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feat(cli): add ktx dev schema to emit ktx.yaml JSON Schema
Annotates the Zod config schema with .describe() text on every field and adds generateKtxProjectConfigJsonSchema() plus a ktx dev schema command that prints (or writes) a draft-07 JSON Schema for editors and LLM agents.
This commit is contained in:
Andrey Avtomonov
parent
b3be54e3fa
commit
bd4b41f681
4 changed files with 299 additions and 110 deletions
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@ -46,5 +46,23 @@ export function registerDevCommands(program: Command, context: KtxCliCommandCont
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},
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);
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dev
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.command('schema')
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.description('Print a JSON Schema describing ktx.yaml (for editors and LLM agents)')
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.option('--output <file>', 'Write the schema to a file instead of stdout')
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.action(async (options: { output?: string }) => {
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const { generateKtxProjectConfigJsonSchema } = await import('@ktx/context/project');
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const json = `${JSON.stringify(generateKtxProjectConfigJsonSchema(), null, 2)}\n`;
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if (options.output) {
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const { writeFile } = await import('node:fs/promises');
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const target = resolve(options.output);
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await writeFile(target, json, 'utf8');
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context.io.stdout.write(`Wrote ${target}\n`);
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} else {
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context.io.stdout.write(json);
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}
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context.setExitCode(0);
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});
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registerRuntimeCommands(dev, context);
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}
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@ -1,6 +1,7 @@
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import { describe, expect, it } from 'vitest';
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import {
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buildDefaultKtxProjectConfig,
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generateKtxProjectConfigJsonSchema,
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parseKtxProjectConfig,
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serializeKtxProjectConfig,
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validateKtxProjectConfig,
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@ -485,3 +486,49 @@ scan:
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});
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});
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});
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describe('generateKtxProjectConfigJsonSchema', () => {
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const schema = generateKtxProjectConfigJsonSchema();
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it('emits draft-07 metadata', () => {
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expect(schema.$schema).toBe('http://json-schema.org/draft-07/schema#');
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expect(schema.$id).toBe('https://ktx.dev/schemas/ktx-project-config.json');
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expect(schema.title).toBe('ktx.yaml');
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expect(schema.type).toBe('object');
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});
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it('exposes every top-level ktx.yaml section under properties', () => {
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const properties = schema.properties as Record<string, unknown>;
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expect(Object.keys(properties).sort()).toEqual(
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['agent', 'connections', 'ingest', 'llm', 'memory', 'project', 'scan', 'setup', 'storage'].sort(),
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);
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});
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it('marks "project" as required', () => {
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expect(schema.required).toEqual(expect.arrayContaining(['project']));
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});
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it('carries .describe() text on top-level fields', () => {
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const properties = schema.properties as Record<string, { description?: string }>;
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expect(properties.project?.description).toMatch(/Project identifier/);
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expect(properties.llm?.description).toMatch(/LLM/);
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expect(properties.scan?.description).toMatch(/Schema-scan/);
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});
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it('propagates enum values through to nested fields', () => {
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const llm = (schema.properties as Record<string, { properties?: Record<string, unknown> }>).llm;
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const provider = llm?.properties?.provider as { properties?: Record<string, unknown> };
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const backend = provider?.properties?.backend as { enum?: readonly string[] };
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expect(backend?.enum).toEqual(['none', 'anthropic', 'vertex', 'gateway']);
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const storage = (schema.properties as Record<string, { properties?: Record<string, unknown> }>).storage;
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const state = storage?.properties?.state as { enum?: readonly string[] };
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expect(state?.enum).toEqual(['sqlite', 'postgres']);
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});
