farcasclaudiu/Flowise
1
0
Fork 0
mirror of https://github.com/farcasclaudiu/Flowise.git synced 2026-06-28 09:00:52 +03:00
Code Issues Packages Projects Releases Wiki Activity

Merge branch 'main' into feature/ChatHistory2

Browse Source
This commit is contained in:
Henry
2023-11-02 21:48:18 +00:00
parent dbde865f1c 4f3d352606
commit 6ab20cd445
40 changed files with 1380 additions and 273 deletions
Download Patch File Download Diff File Expand all files Collapse all files
packages/components/credentials/SearchApi.credential.ts
+26
View File
@@ -0,0 +1,26 @@
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 }
packages/components/nodes/agents/CSVAgent/CSVAgent.ts
+1 -1
View File
@@ -131,7 +131,7 @@ json.dumps(my_dict)`
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: "${pythonCode}"`)
throw new Error(`Sorry, I'm unable to find answer for question: "${input}" using following code: "${pythonCode}"`)
}
}
packages/components/nodes/chains/ConversationChain/ConversationChain.ts
+3 -1
View File
@@ -71,7 +71,9 @@ class ConversationChain_Chains implements INode {
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
finalDocs.push(new Document(flattenDocs[i]))
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
}
}
let finalText = ''
packages/components/nodes/documentloaders/SearchApi/SearchAPI.ts
+109
View File
@@ -0,0 +1,109 @@
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 }
packages/components/nodes/documentloaders/SearchApi/searchapi.svg
+1
View File
@@ -0,0 +1 @@
<svg id="SvgjsSvg1001" width="75.27131652832031" height="63.92396926879883" xmlns="http://www.w3.org/2000/svg" version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svgjs="http://svgjs.com/svgjs" viewBox="0 0 75.27131652832031 63.92396926879883"><defs id="SvgjsDefs1002"></defs><rect id="SvgjsRect1008" width="75.27131652832031" height="63.92396926879883" fill="transparent"></rect><g id="SvgjsG1009" transform="matrix(1,0,0,1,-39.50003433227539,-50.53549575805664)"><title>0479_octopus_verti</title><path id="color_1" d="M97.24234,109.8245a2.57759,2.57759,0,0,1-2.57778,2.57778,9.80672,9.80672,0,0,1-9.79558-9.79557V91.58366a2.57779,2.57779,0,0,1,5.15557,0v11.02305a4.64509,4.64509,0,0,0,4.64,4.64A2.57759,2.57759,0,0,1,97.24234,109.8245ZM112.19348,93.223a2.57759,2.57759,0,0,0-2.57778,2.57779,4.64,4.64,0,1,1-9.28,0V73.73554a23.2,23.2,0,1,0-46.40009,0V95.80076a4.64,4.64,0,1,1-9.28,0,2.57779,2.57779,0,1,0-5.15557,0,9.79558,9.79558,0,0,0,19.59115,0V73.73554a18.04449,18.04449,0,0,1,36.089,0V95.80076a9.79558,9.79558,0,0,0,19.59115,0A2.57759,2.57759,0,0,0,112.19348,93.223ZM77.13563,91.78a2.57759,2.57759,0,0,0-2.57778,2.57778v17.52893a2.57779,2.57779,0,0,0,5.15557,0V94.3578A2.57759,2.57759,0,0,0,77.13563,91.78ZM66.8245,89.00588a2.57759,2.57759,0,0,0-2.57778,2.57778v11.02305a4.64509,4.64509,0,0,1-4.64,4.64,2.57778,2.57778,0,1,0,0,5.15556,9.80671,9.80671,0,0,0,9.79557-9.79557V91.58366A2.57759,2.57759,0,0,0,66.8245,89.00588ZM69.918,70.12639a3.6089,3.6089,0,1,0,3.6089,3.6089A3.60891,3.60891,0,0,0,69.918,70.12639Zm18.04448,3.6089a3.6089,3.6089,0,1,0-3.60889,3.60889A3.60891,3.60891,0,0,0,87.96251,73.73529Z" fill="#3730a3"></path></g></svg>
Side by Side

After

Width:  |  Height:  |  Size: 1.6 KiB

packages/components/nodes/documentloaders/Text/Text.ts
+3 -2
View File
@@ -19,7 +19,7 @@ class Text_DocumentLoaders implements INode {
constructor() {
this.label = 'Text File'
this.name = 'textFile'
this.version = 2.0
this.version = 3.0
this.type = 'Document'
this.icon = 'textFile.svg'
this.category = 'Document Loaders'
@@ -30,7 +30,8 @@ class Text_DocumentLoaders implements INode {
label: 'Txt File',
name: 'txtFile',
type: 'file',
fileType: '.txt'
fileType:
'.txt, .html, .aspx, .asp, .cpp, .c, .cs, .css, .go, .h, .java, .js, .less, .ts, .php, .proto, .python, .py, .rst, .ruby, .rb, .rs, .scala, .sc, .scss, .sol, .sql, .swift, .markdown, .md, .tex, .ltx, .vb, .xml'
},
{
label: 'Text Splitter',
packages/components/nodes/documentloaders/VectorStoreToDocument/VectorStoreToDocument.ts
+11 -2
View File
@@ -17,7 +17,7 @@ class VectorStoreToDocument_DocumentLoaders implements INode {
constructor() {
this.label = 'VectorStore To Document'
this.name = 'vectorStoreToDocument'
this.version = 1.0
this.version = 2.0
this.type = 'Document'
this.icon = 'vectorretriever.svg'
this.category = 'Document Loaders'
@@ -29,6 +29,14 @@ class VectorStoreToDocument_DocumentLoaders implements INode {
name: 'vectorStore',
type: 'VectorStore'
},
{
label: 'Query',
name: 'query',
type: 'string',
description: 'Query to retrieve documents from vector database. If not specified, user question will be used',
optional: true,
acceptVariable: true
},
{
label: 'Minimum Score (%)',
name: 'minScore',
@@ -56,11 +64,12 @@ class VectorStoreToDocument_DocumentLoaders implements INode {
async init(nodeData: INodeData, input: string): Promise<any> {
const vectorStore = nodeData.inputs?.vectorStore as VectorStore
const minScore = nodeData.inputs?.minScore as number
const query = nodeData.inputs?.query as string
const output = nodeData.outputs?.output as string
const topK = (vectorStore as any)?.k ?? 4
const docs = await vectorStore.similaritySearchWithScore(input, topK)
const docs = await vectorStore.similaritySearchWithScore(query ?? input, topK)
// eslint-disable-next-line no-console
console.log('\x1b[94m\x1b[1m\n*****VectorStore Documents*****\n\x1b[0m\x1b[0m')
// eslint-disable-next-line no-console
packages/components/nodes/embeddings/OpenAIEmbeddingCustom/OpenAIEmbeddingCustom.ts
+94
View File
@@ -0,0 +1,94 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { OpenAIEmbeddings, OpenAIEmbeddingsParams } from 'langchain/embeddings/openai'
class OpenAIEmbeddingCustom_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 Custom'
this.name = 'openAIEmbeddingsCustom'
this.version = 1.0
this.type = 'OpenAIEmbeddingsCustom'
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: 'Strip New Lines',
name: 'stripNewLines',
type: 'boolean',
optional: true,
additionalParams: true
},
{
label: 'Batch Size',
name: 'batchSize',
type: 'number',
optional: true,
additionalParams: true
},
{
label: 'Timeout',
name: 'timeout',
type: 'number',
optional: true,
additionalParams: true
},
{
label: 'BasePath',
name: 'basepath',
type: 'string',
optional: true,
additionalParams: true
},
{
label: 'Model Name',
name: 'modelName',
type: 'string',
optional: true
}
]
}
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 modelName = nodeData.inputs?.modelName as string
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, nodeData)
const obj: Partial<OpenAIEmbeddingsParams> & { openAIApiKey?: string } = {
openAIApiKey
}
if (stripNewLines) obj.stripNewLines = stripNewLines
if (batchSize) obj.batchSize = parseInt(batchSize, 10)
if (timeout) obj.timeout = parseInt(timeout, 10)
if (modelName) obj.modelName = modelName
const model = new OpenAIEmbeddings(obj, { basePath })
return model
}
}
module.exports = { nodeClass: OpenAIEmbeddingCustom_Embeddings }
packages/components/nodes/embeddings/OpenAIEmbeddingCustom/openai.png
BIN
View File
Binary file not shown.
