Files
boocode/apps/server/src/services/inference/turn.ts
indifferentketchup bcc89d8adc feat: MistakeTracker + file-provenance ledger (v2.7.4)
Two native-inference hardening features from boocode_code_review_v2 §1 #12.

MistakeTracker: new pure mistake-tracker.ts tracks consecutive heterogeneous
tool failures (kinds surfaced per tool from tool-phase.ts). On 3 in a row the
turn loop soft-nudges (model-facing recovery guidance + mistake_recovery
sentinel + reset), then escalates to stopping the turn (cap-hit-style, Continue
affordance) on a re-trip. Complements doom-loop (identical repeats) + cap-hit.

File-provenance ledger: compaction.ts derives a deterministic ## Files Read list
from the head messages' read-tool calls and injects it into the rolling-summary
prompt so provenance survives compaction (no new table; read-only).

mistake_recovery sentinel: MessageMetadata arm (server + web) + MessageBubble
render branch. Built by 2 parallel agents. Server 545 tests passing (23 new);
build + web tsc clean. Native-inference only. Builds on v2.7.3.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-01 13:05:03 +00:00

566 lines
22 KiB
TypeScript

import type { FastifyBaseLogger } from 'fastify';
import type { Sql } from '../../db.js';
import type { Config } from '../../config.js';
import type {
Agent,
ErrorReason,
Message,
MessageMetadata,
Project,
Session,
ToolCall,
UserStreamFrame,
} from '../../types/api.js';
import { ALL_TOOLS } from '../tools.js';
import { resolveProjectRoot } from '../path_guard.js';
import { maybeAutoNameChat } from '../auto_name.js';
import { rewriteSearchQuery } from '../task-search-rewrite.js';
import { getAgentById } from '../agents.js';
import * as compaction from '../compaction.js';
import type { Broker } from '../broker.js';
import { resolveToolBudget } from './budget.js';
import {
detectDoomLoop,
} from './sentinels.js';
import {
detectMistakePattern,
freshMistakeState,
recordStep,
MISTAKE_RECOVERY_NOTE,
type MistakeState,
} from './mistake-tracker.js';
import {
buildMessagesPayload,
loadContext,
} from './payload.js';
import {
finalizeCompletion,
handleAbortOrError,
} from './error-handler.js';
import {
executeStreamPhase,
} from './stream-phase.js';
import { executeToolPhase, type ToolPhaseResult } from './tool-phase.js';
import type { StreamPhaseState } from './types.js';
import {
runCapHitSummary,
runDoomLoopSummary,
runStepCapSummary,
insertMistakeRecoverySentinel,
} from './sentinel-summaries.js';
// v1.14.0: hard ceiling on the number of stream-and-tool iterations per
// user-message turn. Per-agent cap via agent.steps is the primary knob;
// MAX_STEPS is the safety ceiling. 200 is 4x the effective budget ceiling
// (50 tool calls) — in practice budget fires first unless the model makes
// many 0-tool-call iterations (which exit the loop via the non-tool finish
// path anyway).
export const MAX_STEPS = 200;
// v1.12.4: re-exported so external callers (tests, future consumers) keep
// importing from services/inference.js as the public surface.
export { detectDoomLoop, DOOM_LOOP_THRESHOLD } from './sentinels.js';
export { buildMessagesPayload } from './payload.js';
export interface InferenceFrame {
type:
| 'message_started'
| 'delta'
| 'tool_call'
| 'tool_result'
| 'message_complete'
| 'usage'
| 'messages_deleted'
| 'session_renamed'
| 'chat_renamed'
| 'error';
message_id?: string;
message_ids?: string[];
chat_id?: string;
tool_message_id?: string;
tool_call_id?: string;
// v1.8.2: 'system' added so cap-hit sentinel messages can announce themselves
// through the normal message_started → delta → message_complete sequence.
role?: 'assistant' | 'tool' | 'user' | 'system';
content?: string;
tool_call?: ToolCall;
output?: unknown;
truncated?: boolean;
error?: string;
// v1.8.2: structured error reason. Set on `type: 'error'` so the UI can
// surface a specific message; `error` stays the human-readable text.
reason?: ErrorReason;
// v1.8.2: piggybacks on `message_complete` so static or terminally-resolved
// messages can carry their persisted metadata to the live stream without a
// refetch (sentinels carry { kind: 'cap_hit', ... }; failed messages carry
// { kind: 'error', ... }).
metadata?: MessageMetadata | null;
tokens_used?: number | null;
ctx_used?: number | null;
ctx_max?: number | null;
completion_tokens?: number | null;
started_at?: string | null;
finished_at?: string | null;
model?: string;
session_id?: string;
name?: string;
}
export type FramePublisher = (sessionId: string, frame: InferenceFrame) => void;
export interface InferenceContext {
sql: Sql;
config: Config;
log: FastifyBaseLogger;
publish: FramePublisher;
publishUser: (frame: UserStreamFrame) => void;
// v1.11: passed through so compaction.process can publish 'compacted'
// frames on the same session WS channel useSessionStream subscribes to.
// Compaction is the only path that needs the raw broker handle (regular
// inference goes through `publish`); keeping a separate field avoids
// tempting other code paths into bypassing the session-id binding.
broker: Broker;
}
// v1.12.4: payload assembly extracted to ./inference/payload.ts (tests
// import buildMessagesPayload from this module, so a re-export below
// preserves the public surface). Stream + tool phases extracted to
// ./inference/stream-phase.ts and ./inference/tool-phase.ts.
export interface StreamResult {
finishReason: string | null;
content: string;
toolCalls: ToolCall[];
promptTokens: number | null;
completionTokens: number | null;
// v1.13.1-C: reasoning text accumulated across reasoning-delta parts.
// Empty string when the model doesn't emit reasoning (most cases).
reasoning: string;
}
export interface TurnArgs {
sessionId: string;
chatId: string;
assistantMessageId: string;
// v1.8.2: cumulative tool calls executed this run. Compared against the
// resolved budget at the top of each turn. Replaces the older `depth`
// counter (which counted iterations, not invocations).
toolsUsed: number;
// v1.11.6: ordered tool calls executed in this user-message turn (across
// recursive runAssistantTurn invocations). Reset to [] at user-message
// boundaries by runInference, same as toolsUsed. Doom-loop check at the
// top of runAssistantTurn slices the last DOOM_LOOP_THRESHOLD entries.
recentToolCalls: ToolCall[];
// v#12 MistakeTracker: heterogeneous-failure recovery state. Loop-local,
// reset per runInference (user-message boundary) like recentToolCalls. Folds
// tool-phase outcomes via recordStep each iteration; detectMistakePattern
// gates the nudge/escalate decision.
mistakeTracker: MistakeState;
// v#12: transient model-facing recovery note set when a nudge fires. Consumed
// (appended as a role:'system' message + cleared) on the NEXT payload build.
// Never persisted — mirrors how the cap-hit/doom-loop notes live only inside
// the summary call's messages array.
pendingRecoveryNote?: string;
signal: AbortSignal | undefined;
}
export async function runAssistantTurn(
ctx: InferenceContext,
args: TurnArgs,
): Promise<void> {
const { sessionId, chatId, signal } = args;
// v1.14.0: resolve agent once at the top. The agent stays fixed for the
// duration of this user-message turn — PATCH agent_id mid-conversation
// takes effect on the next runInference, not mid-loop.
const initialLoaded = await loadContext(ctx.sql, sessionId, chatId);
if (!initialLoaded) {
ctx.log.warn({ sessionId }, 'inference: session or project missing');
return;
}
const { session, project } = initialLoaded;
const agent = session.agent_id
? await getAgentById(project.path, session.agent_id)
: null;
const budget = resolveToolBudget(agent);
// v1.14.0: effectiveCap = min(agent.steps ?? Infinity, MAX_STEPS).
// steps: 0 means "no tool calls allowed" — the first stream phase runs
// but if it emits tool calls they are not executed (finalize as text-only).
const effectiveCap = Math.min(agent?.steps ?? Infinity, MAX_STEPS);
// steps: 0 special case — model responds text-only. The while loop would
// never enter (effectiveCap === 0), so we handle it explicitly before the
// loop. The model always gets at least one chance to respond with text.
if (effectiveCap === 0) {
const loaded = await loadContext(ctx.sql, sessionId, chatId);
if (loaded) {
await runTextOnlyTurn(ctx, args, loaded.session, loaded.project, loaded.history, agent);
}
return;
}
let stepNumber = 0;
let toolsUsed = args.toolsUsed;
let recentToolCalls = args.recentToolCalls;
let assistantMessageId = args.assistantMessageId;
// v#12 MistakeTracker: the tracker state is carried on `args` (mutated in
// place by recordStep). pendingRecoveryNote is a loop-local because it is a
// single-step transient — set when a nudge fires, consumed (injected into the
// next payload) and cleared on the following iteration.
const mistakeTracker = args.mistakeTracker;
let pendingRecoveryNote: string | undefined = args.pendingRecoveryNote;
while (stepNumber < effectiveCap) {
// ---- doom-loop check (moved from top-of-function) ----
const loop = detectDoomLoop(recentToolCalls);
if (loop) {
// Need fresh history for the summary.