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it('carries descriptions on deeply nested leaves', () => {
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const scan = (schema.properties as Record<string, { properties?: Record<string, unknown> }>).scan;
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const relationships = scan?.properties?.relationships as { properties?: Record<string, { description?: string }> };
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expect(relationships?.properties?.acceptThreshold?.description).toMatch(/auto-accepted/);
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});
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});
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@ -19,137 +19,247 @@ const DEPRECATED_KEY_HINTS: Record<string, string> = {
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'scan.enrichment.embeddings.provider': 'use scan.enrichment.embeddings.backend',
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};
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const apiCredentialsSchema = z.strictObject({
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api_key: z.string().min(1).optional(),
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base_url: z.string().min(1).optional(),
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});
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const apiCredentialsSchema = z
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.strictObject({
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api_key: z.string().min(1).optional().describe('API key for the provider. Read from this value or the provider-specific environment variable.'),
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base_url: z.string().min(1).optional().describe('Override the provider\'s default API base URL (e.g. a proxy or self-hosted gateway).'),
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})
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.describe('API credentials block: optional key and base URL for an LLM or embedding provider.');
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const vertexProviderSchema = z.strictObject({
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project: z.string().min(1).optional(),
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location: z.string().default(''),
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});
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const vertexProviderSchema = z
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.strictObject({
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project: z.string().min(1).optional().describe('Google Cloud project ID hosting the Vertex AI endpoint.'),
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location: z.string().default('').describe('Vertex AI region (e.g. "us-east5"). Empty string falls back to the SDK default.'),
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})
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.describe('Google Vertex AI provider configuration.');
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const sentenceTransformersSchema = z.strictObject({
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base_url: z.string().default(''),
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pathPrefix: z.string().optional(),
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});
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const sentenceTransformersSchema = z
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.strictObject({
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base_url: z.string().default('').describe('Base URL of the sentence-transformers HTTP server. Empty string uses the managed local runtime.'),
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pathPrefix: z.string().optional().describe('Optional URL path prefix prepended to embedding requests.'),
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})
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.describe('Sentence-transformers embedding server configuration.');
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const llmProviderSchema = z.strictObject({
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backend: z.enum(KTX_LLM_BACKENDS).default('none'),
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vertex: vertexProviderSchema.optional(),
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anthropic: apiCredentialsSchema.optional(),
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gateway: apiCredentialsSchema.optional(),
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});
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const llmProviderSchema = z
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.strictObject({
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backend: z
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.enum(KTX_LLM_BACKENDS)
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.default('none')
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.describe('LLM provider backend. "none" disables LLM features; "anthropic" / "vertex" / "gateway" require the matching nested credentials block.'),
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vertex: vertexProviderSchema.optional().describe('Vertex AI credentials, used when backend is "vertex".'),
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anthropic: apiCredentialsSchema.optional().describe('Anthropic API credentials, used when backend is "anthropic".'),
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gateway: apiCredentialsSchema.optional().describe('AI Gateway credentials, used when backend is "gateway".'),
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})
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.describe('LLM provider selection and credentials.');
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const promptCachingSchema = z.strictObject({
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enabled: z.boolean().optional(),
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systemTtl: z.enum(KTX_PROMPT_CACHE_TTLS).optional(),
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toolsTtl: z.enum(KTX_PROMPT_CACHE_TTLS).optional(),
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historyTtl: z.enum(KTX_PROMPT_CACHE_TTLS).optional(),
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vertexFallbackTo5m: z.boolean().optional(),
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});
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const promptCachingSchema = z
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.strictObject({
