feat: add codex llm backend for ktx runtime work (#253)
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
2026-06-02 13:57:11 +02:00
|
|
|
import { z } from 'zod';
|
|
|
|
|
import { noopLogger, type KtxLogger } from '../core/config.js';
|
feat(cli): add ingest LLM rate-limit governor with paced retries (#261)
* feat(cli): add ingest rate limit governor
* feat(cli): wire ingest rate-limit config
* feat(cli): report provider rate-limit signals
* feat(cli): show ingest rate-limit waits
* fix(cli): complete rate-limit event coverage
* fix(cli): abort ingest provider calls cleanly
* fix(cli): propagate ingest cancellation
* fix(cli): reject pre-aborted ingest rate-limit waits
* fix(cli): honor Claude rate-limit reset waits
* fix(cli): retry thrown Codex rate-limit failures
* fix(cli): type Claude rate-limit result details
* fix(cli): emit ingest rate-limit countdowns from rejected signals
* fix(cli): report ai sdk rate-limit header utilization
* fix(cli): gate LLM rate-limit retries on the governor budget
The AI SDK and Codex runtimes retried 429 / opaque rate-limit failures up
to 6-7 times with no backoff when constructed without a RateLimitGovernor
(scan, memory, setup) or with pacing disabled, ignoring Retry-After and
worsening the limit. The outer retry loop only cooperates with the
governor's pause, so without active pacing there is no backoff to apply.
Route the retry bound through a single source: RateLimitGovernor
.maxRetryAttempts(), which returns retry.maxAttempts when enabled and 1
(no outer retry) when absent or disabled. All three runtimes (ai-sdk,
codex, claude-code) now use it, so ingest.rateLimit.retry.maxAttempts
genuinely controls attempts and the hard-coded 6 (plus Codex's off-by-one
extra attempt) is gone. Backend-native retry (e.g. the AI SDK's maxRetries)
still handles transient 429s.
Also correct the ktx.yaml docs for maxWaitMs (caps each wait, not the whole
run) and maxAttempts, and sync uv.lock ktx-sl/ktx-daemon to 0.9.0.
2026-06-05 12:10:27 +02:00
|
|
|
import { isAbortError, linkAbortSignal } from '../core/abort.js';
|
feat: add codex llm backend for ktx runtime work (#253)
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
2026-06-02 13:57:11 +02:00
|
|
|
import { isCompletedAgentStep, summarizeCodexExecEvents, type CodexExecEventSummary } from './codex-exec-events.js';
|
|
|
|
|
import {
|
|
|
|
|
startCodexRuntimeMcpServer,
|
|
|
|
|
type CodexRuntimeMcpServerHandle,
|
|
|
|
|
} from './codex-mcp-runtime-server.js';
|
|
|
|
|
import { resolveCodexModel } from './codex-models.js';
|
|
|
|
|
import { buildCodexRuntimeConfig } from './codex-runtime-config.js';
|
|
|
|
|
import { CodexSdkCliRunner, type CodexSdkRunner } from './codex-sdk-runner.js';
|
feat(cli): add ingest LLM rate-limit governor with paced retries (#261)
* feat(cli): add ingest rate limit governor
* feat(cli): wire ingest rate-limit config
* feat(cli): report provider rate-limit signals
* feat(cli): show ingest rate-limit waits
* fix(cli): complete rate-limit event coverage
* fix(cli): abort ingest provider calls cleanly
* fix(cli): propagate ingest cancellation
* fix(cli): reject pre-aborted ingest rate-limit waits
* fix(cli): honor Claude rate-limit reset waits
* fix(cli): retry thrown Codex rate-limit failures
* fix(cli): type Claude rate-limit result details
* fix(cli): emit ingest rate-limit countdowns from rejected signals
* fix(cli): report ai sdk rate-limit header utilization
* fix(cli): gate LLM rate-limit retries on the governor budget
The AI SDK and Codex runtimes retried 429 / opaque rate-limit failures up
to 6-7 times with no backoff when constructed without a RateLimitGovernor
(scan, memory, setup) or with pacing disabled, ignoring Retry-After and
worsening the limit. The outer retry loop only cooperates with the
governor's pause, so without active pacing there is no backoff to apply.
Route the retry bound through a single source: RateLimitGovernor
.maxRetryAttempts(), which returns retry.maxAttempts when enabled and 1
(no outer retry) when absent or disabled. All three runtimes (ai-sdk,
codex, claude-code) now use it, so ingest.rateLimit.retry.maxAttempts
genuinely controls attempts and the hard-coded 6 (plus Codex's off-by-one
extra attempt) is gone. Backend-native retry (e.g. the AI SDK's maxRetries)
still handles transient 429s.
Also correct the ktx.yaml docs for maxWaitMs (caps each wait, not the whole
run) and maxAttempts, and sync uv.lock ktx-sl/ktx-daemon to 0.9.0.
2026-06-05 12:10:27 +02:00
|
|
|
import type { RateLimitGovernor } from './rate-limit-governor.js';
|
feat: add codex llm backend for ktx runtime work (#253)
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
2026-06-02 13:57:11 +02:00
|
|
|
import type {
|
|
|
|
|
KtxGenerateObjectInput,
|
|
|
|
|
KtxGenerateTextInput,
|
|
|
|
|
KtxLlmRuntimePort,
|
|
|
|
|
KtxRuntimeToolSet,
|
|
|
|
|
LlmTokenUsage,
|
|
|
|
|
RunLoopParams,
|
|
|
|
|
RunLoopResult,
|
|
|
|
|
} from './runtime-port.js';
|
|
|
|
|
|
|
|
|
|
export interface CodexKtxLlmRuntimeDeps {
|
|
|
|
|
projectDir: string;
|
|
|
|
|
modelSlots: { default: string } & Partial<Record<string, string>>;
|
|
|
|
|
runner?: CodexSdkRunner;
|
|
|
|
|
startMcpServer?: (input: { projectDir: string; toolSet: KtxRuntimeToolSet }) => Promise<CodexRuntimeMcpServerHandle>;
|
|
|
|
|
logger?: KtxLogger;
|
feat(cli): add ingest LLM rate-limit governor with paced retries (#261)
* feat(cli): add ingest rate limit governor
* feat(cli): wire ingest rate-limit config
* feat(cli): report provider rate-limit signals
* feat(cli): show ingest rate-limit waits
* fix(cli): complete rate-limit event coverage
* fix(cli): abort ingest provider calls cleanly
* fix(cli): propagate ingest cancellation
* fix(cli): reject pre-aborted ingest rate-limit waits
* fix(cli): honor Claude rate-limit reset waits
* fix(cli): retry thrown Codex rate-limit failures
* fix(cli): type Claude rate-limit result details
* fix(cli): emit ingest rate-limit countdowns from rejected signals
* fix(cli): report ai sdk rate-limit header utilization
* fix(cli): gate LLM rate-limit retries on the governor budget
The AI SDK and Codex runtimes retried 429 / opaque rate-limit failures up
to 6-7 times with no backoff when constructed without a RateLimitGovernor
(scan, memory, setup) or with pacing disabled, ignoring Retry-After and
worsening the limit. The outer retry loop only cooperates with the
governor's pause, so without active pacing there is no backoff to apply.
