mirror of
https://github.com/Kaelio/ktx.git
synced 2026-06-10 08:05:14 +02:00
feat: run ingest agents through llm runtime
This commit is contained in:
Andrey Avtomonov
parent
bbcfffacb6
commit
418a8e17ae
34 changed files with 386 additions and 282 deletions
|
|
@ -1,4 +1,5 @@
|
|||
import type { KtxLlmProvider } from '@ktx/llm';
|
||||
import type { KtxLogger } from '../core/index.js';
|
||||
import { AiSdkKtxLlmRuntime, type AgentTelemetryPort } from '../llm/ai-sdk-runtime.js';
|
||||
import type { KtxLlmDebugRequestRecorder } from '../llm/debug-request-recorder.js';
|
||||
import type { AgentRunnerPort, RunLoopParams, RunLoopResult } from '../llm/runtime-port.js';
|
||||
|
|
|
|||
|
|
@ -1,7 +1,6 @@
|
|||
import type { KtxModelRole } from '@ktx/llm';
|
||||
import type { ToolSet } from 'ai';
|
||||
import type { AgentRunnerService } from '../../agent/index.js';
|
||||
import { type KtxLogger, noopLogger } from '../../core/index.js';
|
||||
import type { AgentRunnerPort, KtxRuntimeToolSet } from '../../llm/index.js';
|
||||
import type { MemoryAction } from '../../memory/index.js';
|
||||
import type { ContextCandidateForDedup, CuratorPaginationPort, CuratorPaginationReport } from '../ports.js';
|
||||
import type {
|
||||
|
|
@ -38,7 +37,7 @@ export interface CuratorPaginationInput {
|
|||
modelRole: KtxModelRole;
|
||||
buildSystemPrompt: () => string;
|
||||
buildUserPrompt: (input: CuratorPaginationPromptInput) => string;
|
||||
buildToolSet: (passNumber: number) => ToolSet;
|
||||
buildToolSet: (passNumber: number) => KtxRuntimeToolSet;
|
||||
getReconciliationActions: () => MemoryAction[];
|
||||
onStepFinish?: (info: { passNumber: number; stepIndex: number; stepBudget: number }) => void;
|
||||
}
|
||||
|
|
@ -50,7 +49,7 @@ interface CuratorPaginationResult extends ReconciliationOutcome {
|
|||
|
||||
export interface CuratorPaginationServiceDeps {
|
||||
store: ContextCandidateStorePort;
|
||||
agentRunner: AgentRunnerService;
|
||||
agentRunner: AgentRunnerPort;
|
||||
settings: CuratorPaginationSettings;
|
||||
logger?: KtxLogger;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -200,7 +200,7 @@ const makeDeps = () => {
|
|||
const slValidator = { validateSingleSource: vi.fn().mockResolvedValue({ errors: [], warnings: [] }) };
|
||||
const toolsetFactory = {
|
||||
createIngestWuToolset: vi.fn().mockReturnValue({
|
||||
toAiSdkTools: vi.fn().mockReturnValue({}),
|
||||
toRuntimeTools: vi.fn().mockReturnValue({}),
|
||||
getAllTools: vi.fn().mockReturnValue([]),
|
||||
getToolNames: vi.fn().mockReturnValue([]),
|
||||
}),
|
||||
|
|
@ -419,7 +419,7 @@ describe('IngestBundleRunner — Stages 1 → 7', () => {
|
|||
deps.toolsetFactory.createIngestWuToolset.mockImplementation((toolSession: any) => {
|
||||
sessions.push(toolSession);
|
||||
return {
|
||||
toAiSdkTools: vi.fn().mockReturnValue({}),
|
||||
toRuntimeTools: vi.fn().mockReturnValue({}),
|
||||
getAllTools: vi.fn().mockReturnValue([]),
|
||||
getToolNames: vi.fn().mockReturnValue([]),
|
||||
};
|
||||
|
|
@ -591,7 +591,7 @@ describe('IngestBundleRunner — Stages 1 → 7', () => {
|
|||
deps.toolsetFactory.createIngestWuToolset.mockImplementation((toolSession: any) => {
|
||||
currentToolSession = toolSession;
|
||||
return {
|
||||
toAiSdkTools: vi.fn().mockReturnValue({}),
|
||||
toRuntimeTools: vi.fn().mockReturnValue({}),
|
||||
getAllTools: vi.fn().mockReturnValue([]),
|
||||
getToolNames: vi.fn().mockReturnValue([]),
|
||||
};
|
||||
|
|
@ -663,7 +663,7 @@ describe('IngestBundleRunner — Stages 1 → 7', () => {
|
|||
deps.toolsetFactory.createIngestWuToolset.mockImplementation((toolSession: any) => {
|
||||
currentToolSession = toolSession;
|
||||
return {
|
||||
toAiSdkTools: vi.fn().mockReturnValue({}),
|
||||
toRuntimeTools: vi.fn().mockReturnValue({}),
|
||||
getAllTools: vi.fn().mockReturnValue([]),
|
||||
getToolNames: vi.fn().mockReturnValue([]),
|
||||
};
|
||||
|
|
@ -834,7 +834,7 @@ describe('IngestBundleRunner — Stages 1 → 7', () => {
|
|||
it('stores memory-flow provenance and transcript summaries in the ingest report body', async () => {
|
||||
const deps = makeDeps();
|
||||
deps.toolsetFactory.createIngestWuToolset.mockReturnValue({
|
||||
toAiSdkTools: vi.fn().mockReturnValue({
|
||||
toRuntimeTools: vi.fn().mockReturnValue({
|
||||
read_raw_span: {
|
||||
description: 'read a raw span',
|
||||
inputSchema: {},
|
||||
|
|
@ -1376,7 +1376,7 @@ describe('IngestBundleRunner — Stages 1 → 7', () => {
|
|||
deps.toolsetFactory.createIngestWuToolset.mockImplementation((toolSession: any) => {
|
||||
currentToolSession = toolSession;
|
||||
return {
|
||||
toAiSdkTools: vi.fn().mockReturnValue({}),
|
||||
toRuntimeTools: vi.fn().mockReturnValue({}),
|
||||
getAllTools: vi.fn().mockReturnValue([]),
|
||||
getToolNames: vi.fn().mockReturnValue([]),
|
||||
};
|
||||
|
|
@ -1933,7 +1933,7 @@ describe('IngestBundleRunner — Stages 1 → 7', () => {
|
|||
deps.toolsetFactory.createIngestWuToolset.mockImplementation((toolSession: any) => {
|
||||
currentToolSession = toolSession;
|
||||
return {
|
||||
toAiSdkTools: vi.fn().mockReturnValue({}),
|
||||
toRuntimeTools: vi.fn().mockReturnValue({}),
|
||||
getAllTools: vi.fn().mockReturnValue([]),
|
||||
getToolNames: vi.fn().mockReturnValue([]),
|
||||
};
|
||||
|
|
|
|||
|
|
@ -1,9 +1,9 @@
|
|||
import { mkdir, readFile, rm, writeFile } from 'node:fs/promises';
|
||||
import { dirname, join } from 'node:path';
|
||||
import { type Tool, tool } from 'ai';
|
||||
import pLimit from 'p-limit';
|
||||
import { z } from 'zod';
|
||||
import { type KtxLogger, noopLogger } from '../core/index.js';
|
||||
import { createRuntimeToolDescriptorFromAiTool, type KtxRuntimeToolSet } from '../llm/index.js';
|
||||
import type { CaptureSession, MemoryAction } from '../memory/index.js';
|
||||
import type { SemanticLayerService, SemanticLayerSource, SlValidationDeps } from '../sl/index.js';
|
||||
import { createTouchedSlSources, type ToolContext, type ToolSession } from '../tools/index.js';
|
||||
|
|
@ -694,8 +694,9 @@ export class IngestBundleRunner {
|
|||
};
|
||||
|
||||
const skillsLoadedPerWu: string[] = [];
|
||||
const loadSkillTool: Record<string, Tool> = {
|
||||
load_skill: tool({
|
||||
const loadSkillTool: KtxRuntimeToolSet = {
|
||||
load_skill: {
|
||||
name: 'load_skill',
|
||||
description:
|
||||
'Load a skill to get specialized instructions. Call this when a skill listed in the system prompt matches the current task.',
|
||||
inputSchema: z.object({ name: z.string() }),
|
||||
|
|
@ -705,19 +706,23 @@ export class IngestBundleRunner {
|
|||
const available =
|
||||
(await this.deps.skillsRegistry.listSkills('memory_agent')).map((s) => s.name).join(', ') ||
|
||||
'(none)';
|
||||
return `Skill "${name}" not available. Available: ${available}`;
|
||||
return { markdown: `Skill "${name}" not available. Available: ${available}` };
|
||||
}
|
||||
const body = await readFile(join(skill.path, 'SKILL.md'), 'utf-8');
|
||||
if (!skillsLoadedPerWu.includes(skill.name)) {
|
||||
skillsLoadedPerWu.push(skill.name);
|
||||
}
|
||||
return {
|
||||
const structured = {
|
||||
name: skill.name,
|
||||
skillDirectory: skill.path,
|
||||
content: this.deps.skillsRegistry.stripFrontmatter(body),
|
||||
};
|
||||
return {
|
||||
markdown: `# ${structured.name}\n\n${structured.content}`,
|
||||
structured,
|
||||
};
|
||||
},
|
||||
}),
|
||||
},
|
||||
};
|
||||
|
||||
const priorProvenance = await this.deps.provenance.findLatestArtifactsForRawPaths(
|
||||
|
|
@ -726,12 +731,15 @@ export class IngestBundleRunner {
|
|||
wu.rawFiles,
|
||||
);
|
||||
const wuEmitUnmappedFallbackTool = {
|
||||
emit_unmapped_fallback: createEmitUnmappedFallbackTool({
|
||||
stageIndex,
|
||||
allowedPaths: new Set(wu.rawFiles),
|
||||
tableRefExists: (tableRef) =>
|
||||
this.tableRefExistsInSemanticLayer(scopedSemanticLayerService, slConnectionIds, tableRef),
|
||||
}),
|
||||
emit_unmapped_fallback: createRuntimeToolDescriptorFromAiTool(
|
||||
'emit_unmapped_fallback',
|
||||
createEmitUnmappedFallbackTool({
|
||||
stageIndex,
|
||||
allowedPaths: new Set(wu.rawFiles),
|
||||
tableRefExists: (tableRef) =>
|
||||
this.tableRefExistsInSemanticLayer(scopedSemanticLayerService, slConnectionIds, tableRef),
|
||||
}),
|
||||
),
|
||||
};
|
||||
|
||||
const systemPrompt = buildWuSystemPrompt({
|
||||
|
|
@ -765,7 +773,7 @@ export class IngestBundleRunner {
|
|||
wu: wuInner,
|
||||
loadSkillTool,
|
||||
emitUnmappedFallbackTool: wuEmitUnmappedFallbackTool,
|
||||
toolsetTools: wuToolset.toAiSdkTools(wuToolContext),
|
||||
toolsetTools: wuToolset.toRuntimeTools(wuToolContext),
|
||||
}),
|
||||
join(transcriptDir, `${wuInner.unitKey}.jsonl`),
|
||||
wuInner.unitKey,
|
||||
|
|
@ -921,53 +929,79 @@ export class IngestBundleRunner {
|
|||
ingest: ingestToolMetadata,
|
||||
session: rcToolSession,
|
||||
};
|
||||
const rcLoadSkill: Record<string, Tool> = {
|
||||
load_skill: tool({
|
||||
const rcLoadSkill: KtxRuntimeToolSet = {
|
||||
load_skill: {
|
||||
name: 'load_skill',
|
||||
description: 'Load a skill.',
|
||||
inputSchema: z.object({ name: z.string() }),
|
||||
execute: async ({ name }) => {
|
||||
const skill = await this.deps.skillsRegistry.getSkill(name, 'memory_agent');
|
||||
if (!skill) {
|
||||
return `Skill "${name}" not found`;
|
||||
return { markdown: `Skill "${name}" not found` };
|
||||
}
|
||||
const body = await readFile(join(skill.path, 'SKILL.md'), 'utf-8');
|
||||
return { name: skill.name, content: this.deps.skillsRegistry.stripFrontmatter(body) };
|
||||
const structured = { name: skill.name, content: this.deps.skillsRegistry.stripFrontmatter(body) };
|
||||
return { markdown: `# ${structured.name}\n\n${structured.content}`, structured };
|
||||
},
|
||||
}),
|
||||
},
|
||||
};
|
||||
const allStagedPaths = new Set<string>([...currentHashes.keys()]);
|
||||
const rcRawSpanTool = { read_raw_span: createReadRawSpanTool({ stagedDir, allowedPaths: allStagedPaths }) };
|
||||
const rcStageListTool = { stage_list: createStageListTool({ stageIndex }) };
|
||||
const rcStageDiffTool = { stage_diff: createStageDiffTool({ stageIndex }) };
|
||||
const rcRawSpanTool = {
