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280 lines
9.8 KiB
TypeScript
280 lines
9.8 KiB
TypeScript
import { type NextRequest, NextResponse } from 'next/server'
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import { v1KnowledgeSearchContract } from '@/lib/api/contracts/v1/knowledge'
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import { parseRequest } from '@/lib/api/server'
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import { checkActorUsageLimits } from '@/lib/billing/calculations/usage-monitor'
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import { withRouteHandler } from '@/lib/core/utils/with-route-handler'
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import { ALL_TAG_SLOTS } from '@/lib/knowledge/constants'
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import { recordSearchEmbeddingUsage } from '@/lib/knowledge/embeddings'
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import { getDocumentTagDefinitions } from '@/lib/knowledge/tags/service'
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import { buildUndefinedTagsError, validateTagValue } from '@/lib/knowledge/tags/utils'
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import type { StructuredFilter } from '@/lib/knowledge/types'
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import {
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generateSearchEmbedding,
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getDocumentMetadataByIds,
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getQueryStrategy,
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handleTagAndVectorSearch,
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handleTagOnlySearch,
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handleVectorOnlySearch,
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type SearchResult,
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} from '@/app/api/knowledge/search/utils'
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import { checkKnowledgeBaseAccess, type KnowledgeBaseAccessResult } from '@/app/api/knowledge/utils'
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import { handleError } from '@/app/api/v1/knowledge/utils'
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import { authenticateRequest, validateWorkspaceAccess } from '@/app/api/v1/middleware'
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export const dynamic = 'force-dynamic'
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export const revalidate = 0
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/** POST /api/v1/knowledge/search — Vector search across knowledge bases. */
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export const POST = withRouteHandler(async (request: NextRequest) => {
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const auth = await authenticateRequest(request, 'knowledge-search')
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if (auth instanceof NextResponse) return auth
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const { requestId, userId, rateLimit } = auth
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try {
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const parsed = await parseRequest(v1KnowledgeSearchContract, request, {})
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if (!parsed.success) return parsed.response
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const { workspaceId, topK, query, tagFilters } = parsed.data.body
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const accessError = await validateWorkspaceAccess(rateLimit, userId, workspaceId)
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if (accessError) return accessError
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// A query incurs hosted embedding (+ optional rerank) cost — gate the actor's
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// usage and frozen status before spending. Tag-only search is free, so skip it.
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if (query && query.trim().length > 0) {
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const usage = await checkActorUsageLimits(userId, workspaceId)
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if (usage.isExceeded) {
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return NextResponse.json(
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{ error: usage.message || 'Usage limit exceeded. Please upgrade your plan to continue.' },
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{ status: 402 }
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)
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}
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}
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const knowledgeBaseIds = Array.isArray(parsed.data.body.knowledgeBaseIds)
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? parsed.data.body.knowledgeBaseIds
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: [parsed.data.body.knowledgeBaseIds]
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const accessChecks = await Promise.all(
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knowledgeBaseIds.map((kbId) => checkKnowledgeBaseAccess(kbId, userId))
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)
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const accessibleKbs = accessChecks
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.filter(
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(ac): ac is KnowledgeBaseAccessResult =>
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ac.hasAccess === true && ac.knowledgeBase.workspaceId === workspaceId
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)
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.map((ac) => ac.knowledgeBase)
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const accessibleKbIds = accessibleKbs.map((kb) => kb.id)
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if (accessibleKbIds.length === 0) {
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return NextResponse.json(
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{ error: 'Knowledge base not found or access denied' },
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{ status: 404 }
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)
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}
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const inaccessibleKbIds = knowledgeBaseIds.filter((id) => !accessibleKbIds.includes(id))
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if (inaccessibleKbIds.length > 0) {
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return NextResponse.json(
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{ error: `Knowledge bases not found or access denied: ${inaccessibleKbIds.join(', ')}` },
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{ status: 404 }
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)
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}
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let structuredFilters: StructuredFilter[] = []
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const tagDefsCache = new Map<string, Awaited<ReturnType<typeof getDocumentTagDefinitions>>>()
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if (tagFilters && tagFilters.length > 0 && accessibleKbIds.length > 1) {
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return NextResponse.json(
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{ error: 'Tag filters are only supported when searching a single knowledge base' },
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{ status: 400 }
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)
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}
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if (tagFilters && tagFilters.length > 0 && accessibleKbIds.length > 0) {
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const kbId = accessibleKbIds[0]
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const tagDefs = await getDocumentTagDefinitions(kbId)
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tagDefsCache.set(kbId, tagDefs)
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const displayNameToTagDef: Record<string, { tagSlot: string; fieldType: string }> = {}
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tagDefs.forEach((def) => {
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displayNameToTagDef[def.displayName] = {
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tagSlot: def.tagSlot,
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fieldType: def.fieldType,
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}
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})
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const undefinedTags: string[] = []
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const typeErrors: string[] = []
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for (const filter of tagFilters) {
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const tagDef = displayNameToTagDef[filter.tagName]
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if (!tagDef) {
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undefinedTags.push(filter.tagName)
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continue
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}
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const validationError = validateTagValue(
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filter.tagName,
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String(filter.value),
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tagDef.fieldType
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)
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if (validationError) {
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typeErrors.push(validationError)
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}
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}
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if (undefinedTags.length > 0 || typeErrors.length > 0) {
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const errorParts: string[] = []
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if (undefinedTags.length > 0) {
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errorParts.push(buildUndefinedTagsError(undefinedTags))
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}
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if (typeErrors.length > 0) {
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errorParts.push(...typeErrors)
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}
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return NextResponse.json({ error: errorParts.join('\n') }, { status: 400 })
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}
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structuredFilters = tagFilters.map((filter) => {
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const tagDef = displayNameToTagDef[filter.tagName]!