Route the retry bound through a single source: RateLimitGovernor
.maxRetryAttempts(), which returns retry.maxAttempts when enabled and 1
(no outer retry) when absent or disabled. All three runtimes (ai-sdk,
codex, claude-code) now use it, so ingest.rateLimit.retry.maxAttempts
genuinely controls attempts and the hard-coded 6 (plus Codex's off-by-one
extra attempt) is gone. Backend-native retry (e.g. the AI SDK's maxRetries)
still handles transient 429s.
Also correct the ktx.yaml docs for maxWaitMs (caps each wait, not the whole
run) and maxAttempts, and sync uv.lock ktx-sl/ktx-daemon to 0.9.0.
2026-06-05 12:10:27 +02:00
|
|
|
rateLimitGovernor?: Pick<RateLimitGovernor, 'waitForReady' | 'report' | 'maxRetryAttempts'>;
|
feat: add codex llm backend for ktx runtime work (#253)
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
2026-06-02 13:57:11 +02:00
|
|
|
}
|
|
|
|
|
|
|
|
|
|
function modelForRole(modelSlots: CodexKtxLlmRuntimeDeps['modelSlots'], role: string): string {
|
|
|
|
|
return resolveCodexModel(modelSlots[role] ?? modelSlots.default);
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
function promptWithSystem(system: string | undefined, prompt: string): string {
|
|
|
|
|
return [system, prompt].filter(Boolean).join('\n\n');
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
interface CollectCodexEventsOptions {
|
|
|
|
|
stepBudget?: number;
|
|
|
|
|
abortController?: AbortController;
|
|
|
|
|
onStep?: (stepIndex: number) => void | Promise<void>;
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
interface CollectCodexEventsResult {
|
|
|
|
|
events: unknown[];
|
|
|
|
|
budgetExceeded: boolean;
|
|
|
|
|
streamError?: Error;
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
function eventRecord(value: unknown): Record<string, unknown> | undefined {
|
|
|
|
|
return value && typeof value === 'object' ? (value as Record<string, unknown>) : undefined;
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
function isTurnCompleted(event: unknown): boolean {
|
|
|
|
|
return eventRecord(event)?.type === 'turn.completed';
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
/**
|
|
|
|
|
* Drains the Codex stream once, emitting a step as each agent action completes
|
|
|
|
|
* so callers see live progress and the step budget is enforced mid-run. Every
|
|
|
|
|
* completed agent-action item counts (see {@link isCompletedAgentStep}), so
|
|
|
|
|
* built-in `command_execution` steps decrement the budget the same as
|
|
|
|
|
* `mcp_tool_call`s. A turn that produced no actions still counts as one step,
|
|
|
|
|
* matching the metrics summary and the AI SDK backend.
|
|
|
|
|
*/
|
|
|
|
|
async function collectEvents(
|
|
|
|
|
events: AsyncIterable<unknown>,
|
|
|
|
|
options: CollectCodexEventsOptions = {},
|
|
|
|
|
): Promise<CollectCodexEventsResult> {
|
|
|
|
|
const collected: unknown[] = [];
|
|
|
|
|
let completedSteps = 0;
|
|
|
|
|
let sawActionStep = false;
|
|
|
|
|
let budgetExceeded = false;
|
|
|
|
|
let streamError: Error | undefined;
|
|
|
|
|
|
|
|
|
|
// The SDK yields every stdout event, then throws on a non-zero codex exec
|
|
|
|
|
// exit. Catch that throw so the events already collected (which carry the
|
|
|
|
|
// real `turn.failed`/`error` reason) survive for the summary; the masked
|
|
|
|
|
// exit message is kept only as a fallback when no error event was emitted.
|
|
|
|
|
try {
|
|
|
|
|
for await (const event of events) {
|
|
|
|
|
collected.push(event);
|
|
|
|
|
|
|
|
|
|
const isActionStep = isCompletedAgentStep(event);
|
|
|
|
|
if (isActionStep) {
|
|
|
|
|
sawActionStep = true;
|
|
|
|
|
} else if (sawActionStep || !isTurnCompleted(event)) {
|
|
|
|
|
// Only fall back to counting a bare turn as a step when the turn produced
|
|
|
|
|
// no agent actions; a completed turn is terminal, so it never aborts.
|
|
|
|
|
continue;
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
completedSteps += 1;
|
|
|
|
|
await options.onStep?.(completedSteps);
|
|
|
|
|
if (isActionStep && options.stepBudget !== undefined && completedSteps >= options.stepBudget) {
|
|
|
|
|
budgetExceeded = true;
|
|
|
|
|
options.abortController?.abort();
|
|
|
|
|
break;
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
} catch (error) {
|
|
|
|
|
streamError = error instanceof Error ? error : new Error(String(error));
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
return { events: collected, budgetExceeded, ...(streamError ? { streamError } : {}) };
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
function metrics(summary: CodexExecEventSummary, startedAt: number): { totalMs: number; usage: LlmTokenUsage } {
|
|
|
|
|
return { totalMs: Date.now() - startedAt, usage: summary.usage };
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
function summaryError(summary: CodexExecEventSummary, streamError?: Error): Error | undefined {
|
|
|
|
|
// A `turn.failed`/`error` event carries the real reason; prefer it over the
|
|
|
|
|
// SDK's generic non-zero-exit throw. Fall back to the stream error only when
|
|
|
|
|
// no event explained the failure (e.g. spawn failure or auth before a turn).