const loaded = await loadContext(ctx.sql, sessionId, chatId);
if (loaded) {
const iterArgs: TurnArgs = { sessionId, chatId, assistantMessageId, toolsUsed, recentToolCalls, mistakeTracker, signal };
await runDoomLoopSummary(ctx, iterArgs, loaded.session, loaded.project, loaded.history, agent, loop);
}
break;
}
// ---- budget check (moved from top-of-function) ----
if (toolsUsed >= budget) {
const loaded = await loadContext(ctx.sql, sessionId, chatId);
if (loaded) {
const iterArgs: TurnArgs = { sessionId, chatId, assistantMessageId, toolsUsed, recentToolCalls, mistakeTracker, signal };
await runCapHitSummary(ctx, iterArgs, loaded.session, loaded.project, loaded.history, agent, budget);
}
break;
}
// ---- compaction check ----
// v1.11: if the prior turn flagged this chat for compaction, run it
// before loadContext so we read post-compaction history. Swallow
// failures and proceed with un-compacted history.
const chatFlag = await ctx.sql<{ needs_compaction: boolean }[]>`
SELECT needs_compaction FROM chats WHERE id = ${chatId}
`;
if (chatFlag[0]?.needs_compaction) {
try {
await compaction.process({
sql: ctx.sql,
config: ctx.config,
log: ctx.log,
broker: ctx.broker,
chatId,
});
} catch (err) {
ctx.log.warn({ err, chatId }, 'auto-compaction failed; clearing flag and proceeding');
await ctx.sql`UPDATE chats SET needs_compaction = false WHERE id = ${chatId}`;
}
}
// ---- load context (must re-load each iteration — new messages since last step) ----
const loaded = await loadContext(ctx.sql, sessionId, chatId);
if (!loaded) {
ctx.log.warn({ sessionId }, 'inference: session or project missing mid-loop');
break;
}
const { session: iterSession, project: iterProject, history } = loaded;
const projectRoot = await resolveProjectRoot(iterProject.path);
// v1.14.0: log step boundary for instrumentation. step_start parts are in
// the schema CHECK but not emitted here — writing to the assistant message
// before the stream phase creates a sequence-0 collision with
// partsFromAssistantMessage. A WS frame or structured log is sufficient
// since the frontend doesn't render step boundaries in v1.14.
ctx.log.info({ sessionId, chatId, step: stepNumber, assistantMessageId }, 'step_start');
// ---- build messages + stream phase ----
const messages = await buildMessagesPayload(iterSession, iterProject, history, agent, ctx.log);
const webToolsEnabled =
iterSession.web_search_enabled ?? iterProject.default_web_search_enabled ?? false;
if (stepNumber === 0 && webToolsEnabled && messages.length >= 2) {
const lastUserMsg = [...messages].reverse().find((m) => m.role === 'user');
if (lastUserMsg?.content) {
const hint = await rewriteSearchQuery(lastUserMsg.content);
if (hint && messages[0]?.role === 'system' && messages[0].content) {
messages[0].content += `\n\nThe user's search intent can be summarized as: "${hint}"`;
}
}
}
// v#12 MistakeTracker: if the prior iteration's nudge fired, append the
// transient recovery note to THIS payload (consumed exactly once, then
// cleared). Never persisted — same lifecycle as the cap-hit/doom-loop
// summary notes, which live only inside the in-memory messages array.
if (pendingRecoveryNote) {
messages.push({ role: 'system', content: pendingRecoveryNote });
pendingRecoveryNote = undefined;
}
const iterArgs: TurnArgs = { sessionId, chatId, assistantMessageId, toolsUsed, recentToolCalls, mistakeTracker, signal };
const state: StreamPhaseState = { accumulated: '', startedAt: null };
let result: StreamResult;
try {
result = await executeStreamPhase(ctx, iterArgs, iterSession, messages, state, agent, webToolsEnabled);
} catch (err) {
await handleAbortOrError(ctx, iterArgs, state.accumulated, err);
break;
}
// ---- non-tool finish → finalize and exit ----
if (result.toolCalls.length === 0) {
await finalizeCompletion(ctx, iterArgs, result, state.startedAt, iterSession);
break;
}
// ---- steps: 0 edge case ----
// effectiveCap check above guarantees we're inside the loop, but this
// guard handles the theoretical case where the model emits tool calls
// on step 0 when effectiveCap would have been 0 (impossible since the
// while condition prevents entry, but kept for safety). If effectiveCap
// is 1 and we're on step 0, tool calls ARE executed — steps counts
// iterations, not post-first-stream.
// ---- tool phase ----
let toolPhaseResult: ToolPhaseResult;
try {
toolPhaseResult = await executeToolPhase(ctx, iterArgs, result, state.startedAt, iterSession, projectRoot, agent);
} catch (err) {
// Tool phase errors are unexpected (individual tool failures are
// caught inside executeToolPhase). Log and break.
ctx.log.error({ err, sessionId, chatId, step: stepNumber }, 'tool phase threw unexpectedly');
break;
}
// ---- update loop locals ----
toolsUsed += toolPhaseResult.toolCallCount;
recentToolCalls = [...recentToolCalls, ...toolPhaseResult.toolCalls];
stepNumber++;
// v#12 MistakeTracker: fold this iteration's tool outcomes into the
// tracker, in order. recordStep mutates `mistakeTracker` in place (it is
// the same object referenced by args). A 'success' clears the streak.
for (const o of toolPhaseResult.outcomes) {
recordStep(mistakeTracker, o);
}
if (toolPhaseResult.action !== 'continue') {
// 'paused' (user input) or 'synthesis_done' — stop the loop. The turn is
// already ending, so neither a nudge nor an escalate would change the
// control flow; we skip the mistake decision here.
break;
}
// v#12 MistakeTracker: heterogeneous-failure decision. Only evaluated on
// the 'continue' path (the only case where the loop would otherwise
// proceed to another step). Complements the doom-loop check above, which
// only catches *identical* repeats.
const mistake = detectMistakePattern(mistakeTracker);
if (mistake === 'nudge') {
// Soft intervention: inject model-facing recovery guidance into the NEXT
// step's payload, drop a UI sentinel, bump nudges, reset the streak, and
// continue. The note is consumed (and cleared) at the top of the next
// iteration's payload build.
pendingRecoveryNote = MISTAKE_RECOVERY_NOTE;
const failureKinds = [...mistakeTracker.run];
await insertMistakeRecoverySentinel(ctx, sessionId, chatId, {
failureKinds,
count: failureKinds.length,
escalated: false,
canContinue: true,
});
mistakeTracker.nudges += 1;
mistakeTracker.run = [];
ctx.log.info(
{ sessionId, chatId, step: stepNumber, nudges: mistakeTracker.nudges, failureKinds },
'mistake_recovery nudge',
);
assistantMessageId = toolPhaseResult.nextAssistantId!;
continue;
}
if (mistake === 'escalate') {
// The nudge didn't break the failure run — stop the turn (cap-hit-style)
// to avoid burning the whole step budget on heterogeneous failures. The
// next assistant row is still 'streaming'; finalize it as a short note so
// the slot doesn't dangle, then drop the escalate sentinel.
const failureKinds = [...mistakeTracker.run];
assistantMessageId = toolPhaseResult.nextAssistantId!;
await ctx.sql`
UPDATE messages
SET content = '', status = 'complete', finished_at = clock_timestamp()
WHERE id = ${assistantMessageId}
`;
ctx.publish(sessionId, {
type: 'message_complete',
message_id: assistantMessageId,
chat_id: chatId,
});
await insertMistakeRecoverySentinel(ctx, sessionId, chatId, {
failureKinds,
count: failureKinds.length,
escalated: true,
canContinue: true,
});
ctx.publishUser({ type: 'chat_status', chat_id: chatId, status: 'idle', at: new Date().toISOString() });
ctx.log.info(
{ sessionId, chatId, step: stepNumber, failureKinds },
'mistake_recovery escalate — stopping turn',
);
break;
}
// 'continue' — advance to next assistant message.
assistantMessageId = toolPhaseResult.nextAssistantId!;
}
// ---- post-loop: step-cap sentinel ----
// When the loop exits because stepNumber reached effectiveCap, the last
// iteration's tool phase returned 'continue' with a nextAssistantId that
// is still in 'streaming' status (unfilled). Use it for the wrap-up.
if (stepNumber >= effectiveCap && effectiveCap < Infinity) {
const loaded = await loadContext(ctx.sql, sessionId, chatId);
if (loaded) {
const capArgs: TurnArgs = { sessionId, chatId, assistantMessageId, toolsUsed, recentToolCalls, mistakeTracker, signal };
await runStepCapSummary(ctx, capArgs, loaded.session, loaded.project, loaded.history, agent, stepNumber, effectiveCap);
}
}
}
// v1.14.0: special handling for steps: 0 — the model responds text-only.
// The while loop never enters (effectiveCap === 0). We stream once with
// no tools, finalize, and return. If the model emits tool calls despite
// not being offered tools, they're ignored (finalize as text-only).
async function runTextOnlyTurn(
ctx: InferenceContext,
args: TurnArgs,
session: Session,
project: Project,
history: Message[],
agent: Agent | null,
): Promise<void> {
const messages = await buildMessagesPayload(session, project, history, agent, ctx.log);
// Web tools are irrelevant when steps: 0 (no tool execution), but we
// still need to resolve the flag for executeStreamPhase's signature.
const webToolsEnabled =
session.web_search_enabled ?? project.default_web_search_enabled ?? false;
const state: StreamPhaseState = { accumulated: '', startedAt: null };
let result: StreamResult;
try {
result = await executeStreamPhase(ctx, args, session, messages, state, agent, webToolsEnabled);
} catch (err) {
await handleAbortOrError(ctx, args, state.accumulated, err);
return;
}
if (result.toolCalls.length > 0) {
ctx.log.warn(
{ chatId: args.chatId, toolCallCount: result.toolCalls.length },
'steps: 0 agent emitted tool calls; ignoring and finalizing as text-only',
);
// Override: strip tool calls so finalizeCompletion treats it as text-only.
result = { ...result, toolCalls: [] };
}
await finalizeCompletion(ctx, args, result, state.startedAt, session);
}
export async function runInference(
ctx: InferenceContext,
sessionId: string,
chatId: string,
assistantMessageId: string,
signal?: AbortSignal
): Promise<void> {
// v1.8.2: every fresh inference (initial send, regenerate, force_send,
// continue) starts with a clean budget. Tool-call accumulation across
// Continue invocations is what the hard ceiling guards against, not the
// per-call budget.
// v1.11.6: recentToolCalls also resets — doom-loop detection is scoped
// to a single user-message turn, so a Continue starts with no history.
// v#12 MistakeTracker: fresh per user-message turn, like recentToolCalls.
// Tracks consecutive heterogeneous tool failures across the loop's
// stream-and-tool iterations within this turn.
return runAssistantTurn(ctx, {
sessionId,
chatId,
assistantMessageId,
toolsUsed: 0,
recentToolCalls: [],
mistakeTracker: freshMistakeState(),
signal,
});
}
// v1.8.2: cap-hit summary flow. Called instead of erroring when the loop
// hits its budget. Reuses the in-flight assistant message slot to stream a
// short wrap-up reply with the synthetic note prepended and tools disabled,
// then always inserts a cap_hit sentinel afterward (regardless of summary
// outcome) so the UI can show a Continue affordance.
interface InferenceRegistration {
controller: AbortController;
completed: Promise<void>;
}
export function createInferenceRunner(
ctx: Omit<InferenceContext, 'publishUser'>,
publishUserFn: (user: string, frame: UserStreamFrame) => void
) {
const registry = new Map<string, InferenceRegistration>();
return {
enqueue(sessionId: string, chatId: string, assistantMessageId: string, user: string) {
const callCtx: InferenceContext = {
...ctx,
publishUser: (frame) => publishUserFn(user, frame),
// v1.11: broker comes in via ctx (set at registration time). Repeated
// here so the destructure carries it onto the per-call ctx without
// having to add it to every enqueue/cancel signature individually.
broker: ctx.broker,
};
// v1.8 mobile-tabs: announce working before the async loop starts so
// every device subscribed to the user channel sees the amber dot.
callCtx.publishUser({ type: 'chat_status', chat_id: chatId, status: 'streaming', at: new Date().toISOString() });
const controller = new AbortController();
let resolveCompleted!: () => void;
const completed = new Promise<void>((res) => { resolveCompleted = res; });
const registration: InferenceRegistration = { controller, completed };
registry.set(chatId, registration);
void (async () => {
try {
await runInference(callCtx, sessionId, chatId, assistantMessageId, controller.signal);
setImmediate(() => {
void maybeAutoNameChat(callCtx, chatId, sessionId).catch((err: Error) => {
callCtx.log.warn({ err, chatId }, 'auto-name failed');
});
});
} catch (err) {
callCtx.log.error({ err }, 'unhandled inference error');
} finally {
resolveCompleted();
// Only clear our own registration; a force-send may have replaced it.
if (registry.get(chatId) === registration) {
registry.delete(chatId);
}
}
})();
},
async cancel(_sessionId: string, chatId: string): Promise<boolean> {
const reg = registry.get(chatId);
if (!reg) return false;
reg.controller.abort();
// Swallow — we just need to wait for the catch/finally to persist state.
await reg.completed.catch(() => {});
return true;
},
hasActive(chatId: string): boolean {
return registry.has(chatId);
},
};
}
export const _toolNames = ALL_TOOLS.map((t) => t.name);