Side by Side

After

Width:  |  Height:  |  Size: 3.9 KiB

packages/components/nodes/memory/BufferWindowMemory/BufferWindowMemory.ts
+2 -2
View File
@@ -20,7 +20,7 @@ class BufferWindowMemory_Memory implements INode {
this.type = 'BufferWindowMemory'
this.icon = 'memory.svg'
this.category = 'Memory'
this.description = 'Uses a window of size k to surface the last k back-and-forths to use as memory'
this.description = 'Uses a window of size k to surface the last k back-and-forth to use as memory'
this.baseClasses = [this.type, ...getBaseClasses(BufferWindowMemory)]
this.inputs = [
{
@@ -40,7 +40,7 @@ class BufferWindowMemory_Memory implements INode {
name: 'k',
type: 'number',
default: '4',
description: 'Window of size k to surface the last k back-and-forths to use as memory.'
description: 'Window of size k to surface the last k back-and-forth to use as memory.'
}
]
}
packages/components/nodes/memory/RedisBackedChatMemory/RedisBackedChatMemory.ts
+4 -5
View File
@@ -119,27 +119,26 @@ const initalizeRedis = async (nodeData: INodeData, options: ICommonObject): Prom
const redisChatMessageHistory = new RedisChatMessageHistory(obj)
redisChatMessageHistory.getMessages = async (): Promise<BaseMessage[]> => {
const rawStoredMessages = await client.lrange(sessionId ? sessionId : chatId, 0, -1)
const rawStoredMessages = await client.lrange((redisChatMessageHistory as any).sessionId, 0, -1)
const orderedMessages = rawStoredMessages.reverse().map((message) => JSON.parse(message))
return orderedMessages.map(mapStoredMessageToChatMessage)
}
redisChatMessageHistory.addMessage = async (message: BaseMessage): Promise<void> => {
const messageToAdd = [message].map((msg) => msg.toDict())
await client.lpush(sessionId ? sessionId : chatId, JSON.stringify(messageToAdd[0]))
await client.lpush((redisChatMessageHistory as any).sessionId, JSON.stringify(messageToAdd[0]))
if (sessionTTL) {
await client.expire(sessionId ? sessionId : chatId, sessionTTL)
await client.expire((redisChatMessageHistory as any).sessionId, sessionTTL)
}
}
redisChatMessageHistory.clear = async (): Promise<void> => {
await client.del(sessionId ? sessionId : chatId)
await client.del((redisChatMessageHistory as any).sessionId)
}
const memory = new BufferMemoryExtended({
memoryKey,
chatHistory: redisChatMessageHistory,
returnMessages: true,
isSessionIdUsingChatMessageId
})
return memory
packages/components/nodes/memory/ZepMemory/ZepMemory.ts
+1 -1
View File
@@ -60,7 +60,7 @@ class ZepMemory_Memory implements INode {
name: 'k',
type: 'number',
default: '10',
description: 'Window of size k to surface the last k back-and-forths to use as memory.'
description: 'Window of size k to surface the last k back-and-forth to use as memory.'
},
{
label: 'Auto Summary Template',
packages/components/nodes/prompts/FewShotPromptTemplate/FewShotPromptTemplate.ts
+1 -1
View File
@@ -55,7 +55,7 @@ class FewShotPromptTemplate_Prompts implements INode {
placeholder: `Word: {input}\nAntonym:`
},
{
label: 'Example Seperator',
label: 'Example Separator',
name: 'exampleSeparator',
type: 'string',
placeholder: `\n\n`
packages/components/nodes/textsplitters/CharacterTextSplitter/CharacterTextSplitter.ts
+1 -1
View File
@@ -41,7 +41,7 @@ class CharacterTextSplitter_TextSplitters implements INode {
name: 'separator',
type: 'string',
placeholder: `" "`,
description: 'Seperator to determine when to split the text, will override the default separator',
description: 'Separator to determine when to split the text, will override the default separator',
optional: true
}
]
packages/components/nodes/textsplitters/RecursiveCharacterTextSplitter/RecursiveCharacterTextSplitter.ts
+2 -1
View File
@@ -41,8 +41,9 @@ class RecursiveCharacterTextSplitter_TextSplitters implements INode {
name: 'separators',
type: 'string',
rows: 4,
description: 'Array of custom seperators to determine when to split the text, will override the default separators',
description: 'Array of custom separators to determine when to split the text, will override the default separators',
placeholder: `["|", "##", ">", "-"]`,
additionalParams: true,
optional: true
}
]
packages/components/nodes/tools/SearchApi/SearchAPI.ts
+42
View File
@@ -0,0 +1,42 @@
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 }
packages/components/nodes/tools/SearchApi/searchapi.svg
+1
View File
@@ -0,0 +1 @@
<svg id="SvgjsSvg1001" width="75.27131652832031" height="63.92396926879883" xmlns="http://www.w3.org/2000/svg" version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svgjs="http://svgjs.com/svgjs" viewBox="0 0 75.27131652832031 63.92396926879883"><defs id="SvgjsDefs1002"></defs><rect id="SvgjsRect1008" width="75.27131652832031" height="63.92396926879883" fill="transparent"></rect><g id="SvgjsG1009" transform="matrix(1,0,0,1,-39.50003433227539,-50.53549575805664)"><title>0479_octopus_verti</title><path id="color_1" d="M97.24234,109.8245a2.57759,2.57759,0,0,1-2.57778,2.57778,9.80672,9.80672,0,0,1-9.79558-9.79557V91.58366a2.57779,2.57779,0,0,1,5.15557,0v11.02305a4.64509,4.64509,0,0,0,4.64,4.64A2.57759,2.57759,0,0,1,97.24234,109.8245ZM112.19348,93.223a2.57759,2.57759,0,0,0-2.57778,2.57779,4.64,4.64,0,1,1-9.28,0V73.73554a23.2,23.2,0,1,0-46.40009,0V95.80076a4.64,4.64,0,1,1-9.28,0,2.57779,2.57779,0,1,0-5.15557,0,9.79558,9.79558,0,0,0,19.59115,0V73.73554a18.04449,18.04449,0,0,1,36.089,0V95.80076a9.79558,9.79558,0,0,0,19.59115,0A2.57759,2.57759,0,0,0,112.19348,93.223ZM77.13563,91.78a2.57759,2.57759,0,0,0-2.57778,2.57778v17.52893a2.57779,2.57779,0,0,0,5.15557,0V94.3578A2.57759,2.57759,0,0,0,77.13563,91.78ZM66.8245,89.00588a2.57759,2.57759,0,0,0-2.57778,2.57778v11.02305a4.64509,4.64509,0,0,1-4.64,4.64,2.57778,2.57778,0,1,0,0,5.15556,9.80671,9.80671,0,0,0,9.79557-9.79557V91.58366A2.57759,2.57759,0,0,0,66.8245,89.00588ZM69.918,70.12639a3.6089,3.6089,0,1,0,3.6089,3.6089A3.60891,3.60891,0,0,0,69.918,70.12639Zm18.04448,3.6089a3.6089,3.6089,0,1,0-3.60889,3.60889A3.60891,3.60891,0,0,0,87.96251,73.73529Z" fill="#3730a3"></path></g></svg>
Side by Side

After

Width:  |  Height:  |  Size: 1.6 KiB

packages/components/nodes/vectorstores/Chroma/Chroma_Upsert.ts
+3 -1
View File
@@ -98,7 +98,9 @@ class ChromaUpsert_VectorStores implements INode {
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
finalDocs.push(new Document(flattenDocs[i]))
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
}
}
const obj: {
packages/components/nodes/vectorstores/Elasticsearch/Elasticsearch_Upsert.ts
+3 -1
View File
@@ -38,7 +38,9 @@ class ElasicsearchUpsert_VectorStores extends ElasticSearchBase implements INode
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
finalDocs.push(new Document(flattenDocs[i]))
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
}
}
// The following code is a workaround for a bug (Langchain Issue #1589) in the underlying library.
