Merge pull request #1462 from vectara/add_mmr_vectara

added support for MMR

packages/components/nodes/chains/VectaraChain/VectaraChain.ts

@@ -69,22 +69,23 @@ class VectaraChain_Chains implements INode {
                 options: [
                     {
                         label: 'vectara-summary-ext-v1.2.0 (gpt-3.5-turbo)',
-                        name: 'vectara-summary-ext-v1.2.0'
+                        name: 'vectara-summary-ext-v1.2.0',
+                        description: 'base summarizer, available to all Vectara users'
                     },
                     {
                         label: 'vectara-experimental-summary-ext-2023-10-23-small (gpt-3.5-turbo)',
                         name: 'vectara-experimental-summary-ext-2023-10-23-small',
-                        description: 'In beta, available to both Growth and Scale Vectara users'
+                        description: `In beta, available to both Growth and <a target="_blank" href="https://vectara.com/pricing/">Scale</a> Vectara users`
                     },
                     {
                         label: 'vectara-summary-ext-v1.3.0 (gpt-4.0)',
                         name: 'vectara-summary-ext-v1.3.0',
-                        description: 'Only available to paying Scale Vectara users'
+                        description: 'Only available to <a target="_blank" href="https://vectara.com/pricing/">Scale</a> Vectara users'
                     },
                     {
                         label: 'vectara-experimental-summary-ext-2023-10-23-med (gpt-4.0)',
                         name: 'vectara-experimental-summary-ext-2023-10-23-med',
-                        description: 'In beta, only available to paying Scale Vectara users'
+                        description: `In beta, only available to <a target="_blank" href="https://vectara.com/pricing/">Scale</a> Vectara users`
                     }
                 ],
                 default: 'vectara-summary-ext-v1.2.0'
@@ -228,7 +229,7 @@ class VectaraChain_Chains implements INode {
 
     async run(nodeData: INodeData, input: string): Promise<object> {
         const vectorStore = nodeData.inputs?.vectaraStore as VectaraStore
-        const responseLang = (nodeData.inputs?.responseLang as string) ?? 'auto'
+        const responseLang = (nodeData.inputs?.responseLang as string) ?? 'eng'
         const summarizerPromptName = nodeData.inputs?.summarizerPromptName as string
         const maxSummarizedResultsStr = nodeData.inputs?.maxSummarizedResults as string
         const maxSummarizedResults = maxSummarizedResultsStr ? parseInt(maxSummarizedResultsStr, 10) : 7
@@ -247,17 +248,31 @@ class VectaraChain_Chains implements INode {
             lexicalInterpolationConfig: { lambda: vectaraFilter?.lambda ?? 0.025 }
         }))
 
+        // Vectara reranker ID for MMR (https://docs.vectara.com/docs/api-reference/search-apis/reranking#maximal-marginal-relevance-mmr-reranker)
+        const mmrRerankerId = 272725718
+        const mmrEnabled = vectaraFilter?.mmrConfig?.enabled
+
         const data = {
             query: [
                 {
                     query: input,
                     start: 0,
-                    numResults: topK,
+                    numResults: mmrEnabled ? vectaraFilter?.mmrTopK : topK,
+                    corpusKey: corpusKeys,
                     contextConfig: {
                         sentencesAfter: vectaraFilter?.contextConfig?.sentencesAfter ?? 2,
                         sentencesBefore: vectaraFilter?.contextConfig?.sentencesBefore ?? 2
                     },
-                    corpusKey: corpusKeys,
+                    ...(mmrEnabled
+                        ? {
+                              rerankingConfig: {
+                                  rerankerId: mmrRerankerId,
+                                  mmrConfig: {
+                                      diversityBias: vectaraFilter?.mmrConfig.diversityBias
+                                  }
+                              }
+                          }
+                        : {}),
                     summary: [
                         {
                             summarizerPromptName,
@@ -285,6 +300,14 @@ class VectaraChain_Chains implements INode {
             const documents = result.responseSet[0].document
             let rawSummarizedText = ''
 