|
||||
read_raw_span: createRuntimeToolDescriptorFromAiTool(
|
||||
'read_raw_span',
|
||||
createReadRawSpanTool({ stagedDir, allowedPaths: allStagedPaths }),
|
||||
),
|
||||
};
|
||||
const rcStageListTool = {
|
||||
stage_list: createRuntimeToolDescriptorFromAiTool('stage_list', createStageListTool({ stageIndex })),
|
||||
};
|
||||
const rcStageDiffTool = {
|
||||
stage_diff: createRuntimeToolDescriptorFromAiTool('stage_diff', createStageDiffTool({ stageIndex })),
|
||||
};
|
||||
const rcEvictionListTool = {
|
||||
eviction_list: createEvictionListTool({
|
||||
provenance: this.deps.provenance,
|
||||
connectionId: job.connectionId,
|
||||
sourceKey: job.sourceKey,
|
||||
deletedRawPaths: eviction?.deletedRawPaths ?? [],
|
||||
}),
|
||||
eviction_list: createRuntimeToolDescriptorFromAiTool(
|
||||
'eviction_list',
|
||||
createEvictionListTool({
|
||||
provenance: this.deps.provenance,
|
||||
connectionId: job.connectionId,
|
||||
sourceKey: job.sourceKey,
|
||||
deletedRawPaths: eviction?.deletedRawPaths ?? [],
|
||||
}),
|
||||
),
|
||||
};
|
||||
const rcEmitConflictResolutionTool = {
|
||||
emit_conflict_resolution: createEmitConflictResolutionTool({ stageIndex }),
|
||||
emit_conflict_resolution: createRuntimeToolDescriptorFromAiTool(
|
||||
'emit_conflict_resolution',
|
||||
createEmitConflictResolutionTool({ stageIndex }),
|
||||
),
|
||||
};
|
||||
const rcEmitEvictionDecisionTool = {
|
||||
emit_eviction_decision: createEmitEvictionDecisionTool({
|
||||
stageIndex,
|
||||
deletedRawPaths: eviction?.deletedRawPaths ?? [],
|
||||
}),
|
||||
emit_eviction_decision: createRuntimeToolDescriptorFromAiTool(
|
||||
'emit_eviction_decision',
|
||||
createEmitEvictionDecisionTool({
|
||||
stageIndex,
|
||||
deletedRawPaths: eviction?.deletedRawPaths ?? [],
|
||||
}),
|
||||
),
|
||||
};
|
||||
const rcEmitArtifactResolutionTool = {
|
||||
emit_artifact_resolution: createEmitArtifactResolutionTool({
|
||||
stageIndex,
|
||||
allowedPaths: allStagedPaths,
|
||||
}),
|
||||
emit_artifact_resolution: createRuntimeToolDescriptorFromAiTool(
|
||||
'emit_artifact_resolution',
|
||||
createEmitArtifactResolutionTool({
|
||||
stageIndex,
|
||||
allowedPaths: allStagedPaths,
|
||||
}),
|
||||
),
|
||||
};
|
||||
const rcEmitUnmappedFallbackTool = {
|
||||
emit_unmapped_fallback: createEmitUnmappedFallbackTool({
|
||||
stageIndex,
|
||||
allowedPaths: allStagedPaths,
|
||||
tableRefExists: (tableRef) => this.tableRefExistsInSemanticLayer(rcScopedSl, slConnectionIds, tableRef),
|
||||
}),
|
||||
emit_unmapped_fallback: createRuntimeToolDescriptorFromAiTool(
|
||||
'emit_unmapped_fallback',
|
||||
createEmitUnmappedFallbackTool({
|
||||
stageIndex,
|
||||
allowedPaths: allStagedPaths,
|
||||
tableRefExists: (tableRef) => this.tableRefExistsInSemanticLayer(rcScopedSl, slConnectionIds, tableRef),
|
||||
}),
|
||||
),
|
||||
};
|
||||
|
||||
const reconcileBaseFraming = await this.deps.promptService.loadPrompt('memory_agent_bundle_ingest_reconcile');
|
||||
|
|
@ -1026,7 +1060,7 @@ export class IngestBundleRunner {
|
|||
emitArtifactResolutionTool: rcEmitArtifactResolutionTool,
|
||||
emitUnmappedFallbackTool: rcEmitUnmappedFallbackTool,
|
||||
readRawSpanTool: rcRawSpanTool,
|
||||
toolsetTools: rcToolset.toAiSdkTools(rcToolContext),
|
||||
toolsetTools: rcToolset.toRuntimeTools(rcToolContext),
|
||||
}),
|
||||
join(transcriptDir, 'reconcile.jsonl'),
|
||||
'reconcile',
|
||||
|
|
@ -1075,7 +1109,7 @@ export class IngestBundleRunner {
|
|||
emitArtifactResolutionTool: rcEmitArtifactResolutionTool,
|
||||
emitUnmappedFallbackTool: rcEmitUnmappedFallbackTool,
|
||||
readRawSpanTool: rcRawSpanTool,
|
||||
toolsetTools: rcToolset.toAiSdkTools(rcToolContext),
|
||||
toolsetTools: rcToolset.toRuntimeTools(rcToolContext),
|
||||
}),
|
||||
join(transcriptDir, 'reconcile.jsonl'),
|
||||
'reconcile',
|
||||
|
|
|
|||
|
|
@ -55,13 +55,39 @@ describe('createLocalBundleIngestRuntime', () => {
|
|||
}),
|
||||
).toThrow(
|
||||
[
|
||||
'ktx ingest requires llm.provider.backend: anthropic, vertex, or gateway, or an injected agentRunner.',
|
||||
'ktx ingest requires llm.provider.backend: anthropic, vertex, gateway, or claude-code, or an injected agentRunner.',
|
||||
`Configure an Anthropic provider, then rerun ingest:`,
|
||||
` ktx setup --project-dir ${project.projectDir} --anthropic-api-key-env ANTHROPIC_API_KEY --anthropic-model claude-sonnet-4-6 --no-input`,
|
||||
].join('\n'),
|
||||
);
|
||||
});
|
||||
|
||||
it('uses a runtime-backed agent runner when claude-code is configured', () => {
|
||||
const runtime = {
|
||||
generateText: vi.fn(),
|
||||
generateObject: vi.fn(),
|
||||
runAgentLoop: vi.fn(async () => ({ stopReason: 'natural' as const })),
|
||||
};
|
||||
project.config.llm = {
|
||||
provider: { backend: 'claude-code' },
|
||||
models: { default: 'sonnet' },
|
||||
promptCaching: { enabled: false },
|
||||
};
|
||||
const createLlmRuntime = vi.fn(() => runtime);
|
||||
|
||||
const created = createLocalBundleIngestRuntime({
|
||||
project,
|
||||
adapters: [new FakeSourceAdapter()],
|
||||
createLlmRuntime,
|
||||
});
|
||||
|
||||
expect(created).toBeDefined();
|
||||
expect(createLlmRuntime).toHaveBeenCalledWith(
|
||||
project.config.llm,
|
||||
expect.objectContaining({ projectDir: project.projectDir }),
|
||||
);
|
||||
});
|
||||
|
||||
it('builds runner deps with local SQLite stores and context tools enabled', async () => {
|
||||
const agentRunner = new AgentRunnerService({ llmProvider: { getModel: () => ({}) as never } as any });
|
||||
|
||||
|
|
|
|||
|
|
@ -1,20 +1,20 @@
|
|||
import { mkdirSync } from 'node:fs';
|
||||
import { join } from 'node:path';
|
||||
import { fileURLToPath } from 'node:url';
|
||||
import type { KtxLlmProvider } from '@ktx/llm';
|
||||
import type { Tool } from 'ai';
|
||||
import YAML from 'yaml';
|
||||
import type { AgentRunnerService } from '../agent/index.js';
|
||||
import { AgentRunnerService as DefaultAgentRunnerService } from '../agent/index.js';
|
||||
import { localConnectionInfoFromConfig, type KtxSqlQueryExecutorPort } from '../connections/index.js';
|
||||
import type { KtxEmbeddingPort, KtxLogger } from '../core/index.js';
|
||||
import { noopLogger, SessionWorktreeService } from '../core/index.js';
|
||||
import type { KtxSemanticLayerComputePort } from '../daemon/index.js';
|
||||
import {
|
||||
createJsonlKtxLlmDebugRequestRecorder,
|
||||
createRuntimeToolDescriptorFromAiTool,
|
||||
createLocalKtxEmbeddingProviderFromConfig,
|
||||
createLocalKtxLlmProviderFromConfig,
|
||||
createLocalKtxLlmRuntimeFromConfig,
|
||||
KtxIngestEmbeddingPortAdapter,
|
||||
RuntimeAgentRunner,
|
||||
type AgentRunnerPort,
|
||||
type KtxLlmRuntimePort,
|
||||
type KtxRuntimeToolSet,
|
||||
} from '../llm/index.js';
|
||||
import type { KtxLocalProject } from '../project/index.js';
|
||||
import { ktxLocalStateDbPath } from '../project/index.js';
|
||||
|
|
@ -100,8 +100,9 @@ const LOCAL_SHAPE_WARNING = 'Local ingest validates semantic-layer YAML shape on
|
|||
export interface CreateLocalBundleIngestRuntimeOptions {
|
||||
project: KtxLocalProject;
|
||||
adapters: SourceAdapter[];
|
||||
agentRunner?: AgentRunnerService;
|
||||
llmProvider?: KtxLlmProvider;
|
||||
agentRunner?: AgentRunnerPort;
|
||||
llmRuntime?: KtxLlmRuntimePort;
|
||||
createLlmRuntime?: typeof createLocalKtxLlmRuntimeFromConfig;
|
||||
llmDebugRequestFile?: string;
|
||||
memoryModel?: string;
|
||||
semanticLayerCompute?: KtxSemanticLayerComputePort;
|
||||
|
|
@ -456,12 +457,12 @@ class NoopKnowledgeEventPort implements KnowledgeEventPort {
|
|||
class LocalIngestToolSet implements IngestToolsetLike {
|
||||
constructor(
|
||||
private readonly tools: BaseTool[],
|
||||
private readonly sourceTools: Record<string, Tool> = {},
|
||||
private readonly sourceTools: KtxRuntimeToolSet = {},
|
||||
) {}
|
||||
|
||||
toAiSdkTools(context: ToolContext) {
|
||||
toRuntimeTools(context: ToolContext): KtxRuntimeToolSet {
|
||||
return {
|
||||
...Object.fromEntries(this.tools.map((tool) => [tool.name, tool.toAiSdkTool(context)])),
|
||||
...Object.fromEntries(this.tools.map((tool) => [tool.name, tool.toRuntimeTool(context)])),
|
||||
...this.sourceTools,
|
||||
};
|
||||
}
|
||||
|
|
@ -541,13 +542,16 @@ class LocalIngestToolsetFactory implements IngestToolsetFactoryPort {
|
|||
}
|
||||
|
||||
createIngestWuToolset(session: ToolSession, options?: { includeContextEvidenceTools?: boolean }): IngestToolsetLike {
|
||||
const sourceTools: Record<string, Tool> =
|
||||
const sourceTools: KtxRuntimeToolSet =
|
||||
session.ingest?.sourceKey === 'historic-sql'
|
||||
? {
|
||||
emit_historic_sql_evidence: createEmitHistoricSqlEvidenceTool({
|
||||
connectionId: session.connectionId,
|
||||
session,
|
||||
}),
|
||||
emit_historic_sql_evidence: createRuntimeToolDescriptorFromAiTool(
|
||||
'emit_historic_sql_evidence',
|
||||
createEmitHistoricSqlEvidenceTool({
|
||||
connectionId: session.connectionId,
|
||||
session,
|
||||
}),
|
||||
),
|
||||
}
|
||||
: {};
|
||||
return new LocalIngestToolSet(
|
||||
|
|
@ -571,36 +575,35 @@ function nextLocalJobId(): string {
|
|||
|
||||
function localIngestLlmProviderGuardMessage(projectDir: string): string {
|
||||
return [
|
||||
'ktx ingest requires llm.provider.backend: anthropic, vertex, or gateway, or an injected agentRunner.',
|
||||
'ktx ingest requires llm.provider.backend: anthropic, vertex, gateway, or claude-code, or an injected agentRunner.',
|
||||
'Configure an Anthropic provider, then rerun ingest:',
|
||||
` ktx setup --project-dir ${projectDir} --anthropic-api-key-env ANTHROPIC_API_KEY --anthropic-model claude-sonnet-4-6 --no-input`,
|
||||
].join('\n');
|
||||
}
|
||||
|
||||
function resolveAgentRunner(options: CreateLocalBundleIngestRuntimeOptions): {
|
||||
agentRunner: AgentRunnerService;
|
||||
llmProvider?: KtxLlmProvider;
|
||||
agentRunner: AgentRunnerPort;
|
||||
llmRuntime?: KtxLlmRuntimePort;
|
||||
} {
|
||||
const llmProvider =
|
||||
options.llmProvider ?? createLocalKtxLlmProviderFromConfig(options.project.config.llm) ?? undefined;
|
||||
const llmRuntime =
|
||||
options.llmRuntime ??