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enabled: z.boolean().optional().describe('Master switch for Anthropic-style prompt caching. When omitted, the backend\'s default applies.'),
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systemTtl: z.enum(KTX_PROMPT_CACHE_TTLS).optional().describe('Cache TTL for the system prompt segment ("5m" or "1h").'),
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toolsTtl: z.enum(KTX_PROMPT_CACHE_TTLS).optional().describe('Cache TTL for the tools/schema segment ("5m" or "1h").'),
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historyTtl: z.enum(KTX_PROMPT_CACHE_TTLS).optional().describe('Cache TTL for conversation-history cache breakpoints ("5m" or "1h").'),
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vertexFallbackTo5m: z.boolean().optional().describe('When true, transparently downgrade 1h TTLs to 5m on Vertex, which does not support 1h caching.'),
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})
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.describe('Prompt-caching tunables for Anthropic-compatible providers.');
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const llmSchema = z.strictObject({
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provider: llmProviderSchema.prefault({}),
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models: z.partialRecord(z.enum(KTX_MODEL_ROLES), z.string().min(1)).default({}),
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promptCaching: promptCachingSchema.optional(),
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});
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const llmSchema = z
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.strictObject({
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provider: llmProviderSchema.prefault({}).describe('LLM provider backend and credentials.'),
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models: z
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.partialRecord(z.enum(KTX_MODEL_ROLES), z.string().min(1))
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.default({})
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.describe('Per-role model overrides keyed by KTX model role (e.g. "default", "triage"). Values are provider-specific model identifiers.'),
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promptCaching: promptCachingSchema.optional().describe('Optional prompt-caching tunables.'),
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})
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.describe('LLM provider, per-role model overrides, and prompt-caching tunables.');
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const embeddingSchema = z.strictObject({
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backend: z.enum(KTX_EMBEDDING_BACKENDS).default('deterministic'),
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model: z.string().min(1).optional(),
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dimensions: z.int().positive().default(8),
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openai: apiCredentialsSchema.optional(),
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sentenceTransformers: sentenceTransformersSchema.optional(),
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batchSize: z.int().positive().optional(),
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});
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const embeddingSchema = z
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.strictObject({
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backend: z
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.enum(KTX_EMBEDDING_BACKENDS)
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.default('deterministic')
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.describe('Embedding backend. "deterministic" is a built-in hash-based vector for offline use; "openai" and "sentence-transformers" call out to those providers; "none" disables embeddings.'),
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model: z.string().min(1).optional().describe('Provider-specific embedding model identifier (e.g. "text-embedding-3-small"). Ignored by the "deterministic" backend.'),
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dimensions: z.int().positive().default(8).describe('Embedding vector dimensionality. Must match the chosen model when using a real provider.'),
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openai: apiCredentialsSchema.optional().describe('OpenAI credentials, used when backend is "openai".'),
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sentenceTransformers: sentenceTransformersSchema.optional().describe('Sentence-transformers server config, used when backend is "sentence-transformers".'),
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batchSize: z.int().positive().optional().describe('Number of texts per embedding API call. Omit to use the backend default.'),
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})
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.describe('Embedding backend, model, and provider credentials.');
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const workUnitsSchema = z.strictObject({
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stepBudget: z.int().positive().default(40),
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maxConcurrency: z.int().positive().default(1),
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failureMode: z.enum(KTX_WORK_UNIT_FAILURE_MODES).default('continue'),
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});
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const workUnitsSchema = z
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.strictObject({
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stepBudget: z.int().positive().default(40).describe('Maximum number of agent steps allowed per work unit before it is force-terminated.'),
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maxConcurrency: z.int().positive().default(1).describe('Maximum number of work units run concurrently during ingest.'),
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failureMode: z
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.enum(KTX_WORK_UNIT_FAILURE_MODES)
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.default('continue')
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.describe('Behavior when a work unit fails: "abort" stops the whole ingest run; "continue" records the failure and keeps going.'),
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})
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.describe('Concurrency and failure handling for ingest work units.');
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const ingestSchema = z.strictObject({