packages/components/nodes/vectorstores/Faiss_Upsert/Faiss_Upsert.ts
+3 -1
View File
@@ -80,7 +80,9 @@ class FaissUpsert_VectorStores implements INode {
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
finalDocs.push(new Document(flattenDocs[i]))
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
}
}
const vectorStore = await FaissStore.fromDocuments(finalDocs, embeddings)
packages/components/nodes/vectorstores/InMemory/InMemoryVectorStore.ts
+3 -1
View File
@@ -71,7 +71,9 @@ class InMemoryVectorStore_VectorStores implements INode {
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
finalDocs.push(new Document(flattenDocs[i]))
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
}
}
const vectorStore = await MemoryVectorStore.fromDocuments(finalDocs, embeddings)
packages/components/nodes/vectorstores/Milvus/Milvus_Upsert.ts
+4 -2
View File
@@ -110,7 +110,9 @@ class Milvus_Upsert_VectorStores implements INode {
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
finalDocs.push(new Document(flattenDocs[i]))
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
}
}
const vectorStore = await MilvusUpsert.fromDocuments(finalDocs, embeddings, milVusArgs)
@@ -252,7 +254,7 @@ class MilvusUpsert extends Milvus {
collection_name: this.collectionName
})
if (descIndexResp.status.error_code === ErrorCode.INDEX_NOT_EXIST) {
if (descIndexResp.status.error_code === ErrorCode.IndexNotExist) {
const resp = await this.client.createIndex({
collection_name: this.collectionName,
field_name: this.vectorField,
packages/components/nodes/vectorstores/OpenSearch_Upsert/OpenSearch_Upsert.ts
+3 -1
View File
@@ -86,7 +86,9 @@ class OpenSearchUpsert_VectorStores implements INode {
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
finalDocs.push(new Document(flattenDocs[i]))
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
}
}
const client = new Client({
packages/components/nodes/vectorstores/Pinecone/Pinecone_Upsert.ts
+3 -1
View File
@@ -106,7 +106,9 @@ class PineconeUpsert_VectorStores implements INode {
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
finalDocs.push(new Document(flattenDocs[i]))
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
}
}
const obj: PineconeLibArgs = {
packages/components/nodes/vectorstores/Postgres_Upsert/Postgres_Upsert.ts
+3 -1
View File
@@ -143,7 +143,9 @@ class PostgresUpsert_VectorStores implements INode {
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
finalDocs.push(new Document(flattenDocs[i]))
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
}
}
const vectorStore = await TypeORMVectorStore.fromDocuments(finalDocs, embeddings, args)
packages/components/nodes/vectorstores/Qdrant_Upsert/Qdrant_Upsert.ts
+3 -1
View File
@@ -147,7 +147,9 @@ class QdrantUpsert_VectorStores implements INode {
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
finalDocs.push(new Document(flattenDocs[i]))
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
}
}
const dbConfig: QdrantLibArgs = {
packages/components/nodes/vectorstores/Redis/Redis_Upsert.ts
+5 -3
View File
@@ -49,9 +49,11 @@ class RedisUpsert_VectorStores extends RedisSearchBase implements INode {
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
const document = new Document(flattenDocs[i])
escapeAllStrings(document.metadata)
finalDocs.push(document)
if (flattenDocs[i] && flattenDocs[i].pageContent) {
const document = new Document(flattenDocs[i])
escapeAllStrings(document.metadata)
finalDocs.push(document)
}
}
return super.init(nodeData, _, options, flattenDocs)
packages/components/nodes/vectorstores/Singlestore_Upsert/Singlestore_Upsert.ts
+3 -1
View File
@@ -140,7 +140,9 @@ class SingleStoreUpsert_VectorStores implements INode {
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
finalDocs.push(new Document(flattenDocs[i]))
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
}
}
let vectorStore: SingleStoreVectorStore
packages/components/nodes/vectorstores/Vectara/Vectara_Upsert.ts
+3 -1
View File
@@ -132,7 +132,9 @@ class VectaraUpsert_VectorStores implements INode {
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
finalDocs.push(new Document(flattenDocs[i]))
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
}
}
const vectorStore = await VectaraStore.fromDocuments(finalDocs, embeddings, vectaraArgs)
packages/components/nodes/vectorstores/Weaviate_Upsert/Weaviate_Upsert.ts
+3 -1
View File
@@ -143,7 +143,9 @@ class WeaviateUpsert_VectorStores implements INode {
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
finalDocs.push(new Document(flattenDocs[i]))
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
}
}
const obj: WeaviateLibArgs = {
packages/components/nodes/vectorstores/Zep/Zep_Upsert.ts
+3 -1
View File
@@ -106,7 +106,9 @@ class Zep_Upsert_VectorStores implements INode {
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
finalDocs.push(new Document(flattenDocs[i]))
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
}
}
const zepConfig: IZepConfig = {
packages/components/src/utils.ts
+2 -2
View File
@@ -301,7 +301,7 @@ async function crawl(baseURL: string, currentURL: string, pages: string[], limit
}
/**
* Prep URL before passing into recursive carwl function
* Prep URL before passing into recursive crawl function
* @param {string} stringURL
* @param {number} limit
* @returns {Promise<string[]>}
@@ -445,7 +445,7 @@ export const getCredentialData = async (selectedCredentialId: string, options: I
if (!credential) return {}
// Decrpyt credentialData
// Decrypt credentialData
const decryptedCredentialData = await decryptCredentialData(credential.encryptedData)
return decryptedCredentialData
packages/server/marketplaces/chatflows/Antonym.json
+1 -1
View File
@@ -45,7 +45,7 @@
"id": "fewShotPromptTemplate_1-input-suffix-string"
},
{
"label": "Example Seperator",
"label": "Example Separator",
"name": "exampleSeparator",
"type": "string",
"placeholder": "\n\n",
packages/server/marketplaces/chatflows/Chat with a Podcast.json
+669
View File
@@ -0,0 +1,669 @@
{
"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",
