{"version":3,"file":"chroma.mjs","names":["#opts","#client","#collectionCache"],"sources":["../../../src/batteries/vector/chroma/index.ts"],"sourcesContent":["/**\n * @module @nhtio/adk/batteries/vector/chroma\n */\n\nimport { normalizeScore } from '../helpers'\nimport { BaseVectorStore } from '../contract'\nimport { validateRecords } from '../validation'\nimport { isFilterCondition, isRawFilter, isFilterGroup } from '../filters'\nimport {\n E_VECTOR_STORE_DRIVER_UNAVAILABLE,\n E_VECTOR_STORE_CONNECTION_FAILED,\n E_VECTOR_STORE_COLLECTION_FAILED,\n E_VECTOR_STORE_UPSERT_FAILED,\n E_VECTOR_STORE_SEARCH_FAILED,\n E_VECTOR_STORE_DELETE_FAILED,\n E_VECTOR_STORE_DIMENSION_MISMATCH,\n E_VECTOR_STORE_UNSUPPORTED_FILTER_OPERATOR,\n} from '../exceptions'\nimport type { VectorFilter } from '../filters'\nimport type { SearchPlan, UpsertPlan, DeletePlan, CollectionSpec } from '../plan'\nimport type {\n VectorMatch,\n VectorMetadata,\n BaseVectorStoreOptions,\n VectorStoreCapabilities,\n} from '../types'\n\nexport interface ChromaVectorStoreOptions extends BaseVectorStoreOptions {\n /** Connection and authentication parameters for the backend. */\n connection?: { url?: string; host?: string; port?: number; ssl?: boolean }\n}\n\nconst getChromaClient = async () => {\n try {\n const mod = await import('chromadb')\n return mod.ChromaClient\n } catch {\n throw new E_VECTOR_STORE_DRIVER_UNAVAILABLE(['chromadb'])\n }\n}\n\nconst getSpace = (metric: string): string => {\n if (metric === 'cosine') return 'cosine'\n if (metric === 'euclidean') return 'l2'\n if (metric === 'dot') return 'ip'\n return 'cosine'\n}\n\n/** Translate a neutral {@link VectorFilter} into Chroma's `where` filter object. */\nexport const translateChromaWhere = (\n filter?: VectorFilter\n): Record | undefined => {\n if (!filter) return undefined\n if (isRawFilter(filter)) {\n if (filter.$dialect === 'chroma') {\n return filter.$raw as Record\n }\n throw new E_VECTOR_STORE_UNSUPPORTED_FILTER_OPERATOR(['chroma', String(filter.$dialect)])\n }\n if (isFilterCondition(filter)) {\n const { field, op, value } = filter\n if (value === undefined) {\n throw new E_VECTOR_STORE_UNSUPPORTED_FILTER_OPERATOR(['chroma', op])\n }\n if (op === 'eq') {\n return { [field]: { $eq: value } }\n }\n if (op === 'ne') {\n return { [field]: { $ne: value } }\n }\n if (op === 'gt') {\n return { [field]: { $gt: value } }\n }\n if (op === 'gte') {\n return { [field]: { $gte: value } }\n }\n if (op === 'lt') {\n return { [field]: { $lt: value } }\n }\n if (op === 'lte') {\n return { [field]: { $lte: value } }\n }\n if (op === 'in') {\n return { [field]: { $in: value } }\n }\n if (op === 'nin') {\n return { [field]: { $nin: value } }\n }\n if (op === 'exists' || op === 'contains') {\n throw new E_VECTOR_STORE_UNSUPPORTED_FILTER_OPERATOR(['chroma', op])\n }\n throw new E_VECTOR_STORE_UNSUPPORTED_FILTER_OPERATOR(['chroma', op])\n }\n if (isFilterGroup(filter)) {\n const { and, or, not } = filter\n if (and) {\n const children = and\n .map((f) => translateChromaWhere(f) as Record)\n .filter((c) => c !== undefined)\n if (children.length === 0) return undefined\n if (children.length === 1) return children[0]\n return { $and: children }\n }\n if (or) {\n const children = or\n .map((f) => translateChromaWhere(f) as Record)\n .filter((c) => c !== undefined)\n if (children.length === 0) return undefined\n if (children.length === 1) return children[0]\n return { $or: children }\n }\n if (not) {\n throw new E_VECTOR_STORE_UNSUPPORTED_FILTER_OPERATOR(['chroma', 'not'])\n }\n return undefined\n }\n return undefined\n}\n\nexport class ChromaVectorStore extends BaseVectorStore {\n readonly capabilities: VectorStoreCapabilities = {\n transactions: false,\n namedVectors: false,\n rename: true,\n rawSql: false,\n builtInEncoding: false,\n // Strongly consistent on resolve; the option is a no-op.