+            // remove responses that are not in the topK (in case of MMR)
+            // Note that this does not really matter functionally due to the reorder citations, but it is more efficient
+            const maxResponses = mmrEnabled ? Math.min(responses.length, topK) : responses.length
+            if (responses.length > maxResponses) {
+                responses.splice(0, maxResponses)
+            }
+
+            // Add metadata to each text response given its corresponding document metadata
             for (let i = 0; i < responses.length; i += 1) {
                 const responseMetadata = responses[i].metadata
                 const documentMetadata = documents[responses[i].documentIndex].metadata
@@ -301,13 +324,13 @@ class VectaraChain_Chains implements INode {
                 responses[i].metadata = combinedMetadata
             }
 
+            // Create the summarization response
             const summaryStatus = result.responseSet[0].summary[0].status
             if (summaryStatus.length > 0 && summaryStatus[0].code === 'BAD_REQUEST') {
                 throw new Error(
                     `BAD REQUEST: Too much text for the summarizer to summarize. Please try reducing the number of search results to summarize, or the context of each result by adjusting the 'summary_num_sentences', and 'summary_num_results' parameters respectively.`
                 )
             }
-
             if (
                 summaryStatus.length > 0 &&
                 summaryStatus[0].code === 'NOT_FOUND' &&
@@ -316,8 +339,8 @@ class VectaraChain_Chains implements INode {
                 throw new Error(`BAD REQUEST: summarizer ${summarizerPromptName} is invalid for this account.`)
             }
 
+            // Reorder citations in summary and create the list of returned source documents
             rawSummarizedText = result.responseSet[0].summary[0]?.text
-
             let summarizedText = reorderCitations(rawSummarizedText)
             let summaryResponses = applyCitationOrder(responses, rawSummarizedText)
 

packages/components/nodes/vectorstores/Vectara/Vectara.ts

@@ -1,5 +1,5 @@
 import { flatten } from 'lodash'
-import { VectaraStore, VectaraLibArgs, VectaraFilter, VectaraContextConfig, VectaraFile } from 'langchain/vectorstores/vectara'
+import { VectaraStore, VectaraLibArgs, VectaraFilter, VectaraContextConfig, VectaraFile, MMRConfig } from 'langchain/vectorstores/vectara'
 import { Document } from 'langchain/document'
 import { Embeddings } from 'langchain/embeddings/base'
 import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
@@ -22,7 +22,7 @@ class Vectara_VectorStores implements INode {
     constructor() {
         this.label = 'Vectara'
         this.name = 'vectara'
-        this.version = 1.0
+        this.version = 2.0
         this.type = 'Vectara'
         this.icon = 'vectara.png'
         this.category = 'Vector Stores'
@@ -82,7 +82,9 @@ class Vectara_VectorStores implements INode {
                 label: 'Lambda',
                 name: 'lambda',
                 description:
-                    'Improves retrieval accuracy by adjusting the balance (from 0 to 1) between neural search and keyword-based search factors.',
+                    'Enable hybrid search to improve retrieval accuracy by adjusting the balance (from 0 to 1) between neural search and keyword-based search factors.' +
+                    'A value of 0.0 means that only neural search is used, while a value of 1.0 means that only keyword-based search is used. Defaults to 0.0 (neural only).',
+                default: 0.0,
                 type: 'number',
                 additionalParams: true,
                 optional: true
@@ -90,8 +92,30 @@ class Vectara_VectorStores implements INode {
             {
                 label: 'Top K',
                 name: 'topK',
-                description: 'Number of top results to fetch. Defaults to 4',
+                description: 'Number of top results to fetch. Defaults to 5',
-                placeholder: '4',
+                placeholder: '5',
+                type: 'number',
+                additionalParams: true,
+                optional: true
+            },
+            {
+                label: 'MMR K',
+                name: 'mmrK',
+                description: 'Number of top results to fetch for MMR. Defaults to 50',
+                placeholder: '50',
+                type: 'number',
+                additionalParams: true,
+                optional: true
+            },
+            {
+                label: 'MMR diversity bias',
+                name: 'mmrDiversityBias',
+                step: 0.1,
+                description:
+                    'The diversity bias to use for MMR. This is a value between 0.0 and 1.0' +
+                    'Values closer to 1.0 optimize for the most diverse results.' +
+                    'Defaults to 0 (MMR disabled)',
+                placeholder: '0.0',
                 type: 'number',
                 additionalParams: true,
                 optional: true
@@ -191,7 +215,9 @@ 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 ? parseFloat(topK) : 4
+        const k = topK ? parseFloat(topK) : 5
+        const mmrK = nodeData.inputs?.mmrK as number
+        const mmrDiversityBias = nodeData.inputs?.mmrDiversityBias as number
 
