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Third-party integrations for LangChain.js
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{"version":3,"file":"googlevertexai.cjs","names":["Document","fields: IdDocumentInput","GoogleVertexAIConnection","fields: IndexEndpointConnectionParams","caller: AsyncCaller","GoogleAuth","options: AsyncCallerCallOptions","fields: RemoveDatapointParams","datapointIds: string[]","data: RemoveDatapointRequest","fields: UpsertDatapointParams","datapoints: IndexDatapoint[]","data: UpsertDatapointRequest","params: FindNeighborsConnectionParams","request: FindNeighborsRequest","VectorStore","embeddings: EmbeddingsInterface","args: MatchingEngineArgs","AsyncCaller","indexClientParams: IndexEndpointConnectionParams","removeClientParams: RemoveDatapointParams","upsertClientParams: UpsertDatapointParams","documents: Document[]","texts: string[]","vectors: number[][]","docsToStore: Record<string, Document>","documentMetadata: Record<string, any>","prefix: string","m: Record<string, any>","ret: Record<string, string[]>","stringArrays: Record<string, string[]>","flatMetadata: metadataType","metadata: metadataType","restrictions: this[\"FilterType\"]","restriction: Restriction","vector: number[]","document: IdDocument","ret: IndexDatapoint","params: MatchingEngineDeleteParams","query: number[]","k: number","filter?: this[\"FilterType\"]","requestQuery: FindNeighborsRequestQuery","findNeighborsParams: FindNeighborsConnectionParams","ret: [Document, number][]","doc: IdDocument","response: IndexEndpointResponse","metadatas: object[] | object","dbConfig: MatchingEngineArgs","docs: Document[]"],"sources":["../../src/vectorstores/googlevertexai.ts"],"sourcesContent":["import * as uuid from \"uuid\";\nimport flatten from \"flat\";\nimport { GoogleAuth, GoogleAuthOptions } from \"google-auth-library\";\nimport { VectorStore } from \"@langchain/core/vectorstores\";\nimport type { EmbeddingsInterface } from \"@langchain/core/embeddings\";\nimport { Document, DocumentInput } from \"@langchain/core/documents\";\nimport {\n AsyncCaller,\n AsyncCallerCallOptions,\n AsyncCallerParams,\n} from \"@langchain/core/utils/async_caller\";\n\nimport { GoogleVertexAIConnection } from \"../utils/googlevertexai-connection.js\";\nimport { Docstore } from \"../stores/doc/base.js\";\nimport {\n GoogleVertexAIConnectionParams,\n GoogleResponse,\n GoogleAbstractedClientOpsMethod,\n} from \"../types/googlevertexai-types.js\";\n\n/**\n * Allows us to create IdDocument classes that contain the ID.\n */\nexport interface IdDocumentInput extends DocumentInput {\n id?: string;\n}\n\n/**\n * A Document that optionally includes the ID of the document.\n */\nexport class IdDocument extends Document implements IdDocumentInput {\n id?: string;\n\n constructor(fields: IdDocumentInput) {\n super(fields);\n this.id = fields.id;\n }\n}\n\ninterface IndexEndpointConnectionParams\n extends GoogleVertexAIConnectionParams<GoogleAuthOptions> {\n indexEndpoint: string;\n}\n\ninterface DeployedIndex {\n id: string;\n index: string;\n // There are other attributes, but we don't care about them right now\n}\n\ninterface IndexEndpointResponse extends GoogleResponse {\n data: {\n deployedIndexes: DeployedIndex[];\n publicEndpointDomainName: string;\n // There are other attributes, but we don't care about them right now\n };\n}\n\nclass IndexEndpointConnection extends GoogleVertexAIConnection<\n AsyncCallerCallOptions,\n IndexEndpointResponse,\n GoogleAuthOptions\n> {\n indexEndpoint: string;\n\n constructor(fields: IndexEndpointConnectionParams, caller: AsyncCaller) {\n super(fields, caller, new GoogleAuth(fields.authOptions));\n\n this.indexEndpoint = fields.indexEndpoint;\n }\n\n async buildUrl(): Promise<string> {\n const projectId = await this.client.getProjectId();\n const url = `https://${this.endpoint}/${this.apiVersion}/projects/${projectId}/locations/${this.location}/indexEndpoints/${this.indexEndpoint}`;\n return url;\n }\n\n buildMethod(): GoogleAbstractedClientOpsMethod {\n return \"GET\";\n }\n\n async request(\n options: AsyncCallerCallOptions\n ): Promise<IndexEndpointResponse> {\n return this._request(undefined, options);\n }\n}\n\n/**\n * Used to represent parameters that are necessary to delete documents\n * from the matching engine. These must be a list of string IDs\n */\nexport interface MatchingEngineDeleteParams {\n ids: string[];\n}\n\ninterface RemoveDatapointParams\n extends GoogleVertexAIConnectionParams<GoogleAuthOptions> {\n index: string;\n}\n\ninterface RemoveDatapointRequest {\n datapointIds: string[];\n}\n\ninterface RemoveDatapointResponse extends GoogleResponse {\n // Should be empty\n}\n\nclass RemoveDatapointConnection extends GoogleVertexAIConnection<\n AsyncCallerCallOptions,\n RemoveDatapointResponse,\n GoogleAuthOptions\n> {\n index: string;\n\n constructor(fields: RemoveDatapointParams, caller: AsyncCaller) {\n super(fields, caller, new GoogleAuth(fields.authOptions));\n\n this.index = fields.index;\n }\n\n async buildUrl(): Promise<string> {\n const projectId = await this.client.getProjectId();\n const url = `https://${this.endpoint}/${this.apiVersion}/projects/${projectId}/locations/${this.location}/indexes/${this.index}:removeDatapoints`;\n return url;\n }\n\n buildMethod(): GoogleAbstractedClientOpsMethod {\n return \"POST\";\n }\n\n async request(\n datapointIds: string[],\n options: AsyncCallerCallOptions\n ): Promise<RemoveDatapointResponse> {\n const data: RemoveDatapointRequest = {\n datapointIds,\n };\n return this._request(data, options);\n }\n}\n\ninterface UpsertDatapointParams\n extends GoogleVertexAIConnectionParams<GoogleAuthOptions> {\n index: string;\n}\n\nexport interface Restriction {\n namespace: string;\n allowList?: string[];\n denyList?: string[];\n}\n\ninterface CrowdingTag {\n crowdingAttribute: string;\n}\n\ninterface IndexDatapoint {\n datapointId: string;\n featureVector: number[];\n restricts?: Restriction[];\n crowdingTag?: CrowdingTag;\n}\n\ninterface UpsertDatapointRequest {\n datapoints: IndexDatapoint[];\n}\n\ninterface UpsertDatapointResponse extends GoogleResponse {\n // Should be empty\n}\n\nclass UpsertDatapointConnection extends GoogleVertexAIConnection<\n AsyncCallerCallOptions,\n UpsertDatapointResponse,\n GoogleAuthOptions\n> {\n index: string;\n\n constructor(fields: UpsertDatapointParams, caller: AsyncCaller) {\n super(fields, caller, new GoogleAuth(fields.authOptions));\n\n this.index = fields.index;\n }\n\n async buildUrl(): Promise<string> {\n const projectId = await this.client.getProjectId();\n const url = `https://${this.endpoint}/${this.apiVersion}/projects/${projectId}/locations/${this.location}/indexes/${this.index}:upsertDatapoints`;\n return url;\n }\n\n buildMethod(): GoogleAbstractedClientOpsMethod {\n return \"POST\";\n }\n\n async request(\n datapoints: IndexDatapoint[],\n options: AsyncCallerCallOptions\n ): Promise<UpsertDatapointResponse> {\n const data: UpsertDatapointRequest = {\n datapoints,\n };\n return this._request(data, options);\n }\n}\n\ninterface FindNeighborsConnectionParams\n extends GoogleVertexAIConnectionParams<GoogleAuthOptions> {\n indexEndpoint: string;\n\n deployedIndexId: string;\n}\n\ninterface FindNeighborsRequestQuery {\n datapoint: {\n datapointId: string;\n featureVector: number[];\n restricts?: Restriction[];\n };\n neighborCount: number;\n}\n\ninterface FindNeighborsRequest {\n deployedIndexId: string;\n queries: FindNeighborsRequestQuery[];\n}\n\ninterface FindNeighborsResponseNeighbor {\n datapoint: {\n datapointId: string;\n crowdingTag: {\n crowdingTagAttribute: string;\n };\n };\n distance: number;\n}\n\ninterface FindNeighborsResponseNearestNeighbor {\n id: string;\n neighbors: FindNeighborsResponseNeighbor[];\n}\n\ninterface FindNeighborsResponse extends GoogleResponse {\n data: {\n nearestNeighbors: FindNeighborsResponseNearestNeighbor[];\n };\n}\n\nclass FindNeighborsConnection\n extends GoogleVertexAIConnection<\n AsyncCallerCallOptions,\n FindNeighborsResponse,\n GoogleAuthOptions\n >\n implements FindNeighborsConnectionParams\n{\n indexEndpoint: string;\n\n deployedIndexId: string;\n\n constructor(params: FindNeighborsConnectionParams, caller: AsyncCaller) {\n super(params, caller, new GoogleAuth(params.authOptions));\n\n this.indexEndpoint = params.indexEndpoint;\n this.deployedIndexId = params.deployedIndexId;\n }\n\n async buildUrl(): Promise<string> {\n const projectId = await this.client.getProjectId();\n const url = `https://${this.endpoint}/${this.apiVersion}/projects/${projectId}/locations/${this.location}/indexEndpoints/${this.indexEndpoint}:findNeighbors`;\n return url;\n }\n\n buildMethod(): GoogleAbstractedClientOpsMethod {\n return \"POST\";\n }\n\n async request(\n request: FindNeighborsRequest,\n options: AsyncCallerCallOptions\n ): Promise<FindNeighborsResponse> {\n return this._request(request, options);\n }\n}\n\n/**\n * Information about the Matching Engine public API endpoint.\n * Primarily exported to allow for testing.\n */\nexport interface PublicAPIEndpointInfo {\n apiEndpoint?: string;\n\n deployedIndexId?: string;\n}\n\n/**\n * Parameters necessary to configure the Matching Engine.\n */\nexport interface MatchingEngineArgs\n extends GoogleVertexAIConnectionParams<GoogleAuthOptions>,\n IndexEndpointConnectionParams,\n UpsertDatapointParams {\n docstore: Docstore;\n\n callerParams?: AsyncCallerParams;\n\n callerOptions?: AsyncCallerCallOptions;\n\n apiEndpoint?: string;\n\n deployedIndexId?: string;\n}\n\n/**\n * A class that represents a connection to a Google Vertex AI Matching Engine\n * instance.\n */\nexport class MatchingEngine extends VectorStore implements MatchingEngineArgs {\n declare FilterType: Restriction[];\n\n /**\n * Docstore that retains the document, stored by ID\n */\n docstore: Docstore;\n\n /**\n * The host to connect to for queries and upserts.\n */\n apiEndpoint: string;\n\n apiVersion = \"v1\";\n\n endpoint = \"us-central1-aiplatform.googleapis.com\";\n\n location = \"us-central1\";\n\n /**\n * The id for the index endpoint\n */\n indexEndpoint: string;\n\n /**\n * The id for the index\n */\n index: string;\n\n /**\n * Explicitly set Google Auth credentials if you cannot get them from google auth application-default login\n * This is useful for serverless or autoscaling environments like Fargate\n */\n authOptions: GoogleAuthOptions;\n\n /**\n * The id for the \"deployed index\", which is an identifier in the\n * index endpoint that references the index (but is not the index id)\n */\n deployedIndexId: string;\n\n callerParams: AsyncCallerParams;\n\n callerOptions: AsyncCallerCallOptions;\n\n caller: AsyncCaller;\n\n indexEndpointClient: IndexEndpointConnection;\n\n removeDatapointClient: RemoveDatapointConnection;\n\n upsertDatapointClient: UpsertDatapointConnection;\n\n constructor(embeddings: EmbeddingsInterface, args: MatchingEngineArgs) {\n super(embeddings, args);\n\n this.embeddings = embeddings;\n this.docstore = args.docstore;\n\n this.apiEndpoint = args.apiEndpoint ?? this.apiEndpoint;\n this.deployedIndexId = args.deployedIndexId ?? this.deployedIndexId;\n\n this.apiVersion = args.apiVersion ?? this.apiVersion;\n this.endpoint = args.endpoint ?? this.endpoint;\n this.location = args.location ?? this.location;\n this.indexEndpoint = args.indexEndpoint ?? this.indexEndpoint;\n this.index = args.index ?? this.index;\n this.authOptions = args.authOptions ?? this.authOptions;\n\n this.callerParams = args.callerParams ?? this.callerParams;\n this.callerOptions = args.callerOptions ?? this.callerOptions;\n this.caller = new AsyncCaller(this.callerParams || {});\n\n const indexClientParams: IndexEndpointConnectionParams = {\n endpoint: this.endpoint,\n location: this.location,\n apiVersion: this.apiVersion,\n indexEndpoint: this.indexEndpoint,\n authOptions: this.authOptions,\n };\n this.indexEndpointClient = new IndexEndpointConnection(\n indexClientParams,\n this.caller\n );\n\n const removeClientParams: RemoveDatapointParams = {\n endpoint: this.endpoint,\n location: this.location,\n apiVersion: this.apiVersion,\n index: this.index,\n authOptions: this.authOptions,\n };\n this.removeDatapointClient = new RemoveDatapointConnection(\n removeClientParams,\n this.caller\n );\n\n const upsertClientParams: UpsertDatapointParams = {\n endpoint: this.endpoint,\n location: this.location,\n apiVersion: this.apiVersion,\n index: this.index,\n authOptions: this.authOptions,\n };\n this.upsertDatapointClient = new UpsertDatapointConnection(\n upsertClientParams,\n this.caller\n );\n }\n\n _vectorstoreType(): string {\n return \"googlevertexai\";\n }\n\n async addDocuments(documents: Document[]): Promise<void> {\n const texts: string[] = documents.map((doc) => doc.pageContent);\n const vectors: number[][] = await this.embeddings.embedDocuments(texts);\n return this.addVectors(vectors, documents);\n }\n\n async addVectors(vectors: number[][], documents: Document[]): Promise<void> {\n if (vectors.length !== documents.length) {\n throw new Error(`Vectors and metadata must have the same length`);\n }\n const datapoints: IndexDatapoint[] = vectors.map((vector, idx) =>\n this.buildDatapoint(vector, documents[idx])\n );\n const options = {};\n const response = await this.upsertDatapointClient.request(\n datapoints,\n options\n );\n if (Object.keys(response?.data ?? {}).length === 0) {\n // Nothing in the response in the body means we saved it ok\n const idDoc = documents as IdDocument[];\n const docsToStore: Record<string, Document> = {};\n idDoc.forEach((doc) => {\n if (doc.id) {\n docsToStore[doc.id] = doc;\n }\n });\n await this.docstore.add(docsToStore);\n }\n }\n\n // TODO: Refactor this into a utility type and use with pinecone as well?\n // eslint-disable-next-line @typescript-eslint/no-explicit-any\n cleanMetadata(documentMetadata: Record<string, any>): {\n [key: string]: string | number | boolean | string[] | null;\n } {\n type metadataType = {\n [key: string]: string | number | boolean | string[] | null;\n };\n\n function getStringArrays(\n prefix: string,\n // eslint-disable-next-line @typescript-eslint/no-explicit-any\n m: Record<string, any>\n ): Record<string, string[]> {\n let ret: Record<string, string[]> = {};\n\n Object.keys(m).forEach((key) => {\n const newPrefix = prefix.length > 0 ? `${prefix}.${key}` : key;\n const val = m[key];\n if (!val) {\n // Ignore it\n } else if (Array.isArray(val)) {\n // Make sure everything in the array is a string\n ret[newPrefix] = val.map((v) => `${v}`);\n } else if (typeof val === \"object\") {\n const subArrays = getStringArrays(newPrefix, val);\n ret = { ...ret, ...subArrays };\n }\n });\n\n return ret;\n }\n\n const stringArrays: Record<string, string[]> = getStringArrays(\n \"\",\n documentMetadata\n );\n\n const flatMetadata: metadataType = flatten(documentMetadata);\n Object.keys(flatMetadata).forEach((key) => {\n Object.keys(stringArrays).forEach((arrayKey) => {\n const matchKey = `${arrayKey}.