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fix namings, update description, show badge and node info

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Henry
2023-11-22 19:48:01 +00:00
parent 44cadc1cc3
commit 7d13b6323f
30 changed files with 214 additions and 123 deletions
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packages/components/nodes/retrievers/HydeRetriever/HydeRetriever.ts
+1 -1
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@@ -104,7 +104,7 @@ class HydeRetriever_Retrievers implements INode {
const promptKey = nodeData.inputs?.promptKey as PromptKey
const customPrompt = nodeData.inputs?.customPrompt as string
const topK = nodeData.inputs?.topK as string
const k = topK ? parseInt(topK, 10) : 4
const k = topK ? parseFloat(topK) : 4
const obj: HydeRetrieverOptions<any> = {
llm,
packages/components/nodes/vectorstores/Chroma/Chroma.ts
+1 -1
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@@ -27,7 +27,7 @@ class Chroma_VectorStores implements INode {
this.type = 'Chroma'
this.icon = 'chroma.svg'
this.category = 'Vector Stores'
this.description = 'Upsert or Load data to Chroma Vector Database'
this.description = 'Upsert embedded data and perform similarity search upon query using Chroma, an open-source embedding database'
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
this.badge = 'NEW'
this.credential = {
packages/components/nodes/vectorstores/Elasticsearch/Elasticsearch.ts
+2 -1
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@@ -24,7 +24,8 @@ class Elasticsearch_VectorStores implements INode {
this.label = 'Elasticsearch'
this.name = 'elasticsearch'
this.version = 1.0
this.description = 'Upsert or Load data to Elasticsearch Vector Database'
this.description =
'Upsert embedded data and perform similarity search upon query using Elasticsearch, a distributed search and analytics engine'
this.type = 'Elasticsearch'
this.icon = 'elasticsearch.png'
this.category = 'Vector Stores'
packages/components/nodes/vectorstores/Faiss/Faiss.ts
+1 -1
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@@ -25,7 +25,7 @@ class Faiss_VectorStores implements INode {
this.type = 'Faiss'
this.icon = 'faiss.svg'
this.category = 'Vector Stores'
this.description = 'Upsert or Load data to Faiss Vector Store'
this.description = 'Upsert embedded data and perform similarity search upon query using Faiss library from Meta'
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
this.badge = 'NEW'
this.inputs = [
packages/components/nodes/vectorstores/Milvus/Milvus.ts
+2 -2
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@@ -31,7 +31,7 @@ class Milvus_VectorStores implements INode {
this.type = 'Milvus'
this.icon = 'milvus.svg'
this.category = 'Vector Stores'
this.description = 'Upsert or Load data to Milvus Vector Database'
this.description = `Upsert embedded data and perform similarity search upon query using Milvus, world's most advanced open-source vector database`
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
this.badge = 'NEW'
this.credential = {
@@ -159,7 +159,7 @@ class Milvus_VectorStores implements INode {
const output = nodeData.outputs?.output as string
// format data
const k = topK ? parseInt(topK, 10) : 4
const k = topK ? parseFloat(topK) : 4
// credential
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
packages/components/nodes/vectorstores/OpenSearch/OpenSearch.ts
+1 -1
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@@ -26,7 +26,7 @@ class OpenSearch_VectorStores implements INode {
this.type = 'OpenSearch'
this.icon = 'opensearch.png'
this.category = 'Vector Stores'
this.description = 'Upsert or Load data to OpenSearch Vector Database'
this.description = `Upsert embedded data and perform similarity search upon query using OpenSearch, an open-source, all-in-one vector database`
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
this.badge = 'NEW'
this.inputs = [
packages/components/nodes/vectorstores/Pinecone/Pinecone.ts
+1 -1
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@@ -27,7 +27,7 @@ class Pinecone_VectorStores implements INode {
this.type = 'Pinecone'
this.icon = 'pinecone.png'
this.category = 'Vector Stores'
this.description = 'Upsert or Load data to Pinecone Vector Database'
this.description = `Upsert embedded data and perform similarity search upon query using Pinecone, a leading fully managed hosted vector database`
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
this.badge = 'NEW'
this.credential = {
packages/components/nodes/vectorstores/Postgres/Postgres.ts
+1 -1
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@@ -28,7 +28,7 @@ class Postgres_VectorStores implements INode {
this.type = 'Postgres'
this.icon = 'postgres.svg'
this.category = 'Vector Stores'
this.description = 'Upsert or Load data to Postgres using pgvector'
this.description = 'Upsert embedded data and perform similarity search upon query using pgvector on Postgres'
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
this.badge = 'NEW'
this.credential = {
packages/components/nodes/vectorstores/Qdrant/Qdrant.ts
+2 -1
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@@ -30,7 +30,8 @@ class Qdrant_VectorStores implements INode {
