Merge pull request #1162 from SearchApi/feature/add-searchapi

Add SearchApi documentloader, tool & podcast QA example
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Henry Heng 2023-11-02 21:46:13 +00:00 committed by GitHub
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import { INodeParams, INodeCredential } from '../src/Interface'
class SearchApi implements INodeCredential {
label: string
name: string
version: number
description: string
inputs: INodeParams[]
constructor() {
this.label = 'Search API'
this.name = 'searchApi'
this.version = 1.0
this.description =
'Sign in to <a target="_blank" href="https://www.searchapi.io/">SearchApi</a> to obtain a free API key from the dashboard.'
this.inputs = [
{
label: 'SearchApi API Key',
name: 'searchApiKey',
type: 'password'
}
]
}
}
module.exports = { credClass: SearchApi }

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import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { TextSplitter } from 'langchain/text_splitter'
import { SearchApiLoader } from 'langchain/document_loaders/web/searchapi'
import { getCredentialData, getCredentialParam } from '../../../src'
// Provides access to multiple search engines using the SearchApi.
// For available parameters & engines, refer to: https://www.searchapi.io/docs/google
class SearchAPI_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 = 'SearchApi For Web Search'
this.name = 'searchApi'
this.version = 1.0
this.type = 'Document'
this.icon = 'searchapi.svg'
this.category = 'Document Loaders'
this.description = 'Load data from real-time search results'
this.baseClasses = [this.type]
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
optional: false,
credentialNames: ['searchApi']
}
this.inputs = [
{
label: 'Query',
name: 'query',
type: 'string',
optional: true
},
{
label: 'Custom Parameters',
name: 'customParameters',
type: 'json',
optional: true,
additionalParams: true
},
{
label: 'Text Splitter',
name: 'textSplitter',
type: 'TextSplitter',
optional: true
},
{
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 query = nodeData.inputs?.query as string
const customParameters = nodeData.inputs?.customParameters
const metadata = nodeData.inputs?.metadata
// Fetch the API credentials for this node
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const searchApiKey = getCredentialParam('searchApiKey', credentialData, nodeData)
// Check and parse custom parameters (should be JSON or object)
const parsedParameters = typeof customParameters === 'object' ? customParameters : JSON.parse(customParameters || '{}')
// Prepare the configuration for the SearchApiLoader
const loaderConfig = {
q: query,
apiKey: searchApiKey,
...parsedParameters
}
// Initialize the loader with the given configuration
const loader = new SearchApiLoader(loaderConfig)
// Fetch documents, split if a text splitter is provided
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: SearchAPI_DocumentLoaders }

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import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { SearchApi } from 'langchain/tools'
class SearchAPI_Tools 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 = 'SearchApi'
this.name = 'searchAPI'
this.version = 1.0
this.type = 'SearchAPI'
this.icon = 'searchapi.svg'
this.category = 'Tools'
this.description = 'Real-time API for accessing Google Search data'
this.inputs = []
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['searchApi']
}
this.baseClasses = [this.type, ...getBaseClasses(SearchApi)]
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const searchApiKey = getCredentialParam('searchApiKey', credentialData, nodeData)
return new SearchApi(searchApiKey)
}
}
module.exports = { nodeClass: SearchAPI_Tools }

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{
"description": "Engage with data sources such as YouTube Transcripts, Google, and more through intelligent Q&A interactions",
"nodes": [
{
"width": 300,
"height": 483,
"id": "conversationalRetrievalQAChain_0",
"position": {
"x": 1499.2693059023254,
"y": 430.03911199833317
},
"type": "customNode",
"data": {
"id": "conversationalRetrievalQAChain_0",
"label": "Conversational Retrieval QA Chain",
"version": 1,
"name": "conversationalRetrievalQAChain",
"type": "ConversationalRetrievalQAChain",
"baseClasses": ["ConversationalRetrievalQAChain", "BaseChain", "Runnable"],
"category": "Chains",
"description": "Document QA - built on RetrievalQAChain to provide a chat history component",
"inputParams": [
{
"label": "Return Source Documents",
"name": "returnSourceDocuments",
"type": "boolean",
"optional": true,
"id": "conversationalRetrievalQAChain_0-input-returnSourceDocuments-boolean"
},
{
"label": "System Message",
"name": "systemMessagePrompt",
"type": "string",
"rows": 4,
"additionalParams": true,
"optional": true,
"placeholder": "I want you to act as a document that I am having a conversation with. Your name is \"AI Assistant\". You will provide me with answers from the given info. If the answer is not included, say exactly \"Hmm, I am not sure.\" and stop after that. Refuse to answer any question not about the info. Never break character.",
"id": "conversationalRetrievalQAChain_0-input-systemMessagePrompt-string"
},
{
"label": "Chain Option",
"name": "chainOption",
"type": "options",
"options": [
{
"label": "MapReduceDocumentsChain",
"name": "map_reduce",
"description": "Suitable for QA tasks over larger documents and can run the preprocessing step in parallel, reducing the running time"
},
{
"label": "RefineDocumentsChain",
"name": "refine",
"description": "Suitable for QA tasks over a large number of documents."
