Files
stack/apps/api/src/knowledge/services/search.service.ts
T
Jason Woltje 3ec2059470 feat: add semantic search with pgvector (closes #68, #69, #70)
Issues resolved:
- #68: pgvector Setup
  * Added pgvector vector index migration for knowledge_embeddings
  * Vector index uses HNSW algorithm with cosine distance
  * Optimized for 1536-dimension OpenAI embeddings

- #69: Embedding Generation Pipeline
  * Created EmbeddingService with OpenAI integration
  * Automatic embedding generation on entry create/update
  * Batch processing endpoint for existing entries
  * Async generation to avoid blocking API responses
  * Content preparation with title weighting

- #70: Semantic Search API
  * POST /api/knowledge/search/semantic - pure vector search
  * POST /api/knowledge/search/hybrid - RRF combined search
  * POST /api/knowledge/embeddings/batch - batch generation
  * Comprehensive test coverage
  * Full documentation in docs/SEMANTIC_SEARCH.md

Technical details:
- Uses OpenAI text-embedding-3-small model (1536 dims)
- HNSW index for O(log n) similarity search
- Reciprocal Rank Fusion for hybrid search
- Graceful degradation when OpenAI not configured
- Async embedding generation for performance

Configuration:
- Added OPENAI_API_KEY to .env.example
- Optional feature - disabled if API key not set
- Falls back to keyword search in hybrid mode
2026-01-30 15:19:13 -06:00

718 lines
20 KiB
TypeScript

import { Injectable } from "@nestjs/common";
import { EntryStatus, Prisma } from "@prisma/client";
import { PrismaService } from "../../prisma/prisma.service";
import type {
KnowledgeEntryWithTags,
PaginatedEntries,
} from "../entities/knowledge-entry.entity";
import { KnowledgeCacheService } from "./cache.service";
import { EmbeddingService } from "./embedding.service";
/**
* Search options for full-text search
*/
export interface SearchOptions {
status?: EntryStatus | undefined;
page?: number | undefined;
limit?: number | undefined;
}
/**
* Search result with relevance ranking
*/
export interface SearchResult extends KnowledgeEntryWithTags {
rank: number;
headline?: string | undefined;
}
/**
* Paginated search results
*/
export interface PaginatedSearchResults {
data: SearchResult[];
pagination: {
page: number;
limit: number;
total: number;
totalPages: number;
};
query: string;
}
/**
* Raw search result from PostgreSQL query
*/
interface RawSearchResult {
id: string;
workspace_id: string;
slug: string;
title: string;
content: string;
content_html: string | null;
summary: string | null;
status: EntryStatus;
visibility: string;
created_at: Date;
updated_at: Date;
created_by: string;
updated_by: string;
rank: number;
headline: string | null;
}
/**
* Service for searching knowledge entries using PostgreSQL full-text search
*/
@Injectable()
export class SearchService {
constructor(
private readonly prisma: PrismaService,
private readonly cache: KnowledgeCacheService,
private readonly embedding: EmbeddingService
) {}
/**
* Full-text search on title and content using PostgreSQL ts_vector
*
* @param query - The search query string
* @param workspaceId - The workspace to search within
* @param options - Search options (status filter, pagination)
* @returns Paginated search results ranked by relevance
*/
async search(
query: string,
workspaceId: string,
options: SearchOptions = {}
): Promise<PaginatedSearchResults> {
const page = options.page || 1;
const limit = options.limit || 20;
const offset = (page - 1) * limit;
// Sanitize and prepare the search query