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adapters: z.array(z.string().min(1)).default([]),
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embeddings: embeddingSchema.prefault({ backend: 'deterministic', model: 'deterministic' }),
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workUnits: workUnitsSchema.prefault({}),
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});
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const ingestSchema = z
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.strictObject({
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adapters: z
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.array(z.string().min(1))
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.default([])
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.describe('Ingest adapter identifiers to run (e.g. "metabase", "looker", "historic-sql"). Empty array means no adapters are run.'),
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embeddings: embeddingSchema
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.prefault({ backend: 'deterministic', model: 'deterministic' })
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.describe('Embedding configuration used when ingest adapters need to embed documents.'),
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workUnits: workUnitsSchema.prefault({}).describe('Concurrency and failure handling for ingest work units.'),
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})
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.describe('Ingest pipeline configuration: adapters, embeddings, and work-unit policy.');
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const scanEnrichmentSchema = z.strictObject({
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mode: z.enum(KTX_ENRICHMENT_MODES).default('none'),
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embeddings: embeddingSchema.optional(),
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});
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const scanEnrichmentSchema = z
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.strictObject({
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mode: z
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.enum(KTX_ENRICHMENT_MODES)
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.default('none')
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.describe('Column/table enrichment mode. "none" disables enrichment; "deterministic" uses local heuristics; "llm" calls the configured LLM provider.'),
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embeddings: embeddingSchema.optional().describe('Optional embedding override for enrichment-time vectorization. Falls back to ingest.embeddings when omitted.'),
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})
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.describe('Schema-scan enrichment: how columns and tables are described.');
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const scanRelationshipsSchema = z.strictObject({
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enabled: z.boolean().default(true),
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llmProposals: z.boolean().default(true),
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validationRequiredForManifest: z.boolean().default(true),
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acceptThreshold: z.number().min(0).max(1).default(0.85),
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reviewThreshold: z.number().min(0).max(1).default(0.55),
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maxLlmTablesPerBatch: z.int().positive().default(40),
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maxCandidatesPerColumn: z.int().positive().default(25),
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profileSampleRows: z.int().positive().default(10000),
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validationConcurrency: z.int().positive().default(4),
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validationBudget: z.union([z.literal('all'), z.int().nonnegative()]).optional(),
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});
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const scanRelationshipsSchema = z
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.strictObject({
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enabled: z.boolean().default(true).describe('Master switch for relationship discovery during scan.'),
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llmProposals: z.boolean().default(true).describe('When true, propose relationships using the configured LLM in addition to deterministic candidates.'),
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validationRequiredForManifest: z
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.boolean()
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.default(true)
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.describe('When true, only relationships that pass database-side validation are written to the manifest.'),
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acceptThreshold: z
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.number()
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.min(0)
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.max(1)
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.default(0.85)
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.describe('Confidence score (0–1) at or above which an LLM-proposed relationship is auto-accepted into the manifest.'),
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reviewThreshold: z
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.number()
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.min(0)
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.max(1)
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.default(0.55)
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.describe('Confidence score (0–1) at or above which a proposal is surfaced for human review (but not auto-accepted).'),
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maxLlmTablesPerBatch: z
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.int()
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.positive()
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.default(40)
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.describe('Maximum number of tables included in a single LLM relationship-proposal batch.'),
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maxCandidatesPerColumn: z
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.int()
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.positive()
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.default(25)