},
{
"label": "StuffDocumentsChain",
"name": "stuff",
"description": "Suitable for QA tasks over a small number of documents."
}
],
"additionalParams": true,
"optional": true,
"id": "conversationalRetrievalQAChain_0-input-chainOption-options"
}
],
"inputAnchors": [
{
"label": "Language Model",
"name": "model",
"type": "BaseLanguageModel",
"id": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel"
},
{
"label": "Vector Store Retriever",
"name": "vectorStoreRetriever",
"type": "BaseRetriever",
"id": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever"
},
{
"label": "Memory",
"name": "memory",
"type": "BaseMemory",
"optional": true,
"description": "If left empty, a default BufferMemory will be used",
"id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory"
}
],
"inputs": {
"model": "{{chatOpenAI_0.data.instance}}",
"vectorStoreRetriever": "{{memoryVectorStore_0.data.instance}}",
"memory": "",
"returnSourceDocuments": "",
"systemMessagePrompt": "",
"chainOption": ""
},
"outputAnchors": [
{
"id": "conversationalRetrievalQAChain_0-output-conversationalRetrievalQAChain-ConversationalRetrievalQAChain|BaseChain|Runnable",
"name": "conversationalRetrievalQAChain",
"label": "ConversationalRetrievalQAChain",
"type": "ConversationalRetrievalQAChain | BaseChain | Runnable"
}
],
"outputs": {},
"selected": false
},
"selected": false,
"positionAbsolute": {
"x": 1499.2693059023254,
"y": 430.03911199833317
},
"dragging": false
},
{
"width": 300,
"height": 408,
"id": "memoryVectorStore_0",
"position": {
"x": 1082.0280622332507,
"y": 589.9990964387842
},
"type": "customNode",
"data": {
"id": "memoryVectorStore_0",
"label": "In-Memory Vector Store",
"version": 1,
"name": "memoryVectorStore",
"type": "Memory",
"baseClasses": ["Memory", "VectorStoreRetriever", "BaseRetriever"],
"category": "Vector Stores",
"description": "In-memory vectorstore that stores embeddings and does an exact, linear search for the most similar embeddings.",
"inputParams": [
{
"label": "Top K",
"name": "topK",
"description": "Number of top results to fetch. Default to 4",
"placeholder": "4",
"type": "number",
"optional": true,
"id": "memoryVectorStore_0-input-topK-number"
}
],
"inputAnchors": [
{
"label": "Document",
"name": "document",
"type": "Document",
"list": true,
"id": "memoryVectorStore_0-input-document-Document"
},
{
"label": "Embeddings",
"name": "embeddings",
"type": "Embeddings",
"id": "memoryVectorStore_0-input-embeddings-Embeddings"
}
],
"inputs": {
"document": ["{{searchApi_0.data.instance}}", "{{searchApi_0.data.instance}}", "{{searchApi_0.data.instance}}"],
"embeddings": "{{openAIEmbeddings_0.data.instance}}",
"topK": ""
},
"outputAnchors": [
{
"name": "output",
"label": "Output",
"type": "options",
"options": [
{
"id": "memoryVectorStore_0-output-retriever-Memory|VectorStoreRetriever|BaseRetriever",
"name": "retriever",
"label": "Memory Retriever",
"type": "Memory | VectorStoreRetriever | BaseRetriever"
},
{
"id": "memoryVectorStore_0-output-vectorStore-Memory|VectorStore",
"name": "vectorStore",
"label": "Memory Vector Store",
"type": "Memory | VectorStore"
}
],
"default": "retriever"
}
],
"outputs": {
"output": "retriever"
},
"selected": false
},
"positionAbsolute": {
"x": 1082.0280622332507,
"y": 589.9990964387842
},
"selected": false,
"dragging": false
},
{
"width": 300,
"height": 577,
"id": "chatOpenAI_0",
"position": {
"x": 1056.2788608917747,
"y": -60.59149112477064
},
"type": "customNode",
"data": {
"id": "chatOpenAI_0",
"label": "ChatOpenAI",
"version": 2,
"name": "chatOpenAI",
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel", "Runnable"],
"category": "Chat Models",
"description": "Wrapper around OpenAI large language models that use the Chat endpoint",
"inputParams": [
{
"label": "Connect Credential",
"name": "credential",
"type": "credential",
"credentialNames": ["openAIApi"],
"id": "chatOpenAI_0-input-credential-credential"
},
{
"label": "Model Name",
"name": "modelName",
"type": "options",
"options": [
{
"label": "gpt-4",
"name": "gpt-4"
},
{
"label": "gpt-4-0613",
"name": "gpt-4-0613"
},
{
"label": "gpt-4-32k",
"name": "gpt-4-32k"
},
{
"label": "gpt-4-32k-0613",
"name": "gpt-4-32k-0613"
},
{
"label": "gpt-3.5-turbo",
"name": "gpt-3.5-turbo"
},
{
"label": "gpt-3.5-turbo-0613",
"name": "gpt-3.5-turbo-0613"
},
{
"label": "gpt-3.5-turbo-16k",
"name": "gpt-3.5-turbo-16k"
},
{
"label": "gpt-3.5-turbo-16k-0613",
"name": "gpt-3.5-turbo-16k-0613"
}
