mirror of
https://github.com/farcasclaudiu/Flowise.git
synced 2026-06-28 17:01:00 +03:00
add top K to vector stores
This commit is contained in:
@@ -38,6 +38,15 @@ class Chroma_Existing_VectorStores implements INode {
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name: 'chromaURL',
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type: 'string',
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optional: true
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},
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{
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label: 'Top K',
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name: 'topK',
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description: 'Number of top results to fetch. Default to 4',
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placeholder: '4',
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type: 'number',
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additionalParams: true,
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optional: true
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}
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]
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this.outputs = [
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@@ -59,6 +68,8 @@ class Chroma_Existing_VectorStores implements INode {
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const chromaURL = nodeData.inputs?.chromaURL as string
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const output = nodeData.outputs?.output as string
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const topK = nodeData.inputs?.topK as string
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const k = topK ? parseInt(topK, 10) : 4
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const obj: {
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collectionName: string
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@@ -69,9 +80,10 @@ class Chroma_Existing_VectorStores implements INode {
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const vectorStore = await Chroma.fromExistingCollection(embeddings, obj)
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever()
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const retriever = vectorStore.asRetriever(k)
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return retriever
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} else if (output === 'vectorStore') {
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;(vectorStore as any).k = k
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return vectorStore
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}
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return vectorStore
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@@ -46,6 +46,15 @@ class ChromaUpsert_VectorStores implements INode {
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name: 'chromaURL',
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type: 'string',
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optional: true
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},
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{
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label: 'Top K',
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name: 'topK',
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description: 'Number of top results to fetch. Default to 4',
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placeholder: '4',
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type: 'number',
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additionalParams: true,
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optional: true
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}
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]
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this.outputs = [
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@@ -68,6 +77,8 @@ class ChromaUpsert_VectorStores implements INode {
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const chromaURL = nodeData.inputs?.chromaURL as string
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const output = nodeData.outputs?.output as string
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const topK = nodeData.inputs?.topK as string
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const k = topK ? parseInt(topK, 10) : 4
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const flattenDocs = docs && docs.length ? flatten(docs) : []
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const finalDocs = []
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@@ -84,9 +95,10 @@ class ChromaUpsert_VectorStores implements INode {
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const vectorStore = await Chroma.fromDocuments(finalDocs, embeddings, obj)
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever()
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const retriever = vectorStore.asRetriever(k)
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return retriever
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} else if (output === 'vectorStore') {
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;(vectorStore as any).k = k
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return vectorStore
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}
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return vectorStore
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@@ -34,6 +34,15 @@ class Faiss_Existing_VectorStores implements INode {
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description: 'Path to load faiss.index file',
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placeholder: `C:\\Users\\User\\Desktop`,
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type: 'string'
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},
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{
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label: 'Top K',
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name: 'topK',
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description: 'Number of top results to fetch. Default to 4',
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placeholder: '4',
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type: 'number',
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additionalParams: true,
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optional: true
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}
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]
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this.outputs = [
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@@ -54,13 +63,16 @@ class Faiss_Existing_VectorStores implements INode {
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const basePath = nodeData.inputs?.basePath as string
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const output = nodeData.outputs?.output as string
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const topK = nodeData.inputs?.topK as string
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const k = topK ? parseInt(topK, 10) : 4
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const vectorStore = await FaissStore.load(basePath, embeddings)
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever()
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const retriever = vectorStore.asRetriever(k)
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return retriever
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} else if (output === 'vectorStore') {
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;(vectorStore as any).k = k
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return vectorStore
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}
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return vectorStore
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@@ -42,6 +42,15 @@ class FaissUpsert_VectorStores implements INode {
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description: 'Path to store faiss.index file',
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placeholder: `C:\\Users\\User\\Desktop`,
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type: 'string'
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},
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{
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label: 'Top K',
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name: 'topK',
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description: 'Number of top results to fetch. Default to 4',
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placeholder: '4',
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type: 'number',
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additionalParams: true,
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optional: true
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}
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]
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this.outputs = [
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@@ -63,6 +72,8 @@ class FaissUpsert_VectorStores implements INode {
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const output = nodeData.outputs?.output as string
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const basePath = nodeData.inputs?.basePath as string
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const topK = nodeData.inputs?.topK as string
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const k = topK ? parseInt(topK, 10) : 4
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const flattenDocs = docs && docs.length ? flatten(docs) : []
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const finalDocs = []
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@@ -74,9 +85,10 @@ class FaissUpsert_VectorStores implements INode {
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await vectorStore.save(basePath)
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever()
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const retriever = vectorStore.asRetriever(k)
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return retriever
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} else if (output === 'vectorStore') {