|
||||
(options.createLlmRuntime ?? createLocalKtxLlmRuntimeFromConfig)(options.project.config.llm, {
|
||||
projectDir: options.project.projectDir,
|
||||
env: process.env,
|
||||
}) ??
|
||||
undefined;
|
||||
|
||||
if (options.agentRunner) {
|
||||
return { agentRunner: options.agentRunner, ...(llmProvider ? { llmProvider } : {}) };
|
||||
return { agentRunner: options.agentRunner, ...(llmRuntime ? { llmRuntime } : {}) };
|
||||
}
|
||||
|
||||
if (!llmProvider) {
|
||||
if (!llmRuntime) {
|
||||
throw new Error(localIngestLlmProviderGuardMessage(options.project.projectDir));
|
||||
}
|
||||
|
||||
return {
|
||||
agentRunner: new DefaultAgentRunnerService({
|
||||
llmProvider,
|
||||
logger: options.logger ?? noopLogger,
|
||||
...(options.llmDebugRequestFile
|
||||
? { debugRequestRecorder: createJsonlKtxLlmDebugRequestRecorder(options.llmDebugRequestFile) }
|
||||
: {}),
|
||||
}),
|
||||
llmProvider,
|
||||
agentRunner: new RuntimeAgentRunner(llmRuntime),
|
||||
llmRuntime,
|
||||
};
|
||||
}
|
||||
|
||||
|
|
@ -627,7 +630,7 @@ export function createLocalBundleIngestRuntime(
|
|||
const knowledgeIndex = new LocalKnowledgeIndex(options.project, embedding);
|
||||
const knowledgeEvents = new NoopKnowledgeEventPort();
|
||||
const wikiService = new KnowledgeWikiService(rootFileStore, embedding, knowledgeIndex, options.project.git, logger);
|
||||
const { agentRunner, llmProvider } = resolveAgentRunner(options);
|
||||
const { agentRunner, llmRuntime } = resolveAgentRunner(options);
|
||||
const promptService = new PromptService({ promptsDir, partials: [], logger });
|
||||
const storage = new LocalIngestStorage(options.project);
|
||||
const registry = registerAdapters(options.adapters);
|
||||
|
|
@ -681,10 +684,11 @@ export function createLocalBundleIngestRuntime(
|
|||
commitMessages: new LocalCommitMessagePort(),
|
||||
embedding,
|
||||
contextEvidenceIndex: new ContextEvidenceIndexService({ store: contextStore, embeddings: embedding, logger }),
|
||||
pageTriage: llmProvider
|
||||
llmRuntime,
|
||||
pageTriage: llmRuntime
|
||||
? new PageTriageService({
|
||||
store: contextStore,
|
||||
llmProvider,
|
||||
llmRuntime,
|
||||
settings: {
|
||||
enabled: true,
|
||||
maxConcurrency: 2,
|
||||
|
|
|
|||
|
|
@ -1,11 +1,10 @@
|
|||
import { randomUUID } from 'node:crypto';
|
||||
import { cp, mkdir, rm } from 'node:fs/promises';
|
||||
import { isAbsolute, resolve } from 'node:path';
|
||||
import type { KtxLlmProvider } from '@ktx/llm';
|
||||
import type { AgentRunnerService } from '../agent/index.js';
|
||||
import type { KtxSqlQueryExecutorPort } from '../connections/index.js';
|
||||
import type { KtxLogger } from '../core/index.js';
|
||||
import type { KtxSemanticLayerComputePort } from '../daemon/index.js';
|
||||
import type { AgentRunnerPort, KtxLlmRuntimePort } from '../llm/index.js';
|
||||
import type { KtxLocalProject } from '../project/index.js';
|
||||
import { ktxLocalStateDbPath } from '../project/index.js';
|
||||
import { planMetabaseFanoutChildren } from './adapters/metabase/fanout-planner.js';
|
||||
|
|
@ -28,8 +27,8 @@ export interface RunLocalIngestOptions {
|
|||
trigger?: IngestTrigger;
|
||||
jobId?: string;
|
||||
memoryFlow?: MemoryFlowEventSink;
|
||||
agentRunner?: AgentRunnerService;
|
||||
llmProvider?: KtxLlmProvider;
|
||||
agentRunner?: AgentRunnerPort;
|
||||
llmRuntime?: KtxLlmRuntimePort;
|
||||
llmDebugRequestFile?: string;
|
||||
memoryModel?: string;
|
||||
semanticLayerCompute?: KtxSemanticLayerComputePort;
|
||||
|
|
@ -41,7 +40,7 @@ export interface LocalIngestMcpOptions
|
|||
extends Pick<
|
||||
RunLocalIngestOptions,
|
||||
| 'agentRunner'
|
||||
| 'llmProvider'
|
||||
| 'llmRuntime'
|
||||
| 'memoryModel'
|
||||
| 'semanticLayerCompute'
|
||||
| 'queryExecutor'
|
||||
|
|
@ -167,8 +166,8 @@ async function runScheduledPullJob(options: {
|
|||
trigger?: IngestTrigger;
|
||||
jobId?: string;
|
||||
memoryFlow?: MemoryFlowEventSink;
|
||||
agentRunner?: AgentRunnerService;
|
||||
llmProvider?: KtxLlmProvider;
|
||||
agentRunner?: AgentRunnerPort;
|
||||
llmRuntime?: KtxLlmRuntimePort;
|
||||
memoryModel?: string;
|
||||
semanticLayerCompute?: KtxSemanticLayerComputePort;
|
||||
queryExecutor?: KtxSqlQueryExecutorPort;
|
||||
|
|
@ -221,7 +220,7 @@ export async function runLocalIngest(options: RunLocalIngestOptions): Promise<Lo
|
|||
jobId,
|
||||
memoryFlow: options.memoryFlow,
|
||||
agentRunner: options.agentRunner,
|
||||
llmProvider: options.llmProvider,
|
||||
llmRuntime: options.llmRuntime,
|
||||
memoryModel: options.memoryModel,
|
||||
semanticLayerCompute: options.semanticLayerCompute,
|
||||
queryExecutor: options.queryExecutor,
|
||||
|
|
@ -406,7 +405,7 @@ export async function runLocalMetabaseIngest(
|
|||
jobId: childJobId,
|
||||
memoryFlow: options.memoryFlow,
|
||||
agentRunner: options.agentRunner,
|
||||
llmProvider: options.llmProvider,
|
||||
llmRuntime: options.llmRuntime,
|
||||
memoryModel: options.memoryModel,
|
||||
semanticLayerCompute: options.semanticLayerCompute,
|
||||
queryExecutor: options.queryExecutor,
|
||||
|
|
|
|||
|
|
@ -1,8 +1,7 @@
|
|||
import type { ToolSet } from 'ai';
|
||||
import type { KtxModelRole } from '@ktx/llm';
|
||||
import type { AgentRunnerService } from '../agent/index.js';
|
||||
import type { KtxEmbeddingPort } from '../core/embedding.js';
|
||||
import type { GitService, KtxFileStorePort, KtxLogger, SessionOutcome } from '../core/index.js';
|
||||
import type { AgentRunnerPort, KtxLlmRuntimePort, KtxRuntimeToolSet } from '../llm/index.js';
|
||||
import type { CaptureSession, MemoryAction, MemoryKnowledgeSlRefsPort } from '../memory/index.js';
|
||||
import type { PromptService } from '../prompts/index.js';
|
||||
import type { SkillsRegistryService } from '../skills/index.js';
|
||||
|
|
@ -163,7 +162,7 @@ export interface IngestCommitMessagePort {
|
|||
}
|
||||
|
||||
export interface IngestToolsetLike {
|
||||
toAiSdkTools(context: ToolContext): ToolSet;
|
||||
toRuntimeTools(context: ToolContext): KtxRuntimeToolSet;
|
||||
}
|
||||
|
||||
export interface IngestToolsetFactoryPort {
|
||||
|
|
@ -315,7 +314,7 @@ export interface CuratorPaginationPort {
|
|||
items: ReconcileCandidateForPrompt[];
|
||||
runState: ReconcilePromptRunState;
|
||||
}) => string;
|
||||
buildToolSet: (passNumber: number) => ToolSet;
|
||||
buildToolSet: (passNumber: number) => KtxRuntimeToolSet;
|
||||
getReconciliationActions: () => MemoryAction[];
|
||||
onStepFinish?: (info: { passNumber: number; stepIndex: number; stepBudget: number }) => void;
|
||||
}): Promise<ReconciliationOutcome & { report: CuratorPaginationReport; warnings: string[] }>;
|
||||
|
|
@ -350,7 +349,8 @@ export interface IngestBundleRunnerDeps {
|
|||
registry: SourceAdapterRegistryPort;
|
||||
diffSetService: DiffSetComputerPort;
|
||||
sessionWorktreeService: IngestSessionWorktreePort;
|
||||
agentRunner: AgentRunnerService;
|
||||
agentRunner: AgentRunnerPort;
|
||||
llmRuntime?: KtxLlmRuntimePort;
|
||||
gitService: GitService;
|
||||
lockingService: IngestLockPort;
|
||||
storage: IngestStoragePort;
|
||||
|
|
|
|||
|
|
@ -141,26 +141,17 @@ describe('buildReconcileToolSet', () => {
|
|||
toolsetTools: { sl_write_source: { description: 'sl write', inputSchema: {} as any, execute: slWrite } as any },
|
||||
});
|
||||
|
||||
const correction = await toolSet.sl_write_source.execute?.(
|
||||
{ connectionId: 'warehouse', sourceName: 'accounts' },
|
||||
{ toolCallId: 't1' } as any,
|
||||
);
|
||||
const correction = await toolSet.sl_write_source.execute?.({ connectionId: 'warehouse', sourceName: 'accounts' });
|
||||
|
||||
expect(slWrite).not.toHaveBeenCalled();
|
||||
expect(correction).toMatchObject({ structured: { success: false, reason: 'verification_ledger_required' } });
|
||||
|
||||
await toolSet.record_verification_ledger.execute?.(
|
||||
{
|
||||
summary: 'Verified warehouse.accounts with entity_details.',
|
||||
verifiedIdentifiers: ['warehouse.accounts'],
|
||||
unverifiedIdentifiers: [],
|
||||
},
|
||||
{ toolCallId: 't2' } as any,
|
||||
);
|
||||
const written = await toolSet.sl_write_source.execute?.(
|
||||
{ connectionId: 'warehouse', sourceName: 'accounts' },
|
||||
{ toolCallId: 't3' } as any,
|
||||
);
|
||||
await toolSet.record_verification_ledger.execute?.({
|
||||
summary: 'Verified warehouse.accounts with entity_details.',
|
||||
verifiedIdentifiers: ['warehouse.accounts'],
|
||||
unverifiedIdentifiers: [],
|
||||
});
|
||||
const written = await toolSet.sl_write_source.execute?.({ connectionId: 'warehouse', sourceName: 'accounts' });
|
||||
|
||||
expect(slWrite).toHaveBeenCalledTimes(1);
|
||||
expect(written).toMatchObject({ structured: { success: true } });
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
import type { Tool, ToolSet } from 'ai';
|