],
"default": "gpt-3.5-turbo",
"optional": true,
"id": "chatOpenAI_0-input-modelName-options"
},
{
"label": "Temperature",
"name": "temperature",
"type": "number",
"step": 0.1,
"default": 0.9,
"optional": true,
"id": "chatOpenAI_0-input-temperature-number"
},
{
"label": "Max Tokens",
"name": "maxTokens",
"type": "number",
"step": 1,
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-maxTokens-number"
},
{
"label": "Top Probability",
"name": "topP",
"type": "number",
"step": 0.1,
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-topP-number"
},
{
"label": "Frequency Penalty",
"name": "frequencyPenalty",
"type": "number",
"step": 0.1,
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-frequencyPenalty-number"
},
{
"label": "Presence Penalty",
"name": "presencePenalty",
"type": "number",
"step": 0.1,
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-presencePenalty-number"
},
{
"label": "Timeout",
"name": "timeout",
"type": "number",
"step": 1,
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-timeout-number"
},
{
"label": "BasePath",
"name": "basepath",
"type": "string",
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-basepath-string"
},
{
"label": "BaseOptions",
"name": "baseOptions",
"type": "json",
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-baseOptions-json"
}
],
"inputAnchors": [
{
"label": "Cache",
"name": "cache",
"type": "BaseCache",
"optional": true,
"id": "chatOpenAI_0-input-cache-BaseCache"
}
],
"inputs": {
"cache": "",
"modelName": "gpt-3.5-turbo",
"temperature": "0.5",
"maxTokens": "",
"topP": "",
"frequencyPenalty": "",
"presencePenalty": "",
"timeout": "",
"basepath": "",
"baseOptions": ""
},
"outputAnchors": [
{
"id": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable",
"name": "chatOpenAI",
"label": "ChatOpenAI",
"type": "ChatOpenAI | BaseChatModel | BaseLanguageModel | Runnable"
}
],
"outputs": {},
"selected": false
},
"selected": false,
"positionAbsolute": {
"x": 1056.2788608917747,
"y": -60.59149112477064
},
"dragging": false
},
{
"width": 300,
"height": 478,
"id": "characterTextSplitter_0",
"position": {
"x": 260.5475803279806,
"y": -65.1647664861618
},
"type": "customNode",
"data": {
"id": "characterTextSplitter_0",
"label": "Character Text Splitter",
"version": 1,
"name": "characterTextSplitter",
"type": "CharacterTextSplitter",
"baseClasses": ["CharacterTextSplitter", "TextSplitter", "BaseDocumentTransformer", "Runnable"],
"category": "Text Splitters",
"description": "splits only on one type of character (defaults to \"\\n\\n\").",
"inputParams": [
{
"label": "Chunk Size",
"name": "chunkSize",
"type": "number",
"default": 1000,
"optional": true,
"id": "characterTextSplitter_0-input-chunkSize-number"
},
{
"label": "Chunk Overlap",
"name": "chunkOverlap",
"type": "number",
"optional": true,
"id": "characterTextSplitter_0-input-chunkOverlap-number"
},
{
"label": "Custom Separator",
"name": "separator",
"type": "string",
"placeholder": "\" \"",
"description": "Seperator to determine when to split the text, will override the default separator",
"optional": true,
"id": "characterTextSplitter_0-input-separator-string"
}
],
"inputAnchors": [],
"inputs": {
"chunkSize": "2000",
"chunkOverlap": "200",
"separator": ""
},
"outputAnchors": [
{
"id": "characterTextSplitter_0-output-characterTextSplitter-CharacterTextSplitter|TextSplitter|BaseDocumentTransformer|Runnable",
"name": "characterTextSplitter",
"label": "CharacterTextSplitter",
"type": "CharacterTextSplitter | TextSplitter | BaseDocumentTransformer | Runnable"
}
],
"outputs": {},
"selected": false
},
"selected": false,
"positionAbsolute": {
"x": 260.5475803279806,
"y": -65.1647664861618
},
"dragging": false
},
{
"width": 300,
"height": 332,
"id": "openAIEmbeddings_0",
"position": {
"x": 666.3950526535211,
"y": 777.4191705193945
},
"type": "customNode",
"data": {
"id": "openAIEmbeddings_0",
"label": "OpenAI Embeddings",
"version": 1,
"name": "openAIEmbeddings",
"type": "OpenAIEmbeddings",
"baseClasses": ["OpenAIEmbeddings", "Embeddings"],
"category": "Embeddings",
"description": "OpenAI API to generate embeddings for a given text",
"inputParams": [
{
"label": "Connect Credential",
"name": "credential",
"type": "credential",
"credentialNames": ["openAIApi"],
"id": "openAIEmbeddings_0-input-credential-credential"
},
{
"label": "Strip New Lines",
"name": "stripNewLines",
"type": "boolean",
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