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https://github.com/farcasclaudiu/Flowise.git
synced 2026-06-29 13:01:14 +03:00
add get and post api chain
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@@ -0,0 +1,118 @@
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import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
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import { CustomChainHandler, getBaseClasses } from '../../../src/utils'
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import { BaseLanguageModel } from 'langchain/base_language'
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import { PromptTemplate } from 'langchain/prompts'
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import { API_RESPONSE_RAW_PROMPT_TEMPLATE, API_URL_RAW_PROMPT_TEMPLATE, APIChain } from './postCore'
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class POSTApiChain_Chains implements INode {
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label: string
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name: string
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type: string
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icon: string
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category: string
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baseClasses: string[]
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description: string
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inputs: INodeParams[]
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constructor() {
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this.label = 'POST API Chain'
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this.name = 'postApiChain'
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this.type = 'POSTApiChain'
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this.icon = 'apichain.svg'
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this.category = 'Chains'
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this.description = 'Chain to run queries against POST API'
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this.baseClasses = [this.type, ...getBaseClasses(APIChain)]
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this.inputs = [
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{
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label: 'Language Model',
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name: 'model',
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type: 'BaseLanguageModel'
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},
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{
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label: 'API Documentation',
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name: 'apiDocs',
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type: 'string',
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description:
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'Description of how API works. Please refer to more <a target="_blank" href="https://github.com/hwchase17/langchain/blob/master/langchain/chains/api/open_meteo_docs.py">examples</a>',
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rows: 4
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},
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{
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label: 'Headers',
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name: 'headers',
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type: 'json',
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additionalParams: true,
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optional: true
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},
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{
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label: 'URL Prompt',
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name: 'urlPrompt',
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type: 'string',
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description: 'Prompt used to tell LLMs how to construct the URL. Must contains {api_docs} and {question}',
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default: API_URL_RAW_PROMPT_TEMPLATE,
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rows: 4,
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additionalParams: true
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},
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{
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label: 'Answer Prompt',
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name: 'ansPrompt',
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type: 'string',
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description:
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'Prompt used to tell LLMs how to return the API response. Must contains {api_response}, {api_url}, and {question}',
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default: API_RESPONSE_RAW_PROMPT_TEMPLATE,
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rows: 4,
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additionalParams: true
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}
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]
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}
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async init(nodeData: INodeData): Promise<any> {
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const model = nodeData.inputs?.model as BaseLanguageModel
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const apiDocs = nodeData.inputs?.apiDocs as string
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const headers = nodeData.inputs?.headers as string
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const urlPrompt = nodeData.inputs?.urlPrompt as string
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const ansPrompt = nodeData.inputs?.ansPrompt as string
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const chain = await getAPIChain(apiDocs, model, headers, urlPrompt, ansPrompt)
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return chain
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}
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async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
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const model = nodeData.inputs?.model as BaseLanguageModel
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const apiDocs = nodeData.inputs?.apiDocs as string
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const headers = nodeData.inputs?.headers as string
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const urlPrompt = nodeData.inputs?.urlPrompt as string
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const ansPrompt = nodeData.inputs?.ansPrompt as string
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const chain = await getAPIChain(apiDocs, model, headers, urlPrompt, ansPrompt)
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if (options.socketIO && options.socketIOClientId) {
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const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId, 2)
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const res = await chain.run(input, [handler])
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return res
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} else {
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const res = await chain.run(input)
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return res
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}
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}
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}
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const getAPIChain = async (documents: string, llm: BaseLanguageModel, headers: string, urlPrompt: string, ansPrompt: string) => {
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const apiUrlPrompt = new PromptTemplate({
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inputVariables: ['api_docs', 'question'],
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template: urlPrompt ? urlPrompt : API_URL_RAW_PROMPT_TEMPLATE
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})
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const apiResponsePrompt = new PromptTemplate({
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inputVariables: ['api_docs', 'question', 'api_url_body', 'api_response'],
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template: ansPrompt ? ansPrompt : API_RESPONSE_RAW_PROMPT_TEMPLATE
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})
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const chain = APIChain.fromLLMAndAPIDocs(llm, documents, {
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apiUrlPrompt,
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apiResponsePrompt,
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verbose: process.env.DEBUG === 'true' ? true : false,
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headers: typeof headers === 'object' ? headers : headers ? JSON.parse(headers) : {}
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})
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return chain
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}
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module.exports = { nodeClass: POSTApiChain_Chains }
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