const sanitizedQuery = this.sanitizeSearchQuery(query);
if (!sanitizedQuery) {
return {
data: [],
pagination: {
page,
limit,
total: 0,
totalPages: 0,
},
query,
};
}
// Check cache first
const filters = { status: options.status, page, limit };
const cached = await this.cache.getSearch(workspaceId, sanitizedQuery, filters);
if (cached) {
return cached;
}
// Build status filter
const statusFilter = options.status
? Prisma.sql`AND e.status = ${options.status}::text::"EntryStatus"`
: Prisma.sql`AND e.status != 'ARCHIVED'`;
// PostgreSQL full-text search query
// Uses ts_rank for relevance scoring with weights: title (A=1.0), content (B=0.4)
const searchResults = await this.prisma.$queryRaw<RawSearchResult[]>`
WITH search_query AS (
SELECT plainto_tsquery('english', ${sanitizedQuery}) AS query
)
SELECT
e.id,
e.workspace_id,
e.slug,
e.title,
e.content,
e.content_html,
e.summary,
e.status,
e.visibility,
e.created_at,
e.updated_at,
e.created_by,
e.updated_by,
ts_rank(
setweight(to_tsvector('english', e.title), 'A') ||
setweight(to_tsvector('english', e.content), 'B'),
sq.query
) AS rank,
ts_headline(
'english',
e.content,
sq.query,
'MaxWords=50, MinWords=25, StartSel=<mark>, StopSel=</mark>'
) AS headline
FROM knowledge_entries e, search_query sq
WHERE e.workspace_id = ${workspaceId}::uuid
${statusFilter}
AND (
to_tsvector('english', e.title) @@ sq.query
OR to_tsvector('english', e.content) @@ sq.query
)
ORDER BY rank DESC, e.updated_at DESC
LIMIT ${limit}
OFFSET ${offset}
`;
// Get total count for pagination
const countResult = await this.prisma.$queryRaw<[{ count: bigint }]>`
SELECT COUNT(*) as count
FROM knowledge_entries e
WHERE e.workspace_id = ${workspaceId}::uuid
${statusFilter}
AND (
to_tsvector('english', e.title) @@ plainto_tsquery('english', ${sanitizedQuery})
OR to_tsvector('english', e.content) @@ plainto_tsquery('english', ${sanitizedQuery})
)
`;
const total = Number(countResult[0].count);
// Fetch tags for the results
const entryIds = searchResults.map((r) => r.id);
const tagsMap = await this.fetchTagsForEntries(entryIds);
// Transform results to the expected format
const data: SearchResult[] = searchResults.map((row) => ({
id: row.id,
workspaceId: row.workspace_id,
slug: row.slug,
title: row.title,
content: row.content,
contentHtml: row.content_html,
summary: row.summary,
status: row.status,
visibility: row.visibility as "PRIVATE" | "WORKSPACE" | "PUBLIC",
createdAt: row.created_at,
updatedAt: row.updated_at,
createdBy: row.created_by,
updatedBy: row.updated_by,
rank: row.rank,
headline: row.headline ?? undefined,
tags: tagsMap.get(row.id) || [],
}));
const result = {
data,
pagination: {
page,
limit,
total,
totalPages: Math.ceil(total / limit),
},
query,
};
// Cache the result
await this.cache.setSearch(workspaceId, sanitizedQuery, filters, result);
return result;
}
/**
* Search entries by tags (entries must have ALL specified tags)
*
* @param tags - Array of tag slugs to filter by
* @param workspaceId - The workspace to search within
* @param options - Search options (status filter, pagination)
* @returns Paginated entries that have all specified tags
*/
async searchByTags(
tags: string[],
workspaceId: string,
options: SearchOptions = {}
): Promise<PaginatedEntries> {
const page = options.page || 1;
const limit = options.limit || 20;
const skip = (page - 1) * limit;
if (!tags || tags.length === 0) {
return {
data: [],
pagination: {
page,
limit,
total: 0,
totalPages: 0,
},
};
}
// Build where clause for entries that have ALL specified tags
const where: Prisma.KnowledgeEntryWhereInput = {