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return {
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tagSlot: tagDef.tagSlot,
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fieldType: tagDef.fieldType,
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operator: filter.operator,
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value: filter.value,
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valueTo: filter.valueTo,
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}
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})
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}
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const hasQuery = query && query.trim().length > 0
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const hasFilters = structuredFilters.length > 0
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const embeddingModels = Array.from(new Set(accessibleKbs.map((kb) => kb.embeddingModel)))
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if (hasQuery && embeddingModels.length > 1) {
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return NextResponse.json(
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{
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error:
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'Selected knowledge bases use different embedding models and cannot be searched together. Search them separately.',
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},
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{ status: 400 }
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)
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}
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const queryEmbeddingModel = embeddingModels[0]
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let results: SearchResult[]
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let queryEmbeddingIsBYOK: boolean | null = null
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if (!hasQuery && hasFilters) {
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results = await handleTagOnlySearch({
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knowledgeBaseIds: accessibleKbIds,
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topK,
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structuredFilters,
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})
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} else if (hasQuery && hasFilters) {
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const strategy = getQueryStrategy(accessibleKbIds.length, topK)
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const queryEmbeddingResult = await generateSearchEmbedding(
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query!,
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queryEmbeddingModel,
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workspaceId
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)
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queryEmbeddingIsBYOK = queryEmbeddingResult.isBYOK
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const queryVector = JSON.stringify(queryEmbeddingResult.embedding)
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results = await handleTagAndVectorSearch({
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knowledgeBaseIds: accessibleKbIds,
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topK,
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structuredFilters,
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queryVector,
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distanceThreshold: strategy.distanceThreshold,
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})
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} else if (hasQuery) {
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const strategy = getQueryStrategy(accessibleKbIds.length, topK)
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const queryEmbeddingResult = await generateSearchEmbedding(
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query!,
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queryEmbeddingModel,
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workspaceId
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)
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queryEmbeddingIsBYOK = queryEmbeddingResult.isBYOK
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const queryVector = JSON.stringify(queryEmbeddingResult.embedding)
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results = await handleVectorOnlySearch({
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knowledgeBaseIds: accessibleKbIds,
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topK,
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queryVector,
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distanceThreshold: strategy.distanceThreshold,
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})
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} else {
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return NextResponse.json(
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{ error: 'Either query or tagFilters must be provided' },
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{ status: 400 }
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)
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}
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if (queryEmbeddingIsBYOK !== null) {
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await recordSearchEmbeddingUsage({
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userId,
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workspaceId,
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embeddingModel: queryEmbeddingModel,
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query: query!,
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isBYOK: queryEmbeddingIsBYOK,
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sourceReference: `v1-kb-search:${requestId}`,
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})
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}
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const tagDefsResults = await Promise.all(
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accessibleKbIds.map(async (kbId) => {
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try {
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const tagDefs = tagDefsCache.get(kbId) ?? (await getDocumentTagDefinitions(kbId))
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const map: Record<string, string> = {}
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tagDefs.forEach((def) => {
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map[def.tagSlot] = def.displayName
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})
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return { kbId, map }
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} catch {
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return { kbId, map: {} as Record<string, string> }
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}
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})
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)
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const tagDefinitionsMap: Record<string, Record<string, string>> = {}
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tagDefsResults.forEach(({ kbId, map }) => {
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tagDefinitionsMap[kbId] = map
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})
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const documentIds = results.map((r) => r.documentId)
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const documentMetadataMap = await getDocumentMetadataByIds(documentIds)
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return NextResponse.json({
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success: true,
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data: {
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results: results.map((result) => {
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const kbTagMap = tagDefinitionsMap[result.knowledgeBaseId] || {}
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const tags: Record<string, string | number | boolean | Date | null> = {}
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ALL_TAG_SLOTS.forEach((slot) => {
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const tagValue = result[slot as keyof SearchResult]
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if (tagValue !== null && tagValue !== undefined) {
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const displayName = kbTagMap[slot] || slot
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tags[displayName] = tagValue as string | number | boolean | Date | null
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}
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})
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const docMeta = documentMetadataMap[result.documentId]
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return {
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documentId: result.documentId,
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documentName: docMeta?.filename || undefined,
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sourceUrl: docMeta?.sourceUrl ?? null,
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content: result.content,
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chunkIndex: result.chunkIndex,
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metadata: tags,
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similarity: hasQuery ? 1 - result.distance : 1,
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}
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}),
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query: query || '',
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knowledgeBaseIds: accessibleKbIds,
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topK,
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totalResults: results.length,
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},
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})
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} catch (error) {
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return handleError(requestId, error, 'Failed to perform search')
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}
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})
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