||||
import { buildCanonicalPinsPromptBlock, type CanonicalPin } from '../canonical-pins.js';
|
||||
import type { KtxRuntimeToolSet } from '../../llm/index.js';
|
||||
import {
|
||||
createVerificationLedgerState,
|
||||
VERIFICATION_LEDGER_PROMPT,
|
||||
|
|
@ -181,19 +181,19 @@ export function buildReconcileUserPrompt(
|
|||
}
|
||||
|
||||
export interface ReconcileToolSetInput {
|
||||
loadSkillTool: Record<string, Tool>;
|
||||
stageListTool: Record<string, Tool>;
|
||||
stageDiffTool: Record<string, Tool>;
|
||||
evictionListTool: Record<string, Tool>;
|
||||
emitConflictResolutionTool: Record<string, Tool>;
|
||||
emitEvictionDecisionTool: Record<string, Tool>;
|
||||
emitArtifactResolutionTool: Record<string, Tool>;
|
||||
emitUnmappedFallbackTool: Record<string, Tool>;
|
||||
readRawSpanTool: Record<string, Tool>;
|
||||
toolsetTools: ToolSet;
|
||||
loadSkillTool: KtxRuntimeToolSet;
|
||||
stageListTool: KtxRuntimeToolSet;
|
||||
stageDiffTool: KtxRuntimeToolSet;
|
||||
evictionListTool: KtxRuntimeToolSet;
|
||||
emitConflictResolutionTool: KtxRuntimeToolSet;
|
||||
emitEvictionDecisionTool: KtxRuntimeToolSet;
|
||||
emitArtifactResolutionTool: KtxRuntimeToolSet;
|
||||
emitUnmappedFallbackTool: KtxRuntimeToolSet;
|
||||
readRawSpanTool: KtxRuntimeToolSet;
|
||||
toolsetTools: KtxRuntimeToolSet;
|
||||
}
|
||||
|
||||
export function buildReconcileToolSet(input: ReconcileToolSetInput): ToolSet {
|
||||
export function buildReconcileToolSet(input: ReconcileToolSetInput): KtxRuntimeToolSet {
|
||||
const state = createVerificationLedgerState();
|
||||
return withVerificationLedger(
|
||||
{
|
||||
|
|
|
|||
|
|
@ -87,21 +87,18 @@ describe('buildWuToolSet', () => {
|
|||
toolsetTools: { wiki_write: { description: 'write', inputSchema: {} as any, execute: wikiWrite } as any },
|
||||
});
|
||||
|
||||
const correction = await toolSet.wiki_write.execute?.({ key: 'customer-rules' }, { toolCallId: 't1' } as any);
|
||||
const correction = await toolSet.wiki_write.execute?.({ key: 'customer-rules' });
|
||||
|
||||
expect(wikiWrite).not.toHaveBeenCalled();
|
||||
expect(correction).toMatchObject({ structured: { success: false, reason: 'verification_ledger_required' } });
|
||||
expect(String((correction as any).markdown)).toContain('record_verification_ledger');
|
||||
|
||||
await toolSet.record_verification_ledger.execute?.(
|
||||
{
|
||||
summary: 'No warehouse identifiers will be emitted in this wiki write.',
|
||||
verifiedIdentifiers: [],
|
||||
unverifiedIdentifiers: [],
|
||||
},
|
||||
{ toolCallId: 't2' } as any,
|
||||
);
|
||||
const written = await toolSet.wiki_write.execute?.({ key: 'customer-rules' }, { toolCallId: 't3' } as any);
|
||||
await toolSet.record_verification_ledger.execute?.({
|
||||
summary: 'No warehouse identifiers will be emitted in this wiki write.',
|
||||
verifiedIdentifiers: [],
|
||||
unverifiedIdentifiers: [],
|
||||
});
|
||||
const written = await toolSet.wiki_write.execute?.({ key: 'customer-rules' });
|
||||
|
||||
expect(wikiWrite).toHaveBeenCalledTimes(1);
|
||||
expect(written).toMatchObject({ structured: { success: true } });
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
import type { Tool, ToolSet } from 'ai';
|
||||
import { buildCanonicalPinsPromptBlock, type CanonicalPin } from '../canonical-pins.js';
|
||||
import { createLookerQueryToSlTool } from '../adapters/looker/tools/looker-query-to-sl.tool.js';
|
||||
import { createRuntimeToolDescriptorFromAiTool, type KtxRuntimeToolSet } from '../../llm/index.js';
|
||||
import type { IngestProvenanceRow } from '../ports.js';
|
||||
import { createReadRawFileTool } from '../tools/read-raw-file.tool.js';
|
||||
import { createReadRawSpanTool } from '../tools/read-raw-span.tool.js';
|
||||
|
|
@ -88,12 +88,12 @@ export interface BuildWuToolSetInput {
|
|||
sourceKey?: string;
|
||||
stagedDir: string;
|
||||
wu: WorkUnit;
|
||||
loadSkillTool: Record<string, Tool>;
|
||||
emitUnmappedFallbackTool: Record<string, Tool>;
|
||||
toolsetTools: ToolSet;
|
||||
loadSkillTool: KtxRuntimeToolSet;
|
||||
emitUnmappedFallbackTool: KtxRuntimeToolSet;
|
||||
toolsetTools: KtxRuntimeToolSet;
|
||||
}
|
||||
|
||||
function withoutWriteSlTools(toolset: ToolSet, wu: WorkUnit): ToolSet {
|
||||
function withoutWriteSlTools(toolset: KtxRuntimeToolSet, wu: WorkUnit): KtxRuntimeToolSet {
|
||||
if (!wu.slDisallowed) {
|
||||
return toolset;
|
||||
}
|
||||
|
|
@ -103,9 +103,12 @@ function withoutWriteSlTools(toolset: ToolSet, wu: WorkUnit): ToolSet {
|
|||
return next;
|
||||
}
|
||||
|
||||
export function buildWuToolSet(input: BuildWuToolSetInput): ToolSet {
|
||||
export function buildWuToolSet(input: BuildWuToolSetInput): KtxRuntimeToolSet {
|
||||
const allowedPaths = new Set<string>([...input.wu.rawFiles, ...input.wu.dependencyPaths]);
|
||||
const lookerTools: ToolSet = input.sourceKey === 'looker' ? { looker_query_to_sl: createLookerQueryToSlTool() } : {};
|
||||
const lookerTools: KtxRuntimeToolSet =
|
||||
input.sourceKey === 'looker'
|
||||
? { looker_query_to_sl: createRuntimeToolDescriptorFromAiTool('looker_query_to_sl', createLookerQueryToSlTool()) }
|
||||
: {};
|
||||
const state = createVerificationLedgerState();
|
||||
return withVerificationLedger(
|
||||
withoutWriteSlTools(
|
||||
|
|
@ -114,8 +117,14 @@ export function buildWuToolSet(input: BuildWuToolSetInput): ToolSet {
|
|||
...lookerTools,
|
||||
...input.loadSkillTool,
|
||||
...input.emitUnmappedFallbackTool,
|
||||
read_raw_file: createReadRawFileTool({ stagedDir: input.stagedDir, allowedPaths }),
|
||||
read_raw_span: createReadRawSpanTool({ stagedDir: input.stagedDir, allowedPaths }),
|
||||
read_raw_file: createRuntimeToolDescriptorFromAiTool(
|
||||
'read_raw_file',
|
||||
createReadRawFileTool({ stagedDir: input.stagedDir, allowedPaths }),
|
||||
),
|
||||
read_raw_span: createRuntimeToolDescriptorFromAiTool(
|
||||
'read_raw_span',
|
||||
createReadRawSpanTool({ stagedDir: input.stagedDir, allowedPaths }),
|
||||
),
|
||||
},
|
||||
input.wu,
|
||||
),
|
||||
|
|
|
|||
|
|
@ -1,6 +1,5 @@
|
|||
import type { AgentRunnerService } from '@ktx/context/agent';
|
||||
import type { KtxModelRole } from '@ktx/llm';
|
||||
import type { Tool } from 'ai';
|
||||
import type { AgentRunnerPort, KtxRuntimeToolSet } from '@ktx/context';
|
||||
import type { CaptureSession, MemoryAction } from '../../memory/index.js';
|
||||
import { listTouchedSlSources, type TouchedSlSource } from '../../tools/index.js';
|
||||
import type { WorkUnit } from '../types.js';
|
||||
|
|
@ -14,12 +13,12 @@ export interface TouchedValidationResult {
|
|||
|
||||
export interface WorkUnitExecutionDeps {
|
||||
sessionWorktreeGit: { revParseHead(): Promise<string | null> };
|
||||
agentRunner: AgentRunnerService;
|
||||
agentRunner: AgentRunnerPort;
|
||||
validateTouchedSources: (touched: TouchedSlSource[]) => Promise<TouchedValidationResult>;
|
||||
resetHardTo: (targetSha: string) => Promise<void>;
|
||||
buildSystemPrompt: (wu: WorkUnit) => string;
|
||||
buildUserPrompt: (wu: WorkUnit) => string;
|
||||
buildToolSet: (wu: WorkUnit) => Record<string, Tool>;
|
||||
buildToolSet: (wu: WorkUnit) => KtxRuntimeToolSet;
|
||||
captureSession: CaptureSession;
|
||||
sessionActions: MemoryAction[];
|
||||
modelRole: KtxModelRole;
|
||||
|
|
|
|||
|
|
@ -1,16 +1,15 @@
|
|||
import type { AgentRunnerService } from '@ktx/context/agent';
|
||||
import type { AgentRunnerPort, KtxRuntimeToolSet } from '@ktx/context';
|
||||
import type { KtxModelRole } from '@ktx/llm';
|
||||
import type { ToolSet } from 'ai';
|
||||
import type { EvictionUnit } from '../types.js';
|
||||
import type { StageIndex } from './stage-index.types.js';
|
||||
|
||||
export interface ReconciliationContext {
|
||||
stageIndex: StageIndex;
|
||||
evictionUnit: EvictionUnit | undefined;
|
||||
agentRunner: AgentRunnerService;
|
||||
agentRunner: AgentRunnerPort;
|
||||
buildSystemPrompt: (idx: StageIndex, ev: EvictionUnit | undefined) => string;
|
||||
buildUserPrompt: (idx: StageIndex, ev: EvictionUnit | undefined) => string;
|
||||
buildToolSet: () => ToolSet;
|
||||
buildToolSet: () => KtxRuntimeToolSet;
|
||||
modelRole: KtxModelRole;
|
||||
stepBudget: number;
|
||||
sourceKey: string;
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
import { appendFile, mkdir } from 'node:fs/promises';
|
||||
import { dirname } from 'node:path';
|
||||
import type { ToolExecuteFunction, ToolExecutionOptions, ToolSet } from 'ai';
|
||||
import type { KtxRuntimeToolSet } from '../../llm/index.js';
|
||||
|
||||
export interface ToolCallLogEntry {
|
||||
ts: string;
|
||||
|
|
@ -31,7 +31,7 @@ interface ToolCallLoggerOptions {
|
|||
* sequential (`generateText` awaits each tool result), so per-WU files are
|
||||
* effectively single-writer and lines land in call order.