"optional": true,
"additionalParams": true,
"id": "openAIEmbeddings_0-input-stripNewLines-boolean"
},
{
"label": "Batch Size",
"name": "batchSize",
"type": "number",
"optional": true,
"additionalParams": true,
"id": "openAIEmbeddings_0-input-batchSize-number"
},
{
"label": "Timeout",
"name": "timeout",
"type": "number",
"optional": true,
"additionalParams": true,
"id": "openAIEmbeddings_0-input-timeout-number"
},
{
"label": "BasePath",
"name": "basepath",
"type": "string",
"optional": true,
"additionalParams": true,
"id": "openAIEmbeddings_0-input-basepath-string"
}
],
"inputAnchors": [],
"inputs": {
"stripNewLines": "",
"batchSize": "",
"timeout": "",
"basepath": ""
},
"outputAnchors": [
{
"id": "openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings",
"name": "openAIEmbeddings",
"label": "OpenAIEmbeddings",
"type": "OpenAIEmbeddings | Embeddings"
}
],
"outputs": {},
"selected": false
},
"selected": false,
"dragging": false,
"positionAbsolute": {
"x": 666.3950526535211,
"y": 777.4191705193945
}
},
{
"width": 300,
"height": 482,
"id": "searchApi_0",
"position": {
"x": 680.1258121447145,
"y": 144.9905217023999
},
"type": "customNode",
"data": {
"id": "searchApi_0",
"label": "SearchApi",
"version": 1,
"name": "searchApi",
"type": "Document",
"baseClasses": ["Document"],
"category": "Document Loaders",
"description": "Load data from real-time search results",
"inputParams": [
{
"label": "Connect Credential",
"name": "credential",
"type": "credential",
"optional": false,
"credentialNames": ["searchApi"],
"id": "searchApi_0-input-credential-credential"
},
{
"label": "Query",
"name": "query",
"type": "string",
"optional": true,
"id": "searchApi_0-input-query-string"
},
{
"label": "Custom Parameters",
"name": "customParameters",
"type": "json",
"optional": true,
"additionalParams": true,
"id": "searchApi_0-input-customParameters-json"
},
{
"label": "Metadata",
"name": "metadata",
"type": "json",
"optional": true,
"additionalParams": true,
"id": "searchApi_0-input-metadata-json"
}
],
"inputAnchors": [
{
"label": "Text Splitter",
"name": "textSplitter",
"type": "TextSplitter",
"optional": true,
"id": "searchApi_0-input-textSplitter-TextSplitter"
}
],
"inputs": {
"query": "",
"customParameters": "{\"engine\":\"youtube_transcripts\",\"video_id\":\"0e3GPea1Tyg\"}",
"textSplitter": "{{characterTextSplitter_0.data.instance}}",
"metadata": ""
},
"outputAnchors": [
{
"id": "searchApi_0-output-searchApi-Document",
"name": "searchApi",
"label": "Document",
"type": "Document"
}
],
"outputs": {},
"selected": false
},
"selected": false,
"positionAbsolute": {
"x": 680.1258121447145,
"y": 144.9905217023999
},
"dragging": false
}
],
"edges": [
{
"source": "memoryVectorStore_0",
"sourceHandle": "memoryVectorStore_0-output-retriever-Memory|VectorStoreRetriever|BaseRetriever",
"target": "conversationalRetrievalQAChain_0",
"targetHandle": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
"type": "buttonedge",
"id": "memoryVectorStore_0-memoryVectorStore_0-output-retriever-Memory|VectorStoreRetriever|BaseRetriever-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
"data": {
"label": ""
}
},
{
"source": "chatOpenAI_0",
"sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable",
"target": "conversationalRetrievalQAChain_0",
"targetHandle": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel",
"type": "buttonedge",
"id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-model-BaseLanguageModel",
"data": {
"label": ""
}
},
{
"source": "openAIEmbeddings_0",
"sourceHandle": "openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings",
"target": "memoryVectorStore_0",
"targetHandle": "memoryVectorStore_0-input-embeddings-Embeddings",
"type": "buttonedge",
"id": "openAIEmbeddings_0-openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings-memoryVectorStore_0-memoryVectorStore_0-input-embeddings-Embeddings",
"data": {
"label": ""
}
},
{
"source": "characterTextSplitter_0",
"sourceHandle": "characterTextSplitter_0-output-characterTextSplitter-CharacterTextSplitter|TextSplitter|BaseDocumentTransformer|Runnable",
"target": "searchApi_0",
"targetHandle": "searchApi_0-input-textSplitter-TextSplitter",
"type": "buttonedge",
"id": "characterTextSplitter_0-characterTextSplitter_0-output-characterTextSplitter-CharacterTextSplitter|TextSplitter|BaseDocumentTransformer|Runnable-searchApi_0-searchApi_0-input-textSplitter-TextSplitter",
"data": {
"label": ""
}
},
{
"source": "searchApi_0",
"sourceHandle": "searchApi_0-output-searchApi-Document",
"target": "memoryVectorStore_0",
"targetHandle": "memoryVectorStore_0-input-document-Document",
"type": "buttonedge",
"id": "searchApi_0-searchApi_0-output-searchApi-Document-memoryVectorStore_0-memoryVectorStore_0-input-document-Document",
"data": {
"label": ""
}
}
]
}
packages/server/marketplaces/chatflows/Conversational Retrieval QA Chain.json
+14 -3
View File
@@ -368,7 +368,7 @@
"id": "recursiveCharacterTextSplitter_0",
"label": "Recursive Character Text Splitter",
"name": "recursiveCharacterTextSplitter",
"version": 1,
"version": 2,
"type": "RecursiveCharacterTextSplitter",
"baseClasses": ["RecursiveCharacterTextSplitter", "TextSplitter"],
"category": "Text Splitters",
@@ -388,6 +388,17 @@
"type": "number",
"optional": true,
"id": "recursiveCharacterTextSplitter_0-input-chunkOverlap-number"
},
{
"label": "Custom Separators",
"name": "separators",
"type": "string",
"rows": 4,
"description": "Array of custom separators to determine when to split the text, will override the default separators",
"placeholder": "[\"|\", \"##\", \">\", \"-\"]",
"additionalParams": true,
"optional": true,
"id": "recursiveCharacterTextSplitter_0-input-separators-string"
}
],
"inputAnchors": [],
@@ -426,7 +437,7 @@
"id": "textFile_0",
"label": "Text File",
"name": "textFile",
"version": 2,
"version": 3,
"type": "Document",
"baseClasses": ["Document"],
"category": "Document Loaders",
@@ -436,7 +447,7 @@
"label": "Txt File",
"name": "txtFile",
"type": "file",
"fileType": ".txt",