this.type = 'Qdrant'
this.icon = 'qdrant.png'
this.category = 'Vector Stores'
this.description = 'Upsert or Load data to Qdrant Vector Database'
this.description =
'Upsert embedded data and perform similarity search upon query using Qdrant, a scalable open source vector database written in Rust'
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
this.badge = 'NEW'
this.credential = {
packages/components/nodes/vectorstores/Redis/Redis.ts
+2 -1
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@@ -25,7 +25,8 @@ class Redis_VectorStores implements INode {
this.label = 'Redis'
this.name = 'redis'
this.version = 1.0
this.description = 'Upsert or Load data to Redis'
this.description =
'Upsert embedded data and perform similarity search upon query using Redis, an open source, in-memory data structure store'
this.type = 'Redis'
this.icon = 'redis.svg'
this.category = 'Vector Stores'
packages/components/nodes/vectorstores/Singlestore/Singlestore.ts
+3 -4
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@@ -26,7 +26,8 @@ class SingleStore_VectorStores implements INode {
this.type = 'SingleStore'
this.icon = 'singlestore.svg'
this.category = 'Vector Stores'
this.description = 'Upsert or Load data to SingleStore Vector Database'
this.description =
'Upsert embedded data and perform similarity search upon query using SingleStore, a fast and distributed cloud relational database'
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
this.badge = 'NEW'
this.credential = {
@@ -180,9 +181,7 @@ class SingleStore_VectorStores implements INode {
const topK = nodeData.inputs?.topK as string
const k = topK ? parseFloat(topK) : 4
let vectorStore: SingleStoreVectorStore
vectorStore = new SingleStoreVectorStore(embeddings, singleStoreConnectionConfig)
const vectorStore = new SingleStoreVectorStore(embeddings, singleStoreConnectionConfig)
if (output === 'retriever') {
const retriever = vectorStore.asRetriever(k)
packages/components/nodes/vectorstores/Supabase/Supabase.ts
+4 -2
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@@ -27,7 +27,7 @@ class Supabase_VectorStores implements INode {
this.type = 'Supabase'
this.icon = 'supabase.svg'
this.category = 'Vector Stores'
this.description = 'Upsert or Load data to Supabase using pgvector'
this.description = 'Upsert embedded data and perform similarity search upon query using Supabase via pgvector extension'
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
this.badge = 'NEW'
this.credential = {
@@ -112,7 +112,9 @@ class Supabase_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]))
}
}
try {
packages/components/nodes/vectorstores/Vectara/Vectara.ts
+4 -2
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@@ -26,7 +26,7 @@ class Vectara_VectorStores implements INode {
this.type = 'Vectara'
this.icon = 'vectara.png'
this.category = 'Vector Stores'
this.description = 'Upsert or Load data to Vectara Vector Database'
this.description = 'Upsert embedded data and perform similarity search upon query using Vectara, a LLM-powered search-as-a-service'
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
this.badge = 'NEW'
this.credential = {
@@ -65,6 +65,7 @@ class Vectara_VectorStores implements INode {
name: 'sentencesBefore',
description: 'Number of sentences to fetch before the matched sentence. Defaults to 2.',
type: 'number',
default: 2,
additionalParams: true,
optional: true
},
@@ -73,6 +74,7 @@ class Vectara_VectorStores implements INode {
name: 'sentencesAfter',
description: 'Number of sentences to fetch after the matched sentence. Defaults to 2.',
type: 'number',
default: 2,
additionalParams: true,
optional: true
},
@@ -189,7 +191,7 @@ class Vectara_VectorStores implements INode {
const lambda = nodeData.inputs?.lambda as number
const output = nodeData.outputs?.output as string
const topK = nodeData.inputs?.topK as string
const k = topK ? parseInt(topK, 10) : 4
const k = topK ? parseFloat(topK) : 4
const vectaraArgs: VectaraLibArgs = {
apiKey: apiKey,
packages/components/nodes/vectorstores/Weaviate/Weaviate.ts
+2 -1
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@@ -27,7 +27,8 @@ class Weaviate_VectorStores implements INode {
this.type = 'Weaviate'
this.icon = 'weaviate.png'
this.category = 'Vector Stores'
this.description = 'Upsert or Load data to Weaviate Vector Database'
this.description =
'Upsert embedded data and perform similarity search upon query using Weaviate, a scalable open-source vector database'
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
this.badge = 'NEW'
this.credential = {
packages/components/nodes/vectorstores/Zep/Zep.ts
+2 -1
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@@ -27,7 +27,8 @@ class Zep_VectorStores implements INode {
this.type = 'Zep'
this.icon = 'zep.png'
this.category = 'Vector Stores'
this.description = 'Upsert or Load data to Zep Vector Database'
this.description =
'Upsert embedded data and perform similarity search upon query using Zep, a fast and scalable building block for LLM apps'
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
this.badge = 'NEW'
this.credential = {