|
||||
*/
|
||||
export function wrapToolsWithLogger<T extends ToolSet>(
|
||||
export function wrapToolsWithLogger<T extends KtxRuntimeToolSet>(
|
||||
tools: T,
|
||||
logFilePath: string,
|
||||
wuKey: string,
|
||||
|
|
@ -44,17 +44,13 @@ export function wrapToolsWithLogger<T extends ToolSet>(
|
|||
wrapped[name] = original;
|
||||
continue;
|
||||
}
|
||||
const wrappedExecute: ToolExecuteFunction<unknown, unknown> = async (
|
||||
input: unknown,
|
||||
opts: ToolExecutionOptions,
|
||||
) => {
|
||||
const wrappedExecute = async (input: unknown) => {
|
||||
const start = Date.now();
|
||||
try {
|
||||
const output = await (originalExecute as ToolExecuteFunction<unknown, unknown>)(input, opts);
|
||||
const output = await originalExecute(input);
|
||||
const entry: ToolCallLogEntry = {
|
||||
ts: new Date().toISOString(),
|
||||
wuKey,
|
||||
toolCallId: opts.toolCallId,
|
||||
toolName: name,
|
||||
durationMs: Date.now() - start,
|
||||
input,
|
||||
|
|
@ -67,7 +63,6 @@ export function wrapToolsWithLogger<T extends ToolSet>(
|
|||
const entry: ToolCallLogEntry = {
|
||||
ts: new Date().toISOString(),
|
||||
wuKey,
|
||||
toolCallId: opts.toolCallId,
|
||||
toolName: name,
|
||||
durationMs: Date.now() - start,
|
||||
input,
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
import { tool, type ToolExecuteFunction, type ToolExecutionOptions, type ToolSet } from 'ai';
|
||||
import { z } from 'zod';
|
||||
import type { KtxRuntimeToolDescriptor, KtxRuntimeToolSet } from '../../llm/index.js';
|
||||
|
||||
const verificationLedgerInputSchema = z.object({
|
||||
summary: z.string().min(1).max(2000),
|
||||
|
|
@ -37,22 +37,19 @@ export function createVerificationLedgerState(): VerificationLedgerState {
|
|||
return { entries: [] };
|
||||
}
|
||||
|
||||
export function withVerificationLedger(tools: ToolSet, state: VerificationLedgerState): ToolSet {
|
||||
const wrapped: ToolSet = {};
|
||||
export function withVerificationLedger(tools: KtxRuntimeToolSet, state: VerificationLedgerState): KtxRuntimeToolSet {
|
||||
const wrapped: KtxRuntimeToolSet = {};
|
||||
for (const [name, original] of Object.entries(tools)) {
|
||||
if (!WRITE_TOOL_NAMES.has(name) || typeof original.execute !== 'function') {
|
||||
wrapped[name] = original;
|
||||
continue;
|
||||
}
|
||||
const originalExecute = original.execute;
|
||||
const guardedExecute: ToolExecuteFunction<unknown, unknown> = async (
|
||||
input: unknown,
|
||||
opts: ToolExecutionOptions,
|
||||
) => {
|
||||
const guardedExecute = async (input: unknown) => {
|
||||
if (state.entries.length === 0) {
|
||||
return verificationRequiredOutput(name);
|
||||
}
|
||||
return (originalExecute as ToolExecuteFunction<unknown, unknown>)(input, opts);
|
||||
return originalExecute(input);
|
||||
};
|
||||
wrapped[name] = { ...original, execute: guardedExecute };
|
||||
}
|
||||
|
|
@ -60,8 +57,9 @@ export function withVerificationLedger(tools: ToolSet, state: VerificationLedger
|
|||
return wrapped;
|
||||
}
|
||||
|
||||
function createRecordVerificationLedgerTool(state: VerificationLedgerState) {
|
||||
return tool({
|
||||
function createRecordVerificationLedgerTool(state: VerificationLedgerState): KtxRuntimeToolDescriptor {
|
||||
return {
|
||||
name: 'record_verification_ledger',
|
||||
description:
|
||||
'Record the pre-write verification ledger required by loaded ingest skills. Call this before wiki/SL/fallback writes to state what was verified, which tool calls support it, and what remains intentionally unverified.',
|
||||
inputSchema: verificationLedgerInputSchema,
|
||||
|
|
@ -78,7 +76,7 @@ function createRecordVerificationLedgerTool(state: VerificationLedgerState) {
|
|||
structured: { success: true, entry },
|
||||
};
|
||||
},
|
||||
});
|
||||
};
|
||||
}
|
||||
|
||||
function verificationRequiredOutput(toolName: string) {
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
import { KtxMessageBuilder, splitKtxSystemMessages, type KtxLlmProvider } from '@ktx/llm';
|
||||
import { generateText, Output, stepCountIs, type FlexibleSchema, type TelemetrySettings } from 'ai';
|
||||
import { generateText, Output, stepCountIs, type FlexibleSchema, type TelemetrySettings, type ToolSet } from 'ai';
|
||||
import type { z } from 'zod';
|
||||
import { noopLogger, type KtxLogger } from '../core/index.js';
|
||||
import { summarizeKtxLlmDebugRequest, type KtxLlmDebugRequestRecorder } from './debug-request-recorder.js';
|
||||
|
|
@ -52,7 +52,7 @@ export class AiSdkKtxLlmRuntime implements KtxLlmRuntimePort {
|
|||
temperature: input.temperature ?? 0,
|
||||
...(split.system ? { system: split.system } : {}),
|
||||
messages: split.messages,
|
||||
tools: built.tools,
|
||||
tools: built.tools as ToolSet,
|
||||
...(hasTools(tools)
|
||||
? {
|
||||
experimental_repairToolCall: this.deps.llmProvider.repairToolCallHandler({
|
||||
|
|
@ -84,7 +84,7 @@ export class AiSdkKtxLlmRuntime implements KtxLlmRuntimePort {
|
|||
temperature: input.temperature ?? 0,
|
||||
...(split.system ? { system: split.system } : {}),
|
||||
messages: split.messages,
|
||||
tools: built.tools,
|
||||
tools: built.tools as ToolSet,
|
||||
...(hasTools(tools)
|
||||
? {
|
||||
experimental_repairToolCall: this.deps.llmProvider.repairToolCallHandler({
|
||||
|
|
@ -137,7 +137,7 @@ export class AiSdkKtxLlmRuntime implements KtxLlmRuntimePort {
|
|||
}),
|
||||
...(promptMessages.system ? { system: promptMessages.system } : {}),
|
||||
messages: promptMessages.messages,
|
||||
tools: built.tools,
|
||||
tools: built.tools as ToolSet,
|
||||
onStepFinish: async () => {
|
||||
stepIndex += 1;
|
||||
if (!params.onStepFinish) {
|
||||
|
|
|
|||
|
|
@ -16,7 +16,7 @@ function initMessage(overrides: Partial<Extract<SDKMessage, { type: 'system'; su
|
|||
return {
|
||||
type: 'system',
|
||||
subtype: 'init',
|
||||
apiKeySource: 'none',
|
||||
apiKeySource: 'none' as never,
|
||||
claude_code_version: '0.3.142',
|
||||
cwd: '/tmp/project',
|
||||
tools: [],
|
||||
|
|
@ -27,7 +27,7 @@ function initMessage(overrides: Partial<Extract<SDKMessage, { type: 'system'; su
|
|||
output_style: 'default',
|
||||
skills: [],
|
||||
plugins: [],
|
||||
uuid: 'init-id',
|
||||
uuid: '00000000-0000-4000-8000-000000000001',
|
||||
session_id: 'session-id',
|
||||
...overrides,
|
||||
};
|
||||
|
|
@ -51,7 +51,7 @@ function resultMessage(overrides: Partial<Extract<SDKMessage, { type: 'result' }
|
|||
modelUsage: {},
|
||||
permission_denials: [],
|
||||
errors: [],
|
||||
uuid: 'result-id',
|
||||
uuid: '00000000-0000-4000-8000-000000000002',
|
||||
session_id: 'session-id',
|
||||
...overrides,
|
||||
} as Extract<SDKMessage, { type: 'result' }>;
|
||||
|
|
@ -59,7 +59,7 @@ function resultMessage(overrides: Partial<Extract<SDKMessage, { type: 'result' }
|
|||
|
||||
describe('ClaudeCodeKtxLlmRuntime', () => {
|
||||
it('passes isolation options and scrubbed env to text generation', async () => {
|
||||
const query = vi.fn(() => stream([initMessage(), resultMessage({ result: 'hello' })]));
|
||||
const query = vi.fn((_input: any) => stream([initMessage(), resultMessage({ result: 'hello' })]));
|
||||
const runtime = new ClaudeCodeKtxLlmRuntime({
|
||||
projectDir: '/tmp/project',
|
||||
modelSlots: { default: 'sonnet' },
|
||||
|
|
@ -88,7 +88,7 @@ describe('ClaudeCodeKtxLlmRuntime', () => {
|
|||
|
||||
it('validates structured output with the caller schema', async () => {
|
||||
const schema = z.object({ answer: z.string() });
|
||||
const query = vi.fn(() => stream([initMessage(), resultMessage({ structured_output: { answer: 'yes' } })]));
|
||||
const query = vi.fn((_input: any) => stream([initMessage(), resultMessage({ structured_output: { answer: 'yes' } })]));
|
||||
const runtime = new ClaudeCodeKtxLlmRuntime({
|
||||
projectDir: '/tmp/project',
|
||||
modelSlots: { default: 'sonnet' },
|
||||
|
|
@ -104,16 +104,16 @@ describe('ClaudeCodeKtxLlmRuntime', () => {
