mudhorn/n8n
1
0
Fork 0
mirror of https://github.com/n8n-io/n8n.git synced 2025-02-02 07:01:30 -08:00
Code Issues Actions Packages Projects Releases Wiki Activity

refactor: Delete mistakenly commited node file (no-changelog) (#10213)

Browse source
This commit is contained in:
oleg 2024-07-26 15:45:48 +02:00 committed by GitHub
parent cd74f4312b
commit 6f1d4adf05
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
1 changed files with 0 additions and 59 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

59
packages/@n8n/nodes-langchain/nodes/vector_store/VectorStoreIndexer/VectorStoreInMemory.node.ts
View file

@ -1,59 +0,0 @@
import type { INodeProperties } from 'n8n-workflow';
import { createVectorStoreNode } from '../shared/createVectorStoreNode';
import { MemoryVectorStoreManager } from '../shared/MemoryVectorStoreManager';
const insertFields: INodeProperties[] = [
{
displayName:
'The embbded data are stored in the server memory, so they will be lost when the server is restarted. Additionally, if the amount of data is too large, it may cause the server to crash due to insufficient memory.',
name: 'notice',
type: 'notice',
default: '',
},
{
displayName: 'Clear Store',
name: 'clearStore',
type: 'boolean',
default: false,
description: 'Whether to clear the store before inserting new data',
},
];
export const VectorStoreInMemory = createVectorStoreNode({
meta: {
displayName: 'In-Memory Vector Store',
name: 'vectorStoreInMemory',
description: 'Work with your data in In-Memory Vector Store',
icon: 'fa:database',
docsUrl:
'https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.vectorstoreinmemory/',
},
sharedFields: [
{
displayName: 'Memory Key',
name: 'memoryKey',
type: 'string',
default: 'vector_store_key',
description:
'The key to use to store the vector memory in the workflow data. The key will be prefixed with the workflow ID to avoid collisions.',
},
],
insertFields,
loadFields: [],
retrieveFields: [],
async getVectorStoreClient(context, _filter, embeddings, itemIndex) {
const workflowId = context.getWorkflow().id;
const memoryKey = context.getNodeParameter('memoryKey', itemIndex) as string;
const vectorStoreSingleton = MemoryVectorStoreManager.getInstance(embeddings);
return await vectorStoreSingleton.getVectorStore(`${workflowId}__${memoryKey}`);
},
async populateVectorStore(context, embeddings, documents, itemIndex) {
const memoryKey = context.getNodeParameter('memoryKey', itemIndex) as string;
const clearStore = context.getNodeParameter('clearStore', itemIndex) as boolean;
const workflowId = context.getWorkflow().id;
const vectorStoreInstance = MemoryVectorStoreManager.getInstance(embeddings);
void vectorStoreInstance.addDocuments(`${workflowId}__${memoryKey}`, documents, clearStore);
},
});