\n consistency: { configurable: false, default: 'strong', modes: ['strong'] },\n }\n #client: any | null = null\n #collectionCache: Map = new Map()\n get #opts() {\n return this.options as ChromaVectorStoreOptions\n }\n\n /** Static availability probe: whether this adapter's runtime driver can load in the current environment. */\n static isAvailable(): boolean {\n return typeof process !== 'undefined'\n }\n isAvailable(): boolean {\n return typeof process !== 'undefined'\n }\n\n async connect(): Promise {\n if (this.#client) return\n const ChromaClient = await getChromaClient()\n const c = this.#opts.connection || {}\n let host: string | undefined\n let port: number | undefined\n let ssl: boolean = false\n\n if (c.url) {\n const url = new URL(c.url)\n host = url.hostname\n port = url.port ? Number.parseInt(url.port, 10) : url.protocol === 'https:' ? 443 : 80\n ssl = url.protocol === 'https:'\n } else {\n host = c.host\n port = c.port\n ssl = c.ssl || false\n }\n\n const path =\n host && port !== undefined\n ? `${ssl ? 'https://' : 'http://'}${host}${port === 80 || port === 443 ? '' : ':' + port}`\n : undefined\n\n try {\n this.#client = new ChromaClient({ path })\n } catch (err) {\n throw new E_VECTOR_STORE_CONNECTION_FAILED([String(err)])\n }\n }\n\n async close(): Promise {\n this.#client = null\n this.#collectionCache.clear()\n }\n\n /** Resolve (and cache) the underlying Chroma collection handle for `name`. */\n async getCollection(name: string): Promise {\n let collection = this.#collectionCache.get(name)\n if (collection) return collection\n if (!this.#client) await this.connect()\n const metric = this.#opts.metric ?? 'cosine'\n collection = await this.#client.getOrCreateCollection({\n name,\n metadata: { 'hnsw:space': getSpace(metric) },\n })\n this.#collectionCache.set(name, collection)\n return collection\n }\n\n async createCollection(spec: CollectionSpec, ifNotExists: boolean): Promise {\n const name = spec.collection\n if (ifNotExists && (await this.hasCollection(name))) return\n if (await this.hasCollection(name)) {\n throw new E_VECTOR_STORE_COLLECTION_FAILED(['create', 'exists'])\n }\n try {\n await this.connect()\n const metric = spec.vector.metric ?? 'cosine'\n await this.#client!.getOrCreateCollection({\n name,\n metadata: { 'hnsw:space': getSpace(metric) },\n })\n this.#collectionCache.set(name, null)\n } catch (err) {\n throw new E_VECTOR_STORE_COLLECTION_FAILED(['createCollection', String(err)])\n }\n }\n\n async dropCollection(collection: string, ifExists: boolean): Promise {\n if (ifExists && !(await this.hasCollection(collection))) return\n try {\n await this.connect()\n await this.#client!.deleteCollection({ name: collection })\n this.#collectionCache.delete(collection)\n } catch (err) {\n throw new E_VECTOR_STORE_COLLECTION_FAILED(['dropCollection', String(err)])\n }\n }\n\n async hasCollection(collection: string): Promise {\n if (!this.#client) await this.connect()\n try {\n const collections = await this.#client!.listCollections()\n for (const c of collections) {\n if (typeof c === 'object' ? c.name === collection : c === collection) {\n return true\n }\n }\n return false\n } catch {\n return false\n }\n }\n\n async renameCollection(from: string, to: string): Promise {\n try {\n const collection = await this.getCollection(from)\n await collection.modify({ name: to })\n const cached = this.#collectionCache.get(from)\n this.#collectionCache.delete(from)\n if (cached) {\n this.#collectionCache.set(to, cached)\n }\n } catch (err) {\n throw new E_VECTOR_STORE_COLLECTION_FAILED(['renameCollection', String(err)])\n }\n }\n\n async executeUpsert(plan: UpsertPlan): Promise {\n if (plan.records.length === 0) return\n validateRecords(plan.records)\n const collection = await this.getCollection(plan.collection)\n const expected = this.