|
|||
});
|
||||
|
||||
it('registers only exact KTX MCP tool ids and denies non-KTX tools', async () => {
|
||||
const query = vi.fn(() =>
|
||||
const query = vi.fn((_input: any) =>
|
||||
stream([
|
||||
initMessage({ tools: ['mcp__ktx__load_skill'], mcp_servers: [{ name: 'ktx', status: 'connected' }] }),
|
||||
{
|
||||
type: 'assistant',
|
||||
message: { role: 'assistant', content: [] },
|
||||
parent_tool_use_id: null,
|
||||
uuid: 'assistant-1',
|
||||
uuid: '00000000-0000-4000-8000-000000000003',
|
||||
session_id: 'session-id',
|
||||
} as SDKMessage,
|
||||
} as unknown as SDKMessage,
|
||||
resultMessage({ subtype: 'error_max_turns', is_error: true }),
|
||||
]),
|
||||
);
|
||||
|
|
@ -164,7 +164,7 @@ describe('ClaudeCodeKtxLlmRuntime', () => {
|
|||
});
|
||||
|
||||
it('auth probe uses isolation options and a scrubbed env', async () => {
|
||||
const query = vi.fn(() => stream([initMessage(), resultMessage({ result: 'ok' })]));
|
||||
const query = vi.fn((_input: any) => stream([initMessage(), resultMessage({ result: 'ok' })]));
|
||||
|
||||
await expect(
|
||||
runClaudeCodeAuthProbe({ projectDir: '/tmp/project', model: 'sonnet', query, env: { ANTHROPIC_API_KEY: 'sk-ant-test' } }),
|
||||
|
|
|
|||
|
|
@ -183,6 +183,9 @@ export class ClaudeCodeKtxLlmRuntime implements KtxLlmRuntimePort {
|
|||
if (error) {
|
||||
throw error;
|
||||
}
|
||||
if (result.subtype !== 'success') {
|
||||
throw new Error(`Claude Code query failed (${result.subtype})`);
|
||||
}
|
||||
return result.result;
|
||||
}
|
||||
|
||||
|
|
@ -209,6 +212,9 @@ export class ClaudeCodeKtxLlmRuntime implements KtxLlmRuntimePort {
|
|||
if (error) {
|
||||
throw error;
|
||||
}
|
||||
if (result.subtype !== 'success') {
|
||||
throw new Error(`Claude Code query failed (${result.subtype})`);
|
||||
}
|
||||
return (input.schema as z.ZodType<TOutput>).parse(result.structured_output);
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -19,7 +19,13 @@ export type {
|
|||
RunLoopStopReason,
|
||||
} from './runtime-port.js';
|
||||
export { RuntimeAgentRunner } from './runtime-port.js';
|
||||
export { createAiSdkToolSet, createClaudeSdkTools, normalizeKtxRuntimeToolOutput } from './runtime-tools.js';
|
||||
export {
|
||||
createAiSdkToolSet,
|
||||
createClaudeSdkTools,
|
||||
createRuntimeToolDescriptorFromAiTool,
|
||||
createRuntimeToolSetFromAiSdkTools,
|
||||
normalizeKtxRuntimeToolOutput,
|
||||
} from './runtime-tools.js';
|
||||
export type {
|
||||
KtxLlmDebugProviderOptionsEntry,
|
||||
KtxLlmDebugRequest,
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
import { tool as aiTool, type ToolSet } from 'ai';
|
||||
import { tool as aiTool, type Tool, type ToolSet } from 'ai';
|
||||
import { tool as claudeTool, type SdkMcpToolDefinition } from '@anthropic-ai/claude-agent-sdk';
|
||||
import type { CallToolResult } from '@modelcontextprotocol/sdk/types.js';
|
||||
import { z } from 'zod';
|
||||
|
|
@ -67,3 +67,25 @@ export function createClaudeSdkTools(tools: KtxRuntimeToolSet = {}): Array<SdkMc
|
|||
export function mcpToolIds(tools: KtxRuntimeToolSet = {}): string[] {
|
||||
return Object.keys(tools).map((name) => `mcp__ktx__${name}`);
|
||||
}
|
||||
|
||||
export function createRuntimeToolDescriptorFromAiTool(name: string, aiSdkTool: Tool): KtxRuntimeToolDescriptor {
|
||||
return {
|
||||
name,
|
||||
description: aiSdkTool.description ?? '',
|
||||
inputSchema: aiSdkTool.inputSchema as KtxRuntimeToolDescriptor['inputSchema'],
|
||||
execute: async (input) => {
|
||||
if (typeof aiSdkTool.execute !== 'function') {
|
||||
throw new Error(`KTX runtime tool "${name}" has no execute function`);
|
||||
}
|
||||
return normalizeKtxRuntimeToolOutput(
|
||||
await aiSdkTool.execute(input as never, { toolCallId: `runtime-${name}` } as never),
|
||||
);
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
export function createRuntimeToolSetFromAiSdkTools(tools: ToolSet = {}): KtxRuntimeToolSet {
|
||||
return Object.fromEntries(
|
||||
Object.entries(tools).map(([name, aiSdkTool]) => [name, createRuntimeToolDescriptorFromAiTool(name, aiSdkTool as Tool)]),
|
||||
);
|
||||
}
|
||||
|
|
|
|||
|
|
@ -670,7 +670,7 @@ export function createLocalProjectMcpContextPorts(
|
|||
jobIdFactory: options.localIngest?.jobIdFactory,
|
||||
pullConfigOptions: options.localIngest?.pullConfigOptions,
|
||||
agentRunner: options.localIngest?.agentRunner,
|
||||
llmProvider: options.localIngest?.llmProvider,
|
||||
llmRuntime: options.localIngest?.llmRuntime,
|
||||
memoryModel: options.localIngest?.memoryModel,
|
||||
semanticLayerCompute: options.localIngest?.semanticLayerCompute ?? options.semanticLayerCompute,
|
||||
queryExecutor: options.localIngest?.queryExecutor ?? options.queryExecutor,
|
||||
|
|
@ -704,7 +704,7 @@ export function createLocalProjectMcpContextPorts(
|
|||
trigger: input.trigger,
|
||||
jobId: options.localIngest?.jobIdFactory?.(),
|
||||
agentRunner: options.localIngest?.agentRunner,
|
||||
llmProvider: options.localIngest?.llmProvider,
|
||||
llmRuntime: options.localIngest?.llmRuntime,
|
||||
memoryModel: options.localIngest?.memoryModel,
|
||||
semanticLayerCompute: options.localIngest?.semanticLayerCompute ?? options.semanticLayerCompute,
|
||||
queryExecutor: options.localIngest?.queryExecutor ?? options.queryExecutor,
|
||||
|
|
|
|||
|
|
@ -1,13 +1,17 @@
|
|||
import { join } from 'node:path';
|
||||
import { fileURLToPath } from 'node:url';
|
||||
import type { KtxLlmProvider } from '@ktx/llm';
|
||||
import YAML from 'yaml';
|
||||
import { AgentRunnerService } from '../agent/index.js';
|
||||
import { localConnectionInfoFromConfig } from '../connections/index.js';
|
||||
import type { KtxEmbeddingPort, KtxFileStorePort, KtxFileWriteResult } from '../core/index.js';
|
||||
import { type KtxLogger, noopLogger, SessionWorktreeService } from '../core/index.js';
|
||||
import type { KtxSemanticLayerComputePort } from '../daemon/index.js';
|
||||
import { createLocalKtxLlmProviderFromConfig } from '../llm/index.js';
|
||||
import {
|
||||
createLocalKtxLlmRuntimeFromConfig,
|
||||
RuntimeAgentRunner,
|
||||
type AgentRunnerPort,
|
||||
type KtxLlmRuntimePort,
|
||||
type KtxRuntimeToolSet,
|
||||
} from '../llm/index.js';
|
||||
import type { KtxLocalProject } from '../project/index.js';
|
||||
import { PromptService } from '../prompts/index.js';
|
||||
import { SkillsRegistryService } from '../skills/index.js';
|
||||
|
|
@ -63,8 +67,8 @@ const LOCAL_AUTHOR = { name: 'KTX Local', email: 'local@ktx.local' };
|
|||
const LOCAL_SHAPE_WARNING = 'Local memory capture validates semantic-layer YAML shape only.';
|
||||
|
||||
export interface CreateLocalProjectMemoryCaptureOptions {
|
||||
llmProvider?: KtxLlmProvider;
|
||||
agentRunner?: AgentRunnerService;
|
||||
llmRuntime?: KtxLlmRuntimePort;
|
||||
agentRunner?: AgentRunnerPort;
|
||||
memoryModel?: string;
|
||||
semanticLayerCompute?: KtxSemanticLayerComputePort;
|
||||
queryExecutor?: { execute(input: { connectionId: string; sql: string; maxRows?: number }): Promise<KtxQueryResult> };
|
||||
|
|
@ -89,7 +93,8 @@ export function createLocalProjectMemoryCapture(
|
|||
const slSearchService = new SlSearchService(embedding, slSourcesRepository, logger);
|
||||
const wikiService = new KnowledgeWikiService(rootFileStore, embedding, knowledgeIndex, project.git, logger);
|
||||
const authorResolver = new LocalAuthorResolver();
|
||||
const llmProvider = options.llmProvider ?? createLocalKtxLlmProviderFromConfig(project.config.llm);
|
||||
const llmRuntime =
|
||||
options.llmRuntime ?? createLocalKtxLlmRuntimeFromConfig(project.config.llm, { projectDir: project.projectDir });
|
||||
const toolsetFactory = new LocalMemoryToolsetFactory({
|
||||
project,
|
||||
embedding,
|
||||
|
|
@ -104,10 +109,7 @@ export function createLocalProjectMemoryCapture(
|
|||
});
|
||||
const agentRunner =
|
||||
options.agentRunner ??