"fileType": ".txt, .html, .aspx, .asp, .cpp, .c, .cs, .css, .go, .h, .java, .js, .less, .ts, .php, .proto, .python, .py, .rst, .ruby, .rb, .rs, .scala, .sc, .scss, .sol, .sql, .swift, .markdown, .md, .tex, .ltx, .vb, .xml",
"id": "textFile_0-input-txtFile-file"
},
{
packages/server/marketplaces/chatflows/Local QnA.json
+14 -3
View File
@@ -14,7 +14,7 @@
"id": "recursiveCharacterTextSplitter_1",
"label": "Recursive Character Text Splitter",
"name": "recursiveCharacterTextSplitter",
"version": 1,
"version": 2,
"type": "RecursiveCharacterTextSplitter",
"baseClasses": ["RecursiveCharacterTextSplitter", "TextSplitter"],
"category": "Text Splitters",
@@ -34,6 +34,17 @@
"type": "number",
"optional": true,
"id": "recursiveCharacterTextSplitter_1-input-chunkOverlap-number"
},
{
"label": "Custom Separators",
"name": "separators",
"type": "string",
"rows": 4,
"description": "Array of custom separators to determine when to split the text, will override the default separators",
"placeholder": "[\"|\", \"##\", \">\", \"-\"]",
"additionalParams": true,
"optional": true,
"id": "recursiveCharacterTextSplitter_1-input-separators-string"
}
],
"inputAnchors": [],
@@ -373,7 +384,7 @@
"id": "textFile_0",
"label": "Text File",
"name": "textFile",
"version": 1,
"version": 3,
"type": "Document",
"baseClasses": ["Document"],
"category": "Document Loaders",
@@ -383,7 +394,7 @@
"label": "Txt File",
"name": "txtFile",
"type": "file",
"fileType": ".txt",
"fileType": ".txt, .html, .aspx, .asp, .cpp, .c, .cs, .css, .go, .h, .java, .js, .less, .ts, .php, .proto, .python, .py, .rst, .ruby, .rb, .rs, .scala, .sc, .scss, .sol, .sql, .swift, .markdown, .md, .tex, .ltx, .vb, .xml",
"id": "textFile_0-input-txtFile-file"
},
{
packages/server/marketplaces/chatflows/Metadata Filter Upsert.json
+14 -3
View File
@@ -14,7 +14,7 @@
"id": "recursiveCharacterTextSplitter_1",
"label": "Recursive Character Text Splitter",
"name": "recursiveCharacterTextSplitter",
"version": 1,
"version": 2,
"type": "RecursiveCharacterTextSplitter",
"baseClasses": ["RecursiveCharacterTextSplitter", "TextSplitter"],
"category": "Text Splitters",
@@ -34,6 +34,17 @@
"type": "number",
"optional": true,
"id": "recursiveCharacterTextSplitter_1-input-chunkOverlap-number"
},
{
"label": "Custom Separators",
"name": "separators",
"type": "string",
"rows": 4,
"description": "Array of custom separators to determine when to split the text, will override the default separators",
"placeholder": "[\"|\", \"##\", \">\", \"-\"]",
"additionalParams": true,
"optional": true,
"id": "recursiveCharacterTextSplitter_1-input-separators-string"
}
],
"inputAnchors": [],
@@ -72,7 +83,7 @@
"id": "textFile_0",
"label": "Text File",
"name": "textFile",
"version": 1,
"version": 3,
"type": "Document",
"baseClasses": ["Document"],
"category": "Document Loaders",
@@ -82,7 +93,7 @@
"label": "Txt File",
"name": "txtFile",
"type": "file",
"fileType": ".txt",
"fileType": ".txt, .html, .aspx, .asp, .cpp, .c, .cs, .css, .go, .h, .java, .js, .less, .ts, .php, .proto, .python, .py, .rst, .ruby, .rb, .rs, .scala, .sc, .scss, .sol, .sql, .swift, .markdown, .md, .tex, .ltx, .vb, .xml",
"id": "textFile_0-input-txtFile-file"
},
{
packages/server/marketplaces/chatflows/Prompt Chaining with VectorStore.json
+243 -224
View File
@@ -3,120 +3,11 @@
"nodes": [
{
"width": 300,
"height": 503,
"id": "pineconeExistingIndex_0",
"position": {
"x": 1062.7418678410986,
"y": -109.27680365777141
},
"type": "customNode",
"data": {
"id": "pineconeExistingIndex_0",
"label": "Pinecone Load Existing Index",
"version": 1,
"name": "pineconeExistingIndex",
"type": "Pinecone",
"baseClasses": ["Pinecone", "VectorStoreRetriever", "BaseRetriever"],
"category": "Vector Stores",
"description": "Load existing index from Pinecone (i.e: Document has been upserted)",
"inputParams": [
{
"label": "Connect Credential",
"name": "credential",
"type": "credential",
"credentialNames": ["pineconeApi"],
"id": "pineconeExistingIndex_0-input-credential-credential"
},
{
"label": "Pinecone Index",
"name": "pineconeIndex",
"type": "string",
"id": "pineconeExistingIndex_0-input-pineconeIndex-string"
},
{
"label": "Pinecone Namespace",
"name": "pineconeNamespace",
"type": "string",
"placeholder": "my-first-namespace",
"additionalParams": true,
"optional": true,
"id": "pineconeExistingIndex_0-input-pineconeNamespace-string"
},
{
"label": "Pinecone Metadata Filter",
"name": "pineconeMetadataFilter",
"type": "json",
"optional": true,
"additionalParams": true,
"id": "pineconeExistingIndex_0-input-pineconeMetadataFilter-json"
},
{
"label": "Top K",
"name": "topK",
"description": "Number of top results to fetch. Default to 4",
"placeholder": "4",
"type": "number",
"additionalParams": true,
"optional": true,
"id": "pineconeExistingIndex_0-input-topK-number"
}
],
"inputAnchors": [
{
"label": "Embeddings",
"name": "embeddings",
"type": "Embeddings",
"id": "pineconeExistingIndex_0-input-embeddings-Embeddings"
}
],
"inputs": {
"embeddings": "{{openAIEmbeddings_0.data.instance}}",
"pineconeIndex": "newindex",
"pineconeNamespace": "",
"pineconeMetadataFilter": "{}",
"topK": ""
},
"outputAnchors": [
{
"name": "output",
"label": "Output",
"type": "options",
"options": [
{
"id": "pineconeExistingIndex_0-output-retriever-Pinecone|VectorStoreRetriever|BaseRetriever",
"name": "retriever",
"label": "Pinecone Retriever",
"type": "Pinecone | VectorStoreRetriever | BaseRetriever"
},
{
"id": "pineconeExistingIndex_0-output-vectorStore-Pinecone|VectorStore",
"name": "vectorStore",
"label": "Pinecone Vector Store",
"type": "Pinecone | VectorStore"
}
],
"default": "retriever"
}
],
"outputs": {
"output": "vectorStore"
},
"selected": false
},
"selected": false,
"positionAbsolute": {
"x": 1062.7418678410986,
"y": -109.27680365777141
},
"dragging": false
},
{
"width": 300,
"height": 327,
"height": 329,
"id": "openAIEmbeddings_0",
"position": {
"x": 711.3971966563331,
"y": 7.7184225021727
"x": 1198.6643452533754,
"y": -584.4233173804803
},
"type": "customNode",
"data": {
@@ -189,18 +80,18 @@
},
"selected": false,
"positionAbsolute": {
"x": 711.3971966563331,
