse(options.sseStreamer, options.chatId, e.message)
|
|
// }
|
|
return formatResponse(e.message)
|
|
}
|
|
}
|
|
const obj = {
|
|
query: input
|
|
}
|
|
|
|
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
|
|
const callbacks = await additionalCallbacks(nodeData, options)
|
|
|
|
if (shouldStreamResponse) {
|
|
const handler = new CustomChainHandler(sseStreamer, chatId)
|
|
const res = await chain.call(obj, [loggerHandler, handler, ...callbacks])
|
|
return res?.text
|
|
} else {
|
|
const res = await chain.call(obj, [loggerHandler, ...callbacks])
|
|
return res?.text
|
|
}
|
|
}
|
|
}
|
|
|
|
module.exports = { nodeClass: VectorDBQAChain_Chains }
|