|
||||
new AgentRunnerService({
|
||||
llmProvider: requireLlmProvider(llmProvider),
|
||||
logger,
|
||||
});
|
||||
new RuntimeAgentRunner(requireLlmRuntime(llmRuntime));
|
||||
const memoryAgent = new MemoryAgentService({
|
||||
settings: {
|
||||
knowledge: { userScopedKnowledgeEnabled: false },
|
||||
|
|
@ -143,11 +145,11 @@ export function createLocalProjectMemoryCapture(
|
|||
});
|
||||
}
|
||||
|
||||
function requireLlmProvider(provider: KtxLlmProvider | null | undefined): KtxLlmProvider {
|
||||
if (!provider) {
|
||||
function requireLlmRuntime(runtime: KtxLlmRuntimePort | null | undefined): KtxLlmRuntimePort {
|
||||
if (!runtime) {
|
||||
throw new Error('createLocalProjectMemoryCapture requires llm.provider.backend or an injected agentRunner');
|
||||
}
|
||||
return provider;
|
||||
return runtime;
|
||||
}
|
||||
|
||||
class LocalMemoryFileStore implements MemoryFileStorePort {
|
||||
|
|
@ -386,8 +388,8 @@ class LocalShapeOnlySlValidator implements SlValidatorPort<SlValidationDeps> {
|
|||
class LocalMemoryToolSet implements MemoryToolSetLike {
|
||||
constructor(private readonly tools: BaseTool[]) {}
|
||||
|
||||
toAiSdkTools(context: ToolContext) {
|
||||
return Object.fromEntries(this.tools.map((tool) => [tool.name, tool.toAiSdkTool(context)]));
|
||||
toRuntimeTools(context: ToolContext): KtxRuntimeToolSet {
|
||||
return Object.fromEntries(this.tools.map((tool) => [tool.name, tool.toRuntimeTool(context)]));
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -1,3 +1,6 @@
|
|||
import { mkdir, mkdtemp, rm, writeFile } from 'node:fs/promises';
|
||||
import { tmpdir } from 'node:os';
|
||||
import { join } from 'node:path';
|
||||
import { afterEach, beforeEach, describe, expect, it, vi } from 'vitest';
|
||||
|
||||
// Module-level mock for 'ai' so generateText is a stub. This file is separate from
|
||||
|
|
@ -124,11 +127,11 @@ const buildMocks = (overrides: Partial<BuiltMocks> = {}): BuiltMocks => {
|
|||
slValidator: { validateSingleSource: vi.fn().mockResolvedValue({ errors: [], warnings: [] }) },
|
||||
toolsetFactory: {
|
||||
createIngestWuToolset: vi.fn().mockReturnValue({
|
||||
toAiSdkTools: vi.fn().mockReturnValue({}),
|
||||
toRuntimeTools: vi.fn().mockReturnValue({}),
|
||||
getAllTools: vi.fn().mockReturnValue([]),
|
||||
}),
|
||||
createToolset: vi.fn().mockReturnValue({
|
||||
toAiSdkTools: vi.fn().mockReturnValue({}),
|
||||
toRuntimeTools: vi.fn().mockReturnValue({}),
|
||||
getAllTools: vi.fn().mockReturnValue([]),
|
||||
}),
|
||||
},
|
||||
|
|
@ -241,6 +244,39 @@ describe('MemoryAgentService.ingest — session-branch orchestration', () => {
|
|||
expect(result.commitHash).toBe('cafebabe');
|
||||
});
|
||||
|
||||
it('normalizes load_skill output to markdown while preserving structured payload', async () => {
|
||||
const tempDir = await mkdtemp(join(tmpdir(), 'ktx-memory-skill-'));
|
||||
const skillDir = join(tempDir, 'memory_agent');
|
||||
await mkdir(skillDir, { recursive: true });
|
||||
await writeFile(join(skillDir, 'SKILL.md'), '---\nname: memory_agent\n---\nSkill body', 'utf-8');
|
||||
try {
|
||||
const agentRunner = {
|
||||
runLoop: vi.fn(async (params: any) => {
|
||||
const result = await params.toolSet.load_skill.execute({ name: 'memory_agent' });
|
||||
expect(result.markdown).toContain('memory_agent');
|
||||
expect(result.structured).toMatchObject({ name: 'memory_agent' });
|
||||
return { stopReason: 'natural' as const };
|
||||
}),
|
||||
};
|
||||
const mocks = buildMocks({
|
||||
agentRunner,
|
||||
skillsRegistry: {
|
||||
listSkills: vi.fn().mockResolvedValue([{ name: 'memory_agent', path: skillDir }]),
|
||||
buildSkillsPrompt: vi.fn().mockReturnValue(''),
|
||||
getSkill: vi.fn().mockResolvedValue({ name: 'memory_agent', path: skillDir }),
|
||||
stripFrontmatter: vi.fn().mockReturnValue('Skill body'),
|
||||
},
|
||||
});
|
||||
const svc = buildService(mocks);
|
||||
|
||||
await svc.ingest(baseInput);
|
||||
|
||||
expect(agentRunner.runLoop).toHaveBeenCalled();
|
||||
} finally {
|
||||
await rm(tempDir, { recursive: true, force: true });
|
||||
}
|
||||
});
|
||||
|
||||
it('logs prompt debug output when KTX_MEMORY_AGENT_DEBUG_PROMPTS is enabled', async () => {
|
||||
const previousDebugPrompts = process.env.KTX_MEMORY_AGENT_DEBUG_PROMPTS;
|
||||
const mocks = buildMocks();
|
||||
|
|
|
|||
|
|
@ -1,10 +1,10 @@
|
|||
import { createHash } from 'node:crypto';
|
||||
import { readFile } from 'node:fs/promises';
|
||||
import { join } from 'node:path';
|
||||
import { tool } from 'ai';
|
||||
import * as YAML from 'yaml';
|
||||
import { z } from 'zod';
|
||||
import { type KtxLogger, noopLogger } from '../core/index.js';
|
||||
import type { KtxRuntimeToolSet } from '../llm/index.js';
|
||||
import {
|
||||
revertSourceToPreHead,
|
||||
type SemanticLayerSource,
|
||||
|
|
@ -125,8 +125,9 @@ export class MemoryAgentService {
|
|||
session: toolSession,
|
||||
};
|
||||
|
||||
const loadSkillTool = {
|
||||
load_skill: tool({
|
||||
const loadSkillTool: KtxRuntimeToolSet = {
|
||||
load_skill: {
|
||||
name: 'load_skill',
|
||||
description:
|
||||
'Load a skill to get specialized instructions. Call this when a skill listed in the system prompt matches the current task.',
|
||||
inputSchema: z.object({
|
||||
|
|
@ -137,23 +138,27 @@ export class MemoryAgentService {
|
|||
if (!skill) {
|
||||
const available =
|
||||
(await this.deps.skillsRegistry.listSkills('memory_agent')).map((s) => s.name).join(', ') || '(none)';
|
||||
return `Skill "${name}" not available to the memory agent. Available: ${available}`;
|
||||
return { markdown: `Skill "${name}" not available to the memory agent. Available: ${available}` };
|
||||
}
|
||||
try {
|
||||
const body = await readFile(join(skill.path, 'SKILL.md'), 'utf-8');
|
||||
if (!skillsLoaded.includes(skill.name)) {
|
||||
skillsLoaded.push(skill.name);
|
||||
}
|
||||
return {
|
||||
const structured = {
|
||||
name: skill.name,
|
||||
skillDirectory: skill.path,
|
||||
content: this.deps.skillsRegistry.stripFrontmatter(body),
|
||||
};
|
||||
return {
|
||||
markdown: `# ${structured.name}\n\n${structured.content}`,
|
||||
structured,
|
||||
};
|
||||
} catch (e) {
|
||||
return `Error loading skill "${name}": ${e instanceof Error ? e.message : String(e)}`;
|
||||
return { markdown: `Error loading skill "${name}": ${e instanceof Error ? e.message : String(e)}` };
|
||||
}
|
||||
},
|
||||
}),
|
||||
},
|
||||
};
|
||||
|
||||
const skillNames: string[] = [...DEFAULT_SKILL_NAMES];
|
||||
|
|
@ -212,7 +217,7 @@ export class MemoryAgentService {
|
|||
modelRole: 'candidateExtraction',
|
||||
systemPrompt,
|
||||
userPrompt: prompt,
|
||||
toolSet: { ...toolset.toAiSdkTools(toolContext), ...loadSkillTool },
|
||||
toolSet: { ...toolset.toRuntimeTools(toolContext), ...loadSkillTool },
|
||||
stepBudget,
|
||||
telemetryTags: {
|
||||
operationName: 'memory-agent-ingest',
|
||||
|
|
|
|||
|
|
@ -1,5 +1,4 @@
|
|||
import type { Tool } from 'ai';
|
||||
import type { AgentRunnerService } from '../agent/index.js';
|
||||
import type { AgentRunnerPort, KtxRuntimeToolSet } from '../llm/index.js';
|
||||
import type { GitService, KtxFileStorePort, KtxLogger, SessionWorktreeService } from '../core/index.js';
|
||||
import type { PromptService } from '../prompts/index.js';
|
||||
import type { SkillsRegistryService } from '../skills/index.js';
|
||||
|
|
@ -118,7 +117,7 @@ export interface MemoryCommitMessagePort {
|
|||
export interface MemoryFileStorePort extends KtxFileStorePort<MemoryFileStorePort>, MemoryCommitMessagePort {}
|
||||
|
||||
export interface MemoryToolSetLike {
|
||||
toAiSdkTools(context: ToolContext): Record<string, Tool>;
|
||||
toRuntimeTools(context: ToolContext): KtxRuntimeToolSet;
|
||||
}
|
||||
|
||||
export interface MemoryToolsetFactoryPort {
|
||||
|
|
@ -150,7 +149,7 @@ export interface MemoryAgentServiceDeps {
|
|||
slSourcesRepository: SlSourcesIndexPort;
|
||||
sessionWorktreeService: SessionWorktreeService<MemoryFileStorePort>;
|
||||
semanticLayerSourceReconciler: MemorySlSourceReconcilerPort;
|
||||
agentRunner: AgentRunnerService;
|
||||
agentRunner: AgentRunnerPort;
|
||||
slValidator: SlValidatorPort<SlValidationDeps>;
|
||||
toolsetFactory: MemoryToolsetFactoryPort;
|
||||
telemetry?: MemoryTelemetryPort;
|
||||
|
|
|
|||
|
|
@ -264,7 +264,6 @@ export type {
|
|||
} from './relationship-graph-resolver.js';
|
||||
export { resolveKtxRelationshipGraph } from './relationship-graph-resolver.js';
|
||||
export type {
|
||||
KtxRelationshipLlmProposalGenerateText,
|
||||
KtxRelationshipLlmProposalResult,
|
||||
KtxRelationshipLlmProposalSettings,
|
||||
ProposeKtxRelationshipCandidatesWithLlmInput,
|
||||
|
|
|
|||
|
|
@ -356,7 +356,7 @@ describe('local scan enrichment', () => {
|
|||
|
||||
it('honors scan relationship config when LLM proposals are disabled', async () => {
|
||||
const providers = createDeterministicLocalScanEnrichmentProviders({ embeddingDimensions: 3 });
|
||||
const getModel = vi.fn(() => ({ modelId: 'provider/language-model', provider: 'gateway' }));
|
||||
const generateObject = vi.fn();
|
||||
const result = await runLocalScanEnrichment({
|
||||
connectionId: 'warehouse',
|
||||
mode: 'relationships',
|
||||
|
|
@ -365,9 +365,9 @@ describe('local scan enrichment', () => {
|
|||
context: { runId: 'scan-run-llm-disabled' },
|
||||
providers: {
|
||||
...providers,
|
||||
llm: {
|
||||
...providers.llm,
|
||||
getModel: getModel as never,
|
||||
llmRuntime: {
|
||||
...providers.llmRuntime,
|
||||
generateObject: generateObject as never,
|
||||
},
|
||||
},
|
||||
relationshipSettings: {
|
||||
|
|
@ -378,7 +378,7 @@ describe('local scan enrichment', () => {
|
|||
});
|
||||
|
||||
expect(result.summary.llmRelationshipValidation).toBe('skipped');
|
||||
expect(getModel).not.toHaveBeenCalledWith('candidateExtraction');
|
||||
expect(generateObject).not.toHaveBeenCalled();
|
||||
});
|
||||
|
||||
it('skips relationship detection when scan relationships are disabled', async () => {
|
||||
|
|
@ -628,7 +628,7 @@ describe('local scan enrichment', () => {
|
|||
connector: scanConnector,
|
||||
context: { runId: 'scan-run-batched-embeddings' },
|
||||
providers: {
|
||||
llm: deterministicProviders.llm,
|
||||
llmRuntime: deterministicProviders.llmRuntime,
|
||||
embedding: {
|
||||
dimensions: 3,
|
||||
maxBatchSize: 2,
|
||||
|
|
@ -658,7 +658,7 @@ describe('local scan enrichment', () => {
|
|||
providerIdentity: { provider: 'deterministic', embeddingDimensions: 6 },
|
||||
});
|
||||
|
||||
const getModel = vi.spyOn(providers.llm, 'getModel');
|
||||
const generateText = vi.spyOn(providers.llmRuntime, 'generateText');
|
||||
const embedBatch = vi.spyOn(providers.embedding, 'embedBatch');
|
||||
const second = await runLocalScanEnrichment({
|
||||
connectionId: 'warehouse',
|
||||
|
|
@ -676,7 +676,7 @@ describe('local scan enrichment', () => {
|
|||
expect(first.state.resumedStages).toEqual([]);
|
||||
expect(second.state.resumedStages).toEqual(['descriptions', 'embeddings', 'relationships']);
|
||||
expect(second.state.completedStages).toEqual(['descriptions', 'embeddings', 'relationships']);
|
||||
expect(getModel).not.toHaveBeenCalled();
|
||||
expect(generateText).not.toHaveBeenCalled();
|
||||
expect(embedBatch).not.toHaveBeenCalled();
|
||||
expect(second.descriptionUpdates).toEqual(first.descriptionUpdates);
|
||||
expect(second.embeddingUpdates).toEqual(first.embeddingUpdates);
|
||||
|
|
@ -711,7 +711,7 @@ describe('local scan enrichment', () => {
|
|||
tables: [{ ...firstTable, name: 'customers' }],
|
||||
})),
|
||||
};
|
||||
const getModel = vi.spyOn(providers.llm, 'getModel');
|
||||
const generateText = vi.spyOn(providers.llmRuntime, 'generateText');
|
||||
|
||||
const result = await runLocalScanEnrichment({
|
||||
connectionId: 'warehouse',
|
||||
|
|
@ -727,7 +727,7 @@ describe('local scan enrichment', () => {
|
|||
|
||||
expect(result.state.resumedStages).toEqual([]);
|
||||
expect(result.state.completedStages).toEqual(['descriptions', 'embeddings', 'relationships']);
|
||||
expect(getModel).toHaveBeenCalled();
|
||||
expect(generateText).toHaveBeenCalled();
|
||||
});
|
||||
|
||||
it('runs providerless enriched scans as relationship-only discovery enrichment', async () => {
|
||||
|
|
|
|||
|
|
@ -638,7 +638,7 @@ describe('local scan', () => {
|
|||
enrichmentProviders: {
|
||||
llmRuntime: {
|
||||
...deterministicLlmRuntime(),
|
||||
generateObject,
|
||||
generateObject: generateObject as never,
|
||||
},
|
||||
embedding: {
|
||||
dimensions: 8,
|
||||
|
|
|
|||
|
|
@ -6,6 +6,7 @@ import { gunzipSync } from 'node:zlib';
|
|||
import Database from 'better-sqlite3';
|
||||
import YAML from 'yaml';
|
||||
import { z } from 'zod';
|
||||
import type { KtxLlmRuntimePort } from '../llm/index.js';
|
||||
import type { KtxEnrichedRelationship, KtxEnrichedSchema, KtxRelationshipType } from './enrichment-types.js';
|
||||
import { snapshotToKtxEnrichedSchema } from './local-enrichment.js';
|
||||
import type { KtxRelationshipDiscoveryCandidate } from './relationship-candidates.js';
|
||||
|
|
@ -13,7 +14,6 @@ import {
|
|||
generateKtxRelationshipDiscoveryCandidates,
|
||||
mergeKtxRelationshipDiscoveryCandidates,
|
||||
} from './relationship-candidates.js';
|
||||
import type { KtxLlmProvider } from '@ktx/llm';
|
||||
import { proposeKtxRelationshipCandidatesWithLlm } from './relationship-llm-proposal.js';
|
||||
import {
|
||||
discoverKtxCompositeRelationships,
|
||||
|
|
@ -527,7 +527,7 @@ export function isKtxRelationshipBenchmarkTuningEligible(input: {
|
|||
}
|
||||
|
||||
export function ktxRelationshipBenchmarkDetectorWithLlm(
|
||||
llmProvider: KtxLlmProvider,
|
||||
llmRuntime: KtxLlmRuntimePort,
|
||||
): KtxRelationshipBenchmarkDetector {
|
||||
return {
|
||||
async detect(input) {
|
||||
|
|
@ -566,7 +566,7 @@ export function ktxRelationshipBenchmarkDetectorWithLlm(
|
|||
connectionId: input.snapshot.connectionId,
|
||||
schema: input.schema,
|
||||
profile: profiles,
|
||||
llmProvider,
|
||||
llmRuntime,
|
||||
});
|
||||
const candidates = mergeKtxRelationshipDiscoveryCandidates([
|
||||
...broadRelationshipCandidates,
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
import type { KtxLlmProvider } from '@ktx/llm';
|
||||
import Database from 'better-sqlite3';
|
||||
import { afterEach, describe, expect, it, vi } from 'vitest';
|
||||
import type { KtxLlmRuntimePort } from '../llm/index.js';
|
||||
import { buildDefaultKtxProjectConfig } from '../project/config.js';
|
||||
import { snapshotToKtxEnrichedSchema } from './local-enrichment.js';
|
||||
import {
|
||||
|
|
@ -216,29 +216,11 @@ function connector(executor: InMemorySqliteExecutor | null): KtxScanConnector {
|
|||
};
|
||||
}
|
||||
|
||||
function llmProvider(): KtxLlmProvider {
|
||||
const model = { modelId: 'claude-sonnet-4-6', provider: 'anthropic' };
|
||||
function llmRuntime(output: unknown): KtxLlmRuntimePort {
|
||||
return {
|
||||
getModel: vi.fn(() => model as ReturnType<KtxLlmProvider['getModel']>),
|
||||
getModelByName: vi.fn(() => model as ReturnType<KtxLlmProvider['getModelByName']>),
|
||||
cacheMarker: vi.fn(),
|
||||
repairToolCallHandler: vi.fn(),
|
||||
thinkingProviderOptions: vi.fn(() => ({})),
|
||||
telemetryConfig: vi.fn(() => undefined),
|
||||
promptCachingConfig: vi.fn(
|
||||
() =>
|
||||
({
|
||||
enabled: false,
|
||||
systemTtl: '1h',
|
||||
toolsTtl: '1h',
|
||||
historyTtl: '5m',
|
||||
cacheSystem: true,
|
||||
cacheTools: true,
|
||||
cacheHistory: true,
|
||||
vertexFallbackTo5m: false,
|
||||
}) as ReturnType<KtxLlmProvider['promptCachingConfig']>,
|
||||
),
|
||||
activeBackend: vi.fn(() => 'anthropic' as ReturnType<KtxLlmProvider['activeBackend']>),
|
||||
generateText: vi.fn(),
|
||||
generateObject: vi.fn(async () => output) as KtxLlmRuntimePort['generateObject'],
|
||||
runAgentLoop: vi.fn(),
|
||||
};
|
||||
}
|
||||
|
||||
|
|
@ -505,21 +487,19 @@ describe('production relationship discovery', () => {
|
|||
INSERT INTO customers (id) VALUES (1), (2);
|
||||
INSERT INTO orders (id, buyer_ref) VALUES (10, 1), (11, 2);
|
||||
`);
|
||||
const generateText = vi.fn(async () => ({
|
||||
output: {
|
||||
pkCandidates: [{ table: 'customers', column: 'id', confidence: 0.91, rationale: 'Unique customer key.' }],
|
||||
fkCandidates: [
|
||||
{
|
||||
fromTable: 'orders',
|
||||
fromColumn: 'buyer_ref',
|
||||
toTable: 'customers',
|
||||
toColumn: 'id',
|
||||
confidence: 0.89,
|
||||
rationale: 'Buyer reference values align with customer identifiers.',
|
||||
},
|
||||
],
|
||||
},
|
||||
}));
|
||||
const llmOutput = {
|
||||
pkCandidates: [{ table: 'customers', column: 'id', confidence: 0.91, rationale: 'Unique customer key.' }],
|
||||
fkCandidates: [
|
||||
{
|
||||
fromTable: 'orders',
|
||||
fromColumn: 'buyer_ref',
|
||||
toTable: 'customers',
|
||||
toColumn: 'id',
|
||||
confidence: 0.89,
|
||||
rationale: 'Buyer reference values align with customer identifiers.',
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
const result = await discoverKtxRelationships({
|
||||
connectionId: 'warehouse',
|
||||
|
|
@ -528,8 +508,7 @@ describe('production relationship discovery', () => {
|
|||
schema: snapshotToKtxEnrichedSchema(llmOnlyRelationshipSnapshot()),
|
||||
context: { runId: 'llm-relationship-orchestrator' },
|
||||
settings: relationshipSettings(),
|
||||
llmProvider: llmProvider(),
|
||||
generateText,
|
||||
llmRuntime: llmRuntime(llmOutput),
|
||||
});
|
||||
|
||||
expect(result.llmRelationshipValidation).toBe('completed');
|
||||
|
|
|
|||
|
|
@ -7,7 +7,7 @@ import { proposeKtxRelationshipCandidatesWithLlm } from './relationship-llm-prop
|
|||
function llmRuntime(output?: unknown): KtxLlmRuntimePort {
|
||||
return {
|
||||
generateText: vi.fn(),
|
||||
generateObject: vi.fn(async () => output),
|
||||
generateObject: vi.fn(async () => output) as KtxLlmRuntimePort['generateObject'],
|
||||
runAgentLoop: vi.fn(),
|
||||
};
|
||||
}
|
||||
|
|
|
|||
|
|
@ -249,7 +249,6 @@ export async function proposeKtxRelationshipCandidatesWithLlm(
|
|||
system,
|
||||
prompt,
|
||||
schema: relationshipLlmProposalSchema,
|
||||
generateText: input.generateText,
|
||||
});
|
||||
const output = relationshipLlmProposalSchema.parse(generated);
|
||||
const mapped = mapValidProposals(input.schema, output, settings);
|
||||
|
|
|
|||
|
|
@ -171,7 +171,7 @@ export abstract class BaseTool<TInput extends ZodType = ZodType> {
|
|||
return {
|
||||
name: toolName,
|
||||
description: this.description,
|
||||
inputSchema: this.inputSchema as KtxRuntimeToolDescriptor['inputSchema'],
|
||||
inputSchema: this.inputSchema as unknown as KtxRuntimeToolDescriptor['inputSchema'],
|
||||
execute: async (params) => {
|
||||
const callContext = { ...context };
|
||||
if (!callContext.userId) {
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue