Sultan
/
Flowise
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Bugfix/Add astradb collection name and namespace (#2071) 

add astradb collection name and namespace
This commit is contained in:
Henry Heng 2024-03-31 00:07:59 +08:00 committed by GitHub
parent a09b7f7e39
commit 70706a7183
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 20 additions and 11 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

7
packages/components/credentials/AstraApi.credential.ts
View File

@ -10,13 +10,8 @@ class AstraDBApi implements INodeCredential {
constructor() { constructor() {
this.label = 'Astra DB API' this.label = 'Astra DB API'
this.name = 'AstraDBApi' this.name = 'AstraDBApi'
this.version = 1.0 this.version = 2.0
this.inputs = [ this.inputs = [
{
label: 'Astra DB Collection Name',
name: 'collectionName',
type: 'string'
},
{ {
label: 'Astra DB Application Token', label: 'Astra DB Application Token',
name: 'applicationToken', name: 'applicationToken',

24
packages/components/nodes/vectorstores/Astra/Astra.ts
View File

@ -23,13 +23,12 @@ class Astra_VectorStores implements INode {
constructor() { constructor() {
this.label = 'Astra' this.label = 'Astra'
this.name = 'Astra' this.name = 'Astra'
this.version = 1.0 this.version = 2.0
this.type = 'Astra' this.type = 'Astra'
this.icon = 'astra.svg' this.icon = 'astra.svg'
this.category = 'Vector Stores' this.category = 'Vector Stores'
this.description = `Upsert embedded data and perform similarity or mmr search upon query using DataStax Astra DB, a serverless vector database that’s perfect for managing mission-critical AI workloads` this.description = `Upsert embedded data and perform similarity or mmr search upon query using DataStax Astra DB, a serverless vector database that’s perfect for managing mission-critical AI workloads`
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever'] this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
this.badge = 'NEW'
this.credential = { this.credential = {
label: 'Connect Credential', label: 'Connect Credential',
name: 'credential', name: 'credential',
@ -49,6 +48,16 @@ class Astra_VectorStores implements INode {
name: 'embeddings', name: 'embeddings',
type: 'Embeddings' type: 'Embeddings'
}, },
{
label: 'Namespace',
name: 'astraNamespace',
type: 'string'
},
{
label: 'Collection',
name: 'astraCollection',
type: 'string'
},
{ {
label: 'Vector Dimension', label: 'Vector Dimension',
name: 'vectorDimension', name: 'vectorDimension',
@ -96,6 +105,8 @@ class Astra_VectorStores implements INode {
const docs = nodeData.inputs?.document as Document[] const docs = nodeData.inputs?.document as Document[]
const embeddings = nodeData.inputs?.embeddings as Embeddings const embeddings = nodeData.inputs?.embeddings as Embeddings
const vectorDimension = nodeData.inputs?.vectorDimension as number const vectorDimension = nodeData.inputs?.vectorDimension as number
const astraNamespace = nodeData.inputs?.astraNamespace as string
const astraCollection = nodeData.inputs?.astraCollection as string
const similarityMetric = nodeData.inputs?.similarityMetric as 'cosine' | 'euclidean' | 'dot_product' | undefined const similarityMetric = nodeData.inputs?.similarityMetric as 'cosine' | 'euclidean' | 'dot_product' | undefined
const credentialData = await getCredentialData(nodeData.credential ?? '', options) const credentialData = await getCredentialData(nodeData.credential ?? '', options)
@ -111,7 +122,8 @@ class Astra_VectorStores implements INode {
const astraConfig: AstraLibArgs = { const astraConfig: AstraLibArgs = {
...clientConfig, ...clientConfig,
collection: credentialData.collectionName ?? 'flowise_test', namespace: astraNamespace ?? 'default_keyspace',
collection: astraCollection ?? credentialData.collectionName ?? 'flowise_test',
collectionOptions: { collectionOptions: {
vector: { vector: {
dimension: vectorDimension ?? 1536, dimension: vectorDimension ?? 1536,
@ -141,7 +153,8 @@ class Astra_VectorStores implements INode {
const embeddings = nodeData.inputs?.embeddings as Embeddings const embeddings = nodeData.inputs?.embeddings as Embeddings
const vectorDimension = nodeData.inputs?.vectorDimension as number const vectorDimension = nodeData.inputs?.vectorDimension as number
const similarityMetric = nodeData.inputs?.similarityMetric as 'cosine' | 'euclidean' | 'dot_product' | undefined const similarityMetric = nodeData.inputs?.similarityMetric as 'cosine' | 'euclidean' | 'dot_product' | undefined
const astraNamespace = nodeData.inputs?.astraNamespace as string
const astraCollection = nodeData.inputs?.astraCollection as string
const credentialData = await getCredentialData(nodeData.credential ?? '', options) const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const expectedSimilarityMetric = ['cosine', 'euclidean', 'dot_product'] const expectedSimilarityMetric = ['cosine', 'euclidean', 'dot_product']
@ -156,7 +169,8 @@ class Astra_VectorStores implements INode {
const astraConfig: AstraLibArgs = { const astraConfig: AstraLibArgs = {
...clientConfig, ...clientConfig,
collection: credentialData.collectionName ?? 'flowise_test', namespace: astraNamespace ?? 'default_keyspace',
collection: astraCollection ?? credentialData.collectionName ?? 'flowise_test',
collectionOptions: { collectionOptions: {
vector: { vector: {
dimension: vectorDimension ?? 1536, dimension: vectorDimension ?? 1536,