"y": 7.7184225021727
"x": 1198.6643452533754,
"y": -584.4233173804803
},
"dragging": false
},
{
"width": 300,
"height": 473,
"height": 475,
"id": "promptTemplate_0",
"position": {
"x": 348.2881107399286,
"y": -97.74510214137423
"x": 354.2706973608643,
"y": -122.34815000085804
},
"type": "customNode",
"data": {
@@ -249,18 +140,18 @@
},
"selected": false,
"positionAbsolute": {
"x": 348.2881107399286,
"y": -97.74510214137423
"x": 354.2706973608643,
"y": -122.34815000085804
},
"dragging": false
},
{
"width": 300,
"height": 522,
"height": 574,
"id": "chatOpenAI_0",
"position": {
"x": 335.7621848973805,
"y": -721.7411273245009
"x": 353.5672832154869,
"y": -730.6436764835541
},
"type": "customNode",
"data": {
@@ -396,7 +287,7 @@
],
"inputs": {
"modelName": "gpt-3.5-turbo-16k",
"temperature": 0.9,
"temperature": "0",
"maxTokens": "",
"topP": "",
"frequencyPenalty": "",
@@ -418,17 +309,17 @@
"selected": false,
"dragging": false,
"positionAbsolute": {
"x": 335.7621848973805,
"y": -721.7411273245009
"x": 353.5672832154869,
"y": -730.6436764835541
}
},
{
"width": 300,
"height": 522,
"height": 574,
"id": "chatOpenAI_1",
"position": {
"x": 1765.2801848172305,
"y": -737.9261054149061
"x": 2281.9246645710673,
"y": -778.8379360672121
},
"type": "customNode",
"data": {
@@ -564,7 +455,7 @@
],
"inputs": {
"modelName": "gpt-3.5-turbo-16k",
"temperature": 0.9,
"temperature": "0",
"maxTokens": "",
"topP": "",
"frequencyPenalty": "",
@@ -586,36 +477,153 @@
"selected": false,
"dragging": false,
"positionAbsolute": {
"x": 1765.2801848172305,
"y": -737.9261054149061
"x": 2281.9246645710673,
"y": -778.8379360672121
}
},
{
"width": 300,
"height": 473,
"id": "promptTemplate_1",
"height": 505,
"id": "pineconeExistingIndex_0",
"position": {
"x": 1773.720934090435,
"y": -116.71323227575395
"x": 1544.4998097474581,
"y": -628.8477510577202
},
"type": "customNode",
"data": {
"id": "promptTemplate_1",
"label": "Prompt Template",
"id": "pineconeExistingIndex_0",
"label": "Pinecone Load Existing Index",
"version": 1,
"name": "promptTemplate",
"type": "PromptTemplate",
"baseClasses": ["PromptTemplate", "BaseStringPromptTemplate", "BasePromptTemplate", "Runnable"],
"category": "Prompts",
"description": "Schema to represent a basic prompt for an LLM",
"name": "pineconeExistingIndex",
"type": "Pinecone",
"baseClasses": ["Pinecone", "VectorStoreRetriever", "BaseRetriever"],
"category": "Vector Stores",
"description": "Load existing index from Pinecone (i.e: Document has been upserted)",
"inputParams": [
{
"label": "Template",
"name": "template",
"label": "Connect Credential",
"name": "credential",
"type": "credential",
"credentialNames": ["pineconeApi"],
"id": "pineconeExistingIndex_0-input-credential-credential"
},
{
"label": "Pinecone Index",
"name": "pineconeIndex",
"type": "string",
"id": "pineconeExistingIndex_0-input-pineconeIndex-string"
},
{
"label": "Pinecone Namespace",
"name": "pineconeNamespace",
"type": "string",
"placeholder": "my-first-namespace",
"additionalParams": true,
"optional": true,
"id": "pineconeExistingIndex_0-input-pineconeNamespace-string"
},
{
"label": "Pinecone Metadata Filter",
"name": "pineconeMetadataFilter",
"type": "json",
"optional": true,
"additionalParams": true,
"id": "pineconeExistingIndex_0-input-pineconeMetadataFilter-json"
},
{
"label": "Top K",
"name": "topK",
"description": "Number of top results to fetch. Default to 4",
"placeholder": "4",
"type": "number",
"additionalParams": true,
"optional": true,
"id": "pineconeExistingIndex_0-input-topK-number"
}
],
"inputAnchors": [
{
"label": "Embeddings",
"name": "embeddings",
"type": "Embeddings",
"id": "pineconeExistingIndex_0-input-embeddings-Embeddings"
}
],
"inputs": {
"embeddings": "{{openAIEmbeddings_0.data.instance}}",
"pineconeIndex": "",
"pineconeNamespace": "",
"pineconeMetadataFilter": "",
"topK": ""
},
"outputAnchors": [
{
"name": "output",
"label": "Output",
"type": "options",
"options": [
{
"id": "pineconeExistingIndex_0-output-retriever-Pinecone|VectorStoreRetriever|BaseRetriever",
"name": "retriever",
"label": "Pinecone Retriever",
"type": "Pinecone | VectorStoreRetriever | BaseRetriever"
},
{
"id": "pineconeExistingIndex_0-output-vectorStore-Pinecone|VectorStore",
"name": "vectorStore",
"label": "Pinecone Vector Store",
"type": "Pinecone | VectorStore"
}
],
"default": "retriever"
}
],
"outputs": {
"output": "vectorStore"
},
"selected": false
},
"selected": false,
"positionAbsolute": {
"x": 1544.4998097474581,
"y": -628.8477510577202
},
"dragging": false
},
{
"width": 300,
"height": 652,
"id": "chatPromptTemplate_0",
"position": {
"x": 2290.8365353040026,
"y": -168.49082887954518
},
"type": "customNode",
"data": {
"id": "chatPromptTemplate_0",
"label": "Chat Prompt Template",
"version": 1,
"name": "chatPromptTemplate",
"type": "ChatPromptTemplate",
"baseClasses": ["ChatPromptTemplate", "BaseChatPromptTemplate", "BasePromptTemplate", "Runnable"],
"category": "Prompts",
"description": "Schema to represent a chat prompt",
"inputParams": [
{
"label": "System Message",
"name": "systemMessagePrompt",
"type": "string",
"rows": 4,
"placeholder": "What is a good name for a company that makes {product}?",
"id": "promptTemplate_1-input-template-string"
"placeholder": "You are a helpful assistant that translates {input_language} to {output_language}.",
"id": "chatPromptTemplate_0-input-systemMessagePrompt-string"
},
{
"label": "Human Message",
"name": "humanMessagePrompt",
"type": "string",
"rows": 4,
"placeholder": "{text}",
"id": "chatPromptTemplate_0-input-humanMessagePrompt-string"
},
{
"label": "Format Prompt Values",
@@ -624,20 +632,21 @@
"optional": true,
"acceptVariable": true,
"list": true,
"id": "promptTemplate_1-input-promptValues-json"
"id": "chatPromptTemplate_0-input-promptValues-json"
}
],
"inputAnchors": [],
"inputs": {
"template": "Use the following pieces of context to answer the question at the end.\n\n{context}\n\nQuestion: {question}\nHelpful Answer:",
"promptValues": "{\"context\":\"{{vectorStoreToDocument_0.data.instance}}\",\"question\":\"{{llmChain_0.data.instance}}\"}"
