alvis
9ddeea6cac
Each unique task title is now enriched by LiteLLM once and cached in the DB. Subsequent agent compute cycles (every 12h) fetch the cache before calling ml-serving; only new titles hit the tip-generator. - DB: task_enrichments(content_hash PK, description, model, created_at) - TS: fetchEnrichmentCache / persistEnrichments helpers in agent-outputs.ts; enrichment_cache passed in compute request, new_enrichments persisted from response - Python: AgentComputeRequest.enrichment_cache / AgentComputeResponse.new_enrichments; AgentInput.enrichment_cache; _enrich_batch returns (descriptions, new_entries); cluster_tasks returns (clusters, new_enrichments) - FocusAreaAgent stashes new_enrichments in signals_snapshot under _new_enrichments; compute_agent endpoint pops it before storing the snapshot Closes part of #129 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
209 lines
10 KiB
TypeScript
209 lines
10 KiB
TypeScript
import { sqliteTable, text, integer } from 'drizzle-orm/sqlite-core';
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export const users = sqliteTable('users', {
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id: text('id').primaryKey(),
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email: text('email').notNull().unique(),
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name: text('name'),
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image: text('image'),
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googleId: text('google_id').unique(),
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role: text('role').notNull().default('user'), // 'user' | 'admin'
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// Stable globals (ADR-0014). Per-agent prefs land in user_preferences instead.
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tone: text('tone'), // 'direct' | 'gentle' | 'motivational'
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tipKindsJson: text('tip_kinds_json'), // JSON array of allowed tip kinds; null = all
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createdAt: text('created_at').notNull(),
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deletedAt: text('deleted_at'),
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});
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// ── Unified Profile model (ADR-0014) ────────────────────────────────────────
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// Open-ended per-scope preferences. `scope` is 'orchestrator' or 'agent:<id>';
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// the agent's pref_schema (from its manifest) validates value_json on read.
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// `source='inferred'` is written by the inference framework (#111); never
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// overwrites a `source='user'` row.
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export const userPreferences = sqliteTable('user_preferences', {
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userId: text('user_id').notNull().references(() => users.id),
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scope: text('scope').notNull(), // 'orchestrator' | 'agent:<id>'
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key: text('key').notNull(),
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valueJson: text('value_json').notNull(),
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source: text('source').notNull().default('user'), // 'user' | 'inferred'
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updatedAt: text('updated_at').notNull(),
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});
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// Per-key consent. Revocation writes `revoked_at`; rows are never deleted
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// so audits stay clean. `revoked_at IS NULL` = currently active.
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export const userConsents = sqliteTable('user_consents', {
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userId: text('user_id').notNull().references(() => users.id),
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consentKey: text('consent_key').notNull(), // 'data:core' | 'data:todoist' | 'agent:<id>' | …
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grantedAt: text('granted_at').notNull(),
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revokedAt: text('revoked_at'),
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});
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// User-named contexts (work / home / vacation). M2 ships manual toggle only;
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// auto-inference is per-agent (#112–#116).
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export const userContexts = sqliteTable('user_contexts', {
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userId: text('user_id').notNull().references(() => users.id),
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name: text('name').notNull(),
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active: integer('active', { mode: 'boolean' }).notNull().default(false),
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scheduleJson: text('schedule_json'), // optional: when active
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createdAt: text('created_at').notNull(),
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});
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export const integrationTokens = sqliteTable('integration_tokens', {
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id: text('id').primaryKey(),
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userId: text('user_id').notNull().references(() => users.id),
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provider: text('provider').notNull(), // 'todoist'
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accessToken: text('access_token').notNull(),
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refreshToken: text('refresh_token'),
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expiresAt: text('expires_at'),
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tokenStatus: text('token_status').notNull().default('active'), // 'active' | 'needs_reconnect'
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connectedAt: text('connected_at').notNull(),
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});
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export const tipFeedback = sqliteTable('tip_feedback', {
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id: text('id').primaryKey(),
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userId: text('user_id').notNull().references(() => users.id),
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tipId: text('tip_id').notNull(),
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action: text('action').notNull(), // 'done' | 'dismiss' | 'snooze'
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sourceId: text('source_id'),
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dwellMs: integer('dwell_ms'), // ms between servedAt and feedback; null if unknown
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rewardMilli: integer('reward_milli'), // inferred reward × 1000 (e.g. 1000 = +1.0)
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createdAt: text('created_at').notNull(),
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});
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// Each row = one tip served. Join with tipFeedback on tipId to compute reaction rate + dwell.
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export const tipViews = sqliteTable('tip_views', {
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id: text('id').primaryKey(),
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userId: text('user_id').notNull().references(() => users.id),
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tipId: text('tip_id').notNull(),
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servedAt: text('served_at').notNull(),
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});
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export const pushSubscriptions = sqliteTable('push_subscriptions', {
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id: text('id').primaryKey(),
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userId: text('user_id').notNull().references(() => users.id),
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endpoint: text('endpoint').notNull().unique(),
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p256dh: text('p256dh').notNull(),
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auth: text('auth').notNull(),
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createdAt: text('created_at').notNull(),
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});
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export const sessions = sqliteTable('sessions', {
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id: text('id').primaryKey(),
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userId: text('user_id').notNull().references(() => users.id),
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expiresAt: text('expires_at').notNull(),
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createdAt: text('created_at').notNull(),
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});
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// Audit log — every admin write action is appended here.
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export const adminActions = sqliteTable('admin_actions', {
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id: text('id').primaryKey(),
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adminId: text('admin_id').notNull().references(() => users.id),
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action: text('action').notNull(), // e.g. 'revoke_token', 'reset_bandit'
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targetType: text('target_type'), // e.g. 'user', 'integration'
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targetId: text('target_id'),
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detail: text('detail'), // JSON blob for extra context
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createdAt: text('created_at').notNull(),
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});
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// Recommendation explainability log — one row per tip served.
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// features/scores are JSON blobs. Retained 30 days (GDPR).
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export const tipScores = sqliteTable('tip_scores', {
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id: text('id').primaryKey(),
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userId: text('user_id').notNull().references(() => users.id),
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tipId: text('tip_id').notNull(),
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policy: text('policy').notNull(),
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mlScore: integer('ml_score', { mode: 'number' }), // null when random fallback
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featuresJson: text('features_json'), // JSON: { is_overdue, task_age_days, priority, hour_of_day, day_of_week }
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candidateCount: integer('candidate_count'),
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latencyMs: integer('latency_ms'),
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servedAt: text('served_at').notNull(),
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promptVersion: text('prompt_version'), // e.g. 'v1' — tracks which prompt template generated this tip
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llmModel: text('llm_model'), // e.g. 'tip-generator/qwen2.5:7b' — null for bandit-only tips
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tipKind: text('tip_kind'), // 'task' | 'advice' | 'insight' | 'reminder'
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});
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// ── User profile features (#81 phase A) ────────────────────────────────────
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// One row per (userId, name). KV store for aggregated user-level features
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// computed from tip_views/tip_feedback/tip_scores. Numeric values land in
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// `value`; categorical/string values use `value_text` (never both). Entries
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// are recomputed lazily by the profile builder when older than `ttl_sec`.
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export const userProfileFeatures = sqliteTable('user_profile_features', {
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userId: text('user_id').notNull().references(() => users.id),
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name: text('name').notNull(), // e.g. 'completion_rate_30d'
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value: integer('value', { mode: 'number' }), // numeric (REAL stored as number); null if categorical
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valueText: text('value_text'), // categorical/string; null if numeric
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updatedAt: text('updated_at').notNull(),
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ttlSec: integer('ttl_sec').notNull(), // staleness threshold; 0 = never auto-refresh
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});
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// ── Simulation runs ──────────────────────────────────────────────────────────
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// One row per offline simulation run (two-policy comparison).
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export const simRuns = sqliteTable('sim_runs', {
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id: text('id').primaryKey(),
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policyA: text('policy_a').notNull(),
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policyB: text('policy_b').notNull(),
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nUsers: integer('n_users').notNull(),
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nRounds: integer('n_rounds').notNull(),
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tasksPerRound: integer('tasks_per_round').notNull().default(8),
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useLlm: integer('use_llm', { mode: 'boolean' }).notNull().default(false),
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status: text('status').notNull().default('pending'), // 'pending'|'running'|'done'|'failed'
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judgeMode: text('judge_mode').notNull().default('rule'),
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nPolicies: integer('n_policies').notNull().default(2),
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summaryJson: text('summary_json'), // JSON: { [policy]: PolicySummary }
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winner: text('winner'),
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personaBreakdownJson: text('persona_breakdown_json'), // JSON: { [persona]: { [policy]: {reward,n} } }
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mlflowRunId: text('mlflow_run_id'),
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createdAt: text('created_at').notNull(),
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finishedAt: text('finished_at'),
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});
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// One row per tip served in a simulation round.
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export const simEvents = sqliteTable('sim_events', {
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id: text('id').primaryKey(),
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runId: text('run_id').notNull().references(() => simRuns.id),
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round: integer('round').notNull(),
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userId: text('user_id').notNull(),
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persona: text('persona').notNull(),
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policy: text('policy').notNull(),
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tipContent: text('tip_content').notNull(),
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priority: integer('priority').notNull(),
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isOverdue: integer('is_overdue', { mode: 'boolean' }).notNull(),
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action: text('action').notNull(), // 'done' | 'snooze' | 'dismiss'
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dwellMs: integer('dwell_ms'), // simulated ms between tip appear and user action
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rewardMilli: integer('reward_milli').notNull(), // inferred reward × 1000
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hour: integer('hour').notNull(),
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dayOfWeek: integer('day_of_week').notNull(),
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createdAt: text('created_at').notNull(),
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});
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// ── Agent outputs (#multi-agent) ─────────────────────────────────────────────
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// One row per (userId, agentId) pre-compute run. The orchestrator reads the
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// freshest non-expired row per agent when assembling the tip prompt.
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export const agentOutputs = sqliteTable('agent_outputs', {
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id: text('id').primaryKey(),
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userId: text('user_id').notNull().references(() => users.id),
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agentId: text('agent_id').notNull(), // e.g. 'overdue-task'
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promptText: text('prompt_text').notNull(), // snippet for orchestrator prompt
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signalsSnapshot: text('signals_snapshot'), // JSON: inputs the agent consumed
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computedAt: text('computed_at').notNull(), // ISO 8601
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expiresAt: text('expires_at').notNull(), // ISO 8601 = computedAt + TTL
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agentVersion: text('agent_version').notNull(), // bump to invalidate on logic changes
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});
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// Persistent cache for LLM-enriched task descriptions used by clustering.
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// Keyed by MD5 of raw task content; avoids re-calling LiteLLM on every agent compute cycle.
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export const taskEnrichments = sqliteTable('task_enrichments', {
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contentHash: text('content_hash').primaryKey(),
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description: text('description').notNull(),
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model: text('model').notNull().default('tip-generator'),
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createdAt: text('created_at').notNull(),
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});
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// Admin saved SQL queries.
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export const savedQueries = sqliteTable('saved_queries', {
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id: text('id').primaryKey(),
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adminId: text('admin_id').notNull().references(() => users.id),
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name: text('name').notNull(),
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sql: text('sql').notNull(),
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createdAt: text('created_at').notNull(),
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});
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