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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.
This commit is contained in:
Andrey Avtomonov
GitHub
parent
74c6076b72
commit
494618ab14
41 changed files with 2544 additions and 30 deletions
460
packages/cli/test/context/llm/codex-runtime.test.ts
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460
packages/cli/test/context/llm/codex-runtime.test.ts
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@ -0,0 +1,460 @@
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import { describe, expect, it, vi } from 'vitest';
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import { z } from 'zod';
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import {
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CodexKtxLlmRuntime,
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runCodexAuthProbe,
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} from '../../../src/context/llm/codex-runtime.js';
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async function* events(items: unknown[]) {
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for (const item of items) {
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yield item;
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}
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}
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function runner(items: unknown[]) {
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return {
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runStreamed: vi.fn(async () => events(items)),
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};
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}
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/** Yields the given events, then throws — mirroring the SDK throwing on a non-zero codex exec exit. */
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function throwingRunner(items: unknown[], error: Error) {
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return {
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runStreamed: vi.fn(async () =>
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(async function* () {
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for (const item of items) {
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yield item;
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}
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throw error;
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})(),
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),
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};
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}
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const MODEL_UNSUPPORTED_API_ERROR = JSON.stringify({
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type: 'error',
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status: 400,
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error: {
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type: 'invalid_request_error',
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message: "The 'gpt-5.3-codex' model is not supported when using Codex with a ChatGPT account.",
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},
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});
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function budgetRunner() {
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let observedSignal: AbortSignal | undefined;
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return {
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observedSignal: () => observedSignal,
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runStreamed: vi.fn(async (input: { signal?: AbortSignal }) => {
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observedSignal = input.signal;
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return events([
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{ type: 'turn.started' },
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{ type: 'item.started', item: { type: 'mcp_tool_call', server: 'ktx', tool: 'first', status: 'in_progress' } },
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{ type: 'item.completed', item: { type: 'mcp_tool_call', server: 'ktx', tool: 'first', status: 'completed' } },
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{ type: 'item.started', item: { type: 'mcp_tool_call', server: 'ktx', tool: 'second', status: 'in_progress' } },
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{ type: 'item.completed', item: { type: 'mcp_tool_call', server: 'ktx', tool: 'second', status: 'completed' } },
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{ type: 'turn.completed', usage: { input_tokens: 1, output_tokens: 1 } },
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]);
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}),
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};
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}
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describe('CodexKtxLlmRuntime', () => {
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it('generates text with the role-selected model and metrics', async () => {
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const onMetrics = vi.fn();
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const fakeRunner = runner([
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{ type: 'turn.started' },
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{ type: 'item.completed', item: { type: 'agent_message', text: 'hello' } },
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{ type: 'turn.completed', usage: { input_tokens: 3, output_tokens: 4, total_tokens: 7 } },
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]);
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const runtime = new CodexKtxLlmRuntime({
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projectDir: '/tmp/project',
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modelSlots: { default: 'codex', triage: 'gpt-5.4' },
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runner: fakeRunner,
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});
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await expect(runtime.generateText({ role: 'triage', system: 'system', prompt: 'prompt', onMetrics })).resolves.toBe('hello');
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expect(fakeRunner.runStreamed).toHaveBeenCalledWith(
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expect.objectContaining({
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projectDir: '/tmp/project',
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model: 'gpt-5.4',
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prompt: 'system\n\nprompt',
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}),
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);
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expect(onMetrics).toHaveBeenCalledWith(expect.objectContaining({ usage: { inputTokens: 3, outputTokens: 4, totalTokens: 7 } }));
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});
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it('generates and validates structured output', async () => {
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const fakeRunner = runner([
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{ type: 'turn.started' },
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{ type: 'item.completed', item: { type: 'agent_message', text: '{"answer":"yes"}' } },
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{ type: 'turn.completed' },
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]);
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const runtime = new CodexKtxLlmRuntime({
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projectDir: '/tmp/project',
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modelSlots: { default: 'codex' },
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runner: fakeRunner,
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});
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await expect(
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runtime.generateObject({
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role: 'default',
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prompt: 'json',
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schema: z.object({ answer: z.string() }),
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}),
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).resolves.toEqual({ answer: 'yes' });
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expect(fakeRunner.runStreamed).toHaveBeenCalledWith(
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expect.objectContaining({
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outputSchema: expect.objectContaining({ type: 'object' }),
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}),
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);
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});
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it('returns a structured-output error when Codex final text is invalid JSON', async () => {
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const fakeRunner = runner([
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{ type: 'turn.started' },
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{ type: 'item.completed', item: { type: 'agent_message', text: 'not json' } },
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{ type: 'turn.completed' },
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]);
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const runtime = new CodexKtxLlmRuntime({
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projectDir: '/tmp/project',
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modelSlots: { default: 'codex' },
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runner: fakeRunner,
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});
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await expect(
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runtime.generateObject({
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role: 'default',
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prompt: 'json',
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schema: z.object({ answer: z.string() }),
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}),
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).rejects.toThrow('Codex structured output failed validation');
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});
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it('starts and closes a temporary MCP server for tool-backed agent loops', async () => {
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const close = vi.fn(async () => undefined);
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const startMcpServer = vi.fn(async () => ({
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url: 'http://127.0.0.1:4321/mcp',
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bearerTokenEnvVar: 'KTX_CODEX_RUNTIME_MCP_TOKEN' as const,
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bearerToken: 'token',
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close,
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}));
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const fakeRunner = runner([
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{ type: 'turn.started' },
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{ type: 'item.started', item: { type: 'mcp_tool_call', name: 'wiki_search' } },
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{ type: 'item.completed', item: { type: 'agent_message', text: 'done' } },
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{ type: 'turn.completed', usage: { input_tokens: 1, output_tokens: 1, total_tokens: 2 } },
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]);
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const runtime = new CodexKtxLlmRuntime({
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projectDir: '/tmp/project',
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modelSlots: { default: 'codex' },
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runner: fakeRunner,
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startMcpServer,
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});
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const onStepFinish = vi.fn();
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const result = await runtime.runAgentLoop({
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modelRole: 'default',
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systemPrompt: 'system',
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userPrompt: 'user',
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stepBudget: 5,
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telemetryTags: {},
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onStepFinish,
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toolSet: {
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aliased_wiki_tool: {
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name: 'wiki_search',
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description: 'Search wiki',
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inputSchema: z.object({ query: z.string() }),
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execute: vi.fn(),
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},
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},
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});
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expect(result.stopReason).toBe('natural');
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expect(result.metrics).toMatchObject({ stepCount: 1, usage: { inputTokens: 1, outputTokens: 1, totalTokens: 2 } });
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expect(onStepFinish).toHaveBeenCalledWith({ stepIndex: 1, stepBudget: 5 });
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expect(startMcpServer).toHaveBeenCalledWith({ projectDir: '/tmp/project', toolSet: expect.any(Object) });
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expect(fakeRunner.runStreamed).toHaveBeenCalledWith(
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expect.objectContaining({
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env: { KTX_CODEX_RUNTIME_MCP_TOKEN: 'token' },
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configOverrides: expect.objectContaining({
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mcp_servers: expect.objectContaining({
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ktx: expect.objectContaining({
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url: 'http://127.0.0.1:4321/mcp',
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enabled_tools: ['wiki_search'],
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required: true,
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}),
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}),
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}),
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}),
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);
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expect(close).toHaveBeenCalled();
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});
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it('returns error stop reason on turn failure', async () => {
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const runtime = new CodexKtxLlmRuntime({
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projectDir: '/tmp/project',
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modelSlots: { default: 'codex' },
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runner: runner([{ type: 'turn.failed', error: { message: 'boom' } }]),
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});
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const result = await runtime.runAgentLoop({
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modelRole: 'default',
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systemPrompt: 'system',
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userPrompt: 'user',
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stepBudget: 5,
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telemetryTags: {},
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toolSet: {},
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});
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expect(result.stopReason).toBe('error');
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expect(result.error?.message).toBe('boom');
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});
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it('surfaces failed MCP tool calls as agent-loop errors', async () => {
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const runtime = new CodexKtxLlmRuntime({
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projectDir: '/tmp/project',
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modelSlots: { default: 'codex' },
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runner: runner([
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{ type: 'turn.started' },
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{ type: 'item.started', item: { type: 'mcp_tool_call', server: 'ktx', tool: 'search', status: 'in_progress' } },
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{
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type: 'item.completed',
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item: {
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type: 'mcp_tool_call',
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server: 'ktx',
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tool: 'search',
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status: 'failed',
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error: { message: 'denied' },
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},
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},
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{ type: 'turn.completed', usage: { input_tokens: 1, output_tokens: 1 } },
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]),
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});
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const result = await runtime.runAgentLoop({
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modelRole: 'default',
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systemPrompt: 'system',
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userPrompt: 'user',
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stepBudget: 5,
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telemetryTags: {},
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toolSet: {},
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});
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expect(result.stopReason).toBe('error');
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expect(result.error?.message).toBe('Codex runtime tool call failed: search: denied');
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expect(result.metrics).toMatchObject({
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stepCount: 1,
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usage: { inputTokens: 1, outputTokens: 1, totalTokens: 2 },
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});
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});
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it('returns budget and aborts the Codex stream when local MCP step budget is reached', async () => {
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const fakeRunner = budgetRunner();
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const runtime = new CodexKtxLlmRuntime({
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projectDir: '/tmp/project',
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modelSlots: { default: 'codex' },
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runner: fakeRunner,
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});
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const onStepFinish = vi.fn();
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const result = await runtime.runAgentLoop({
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modelRole: 'default',
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systemPrompt: 'system',
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userPrompt: 'user',
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stepBudget: 1,
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telemetryTags: {},
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onStepFinish,
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toolSet: {
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first: {
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name: 'first',
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description: 'First tool',
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inputSchema: z.object({}),
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execute: vi.fn(),
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},
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},
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});
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expect(result.stopReason).toBe('budget');
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expect(result.error).toBeUndefined();
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expect(result.metrics).toMatchObject({ stepCount: 1 });
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expect(onStepFinish).toHaveBeenCalledTimes(1);
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expect(onStepFinish).toHaveBeenCalledWith({ stepIndex: 1, stepBudget: 1 });
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expect(fakeRunner.observedSignal()?.aborted).toBe(true);
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});
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it('counts built-in command_execution steps against the budget and aborts the stream', async () => {
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let observedSignal: AbortSignal | undefined;
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const fakeRunner = {
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observedSignal: () => observedSignal,
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runStreamed: vi.fn(async (input: { signal?: AbortSignal }) => {
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observedSignal = input.signal;
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return events([
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{ type: 'turn.started' },
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{ type: 'item.started', item: { type: 'command_execution', command: 'ls', status: 'in_progress' } },
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{ type: 'item.completed', item: { type: 'command_execution', command: 'ls', status: 'completed', exit_code: 0 } },
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{ type: 'item.started', item: { type: 'command_execution', command: 'cat a', status: 'in_progress' } },
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{ type: 'item.completed', item: { type: 'command_execution', command: 'cat a', status: 'completed', exit_code: 0 } },
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{ type: 'item.completed', item: { type: 'command_execution', command: 'cat b', status: 'completed', exit_code: 0 } },
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{ type: 'turn.completed', usage: { input_tokens: 1, output_tokens: 1 } },
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]);
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}),
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};
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const runtime = new CodexKtxLlmRuntime({
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projectDir: '/tmp/project',
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modelSlots: { default: 'codex' },
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runner: fakeRunner,
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});
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const onStepFinish = vi.fn();
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const result = await runtime.runAgentLoop({
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modelRole: 'default',
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systemPrompt: 'system',
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userPrompt: 'user',
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stepBudget: 2,
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telemetryTags: {},
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onStepFinish,
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toolSet: {},
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});
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expect(result.stopReason).toBe('budget');
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expect(result.error).toBeUndefined();
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expect(result.metrics).toMatchObject({ stepCount: 2 });
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expect(onStepFinish).toHaveBeenCalledTimes(2);
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expect(onStepFinish).toHaveBeenLastCalledWith({ stepIndex: 2, stepBudget: 2 });
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expect(fakeRunner.observedSignal()?.aborted).toBe(true);
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});
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it('fires onStepFinish live as each step completes, before the stream drains', async () => {
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const order: string[] = [];
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async function* liveEvents() {
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yield { type: 'turn.started' };
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yield { type: 'item.completed', item: { type: 'mcp_tool_call', server: 'ktx', tool: 'a', status: 'completed' } };
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order.push('yielded-after-step-1');
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yield { type: 'item.completed', item: { type: 'mcp_tool_call', server: 'ktx', tool: 'b', status: 'completed' } };
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order.push('yielded-after-step-2');
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yield { type: 'item.completed', item: { type: 'agent_message', text: 'done' } };
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yield { type: 'turn.completed', usage: { input_tokens: 1, output_tokens: 1 } };
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}
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const fakeRunner = { runStreamed: vi.fn(async () => liveEvents()) };
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const runtime = new CodexKtxLlmRuntime({
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projectDir: '/tmp/project',
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modelSlots: { default: 'codex' },
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runner: fakeRunner,
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});
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const result = await runtime.runAgentLoop({
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modelRole: 'default',
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systemPrompt: 'system',
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userPrompt: 'user',
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stepBudget: 10,
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telemetryTags: {},
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onStepFinish: ({ stepIndex }) => {
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order.push(`step-${stepIndex}`);
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},
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toolSet: {},
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});
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expect(result.stopReason).toBe('natural');
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expect(result.metrics).toMatchObject({ stepCount: 2 });
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expect(order).toEqual(['step-1', 'yielded-after-step-1', 'step-2', 'yielded-after-step-2']);
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});
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it('surfaces the real Codex error event even when the SDK stream throws afterward', async () => {
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// The SDK yields the error/turn.failed events on stdout, then throws on the
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// non-zero exit. The masked exit message must not hide the real API error.
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const fakeRunner = throwingRunner(
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[
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{ type: 'thread.started', thread_id: 't' },
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{ type: 'turn.started' },
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{ type: 'error', message: MODEL_UNSUPPORTED_API_ERROR },
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{ type: 'turn.failed', error: { message: MODEL_UNSUPPORTED_API_ERROR } },
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],
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new Error('Codex Exec exited with code 1: Reading prompt from stdin...'),
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);
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const runtime = new CodexKtxLlmRuntime({
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projectDir: '/tmp/project',
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modelSlots: { default: 'codex' },
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runner: fakeRunner,
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});
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await expect(runtime.generateText({ role: 'default', prompt: 'hi' })).rejects.toThrow(
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'not supported when using Codex with a ChatGPT account',
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);
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||||
});
|
||||
|
||||
it('probes Codex authentication through a minimal non-interactive turn', async () => {
|
||||
const fakeRunner = runner([
|
||||
{ type: 'turn.started' },
|
||||
{ type: 'item.completed', item: { type: 'agent_message', text: 'ok' } },
|
||||
{ type: 'turn.completed' },
|
||||
]);
|
||||
|
||||
await expect(
|
||||
runCodexAuthProbe({
|
||||
projectDir: '/tmp/project',
|
||||
model: 'codex',
|
||||
runner: fakeRunner,
|
||||
}),
|
||||
).resolves.toEqual({ ok: true });
|
||||
});
|
||||
|
||||
it('reports an unavailable model without blaming auth when Codex rejects the model', async () => {
|
||||
const fakeRunner = throwingRunner(
|
||||
[
|
||||
{ type: 'turn.started' },
|
||||
{ type: 'turn.failed', error: { message: MODEL_UNSUPPORTED_API_ERROR } },
|
||||
],
|
||||
new Error('Codex Exec exited with code 1: Reading prompt from stdin...'),
|
||||
);
|
||||
|
||||
const result = await runCodexAuthProbe({
|
||||
projectDir: '/tmp/project',
|
||||
model: 'gpt-5.3-codex',
|
||||
runner: fakeRunner,
|
||||
});
|
||||
|
||||
expect(result.ok).toBe(false);
|
||||
if (!result.ok) {
|
||||
expect(result.message).not.toContain('authentication is not usable');
|
||||
expect(result.message).toContain('not available');
|
||||
expect(result.message).toContain('gpt-5.3-codex');
|
||||
expect(result.message).toContain('not supported when using Codex with a ChatGPT account');
|
||||
// A model-access failure must steer the user at the model config, not auth.
|
||||
expect(result.fix).toContain('llm.models.default');
|
||||
expect(result.fix).not.toContain('Authenticate Codex');
|
||||
}
|
||||
});
|
||||
|
||||
it('reports an auth failure when Codex exits without an error event', async () => {
|
||||
const fakeRunner = throwingRunner(
|
||||
[],
|
||||
new Error('Codex Exec exited with code 1: Not logged in. Run `codex login`.'),
|
||||
);
|
||||
|
||||
const result = await runCodexAuthProbe({
|
||||
projectDir: '/tmp/project',
|
||||
model: 'gpt-5.5',
|
||||
runner: fakeRunner,
|
||||
});
|
||||
|
||||
expect(result.ok).toBe(false);
|
||||
if (!result.ok) {
|
||||
expect(result.message).toContain('authentication is not usable');
|
||||
expect(result.message).toContain('Not logged in');
|
||||
expect(result.fix).toContain('Authenticate Codex');
|
||||
}
|
||||
});
|
||||
|
||||
it('rejects an unsupported model id before probing, steering at llm.models.default', async () => {
|
||||
const result = await runCodexAuthProbe({
|
||||
projectDir: '/tmp/project',
|
||||
model: 'not-a-real-model',
|
||||
});
|
||||
|
||||
expect(result.ok).toBe(false);
|
||||
if (!result.ok) {
|
||||
expect(result.message).toContain('Unsupported Codex model');
|
||||
expect(result.fix).toContain('llm.models.default');
|
||||
}
|
||||
});
|
||||
});
|
||||
Loading…
Add table
Add a link
Reference in a new issue