|
|
|
|
|
if (summary.error) {
|
|
|
|
|
return summary.error;
|
|
|
|
|
}
|
|
|
|
|
if (summary.toolFailures.length > 0) {
|
|
|
|
|
return new Error(`Codex runtime tool call failed: ${summary.toolFailures.join('; ')}`);
|
|
|
|
|
}
|
|
|
|
|
return streamError;
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
function assertSuccessfulText(summary: CodexExecEventSummary, streamError?: Error): string {
|
|
|
|
|
const error = summaryError(summary, streamError);
|
|
|
|
|
if (error) {
|
|
|
|
|
throw error;
|
|
|
|
|
}
|
|
|
|
|
if (!summary.finalText.trim()) {
|
|
|
|
|
throw new Error('Codex completed without an agent message');
|
|
|
|
|
}
|
|
|
|
|
return summary.finalText;
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
function parseStructuredOutput<TOutput, TSchema extends z.ZodType<TOutput>>(schema: TSchema, text: string): TOutput {
|
|
|
|
|
try {
|
|
|
|
|
return schema.parse(JSON.parse(text));
|
|
|
|
|
} catch (error) {
|
|
|
|
|
const message = error instanceof Error ? error.message : String(error);
|
|
|
|
|
throw new Error(`Codex structured output failed validation: ${message}`);
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
async function mcpForTools(input: {
|
|
|
|
|
projectDir: string;
|
|
|
|
|
toolSet?: KtxRuntimeToolSet;
|
|
|
|
|
startMcpServer: CodexKtxLlmRuntimeDeps['startMcpServer'];
|
|
|
|
|
}): Promise<CodexRuntimeMcpServerHandle | undefined> {
|
|
|
|
|
if (!input.toolSet || Object.keys(input.toolSet).length === 0) {
|
|
|
|
|
return undefined;
|
|
|
|
|
}
|
|
|
|
|
return (input.startMcpServer ?? startCodexRuntimeMcpServer)({
|
|
|
|
|
projectDir: input.projectDir,
|
|
|
|
|
toolSet: input.toolSet,
|
|
|
|
|
});
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
function runtimeToolNames(toolSet: KtxRuntimeToolSet | undefined): string[] {
|
|
|
|
|
return Object.values(toolSet ?? {}).map((descriptor) => descriptor.name);
|
|
|
|
|
}
|
|
|
|
|
|
feat(cli): add ingest LLM rate-limit governor with paced retries (#261)
* feat(cli): add ingest rate limit governor
* feat(cli): wire ingest rate-limit config
* feat(cli): report provider rate-limit signals
* feat(cli): show ingest rate-limit waits
* fix(cli): complete rate-limit event coverage
* fix(cli): abort ingest provider calls cleanly
* fix(cli): propagate ingest cancellation
* fix(cli): reject pre-aborted ingest rate-limit waits
* fix(cli): honor Claude rate-limit reset waits
* fix(cli): retry thrown Codex rate-limit failures
* fix(cli): type Claude rate-limit result details
* fix(cli): emit ingest rate-limit countdowns from rejected signals
* fix(cli): report ai sdk rate-limit header utilization
* fix(cli): gate LLM rate-limit retries on the governor budget
The AI SDK and Codex runtimes retried 429 / opaque rate-limit failures up
to 6-7 times with no backoff when constructed without a RateLimitGovernor
(scan, memory, setup) or with pacing disabled, ignoring Retry-After and
worsening the limit. The outer retry loop only cooperates with the
governor's pause, so without active pacing there is no backoff to apply.
Route the retry bound through a single source: RateLimitGovernor
.maxRetryAttempts(), which returns retry.maxAttempts when enabled and 1
(no outer retry) when absent or disabled. All three runtimes (ai-sdk,
codex, claude-code) now use it, so ingest.rateLimit.retry.maxAttempts
genuinely controls attempts and the hard-coded 6 (plus Codex's off-by-one
extra attempt) is gone. Backend-native retry (e.g. the AI SDK's maxRetries)
still handles transient 429s.
Also correct the ktx.yaml docs for maxWaitMs (caps each wait, not the whole
run) and maxAttempts, and sync uv.lock ktx-sl/ktx-daemon to 0.9.0.
2026-06-05 12:10:27 +02:00
|
|
|
const CODEX_RATE_LIMIT_MARKERS = /\b429\b|rate limit|too many requests|quota exceeded|temporarily overloaded/i;
|
|
|
|
|
|
|
|
|
|
function isCodexRateLimitError(error: Error | undefined): boolean {
|
|
|
|
|
return !!error && CODEX_RATE_LIMIT_MARKERS.test(error.message);
|
|
|
|
|
}
|
|
|
|
|
|
feat: add codex llm backend for ktx runtime work (#253)
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
2026-06-02 13:57:11 +02:00
|
|
|
export class CodexKtxLlmRuntime implements KtxLlmRuntimePort {
|
|
|
|
|
private readonly runner: CodexSdkRunner;
|
|
|
|
|
private readonly logger: KtxLogger;
|
|
|
|
|
|
|
|
|
|
constructor(private readonly deps: CodexKtxLlmRuntimeDeps) {
|
|
|
|
|
this.runner = deps.runner ?? new CodexSdkCliRunner();
|
|
|
|
|
this.logger = deps.logger ?? noopLogger;
|
|
|
|
|
}
|
|
|
|
|
|
feat(cli): add ingest LLM rate-limit governor with paced retries (#261)
* feat(cli): add ingest rate limit governor
* feat(cli): wire ingest rate-limit config
* feat(cli): report provider rate-limit signals
* feat(cli): show ingest rate-limit waits
* fix(cli): complete rate-limit event coverage
* fix(cli): abort ingest provider calls cleanly
* fix(cli): propagate ingest cancellation
* fix(cli): reject pre-aborted ingest rate-limit waits
* fix(cli): honor Claude rate-limit reset waits
* fix(cli): retry thrown Codex rate-limit failures
* fix(cli): type Claude rate-limit result details
* fix(cli): emit ingest rate-limit countdowns from rejected signals
* fix(cli): report ai sdk rate-limit header utilization
* fix(cli): gate LLM rate-limit retries on the governor budget
The AI SDK and Codex runtimes retried 429 / opaque rate-limit failures up
to 6-7 times with no backoff when constructed without a RateLimitGovernor
(scan, memory, setup) or with pacing disabled, ignoring Retry-After and
worsening the limit. The outer retry loop only cooperates with the
governor's pause, so without active pacing there is no backoff to apply.
Route the retry bound through a single source: RateLimitGovernor
.maxRetryAttempts(), which returns retry.maxAttempts when enabled and 1
(no outer retry) when absent or disabled. All three runtimes (ai-sdk,
codex, claude-code) now use it, so ingest.rateLimit.retry.maxAttempts
genuinely controls attempts and the hard-coded 6 (plus Codex's off-by-one
extra attempt) is gone. Backend-native retry (e.g. the AI SDK's maxRetries)
still handles transient 429s.
Also correct the ktx.yaml docs for maxWaitMs (caps each wait, not the whole
run) and maxAttempts, and sync uv.lock ktx-sl/ktx-daemon to 0.9.0.
2026-06-05 12:10:27 +02:00
|
|
|
private async runWithRateLimitRetry<T>(
|
|
|
|
|
abortSignal: AbortSignal | undefined,
|
|
|
|
|
run: () => Promise<T>,
|
|
|
|
|
getError: (result: T) => Error | undefined,
|
|
|
|
|
): Promise<T> {
|
|
|
|
|
// maxRetryAttempts() returns 1 when no governor is present or pacing is
|
|
|
|
|
// disabled, so an opaque rate-limit failure surfaces on the first attempt
|
|
|
|
|
// instead of being retried with no backoff.
|
|
|
|
|
const maxAttempts = this.deps.rateLimitGovernor?.maxRetryAttempts() ?? 1;
|
|
|
|
|
for (let attempt = 0; ; attempt += 1) {
|
|
|
|
|
await this.deps.rateLimitGovernor?.waitForReady(abortSignal);
|
|
|
|
|
const lastAttempt = attempt >= maxAttempts - 1;
|
|
|
|
|
try {
|
|
|
|
|
const result = await run();
|
|
|
|
|
const error = getError(result);
|
|
|
|
|
if (!isCodexRateLimitError(error) || lastAttempt) {
|
|
|
|
|
return result;
|
|
|
|
|
}
|
|
|
|
|
} catch (error) {
|
|
|
|
|
if (isAbortError(error)) {
|
|
|
|
|
throw error;
|
|
|
|
|
}
|
|
|
|
|
const err = error instanceof Error ? error : new Error(String(error));
|
|
|
|
|
if (!isCodexRateLimitError(err) || lastAttempt) {
|
|
|
|
|
throw error;
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
this.deps.rateLimitGovernor?.report({ provider: 'codex', status: 'rejected', rateLimitType: 'opaque' });
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
feat: add codex llm backend for ktx runtime work (#253)
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
2026-06-02 13:57:11 +02:00
|
|
|
async generateText(input: KtxGenerateTextInput): Promise<string> {
|
|
|
|
|
const startedAt = Date.now();
|
|
|
|
|
const model = modelForRole(this.deps.modelSlots, input.role);
|
|
|
|
|
const mcp = await mcpForTools({
|
|
|
|
|
projectDir: this.deps.projectDir,
|
|
|
|
|
toolSet: input.tools,
|
|
|
|
|
startMcpServer: this.deps.startMcpServer,
|
|
|
|
|
});
|
|
|
|
|
try {
|
|
|
|
|
const config = buildCodexRuntimeConfig({
|
|
|
|
|
model,
|
|
|
|
|
...(mcp
|
|
|
|
|
? {
|
|
|
|
|
mcp: {
|
|
|
|
|
url: mcp.url,
|
|
|
|
|
bearerTokenEnvVar: mcp.bearerTokenEnvVar,
|
|
|
|
|
bearerToken: mcp.bearerToken,
|
|
|
|
|
toolNames: runtimeToolNames(input.tools),
|
|
|
|
|
},
|
|
|
|
|
}
|
|
|
|
|
: {}),
|
|
|
|
|
});
|
feat(cli): add ingest LLM rate-limit governor with paced retries (#261)
* feat(cli): add ingest rate limit governor
* feat(cli): wire ingest rate-limit config
* feat(cli): report provider rate-limit signals
* feat(cli): show ingest rate-limit waits
* fix(cli): complete rate-limit event coverage
* fix(cli): abort ingest provider calls cleanly
* fix(cli): propagate ingest cancellation
* fix(cli): reject pre-aborted ingest rate-limit waits
* fix(cli): honor Claude rate-limit reset waits
* fix(cli): retry thrown Codex rate-limit failures
* fix(cli): type Claude rate-limit result details
* fix(cli): emit ingest rate-limit countdowns from rejected signals
* fix(cli): report ai sdk rate-limit header utilization
* fix(cli): gate LLM rate-limit retries on the governor budget
The AI SDK and Codex runtimes retried 429 / opaque rate-limit failures up
to 6-7 times with no backoff when constructed without a RateLimitGovernor
(scan, memory, setup) or with pacing disabled, ignoring Retry-After and
worsening the limit. The outer retry loop only cooperates with the
governor's pause, so without active pacing there is no backoff to apply.
Route the retry bound through a single source: RateLimitGovernor
.maxRetryAttempts(), which returns retry.maxAttempts when enabled and 1
(no outer retry) when absent or disabled. All three runtimes (ai-sdk,
codex, claude-code) now use it, so ingest.rateLimit.retry.maxAttempts
genuinely controls attempts and the hard-coded 6 (plus Codex's off-by-one
extra attempt) is gone. Backend-native retry (e.g. the AI SDK's maxRetries)
still handles transient 429s.
Also correct the ktx.yaml docs for maxWaitMs (caps each wait, not the whole
run) and maxAttempts, and sync uv.lock ktx-sl/ktx-daemon to 0.9.0.
2026-06-05 12:10:27 +02:00
|
|
|
const result = await this.runWithRateLimitRetry(
|
|
|
|
|
input.abortSignal,
|
|
|
|
|
async () => {
|
|
|
|
|
const collected = await collectEvents(
|
|
|
|
|
await this.runner.runStreamed({
|
|
|
|
|
projectDir: this.deps.projectDir,
|
|
|
|
|
model,
|
|
|
|
|
prompt: promptWithSystem(input.system, input.prompt),
|
|
|
|
|
configOverrides: config.configOverrides,
|
|
|
|
|
env: config.env,
|
|
|
|
|
...(input.abortSignal ? { signal: input.abortSignal } : {}),
|
|
|
|
|
}),
|
|
|
|
|
);
|
|
|
|
|
const summary = summarizeCodexExecEvents(collected.events, { startedAt });
|
|
|
|
|
return { collected, summary };
|
|
|
|
|
},
|
|
|
|
|
({ collected, summary }) => summaryError(summary, collected.streamError),
|
feat: add codex llm backend for ktx runtime work (#253)
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
2026-06-02 13:57:11 +02:00
|
|
|
);
|
feat(cli): add ingest LLM rate-limit governor with paced retries (#261)
* feat(cli): add ingest rate limit governor
* feat(cli): wire ingest rate-limit config
* feat(cli): report provider rate-limit signals
* feat(cli): show ingest rate-limit waits
* fix(cli): complete rate-limit event coverage
* fix(cli): abort ingest provider calls cleanly
* fix(cli): propagate ingest cancellation
* fix(cli): reject pre-aborted ingest rate-limit waits
* fix(cli): honor Claude rate-limit reset waits
* fix(cli): retry thrown Codex rate-limit failures
* fix(cli): type Claude rate-limit result details
* fix(cli): emit ingest rate-limit countdowns from rejected signals
* fix(cli): report ai sdk rate-limit header utilization
* fix(cli): gate LLM rate-limit retries on the governor budget
The AI SDK and Codex runtimes retried 429 / opaque rate-limit failures up
to 6-7 times with no backoff when constructed without a RateLimitGovernor
(scan, memory, setup) or with pacing disabled, ignoring Retry-After and
worsening the limit. The outer retry loop only cooperates with the
governor's pause, so without active pacing there is no backoff to apply.
Route the retry bound through a single source: RateLimitGovernor
.maxRetryAttempts(), which returns retry.maxAttempts when enabled and 1
(no outer retry) when absent or disabled. All three runtimes (ai-sdk,
codex, claude-code) now use it, so ingest.rateLimit.retry.maxAttempts
genuinely controls attempts and the hard-coded 6 (plus Codex's off-by-one
extra attempt) is gone. Backend-native retry (e.g. the AI SDK's maxRetries)
still handles transient 429s.
Also correct the ktx.yaml docs for maxWaitMs (caps each wait, not the whole
run) and maxAttempts, and sync uv.lock ktx-sl/ktx-daemon to 0.9.0.
2026-06-05 12:10:27 +02:00
|
|
|
input.onMetrics?.(metrics(result.summary, startedAt));
|
|
|
|
|
return assertSuccessfulText(result.summary, result.collected.streamError);
|
feat: add codex llm backend for ktx runtime work (#253)
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
2026-06-02 13:57:11 +02:00
|
|
|
} finally {
|
|
|
|
|
await mcp?.close();
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
async generateObject<TOutput, TSchema extends z.ZodType<TOutput>>(
|
|
|
|
|
input: KtxGenerateObjectInput<TOutput, TSchema>,
|
|
|
|
|
): Promise<TOutput> {
|
|
|
|
|
const startedAt = Date.now();
|
|
|
|
|
const model = modelForRole(this.deps.modelSlots, input.role);
|
|
|
|
|
const mcp = await mcpForTools({
|
|
|
|
|
projectDir: this.deps.projectDir,
|
|
|
|
|
toolSet: input.tools,
|
|
|
|
|
startMcpServer: this.deps.startMcpServer,
|
|
|
|
|
});
|
|
|
|
|
try {
|
|
|
|
|
const config = buildCodexRuntimeConfig({
|
|
|
|
|
model,
|
|
|
|
|
...(mcp
|
|
|
|
|
? {
|
|
|
|
|
mcp: {
|
|
|
|
|
url: mcp.url,
|
|
|
|
|
bearerTokenEnvVar: mcp.bearerTokenEnvVar,
|
|
|
|
|
bearerToken: mcp.bearerToken,
|
|
|
|
|
toolNames: runtimeToolNames(input.tools),
|
|
|
|
|
},
|
|
|
|
|
}
|
|
|
|
|
: {}),
|
|
|
|
|
});
|
feat(cli): add ingest LLM rate-limit governor with paced retries (#261)
* feat(cli): add ingest rate limit governor
* feat(cli): wire ingest rate-limit config
* feat(cli): report provider rate-limit signals
* feat(cli): show ingest rate-limit waits
* fix(cli): complete rate-limit event coverage
* fix(cli): abort ingest provider calls cleanly
* fix(cli): propagate ingest cancellation
* fix(cli): reject pre-aborted ingest rate-limit waits
* fix(cli): honor Claude rate-limit reset waits
* fix(cli): retry thrown Codex rate-limit failures
* fix(cli): type Claude rate-limit result details
* fix(cli): emit ingest rate-limit countdowns from rejected signals
* fix(cli): report ai sdk rate-limit header utilization
* fix(cli): gate LLM rate-limit retries on the governor budget
The AI SDK and Codex runtimes retried 429 / opaque rate-limit failures up
to 6-7 times with no backoff when constructed without a RateLimitGovernor
(scan, memory, setup) or with pacing disabled, ignoring Retry-After and
worsening the limit. The outer retry loop only cooperates with the
governor's pause, so without active pacing there is no backoff to apply.
Route the retry bound through a single source: RateLimitGovernor
.maxRetryAttempts(), which returns retry.maxAttempts when enabled and 1
(no outer retry) when absent or disabled. All three runtimes (ai-sdk,
codex, claude-code) now use it, so ingest.rateLimit.retry.maxAttempts
genuinely controls attempts and the hard-coded 6 (plus Codex's off-by-one
extra attempt) is gone. Backend-native retry (e.g. the AI SDK's maxRetries)
still handles transient 429s.
Also correct the ktx.yaml docs for maxWaitMs (caps each wait, not the whole
run) and maxAttempts, and sync uv.lock ktx-sl/ktx-daemon to 0.9.0.
2026-06-05 12:10:27 +02:00
|
|
|
const result = await this.runWithRateLimitRetry(
|
|
|
|
|
input.abortSignal,
|
|
|
|
|
async () => {
|
|
|
|
|
const collected = await collectEvents(
|
|
|
|
|
await this.runner.runStreamed({
|
|
|
|
|
projectDir: this.deps.projectDir,
|
|
|
|
|
model,
|
|
|
|
|
prompt: promptWithSystem(input.system, input.prompt),
|
|
|
|
|
configOverrides: config.configOverrides,
|
|
|
|
|
env: config.env,
|
|
|
|
|
outputSchema: z.toJSONSchema(input.schema, { target: 'draft-7' }) as Record<string, unknown>,
|
|
|
|
|
...(input.abortSignal ? { signal: input.abortSignal } : {}),
|
|
|
|
|
}),
|
|
|
|
|
);
|
|
|
|
|
const summary = summarizeCodexExecEvents(collected.events, { startedAt });
|
|
|
|
|
return { collected, summary };
|
|
|
|
|
},
|
|
|
|
|
({ collected, summary }) => summaryError(summary, collected.streamError),
|
feat: add codex llm backend for ktx runtime work (#253)
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
2026-06-02 13:57:11 +02:00
|
|
|
);
|
feat(cli): add ingest LLM rate-limit governor with paced retries (#261)
* feat(cli): add ingest rate limit governor
* feat(cli): wire ingest rate-limit config
* feat(cli): report provider rate-limit signals
* feat(cli): show ingest rate-limit waits
* fix(cli): complete rate-limit event coverage
* fix(cli): abort ingest provider calls cleanly
* fix(cli): propagate ingest cancellation
* fix(cli): reject pre-aborted ingest rate-limit waits
* fix(cli): honor Claude rate-limit reset waits
* fix(cli): retry thrown Codex rate-limit failures
* fix(cli): type Claude rate-limit result details
* fix(cli): emit ingest rate-limit countdowns from rejected signals
* fix(cli): report ai sdk rate-limit header utilization
* fix(cli): gate LLM rate-limit retries on the governor budget
The AI SDK and Codex runtimes retried 429 / opaque rate-limit failures up
to 6-7 times with no backoff when constructed without a RateLimitGovernor
(scan, memory, setup) or with pacing disabled, ignoring Retry-After and
worsening the limit. The outer retry loop only cooperates with the
governor's pause, so without active pacing there is no backoff to apply.
Route the retry bound through a single source: RateLimitGovernor
.maxRetryAttempts(), which returns retry.maxAttempts when enabled and 1
(no outer retry) when absent or disabled. All three runtimes (ai-sdk,
codex, claude-code) now use it, so ingest.rateLimit.retry.maxAttempts
genuinely controls attempts and the hard-coded 6 (plus Codex's off-by-one
extra attempt) is gone. Backend-native retry (e.g. the AI SDK's maxRetries)
still handles transient 429s.
Also correct the ktx.yaml docs for maxWaitMs (caps each wait, not the whole
run) and maxAttempts, and sync uv.lock ktx-sl/ktx-daemon to 0.9.0.
2026-06-05 12:10:27 +02:00
|
|
|
input.onMetrics?.(metrics(result.summary, startedAt));
|
|
|
|
|
return parseStructuredOutput(input.schema, assertSuccessfulText(result.summary, result.collected.streamError));
|
feat: add codex llm backend for ktx runtime work (#253)
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
2026-06-02 13:57:11 +02:00
|
|
|
} finally {
|
|
|
|
|
await mcp?.close();
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
async runAgentLoop(params: RunLoopParams): Promise<RunLoopResult> {
|
|
|
|
|
const startedAt = Date.now();
|
|
|
|
|
const model = modelForRole(this.deps.modelSlots, params.modelRole);
|
|
|
|
|
let mcp: CodexRuntimeMcpServerHandle | undefined;
|
|
|
|
|
try {
|
|
|
|
|
mcp = await mcpForTools({
|
|
|
|
|
projectDir: this.deps.projectDir,
|
|
|
|
|
toolSet: params.toolSet,
|
|
|
|
|
startMcpServer: this.deps.startMcpServer,
|
|
|
|
|
});
|
|
|
|
|
const config = buildCodexRuntimeConfig({
|
|
|
|
|
model,
|
|
|
|
|
...(mcp
|
|
|
|
|
? {
|
|
|
|
|
mcp: {
|
|
|
|
|
url: mcp.url,
|
|
|
|
|
bearerTokenEnvVar: mcp.bearerTokenEnvVar,
|
|
|
|
|
bearerToken: mcp.bearerToken,
|
|
|
|
|
toolNames: runtimeToolNames(params.toolSet),
|
|
|
|
|
},
|
|
|
|
|
}
|
|
|
|
|
: {}),
|
|
|
|
|
});
|
|
|
|
|
const onStep = async (stepIndex: number): Promise<void> => {
|
|
|
|
|
try {
|
|
|
|
|
await params.onStepFinish?.({ stepIndex, stepBudget: params.stepBudget });
|
|
|
|
|
} catch (error) {
|
|
|
|
|
this.logger.warn(
|
|
|
|
|
`[codex-runner] onStepFinish callback threw; ignoring: ${error instanceof Error ? error.message : String(error)}`,
|
|
|
|
|
);
|
|
|
|
|
}
|
|
|
|
|
};
|
feat(cli): add ingest LLM rate-limit governor with paced retries (#261)
* feat(cli): add ingest rate limit governor
* feat(cli): wire ingest rate-limit config
* feat(cli): report provider rate-limit signals
* feat(cli): show ingest rate-limit waits
* fix(cli): complete rate-limit event coverage
* fix(cli): abort ingest provider calls cleanly
* fix(cli): propagate ingest cancellation
* fix(cli): reject pre-aborted ingest rate-limit waits
* fix(cli): honor Claude rate-limit reset waits
* fix(cli): retry thrown Codex rate-limit failures
* fix(cli): type Claude rate-limit result details
* fix(cli): emit ingest rate-limit countdowns from rejected signals
* fix(cli): report ai sdk rate-limit header utilization
* fix(cli): gate LLM rate-limit retries on the governor budget
The AI SDK and Codex runtimes retried 429 / opaque rate-limit failures up
to 6-7 times with no backoff when constructed without a RateLimitGovernor
(scan, memory, setup) or with pacing disabled, ignoring Retry-After and
worsening the limit. The outer retry loop only cooperates with the
governor's pause, so without active pacing there is no backoff to apply.
Route the retry bound through a single source: RateLimitGovernor
.maxRetryAttempts(), which returns retry.maxAttempts when enabled and 1
(no outer retry) when absent or disabled. All three runtimes (ai-sdk,
codex, claude-code) now use it, so ingest.rateLimit.retry.maxAttempts
genuinely controls attempts and the hard-coded 6 (plus Codex's off-by-one
extra attempt) is gone. Backend-native retry (e.g. the AI SDK's maxRetries)
still handles transient 429s.
Also correct the ktx.yaml docs for maxWaitMs (caps each wait, not the whole
run) and maxAttempts, and sync uv.lock ktx-sl/ktx-daemon to 0.9.0.
2026-06-05 12:10:27 +02:00
|
|
|
const result = await this.runWithRateLimitRetry(
|
|
|
|
|
params.abortSignal,
|
|
|
|
|
async () => {
|
|
|
|
|
const linked = linkAbortSignal(params.abortSignal);
|
|
|
|
|
const abortController = linked.controller;
|
|
|
|
|
try {
|
|
|
|
|
const collected = await collectEvents(
|
|
|
|
|
await this.runner.runStreamed({
|
|
|
|
|
projectDir: this.deps.projectDir,
|
|
|
|
|
model,
|
|
|
|
|
prompt: promptWithSystem(params.systemPrompt, params.userPrompt),
|
|
|
|
|
configOverrides: config.configOverrides,
|
|
|
|
|
env: config.env,
|
|
|
|
|
signal: abortController.signal,
|
|
|
|
|
}),
|
|
|
|
|
{ stepBudget: params.stepBudget, abortController, onStep },
|
|
|
|
|
);
|
|
|
|
|
const summary = summarizeCodexExecEvents(collected.events, { startedAt });
|
|
|
|
|
return { collected, summary };
|
|
|
|
|
} finally {
|
|
|
|
|
linked.dispose();
|
|
|
|
|
}
|
|
|
|
|
},
|
|
|
|
|
({ collected, summary }) => summaryError(summary, collected.streamError),
|
feat: add codex llm backend for ktx runtime work (#253)
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
2026-06-02 13:57:11 +02:00
|
|
|
);
|
feat(cli): add ingest LLM rate-limit governor with paced retries (#261)
* feat(cli): add ingest rate limit governor
* feat(cli): wire ingest rate-limit config
* feat(cli): report provider rate-limit signals
* feat(cli): show ingest rate-limit waits
* fix(cli): complete rate-limit event coverage
* fix(cli): abort ingest provider calls cleanly
* fix(cli): propagate ingest cancellation
* fix(cli): reject pre-aborted ingest rate-limit waits
* fix(cli): honor Claude rate-limit reset waits
* fix(cli): retry thrown Codex rate-limit failures
* fix(cli): type Claude rate-limit result details
* fix(cli): emit ingest rate-limit countdowns from rejected signals
* fix(cli): report ai sdk rate-limit header utilization
* fix(cli): gate LLM rate-limit retries on the governor budget
The AI SDK and Codex runtimes retried 429 / opaque rate-limit failures up
to 6-7 times with no backoff when constructed without a RateLimitGovernor
(scan, memory, setup) or with pacing disabled, ignoring Retry-After and
worsening the limit. The outer retry loop only cooperates with the
governor's pause, so without active pacing there is no backoff to apply.
Route the retry bound through a single source: RateLimitGovernor
.maxRetryAttempts(), which returns retry.maxAttempts when enabled and 1
(no outer retry) when absent or disabled. All three runtimes (ai-sdk,
codex, claude-code) now use it, so ingest.rateLimit.retry.maxAttempts
genuinely controls attempts and the hard-coded 6 (plus Codex's off-by-one
extra attempt) is gone. Backend-native retry (e.g. the AI SDK's maxRetries)
still handles transient 429s.
Also correct the ktx.yaml docs for maxWaitMs (caps each wait, not the whole
run) and maxAttempts, and sync uv.lock ktx-sl/ktx-daemon to 0.9.0.
2026-06-05 12:10:27 +02:00
|
|
|
const error = summaryError(result.summary, result.collected.streamError);
|
|
|
|
|
if (isAbortError(error)) {
|
|
|
|
|
throw error;
|
|
|
|
|
}
|
|
|
|
|
const stopReason = result.collected.budgetExceeded ? 'budget' : error ? 'error' : result.summary.stopReason;
|
feat: add codex llm backend for ktx runtime work (#253)
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
2026-06-02 13:57:11 +02:00
|
|
|
return {
|
|
|
|
|
stopReason,
|
|
|
|
|
...(stopReason === 'error' && error ? { error } : {}),
|
|
|
|
|
metrics: {
|
|
|
|
|
totalMs: Date.now() - startedAt,
|
feat(cli): add ingest LLM rate-limit governor with paced retries (#261)
* feat(cli): add ingest rate limit governor
* feat(cli): wire ingest rate-limit config
* feat(cli): report provider rate-limit signals
* feat(cli): show ingest rate-limit waits
* fix(cli): complete rate-limit event coverage
* fix(cli): abort ingest provider calls cleanly
* fix(cli): propagate ingest cancellation
* fix(cli): reject pre-aborted ingest rate-limit waits
* fix(cli): honor Claude rate-limit reset waits
* fix(cli): retry thrown Codex rate-limit failures
* fix(cli): type Claude rate-limit result details
* fix(cli): emit ingest rate-limit countdowns from rejected signals
* fix(cli): report ai sdk rate-limit header utilization
* fix(cli): gate LLM rate-limit retries on the governor budget
The AI SDK and Codex runtimes retried 429 / opaque rate-limit failures up
to 6-7 times with no backoff when constructed without a RateLimitGovernor
(scan, memory, setup) or with pacing disabled, ignoring Retry-After and
worsening the limit. The outer retry loop only cooperates with the
governor's pause, so without active pacing there is no backoff to apply.
Route the retry bound through a single source: RateLimitGovernor
.maxRetryAttempts(), which returns retry.maxAttempts when enabled and 1
(no outer retry) when absent or disabled. All three runtimes (ai-sdk,
codex, claude-code) now use it, so ingest.rateLimit.retry.maxAttempts
genuinely controls attempts and the hard-coded 6 (plus Codex's off-by-one
extra attempt) is gone. Backend-native retry (e.g. the AI SDK's maxRetries)
still handles transient 429s.
Also correct the ktx.yaml docs for maxWaitMs (caps each wait, not the whole
run) and maxAttempts, and sync uv.lock ktx-sl/ktx-daemon to 0.9.0.
2026-06-05 12:10:27 +02:00
|
|
|
usage: result.summary.usage,
|
|
|
|
|
stepCount: result.summary.stepCount,
|
|
|
|
|
stepBoundariesMs: result.summary.stepBoundariesMs,
|
feat: add codex llm backend for ktx runtime work (#253)
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
2026-06-02 13:57:11 +02:00
|
|
|
},
|
|
|
|
|
};
|
|
|
|
|
} catch (error) {
|
feat(cli): add ingest LLM rate-limit governor with paced retries (#261)
* feat(cli): add ingest rate limit governor
* feat(cli): wire ingest rate-limit config
* feat(cli): report provider rate-limit signals
* feat(cli): show ingest rate-limit waits
* fix(cli): complete rate-limit event coverage
* fix(cli): abort ingest provider calls cleanly
* fix(cli): propagate ingest cancellation
* fix(cli): reject pre-aborted ingest rate-limit waits
* fix(cli): honor Claude rate-limit reset waits
* fix(cli): retry thrown Codex rate-limit failures
* fix(cli): type Claude rate-limit result details
* fix(cli): emit ingest rate-limit countdowns from rejected signals
* fix(cli): report ai sdk rate-limit header utilization
* fix(cli): gate LLM rate-limit retries on the governor budget
The AI SDK and Codex runtimes retried 429 / opaque rate-limit failures up
to 6-7 times with no backoff when constructed without a RateLimitGovernor
(scan, memory, setup) or with pacing disabled, ignoring Retry-After and
worsening the limit. The outer retry loop only cooperates with the
governor's pause, so without active pacing there is no backoff to apply.
Route the retry bound through a single source: RateLimitGovernor
.maxRetryAttempts(), which returns retry.maxAttempts when enabled and 1
(no outer retry) when absent or disabled. All three runtimes (ai-sdk,
codex, claude-code) now use it, so ingest.rateLimit.retry.maxAttempts
genuinely controls attempts and the hard-coded 6 (plus Codex's off-by-one
extra attempt) is gone. Backend-native retry (e.g. the AI SDK's maxRetries)
still handles transient 429s.
Also correct the ktx.yaml docs for maxWaitMs (caps each wait, not the whole
run) and maxAttempts, and sync uv.lock ktx-sl/ktx-daemon to 0.9.0.
2026-06-05 12:10:27 +02:00
|
|
|
if (isAbortError(error)) {
|
|
|
|
|
throw error;
|
|
|
|
|
}
|
feat: add codex llm backend for ktx runtime work (#253)
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
2026-06-02 13:57:11 +02:00
|
|
|
const err = error instanceof Error ? error : new Error(String(error));
|
|
|
|
|
return {
|
|
|
|
|
stopReason: 'error',
|
|
|
|
|
error: err,
|
|
|
|
|
metrics: { totalMs: Date.now() - startedAt, usage: {}, stepCount: 0, stepBoundariesMs: [] },
|
|
|
|
|
};
|
|
|
|
|
} finally {
|
|
|
|
|
await mcp?.close();
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// A rejected model is not an auth failure: Codex authenticated, connected, and
|
|
|
|
|
// the API refused the model id. These markers come from the API error envelope
|
|
|
|
|
// (e.g. "model is not supported", "invalid_request_error").
|
|
|
|
|
const MODEL_UNAVAILABLE_MARKERS =
|
|
|
|
|
/\bnot supported\b|\bnot available\b|\bdoes not exist\b|invalid_request_error|\bunknown model\b|\bunsupported model\b/i;
|
|
|
|
|
|
|
|
|
|
function describeCodexProbeFailure(model: string, message: string): { message: string; fix: string } {
|
|
|
|
|
if (MODEL_UNAVAILABLE_MARKERS.test(message)) {
|
|
|
|
|
const fix = `Run \`codex\` to see the models your account supports, then set llm.models.default in ktx.yaml (or rerun \`ktx setup\`).`;
|
|
|
|
|
return {
|
|
|
|
|
message: `Codex is authenticated, but the configured model "${model}" is not available for this Codex account. ${fix} Details: ${message}`,
|
|
|
|
|
fix,
|
|
|
|
|
};
|
|
|
|
|
}
|
|
|
|
|
const fix = `Authenticate Codex locally with the Codex CLI, verify the Codex CLI is installed, then rerun setup or \`ktx status\`.`;
|
|
|
|
|
return {
|
|
|
|
|
message: `Codex authentication is not usable. ${fix} Details: ${message}`,
|
|
|
|
|
fix,
|
|
|
|
|
};
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
export async function runCodexAuthProbe(input: {
|
|
|
|
|
projectDir: string;
|
|
|
|
|
model: string;
|
|
|
|
|
runner?: CodexSdkRunner;
|
|
|
|
|
}): Promise<{ ok: true } | { ok: false; message: string; fix: string }> {
|
|
|
|
|
let model: string;
|
|
|
|
|
try {
|
|
|
|
|
model = resolveCodexModel(input.model);
|
|
|
|
|
} catch (error) {
|
|
|
|
|
return {
|
|
|
|
|
ok: false,
|
|
|
|
|
message: error instanceof Error ? error.message : String(error),
|
|
|
|
|
fix: 'Set llm.models.default in ktx.yaml to a supported codex model (codex, default, or a gpt-* / codex-* id), or rerun `ktx setup`.',
|
|
|
|
|
};
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
const runtime = new CodexKtxLlmRuntime({
|
|
|
|
|
projectDir: input.projectDir,
|
|
|
|
|
modelSlots: { default: model },
|
|
|
|
|
...(input.runner ? { runner: input.runner } : {}),
|
|
|
|
|
});
|
|
|
|
|
try {
|
|
|
|
|
await runtime.generateText({ role: 'default', prompt: 'Reply with exactly: ok' });
|
|
|
|
|
return { ok: true };
|
|
|
|
|
} catch (error) {
|
|
|
|
|
const message = error instanceof Error ? error.message : String(error);
|
|
|
|
|
return { ok: false, ...describeCodexProbeFailure(model, message) };
|
|
|
|
|
}
|
|
|
|
|
}
|