`;\n if (key.startsWith(matchKey)) {\n delete flatMetadata[key];\n }\n });\n });\n\n const metadata: metadataType = {\n ...flatMetadata,\n ...stringArrays,\n };\n return metadata;\n }\n\n /**\n * Given the metadata from a document, convert it to an array of Restriction\n * objects that may be passed to the Matching Engine and stored.\n * The default implementation flattens any metadata and includes it as\n * an \"allowList\". Subclasses can choose to convert some of these to\n * \"denyList\" items or to add additional restrictions (for example, to format\n * dates into a different structure or to add additional restrictions\n * based on the date).\n * @param documentMetadata - The metadata from a document\n * @returns a Restriction[] (or an array of a subclass, from the FilterType)\n */\n metadataToRestrictions(\n // eslint-disable-next-line @typescript-eslint/no-explicit-any\n documentMetadata: Record<string, any>\n ): this[\"FilterType\"] {\n const metadata = this.cleanMetadata(documentMetadata);\n\n const restrictions: this[\"FilterType\"] = [];\n for (const key of Object.keys(metadata)) {\n // Make sure the value is an array (or that we'll ignore it)\n let valArray;\n const val = metadata[key];\n if (val === null) {\n valArray = null;\n } else if (Array.isArray(val) && val.length > 0) {\n valArray = val;\n } else {\n valArray = [`${val}`];\n }\n\n // Add to the restrictions if we do have a valid value\n if (valArray) {\n // Determine if this key is for the allowList or denyList\n // TODO: get which ones should be on the deny list\n const listType = \"allowList\";\n\n // Create the restriction\n const restriction: Restriction = {\n namespace: key,\n [listType]: valArray,\n };\n\n // Add it to the restriction list\n restrictions.push(restriction);\n }\n }\n return restrictions;\n }\n\n /**\n * Create an index datapoint for the vector and document id.\n * If an id does not exist, create it and set the document to its value.\n * @param vector\n * @param document\n */\n buildDatapoint(vector: number[], document: IdDocument): IndexDatapoint {\n if (!document.id) {\n document.id = uuid.v4();\n }\n const ret: IndexDatapoint = {\n datapointId: document.id,\n featureVector: vector,\n };\n const restrictions = this.metadataToRestrictions(document.metadata);\n if (restrictions?.length > 0) {\n ret.restricts = restrictions;\n }\n return ret;\n }\n\n async delete(params: MatchingEngineDeleteParams): Promise<void> {\n const options = {};\n await this.removeDatapointClient.request(params.ids, options);\n }\n\n async similaritySearchVectorWithScore(\n query: number[],\n k: number,\n filter?: this[\"FilterType\"]\n ): Promise<[Document, number][]> {\n // Format the query into the request\n const deployedIndexId = await this.getDeployedIndexId();\n const requestQuery: FindNeighborsRequestQuery = {\n neighborCount: k,\n datapoint: {\n datapointId: `0`,\n featureVector: query,\n },\n };\n if (filter) {\n requestQuery.datapoint.restricts = filter;\n }\n const request: FindNeighborsRequest = {\n deployedIndexId,\n queries: [requestQuery],\n };\n\n // Build the connection.\n // Has to be done here, since we defer getting the endpoint until\n // we need it.