"systemMessagePrompt": "Using the provided context, answer the user's question to the best of your ability using the resources provided. If there is nothing in the context relevant to the question at hand, just say \"Hmm, I'm not sure.\" Don't try to make up an answer.\n\nAnything between the following \\`context\\` html blocks is retrieved from a knowledge bank, not part of the conversation with the user.\n\n<context>\n {context}\n<context/>\n\nREMEMBER: If there is no relevant information within the context, just say \"Hmm, I'm not sure.\" Don't try to make up an answer. Anything between the preceding 'context' html blocks is retrieved from a knowledge bank, not part of the conversation with the user.",
"humanMessagePrompt": "{text}",
"promptValues": "{\"context\":\"{{vectorStoreToDocument_0.data.instance}}\",\"text\":\"{{question}}\"}"
},
"outputAnchors": [
{
"id": "promptTemplate_1-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate|Runnable",
"name": "promptTemplate",
"label": "PromptTemplate",
"type": "PromptTemplate | BaseStringPromptTemplate | BasePromptTemplate | Runnable"
"id": "chatPromptTemplate_0-output-chatPromptTemplate-ChatPromptTemplate|BaseChatPromptTemplate|BasePromptTemplate|Runnable",
"name": "chatPromptTemplate",
"label": "ChatPromptTemplate",
"type": "ChatPromptTemplate | BaseChatPromptTemplate | BasePromptTemplate | Runnable"
}
],
"outputs": {},
@@ -645,18 +654,18 @@
},
"selected": false,
"positionAbsolute": {
"x": 1773.720934090435,
"y": -116.71323227575395
"x": 2290.8365353040026,
"y": -168.49082887954518
},
"dragging": false
},
{
"width": 300,
"height": 404,
"height": 405,
"id": "llmChain_0",
"position": {
"x": 756.1670091985342,
"y": -592.5151355056942
"x": 747.1299875516488,
"y": -267.01184813798244
},
"type": "customNode",
"data": {
@@ -695,7 +704,7 @@
"inputs": {
"model": "{{chatOpenAI_0.data.instance}}",
"prompt": "{{promptTemplate_0.data.instance}}",
"chainName": "QuestionChain"
"chainName": "RephraseQuestion"
},
"outputAnchors": [
{
@@ -726,18 +735,18 @@
},
"selected": false,
"positionAbsolute": {
"x": 756.1670091985342,
"y": -592.5151355056942
"x": 747.1299875516488,
"y": -267.01184813798244
},
"dragging": false
},
{
"width": 300,
"height": 404,
"height": 405,
"id": "llmChain_1",
"position": {
"x": 2200.1274896215496,
"y": -144.29167974642334
"x": 2694.8707655351186,
"y": -308.59150355411236
},
"type": "customNode",
"data": {
@@ -775,8 +784,8 @@
],
"inputs": {
"model": "{{chatOpenAI_1.data.instance}}",
"prompt": "{{promptTemplate_1.data.instance}}",
"chainName": ""
"prompt": "{{chatPromptTemplate_0.data.instance}}",
"chainName": "FinalResponse"
},
"outputAnchors": [
{
@@ -807,30 +816,39 @@
},
"selected": false,
"positionAbsolute": {
"x": 2200.1274896215496,
"y": -144.29167974642334
"x": 2694.8707655351186,
"y": -308.59150355411236
},
"dragging": false
},
{
"width": 300,
"height": 353,
"height": 454,
"id": "vectorStoreToDocument_0",
"position": {
"x": 1407.7038120189868,
"y": -26.16468811205081
"x": 1906.6871314089658,
"y": -157.0046189166955
},
"type": "customNode",
"data": {
"id": "vectorStoreToDocument_0",
"label": "VectorStore To Document",
"version": 1,
"version": 2,
"name": "vectorStoreToDocument",
"type": "Document",
"baseClasses": ["Document"],
"category": "Document Loaders",
"description": "Search documents with scores from vector store",
"inputParams": [
{
"label": "Query",
"name": "query",
"type": "string",
"description": "Query to retrieve documents from vector database. If not specified, user question will be used",
"optional": true,
"acceptVariable": true,
"id": "vectorStoreToDocument_0-input-query-string"
},
{
"label": "Minimum Score (%)",
"name": "minScore",
@@ -852,6 +870,7 @@
],
"inputs": {
"vectorStore": "{{pineconeExistingIndex_0.data.instance}}",
"query": "{{llmChain_0.data.instance}}",
"minScore": ""
},
"outputAnchors": [
@@ -883,8 +902,8 @@
},
"selected": false,
"positionAbsolute": {
"x": 1407.7038120189868,
"y": -26.16468811205081
"x": 1906.6871314089658,
"y": -157.0046189166955
},
"dragging": false
}
@@ -901,6 +920,50 @@
"label": ""
}
},
{
"source": "promptTemplate_0",
"sourceHandle": "promptTemplate_0-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate|Runnable",
"target": "llmChain_0",
"targetHandle": "llmChain_0-input-prompt-BasePromptTemplate",
"type": "buttonedge",
"id": "promptTemplate_0-promptTemplate_0-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate|Runnable-llmChain_0-llmChain_0-input-prompt-BasePromptTemplate",
"data": {
"label": ""
}
},
{
"source": "chatOpenAI_0",
"sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable",
"target": "llmChain_0",
"targetHandle": "llmChain_0-input-model-BaseLanguageModel",
"type": "buttonedge",
"id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable-llmChain_0-llmChain_0-input-model-BaseLanguageModel",
"data": {
"label": ""
}
},
{
"source": "chatPromptTemplate_0",
"sourceHandle": "chatPromptTemplate_0-output-chatPromptTemplate-ChatPromptTemplate|BaseChatPromptTemplate|BasePromptTemplate|Runnable",
"target": "llmChain_1",
"targetHandle": "llmChain_1-input-prompt-BasePromptTemplate",
"type": "buttonedge",
"id": "chatPromptTemplate_0-chatPromptTemplate_0-output-chatPromptTemplate-ChatPromptTemplate|BaseChatPromptTemplate|BasePromptTemplate|Runnable-llmChain_1-llmChain_1-input-prompt-BasePromptTemplate",
"data": {
"label": ""
}
},
{
"source": "chatOpenAI_1",
"sourceHandle": "chatOpenAI_1-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable",
"target": "llmChain_1",
"targetHandle": "llmChain_1-input-model-BaseLanguageModel",
"type": "buttonedge",
"id": "chatOpenAI_1-chatOpenAI_1-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable-llmChain_1-llmChain_1-input-model-BaseLanguageModel",
"data": {
"label": ""
}
},
{
"source": "pineconeExistingIndex_0",
"sourceHandle": "pineconeExistingIndex_0-output-vectorStore-Pinecone|VectorStore",
@@ -915,32 +978,10 @@
{
"source": "vectorStoreToDocument_0",
"sourceHandle": "vectorStoreToDocument_0-output-text-string|json",
"target": "promptTemplate_1",