workspaceId,
status: options.status || { not: EntryStatus.ARCHIVED },
AND: tags.map((tagSlug) => ({
tags: {
some: {
tag: {
slug: tagSlug,
},
},
},
})),
};
// Get total count
const total = await this.prisma.knowledgeEntry.count({ where });
// Get entries
const entries = await this.prisma.knowledgeEntry.findMany({
where,
include: {
tags: {
include: {
tag: true,
},
},
},
orderBy: {
updatedAt: "desc",
},
skip,
take: limit,
});
// Transform to response format
const data: KnowledgeEntryWithTags[] = entries.map((entry) => ({
id: entry.id,
workspaceId: entry.workspaceId,
slug: entry.slug,
title: entry.title,
content: entry.content,
contentHtml: entry.contentHtml,
summary: entry.summary,
status: entry.status,
visibility: entry.visibility,
createdAt: entry.createdAt,
updatedAt: entry.updatedAt,
createdBy: entry.createdBy,
updatedBy: entry.updatedBy,
tags: entry.tags.map((et) => ({
id: et.tag.id,
name: et.tag.name,
slug: et.tag.slug,
color: et.tag.color,
})),
}));
return {
data,
pagination: {
page,
limit,
total,
totalPages: Math.ceil(total / limit),
},
};
}
/**
* Get recently modified entries
*
* @param workspaceId - The workspace to query
* @param limit - Maximum number of entries to return (default: 10)
* @param status - Optional status filter
* @returns Array of recently modified entries
*/
async recentEntries(
workspaceId: string,
limit: number = 10,
status?: EntryStatus
): Promise<KnowledgeEntryWithTags[]> {
const where: Prisma.KnowledgeEntryWhereInput = {
workspaceId,
status: status || { not: EntryStatus.ARCHIVED },
};
const entries = await this.prisma.knowledgeEntry.findMany({
where,
include: {
tags: {
include: {
tag: true,
},
},
},
orderBy: {
updatedAt: "desc",
},
take: limit,
});
return entries.map((entry) => ({
id: entry.id,
workspaceId: entry.workspaceId,
slug: entry.slug,
title: entry.title,
content: entry.content,
contentHtml: entry.contentHtml,
summary: entry.summary,
status: entry.status,
visibility: entry.visibility,
createdAt: entry.createdAt,
updatedAt: entry.updatedAt,
createdBy: entry.createdBy,
updatedBy: entry.updatedBy,
tags: entry.tags.map((et) => ({
id: et.tag.id,
name: et.tag.name,
slug: et.tag.slug,
color: et.tag.color,
})),
}));
}
/**
* Sanitize search query to prevent SQL injection and handle special characters
*/
private sanitizeSearchQuery(query: string): string {
if (!query || typeof query !== "string") {
return "";
}
// Trim and normalize whitespace
let sanitized = query.trim().replace(/\s+/g, " ");
// Remove PostgreSQL full-text search operators that could cause issues
sanitized = sanitized.replace(/[&|!:*()]/g, " ");
// Trim again after removing special chars
sanitized = sanitized.trim();
return sanitized;
}
/**
* Fetch tags for a list of entry IDs
*/
private async fetchTagsForEntries(
entryIds: string[]
): Promise<
Map<
string,
Array<{ id: string; name: string; slug: string; color: string | null }>
>
> {
if (entryIds.length === 0) {
return new Map();
}
const entryTags = await this.prisma.knowledgeEntryTag.findMany({
where: {
entryId: { in: entryIds },
},
include: {
tag: true,
},
});
const tagsMap = new Map<
string,
Array<{ id: string; name: string; slug: string; color: string | null }>
>();
for (const et of entryTags) {
const tags = tagsMap.get(et.entryId) || [];
tags.push({
id: et.tag.id,
name: et.tag.name,
slug: et.tag.slug,
color: et.tag.color,
});
tagsMap.set(et.entryId, tags);
}
return tagsMap;
}
/**
* Semantic search using vector similarity
*
* @param query - The search query string
* @param workspaceId - The workspace to search within