         const vectaraArgs: VectaraLibArgs = {
             apiKey: apiKey,
@@ -208,6 +234,11 @@ class Vectara_VectorStores implements INode {
         if (sentencesBefore) vectaraContextConfig.sentencesBefore = sentencesBefore
         if (sentencesAfter) vectaraContextConfig.sentencesAfter = sentencesAfter
         vectaraFilter.contextConfig = vectaraContextConfig
+        const mmrConfig: MMRConfig = {}
+        mmrConfig.enabled = mmrDiversityBias > 0
+        mmrConfig.mmrTopK = mmrK
+        mmrConfig.diversityBias = mmrDiversityBias
+        vectaraFilter.mmrConfig = mmrConfig
 
         const vectorStore = new VectaraStore(vectaraArgs)
 

packages/components/package.json

@@ -49,7 +49,7 @@
         "express": "^4.17.3",
         "faiss-node": "^0.2.2",
         "form-data": "^4.0.0",
-        "google-auth-library": "^9.0.0",
+        "google-auth-library": "^9.4.0",
         "graphql": "^16.6.0",
         "html-to-text": "^9.0.5",
         "husky": "^8.0.3",

packages/server/marketplaces/chatflows/Vectara LLM Chain Upload.json

@@ -361,12 +361,33 @@
                     {
                         "label": "Top K",
                         "name": "topK",
-                        "description": "Number of top results to fetch. Defaults to 4",
+                        "description": "Number of top results to fetch. Defaults to 5",
-                        "placeholder": "4",
+                        "placeholder": "5",
                         "type": "number",
                         "additionalParams": true,
                         "optional": true,
                         "id": "vectara_0-input-topK-number"
+                    },
+                    {
+                        "label": "MMR K",
+                        "name": "mmrK",
+                        "description": "The number of results to rerank if MMR is enabled.",
+                        "placeholder": "50",
+                        "type": "number",
+                        "additionalParams": true,
+                        "optional": true,
+                        "id": "vectara_0-input-mmrK-number"
+                    },
+                    {
+                        "label": "MMR Diversity Bias",
+                        "name": "mmrDiversityBias",
+                        "step": 0.1,
+                        "description": "Diversity Bias parameter for MMR, if enabled. 0.0 means no diversiry bias, 1.0 means maximum diversity bias. Defaults to 0.0 (MMR disabled).",
+                        "placeholder": "0.0",
+                        "type": "number",
+                        "additionalParams": true,
+                        "optional": true,
+                        "id": "vectara_0-input-mmrDiversityBias-number"
                     }
                 ],
                 "inputAnchors": [
@@ -385,7 +406,9 @@
                     "sentencesBefore": "",
                     "sentencesAfter": "",
                     "lambda": "",
-                    "topK": ""
+                    "topK": "",
+                    "mmrK": "",
+                    "mmrDiversityBias": ""
                 },
                 "outputAnchors": [
                     {