fix(ai-chat): OpenAI Chat Completions for multi-turn + provider settings, stream UX & errors" -m "Live-stand fixes (OpenRouter / OpenAI-compatible):
- openai provider: use .chat() (Chat Completions) instead of the default callable (Responses API), which gateways reject on multi-turn -> 400. - updateAiProviderSettings: assemble settings.ai.provider via jsonb_build_object with ::text-cast bound params + jsonb_typeof self-heal (postgres.js was double-encoding it into an array; the ::text cast avoids 'could not determine data type of parameter'). - chat agent: drop the hard maxOutputTokens cap (truncated complex tool calls); keep a tiny cap only on the test-connection ping. - testConnection + chat stream: surface the real provider error (statusCode+message) to logs and the UI instead of generic masks; never log the API key. - chat UI: typing indicator, incremental streaming render, tool 'running' status, Stop. Also bundled (prior uncommitted ai-chat work): - history 'AI agent' provenance badge; vector RAG (pgvector image + page_embeddings + AI_QUEUE indexer + space-scoped semanticSearch); external MCP servers backend (@ai-sdk/mcp client, SSRF IP-pinning, encrypted headers, admin CRUD/Test); yjs duplicate-instance fix via pnpm patch (single CJS instance server-side).
This commit is contained in:
vvzvlad
143
apps/server/src/database/repos/ai-chat/ai-mcp-server.repo.ts
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143
apps/server/src/database/repos/ai-chat/ai-mcp-server.repo.ts
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@@ -0,0 +1,143 @@
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import { Injectable } from '@nestjs/common';
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import { InjectKysely } from 'nestjs-kysely';
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import { sql } from 'kysely';
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import { KyselyDB, KyselyTransaction } from '../../types/kysely.types';
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import { dbOrTx } from '../../utils';
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import { AiMcpServer } from '@docmost/db/types/entity.types';
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/**
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* Repository for per-workspace external MCP servers the agent may use (§5.4).
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*
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* SECURITY (§8.10): rows hold the encrypted auth-header blob (`headersEnc`).
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* That column must NEVER be returned to a non-admin path nor logged; the admin
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* controller projects an explicit allowlist of columns and the connect path
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* decrypts only server-side. All lookups are workspace-scoped.
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*/
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@Injectable()
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export class AiMcpServerRepo {
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constructor(@InjectKysely() private readonly db: KyselyDB) {}
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async findById(
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id: string,
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workspaceId: string,
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): Promise<AiMcpServer | undefined> {
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return this.db
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.selectFrom('aiMcpServers')
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.selectAll('aiMcpServers')
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.where('id', '=', id)
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.where('workspaceId', '=', workspaceId)
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.executeTakeFirst();
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}
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async listByWorkspace(workspaceId: string): Promise<AiMcpServer[]> {
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return this.db
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.selectFrom('aiMcpServers')
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.selectAll('aiMcpServers')
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.where('workspaceId', '=', workspaceId)
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.orderBy('createdAt', 'asc')
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.execute();
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}
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/** Enabled servers only — used by the agent loop to build the toolset. */
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async listEnabled(workspaceId: string): Promise<AiMcpServer[]> {
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return this.db
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.selectFrom('aiMcpServers')
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.selectAll('aiMcpServers')
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.where('workspaceId', '=', workspaceId)
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.where('enabled', '=', true)
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.orderBy('createdAt', 'asc')
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.execute();
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}
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async insert(
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values: {
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workspaceId: string;
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name: string;
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transport: string;
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url: string;
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headersEnc?: string | null;
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toolAllowlist?: string[] | null;
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enabled?: boolean;
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},
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trx?: KyselyTransaction,
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): Promise<AiMcpServer> {
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const db = dbOrTx(this.db, trx);
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return db
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.insertInto('aiMcpServers')
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.values({
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workspaceId: values.workspaceId,
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name: values.name,
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transport: values.transport,
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url: values.url,
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headersEnc: values.headersEnc ?? null,
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// jsonb column: the postgres driver would otherwise encode a JS array as
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// a Postgres array literal. Bind the JSON text and cast it to jsonb.
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toolAllowlist: jsonbArray(values.toolAllowlist),
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enabled: values.enabled ?? true,
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})
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.returningAll()
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.executeTakeFirst();
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}
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async update(
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id: string,
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workspaceId: string,
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patch: {
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name?: string;
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transport?: string;
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url?: string;
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// undefined => leave unchanged; null => clear; string => set.
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headersEnc?: string | null;
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// undefined => leave unchanged; null => clear; string[] => set.
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toolAllowlist?: string[] | null;
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enabled?: boolean;
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},
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trx?: KyselyTransaction,
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): Promise<void> {
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const db = dbOrTx(this.db, trx);
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const set: Record<string, unknown> = { updatedAt: new Date() };
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if (patch.name !== undefined) set.name = patch.name;
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if (patch.transport !== undefined) set.transport = patch.transport;
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if (patch.url !== undefined) set.url = patch.url;
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if (patch.headersEnc !== undefined) set.headersEnc = patch.headersEnc;
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if (patch.toolAllowlist !== undefined) {
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set.toolAllowlist = jsonbArray(patch.toolAllowlist);
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}
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if (patch.enabled !== undefined) set.enabled = patch.enabled;
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await db
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.updateTable('aiMcpServers')
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.set(set)
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.where('id', '=', id)
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.where('workspaceId', '=', workspaceId)
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.execute();
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}
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async delete(
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id: string,
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workspaceId: string,
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trx?: KyselyTransaction,
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): Promise<void> {
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const db = dbOrTx(this.db, trx);
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await db
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.deleteFrom('aiMcpServers')
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.where('id', '=', id)
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.where('workspaceId', '=', workspaceId)
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.execute();
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}
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}
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/**
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* Encode a string[] as a jsonb bind for the `tool_allowlist` column. Passing a
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* plain JS array to the postgres driver would serialize it as a Postgres array
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* literal (incompatible with jsonb), so we bind the JSON text and cast it.
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* Returns null for null/empty arrays (an empty allowlist means "no restriction"
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* is not intended — callers pass null to clear; an empty array is normalized to
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* null here so it never round-trips as `[]`).
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*/
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function jsonbArray(value: string[] | null | undefined) {
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if (value === null || value === undefined || value.length === 0) {
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return null;
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}
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// Typed as string[] so it is assignable to the toolAllowlist column.
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return sql<string[]>`${JSON.stringify(value)}::jsonb`;
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}
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142
apps/server/src/database/repos/ai-chat/page-embedding.repo.ts
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142
apps/server/src/database/repos/ai-chat/page-embedding.repo.ts
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@@ -0,0 +1,142 @@
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import { Injectable } from '@nestjs/common';
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import { InjectKysely } from 'nestjs-kysely';
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import { sql } from 'kysely';
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import * as pgvector from 'pgvector';
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import { KyselyDB, KyselyTransaction } from '../../types/kysely.types';
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import { dbOrTx } from '../../utils';
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/**
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* Repository for `page_embeddings` — the pgvector store backing the AI agent's
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* semantic search (§5.5 / §6.7 stage D).
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*
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* The `embedding` column is `vector(1536)`, which is NOT a native Kysely column
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* type, so every read/write of a vector is serialized with the `pgvector` npm
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* helper (`pgvector.toSql(number[])` → a `'[1,2,3]'` text literal) and cast back
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* to `vector` via a raw `::vector` SQL cast. Reindex is a HARD delete + insert
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* (see `deleteByPage`) so the HNSW ANN index never returns stale vectors.
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*/
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/** A single chunk row to persist for a page (page-body embeddings). */
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export interface PageEmbeddingChunkRow {
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pageId: string;
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workspaceId: string;
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spaceId: string;
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// null for page-body chunks; set only for attachment chunks (future).
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attachmentId: string | null;
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chunkIndex: number;
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chunkStart: number;
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chunkLength: number;
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content: string;
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modelName: string;
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modelDimensions: number;
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embedding: number[];
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}
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/** A single ANN search hit. */
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export interface PageEmbeddingSearchHit {
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pageId: string;
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spaceId: string;
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title: string | null;
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content: string;
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// Cosine distance (0 = identical direction). Lower is more similar.
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distance: number;
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}
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@Injectable()
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export class PageEmbeddingRepo {
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constructor(@InjectKysely() private readonly db: KyselyDB) {}
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/**
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* HARD-delete every embedding row for a page (within its workspace). Used
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* before a reindex and on page deletion — a hard delete (not soft) guarantees
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* the HNSW index never returns vectors for content that no longer exists.
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*/
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async deleteByPage(
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pageId: string,
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workspaceId: string,
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trx?: KyselyTransaction,
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): Promise<void> {
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const db = dbOrTx(this.db, trx);
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await db
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.deleteFrom('pageEmbeddings')
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.where('pageId', '=', pageId)
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.where('workspaceId', '=', workspaceId)
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.execute();
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}
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/**
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* Bulk-insert chunk rows for a page. The `embedding` value is serialized with
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* `pgvector.toSql` and cast to `vector` so Postgres stores it in the fixed
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* `vector(1536)` column. No-op on an empty array.
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*/
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async insertChunks(
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rows: PageEmbeddingChunkRow[],
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trx?: KyselyTransaction,
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): Promise<void> {
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if (rows.length === 0) return;
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const db = dbOrTx(this.db, trx);
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await db
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.insertInto('pageEmbeddings')
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.values(
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rows.map((row) => ({
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pageId: row.pageId,
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workspaceId: row.workspaceId,
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spaceId: row.spaceId,
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attachmentId: row.attachmentId,
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chunkIndex: row.chunkIndex,
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chunkStart: row.chunkStart,
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chunkLength: row.chunkLength,
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content: row.content,
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modelName: row.modelName,
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modelDimensions: row.modelDimensions,
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// pgvector.toSql -> '[1,2,3]'; cast the bound literal to vector.
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embedding: sql`${pgvector.toSql(row.embedding)}::vector`,
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})),
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)
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.execute();
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}
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/**
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* Cosine ANN search over the embeddings, scoped to a workspace AND a set of
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* spaces the caller may read (see semanticSearch access-scoping). Orders by
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* `embedding <=> $query` (cosine distance) and joins the page title cheaply.
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* Returns [] when `spaceIds` is empty (no accessible spaces => no results).
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*/
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async searchByEmbedding(
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workspaceId: string,
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queryEmbedding: number[],
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spaceIds: string[],
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limit: number,
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): Promise<PageEmbeddingSearchHit[]> {
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if (spaceIds.length === 0) return [];
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// Serialized + cast query vector reused for the distance expression.
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const queryVector = sql`${pgvector.toSql(queryEmbedding)}::vector`;
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const rows = await this.db
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.selectFrom('pageEmbeddings as pe')
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.innerJoin('pages as p', 'p.id', 'pe.pageId')
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.select([
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'pe.pageId as pageId',
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'pe.spaceId as spaceId',
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'pe.content as content',
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'p.title as title',
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sql<number>`pe.embedding <=> ${queryVector}`.as('distance'),
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])
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.where('pe.workspaceId', '=', workspaceId)
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.where('pe.spaceId', 'in', spaceIds)
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// Exclude chunks whose page is in the trash (defence in depth).
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.where('p.deletedAt', 'is', null)
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.orderBy('distance', 'asc')
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.limit(limit)
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.execute();
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return rows.map((row) => ({
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pageId: row.pageId,
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spaceId: row.spaceId,
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title: row.title,
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content: row.content,
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distance: Number(row.distance),
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}));
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}
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}
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@@ -214,11 +214,16 @@ export class WorkspaceRepo {
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/**
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* Deep-merge a partial provider config into the fixed path
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* `settings.ai.provider`. Unlike `updateAiSettings` (single scalar key under
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* `settings.ai`), this stores a nested object. The path is constant — only the
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* provider value is parameterized (bound, not `sql.raw`) — so it cannot store
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* a secret and is safe from injection. Sibling `settings.ai.*` keys (search /
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* generative / chat / mcp / systemPrompt) and provider fields absent from the
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* partial are preserved via jsonb `||` merge.
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* `settings.ai`), this stores a nested object. The provider object is assembled
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* IN SQL via `jsonb_build_object`: keys come from a fixed allowlist (inlined
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* via `sql.lit`, so no injection) and values are bound params, so the result is
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* a real jsonb object and never a double-encoded string (postgres.js would
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* otherwise re-serialize a `JSON.stringify`'d string, yielding a jsonb string
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* that `||` turns into an array). A `jsonb_typeof = 'object'` CASE self-heals
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* workspaces whose `settings.ai.provider` was previously corrupted into an
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* array/string. Sibling `settings.ai.*` keys (search / generative / chat / mcp
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* / systemPrompt) and provider fields absent from the partial are preserved via
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* jsonb `||` merge.
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*/
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async updateAiProviderSettings(
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workspaceId: string,
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@@ -226,14 +231,33 @@ export class WorkspaceRepo {
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trx?: KyselyTransaction,
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): Promise<Workspace> {
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const db = dbOrTx(this.db, trx);
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const providerJson = JSON.stringify(provider);
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// Assemble the provider object IN SQL. Keys are fixed provider field names
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// (sql.lit -> inlined literals, no injection); values are bound params cast
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// to ::text — postgres.js sends bound params untyped, and jsonb_build_object's
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// value args are polymorphic ("any"), so without the explicit ::text cast
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// Postgres throws "could not determine data type of parameter $1". The result
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// is a real jsonb object, never a double-encoded string. The CASE self-heals
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// workspaces whose settings.ai.provider was previously corrupted into an
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// array/string.
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const ALLOWED = ['driver', 'chatModel', 'embeddingModel', 'baseUrl', 'systemPrompt'];
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const entries = Object.entries(provider).filter(
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([k, v]) => v !== undefined && ALLOWED.includes(k),
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);
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const patch = entries.length
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? sql`jsonb_build_object(${sql.join(
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entries.flatMap(([k, v]) => [sql.lit(k), sql`${v}::text`]),
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)})`
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: sql`'{}'::jsonb`;
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return db
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.updateTable('workspaces')
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.set({
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settings: sql`COALESCE(settings, '{}'::jsonb)
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|| jsonb_build_object('ai', COALESCE(settings->'ai', '{}'::jsonb)
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|| jsonb_build_object('provider', COALESCE(settings->'ai'->'provider', '{}'::jsonb)
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|| ${providerJson}::jsonb))`,
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settings: sql`COALESCE(settings, '{}'::jsonb) || jsonb_build_object(
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'ai', COALESCE(settings->'ai', '{}'::jsonb) || jsonb_build_object(
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'provider',
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(CASE WHEN jsonb_typeof(settings->'ai'->'provider') = 'object'
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THEN settings->'ai'->'provider' ELSE '{}'::jsonb END)
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|| ${patch}
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))`,
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updatedAt: new Date(),
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})
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.where('id', '=', workspaceId)
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|
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Reference in New Issue
Block a user