* @param options - Search options (status filter, pagination)
* @returns Paginated search results ranked by semantic similarity
*/
async semanticSearch(
query: string,
workspaceId: string,
options: SearchOptions = {}
): Promise<PaginatedSearchResults> {
if (!this.embedding.isConfigured()) {
throw new Error("Semantic search requires OPENAI_API_KEY to be configured");
}
const page = options.page || 1;
const limit = options.limit || 20;
const offset = (page - 1) * limit;
// Generate embedding for the query
const queryEmbedding = await this.embedding.generateEmbedding(query);
const embeddingString = `[${queryEmbedding.join(",")}]`;
// Build status filter
const statusFilter = options.status
? Prisma.sql`AND e.status = ${options.status}::text::"EntryStatus"`
: Prisma.sql`AND e.status != 'ARCHIVED'`;
// Vector similarity search using cosine distance
const searchResults = await this.prisma.$queryRaw<RawSearchResult[]>`
SELECT
e.id,
e.workspace_id,
e.slug,
e.title,
e.content,
e.content_html,
e.summary,
e.status,
e.visibility,
e.created_at,
e.updated_at,
e.created_by,
e.updated_by,
(1 - (emb.embedding <=> ${embeddingString}::vector)) AS rank,
NULL AS headline
FROM knowledge_entries e
INNER JOIN knowledge_embeddings emb ON e.id = emb.entry_id
WHERE e.workspace_id = ${workspaceId}::uuid
${statusFilter}
ORDER BY emb.embedding <=> ${embeddingString}::vector
LIMIT ${limit}
OFFSET ${offset}
`;
// Get total count for pagination
const countResult = await this.prisma.$queryRaw<[{ count: bigint }]>`
SELECT COUNT(*) as count
FROM knowledge_entries e
INNER JOIN knowledge_embeddings emb ON e.id = emb.entry_id
WHERE e.workspace_id = ${workspaceId}::uuid
${statusFilter}
`;
const total = Number(countResult[0].count);
// Fetch tags for the results
const entryIds = searchResults.map((r) => r.id);
const tagsMap = await this.fetchTagsForEntries(entryIds);
// Transform results to the expected format
const data: SearchResult[] = searchResults.map((row) => ({
id: row.id,
workspaceId: row.workspace_id,
slug: row.slug,
title: row.title,
content: row.content,
contentHtml: row.content_html,
summary: row.summary,
status: row.status,
visibility: row.visibility as "PRIVATE" | "WORKSPACE" | "PUBLIC",
createdAt: row.created_at,
updatedAt: row.updated_at,
createdBy: row.created_by,
updatedBy: row.updated_by,
rank: row.rank,
headline: row.headline ?? undefined,
tags: tagsMap.get(row.id) || [],
}));
return {
data,
pagination: {
page,
limit,
total,
totalPages: Math.ceil(total / limit),
},
query,
};
}
/**
* Hybrid search combining vector similarity and full-text search
* Uses Reciprocal Rank Fusion (RRF) to combine rankings
*
* @param query - The search query string
* @param workspaceId - The workspace to search within
* @param options - Search options (status filter, pagination)
* @returns Paginated search results ranked by combined relevance
*/
async hybridSearch(
query: string,
workspaceId: string,
options: SearchOptions = {}
): Promise<PaginatedSearchResults> {
if (!this.embedding.isConfigured()) {
// Fall back to keyword search if embeddings not configured
return this.search(query, workspaceId, options);
}
const page = options.page || 1;
const limit = options.limit || 20;
const offset = (page - 1) * limit;
// Sanitize query for keyword search
const sanitizedQuery = this.sanitizeSearchQuery(query);
if (!sanitizedQuery) {
return {
data: [],
pagination: {
page,
limit,
total: 0,
totalPages: 0,
},
query,
};
}
// Generate embedding for vector search
const queryEmbedding = await this.embedding.generateEmbedding(query);