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;(vectorStore as any).k = k
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return vectorStore
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}
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return vectorStore
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@@ -35,6 +35,14 @@ class InMemoryVectorStore_VectorStores implements INode {
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label: 'Embeddings',
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name: 'embeddings',
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type: 'Embeddings'
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},
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{
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label: 'Top K',
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name: 'topK',
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description: 'Number of top results to fetch. Default to 4',
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placeholder: '4',
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type: 'number',
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optional: true
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}
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]
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this.outputs = [
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@@ -55,6 +63,8 @@ class InMemoryVectorStore_VectorStores implements INode {
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const docs = nodeData.inputs?.document as Document[]
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const output = nodeData.outputs?.output as string
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const topK = nodeData.inputs?.topK as string
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const k = topK ? parseInt(topK, 10) : 4
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const flattenDocs = docs && docs.length ? flatten(docs) : []
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const finalDocs = []
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@@ -65,9 +75,10 @@ class InMemoryVectorStore_VectorStores implements INode {
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const vectorStore = await MemoryVectorStore.fromDocuments(finalDocs, embeddings)
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever()
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const retriever = vectorStore.asRetriever(k)
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return retriever
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} else if (output === 'vectorStore') {
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;(vectorStore as any).k = k
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return vectorStore
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}
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return vectorStore
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@@ -49,6 +49,7 @@ class Pinecone_Existing_VectorStores implements INode {
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name: 'pineconeNamespace',
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type: 'string',
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placeholder: 'my-first-namespace',
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additionalParams: true,
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optional: true
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},
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{
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@@ -57,6 +58,15 @@ class Pinecone_Existing_VectorStores implements INode {
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type: 'json',
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optional: true,
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additionalParams: true
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},
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{
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label: 'Top K',
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name: 'topK',
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description: 'Number of top results to fetch. Default to 4',
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placeholder: '4',
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type: 'number',
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additionalParams: true,
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optional: true
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}
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]
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this.outputs = [
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@@ -79,9 +89,10 @@ class Pinecone_Existing_VectorStores implements INode {
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const index = nodeData.inputs?.pineconeIndex as string
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const pineconeNamespace = nodeData.inputs?.pineconeNamespace as string
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const pineconeMetadataFilter = nodeData.inputs?.pineconeMetadataFilter
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const output = nodeData.outputs?.output as string
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const topK = nodeData.inputs?.topK as string
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const k = topK ? parseInt(topK, 10) : 4
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const client = new PineconeClient()
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await client.init({
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@@ -104,9 +115,10 @@ class Pinecone_Existing_VectorStores implements INode {
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const vectorStore = await PineconeStore.fromExistingIndex(embeddings, obj)
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever()
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const retriever = vectorStore.asRetriever(k)
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return retriever
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} else if (output === 'vectorStore') {
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;(vectorStore as any).k = k
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return vectorStore
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}
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return vectorStore
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@@ -57,6 +57,16 @@ class PineconeUpsert_VectorStores implements INode {
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name: 'pineconeNamespace',
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type: 'string',
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placeholder: 'my-first-namespace',
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additionalParams: true,
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optional: true
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},
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{
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label: 'Top K',
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name: 'topK',
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description: 'Number of top results to fetch. Default to 4',
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placeholder: '4',
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type: 'number',
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additionalParams: true,
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optional: true
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}
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]
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@@ -82,6 +92,8 @@ class PineconeUpsert_VectorStores implements INode {
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const docs = nodeData.inputs?.document as Document[]
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const output = nodeData.outputs?.output as string
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const topK = nodeData.inputs?.topK as string
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const k = topK ? parseInt(topK, 10) : 4
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const client = new PineconeClient()
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await client.init({
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@@ -106,9 +118,10 @@ class PineconeUpsert_VectorStores implements INode {
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const vectorStore = await PineconeStore.fromDocuments(finalDocs, embeddings, obj)
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever()
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const retriever = vectorStore.asRetriever(k)
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return retriever
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} else if (output === 'vectorStore') {
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;(vectorStore as any).k = k
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return vectorStore
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}
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return vectorStore
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@@ -55,6 +55,15 @@ class Supabase_Existing_VectorStores implements INode {
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type: 'json',
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optional: true,
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additionalParams: true
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},
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{
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label: 'Top K',
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name: 'topK',
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description: 'Number of top results to fetch. Default to 4',
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placeholder: '4',
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type: 'number',
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additionalParams: true,
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optional: true
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}
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]
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this.outputs = [
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@@ -79,6 +88,8 @@ class Supabase_Existing_VectorStores implements INode {
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const supabaseMetadataFilter = nodeData.inputs?.supabaseMetadataFilter
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const output = nodeData.outputs?.output as string
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const topK = nodeData.inputs?.topK as string
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const k = topK ? parseInt(topK, 10) : 4
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const client = createClient(supabaseProjUrl, supabaseApiKey)
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@@ -96,9 +107,10 @@ class Supabase_Existing_VectorStores implements INode {
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const vectorStore = await SupabaseVectorStore.fromExistingIndex(embeddings, obj)
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever()
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const retriever = vectorStore.asRetriever(k)
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return retriever
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} else if (output === 'vectorStore') {
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;(vectorStore as any).k = k
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return vectorStore
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}
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return vectorStore
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@@ -56,6 +56,15 @@ class SupabaseUpsert_VectorStores implements INode {
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label: 'Query Name',
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name: 'queryName',
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type: 'string'
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},
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{
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label: 'Top K',
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name: 'topK',
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description: 'Number of top results to fetch. Default to 4',
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placeholder: '4',
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type: 'number',
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additionalParams: true,
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optional: true
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}
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]
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this.outputs = [
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@@ -80,6 +89,8 @@ class SupabaseUpsert_VectorStores implements INode {
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const docs = nodeData.inputs?.document as Document[]
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const output = nodeData.outputs?.output as string
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const topK = nodeData.inputs?.topK as string
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const k = topK ? parseInt(topK, 10) : 4
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const client = createClient(supabaseProjUrl, supabaseApiKey)
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@@ -96,9 +107,10 @@ class SupabaseUpsert_VectorStores implements INode {
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})
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever()
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const retriever = vectorStore.asRetriever(k)
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return retriever
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} else if (output === 'vectorStore') {
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;(vectorStore as any).k = k
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return vectorStore
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}
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return vectorStore
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@@ -79,6 +79,15 @@ class Weaviate_Existing_VectorStores implements INode {
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placeholder: `["foo"]`,
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optional: true,
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additionalParams: true
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},
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{
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label: 'Top K',
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name: 'topK',
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description: 'Number of top results to fetch. Default to 4',
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placeholder: '4',
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type: 'number',
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additionalParams: true,
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optional: true
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}
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]
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this.outputs = [
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@@ -102,9 +111,10 @@ class Weaviate_Existing_VectorStores implements INode {
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const weaviateApiKey = nodeData.inputs?.weaviateApiKey as string
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const weaviateTextKey = nodeData.inputs?.weaviateTextKey as string
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const weaviateMetadataKeys = nodeData.inputs?.weaviateMetadataKeys as string
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const output = nodeData.outputs?.output as string
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const topK = nodeData.inputs?.topK as string
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const k = topK ? parseInt(topK, 10) : 4
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const clientConfig: any = {
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scheme: weaviateScheme,
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@@ -125,9 +135,10 @@ class Weaviate_Existing_VectorStores implements INode {
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const vectorStore = await WeaviateStore.fromExistingIndex(embeddings, obj)
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever()
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const retriever = vectorStore.asRetriever(k)
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return retriever
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} else if (output === 'vectorStore') {
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;(vectorStore as any).k = k
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return vectorStore
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}
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return vectorStore
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@@ -87,6 +87,15 @@ class WeaviateUpsert_VectorStores implements INode {
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placeholder: `["foo"]`,
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optional: true,
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additionalParams: true
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},
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{
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label: 'Top K',
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name: 'topK',
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description: 'Number of top results to fetch. Default to 4',
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placeholder: '4',
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type: 'number',
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additionalParams: true,
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optional: true
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}
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]
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this.outputs = [
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@@ -110,10 +119,11 @@ class WeaviateUpsert_VectorStores implements INode {
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const weaviateApiKey = nodeData.inputs?.weaviateApiKey as string
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const weaviateTextKey = nodeData.inputs?.weaviateTextKey as string
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const weaviateMetadataKeys = nodeData.inputs?.weaviateMetadataKeys as string
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const docs = nodeData.inputs?.document as Document[]
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const output = nodeData.outputs?.output as string
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const topK = nodeData.inputs?.topK as string
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const k = topK ? parseInt(topK, 10) : 4
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const clientConfig: any = {
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scheme: weaviateScheme,
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@@ -140,9 +150,10 @@ class WeaviateUpsert_VectorStores implements INode {
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const vectorStore = await WeaviateStore.fromDocuments(finalDocs, embeddings, obj)
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever()
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const retriever = vectorStore.asRetriever(k)
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return retriever
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} else if (output === 'vectorStore') {
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;(vectorStore as any).k = k
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return vectorStore
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}
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return vectorStore
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