"targetHandle": "promptTemplate_1-input-promptValues-json",
"target": "chatPromptTemplate_0",
"targetHandle": "chatPromptTemplate_0-input-promptValues-json",
"type": "buttonedge",
"id": "vectorStoreToDocument_0-vectorStoreToDocument_0-output-text-string|json-promptTemplate_1-promptTemplate_1-input-promptValues-json",
"data": {
"label": ""
}
},
{
"source": "chatOpenAI_0",
"sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable",
"target": "llmChain_0",
"targetHandle": "llmChain_0-input-model-BaseLanguageModel",
"type": "buttonedge",
"id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable-llmChain_0-llmChain_0-input-model-BaseLanguageModel",
"data": {
"label": ""
}
},
{
"source": "promptTemplate_0",
"sourceHandle": "promptTemplate_0-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate|Runnable",
"target": "llmChain_0",
"targetHandle": "llmChain_0-input-prompt-BasePromptTemplate",
"type": "buttonedge",
"id": "promptTemplate_0-promptTemplate_0-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate|Runnable-llmChain_0-llmChain_0-input-prompt-BasePromptTemplate",
"id": "vectorStoreToDocument_0-vectorStoreToDocument_0-output-text-string|json-chatPromptTemplate_0-chatPromptTemplate_0-input-promptValues-json",
"data": {
"label": ""
}
@@ -948,32 +989,10 @@
{
"source": "llmChain_0",
"sourceHandle": "llmChain_0-output-outputPrediction-string|json",
"target": "promptTemplate_1",
"targetHandle": "promptTemplate_1-input-promptValues-json",
"target": "vectorStoreToDocument_0",
"targetHandle": "vectorStoreToDocument_0-input-query-string",
"type": "buttonedge",
"id": "llmChain_0-llmChain_0-output-outputPrediction-string|json-promptTemplate_1-promptTemplate_1-input-promptValues-json",
"data": {
"label": ""
}
},
{
"source": "chatOpenAI_1",
"sourceHandle": "chatOpenAI_1-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable",
"target": "llmChain_1",
"targetHandle": "llmChain_1-input-model-BaseLanguageModel",
"type": "buttonedge",
"id": "chatOpenAI_1-chatOpenAI_1-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable-llmChain_1-llmChain_1-input-model-BaseLanguageModel",
"data": {
"label": ""
}
},
{
"source": "promptTemplate_1",
"sourceHandle": "promptTemplate_1-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate|Runnable",
"target": "llmChain_1",
"targetHandle": "llmChain_1-input-prompt-BasePromptTemplate",
"type": "buttonedge",
"id": "promptTemplate_1-promptTemplate_1-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate|Runnable-llmChain_1-llmChain_1-input-prompt-BasePromptTemplate",
"id": "llmChain_0-llmChain_0-output-outputPrediction-string|json-vectorStoreToDocument_0-vectorStoreToDocument_0-input-query-string",
"data": {
"label": ""
}
packages/ui/src/ui-component/input/Input.js
+73 -3
View File
@@ -1,10 +1,39 @@
import { useState } from 'react'
import { useState, useEffect, useRef } from 'react'
import PropTypes from 'prop-types'
import { FormControl, OutlinedInput } from '@mui/material'
import { FormControl, OutlinedInput, Popover } from '@mui/material'
import ExpandTextDialog from 'ui-component/dialog/ExpandTextDialog'
import SelectVariable from 'ui-component/json/SelectVariable'
import { getAvailableNodesForVariable } from 'utils/genericHelper'
export const Input = ({ inputParam, value, onChange, disabled = false, showDialog, dialogProps, onDialogCancel, onDialogConfirm }) => {
export const Input = ({
inputParam,
value,
nodes,
edges,
nodeId,
onChange,
disabled = false,
showDialog,
dialogProps,
onDialogCancel,
onDialogConfirm
}) => {
const [myValue, setMyValue] = useState(value ?? '')
const [anchorEl, setAnchorEl] = useState(null)
const [availableNodesForVariable, setAvailableNodesForVariable] = useState([])
const ref = useRef(null)
const openPopOver = Boolean(anchorEl)
const handleClosePopOver = () => {
setAnchorEl(null)
}
const setNewVal = (val) => {
const newVal = myValue + val.substring(2)
onChange(newVal)
setMyValue(newVal)
}
const getInputType = (type) => {
switch (type) {
@@ -19,6 +48,19 @@ export const Input = ({ inputParam, value, onChange, disabled = false, showDialo
}
}
useEffect(() => {
if (!disabled && nodes && edges && nodeId && inputParam) {
const nodesForVariable = inputParam?.acceptVariable ? getAvailableNodesForVariable(nodes, edges, nodeId, inputParam.id) : []
setAvailableNodesForVariable(nodesForVariable)
}
}, [disabled, inputParam, nodes, edges, nodeId])
useEffect(() => {
if (typeof myValue === 'string' && myValue && myValue.endsWith('{{')) {
setAnchorEl(ref.current)
}
}, [myValue])
return (
<>
<FormControl sx={{ mt: 1, width: '100%' }} size='small'>
@@ -55,6 +97,31 @@ export const Input = ({ inputParam, value, onChange, disabled = false, showDialo
}}
></ExpandTextDialog>
)}
<div ref={ref}></div>
{inputParam?.acceptVariable && (
<Popover
open={openPopOver}
anchorEl={anchorEl}
onClose={handleClosePopOver}
anchorOrigin={{
vertical: 'bottom',
horizontal: 'left'
}}
transformOrigin={{
vertical: 'top',
horizontal: 'left'
}}
>
<SelectVariable
disabled={disabled}
availableNodesForVariable={availableNodesForVariable}
onSelectAndReturnVal={(val) => {
setNewVal(val)
handleClosePopOver()
}}
/>
</Popover>
)}
</>
)
}
@@ -66,6 +133,9 @@ Input.propTypes = {
disabled: PropTypes.bool,
showDialog: PropTypes.bool,
dialogProps: PropTypes.object,
nodes: PropTypes.array,
edges: PropTypes.array,
nodeId: PropTypes.string,
onDialogCancel: PropTypes.func,
onDialogConfirm: PropTypes.func
}
packages/ui/src/views/canvas/NodeInputHandler.js
+3
View File
@@ -265,6 +265,9 @@ const NodeInputHandler = ({ inputAnchor, inputParam, data, disabled = false, isA
inputParam={inputParam}
onChange={(newValue) => (data.inputs[inputParam.name] = newValue)}
value={data.inputs[inputParam.name] ?? inputParam.default ?? ''}
nodes={inputParam?.acceptVariable && reactFlowInstance ? reactFlowInstance.getNodes() : []}
edges={inputParam?.acceptVariable && reactFlowInstance ? reactFlowInstance.getEdges() : []}
nodeId={data.id}
showDialog={showExpandDialog}
dialogProps={expandDialogProps}
onDialogCancel={() => setShowExpandDialog(false)}