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.describe('Maximum number of candidate join partners considered per column during relationship discovery.'),
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profileSampleRows: z.int().positive().default(10000).describe('Number of rows sampled per table when profiling values for relationship inference.'),
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validationConcurrency: z.int().positive().default(4).describe('Number of relationship validation queries run in parallel against the database.'),
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validationBudget: z
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.union([z.literal('all'), z.int().nonnegative()])
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.optional()
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.describe('Cap on validation queries per scan run. Use "all" for unlimited, an integer for a hard cap, or omit for the runtime default.'),
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})
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.describe('Schema-scan relationship discovery and validation tunables.');
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const scanSchema = z.strictObject({
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enrichment: scanEnrichmentSchema.prefault({}),
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relationships: scanRelationshipsSchema.prefault({}),
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});
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const scanSchema = z
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.strictObject({
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enrichment: scanEnrichmentSchema.prefault({}).describe('Column/table enrichment configuration.'),
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relationships: scanRelationshipsSchema.prefault({}).describe('Relationship discovery and validation configuration.'),
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})
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.describe('Schema-scan configuration: enrichment and relationship discovery.');
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const setupSchema = z
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.strictObject({
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database_connection_ids: z.array(z.string().min(1)).default([]),
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completed_steps: z.unknown().optional(),
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database_connection_ids: z
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.array(z.string().min(1))
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.default([])
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.describe('Connection IDs (keys of the top-level `connections` map) that the setup wizard treats as the project\'s primary databases.'),
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completed_steps: z
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.unknown()
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.optional()
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.describe('Deprecated. Accepted for backward compatibility but ignored; KTX no longer tracks setup progress here.'),
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})
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.transform(({ database_connection_ids }) => ({ database_connection_ids }));
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.transform(({ database_connection_ids }) => ({ database_connection_ids }))
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.describe('Setup-wizard state captured during `ktx setup`.');
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const storageGitSchema = z.strictObject({
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auto_commit: z.boolean().default(true),
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author: z.string().min(1).default('ktx <ktx@example.com>'),
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});
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const storageGitSchema = z
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.strictObject({
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auto_commit: z.boolean().default(true).describe('When true, KTX automatically commits state changes to the local Git-backed store.'),
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author: z
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.string()
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.min(1)
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.default('ktx <ktx@example.com>')
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.describe('Git author identity used for auto-commits, in standard "Name <email>" form.'),
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})
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.describe('Git-backed storage commit policy.');
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const storageSchema = z.strictObject({
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state: z.enum(KTX_STORAGE_STATES).default('sqlite'),
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search: z.enum(KTX_SEARCH_BACKENDS).default('sqlite-fts5'),
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git: storageGitSchema.prefault({}),
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});
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const storageSchema = z
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.strictObject({
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state: z
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.enum(KTX_STORAGE_STATES)
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.default('sqlite')
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.describe('Backend for KTX state storage. "sqlite" uses .ktx/db.sqlite; "postgres" expects a configured Postgres connection.'),
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search: z
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.enum(KTX_SEARCH_BACKENDS)
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.default('sqlite-fts5')
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.describe('Backend for search indexes. "sqlite-fts5" uses SQLite FTS5; "postgres-hybrid" uses Postgres lexical + vector hybrid search.'),
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git: storageGitSchema.prefault({}).describe('Git-backed storage commit policy.'),
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})
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.describe('Storage backends and commit policy for KTX state and search indexes.');