#opts.dimensions\n const ids: string[] = []\n const embeddings: number[][] = []\n const documents: string[] = []\n const metadatas: VectorMetadata[] = []\n\n for (const r of plan.records) {\n let vector = r.vector\n if (!vector && r.document) {\n const [v] = await this.encode([r.document], 'document')\n vector = v\n }\n if (!vector) {\n throw new E_VECTOR_STORE_UPSERT_FAILED(['Record missing vector and document'])\n }\n if (expected !== undefined && vector.length !== expected) {\n throw new E_VECTOR_STORE_DIMENSION_MISMATCH([expected, vector.length])\n }\n ids.push(r.id)\n embeddings.push(vector)\n documents.push(r.document ?? '')\n const md = { ...(r.metadata ?? {}), internalId: r.id }\n metadatas.push(md)\n }\n\n try {\n await collection.upsert({ ids, embeddings, documents, metadatas })\n } catch (err) {\n throw new E_VECTOR_STORE_UPSERT_FAILED([String(err)])\n }\n }\n\n async executeSearch(plan: SearchPlan): Promise {\n const collection = await this.getCollection(plan.collection)\n const metric = this.#opts.metric ?? 'cosine'\n let queryVector: number[] | undefined\n\n if (plan.near) {\n if ('vector' in plan.near) {\n queryVector = plan.near.vector\n } else if ('serverText' in plan.near) {\n const [v] = await this.encode([plan.near.serverText], 'query')\n queryVector = v\n } else if ('id' in plan.near) {\n const res = await collection.get({ ids: [plan.near.id], include: ['embeddings'] })\n if (!res.ids || res.ids.length === 0) {\n throw new E_VECTOR_STORE_SEARCH_FAILED(['Referenced id not found: ' + plan.near.id])\n }\n const embeddings = res.embeddings || []\n if (!embeddings || embeddings.length === 0 || !embeddings[0]) {\n throw new E_VECTOR_STORE_SEARCH_FAILED(['Referenced id has no vector: ' + plan.near.id])\n }\n queryVector = embeddings[0]\n }\n }\n\n const where = translateChromaWhere(plan.filter)\n\n let results: any\n if (queryVector) {\n try {\n results = await collection.query({\n queryEmbeddings: [queryVector],\n nResults: plan.topK,\n where,\n include: ['documents', 'metadatas', 'distances', 'embeddings'],\n })\n } catch (err) {\n throw new E_VECTOR_STORE_SEARCH_FAILED([String(err)])\n }\n } else {\n try {\n results = await collection.get({\n where,\n limit: plan.topK,\n include: ['documents', 'metadatas', 'embeddings'],\n })\n } catch (err) {\n throw new E_VECTOR_STORE_SEARCH_FAILED([String(err)])\n }\n }\n\n const proj = plan.projection\n const out: VectorMatch[] = []\n // `query()` returns per-query nested arrays (`ids: [[...]]`); `get()` (the filter-scan path)\n // returns flat arrays (`ids: [...]`). 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[]) : col\n }\n const ids = unwrap(results.ids)\n const documents = unwrap(results.documents)\n const metadatas = unwrap(results.metadatas)\n const embeddings = unwrap(results.embeddings)\n const distances = unwrap(results.distances)\n\n const start = plan.offset || 0\n const limit = plan.topK\n\n for (let i = start; i < Math.min(ids.length, start + limit); i++) {\n const match: VectorMatch = {}\n if (proj.id) {\n match.id = ids[i]\n }\n if (proj.vector && embeddings[i]) {\n match.vector = embeddings[i]\n }\n if (proj.document) {\n match.document = documents[i] ?? undefined\n }\n if (proj.metadata && metadatas[i]) {\n const rawMeta = metadatas[i] as VectorMetadata\n const { internalId, ...rest } = rawMeta\n match.metadata = rest\n }\n if (queryVector && distances && distances[i] !== undefined) {\n match.score = normalizeScore(distances[i], metric, 'distance')\n }\n out.push(match)\n }\n\n return out\n }\n\n async executeDelete(plan: DeletePlan): Promise {\n const collection = await 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