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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
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@ -66,6 +66,7 @@ function makePromptAdapter(options: {
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nextProviderChoice === 'anthropic' ||
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nextProviderChoice === 'vertex' ||
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nextProviderChoice === 'claude-code' ||
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nextProviderChoice === 'codex' ||
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nextProviderChoice === 'back'
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) {
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return selectValues.shift() ?? nextProviderChoice;
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@ -183,6 +184,7 @@ describe('setup Anthropic model step', () => {
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message: expect.stringContaining('Which LLM provider should KTX use?'),
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options: [
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{ value: 'claude-code', label: 'Claude subscription (Pro/Max)' },
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{ value: 'codex', label: 'Codex subscription' },
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{ value: 'anthropic', label: 'Anthropic API key' },
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{ value: 'vertex', label: 'Google Vertex AI for Anthropic Claude' },
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{ value: 'back', label: 'Back' },
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@ -215,6 +217,85 @@ describe('setup Anthropic model step', () => {
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expect(authProbe).toHaveBeenCalledWith(expect.objectContaining({ projectDir: tempDir, model: 'sonnet' }));
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});
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it('configures Codex backend and validates local auth', async () => {
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const io = makeIo();
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const codexAuthProbe = vi.fn(async () => ({ ok: true as const }));
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const result = await runKtxSetupAnthropicModelStep(
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{
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projectDir: tempDir,
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inputMode: 'disabled',
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llmBackend: 'codex',
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llmModel: 'gpt-5.5',
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skipLlm: false,
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},
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io.io,
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{ codexAuthProbe },
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);
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expect(result.status).toBe('ready');
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const config = parseKtxProjectConfig(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8'));
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expect(config.llm).toMatchObject({
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provider: { backend: 'codex' },
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models: { default: 'gpt-5.5' },
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});
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expect(codexAuthProbe).toHaveBeenCalledWith(expect.objectContaining({ projectDir: tempDir, model: 'gpt-5.5' }));
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// The warning carries the clack gutter so it renders inside the setup frame.
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expect(io.stderr()).toContain('│ Codex backend isolation is limited');
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expect(io.stderr()).toContain('may still load user Codex config');
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});
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it('defaults the Codex model to gpt-5.5 when none is provided non-interactively', async () => {
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const io = makeIo();
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const codexAuthProbe = vi.fn(async () => ({ ok: true as const }));
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const result = await runKtxSetupAnthropicModelStep(
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{
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projectDir: tempDir,
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inputMode: 'disabled',
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llmBackend: 'codex',
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skipLlm: false,
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},
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io.io,
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{ codexAuthProbe },
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);
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expect(result.status).toBe('ready');
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const config = parseKtxProjectConfig(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8'));
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expect(config.llm).toMatchObject({
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provider: { backend: 'codex' },
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models: { default: 'gpt-5.5' },
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});
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expect(codexAuthProbe).toHaveBeenCalledWith(expect.objectContaining({ projectDir: tempDir, model: 'gpt-5.5' }));
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});
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it('offers the curated Codex models during interactive setup', async () => {
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const io = makeIo();
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const prompts = makePromptAdapter({ selectValues: ['codex', 'gpt-5.5'] });
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const codexAuthProbe = vi.fn(async () => ({ ok: true as const }));
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const result = await runKtxSetupAnthropicModelStep(
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{ projectDir: tempDir, inputMode: 'auto', skipLlm: false },
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io.io,
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{ prompts, codexAuthProbe },
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);
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expect(result.status).toBe('ready');
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expect(prompts.select).toHaveBeenCalledWith(
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expect.objectContaining({
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message: expect.stringContaining('Which Codex model should KTX use?'),
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options: [
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{ value: 'gpt-5.5', label: 'GPT-5.5', hint: 'recommended' },
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{ value: 'gpt-5.4', label: 'GPT-5.4' },
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{ value: 'gpt-5.4-mini', label: 'GPT-5.4 mini' },
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{ value: 'manual', label: 'Enter a Codex model ID manually' },
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{ value: 'back', label: 'Back' },
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],
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}),
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);
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expect(codexAuthProbe).toHaveBeenCalledWith(expect.objectContaining({ model: 'gpt-5.5' }));
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});
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it('prompts for the Claude Code model during interactive setup', async () => {
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const io = makeIo();
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const prompts = makePromptAdapter({ selectValues: ['claude-code', 'opus'] });
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