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const connectionSchema = z.looseObject({
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driver: z.string().min(1).optional(),
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url: z.string().optional(),
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});
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const connectionSchema = z
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.looseObject({
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driver: z.string().min(1).optional().describe('Connector driver identifier (e.g. "postgres", "bigquery", "snowflake").'),
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url: z.string().optional().describe('Connection URL or DSN. Format depends on the driver; may contain environment-variable references.'),
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})
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.describe('A single database/connector connection entry. Additional driver-specific fields are accepted and passed through.');
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const agentSchema = z.strictObject({
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run_research: z
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.strictObject({
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enabled: z.boolean().default(false),
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max_iterations: z.number().int().nonnegative().default(20),
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default_toolset: z.array(z.string().min(1)).default(['sl_query', 'wiki_search', 'sl_read_source']),
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})
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.prefault({}),
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});
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const agentSchema = z
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.strictObject({
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run_research: z
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.strictObject({
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enabled: z.boolean().default(false).describe('Master switch for the research agent.'),
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max_iterations: z
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.number()
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.int()
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.nonnegative()
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.default(20)
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.describe('Maximum number of tool-call iterations the research agent may take per run.'),
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default_toolset: z
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.array(z.string().min(1))
|
||||
.default(['sl_query', 'wiki_search', 'sl_read_source'])
|
||||
.describe('Default list of tool identifiers exposed to the research agent.'),
|
||||
})
|
||||
.prefault({})
|
||||
.describe('Research-agent configuration.'),
|
||||
})
|
||||
.describe('Agent feature configuration.');
|
||||
|
||||
const memorySchema = z.strictObject({
|
||||
auto_commit: z.boolean().default(true),
|
||||
});
|
||||
const memorySchema = z
|
||||
.strictObject({
|
||||
auto_commit: z.boolean().default(true).describe('When true, KTX automatically commits memory updates to the Git-backed store.'),
|
||||
})
|
||||
.describe('Memory subsystem configuration.');
|
||||
|
||||
const ktxProjectConfigSchema = z.strictObject({
|
||||
project: z
|
||||
.string({ error: 'ktx.yaml field "project" is required' })
|
||||
.trim()
|
||||
.min(1, 'ktx.yaml field "project" is required'),
|
||||
setup: setupSchema.optional(),
|
||||
connections: z.record(z.string(), connectionSchema).default({}),
|
||||
storage: storageSchema.prefault({}),
|
||||
llm: llmSchema.prefault({}),
|
||||
ingest: ingestSchema.prefault({}),
|
||||
agent: agentSchema.prefault({}),
|
||||
memory: memorySchema.prefault({}),
|
||||
scan: scanSchema.prefault({}),
|
||||
});
|
||||
const ktxProjectConfigSchema = z
|
||||
.strictObject({
|
||||
project: z
|
||||
.string({ error: 'ktx.yaml field "project" is required' })
|
||||
.trim()
|
||||
.min(1, 'ktx.yaml field "project" is required')
|
||||
.describe('Project identifier; used in logs, ktx state files, and as the default workspace name.'),
|
||||
setup: setupSchema.optional().describe('Setup-wizard state. Written by `ktx setup`; may be omitted.'),
|
||||
connections: z
|
||||
.record(z.string(), connectionSchema)
|
||||
.default({})
|
||||
.describe('Map of connection ID to connector configuration. Keys are user-chosen names referenced elsewhere in the config.'),
|
||||
storage: storageSchema.prefault({}).describe('Storage backends and commit policy for KTX state and search indexes.'),
|
||||
llm: llmSchema.prefault({}).describe('LLM provider, per-role model overrides, and prompt-caching tunables.'),
|
||||
ingest: ingestSchema.prefault({}).describe('Ingest pipeline configuration.'),
|
||||
agent: agentSchema.prefault({}).describe('Agent feature configuration.'),
|
||||
memory: memorySchema.prefault({}).describe('Memory subsystem configuration.'),
|
||||
scan: scanSchema.prefault({}).describe('Schema-scan configuration: enrichment and relationship discovery.'),
|
||||
})
|
||||
.describe('Configuration schema for KTX project files (ktx.yaml).');
|
||||
|
||||
export type KtxProjectConfig = z.infer<typeof ktxProjectConfigSchema>;
|
||||
export type KtxProjectLlmConfig = z.infer<typeof llmSchema>;
|
||||
|
|
@ -260,6 +370,19 @@ export function validateKtxProjectConfig(raw: string): KtxConfigValidation {
|
|||
return { ok: false, issues: collectIssues(result.error, parsed) };
|
||||
}
|
||||
|
||||
export function generateKtxProjectConfigJsonSchema(): Record<string, unknown> {
|
||||
const schema = z.toJSONSchema(ktxProjectConfigSchema, {
|
||||
target: 'draft-7',
|
||||
io: 'input',
|
||||
}) as Record<string, unknown>;
|
||||
return {
|
||||
$schema: 'http://json-schema.org/draft-07/schema#',
|
||||
$id: 'https://ktx.dev/schemas/ktx-project-config.json',
|
||||
title: 'ktx.yaml',
|
||||
...schema,
|
||||
};
|
||||
}
|
||||
|
||||
export function serializeKtxProjectConfig(config: KtxProjectConfig): string {
|
||||
const serializedConfig =
|
||||
config.ingest.adapters.length === 0
|
||||
|
|
|
|||
|
|
@ -10,6 +10,7 @@ export type {
|
|||
} from './config.js';
|
||||
export {
|
||||
buildDefaultKtxProjectConfig,
|
||||
generateKtxProjectConfigJsonSchema,
|
||||
parseKtxProjectConfig,
|
||||
serializeKtxProjectConfig,
|
||||
validateKtxProjectConfig,
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue