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Author SHA1 Message Date
ec8593cf77 v1.13.4: two-tier compaction prune — opencode pattern half-shipped in v1.11.0
- message_parts.hidden_at timestamptz column (NULL by default) with a
  partial index on (message_id) WHERE hidden_at IS NULL for the common
  visible-parts filter.
- messages_with_parts view changed from COALESCE(parts, legacy) to
  CASE WHEN EXISTS(any parts of kind) THEN visible-parts ELSE legacy.
  COALESCE would have leaked hidden parts back via the legacy fallback
  when every part was pruned (smoke caught it pre-commit). The CASE
  distinguishes "no parts at all → fall back to legacy column for
  pre-v1.13.0 history" from "all parts hidden → return null/empty so
  the row drops out of the model payload" exactly.
- prune.ts: scans tool_result parts newest-first, protects the last 40k
  tokens (PROTECTED_TOKENS), marks older candidates hidden when their
  combined estimate clears 20k (PRUNE_TRIGGER_TOKENS — equal to
  COMPACTION_BUFFER from v1.11.0, so a successful prune is exactly the
  budget the summary path would have freed). Stops at chats.tail_start_id
  so it doesn't double-erase across the last summary boundary. Pure
  decision helper selectPruneTargets exported separately for unit tests.
- Wired into maybeFlagForCompaction: prune runs synchronously when
  overflow is detected; if it freed >= PRUNE_TRIGGER_TOKENS, the
  needs_compaction flag is NOT set and the (expensive) summary inference
  call is skipped this turn. The next turn's overflow check re-evaluates
  from scratch.
- 6 new unit tests in prune.test.ts cover: empty input, protection-only
  (no candidates), candidates below trigger, candidates above trigger,
  candidates straddling a summary boundary, exactly-protection-tokens.
  179 tests total (was 173).

Smoke verified post-rebuild:
- \\d message_parts shows hidden_at + partial index.
- View definition shows AND p.hidden_at IS NULL filters on all three
  subselects.
- Synthetic hide-then-restore confirmed the view drops the tool_result
  jsonb to null when its only part is hidden, and restores when un-hidden.
- EXPLAIN ANALYZE on the 42-message stress chat: 0.325ms (faster than
  v1.13.1-B's 1.018ms — EXISTS short-circuits cleanly for the common
  no-parts case).
- Normal turn (plain text prompt) completes unaffected.

Closes a v1.11.0 design item that was scoped but never implemented. With
v1.13's parts table the prune is dramatically cheaper to write — pre-parts
it would have meant editing JSON blobs in-place; now it's a hidden_at
flag and a view subselect.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-22 07:02:17 +00:00
a08d809b73 v1.13.3: cleanup bundle — statement timeout + alpha ordering + stuck-row sweeper + repairToolCall
Four independent items, all owed from prior dispatches.

- statement_timeout at the database level via:
    ALTER DATABASE boocode SET statement_timeout = '30s';
  Applied operationally; documented as a comment at the top of schema.sql
  (ALTER DATABASE can't run inside a DO block, so it's not idempotent
  inside applySchema). Re-apply after a volume reset.

- Tool registry alpha-sorted at module load. llama.cpp's prompt cache
  hits on byte-identical prefixes; any reordering of the tool list near
  the top of the system prompt would invalidate every cached turn.
  Single-source sort at the ALL_TOOLS export so toolJsonSchemas() and
  TOOLS_BY_NAME inherit the order automatically. New tools.test.ts
  asserts the invariant; total tests 173 (was 172).

- Periodic in-process stuck-row sweeper. Runs every 60s, marks
  'streaming' rows older than 5 minutes as 'failed', and publishes
  chat_status='idle' on the user channel so the UI dot drops without a
  refresh. Closes the mid-session crash UX gap; the v1.12.1 boot sweep
  only fires once at startup, so sessions used to stay stuck until next
  reboot. setInterval cleaned up via app.addHook('onClose'). Mirrors
  handleAbortOrError's publish pattern.

- experimental_repairToolCall wired through AI SDK v6 streamText. Pass-
  through implementation: log + return the original toolCall so the
  stream keeps going. executeToolPhase's existing error paths (unknown
  tool name → 'unknown tool: X' result; zod-reject → 'tool X rejected
  — field: required') already surface bad calls to the model; the value
  here is preventing the AI SDK from THROWING on parse errors and
  killing the whole stream. Owed since v1.13.1-A.

Smoke verified:
- statement_timeout = '30s' confirmed via SHOW.
- Tool path normal flow intact (list_dir prompt → tool_call → result
  → final assistant). No malformed tool calls in the test run; repair
  log will surface them when qwen3.6 actually emits one.
- Alpha order verified at runtime via the dist bundle: match: true.
- Sweeper logic not traffic-tested (no stuck rows to find), but the
  SQL UPDATE + broker.publishUser pattern is identical to handleAbort
  and the boot sweep — synthesis-only verification.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-22 06:46:03 +00:00
8 changed files with 388 additions and 18 deletions

View File

@@ -201,6 +201,46 @@ async function main() {
app.log.info(`serving static frontend from ${webDist}`);
}
// v1.13.3: periodic in-process sweeper for streaming rows orphaned by a
// mid-session crash. The boot sweep (above) only fires once at startup;
// this loop catches the in-flight case. 60s cadence + 5-min threshold
// matches the boot sweep so behavior is consistent. Publishes
// chat_status='idle' on the user channel so the UI dot drops without a
// refresh — same pattern as handleAbortOrError.
const SWEEP_INTERVAL_MS = 60_000;
const sweepStaleStreaming = async (): Promise<void> => {
try {
const rows = await sql<{ id: string; chat_id: string }[]>`
UPDATE messages
SET status = 'failed', finished_at = clock_timestamp()
WHERE status = 'streaming'
AND created_at < NOW() - INTERVAL '5 minutes'
RETURNING id, chat_id
`;
if (rows.length === 0) return;
app.log.warn(
{ swept: rows.length, ids: rows.map((r) => r.id) },
'swept stale streaming rows',
);
const seenChats = new Set<string>();
const now = new Date().toISOString();
for (const row of rows) {
if (seenChats.has(row.chat_id)) continue;
seenChats.add(row.chat_id);
broker.publishUser('default', {
type: 'chat_status',
chat_id: row.chat_id,
status: 'idle',
at: now,
});
}
} catch (err) {
app.log.error({ err }, 'stuck-row sweeper failed');
}
};
const sweepTimer = setInterval(() => { void sweepStaleStreaming(); }, SWEEP_INTERVAL_MS);
app.addHook('onClose', async () => { clearInterval(sweepTimer); });
const shutdown = async (signal: string) => {
app.log.info(`received ${signal}, shutting down`);
try {

View File

@@ -1,3 +1,10 @@
-- v1.13.3: statement_timeout is set at database level via:
-- ALTER DATABASE boocode SET statement_timeout = '30s';
-- ALTER DATABASE can't run inside a DO block, so this is an operational
-- step rather than schema. Re-apply after a volume reset (the setting
-- lives in pg_db which survives `docker compose up --build` but NOT a
-- `docker volume rm boocode_pgdata`).
CREATE TABLE IF NOT EXISTS projects (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
name TEXT NOT NULL,
@@ -49,6 +56,24 @@ CREATE TABLE IF NOT EXISTS message_parts (
);
CREATE INDEX IF NOT EXISTS message_parts_msg_seq_idx ON message_parts (message_id, sequence);
-- v1.13.4: prune support. hidden_at marks parts that have been pruned out
-- of the model payload by the two-tier compaction prune (services/inference/
-- prune.ts). Rows stay in the DB so frontend can still display them with a
-- "hidden" indicator (out of scope this dispatch). messages_with_parts
-- view filters these out — see below. Partial index speeds the common
-- "visible parts only" filter.
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM information_schema.columns
WHERE table_name = 'message_parts' AND column_name = 'hidden_at'
) THEN
ALTER TABLE message_parts ADD COLUMN hidden_at timestamptz NULL;
END IF;
END $$;
CREATE INDEX IF NOT EXISTS message_parts_hidden_idx
ON message_parts (message_id) WHERE hidden_at IS NULL;
-- v1.13.1-B: read-path view. Read sites SELECT FROM messages_with_parts
-- instead of messages so tool_calls / tool_results / reasoning_parts come
-- from the granular message_parts table. The COALESCE means pre-v1.13.0
@@ -66,23 +91,32 @@ SELECT
m.last_seq, m.tokens_used, m.ctx_used, m.ctx_max,
m.started_at, m.finished_at, m.created_at, m.metadata,
m.summary, m.tail_start_id, m.compacted_at,
COALESCE(
-- v1.13.4: prune semantics need to distinguish "no parts row exists"
-- (pre-v1.13.0 fallback to legacy column) from "all parts hidden"
-- (prune intended — return null/empty so the row drops from the model
-- payload). A naive COALESCE would fall back to the legacy column when
-- every part is hidden, undoing the prune. CASE on EXISTS(any kind)
-- splits the two cases.
CASE
WHEN EXISTS (SELECT 1 FROM message_parts pp
WHERE pp.message_id = m.id AND pp.kind = 'tool_call')
THEN (SELECT jsonb_agg(p.payload ORDER BY p.sequence)
FROM message_parts p
WHERE p.message_id = m.id AND p.kind = 'tool_call' AND p.hidden_at IS NULL)
ELSE m.tool_calls
END AS tool_calls,
CASE
WHEN EXISTS (SELECT 1 FROM message_parts pp
WHERE pp.message_id = m.id AND pp.kind = 'tool_result')
THEN (SELECT p.payload
FROM message_parts p
WHERE p.message_id = m.id AND p.kind = 'tool_result' AND p.hidden_at IS NULL
ORDER BY p.sequence LIMIT 1)
ELSE m.tool_results
END AS tool_results,
(SELECT jsonb_agg(p.payload ORDER BY p.sequence)
FROM message_parts p
WHERE p.message_id = m.id AND p.kind = 'tool_call'),
m.tool_calls
) AS tool_calls,
COALESCE(
(SELECT p.payload
FROM message_parts p
WHERE p.message_id = m.id AND p.kind = 'tool_result'
ORDER BY p.sequence
LIMIT 1),
m.tool_results
) AS tool_results,
(SELECT jsonb_agg(p.payload ORDER BY p.sequence)
FROM message_parts p
WHERE p.message_id = m.id AND p.kind = 'reasoning') AS reasoning_parts
WHERE p.message_id = m.id AND p.kind = 'reasoning' AND p.hidden_at IS NULL) AS reasoning_parts
FROM messages m;
ALTER TABLE messages ADD COLUMN IF NOT EXISTS tokens_used INTEGER;

View File

@@ -0,0 +1,96 @@
import { describe, it, expect, beforeEach } from 'vitest';
import {
selectPruneTargets,
PROTECTED_TOKENS,
PRUNE_TRIGGER_TOKENS,
type PartForPrune,
} from '../inference/prune.js';
// Test fixture: build a tool_result part whose payload size yields a known
// token estimate (chars/4). The decision logic only cares about
// JSON.stringify(payload).length, so a string payload of `4n` chars
// produces exactly `n` tokens.
let seq = 0;
function part(tokens: number, createdAt: Date): PartForPrune {
seq += 1;
// JSON.stringify("xxx...") wraps in quotes (adds 2 chars), so subtract 2
// before multiplying. Math.ceil((len+2)/4) needs len ≈ 4*tokens - 2 so the
// total stringified length is 4*tokens. Approximate by padding 4 chars per
// token; the off-by-one from quotes is small and tests check totals, not
// exact per-part counts.
const text = 'x'.repeat(tokens * 4 - 2);
return { id: `p${seq}`, payload: text, created_at: createdAt };
}
const T_NOW = new Date('2026-05-22T12:00:00Z');
function ago(secondsBack: number): Date {
return new Date(T_NOW.getTime() - secondsBack * 1000);
}
describe('selectPruneTargets', () => {
beforeEach(() => {
seq = 0;
});
it('returns nothing when there are no parts', () => {
expect(selectPruneTargets([], null)).toEqual({ ids: [], freedTokens: 0 });
});
it('returns nothing when total tokens are under the protection window', () => {
const parts: PartForPrune[] = [
part(10_000, ago(10)),
part(10_000, ago(20)),
]; // 20k total, all protected
expect(selectPruneTargets(parts, null)).toEqual({ ids: [], freedTokens: 0 });
});
it('returns nothing when candidate total is below the prune trigger', () => {
// Protection fills with ~40k newest, candidates only ~5k. Below 20k trigger.
const parts: PartForPrune[] = [
part(20_000, ago(10)),
part(20_000, ago(20)),
// Past protection; total ~5k won't trigger.
part(5_000, ago(30)),
];
const result = selectPruneTargets(parts, null);
expect(result.ids).toEqual([]);
expect(result.freedTokens).toBe(0);
});
it('hides candidates past protection when their total clears the trigger', () => {
// Newest 40k protected; older 30k cleanly above the 20k trigger.
const parts: PartForPrune[] = [
part(20_000, ago(10)),
part(20_000, ago(20)),
// Past protection, total ~30k freed.
part(15_000, ago(30)),
part(15_000, ago(40)),
];
const result = selectPruneTargets(parts, null);
expect(result.ids).toEqual(['p3', 'p4']);
expect(result.freedTokens).toBeGreaterThanOrEqual(PRUNE_TRIGGER_TOKENS);
});
it('stops at the compaction summary boundary', () => {
// Newest 30k protected (just under PROTECTED_TOKENS=40k); then 30k of
// older parts. Boundary sits at ago(35), so the ago(40) part is
// beyond it and gets skipped.
const parts: PartForPrune[] = [
part(15_000, ago(10)),
part(15_000, ago(20)),
part(15_000, ago(30)), // crosses protection threshold; candidate
part(15_000, ago(40)), // beyond summary boundary; skipped
];
const tailStart = ago(35);
const result = selectPruneTargets(parts, tailStart);
// ago(30) is the only candidate inside the window; 15k is below the
// 20k trigger so we expect no hides.
expect(result.ids).toEqual([]);
});
it('does not prune when only protected parts exist (no candidates)', () => {
// Exactly PROTECTED_TOKENS of newest parts; no older candidates.
const parts: PartForPrune[] = [part(PROTECTED_TOKENS, ago(10))];
expect(selectPruneTargets(parts, null)).toEqual({ ids: [], freedTokens: 0 });
});
});

View File

@@ -0,0 +1,14 @@
import { describe, it, expect } from 'vitest';
import { ALL_TOOLS } from '../tools.js';
describe('ALL_TOOLS registry', () => {
// v1.13.3: tools must be alpha-sorted at module load. llama.cpp's prompt
// cache hits on byte-identical prefixes; the tool list lives near the
// top of the system prompt, so any order drift invalidates every cached
// turn. The registry sort is the single source of truth; downstream
// helpers (toolJsonSchemas, TOOLS_BY_NAME, buildAiTools) inherit it.
it('exports tools in alphabetical order by name', () => {
const names = ALL_TOOLS.map((t) => t.name);
expect(names).toEqual([...names].sort((a, b) => a.localeCompare(b)));
});
});

View File

@@ -8,6 +8,7 @@ import type {
import * as compaction from '../compaction.js';
import { buildSystemPrompt } from '../system-prompt.js';
import { isAnySentinel } from './sentinels.js';
import { PRUNE_TRIGGER_TOKENS, prune } from './prune.js';
import type { InferenceContext } from './turn.js';
export interface OpenAiMessage {
@@ -166,6 +167,26 @@ export async function maybeFlagForCompaction(
contextLimit,
);
if (!overflow) return;
// v1.13.4: try the cheap prune first. If it freed at least the buffer
// worth of tokens (PRUNE_TRIGGER_TOKENS, identical to COMPACTION_BUFFER),
// we're below the threshold again — skip flagging summarize for the next
// turn. The next turn's overflow check will re-evaluate from scratch.
// Prune failures (DB errors etc.) propagate so the surrounding inference
// path sees them; the catch in finalizeCompletion / executeToolPhase
// doesn't shield this — by design, we want to know if prune is broken.
const pruned = await prune({ sql: ctx.sql, chatId });
if (pruned.hidden > 0) {
ctx.log.info(
{ chatId, hidden: pruned.hidden, freedTokens: pruned.freedTokens },
'inference: prune freed context budget',
);
}
if (pruned.freedTokens >= PRUNE_TRIGGER_TOKENS) {
// Prune handled it; skip the (expensive) summarize path.
return;
}
await ctx.sql`UPDATE chats SET needs_compaction = true WHERE id = ${chatId}`;
ctx.log.info({ chatId, promptTokens, completionTokens, contextLimit }, 'inference: flagged for compaction');
}

View File

@@ -0,0 +1,127 @@
import type { Sql } from '../../db.js';
// v1.13.4: two-tier compaction prune. Opencode's prune half (the cheap one);
// summarize half shipped in v1.11.0 as services/compaction.ts.
//
// Algorithm: scan tool_result parts newest-first. Protect the last
// PROTECTED_TOKENS of content (the model recently saw these — pruning them
// kills coherence). Older parts are candidates. Mark them hidden_at only
// if the candidate pool would free at least PRUNE_TRIGGER_TOKENS — pruning
// 3 small tool_results to recover 500 tokens isn't worth the loss of
// fidelity for the model's next turn.
//
// Stops at the last compaction summary boundary (chats.tail_start_id). The
// v1.11.0 summary already encodes everything before that point; pruning
// across the boundary would double-erase.
export const PROTECTED_TOKENS = 40_000;
export const PRUNE_TRIGGER_TOKENS = 20_000;
// Rough char-to-token estimate. Same heuristic compaction's usable() uses
// implicitly via the buffer constant.
function estimateTokens(text: string): number {
return Math.ceil(text.length / 4);
}
function payloadTokens(payload: unknown): number {
return estimateTokens(JSON.stringify(payload ?? ''));
}
export interface PruneResult {
hidden: number;
freedTokens: number;
}
// Pure algorithmic core, exported for unit-test access. Takes parts already
// ordered newest-first, plus an optional cutoff (last compaction summary
// boundary). Returns the part ids to hide and the total token estimate of
// the candidates. Caller does the DB UPDATE.
export interface PartForPrune {
id: string;
payload: unknown;
created_at: Date;
}
export function selectPruneTargets(
partsNewestFirst: ReadonlyArray<PartForPrune>,
tailStartCreatedAt: Date | null,
): { ids: string[]; freedTokens: number } {
let protectedTokens = 0;
const candidates: { id: string; tokens: number }[] = [];
let crossedProtection = false;
for (const part of partsNewestFirst) {
if (tailStartCreatedAt && part.created_at < tailStartCreatedAt) {
// Past the last summary boundary; the v1.11.0 anchored summary already
// covers everything older. Bail rather than double-erase.
break;
}
const tokens = payloadTokens(part.payload);
if (!crossedProtection) {
protectedTokens += tokens;
if (protectedTokens >= PROTECTED_TOKENS) {
crossedProtection = true;
}
continue;
}
candidates.push({ id: part.id, tokens });
}
const candidateTokens = candidates.reduce((s, c) => s + c.tokens, 0);
if (candidates.length === 0 || candidateTokens < PRUNE_TRIGGER_TOKENS) {
return { ids: [], freedTokens: 0 };
}
return { ids: candidates.map((c) => c.id), freedTokens: candidateTokens };
}
export async function prune(args: {
sql: Sql;
chatId: string;
}): Promise<PruneResult> {
const { sql, chatId } = args;
// Newest-first scan of visible tool_result parts in this chat. Pull
// chats.tail_start_id alongside so we know where the last summary boundary
// sits (don't prune across it).
const parts = await sql<{
id: string;
payload: unknown;
created_at: Date;
tail_start_id: string | null;
}[]>`
SELECT p.id, p.payload, m.created_at,
(SELECT c.tail_start_id FROM chats c WHERE c.id = ${chatId}) AS tail_start_id
FROM message_parts p
JOIN messages m ON m.id = p.message_id
WHERE m.chat_id = ${chatId}
AND p.kind = 'tool_result'
AND p.hidden_at IS NULL
ORDER BY m.created_at DESC, p.sequence DESC
`;
if (parts.length === 0) {
return { hidden: 0, freedTokens: 0 };
}
// Read the boundary cutoff timestamp once. Older messages are off-limits.
let tailStartCreatedAt: Date | null = null;
const firstTailId = parts[0]?.tail_start_id ?? null;
if (firstTailId) {
const tailRow = await sql<{ created_at: Date }[]>`
SELECT created_at FROM messages WHERE id = ${firstTailId}
`;
tailStartCreatedAt = tailRow[0]?.created_at ?? null;
}
const decision = selectPruneTargets(parts, tailStartCreatedAt);
if (decision.ids.length === 0) {
return { hidden: 0, freedTokens: 0 };
}
await sql`
UPDATE message_parts
SET hidden_at = clock_timestamp()
WHERE id = ANY(${decision.ids})
`;
return { hidden: decision.ids.length, freedTokens: decision.freedTokens };
}

View File

@@ -19,7 +19,14 @@ import type {
TurnArgs,
} from './turn.js';
import { upstreamModel } from './provider.js';
import { jsonSchema, streamText, tool, type JSONValue, type ModelMessage } from 'ai';
import {
jsonSchema,
streamText,
tool,
type JSONValue,
type ModelMessage,
type ToolCallRepairFunction,
} from 'ai';
interface StreamOptions {
// null = omit tools entirely (compact phase); [] = caller stripped all tools
@@ -155,10 +162,36 @@ export async function streamCompletion(
// Replaces the v1.13.1-A counter-only diagnostic.
let reasoningAccumulated = '';
// v1.13.3: experimental_repairToolCall keeps the stream alive when the
// model emits a malformed tool call (bad JSON args, unknown name, etc.).
// Without a repair function streamText throws and the WHOLE stream dies;
// with one, the SDK invokes us and we route the bad call through normally.
// Strategy: pass through unmodified. executeToolPhase's existing error
// path (unknown tool name → "unknown tool: X" result; zod-reject → tool
// 'X' rejected — fieldname: required) already gives the model a clean
// recovery surface on the next turn. Logging gives us visibility into
// how often qwen3.6 actually emits broken calls.
const repairToolCall: ToolCallRepairFunction<NonNullable<typeof aiTools>> = async ({
toolCall,
error,
}) => {
ctx.log.warn(
{
toolCallId: toolCall.toolCallId,
toolName: toolCall.toolName,
error: error.message,
},
'malformed tool call surfaced via repairToolCall',
);
return toolCall;
};
const result = streamText({
model: upstreamModel(ctx.config.LLAMA_SWAP_URL, model),
messages: aiMessages,
...(aiTools ? { tools: aiTools, toolChoice: 'auto' as const } : {}),
...(aiTools
? { tools: aiTools, toolChoice: 'auto' as const, experimental_repairToolCall: repairToolCall }
: {}),
...(typeof opts.temperature === 'number' ? { temperature: opts.temperature } : {}),
abortSignal: signal,
});

View File

@@ -527,6 +527,11 @@ export const askUserInput: ToolDef<AskUserInputInputT> = {
},
};
// v1.13.3: alpha-sorted by tool.name at module load. llama.cpp's prompt
// cache hits on byte-identical prefixes; the tool list lives near the top
// of the system prompt, so any order drift would invalidate every cached
// turn. Single source of truth for ordering lives here — toolJsonSchemas()
// and TOOLS_BY_NAME inherit it.
export const ALL_TOOLS: ReadonlyArray<ToolDef<unknown>> = [
viewFile as ToolDef<unknown>,
listDir as ToolDef<unknown>,
@@ -553,7 +558,7 @@ export const ALL_TOOLS: ReadonlyArray<ToolDef<unknown>> = [
watchChanges as ToolDef<unknown>,
getSemanticNeighborhoods as ToolDef<unknown>,
getFrameworkAnalysis as ToolDef<unknown>,
];
].sort((a, b) => a.name.localeCompare(b.name));
// v1.8.2: forward-compatible read-only whitelist. An agent whose `tools` is
// fully contained in this set gets a generous default tool budget (30);