\n const apiEndpoint = await this.getPublicAPIEndpoint();\n const findNeighborsParams: FindNeighborsConnectionParams = {\n endpoint: apiEndpoint,\n indexEndpoint: this.indexEndpoint,\n apiVersion: this.apiVersion,\n location: this.location,\n deployedIndexId,\n authOptions: this.authOptions,\n };\n const connection = new FindNeighborsConnection(\n findNeighborsParams,\n this.caller\n );\n\n // Make the call\n const options = {};\n const response = await connection.request(request, options);\n\n // Get the document for each datapoint id and return them\n const nearestNeighbors = response?.data?.nearestNeighbors ?? [];\n const nearestNeighbor = nearestNeighbors[0];\n const neighbors = nearestNeighbor?.neighbors ?? [];\n const ret: [Document, number][] = await Promise.all(\n neighbors.map(async (neighbor) => {\n const id = neighbor?.datapoint?.datapointId;\n const distance = neighbor?.distance;\n let doc: IdDocument;\n try {\n doc = await this.docstore.search(id);\n } catch (xx) {\n // Documents that are in the index are returned, even if they\n // are not in the document store, to allow for some way to get\n // the id so they can be deleted.\n console.error(xx);\n console.warn(\n [\n `Document with id \"${id}\" is missing from the backing docstore.`,\n `This can occur if you clear the docstore without deleting from the corresponding Matching Engine index.`,\n `To resolve this, you should call .delete() with this id as part of the \"ids\" parameter.`,\n ].join(\"\\n\")\n );\n doc = new Document({ pageContent: `Missing document ${id}` });\n }\n doc.id ??= id;\n return [doc, distance];\n })\n );\n\n return ret;\n }\n\n /**\n * For this index endpoint, figure out what API Endpoint URL and deployed\n * index ID should be used to do upserts and queries.\n * Also sets the `apiEndpoint` and `deployedIndexId` property for future use.\n * @return The URL\n */\n async determinePublicAPIEndpoint(): Promise<PublicAPIEndpointInfo> {\n const response: IndexEndpointResponse =\n await this.indexEndpointClient.request(this.callerOptions);\n\n // Get the endpoint\n const publicEndpointDomainName = response?.data?.publicEndpointDomainName;\n this.apiEndpoint = publicEndpointDomainName;\n\n // Determine which of the deployed indexes match the index id\n // and get the deployed index id. The list of deployed index ids\n // contain the \"index name\" or path, but not the index id by itself,\n // so we need to extract it from the name\n const indexPathPattern = /projects\\/.+\\/locations\\/.+\\/indexes\\/(.+)$/;\n const deployedIndexes = response?.data?.deployedIndexes ?? [];\n const deployedIndex = deployedIndexes.find((index) => {\n const deployedIndexPath = index.index;\n const match = deployedIndexPath.match(indexPathPattern);\n if (match) {\n const [, potentialIndexId] = match;\n if (potentialIndexId === this.index) {\n return true;\n }\n }\n return false;\n });\n if (deployedIndex) {\n this.deployedIndexId = deployedIndex.id;\n }\n\n return {\n apiEndpoint: this.apiEndpoint,\n deployedIndexId: this.deployedIndexId,\n };\n }\n\n async getPublicAPIEndpoint(): Promise<string> {\n return (\n this.apiEndpoint ?? (await this.determinePublicAPIEndpoint()).apiEndpoint\n );\n }\n\n async getDeployedIndexId(): Promise<string> {\n return (\n this.deployedIndexId ??\n (await this.determinePublicAPIEndpoint()).deployedIndexId\n );\n }\n\n static async fromTexts(\n texts: string[],\n metadatas: object[] | object,\n embeddings: EmbeddingsInterface,\n dbConfig: MatchingEngineArgs\n ): Promise<VectorStore> {\n const docs: Document[] = texts.map(\n (text, index): Document => ({\n pageContent: text,\n metadata: Array.isArray(metadatas) ? metadatas[index] : metadatas,\n })\n );\n return this.fromDocuments(docs, embeddings, dbConfig);\n }\n\n static async fromDocuments(\n docs: Document[],\n embeddings: EmbeddingsInterface,\n dbConfig: MatchingEngineArgs\n ): Promise<VectorStore> {\n const ret = new MatchingEngine(embeddings, dbConfig);\n await ret.addDocuments(docs);\n return ret;\n 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