const embeddingString = `[${queryEmbedding.join(",")}]`;
// Build status filter
const statusFilter = options.status
? Prisma.sql`AND e.status = ${options.status}::text::"EntryStatus"`
: Prisma.sql`AND e.status != 'ARCHIVED'`;
// Hybrid search using Reciprocal Rank Fusion (RRF)
// Combines vector similarity and full-text search rankings
const searchResults = await this.prisma.$queryRaw<RawSearchResult[]>`
WITH vector_search AS (
SELECT
e.id,
ROW_NUMBER() OVER (ORDER BY emb.embedding <=> ${embeddingString}::vector) AS rank
FROM knowledge_entries e
INNER JOIN knowledge_embeddings emb ON e.id = emb.entry_id
WHERE e.workspace_id = ${workspaceId}::uuid
${statusFilter}
),
keyword_search AS (
SELECT
e.id,
ROW_NUMBER() OVER (
ORDER BY ts_rank(
setweight(to_tsvector('english', e.title), 'A') ||
setweight(to_tsvector('english', e.content), 'B'),
plainto_tsquery('english', ${sanitizedQuery})
) DESC
) AS rank
FROM knowledge_entries e
WHERE e.workspace_id = ${workspaceId}::uuid
${statusFilter}
AND (
to_tsvector('english', e.title) @@ plainto_tsquery('english', ${sanitizedQuery})
OR to_tsvector('english', e.content) @@ plainto_tsquery('english', ${sanitizedQuery})
)
),
combined AS (
SELECT
COALESCE(v.id, k.id) AS id,
-- Reciprocal Rank Fusion: RRF(d) = sum(1 / (k + rank_i))
-- k=60 is a common constant that prevents high rankings from dominating
(COALESCE(1.0 / (60 + v.rank), 0) + COALESCE(1.0 / (60 + k.rank), 0)) AS rrf_score
FROM vector_search v
FULL OUTER JOIN keyword_search k ON v.id = k.id
)
SELECT
e.id,
e.workspace_id,
e.slug,
e.title,
e.content,
e.content_html,
e.summary,
e.status,
e.visibility,
e.created_at,
e.updated_at,
e.created_by,
e.updated_by,
c.rrf_score AS rank,
ts_headline(
'english',
e.content,
plainto_tsquery('english', ${sanitizedQuery}),
'MaxWords=50, MinWords=25, StartSel=<mark>, StopSel=</mark>'
) AS headline
FROM combined c
INNER JOIN knowledge_entries e ON c.id = e.id
ORDER BY c.rrf_score DESC, e.updated_at DESC
LIMIT ${limit}
OFFSET ${offset}
`;
// Get total count
const countResult = await this.prisma.$queryRaw<[{ count: bigint }]>`
WITH vector_search AS (
SELECT e.id
FROM knowledge_entries e
INNER JOIN knowledge_embeddings emb ON e.id = emb.entry_id
WHERE e.workspace_id = ${workspaceId}::uuid
${statusFilter}
),
keyword_search AS (
SELECT e.id
FROM knowledge_entries e
WHERE e.workspace_id = ${workspaceId}::uuid
${statusFilter}
AND (
to_tsvector('english', e.title) @@ plainto_tsquery('english', ${sanitizedQuery})
OR to_tsvector('english', e.content) @@ plainto_tsquery('english', ${sanitizedQuery})
)
)
SELECT COUNT(DISTINCT id) as count
FROM (
SELECT id FROM vector_search
UNION
SELECT id FROM keyword_search
) AS combined
`;
const total = Number(countResult[0].count);
// Fetch tags for the results
const entryIds = searchResults.map((r) => r.id);
const tagsMap = await this.fetchTagsForEntries(entryIds);
// Transform results to the expected format
const data: SearchResult[] = searchResults.map((row) => ({
id: row.id,
workspaceId: row.workspace_id,
slug: row.slug,
title: row.title,
content: row.content,
contentHtml: row.content_html,
summary: row.summary,
status: row.status,
visibility: row.visibility as "PRIVATE" | "WORKSPACE" | "PUBLIC",
createdAt: row.created_at,
updatedAt: row.updated_at,
createdBy: row.created_by,
updatedBy: row.updated_by,
rank: row.rank,
headline: row.headline ?? undefined,
tags: tagsMap.get(row.id) || [],
}));
return {
data,
pagination: {
page,
limit,
total,
totalPages: Math.ceil(total / limit),
},
query,
};
}
}