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feat(setup): apply per-role LLM model presets, remove --llm-model (#268)
* feat(setup): write per-role llm model presets * feat(setup): remove llm model setup flag * chore(setup): update llm preset guidance * docs(setup): document llm model presets * chore(release): sync uv.lock to 0.9.0 * fix(cli): make sl query --execute work on secret-backed connections sl query --execute used a parallel SQL executor (createDefaultLocalQueryExecutor) that passed connection.url verbatim into pg, so file:/env: secret references failed with "SASL: SCRAM-SERVER-FIRST-MESSAGE: client password must be a string". Collapse onto the connector-based executor already used by MCP and ingest (createKtxCliIngestQueryExecutor), which resolves secret references and supports every driver. Delete the now-dead local/postgres/sqlite query executors, their tests, and the orphaned hasLocalQueryExecutor driver flag. * docs(agents): require one implementation per capability Add a design-reasoning default and a matching self-check question telling agents to route callers through a single shared implementation of a capability rather than forking a parallel one, and to fix the shared layer rather than patch one branch. Encodes the lesson from a divergent SQL-execution-path bug, stated generally. CLAUDE.md is a symlink to AGENTS.md, so both agent-instruction files are covered.
This commit is contained in:
Andrey Avtomonov
GitHub
parent
2896f9fb91
commit
2c18a62de4
25 changed files with 404 additions and 1384 deletions
17
AGENTS.md
17
AGENTS.md
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@ -192,6 +192,19 @@ autonomously — without being asked the leading question — is the bar.
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next stack. The only acceptable static patterns are genuinely universal
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invariants (e.g. DB-engine system catalogs) and ktx's own self-emitted
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signatures.
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- **MUST**: Give each capability one implementation and route every caller
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through it. When some behavior — running a query, resolving a credential or
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config reference, authenticating, selecting a dialect, loading config —
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already has a working implementation that some call sites use, make new or
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divergent call sites depend on that path instead of standing up a second one.
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Parallel implementations of one capability drift apart silently: a fix, a
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newly supported input, or an added case lands on one path and not the other,
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so one entry point (a CLI command, an MCP tool, an ingest stage) succeeds
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while another fails on the same input. When two paths already do the same
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job, collapse onto the shared one and delete the duplicate instead of
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keeping both. When fixing a defect that lives on one path, fix the shared
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implementation; do not patch the symptom on a forked branch, which preserves
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the divergence you set out to remove.
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- **SHOULD**: Before inventing an abstraction or hand-rolling structural logic,
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search for what already exists and reuse it — the codebase's canonical
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representation (a structured ref/key type) instead of a parallel string scheme,
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@ -212,6 +225,10 @@ Before presenting a design, answer these explicitly:
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instead of building or parsing my own?
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5. Am I discarding the better option on a weak or misapplied constraint
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(one-time vs recurring cost, "more surface area", "more work now")?
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6. Does another entry point already perform this operation through a shared
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implementation? If so, am I routing through that path instead of forking a
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parallel one — and if I'm fixing a bug, am I fixing the shared layer rather
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than one branch?
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A user question that nudges toward an alternative ("would X help?", "should I
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always do Y?", "will you hardcode Z?") is a signal that a better option exists.
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@ -54,7 +54,6 @@ prompts.
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| `--llm-backend <backend>` | LLM backend: `anthropic`, `vertex`, `claude-code`, or `codex` |
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| `--llm-backend claude-code` | Use the local Claude Code session for **ktx** LLM calls |
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| `--llm-backend codex` | Use local Codex authentication for **ktx** LLM calls |
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| `--llm-model <model>` | LLM model ID or backend model alias to validate and save |
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| `--anthropic-api-key-env <name>` | Environment variable containing the Anthropic API key |
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| `--anthropic-api-key-file <path>` | File containing the Anthropic API key |
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| `--vertex-project <project>` | Vertex AI project ID, `env:NAME`, or `file:/path` reference |
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@ -64,13 +63,9 @@ prompts.
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Choose only one Anthropic credential source. Anthropic credential flags are only
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valid with the Anthropic backend; Vertex flags are only valid with the Vertex
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backend. The `claude-code` and `codex` backends use local authentication instead
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of Anthropic API key or Vertex flags. For Claude Code, `--llm-model` accepts
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`sonnet`, `opus`, `haiku`, or a full Claude model ID. For Codex, `--llm-model`
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accepts `codex`, `default`, or a `gpt-*` / `codex-*` model ID such as
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`gpt-5.5`; any other value is rejected before the auth probe. Run `codex` to
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see the models available to your login, and pick a `gpt-*` / `codex-*` id from
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that list. Note that `*-codex` API-billing model IDs (for example
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`gpt-5.3-codex`) are not available to ChatGPT-subscription logins.
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of Anthropic API key or Vertex flags. After you choose a backend, `ktx setup`
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writes that backend's per-role model preset to `ktx.yaml`. To change a model,
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edit the matching `llm.models.<role>` value in `ktx.yaml`.
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### Embeddings
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@ -198,14 +193,13 @@ ktx setup
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# Run setup for a specific project directory
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ktx setup --project-dir ./analytics
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# Use Claude Code with Opus for ktx LLM calls
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# Use Claude Code for ktx LLM calls
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ktx setup \
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--project-dir ./analytics \
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--llm-backend claude-code \
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--llm-model opus
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--llm-backend claude-code
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# Configure **ktx** to use local Codex authentication for LLM work
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ktx setup --llm-backend codex --llm-model gpt-5.5 --no-input
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ktx setup --llm-backend codex --no-input
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```
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When you choose `--llm-backend codex`, setup prints a warning if the public
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@ -377,6 +377,10 @@ llm:
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models:
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default: claude-sonnet-4-6
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triage: claude-haiku-4-5
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candidateExtraction: claude-sonnet-4-6
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curator: claude-opus-4-7
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reconcile: claude-opus-4-7
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repair: claude-haiku-4-5
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promptCaching:
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enabled: true
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systemTtl: 1h
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@ -404,6 +408,11 @@ llm:
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backend: codex
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models:
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default: gpt-5.5
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triage: gpt-5.5
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candidateExtraction: gpt-5.5
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curator: gpt-5.5
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reconcile: gpt-5.5
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repair: gpt-5.5
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```
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### Model roles
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@ -643,6 +652,11 @@ llm:
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backend: claude-code
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models:
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default: sonnet
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triage: haiku
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candidateExtraction: sonnet
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curator: opus
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reconcile: opus
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repair: haiku
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ingest:
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adapters:
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- live-database
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@ -43,7 +43,7 @@ Local-auth backends keep provider credentials out of `ktx.yaml`:
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```bash
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ktx setup --llm-backend claude-code --no-input
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ktx setup --llm-backend codex --llm-model gpt-5.5 --no-input
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ktx setup --llm-backend codex --no-input
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```
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With `claude-code`, **ktx** agent loops can invoke only the **ktx** MCP tools
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@ -30,19 +30,19 @@ llm:
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default: sonnet
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triage: haiku
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candidateExtraction: sonnet
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curator: sonnet
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reconcile: sonnet
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repair: sonnet
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curator: opus
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reconcile: opus
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repair: haiku
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```
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During setup, choose the backend interactively or pass the model in automation:
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During setup, choose the backend interactively or pass it in automation:
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```bash
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ktx setup --llm-backend claude-code --llm-model opus --no-input
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ktx setup --llm-backend claude-code --no-input
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```
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For Claude Code, `sonnet`, `opus`, and `haiku` map to **ktx** defaults. Full Claude
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model IDs are also accepted.
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Setup writes `sonnet`, `haiku`, and `opus` aliases into `llm.models`. You can
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edit any role to another alias or a full Claude model ID after setup.
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`claude-code` exposes only **ktx** MCP tools for the current agent loop. SDK init
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metadata may still list host slash commands, skills, and subagents; **ktx** does not
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@ -59,12 +59,17 @@ llm:
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backend: codex
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models:
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default: gpt-5.5
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triage: gpt-5.5
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candidateExtraction: gpt-5.5
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curator: gpt-5.5
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reconcile: gpt-5.5
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repair: gpt-5.5
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```
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Configure it non-interactively:
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```bash
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ktx setup --llm-backend codex --llm-model gpt-5.5 --no-input
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ktx setup --llm-backend codex --no-input
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```
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This is separate from Codex agent-client setup. `ktx setup --agents --target
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@ -95,7 +95,6 @@ function shouldShowSetupEntryMenu(
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llmBackend?: KtxSetupLlmBackend;
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anthropicApiKeyEnv?: string;
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anthropicApiKeyFile?: string;
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llmModel?: string;
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vertexProject?: string;
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vertexLocation?: string;
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skipLlm?: boolean;
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@ -166,7 +165,6 @@ function shouldShowSetupEntryMenu(
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'llmBackend',
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'anthropicApiKeyEnv',
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'anthropicApiKeyFile',
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'llmModel',
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'vertexProject',
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'vertexLocation',
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'skipLlm',
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@ -229,7 +227,6 @@ export function registerSetupCommands(program: Command, context: KtxCliCommandCo
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.addOption(
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new Option('--anthropic-api-key-file <path>', 'File containing the Anthropic API key').hideHelp(),
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)
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.addOption(new Option('--llm-model <model>', 'LLM model ID or backend model alias').hideHelp())
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.addOption(new Option('--vertex-project <project>', 'Google Vertex AI project ID, env:NAME, or file:/path').hideHelp())
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.addOption(new Option('--vertex-location <location>', 'Google Vertex AI location, env:NAME, or file:/path').hideHelp())
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.addOption(new Option('--skip-llm', 'Leave LLM setup incomplete for now').hideHelp().default(false))
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@ -423,7 +420,6 @@ export function registerSetupCommands(program: Command, context: KtxCliCommandCo
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...(options.llmBackend ? { llmBackend: options.llmBackend } : {}),
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...(options.anthropicApiKeyEnv ? { anthropicApiKeyEnv: options.anthropicApiKeyEnv } : {}),
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...(options.anthropicApiKeyFile ? { anthropicApiKeyFile: options.anthropicApiKeyFile } : {}),
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...(options.llmModel ? { llmModel: options.llmModel } : {}),
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...(options.vertexProject ? { vertexProject: options.vertexProject } : {}),
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...(options.vertexLocation ? { vertexLocation: options.vertexLocation } : {}),
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skipLlm: options.skipLlm === true,
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@ -17,7 +17,6 @@ export interface KtxDriverRegistration {
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readonly driver: KtxConnectionDriver;
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readonly scopeConfigKey: KtxScopeConfigKey | null;
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readonly hasHistoricSqlReader: boolean;
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readonly hasLocalQueryExecutor: boolean;
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load(): Promise<KtxDriverConnectorModule>;
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}
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@ -31,7 +30,6 @@ export const driverRegistrations: Record<KtxConnectionDriver, KtxDriverRegistrat
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driver: 'bigquery',
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scopeConfigKey: 'dataset_ids',
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hasHistoricSqlReader: true,
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hasLocalQueryExecutor: false,
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load: async () => {
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const m = await import('../../connectors/bigquery/connector.js');
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return {
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@ -53,7 +51,6 @@ export const driverRegistrations: Record<KtxConnectionDriver, KtxDriverRegistrat
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driver: 'clickhouse',
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scopeConfigKey: 'databases',
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hasHistoricSqlReader: false,
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hasLocalQueryExecutor: false,
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load: async () => {
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const m = await import('../../connectors/clickhouse/connector.js');
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return {
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@ -75,7 +72,6 @@ export const driverRegistrations: Record<KtxConnectionDriver, KtxDriverRegistrat
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driver: 'mysql',
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scopeConfigKey: 'schemas',
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hasHistoricSqlReader: false,
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hasLocalQueryExecutor: false,
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load: async () => {
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const m = await import('../../connectors/mysql/connector.js');
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return {
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@ -97,7 +93,6 @@ export const driverRegistrations: Record<KtxConnectionDriver, KtxDriverRegistrat
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driver: 'postgres',
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scopeConfigKey: 'schemas',
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hasHistoricSqlReader: true,
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hasLocalQueryExecutor: true,
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load: async () => {
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const m = await import('../../connectors/postgres/connector.js');
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return {
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@ -119,7 +114,6 @@ export const driverRegistrations: Record<KtxConnectionDriver, KtxDriverRegistrat
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driver: 'sqlite',
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scopeConfigKey: null,
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hasHistoricSqlReader: false,
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hasLocalQueryExecutor: true,
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load: async () => {
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const m = await import('../../connectors/sqlite/connector.js');
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return {
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@ -141,7 +135,6 @@ export const driverRegistrations: Record<KtxConnectionDriver, KtxDriverRegistrat
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driver: 'snowflake',
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scopeConfigKey: 'schema_names',
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hasHistoricSqlReader: true,
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hasLocalQueryExecutor: false,
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load: async () => {
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const m = await import('../../connectors/snowflake/connector.js');
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return {
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@ -163,7 +156,6 @@ export const driverRegistrations: Record<KtxConnectionDriver, KtxDriverRegistrat
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driver: 'sqlserver',
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scopeConfigKey: 'schemas',
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hasHistoricSqlReader: false,
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hasLocalQueryExecutor: false,
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load: async () => {
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const m = await import('../../connectors/sqlserver/connector.js');
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return {
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|
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@ -1,59 +0,0 @@
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import { driverRegistrations, getDriverRegistration } from './drivers.js';
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import { createPostgresQueryExecutor } from './postgres-query-executor.js';
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import type {
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KtxSqlQueryExecutionInput,
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KtxSqlQueryExecutionResult,
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KtxSqlQueryExecutorPort,
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} from './query-executor.js';
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import { createSqliteQueryExecutor } from './sqlite-query-executor.js';
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import type { KtxConnectionDriver } from '../scan/types.js';
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export interface DefaultLocalQueryExecutorOptions {
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postgres?: KtxSqlQueryExecutorPort;
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sqlite?: KtxSqlQueryExecutorPort;
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}
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function driverFor(input: KtxSqlQueryExecutionInput): string {
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return String(input.connection?.driver ?? '').toLowerCase();
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}
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function localExecutorMap(
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options: DefaultLocalQueryExecutorOptions,
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): Partial<Record<KtxConnectionDriver, KtxSqlQueryExecutorPort>> {
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const wiredExecutors: Partial<Record<KtxConnectionDriver, KtxSqlQueryExecutorPort>> = {
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postgres: options.postgres ?? createPostgresQueryExecutor(),
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sqlite: options.sqlite ?? createSqliteQueryExecutor(),
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};
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const executors: Partial<Record<KtxConnectionDriver, KtxSqlQueryExecutorPort>> = {};
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for (const registration of Object.values(driverRegistrations)) {
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if (!registration.hasLocalQueryExecutor) continue;
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const executor = wiredExecutors[registration.driver];
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if (executor) {
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executors[registration.driver] = executor;
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}
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}
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return executors;
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}
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export function createDefaultLocalQueryExecutor(options: DefaultLocalQueryExecutorOptions = {}): KtxSqlQueryExecutorPort {
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const executors = localExecutorMap(options);
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return {
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async execute(input: KtxSqlQueryExecutionInput): Promise<KtxSqlQueryExecutionResult> {
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const driver = driverFor(input);
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const registration = getDriverRegistration(driver);
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if (!registration?.hasLocalQueryExecutor) {
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throw new Error(`No local query executor is configured for driver "${input.connection?.driver ?? 'unknown'}".`);
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}
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const executor = executors[registration.driver];
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if (!executor) {
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throw new Error(
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`Local query executor flag is enabled for driver "${registration.driver}", but no executor factory is wired.`,
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);
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}
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return executor.execute(input);
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},
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};
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}
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|
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@ -1,78 +0,0 @@
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import { Client, type ClientConfig } from 'pg';
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import type {
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KtxSqlQueryExecutionInput,
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KtxSqlQueryExecutionResult,
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KtxSqlQueryExecutorPort,
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} from './query-executor.js';
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import { limitSqlForExecution } from './read-only-sql.js';
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interface PgClientLike {
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connect(): Promise<unknown>;
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query(input: string | { text: string; rowMode: 'array' }): Promise<{
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fields: Array<{ name: string }>;
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rows: unknown[][];
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command: string;
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rowCount: number | null;
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}>;
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end(): Promise<void>;
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}
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interface PostgresQueryExecutorOptions {
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statementTimeoutMs?: number;
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queryTimeoutMs?: number;
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connectionTimeoutMs?: number;
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clientFactory?: (config: ClientConfig) => PgClientLike;
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}
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|
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function connectionDriver(input: KtxSqlQueryExecutionInput): string {
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return String(input.connection?.driver ?? '').toLowerCase();
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}
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function createDefaultClient(config: ClientConfig): PgClientLike {
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return new Client(config);
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}
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export function createPostgresQueryExecutor(options: PostgresQueryExecutorOptions = {}): KtxSqlQueryExecutorPort {
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const clientFactory = options.clientFactory ?? createDefaultClient;
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return {
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async execute(input: KtxSqlQueryExecutionInput): Promise<KtxSqlQueryExecutionResult> {
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const driver = connectionDriver(input);
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const connection = input.connection;
|
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if (driver !== 'postgres') {
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throw new Error(`Local Postgres execution cannot run driver "${connection?.driver ?? 'unknown'}".`);
|
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}
|
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if (typeof connection?.url !== 'string' || connection.url.trim().length === 0) {
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throw new Error(`Local Postgres execution requires connections.${input.connectionId}.url.`);
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}
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|
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const client = clientFactory({
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connectionString: connection.url,
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statement_timeout: options.statementTimeoutMs ?? 30_000,
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query_timeout: options.queryTimeoutMs ?? 35_000,
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connectionTimeoutMillis: options.connectionTimeoutMs ?? 5_000,
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application_name: 'ktx-local-query',
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});
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await client.connect();
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try {
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await client.query('BEGIN READ ONLY');
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const result = await client.query({
|
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text: limitSqlForExecution(input.sql, input.maxRows),
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rowMode: 'array',
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});
|
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await client.query('COMMIT');
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return {
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headers: result.fields.map((field) => field.name),
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rows: result.rows,
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||||
totalRows: result.rows.length,
|
||||
command: result.command,
|
||||
rowCount: result.rowCount,
|
||||
};
|
||||
} catch (error) {
|
||||
await client.query('ROLLBACK').catch(() => undefined);
|
||||
throw error;
|
||||
} finally {
|
||||
await client.end();
|
||||
}
|
||||
},
|
||||
};
|
||||
}
|
||||
|
|
@ -8,7 +8,7 @@ export interface KtxSqlQueryExecutionInput {
|
|||
maxRows?: number;
|
||||
}
|
||||
|
||||
export interface KtxSqlQueryExecutionResult {
|
||||
interface KtxSqlQueryExecutionResult {
|
||||
headers: string[];
|
||||
rows: unknown[][];
|
||||
totalRows: number;
|
||||
|
|
|
|||
|
|
@ -1,92 +0,0 @@
|
|||
import { isAbsolute, resolve } from 'node:path';
|
||||
import { fileURLToPath } from 'node:url';
|
||||
import Database from 'better-sqlite3';
|
||||
import { readFileSync } from 'node:fs';
|
||||
import { homedir } from 'node:os';
|
||||
import type {
|
||||
KtxSqlQueryExecutionInput,
|
||||
KtxSqlQueryExecutionResult,
|
||||
KtxSqlQueryExecutorPort,
|
||||
} from './query-executor.js';
|
||||
import { normalizeQueryRows } from './query-executor.js';
|
||||
import { limitSqlForExecution } from './read-only-sql.js';
|
||||
|
||||
type SqliteConnectionConfig = Record<string, unknown> | undefined;
|
||||
|
||||
function connectionDriver(input: KtxSqlQueryExecutionInput): string {
|
||||
return String(input.connection?.driver ?? '').toLowerCase();
|
||||
}
|
||||
|
||||
function stringConfigValue(connection: SqliteConnectionConfig, key: string): string | undefined {
|
||||
const value = connection?.[key];
|
||||
return typeof value === 'string' && value.trim().length > 0 ? resolveStringReference(key, value.trim()) : undefined;
|
||||
}
|
||||
|
||||
function resolveStringReference(key: string, value: string): string {
|
||||
if (value.startsWith('env:')) {
|
||||
return process.env[value.slice('env:'.length)] ?? '';
|
||||
}
|
||||
if (key !== 'url' && value.startsWith('file:')) {
|
||||
const rawPath = value.slice('file:'.length);
|
||||
const path = rawPath.startsWith('~') ? resolve(homedir(), rawPath.slice(1)) : rawPath;
|
||||
return readFileSync(path, 'utf-8').trim();
|
||||
}
|
||||
return value;
|
||||
}
|
||||
|
||||
function sqlitePathFromUrl(url: string): string {
|
||||
if (url.startsWith('file:')) {
|
||||
return fileURLToPath(url);
|
||||
}
|
||||
|
||||
if (url.startsWith('sqlite:')) {
|
||||
const parsed = new URL(url);
|
||||
if (parsed.pathname.length > 0) {
|
||||
return decodeURIComponent(parsed.pathname);
|
||||
}
|
||||
}
|
||||
|
||||
return url;
|
||||
}
|
||||
|
||||
/** @internal */
|
||||
export function sqliteDatabasePathFromConnection(input: KtxSqlQueryExecutionInput): string {
|
||||
const driver = connectionDriver(input);
|
||||
if (driver !== 'sqlite') {
|
||||
throw new Error(`Local SQLite execution cannot run driver "${input.connection?.driver ?? 'unknown'}".`);
|
||||
}
|
||||
|
||||
const pathValue = stringConfigValue(input.connection, 'path');
|
||||
const urlValue = stringConfigValue(input.connection, 'url');
|
||||
if (!pathValue && !urlValue) {
|
||||
throw new Error(
|
||||
`Local SQLite execution requires connections.${input.connectionId}.path or connections.${input.connectionId}.url.`,
|
||||
);
|
||||
}
|
||||
|
||||
const candidate = pathValue ?? sqlitePathFromUrl(urlValue as string);
|
||||
return isAbsolute(candidate) ? candidate : resolve(input.projectDir ?? process.cwd(), candidate);
|
||||
}
|
||||
|
||||
export function createSqliteQueryExecutor(): KtxSqlQueryExecutorPort {
|
||||
return {
|
||||
async execute(input: KtxSqlQueryExecutionInput): Promise<KtxSqlQueryExecutionResult> {
|
||||
const sql = limitSqlForExecution(input.sql, input.maxRows);
|
||||
const dbPath = sqliteDatabasePathFromConnection(input);
|
||||
const db = new Database(dbPath, { readonly: true, fileMustExist: true });
|
||||
try {
|
||||
const statement = db.prepare(sql);
|
||||
const rows = statement.all() as unknown[];
|
||||
return {
|
||||
headers: statement.columns().map((column) => column.name),
|
||||
rows: normalizeQueryRows(rows),
|
||||
totalRows: rows.length,
|
||||
command: 'SELECT',
|
||||
rowCount: rows.length,
|
||||
};
|
||||
} finally {
|
||||
db.close();
|
||||
}
|
||||
},
|
||||
};
|
||||
}
|
||||
|
|
@ -615,8 +615,8 @@ function localIngestLlmProviderGuardMessage(projectDir: string): string {
|
|||
'ktx ingest requires llm.provider.backend: anthropic, vertex, gateway, claude-code, or codex, or an injected agentRunner.',
|
||||
'Configure a local Claude Code/Codex session or API-backed LLM, then rerun ingest:',
|
||||
` ktx setup --project-dir ${projectDir} --llm-backend claude-code --no-input`,
|
||||
` ktx setup --project-dir ${projectDir} --llm-backend codex --llm-model gpt-5.5 --no-input`,
|
||||
` ktx setup --project-dir ${projectDir} --llm-backend anthropic --anthropic-api-key-env ANTHROPIC_API_KEY --llm-model claude-sonnet-4-6 --no-input`,
|
||||
` ktx setup --project-dir ${projectDir} --llm-backend codex --no-input`,
|
||||
` ktx setup --project-dir ${projectDir} --llm-backend anthropic --anthropic-api-key-env ANTHROPIC_API_KEY --no-input`,
|
||||
].join('\n');
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -10,7 +10,7 @@ import { resolveKtxConfigReference } from './context/core/config-reference.js';
|
|||
import { type KtxProjectConfig, type KtxProjectLlmConfig, serializeKtxProjectConfig } from './context/project/config.js';
|
||||
import { loadKtxProject } from './context/project/project.js';
|
||||
import { markKtxSetupStateStepComplete } from './context/project/setup-config.js';
|
||||
import type { KtxLlmConfig } from './llm/types.js';
|
||||
import { type KtxModelRole, KTX_MODEL_ROLES, type KtxLlmConfig } from './llm/types.js';
|
||||
import { type KtxLlmHealthCheckResult, runKtxLlmHealthCheck } from './llm/model-health.js';
|
||||
import {
|
||||
formatClaudeCodePromptCachingWarning,
|
||||
|
|
@ -37,7 +37,6 @@ export interface KtxSetupModelArgs {
|
|||
llmBackend?: KtxSetupLlmBackend;
|
||||
anthropicApiKeyEnv?: string;
|
||||
anthropicApiKeyFile?: string;
|
||||
llmModel?: string;
|
||||
vertexProject?: string;
|
||||
vertexLocation?: string;
|
||||
forcePrompt?: boolean;
|
||||
|
|
@ -52,13 +51,6 @@ export type KtxSetupModelResult =
|
|||
| { status: 'missing-input'; projectDir: string }
|
||||
| { status: 'failed'; projectDir: string };
|
||||
|
||||
/** @internal */
|
||||
export interface AnthropicModelChoice {
|
||||
id: string;
|
||||
label: string;
|
||||
recommended: boolean;
|
||||
}
|
||||
|
||||
export type KtxSetupLlmBackend = 'anthropic' | 'vertex' | 'claude-code' | 'codex';
|
||||
|
||||
/** @internal */
|
||||
|
|
@ -76,9 +68,7 @@ export interface KtxSetupModelPromptAdapter {
|
|||
|
||||
export interface KtxSetupModelDeps {
|
||||
env?: NodeJS.ProcessEnv;
|
||||
fetch?: typeof fetch;
|
||||
prompts?: KtxSetupModelPromptAdapter;
|
||||
listModels?: (apiKey: string) => Promise<AnthropicModelChoice[]>;
|
||||
healthCheck?: (config: KtxLlmConfig) => Promise<KtxLlmHealthCheckResult>;
|
||||
claudeCodeAuthProbe?: (input: {
|
||||
projectDir: string;
|
||||
|
|
@ -91,91 +81,58 @@ export interface KtxSetupModelDeps {
|
|||
spinner?: () => KtxCliSpinner;
|
||||
}
|
||||
|
||||
/** @internal */
|
||||
export const BUNDLED_ANTHROPIC_MODELS: AnthropicModelChoice[] = [
|
||||
{ id: 'claude-sonnet-4-6', label: 'Claude Sonnet 4.6', recommended: true },
|
||||
{ id: 'claude-opus-4-6', label: 'Claude Opus 4.6', recommended: false },
|
||||
{ id: 'claude-haiku-4-5', label: 'Claude Haiku 4.5', recommended: false },
|
||||
];
|
||||
|
||||
const VERTEX_ANTHROPIC_MODELS: AnthropicModelChoice[] = [
|
||||
{ id: 'claude-opus-4-7', label: 'Claude Opus 4.7', recommended: false },
|
||||
{ id: 'claude-sonnet-4-6', label: 'Claude Sonnet 4.6', recommended: false },
|
||||
{ id: 'claude-opus-4-6', label: 'Claude Opus 4.6', recommended: false },
|
||||
{ id: 'claude-opus-4-5', label: 'Claude Opus 4.5', recommended: false },
|
||||
{ id: 'claude-haiku-4-5', label: 'Claude Haiku 4.5', recommended: false },
|
||||
{ id: 'claude-sonnet-4-5', label: 'Claude Sonnet 4.5', recommended: false },
|
||||
{ id: 'claude-opus-4-1', label: 'Claude Opus 4.1', recommended: false },
|
||||
];
|
||||
|
||||
const CLAUDE_CODE_MODELS: AnthropicModelChoice[] = [
|
||||
{ id: 'sonnet', label: 'Claude Sonnet', recommended: true },
|
||||
{ id: 'opus', label: 'Claude Opus', recommended: false },
|
||||
{ id: 'haiku', label: 'Claude Haiku', recommended: false },
|
||||
];
|
||||
|
||||
// Curated Codex models from OpenAI's current lineup that work under both
|
||||
// ChatGPT-account (subscription) and API-key auth. Intentionally omitted:
|
||||
// the `*-codex` ids (e.g. gpt-5.3-codex, gpt-5.2-codex) are API-key-only and
|
||||
// fail on ChatGPT-account auth, and gpt-5.3-codex-spark is a ChatGPT-Pro-only
|
||||
// research preview. Codex resolves real availability per account at runtime
|
||||
// (its binary remote-fetches the model list), so this is a convenience
|
||||
// shortlist only — the manual-entry option accepts any id your account's
|
||||
// `codex` picker exposes, and the auth probe reports an unsupported choice.
|
||||
const CODEX_MODELS: AnthropicModelChoice[] = [
|
||||
{ id: 'gpt-5.5', label: 'GPT-5.5', recommended: true },
|
||||
{ id: 'gpt-5.4', label: 'GPT-5.4', recommended: false },
|
||||
{ id: 'gpt-5.4-mini', label: 'GPT-5.4 mini', recommended: false },
|
||||
];
|
||||
|
||||
const HIDDEN_ANTHROPIC_MODEL_PATTERNS = [
|
||||
/^claude-sonnet-4$/i,
|
||||
/^claude-opus-4$/i,
|
||||
/^Claude Sonnet 4$/i,
|
||||
/^Claude Opus 4$/i,
|
||||
];
|
||||
|
||||
const ANTHROPIC_CREDENTIAL_PROMPT_CONTEXT =
|
||||
'KTX uses the key to verify Anthropic model access now and to run ingest agents that turn schemas, SQL, ' +
|
||||
'BI metadata, and docs into semantic-layer sources and wiki context. ktx.yaml stores an env: or file: ' +
|
||||
'reference, not the raw key.';
|
||||
|
||||
const ANTHROPIC_MODEL_PROMPT_CONTEXT =
|
||||
'KTX uses this as the default model for ingest agents that turn schemas, SQL, BI metadata, and docs ' +
|
||||
'into semantic-layer sources and wiki context.';
|
||||
|
||||
const VERTEX_PROJECT_PROMPT_CONTEXT =
|
||||
'KTX stores the selected Google Cloud project ID in ktx.yaml and uses Application Default Credentials for ' +
|
||||
'access. Project visibility depends on the signed-in Google account and organization permissions.';
|
||||
const DEFAULT_VERTEX_LOCATION = 'us-east5';
|
||||
|
||||
type KtxSetupModelPreset = Record<KtxModelRole, string>;
|
||||
|
||||
const ANTHROPIC_PRESET = {
|
||||
default: 'claude-sonnet-4-6',
|
||||
triage: 'claude-haiku-4-5',
|
||||
candidateExtraction: 'claude-sonnet-4-6',
|
||||
curator: 'claude-opus-4-7',
|
||||
reconcile: 'claude-opus-4-7',
|
||||
repair: 'claude-haiku-4-5',
|
||||
} satisfies KtxSetupModelPreset;
|
||||
|
||||
const CLAUDE_CODE_PRESET = {
|
||||
default: 'sonnet',
|
||||
triage: 'haiku',
|
||||
candidateExtraction: 'sonnet',
|
||||
curator: 'opus',
|
||||
reconcile: 'opus',
|
||||
repair: 'haiku',
|
||||
} satisfies KtxSetupModelPreset;
|
||||
|
||||
const CODEX_PRESET = {
|
||||
default: DEFAULT_CODEX_MODEL,
|
||||
triage: DEFAULT_CODEX_MODEL,
|
||||
candidateExtraction: DEFAULT_CODEX_MODEL,
|
||||
curator: DEFAULT_CODEX_MODEL,
|
||||
reconcile: DEFAULT_CODEX_MODEL,
|
||||
repair: DEFAULT_CODEX_MODEL,
|
||||
} satisfies KtxSetupModelPreset;
|
||||
|
||||
const MODEL_PRESETS = {
|
||||
anthropic: ANTHROPIC_PRESET,
|
||||
vertex: ANTHROPIC_PRESET,
|
||||
'claude-code': CLAUDE_CODE_PRESET,
|
||||
codex: CODEX_PRESET,
|
||||
} satisfies Record<KtxSetupLlmBackend, KtxSetupModelPreset>;
|
||||
|
||||
function presetForBackend(backend: KtxSetupLlmBackend): KtxSetupModelPreset {
|
||||
return MODEL_PRESETS[backend];
|
||||
}
|
||||
|
||||
const execFileAsync = promisify(execFile);
|
||||
|
||||
type AnthropicModelDiscoveryErrorReason = 'authentication' | 'http' | 'empty-response';
|
||||
|
||||
class AnthropicModelDiscoveryError extends Error {
|
||||
constructor(
|
||||
message: string,
|
||||
public readonly reason: AnthropicModelDiscoveryErrorReason,
|
||||
public readonly status?: number,
|
||||
) {
|
||||
super(message);
|
||||
this.name = 'AnthropicModelDiscoveryError';
|
||||
}
|
||||
}
|
||||
|
||||
function isAnthropicModelAuthenticationError(error: unknown): error is AnthropicModelDiscoveryError {
|
||||
return error instanceof AnthropicModelDiscoveryError && error.reason === 'authentication';
|
||||
}
|
||||
|
||||
function isSelectableAnthropicModel(model: AnthropicModelChoice): boolean {
|
||||
return !HIDDEN_ANTHROPIC_MODEL_PATTERNS.some((pattern) => pattern.test(model.id) || pattern.test(model.label));
|
||||
}
|
||||
|
||||
type ChooseModelResult =
|
||||
| { status: 'ready'; model: string }
|
||||
| { status: 'back' | 'missing-input' | 'invalid-credential' };
|
||||
|
||||
type ChooseBackendResult =
|
||||
| { status: 'ready'; backend: KtxSetupLlmBackend; prompted: boolean }
|
||||
| { status: 'back' };
|
||||
|
|
@ -234,47 +191,6 @@ async function defaultListGcloudProjects(): Promise<GcloudProjectChoice[]> {
|
|||
.filter((project): project is GcloudProjectChoice => Boolean(project));
|
||||
}
|
||||
|
||||
/** @internal */
|
||||
export async function fetchAnthropicModels(
|
||||
apiKey: string,
|
||||
fetchFn: typeof fetch = fetch,
|
||||
): Promise<AnthropicModelChoice[]> {
|
||||
const response = await fetchFn('https://api.anthropic.com/v1/models?limit=1000', {
|
||||
headers: {
|
||||
'anthropic-version': '2023-06-01',
|
||||
'x-api-key': apiKey,
|
||||
},
|
||||
});
|
||||
if (!response.ok) {
|
||||
if (response.status === 401 || response.status === 403) {
|
||||
throw new AnthropicModelDiscoveryError(
|
||||
`Anthropic model discovery failed with HTTP ${response.status}`,
|
||||
'authentication',
|
||||
response.status,
|
||||
);
|
||||
}
|
||||
throw new AnthropicModelDiscoveryError(
|
||||
`Anthropic model discovery failed with HTTP ${response.status}`,
|
||||
'http',
|
||||
response.status,
|
||||
);
|
||||
}
|
||||
const body = (await response.json()) as { data?: Array<{ id?: unknown; display_name?: unknown; type?: unknown }> };
|
||||
const models = (body.data ?? [])
|
||||
.map((item) => ({
|
||||
id: typeof item.id === 'string' ? item.id : '',
|
||||
label: typeof item.display_name === 'string' ? item.display_name : typeof item.id === 'string' ? item.id : '',
|
||||
recommended: false,
|
||||
}))
|
||||
.filter((item) => item.id.startsWith('claude-'))
|
||||
.filter(isSelectableAnthropicModel);
|
||||
if (models.length === 0) {
|
||||
throw new AnthropicModelDiscoveryError('Anthropic model discovery returned no Claude models', 'empty-response');
|
||||
}
|
||||
const recommendedIndex = models.findIndex((item) => item.id.includes('sonnet'));
|
||||
return models.map((item, index) => ({ ...item, recommended: index === Math.max(recommendedIndex, 0) }));
|
||||
}
|
||||
|
||||
export function isKtxSetupLlmConfigReady(config: KtxProjectLlmConfig): boolean {
|
||||
let resolved: KtxLlmConfig | null;
|
||||
try {
|
||||
|
|
@ -309,12 +225,12 @@ function buildProjectLlmConfig(
|
|||
| { backend: 'vertex'; vertex: { project?: string; location: string } }
|
||||
| { backend: 'claude-code' }
|
||||
| { backend: 'codex' },
|
||||
model: string,
|
||||
models: KtxSetupModelPreset,
|
||||
): KtxProjectLlmConfig {
|
||||
if (provider.backend === 'claude-code') {
|
||||
return {
|
||||
provider: { backend: 'claude-code' },
|
||||
models: { ...existing.models, default: model },
|
||||
models,
|
||||
promptCaching: existing.promptCaching,
|
||||
};
|
||||
}
|
||||
|
|
@ -322,7 +238,7 @@ function buildProjectLlmConfig(
|
|||
if (provider.backend === 'codex') {
|
||||
return {
|
||||
provider: { backend: 'codex' },
|
||||
models: { ...existing.models, default: model },
|
||||
models,
|
||||
promptCaching: existing.promptCaching,
|
||||
};
|
||||
}
|
||||
|
|
@ -333,7 +249,7 @@ function buildProjectLlmConfig(
|
|||
backend: 'vertex',
|
||||
vertex: provider.vertex,
|
||||
},
|
||||
models: { ...existing.models, default: model },
|
||||
models,
|
||||
promptCaching: { ...(existing.promptCaching ?? {}), enabled: true, vertexFallbackTo5m: true },
|
||||
};
|
||||
}
|
||||
|
|
@ -343,7 +259,7 @@ function buildProjectLlmConfig(
|
|||
backend: 'anthropic',
|
||||
anthropic: { api_key: provider.credentialRef },
|
||||
},
|
||||
models: { ...existing.models, default: model },
|
||||
models,
|
||||
promptCaching: { ...(existing.promptCaching ?? {}), enabled: true },
|
||||
};
|
||||
}
|
||||
|
|
@ -514,16 +430,12 @@ function requestedBackend(args: KtxSetupModelArgs): KtxSetupLlmBackend | undefin
|
|||
if (args.vertexProject || args.vertexLocation) {
|
||||
return 'vertex';
|
||||
}
|
||||
if (args.anthropicApiKeyEnv || args.anthropicApiKeyFile || args.llmModel) {
|
||||
if (args.anthropicApiKeyEnv || args.anthropicApiKeyFile) {
|
||||
return 'anthropic';
|
||||
}
|
||||
return undefined;
|
||||
}
|
||||
|
||||
function requestedModel(args: KtxSetupModelArgs): string | undefined {
|
||||
return args.llmModel;
|
||||
}
|
||||
|
||||
async function chooseBackend(
|
||||
args: KtxSetupModelArgs,
|
||||
io: KtxCliIo,
|
||||
|
|
@ -774,187 +686,6 @@ async function chooseVertexConfig(
|
|||
};
|
||||
}
|
||||
|
||||
async function chooseModel(
|
||||
args: KtxSetupModelArgs,
|
||||
credentialValue: string,
|
||||
io: KtxCliIo,
|
||||
deps: KtxSetupModelDeps,
|
||||
): Promise<ChooseModelResult> {
|
||||
const providedModel = requestedModel(args);
|
||||
if (providedModel) {
|
||||
return { status: 'ready', model: providedModel };
|
||||
}
|
||||
if (args.inputMode === 'disabled') {
|
||||
io.stderr.write('Missing LLM model: pass --llm-model.\n');
|
||||
return { status: 'missing-input' };
|
||||
}
|
||||
|
||||
let models: AnthropicModelChoice[];
|
||||
try {
|
||||
models = deps.listModels
|
||||
? await deps.listModels(credentialValue)
|
||||
: await fetchAnthropicModels(credentialValue, deps.fetch);
|
||||
} catch (error) {
|
||||
if (isAnthropicModelAuthenticationError(error)) {
|
||||
const statusSuffix = error.status ? ` (HTTP ${error.status})` : '';
|
||||
io.stderr.write(`Anthropic API key is invalid or unauthorized${statusSuffix}. Check the key and try again.\n`);
|
||||
return { status: 'invalid-credential' };
|
||||
}
|
||||
io.stderr.write(
|
||||
'Could not fetch live Anthropic models. Showing bundled defaults. Setup will still test the selected model before saving it.\n',
|
||||
);
|
||||
models = BUNDLED_ANTHROPIC_MODELS;
|
||||
}
|
||||
|
||||
const selectableModels = models.filter(isSelectableAnthropicModel);
|
||||
const prompts = deps.prompts ?? createPromptAdapter();
|
||||
const modelOptions = [
|
||||
...selectableModels.map((model) => ({
|
||||
value: model.id,
|
||||
label: model.label || model.id,
|
||||
...(model.recommended ? { hint: 'recommended' } : {}),
|
||||
})),
|
||||
{ value: 'manual', label: 'Enter a model ID manually' },
|
||||
{ value: 'back', label: 'Back' },
|
||||
];
|
||||
const choice = await prompts.autocomplete({
|
||||
message: `Which Anthropic model should KTX use?\n\n${ANTHROPIC_MODEL_PROMPT_CONTEXT}`,
|
||||
placeholder: 'Type to search models',
|
||||
options: modelOptions,
|
||||
});
|
||||
if (choice === 'back') {
|
||||
return { status: 'back' };
|
||||
}
|
||||
if (choice === 'manual') {
|
||||
const manual = await prompts.text({
|
||||
message: withTextInputNavigation('Anthropic model ID'),
|
||||
placeholder: selectableModels.find((model) => model.recommended)?.id ?? selectableModels[0]?.id,
|
||||
});
|
||||
if (manual === undefined) {
|
||||
return { status: 'back' };
|
||||
}
|
||||
return manual.trim() ? { status: 'ready', model: manual.trim() } : { status: 'missing-input' };
|
||||
}
|
||||
return { status: 'ready', model: choice };
|
||||
}
|
||||
|
||||
async function chooseVertexModel(args: KtxSetupModelArgs, io: KtxCliIo, deps: KtxSetupModelDeps): Promise<ChooseModelResult> {
|
||||
const providedModel = requestedModel(args);
|
||||
if (providedModel) {
|
||||
return { status: 'ready', model: providedModel };
|
||||
}
|
||||
if (args.inputMode === 'disabled') {
|
||||
io.stderr.write('Missing LLM model: pass --llm-model.\n');
|
||||
return { status: 'missing-input' };
|
||||
}
|
||||
|
||||
const selectableModels = VERTEX_ANTHROPIC_MODELS.filter(isSelectableAnthropicModel);
|
||||
const prompts = deps.prompts ?? createPromptAdapter();
|
||||
const choice = await prompts.autocomplete({
|
||||
message: `Which Anthropic model should KTX use?\n\n${ANTHROPIC_MODEL_PROMPT_CONTEXT}`,
|
||||
placeholder: 'Type to search models',
|
||||
options: [
|
||||
...selectableModels.map((model) => ({
|
||||
value: model.id,
|
||||
label: model.label || model.id,
|
||||
...(model.recommended ? { hint: 'recommended' } : {}),
|
||||
})),
|
||||
{ value: 'manual', label: 'Enter a model ID manually' },
|
||||
{ value: 'back', label: 'Back' },
|
||||
],
|
||||
});
|
||||
if (choice === 'back') {
|
||||
return { status: 'back' };
|
||||
}
|
||||
if (choice === 'manual') {
|
||||
const manual = await prompts.text({
|
||||
message: withTextInputNavigation('Anthropic model ID'),
|
||||
placeholder: selectableModels.find((model) => model.recommended)?.id ?? selectableModels[0]?.id,
|
||||
});
|
||||
if (manual === undefined) {
|
||||
return { status: 'back' };
|
||||
}
|
||||
return manual.trim() ? { status: 'ready', model: manual.trim() } : { status: 'missing-input' };
|
||||
}
|
||||
return { status: 'ready', model: choice };
|
||||
}
|
||||
|
||||
async function chooseClaudeCodeModel(args: KtxSetupModelArgs, deps: KtxSetupModelDeps): Promise<ChooseModelResult> {
|
||||
const providedModel = requestedModel(args);
|
||||
if (providedModel) {
|
||||
return { status: 'ready', model: providedModel };
|
||||
}
|
||||
if (args.inputMode === 'disabled') {
|
||||
return { status: 'ready', model: 'sonnet' };
|
||||
}
|
||||
|
||||
const prompts = deps.prompts ?? createPromptAdapter();
|
||||
const choice = await prompts.select({
|
||||
message: `Which Claude Code model should KTX use?\n\n${ANTHROPIC_MODEL_PROMPT_CONTEXT}`,
|
||||
options: [
|
||||
...CLAUDE_CODE_MODELS.map((model) => ({
|
||||
value: model.id,
|
||||
label: model.label,
|
||||
...(model.recommended ? { hint: 'recommended' } : {}),
|
||||
})),
|
||||
{ value: 'manual', label: 'Enter a Claude Code model ID manually' },
|
||||
{ value: 'back', label: 'Back' },
|
||||
],
|
||||
});
|
||||
if (choice === 'back') {
|
||||
return { status: 'back' };
|
||||
}
|
||||
if (choice === 'manual') {
|
||||
const manual = await prompts.text({
|
||||
message: withTextInputNavigation('Claude Code model ID'),
|
||||
placeholder: CLAUDE_CODE_MODELS.find((model) => model.recommended)?.id ?? CLAUDE_CODE_MODELS[0]?.id,
|
||||
});
|
||||
if (manual === undefined) {
|
||||
return { status: 'back' };
|
||||
}
|
||||
return manual.trim() ? { status: 'ready', model: manual.trim() } : { status: 'missing-input' };
|
||||
}
|
||||
return { status: 'ready', model: choice };
|
||||
}
|
||||
|
||||
async function chooseCodexModel(args: KtxSetupModelArgs, deps: KtxSetupModelDeps): Promise<ChooseModelResult> {
|
||||
const providedModel = requestedModel(args);
|
||||
if (providedModel) {
|
||||
return { status: 'ready', model: providedModel };
|
||||
}
|
||||
if (args.inputMode === 'disabled') {
|
||||
return { status: 'ready', model: DEFAULT_CODEX_MODEL };
|
||||
}
|
||||
|
||||
const prompts = deps.prompts ?? createPromptAdapter();
|
||||
const choice = await prompts.select({
|
||||
message: `Which Codex model should KTX use?\n\n${ANTHROPIC_MODEL_PROMPT_CONTEXT}`,
|
||||
options: [
|
||||
...CODEX_MODELS.map((model) => ({
|
||||
value: model.id,
|
||||
label: model.label,
|
||||
...(model.recommended ? { hint: 'recommended' } : {}),
|
||||
})),
|
||||
{ value: 'manual', label: 'Enter a Codex model ID manually' },
|
||||
{ value: 'back', label: 'Back' },
|
||||
],
|
||||
});
|
||||
if (choice === 'back') {
|
||||
return { status: 'back' };
|
||||
}
|
||||
if (choice === 'manual') {
|
||||
const manual = await prompts.text({
|
||||
message: withTextInputNavigation('Codex model ID'),
|
||||
placeholder: CODEX_MODELS.find((model) => model.recommended)?.id ?? CODEX_MODELS[0]?.id,
|
||||
});
|
||||
if (manual === undefined) {
|
||||
return { status: 'back' };
|
||||
}
|
||||
return manual.trim() ? { status: 'ready', model: manual.trim() } : { status: 'missing-input' };
|
||||
}
|
||||
return { status: 'ready', model: choice };
|
||||
}
|
||||
|
||||
async function persistLlmConfig(
|
||||
projectDir: string,
|
||||
provider:
|
||||
|
|
@ -962,12 +693,12 @@ async function persistLlmConfig(
|
|||
| { backend: 'vertex'; vertex: { project?: string; location: string } }
|
||||
| { backend: 'claude-code' }
|
||||
| { backend: 'codex' },
|
||||
model: string,
|
||||
models: KtxSetupModelPreset,
|
||||
): Promise<void> {
|
||||
const project = await loadKtxProject({ projectDir });
|
||||
const config = {
|
||||
...project.config,
|
||||
llm: buildProjectLlmConfig(project.config.llm, provider, model),
|
||||
llm: buildProjectLlmConfig(project.config.llm, provider, models),
|
||||
scan: {
|
||||
...project.config.scan,
|
||||
enrichment: {
|
||||
|
|
@ -990,6 +721,61 @@ function buildInteractiveRetryArgs(args: KtxSetupModelArgs, backend?: KtxSetupLl
|
|||
};
|
||||
}
|
||||
|
||||
type PresetModelValidationResult = { ok: true } | { ok: false; message: string };
|
||||
|
||||
function distinctPresetModels(preset: KtxSetupModelPreset): string[] {
|
||||
const models: string[] = [];
|
||||
const seen = new Set<string>();
|
||||
for (const role of KTX_MODEL_ROLES) {
|
||||
const model = preset[role];
|
||||
if (!seen.has(model)) {
|
||||
seen.add(model);
|
||||
models.push(model);
|
||||
}
|
||||
}
|
||||
return models;
|
||||
}
|
||||
|
||||
function rolesUsingModel(preset: KtxSetupModelPreset, model: string): KtxModelRole[] {
|
||||
return KTX_MODEL_ROLES.filter((role) => preset[role] === model);
|
||||
}
|
||||
|
||||
function formatPresetFallbackWarning(roles: KtxModelRole[], unavailableModel: string, anchorModel: string): string {
|
||||
return `LLM model ${unavailableModel} is unavailable for ${roles.join(', ')}; using ${anchorModel} for those roles.`;
|
||||
}
|
||||
|
||||
async function validatePresetModels(
|
||||
preset: KtxSetupModelPreset,
|
||||
validateModel: (model: string) => Promise<PresetModelValidationResult>,
|
||||
io: KtxCliIo,
|
||||
): Promise<{ status: 'ready'; models: KtxSetupModelPreset } | { status: 'failed'; message: string }> {
|
||||
const anchorModel = preset.default;
|
||||
const degraded = { ...preset };
|
||||
const models = distinctPresetModels(preset);
|
||||
|
||||
const anchorResult = await validateModel(anchorModel);
|
||||
if (!anchorResult.ok) {
|
||||
return { status: 'failed', message: anchorResult.message };
|
||||
}
|
||||
|
||||
for (const model of models) {
|
||||
if (model === anchorModel) {
|
||||
continue;
|
||||
}
|
||||
const result = await validateModel(model);
|
||||
if (result.ok) {
|
||||
continue;
|
||||
}
|
||||
const affectedRoles = rolesUsingModel(degraded, model);
|
||||
for (const role of affectedRoles) {
|
||||
degraded[role] = anchorModel;
|
||||
}
|
||||
io.stderr.write(`${formatPresetFallbackWarning(affectedRoles, model, anchorModel)}\n`);
|
||||
}
|
||||
|
||||
return { status: 'ready', models: degraded };
|
||||
}
|
||||
|
||||
export async function runKtxSetupAnthropicModelStep(
|
||||
args: KtxSetupModelArgs,
|
||||
io: KtxCliIo,
|
||||
|
|
@ -1007,7 +793,6 @@ export async function runKtxSetupAnthropicModelStep(
|
|||
!args.llmBackend &&
|
||||
!args.anthropicApiKeyEnv &&
|
||||
!args.anthropicApiKeyFile &&
|
||||
!args.llmModel &&
|
||||
!args.vertexProject &&
|
||||
!args.vertexLocation
|
||||
) {
|
||||
|
|
@ -1038,94 +823,74 @@ export async function runKtxSetupAnthropicModelStep(
|
|||
return { status: vertex.status, projectDir: args.projectDir };
|
||||
}
|
||||
|
||||
const model = await chooseVertexModel(backendArgs, io, deps);
|
||||
if (model.status === 'back' && !backendArgs.vertexLocation) {
|
||||
const preset = presetForBackend('vertex');
|
||||
const validation = await validatePresetModels(
|
||||
preset,
|
||||
async (model) =>
|
||||
runLlmHealthCheckWithProgress(
|
||||
buildVertexHealthConfig(vertex.values, model),
|
||||
'Vertex AI',
|
||||
model,
|
||||
healthCheck,
|
||||
deps,
|
||||
),
|
||||
io,
|
||||
);
|
||||
if (validation.status !== 'ready') {
|
||||
io.stderr.write(
|
||||
`Vertex AI Anthropic model health check failed: ${formatVertexHealthFailure(validation.message, vertex.values)}\n`,
|
||||
);
|
||||
if (args.inputMode === 'disabled') {
|
||||
return { status: 'failed', projectDir: args.projectDir };
|
||||
}
|
||||
io.stderr.write('Choose a different Vertex AI project or location, or Back.\n');
|
||||
attemptArgs = buildInteractiveRetryArgs(args, backendChoice.backend);
|
||||
continue;
|
||||
}
|
||||
if (model.status === 'invalid-credential') {
|
||||
return { status: 'failed', projectDir: args.projectDir };
|
||||
}
|
||||
if (model.status !== 'ready') {
|
||||
return { status: model.status, projectDir: args.projectDir };
|
||||
}
|
||||
|
||||
const health = await runLlmHealthCheckWithProgress(
|
||||
buildVertexHealthConfig(vertex.values, model.model),
|
||||
'Vertex AI',
|
||||
model.model,
|
||||
healthCheck,
|
||||
deps,
|
||||
);
|
||||
if (health.ok) {
|
||||
await persistLlmConfig(args.projectDir, { backend: 'vertex', vertex: vertex.refs }, model.model);
|
||||
io.stdout.write(`│ LLM ready: yes (${model.model})\n`);
|
||||
return { status: 'ready', projectDir: args.projectDir };
|
||||
}
|
||||
|
||||
io.stderr.write(`Vertex AI Anthropic model health check failed: ${formatVertexHealthFailure(health.message, vertex.values)}\n`);
|
||||
if (args.inputMode === 'disabled') {
|
||||
return { status: 'failed', projectDir: args.projectDir };
|
||||
}
|
||||
io.stderr.write('Choose a different Vertex AI project, location, or model, or Back.\n');
|
||||
attemptArgs = buildInteractiveRetryArgs(args, backendChoice.backend);
|
||||
continue;
|
||||
await persistLlmConfig(args.projectDir, { backend: 'vertex', vertex: vertex.refs }, validation.models);
|
||||
io.stdout.write(`│ LLM ready: yes (${validation.models.default})\n`);
|
||||
return { status: 'ready', projectDir: args.projectDir };
|
||||
}
|
||||
|
||||
if (backendChoice.backend === 'claude-code') {
|
||||
const model = await chooseClaudeCodeModel(backendArgs, deps);
|
||||
if (model.status === 'back' && backendChoice.prompted) {
|
||||
attemptArgs = buildInteractiveRetryArgs(args);
|
||||
continue;
|
||||
}
|
||||
if (model.status === 'invalid-credential') {
|
||||
return { status: 'failed', projectDir: args.projectDir };
|
||||
}
|
||||
if (model.status !== 'ready') {
|
||||
return { status: model.status, projectDir: args.projectDir };
|
||||
}
|
||||
const preset = presetForBackend('claude-code');
|
||||
const probe = deps.claudeCodeAuthProbe ?? runClaudeCodeAuthProbe;
|
||||
const health = await probe({ projectDir: args.projectDir, model: model.model, env: deps.env ?? process.env });
|
||||
if (!health.ok) {
|
||||
io.stderr.write(`${health.message}\n`);
|
||||
const validation = await validatePresetModels(
|
||||
preset,
|
||||
async (model) => probe({ projectDir: args.projectDir, model, env: deps.env ?? process.env }),
|
||||
io,
|
||||
);
|
||||
if (validation.status !== 'ready') {
|
||||
io.stderr.write(`${validation.message}\n`);
|
||||
return { status: 'failed', projectDir: args.projectDir };
|
||||
}
|
||||
const warning = formatClaudeCodePromptCachingWarning(
|
||||
ignoredClaudeCodePromptCachingFields(
|
||||
buildProjectLlmConfig(project.config.llm, { backend: 'claude-code' }, model.model),
|
||||
buildProjectLlmConfig(project.config.llm, { backend: 'claude-code' }, validation.models),
|
||||
),
|
||||
);
|
||||
if (warning) {
|
||||
io.stderr.write(`${warning}\n`);
|
||||
}
|
||||
await persistLlmConfig(args.projectDir, { backend: 'claude-code' }, model.model);
|
||||
io.stdout.write(`│ LLM ready: yes (${model.model})\n`);
|
||||
await persistLlmConfig(args.projectDir, { backend: 'claude-code' }, validation.models);
|
||||
io.stdout.write(`│ LLM ready: yes (${validation.models.default})\n`);
|
||||
return { status: 'ready', projectDir: args.projectDir };
|
||||
}
|
||||
|
||||
if (backendChoice.backend === 'codex') {
|
||||
const model = await chooseCodexModel(backendArgs, deps);
|
||||
if (model.status === 'back' && backendChoice.prompted) {
|
||||
attemptArgs = buildInteractiveRetryArgs(args);
|
||||
continue;
|
||||
}
|
||||
if (model.status === 'invalid-credential') {
|
||||
return { status: 'failed', projectDir: args.projectDir };
|
||||
}
|
||||
if (model.status !== 'ready') {
|
||||
return { status: model.status, projectDir: args.projectDir };
|
||||
}
|
||||
const preset = presetForBackend('codex');
|
||||
const probe = deps.codexAuthProbe ?? runCodexAuthProbe;
|
||||
const health = await probe({ projectDir: args.projectDir, model: model.model });
|
||||
if (!health.ok) {
|
||||
io.stderr.write(`${health.message}\n`);
|
||||
const validation = await validatePresetModels(preset, async (model) => probe({ projectDir: args.projectDir, model }), io);
|
||||
if (validation.status !== 'ready') {
|
||||
io.stderr.write(`${validation.message}\n`);
|
||||
return { status: 'failed', projectDir: args.projectDir };
|
||||
}
|
||||
// Prefix the clack gutter so the warning sits inside the setup frame
|
||||
// instead of breaking out of it; kept on stderr for scripted runs.
|
||||
io.stderr.write(`│ ${formatCodexIsolationWarning()}\n`);
|
||||
await persistLlmConfig(args.projectDir, { backend: 'codex' }, model.model);
|
||||
io.stdout.write(`│ LLM ready: yes (codex, ${model.model})\n`);
|
||||
await persistLlmConfig(args.projectDir, { backend: 'codex' }, validation.models);
|
||||
io.stdout.write(`│ LLM ready: yes (codex, ${validation.models.default})\n`);
|
||||
return { status: 'ready', projectDir: args.projectDir };
|
||||
}
|
||||
|
||||
|
|
@ -1138,8 +903,21 @@ export async function runKtxSetupAnthropicModelStep(
|
|||
return { status: credential.status, projectDir: args.projectDir };
|
||||
}
|
||||
|
||||
const model = await chooseModel(backendArgs, credential.value, io, deps);
|
||||
if (model.status === 'invalid-credential') {
|
||||
const preset = presetForBackend('anthropic');
|
||||
const validation = await validatePresetModels(
|
||||
preset,
|
||||
async (model) =>
|
||||
runLlmHealthCheckWithProgress(
|
||||
buildAnthropicHealthConfig(credential.value, model),
|
||||
'Anthropic API',
|
||||
model,
|
||||
healthCheck,
|
||||
deps,
|
||||
),
|
||||
io,
|
||||
);
|
||||
if (validation.status !== 'ready') {
|
||||
io.stderr.write(`Anthropic model health check failed: ${validation.message}\n`);
|
||||
if (args.inputMode === 'disabled') {
|
||||
return { status: 'failed', projectDir: args.projectDir };
|
||||
}
|
||||
|
|
@ -1147,32 +925,9 @@ export async function runKtxSetupAnthropicModelStep(
|
|||
attemptArgs = buildInteractiveRetryArgs(args, backendChoice.backend);
|
||||
continue;
|
||||
}
|
||||
if (model.status === 'back' && !backendArgs.anthropicApiKeyEnv && !backendArgs.anthropicApiKeyFile) {
|
||||
attemptArgs = buildInteractiveRetryArgs(args, backendChoice.backend);
|
||||
continue;
|
||||
}
|
||||
if (model.status !== 'ready') {
|
||||
return { status: model.status, projectDir: args.projectDir };
|
||||
}
|
||||
|
||||
const health = await runLlmHealthCheckWithProgress(
|
||||
buildAnthropicHealthConfig(credential.value, model.model),
|
||||
'Anthropic API',
|
||||
model.model,
|
||||
healthCheck,
|
||||
deps,
|
||||
);
|
||||
if (health.ok) {
|
||||
await persistLlmConfig(args.projectDir, { backend: 'anthropic', credentialRef: credential.ref }, model.model);
|
||||
io.stdout.write(`│ LLM ready: yes (${model.model})\n`);
|
||||
return { status: 'ready', projectDir: args.projectDir };
|
||||
}
|
||||
|
||||
io.stderr.write(`Anthropic model health check failed: ${health.message}\n`);
|
||||
if (args.inputMode === 'disabled') {
|
||||
return { status: 'failed', projectDir: args.projectDir };
|
||||
}
|
||||
io.stderr.write('Choose a different credential source or model, or Back.\n');
|
||||
attemptArgs = buildInteractiveRetryArgs(args, backendChoice.backend);
|
||||
await persistLlmConfig(args.projectDir, { backend: 'anthropic', credentialRef: credential.ref }, validation.models);
|
||||
io.stdout.write(`│ LLM ready: yes (${validation.models.default})\n`);
|
||||
return { status: 'ready', projectDir: args.projectDir };
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -86,7 +86,6 @@ export type KtxSetupArgs =
|
|||
llmBackend?: KtxSetupLlmBackend;
|
||||
anthropicApiKeyEnv?: string;
|
||||
anthropicApiKeyFile?: string;
|
||||
llmModel?: string;
|
||||
vertexProject?: string;
|
||||
vertexLocation?: string;
|
||||
skipLlm: boolean;
|
||||
|
|
@ -700,7 +699,6 @@ async function runKtxSetupInner(args: KtxSetupArgs, io: KtxCliIo, deps: KtxSetup
|
|||
...(args.llmBackend ? { llmBackend: args.llmBackend } : {}),
|
||||
...(args.anthropicApiKeyEnv ? { anthropicApiKeyEnv: args.anthropicApiKeyEnv } : {}),
|
||||
...(args.anthropicApiKeyFile ? { anthropicApiKeyFile: args.anthropicApiKeyFile } : {}),
|
||||
...(args.llmModel ? { llmModel: args.llmModel } : {}),
|
||||
...(args.vertexProject ? { vertexProject: args.vertexProject } : {}),
|
||||
...(args.vertexLocation ? { vertexLocation: args.vertexLocation } : {}),
|
||||
forcePrompt: forcePromptSteps.has('models') || runOnly === 'models',
|
||||
|
|
|
|||
|
|
@ -1,6 +1,5 @@
|
|||
import { readFile } from 'node:fs/promises';
|
||||
import type { KtxCliIo } from './cli-runtime.js';
|
||||
import { createDefaultLocalQueryExecutor } from './context/connections/local-query-executor.js';
|
||||
import type { KtxSqlQueryExecutorPort } from './context/connections/query-executor.js';
|
||||
import { KtxIngestEmbeddingPortAdapter } from './context/llm/embedding-port.js';
|
||||
import type { KtxEmbeddingPort } from './context/core/embedding.js';
|
||||
|
|
@ -20,6 +19,7 @@ import {
|
|||
resolveProjectEmbeddingProvider,
|
||||
type EmbeddingProviderResolution,
|
||||
} from './embedding-resolution.js';
|
||||
import { createKtxCliIngestQueryExecutor } from './ingest-query-executor.js';
|
||||
import type { PrintListColumn } from './io/print-list.js';
|
||||
import {
|
||||
createManagedPythonSemanticLayerComputePort,
|
||||
|
|
@ -81,7 +81,7 @@ interface KtxSlDeps {
|
|||
io: KtxSlIo;
|
||||
projectDir?: string;
|
||||
}) => Promise<KtxSemanticLayerComputePort>;
|
||||
createQueryExecutor?: () => KtxSqlQueryExecutorPort;
|
||||
createQueryExecutor?: (project: KtxLocalProject) => KtxSqlQueryExecutorPort;
|
||||
}
|
||||
|
||||
function resolutionToEmbeddingPort(resolution: EmbeddingProviderResolution): KtxEmbeddingPort | null {
|
||||
|
|
@ -321,7 +321,7 @@ export async function runKtxSl(args: KtxSlArgs, io: KtxSlIo = process, deps: Ktx
|
|||
io,
|
||||
projectDir: args.projectDir,
|
||||
});
|
||||
const queryExecutor = args.execute ? (deps.createQueryExecutor ?? createDefaultLocalQueryExecutor)() : undefined;
|
||||
const queryExecutor = args.execute ? (deps.createQueryExecutor ?? createKtxCliIngestQueryExecutor)(project) : undefined;
|
||||
const result = await compileLocalSlQuery(project, {
|
||||
connectionId: args.connectionId,
|
||||
query,
|
||||
|
|
|
|||
|
|
@ -68,7 +68,6 @@ const connectionFixtures: Record<KtxConnectionDriver, FixtureFactory> = {
|
|||
|
||||
const allowedScopeKeys = new Set(['dataset_ids', 'databases', 'schemas', 'schema_names']);
|
||||
const historicSqlReaderDrivers = new Set<KtxConnectionDriver>(['postgres', 'bigquery', 'snowflake']);
|
||||
const localExecutorDrivers = new Set<KtxConnectionDriver>(['postgres', 'sqlite']);
|
||||
|
||||
function assertExportedRegistryBoundaryTypes(input: {
|
||||
scopeConfigKey: KtxScopeConfigKey;
|
||||
|
|
@ -140,6 +139,5 @@ describe('driverRegistrations', () => {
|
|||
expect(allowedScopeKeys.has(registration.scopeConfigKey ?? '')).toBe(true);
|
||||
}
|
||||
expect(registration.hasHistoricSqlReader).toBe(historicSqlReaderDrivers.has(registration.driver));
|
||||
expect(registration.hasLocalQueryExecutor).toBe(localExecutorDrivers.has(registration.driver));
|
||||
});
|
||||
});
|
||||
|
|
|
|||
|
|
@ -1,59 +0,0 @@
|
|||
import { describe, expect, it, vi } from 'vitest';
|
||||
import { createDefaultLocalQueryExecutor } from '../../../src/context/connections/local-query-executor.js';
|
||||
|
||||
describe('createDefaultLocalQueryExecutor', () => {
|
||||
it('dispatches postgres and sqlite drivers to their executors', async () => {
|
||||
const postgres = {
|
||||
execute: vi.fn(async () => ({
|
||||
headers: ['pg'],
|
||||
rows: [[1]],
|
||||
totalRows: 1,
|
||||
command: 'SELECT',
|
||||
rowCount: 1,
|
||||
})),
|
||||
};
|
||||
const sqlite = {
|
||||
execute: vi.fn(async () => ({
|
||||
headers: ['sqlite'],
|
||||
rows: [[2]],
|
||||
totalRows: 1,
|
||||
command: 'SELECT',
|
||||
rowCount: 1,
|
||||
})),
|
||||
};
|
||||
const executor = createDefaultLocalQueryExecutor({ postgres, sqlite });
|
||||
|
||||
await expect(
|
||||
executor.execute({
|
||||
connectionId: 'pg',
|
||||
connection: { driver: 'postgres' },
|
||||
sql: 'select 1',
|
||||
}),
|
||||
).resolves.toMatchObject({ headers: ['pg'] });
|
||||
await expect(
|
||||
executor.execute({
|
||||
connectionId: 'local',
|
||||
connection: { driver: 'sqlite' },
|
||||
sql: 'select 1',
|
||||
}),
|
||||
).resolves.toMatchObject({ headers: ['sqlite'] });
|
||||
|
||||
expect(postgres.execute).toHaveBeenCalledTimes(1);
|
||||
expect(sqlite.execute).toHaveBeenCalledTimes(1);
|
||||
});
|
||||
|
||||
it('rejects unsupported local execution drivers', async () => {
|
||||
const executor = createDefaultLocalQueryExecutor({
|
||||
postgres: { execute: vi.fn() },
|
||||
sqlite: { execute: vi.fn() },
|
||||
});
|
||||
|
||||
await expect(
|
||||
executor.execute({
|
||||
connectionId: 'warehouse',
|
||||
connection: { driver: 'snowflake' },
|
||||
sql: 'select 1',
|
||||
}),
|
||||
).rejects.toThrow('No local query executor is configured for driver "snowflake".');
|
||||
});
|
||||
});
|
||||
|
|
@ -1,103 +0,0 @@
|
|||
import { describe, expect, it, vi } from 'vitest';
|
||||
import { createPostgresQueryExecutor } from '../../../src/context/connections/postgres-query-executor.js';
|
||||
|
||||
function makeClient() {
|
||||
const calls: unknown[] = [];
|
||||
const client = {
|
||||
connect: vi.fn(async () => undefined),
|
||||
query: vi.fn(async (input: unknown) => {
|
||||
calls.push(input);
|
||||
if (input === 'BEGIN READ ONLY') {
|
||||
return { rows: [], fields: [], rowCount: null, command: 'BEGIN' };
|
||||
}
|
||||
if (input === 'COMMIT') {
|
||||
return { rows: [], fields: [], rowCount: null, command: 'COMMIT' };
|
||||
}
|
||||
return {
|
||||
rows: [
|
||||
['paid', 2],
|
||||
['open', 1],
|
||||
],
|
||||
fields: [{ name: 'status' }, { name: 'order_count' }],
|
||||
rowCount: 2,
|
||||
command: 'SELECT',
|
||||
};
|
||||
}),
|
||||
end: vi.fn(async () => undefined),
|
||||
};
|
||||
return { client, calls };
|
||||
}
|
||||
|
||||
describe('createPostgresQueryExecutor', () => {
|
||||
it('runs a read-only transaction in array row mode and closes the client', async () => {
|
||||
const { client, calls } = makeClient();
|
||||
const executor = createPostgresQueryExecutor({
|
||||
clientFactory: vi.fn(() => client),
|
||||
});
|
||||
|
||||
const result = await executor.execute({
|
||||
connectionId: 'warehouse',
|
||||
connection: { driver: 'postgres', url: 'postgres://example/db' },
|
||||
sql: 'select status, count(*) as order_count from public.orders group by status',
|
||||
maxRows: 50,
|
||||
});
|
||||
|
||||
expect(client.connect).toHaveBeenCalledTimes(1);
|
||||
expect(calls[0]).toBe('BEGIN READ ONLY');
|
||||
expect(calls[1]).toEqual({
|
||||
text: 'select * from (select status, count(*) as order_count from public.orders group by status) as ktx_query_result limit 50',
|
||||
rowMode: 'array',
|
||||
});
|
||||
expect(calls[2]).toBe('COMMIT');
|
||||
expect(client.end).toHaveBeenCalledTimes(1);
|
||||
expect(result).toEqual({
|
||||
headers: ['status', 'order_count'],
|
||||
rows: [
|
||||
['paid', 2],
|
||||
['open', 1],
|
||||
],
|
||||
totalRows: 2,
|
||||
command: 'SELECT',
|
||||
rowCount: 2,
|
||||
});
|
||||
});
|
||||
|
||||
it('rolls back and closes the client when query execution fails', async () => {
|
||||
const client = {
|
||||
connect: vi.fn(async () => undefined),
|
||||
query: vi.fn(async (input: unknown) => {
|
||||
if (input === 'BEGIN READ ONLY' || input === 'ROLLBACK') {
|
||||
return { rows: [], fields: [], rowCount: null, command: String(input) };
|
||||
}
|
||||
throw new Error('syntax error');
|
||||
}),
|
||||
end: vi.fn(async () => undefined),
|
||||
};
|
||||
const executor = createPostgresQueryExecutor({
|
||||
clientFactory: vi.fn(() => client),
|
||||
});
|
||||
|
||||
await expect(
|
||||
executor.execute({
|
||||
connectionId: 'warehouse',
|
||||
connection: { driver: 'postgres', url: 'postgres://example/db' },
|
||||
sql: 'select * from broken',
|
||||
maxRows: 10,
|
||||
}),
|
||||
).rejects.toThrow('syntax error');
|
||||
expect(client.query).toHaveBeenCalledWith('ROLLBACK');
|
||||
expect(client.end).toHaveBeenCalledTimes(1);
|
||||
});
|
||||
|
||||
it('requires a Postgres url', async () => {
|
||||
const executor = createPostgresQueryExecutor({ clientFactory: vi.fn() });
|
||||
|
||||
await expect(
|
||||
executor.execute({
|
||||
connectionId: 'warehouse',
|
||||
connection: { driver: 'postgres' },
|
||||
sql: 'select 1',
|
||||
}),
|
||||
).rejects.toThrow('Local Postgres execution requires connections.warehouse.url');
|
||||
});
|
||||
});
|
||||
|
|
@ -1,139 +0,0 @@
|
|||
import { mkdtemp, rm } from 'node:fs/promises';
|
||||
import { writeFileSync } from 'node:fs';
|
||||
import { tmpdir } from 'node:os';
|
||||
import { join } from 'node:path';
|
||||
import Database from 'better-sqlite3';
|
||||
import { afterEach, beforeEach, describe, expect, it } from 'vitest';
|
||||
import { createSqliteQueryExecutor, sqliteDatabasePathFromConnection } from '../../../src/context/connections/sqlite-query-executor.js';
|
||||
|
||||
describe('createSqliteQueryExecutor', () => {
|
||||
let tempDir: string;
|
||||
let dbPath: string;
|
||||
|
||||
beforeEach(async () => {
|
||||
tempDir = await mkdtemp(join(tmpdir(), 'ktx-sqlite-query-'));
|
||||
dbPath = join(tempDir, 'warehouse.db');
|
||||
const db = new Database(dbPath);
|
||||
db.exec(`
|
||||
CREATE TABLE orders (
|
||||
id INTEGER PRIMARY KEY,
|
||||
status TEXT NOT NULL,
|
||||
amount INTEGER NOT NULL
|
||||
);
|
||||
INSERT INTO orders (status, amount) VALUES
|
||||
('paid', 20),
|
||||
('paid', 30),
|
||||
('open', 10);
|
||||
`);
|
||||
db.close();
|
||||
});
|
||||
|
||||
afterEach(async () => {
|
||||
await rm(tempDir, { recursive: true, force: true });
|
||||
});
|
||||
|
||||
it('executes read-only SELECT SQL against a relative SQLite path', async () => {
|
||||
const executor = createSqliteQueryExecutor();
|
||||
|
||||
const result = await executor.execute({
|
||||
connectionId: 'warehouse',
|
||||
projectDir: tempDir,
|
||||
connection: { driver: 'sqlite', path: 'warehouse.db' },
|
||||
sql: 'select status, count(*) as order_count from orders group by status order by status',
|
||||
maxRows: 10,
|
||||
});
|
||||
|
||||
expect(result).toEqual({
|
||||
headers: ['status', 'order_count'],
|
||||
rows: [
|
||||
['open', 1],
|
||||
['paid', 2],
|
||||
],
|
||||
totalRows: 2,
|
||||
command: 'SELECT',
|
||||
rowCount: 2,
|
||||
});
|
||||
});
|
||||
|
||||
it('supports file urls for SQLite database paths', async () => {
|
||||
expect(
|
||||
sqliteDatabasePathFromConnection({
|
||||
connectionId: 'warehouse',
|
||||
projectDir: tempDir,
|
||||
connection: { driver: 'sqlite', url: `file://${dbPath}` },
|
||||
sql: 'select 1',
|
||||
}),
|
||||
).toBe(dbPath);
|
||||
});
|
||||
|
||||
it('resolves file references for SQLite path fields', async () => {
|
||||
const pointerPath = join(tempDir, 'sqlite-path.txt');
|
||||
writeFileSync(pointerPath, dbPath, 'utf-8');
|
||||
|
||||
expect(
|
||||
sqliteDatabasePathFromConnection({
|
||||
connectionId: 'warehouse',
|
||||
projectDir: tempDir,
|
||||
connection: { driver: 'sqlite', path: `file:${pointerPath}` },
|
||||
sql: 'select 1',
|
||||
}),
|
||||
).toBe(dbPath);
|
||||
});
|
||||
|
||||
it('resolves env references for SQLite database urls', async () => {
|
||||
const originalDatabaseUrl = process.env.KTX_SQLITE_TEST_URL;
|
||||
process.env.KTX_SQLITE_TEST_URL = `sqlite:${dbPath}`;
|
||||
|
||||
try {
|
||||
expect(
|
||||
sqliteDatabasePathFromConnection({
|
||||
connectionId: 'warehouse',
|
||||
projectDir: tempDir,
|
||||
connection: { driver: 'sqlite', url: 'env:KTX_SQLITE_TEST_URL' },
|
||||
sql: 'select 1',
|
||||
}),
|
||||
).toBe(dbPath);
|
||||
} finally {
|
||||
if (originalDatabaseUrl === undefined) {
|
||||
delete process.env.KTX_SQLITE_TEST_URL;
|
||||
} else {
|
||||
process.env.KTX_SQLITE_TEST_URL = originalDatabaseUrl;
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
it('rejects mutating SQL before opening the database', async () => {
|
||||
const executor = createSqliteQueryExecutor();
|
||||
|
||||
await expect(
|
||||
executor.execute({
|
||||
connectionId: 'warehouse',
|
||||
projectDir: tempDir,
|
||||
connection: { driver: 'sqlite', path: 'warehouse.db' },
|
||||
sql: 'delete from orders',
|
||||
}),
|
||||
).rejects.toThrow('Only read-only SELECT/WITH queries can be executed locally');
|
||||
});
|
||||
|
||||
it('requires a SQLite driver and a database path', async () => {
|
||||
const executor = createSqliteQueryExecutor();
|
||||
|
||||
await expect(
|
||||
executor.execute({
|
||||
connectionId: 'warehouse',
|
||||
projectDir: tempDir,
|
||||
connection: { driver: 'postgres', path: 'warehouse.db' },
|
||||
sql: 'select 1',
|
||||
}),
|
||||
).rejects.toThrow('Local SQLite execution cannot run driver "postgres"');
|
||||
|
||||
await expect(
|
||||
executor.execute({
|
||||
connectionId: 'warehouse',
|
||||
projectDir: tempDir,
|
||||
connection: { driver: 'sqlite' },
|
||||
sql: 'select 1',
|
||||
}),
|
||||
).rejects.toThrow('Local SQLite execution requires connections.warehouse.path or connections.warehouse.url');
|
||||
});
|
||||
});
|
||||
|
|
@ -80,8 +80,8 @@ describe('createLocalBundleIngestRuntime', () => {
|
|||
'ktx ingest requires llm.provider.backend: anthropic, vertex, gateway, claude-code, or codex, or an injected agentRunner.',
|
||||
'Configure a local Claude Code/Codex session or API-backed LLM, then rerun ingest:',
|
||||
` ktx setup --project-dir ${project.projectDir} --llm-backend claude-code --no-input`,
|
||||
` ktx setup --project-dir ${project.projectDir} --llm-backend codex --llm-model gpt-5.5 --no-input`,
|
||||
` ktx setup --project-dir ${project.projectDir} --llm-backend anthropic --anthropic-api-key-env ANTHROPIC_API_KEY --llm-model claude-sonnet-4-6 --no-input`,
|
||||
` ktx setup --project-dir ${project.projectDir} --llm-backend codex --no-input`,
|
||||
` ktx setup --project-dir ${project.projectDir} --llm-backend anthropic --anthropic-api-key-env ANTHROPIC_API_KEY --no-input`,
|
||||
].join('\n'),
|
||||
);
|
||||
});
|
||||
|
|
|
|||
|
|
@ -1136,8 +1136,6 @@ describe('runKtxCli', () => {
|
|||
'--no-input',
|
||||
'--anthropic-api-key-env',
|
||||
'ANTHROPIC_API_KEY',
|
||||
'--llm-model',
|
||||
'claude-sonnet-4-6',
|
||||
],
|
||||
setupIo.io,
|
||||
{ setup },
|
||||
|
|
@ -1151,7 +1149,6 @@ describe('runKtxCli', () => {
|
|||
inputMode: 'disabled',
|
||||
cliVersion,
|
||||
anthropicApiKeyEnv: 'ANTHROPIC_API_KEY', // pragma: allowlist secret
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
}),
|
||||
setupIo.io,
|
||||
|
|
@ -1175,8 +1172,6 @@ describe('runKtxCli', () => {
|
|||
'local-gcp-project',
|
||||
'--vertex-location',
|
||||
'us-east5',
|
||||
'--llm-model',
|
||||
'claude-sonnet-4-6',
|
||||
],
|
||||
setupIo.io,
|
||||
{ setup },
|
||||
|
|
@ -1192,14 +1187,13 @@ describe('runKtxCli', () => {
|
|||
llmBackend: 'vertex',
|
||||
vertexProject: 'local-gcp-project',
|
||||
vertexLocation: 'us-east5',
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
}),
|
||||
setupIo.io,
|
||||
);
|
||||
});
|
||||
|
||||
it('dispatches the provider-neutral LLM model setup flag to the setup runner', async () => {
|
||||
it('rejects the removed --llm-model setup flag', async () => {
|
||||
const setup = vi.fn(async () => 0);
|
||||
const setupIo = makeIo();
|
||||
|
||||
|
|
@ -1218,20 +1212,10 @@ describe('runKtxCli', () => {
|
|||
setupIo.io,
|
||||
{ setup },
|
||||
),
|
||||
).resolves.toBe(0);
|
||||
).resolves.toBe(1);
|
||||
|
||||
expect(setup).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
command: 'run',
|
||||
projectDir: tempDir,
|
||||
inputMode: 'disabled',
|
||||
cliVersion,
|
||||
llmBackend: 'claude-code',
|
||||
llmModel: 'opus',
|
||||
skipLlm: false,
|
||||
}),
|
||||
setupIo.io,
|
||||
);
|
||||
expect(setup).not.toHaveBeenCalled();
|
||||
expect(setupIo.stderr()).toContain("unknown option '--llm-model'");
|
||||
});
|
||||
|
||||
it('rejects conflicting Anthropic credential setup flags', async () => {
|
||||
|
|
|
|||
|
|
@ -341,11 +341,9 @@ describe('runKtxIngest', () => {
|
|||
);
|
||||
expect(runIo.stderr()).toContain('Configure a local Claude Code/Codex session or API-backed LLM, then rerun ingest:');
|
||||
expect(runIo.stderr()).toContain(`ktx setup --project-dir ${projectDir} --llm-backend claude-code --no-input`);
|
||||
expect(runIo.stderr()).toContain(`ktx setup --project-dir ${projectDir} --llm-backend codex --no-input`);
|
||||
expect(runIo.stderr()).toContain(
|
||||
`ktx setup --project-dir ${projectDir} --llm-backend codex --llm-model gpt-5.5 --no-input`,
|
||||
);
|
||||
expect(runIo.stderr()).toContain(
|
||||
`ktx setup --project-dir ${projectDir} --llm-backend anthropic --anthropic-api-key-env ANTHROPIC_API_KEY --llm-model claude-sonnet-4-6 --no-input`,
|
||||
`ktx setup --project-dir ${projectDir} --llm-backend anthropic --anthropic-api-key-env ANTHROPIC_API_KEY --no-input`,
|
||||
);
|
||||
});
|
||||
|
||||
|
|
|
|||
|
|
@ -6,8 +6,6 @@ import { parseKtxProjectConfig } from '../src/context/project/config.js';
|
|||
import { readKtxSetupState, writeKtxSetupState } from '../src/context/project/setup-config.js';
|
||||
import { afterEach, beforeEach, describe, expect, it, vi } from 'vitest';
|
||||
import {
|
||||
BUNDLED_ANTHROPIC_MODELS,
|
||||
fetchAnthropicModels,
|
||||
type KtxSetupModelPromptAdapter,
|
||||
runKtxSetupAnthropicModelStep,
|
||||
} from '../src/setup-models.js';
|
||||
|
|
@ -97,6 +95,33 @@ function makePromptAdapter(options: {
|
|||
};
|
||||
}
|
||||
|
||||
const anthropicPreset = {
|
||||
default: 'claude-sonnet-4-6',
|
||||
triage: 'claude-haiku-4-5',
|
||||
candidateExtraction: 'claude-sonnet-4-6',
|
||||
curator: 'claude-opus-4-7',
|
||||
reconcile: 'claude-opus-4-7',
|
||||
repair: 'claude-haiku-4-5',
|
||||
};
|
||||
|
||||
const claudeCodePreset = {
|
||||
default: 'sonnet',
|
||||
triage: 'haiku',
|
||||
candidateExtraction: 'sonnet',
|
||||
curator: 'opus',
|
||||
reconcile: 'opus',
|
||||
repair: 'haiku',
|
||||
};
|
||||
|
||||
const codexPreset = {
|
||||
default: 'gpt-5.5',
|
||||
triage: 'gpt-5.5',
|
||||
candidateExtraction: 'gpt-5.5',
|
||||
curator: 'gpt-5.5',
|
||||
reconcile: 'gpt-5.5',
|
||||
repair: 'gpt-5.5',
|
||||
};
|
||||
|
||||
describe('setup Anthropic model step', () => {
|
||||
let tempDir: string;
|
||||
|
||||
|
|
@ -109,66 +134,6 @@ describe('setup Anthropic model step', () => {
|
|||
await rm(tempDir, { recursive: true, force: true });
|
||||
});
|
||||
|
||||
it('does not expose Claude Sonnet 4 or Claude Opus 4 as selectable Anthropic models', async () => {
|
||||
const fetchModels = vi.fn(
|
||||
async () =>
|
||||
new Response(
|
||||
JSON.stringify({
|
||||
data: [
|
||||
{ id: 'claude-sonnet-4', display_name: 'Claude Sonnet 4' },
|
||||
{ id: 'claude-opus-4', display_name: 'Claude Opus 4' },
|
||||
{ id: 'claude-sonnet-4-6', display_name: 'Claude Sonnet 4.6' },
|
||||
{ id: 'claude-opus-4-6', display_name: 'Claude Opus 4.6' },
|
||||
{ id: 'claude-haiku-4-5', display_name: 'Claude Haiku 4.5' },
|
||||
],
|
||||
}),
|
||||
{ status: 200 },
|
||||
),
|
||||
);
|
||||
|
||||
await expect(fetchAnthropicModels('sk-ant-test', fetchModels)).resolves.toEqual([ // pragma: allowlist secret
|
||||
{ id: 'claude-sonnet-4-6', label: 'Claude Sonnet 4.6', recommended: true },
|
||||
{ id: 'claude-opus-4-6', label: 'Claude Opus 4.6', recommended: false },
|
||||
{ id: 'claude-haiku-4-5', label: 'Claude Haiku 4.5', recommended: false },
|
||||
]);
|
||||
expect(BUNDLED_ANTHROPIC_MODELS.map((model) => model.id)).not.toEqual(
|
||||
expect.arrayContaining(['claude-sonnet-4', 'claude-opus-4']),
|
||||
);
|
||||
});
|
||||
|
||||
it('filters Claude Sonnet 4 and Claude Opus 4 from Anthropic model prompt choices', async () => {
|
||||
const prompts = makePromptAdapter({ selectValues: ['env', 'back', 'back'] });
|
||||
|
||||
await runKtxSetupAnthropicModelStep(
|
||||
{ projectDir: tempDir, inputMode: 'auto', skipLlm: false },
|
||||
makeIo().io,
|
||||
{
|
||||
prompts,
|
||||
env: { ANTHROPIC_API_KEY: 'sk-ant-test' }, // pragma: allowlist secret
|
||||
listModels: vi.fn(async () => [
|
||||
{ id: 'claude-sonnet-4', label: 'Claude Sonnet 4', recommended: true },
|
||||
{ id: 'claude-opus-4', label: 'Claude Opus 4', recommended: false },
|
||||
{ id: 'claude-sonnet-4-6', label: 'Claude Sonnet 4.6', recommended: true },
|
||||
{ id: 'claude-opus-4-6', label: 'Claude Opus 4.6', recommended: false },
|
||||
{ id: 'claude-haiku-4-5', label: 'Claude Haiku 4.5', recommended: false },
|
||||
]),
|
||||
},
|
||||
);
|
||||
|
||||
expect(prompts.autocomplete).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which Anthropic model should KTX use?'),
|
||||
options: [
|
||||
{ value: 'claude-sonnet-4-6', label: 'Claude Sonnet 4.6', hint: 'recommended' },
|
||||
{ value: 'claude-opus-4-6', label: 'Claude Opus 4.6' },
|
||||
{ value: 'claude-haiku-4-5', label: 'Claude Haiku 4.5' },
|
||||
{ value: 'manual', label: 'Enter a model ID manually' },
|
||||
{ value: 'back', label: 'Back' },
|
||||
],
|
||||
}),
|
||||
);
|
||||
});
|
||||
|
||||
it('offers Anthropic provider paths in the preferred order', async () => {
|
||||
const prompts = makePromptAdapter({ providerChoice: 'back' });
|
||||
|
||||
|
|
@ -212,9 +177,38 @@ describe('setup Anthropic model step', () => {
|
|||
const config = parseKtxProjectConfig(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8'));
|
||||
expect(config.llm).toMatchObject({
|
||||
provider: { backend: 'claude-code' },
|
||||
models: { default: 'sonnet' },
|
||||
models: claudeCodePreset,
|
||||
});
|
||||
expect(authProbe).toHaveBeenCalledWith(expect.objectContaining({ projectDir: tempDir, model: 'sonnet' }));
|
||||
expect(authProbe).toHaveBeenCalledTimes(3);
|
||||
expect(authProbe).toHaveBeenNthCalledWith(1, expect.objectContaining({ projectDir: tempDir, model: 'sonnet' }));
|
||||
expect(authProbe).toHaveBeenNthCalledWith(2, expect.objectContaining({ projectDir: tempDir, model: 'haiku' }));
|
||||
expect(authProbe).toHaveBeenNthCalledWith(3, expect.objectContaining({ projectDir: tempDir, model: 'opus' }));
|
||||
});
|
||||
|
||||
it('does not prompt for a Claude Code model during interactive setup', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({ selectValues: ['claude-code'] });
|
||||
const authProbe = vi.fn(async () => ({ ok: true as const }));
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
{ projectDir: tempDir, inputMode: 'auto', skipLlm: false },
|
||||
io.io,
|
||||
{ prompts, claudeCodeAuthProbe: authProbe },
|
||||
);
|
||||
|
||||
expect(result.status).toBe('ready');
|
||||
expect(prompts.select).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which LLM provider should KTX use?'),
|
||||
}),
|
||||
);
|
||||
expect(prompts.select).not.toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which Claude Code model should KTX use?'),
|
||||
}),
|
||||
);
|
||||
const config = parseKtxProjectConfig(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8'));
|
||||
expect(config.llm.models).toMatchObject(claudeCodePreset);
|
||||
});
|
||||
|
||||
it('configures Codex backend and validates local auth', async () => {
|
||||
|
|
@ -226,7 +220,6 @@ describe('setup Anthropic model step', () => {
|
|||
projectDir: tempDir,
|
||||
inputMode: 'disabled',
|
||||
llmBackend: 'codex',
|
||||
llmModel: 'gpt-5.5',
|
||||
skipLlm: false,
|
||||
},
|
||||
io.io,
|
||||
|
|
@ -237,8 +230,9 @@ describe('setup Anthropic model step', () => {
|
|||
const config = parseKtxProjectConfig(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8'));
|
||||
expect(config.llm).toMatchObject({
|
||||
provider: { backend: 'codex' },
|
||||
models: { default: 'gpt-5.5' },
|
||||
models: codexPreset,
|
||||
});
|
||||
expect(codexAuthProbe).toHaveBeenCalledTimes(1);
|
||||
expect(codexAuthProbe).toHaveBeenCalledWith(expect.objectContaining({ projectDir: tempDir, model: 'gpt-5.5' }));
|
||||
// The warning carries the clack gutter so it renders inside the setup frame.
|
||||
expect(io.stderr()).toContain('│ Codex backend isolation is limited');
|
||||
|
|
@ -264,70 +258,12 @@ describe('setup Anthropic model step', () => {
|
|||
const config = parseKtxProjectConfig(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8'));
|
||||
expect(config.llm).toMatchObject({
|
||||
provider: { backend: 'codex' },
|
||||
models: { default: 'gpt-5.5' },
|
||||
models: codexPreset,
|
||||
});
|
||||
expect(codexAuthProbe).toHaveBeenCalledTimes(1);
|
||||
expect(codexAuthProbe).toHaveBeenCalledWith(expect.objectContaining({ projectDir: tempDir, model: 'gpt-5.5' }));
|
||||
});
|
||||
|
||||
it('offers the curated Codex models during interactive setup', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({ selectValues: ['codex', 'gpt-5.5'] });
|
||||
const codexAuthProbe = vi.fn(async () => ({ ok: true as const }));
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
{ projectDir: tempDir, inputMode: 'auto', skipLlm: false },
|
||||
io.io,
|
||||
{ prompts, codexAuthProbe },
|
||||
);
|
||||
|
||||
expect(result.status).toBe('ready');
|
||||
expect(prompts.select).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which Codex model should KTX use?'),
|
||||
options: [
|
||||
{ value: 'gpt-5.5', label: 'GPT-5.5', hint: 'recommended' },
|
||||
{ value: 'gpt-5.4', label: 'GPT-5.4' },
|
||||
{ value: 'gpt-5.4-mini', label: 'GPT-5.4 mini' },
|
||||
{ value: 'manual', label: 'Enter a Codex model ID manually' },
|
||||
{ value: 'back', label: 'Back' },
|
||||
],
|
||||
}),
|
||||
);
|
||||
expect(codexAuthProbe).toHaveBeenCalledWith(expect.objectContaining({ model: 'gpt-5.5' }));
|
||||
});
|
||||
|
||||
it('prompts for the Claude Code model during interactive setup', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({ selectValues: ['claude-code', 'opus'] });
|
||||
const authProbe = vi.fn(async () => ({ ok: true as const }));
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
{ projectDir: tempDir, inputMode: 'auto', skipLlm: false },
|
||||
io.io,
|
||||
{ prompts, claudeCodeAuthProbe: authProbe },
|
||||
);
|
||||
|
||||
expect(result.status).toBe('ready');
|
||||
expect(prompts.select).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which Claude Code model should KTX use?'),
|
||||
options: [
|
||||
{ value: 'sonnet', label: 'Claude Sonnet', hint: 'recommended' },
|
||||
{ value: 'opus', label: 'Claude Opus' },
|
||||
{ value: 'haiku', label: 'Claude Haiku' },
|
||||
{ value: 'manual', label: 'Enter a Claude Code model ID manually' },
|
||||
{ value: 'back', label: 'Back' },
|
||||
],
|
||||
}),
|
||||
);
|
||||
const config = parseKtxProjectConfig(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8'));
|
||||
expect(config.llm).toMatchObject({
|
||||
provider: { backend: 'claude-code' },
|
||||
models: { default: 'opus' },
|
||||
});
|
||||
expect(authProbe).toHaveBeenCalledWith(expect.objectContaining({ projectDir: tempDir, model: 'opus' }));
|
||||
});
|
||||
|
||||
it('warns during Claude Code setup when existing prompt-caching fields will be ignored', async () => {
|
||||
await writeFile(
|
||||
join(tempDir, 'ktx.yaml'),
|
||||
|
|
@ -392,7 +328,6 @@ describe('setup Anthropic model step', () => {
|
|||
projectDir: tempDir,
|
||||
inputMode: 'disabled',
|
||||
anthropicApiKeyEnv: 'ANTHROPIC_API_KEY', // pragma: allowlist secret
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
},
|
||||
io.io,
|
||||
|
|
@ -410,7 +345,7 @@ describe('setup Anthropic model step', () => {
|
|||
backend: 'anthropic',
|
||||
anthropic: { api_key: 'env:ANTHROPIC_API_KEY' }, // pragma: allowlist secret
|
||||
},
|
||||
models: { default: 'claude-sonnet-4-6' },
|
||||
models: anthropicPreset,
|
||||
promptCaching: { enabled: true },
|
||||
});
|
||||
expect(config.scan.enrichment.mode).toBe('llm');
|
||||
|
|
@ -419,11 +354,62 @@ describe('setup Anthropic model step', () => {
|
|||
expect(spinnerEvents).toEqual([
|
||||
'start:Checking Anthropic API LLM (claude-sonnet-4-6).',
|
||||
'stop:LLM test passed (Anthropic API, claude-sonnet-4-6)',
|
||||
'start:Checking Anthropic API LLM (claude-haiku-4-5).',
|
||||
'stop:LLM test passed (Anthropic API, claude-haiku-4-5)',
|
||||
'start:Checking Anthropic API LLM (claude-opus-4-7).',
|
||||
'stop:LLM test passed (Anthropic API, claude-opus-4-7)',
|
||||
]);
|
||||
expect(io.stdout()).toContain('LLM ready: yes');
|
||||
expect(io.stdout()).not.toContain('sk-ant-test');
|
||||
});
|
||||
|
||||
it('degrades unavailable Anthropic non-anchor models to the anchor before persisting', async () => {
|
||||
const io = makeIo();
|
||||
const { events: spinnerEvents, spinner } = makeSpinnerEvents();
|
||||
const healthCheck = vi
|
||||
.fn()
|
||||
.mockResolvedValueOnce({ ok: true as const })
|
||||
.mockResolvedValueOnce({ ok: false as const, message: 'model not enabled' })
|
||||
.mockResolvedValueOnce({ ok: true as const });
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
{
|
||||
projectDir: tempDir,
|
||||
inputMode: 'disabled',
|
||||
anthropicApiKeyEnv: 'ANTHROPIC_API_KEY', // pragma: allowlist secret
|
||||
skipLlm: false,
|
||||
},
|
||||
io.io,
|
||||
{
|
||||
env: { ANTHROPIC_API_KEY: 'sk-ant-test' }, // pragma: allowlist secret
|
||||
healthCheck,
|
||||
spinner,
|
||||
},
|
||||
);
|
||||
|
||||
expect(result.status).toBe('ready');
|
||||
const config = parseKtxProjectConfig(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8'));
|
||||
expect(config.llm.models).toMatchObject({
|
||||
default: 'claude-sonnet-4-6',
|
||||
triage: 'claude-sonnet-4-6',
|
||||
candidateExtraction: 'claude-sonnet-4-6',
|
||||
curator: 'claude-opus-4-7',
|
||||
reconcile: 'claude-opus-4-7',
|
||||
repair: 'claude-sonnet-4-6',
|
||||
});
|
||||
expect(io.stderr()).toContain(
|
||||
'LLM model claude-haiku-4-5 is unavailable for triage, repair; using claude-sonnet-4-6 for those roles.',
|
||||
);
|
||||
expect(spinnerEvents).toEqual([
|
||||
'start:Checking Anthropic API LLM (claude-sonnet-4-6).',
|
||||
'stop:LLM test passed (Anthropic API, claude-sonnet-4-6)',
|
||||
'start:Checking Anthropic API LLM (claude-haiku-4-5).',
|
||||
'error:LLM test failed',
|
||||
'start:Checking Anthropic API LLM (claude-opus-4-7).',
|
||||
'stop:LLM test passed (Anthropic API, claude-opus-4-7)',
|
||||
]);
|
||||
});
|
||||
|
||||
it('configures Vertex AI provider, selected model, prompt caching, and llm completion state', async () => {
|
||||
const io = makeIo();
|
||||
const healthCheck = vi.fn(async () => ({ ok: true as const }));
|
||||
|
|
@ -436,7 +422,6 @@ describe('setup Anthropic model step', () => {
|
|||
llmBackend: 'vertex',
|
||||
vertexProject: 'local-gcp-project',
|
||||
vertexLocation: 'us-east5',
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
},
|
||||
io.io,
|
||||
|
|
@ -444,19 +429,31 @@ describe('setup Anthropic model step', () => {
|
|||
);
|
||||
|
||||
expect(result.status).toBe('ready');
|
||||
expect(healthCheck).toHaveBeenCalledWith({
|
||||
expect(healthCheck).toHaveBeenNthCalledWith(1, {
|
||||
backend: 'vertex',
|
||||
vertex: { project: 'local-gcp-project', location: 'us-east5' },
|
||||
modelSlots: { default: 'claude-sonnet-4-6' },
|
||||
promptCaching: { enabled: true, vertexFallbackTo5m: true },
|
||||
});
|
||||
expect(healthCheck).toHaveBeenNthCalledWith(2, {
|
||||
backend: 'vertex',
|
||||
vertex: { project: 'local-gcp-project', location: 'us-east5' },
|
||||
modelSlots: { default: 'claude-haiku-4-5' },
|
||||
promptCaching: { enabled: true, vertexFallbackTo5m: true },
|
||||
});
|
||||
expect(healthCheck).toHaveBeenNthCalledWith(3, {
|
||||
backend: 'vertex',
|
||||
vertex: { project: 'local-gcp-project', location: 'us-east5' },
|
||||
modelSlots: { default: 'claude-opus-4-7' },
|
||||
promptCaching: { enabled: true, vertexFallbackTo5m: true },
|
||||
});
|
||||
const config = parseKtxProjectConfig(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8'));
|
||||
expect(config.llm).toMatchObject({
|
||||
provider: {
|
||||
backend: 'vertex',
|
||||
vertex: { project: 'local-gcp-project', location: 'us-east5' },
|
||||
},
|
||||
models: { default: 'claude-sonnet-4-6' },
|
||||
models: anthropicPreset,
|
||||
promptCaching: { enabled: true, vertexFallbackTo5m: true },
|
||||
});
|
||||
expect(config.scan.enrichment.mode).toBe('llm');
|
||||
|
|
@ -465,13 +462,17 @@ describe('setup Anthropic model step', () => {
|
|||
expect(spinnerEvents).toEqual([
|
||||
'start:Checking Vertex AI LLM (claude-sonnet-4-6).',
|
||||
'stop:LLM test passed (Vertex AI, claude-sonnet-4-6)',
|
||||
'start:Checking Vertex AI LLM (claude-haiku-4-5).',
|
||||
'stop:LLM test passed (Vertex AI, claude-haiku-4-5)',
|
||||
'start:Checking Vertex AI LLM (claude-opus-4-7).',
|
||||
'stop:LLM test passed (Vertex AI, claude-opus-4-7)',
|
||||
]);
|
||||
expect(io.stdout()).toContain('LLM ready: yes (claude-sonnet-4-6)');
|
||||
});
|
||||
|
||||
it('uses existing Vertex AI credentials without an extra auth choice', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({ selectValues: ['vertex', 'local-gcp-project', 'claude-sonnet-4-6'] });
|
||||
const prompts = makePromptAdapter({ selectValues: ['vertex', 'local-gcp-project'] });
|
||||
const readGcloudProject = vi.fn(async () => 'local-gcp-project');
|
||||
const listGcloudProjects = vi.fn(async () => [
|
||||
{ projectId: 'local-gcp-project', name: 'Local project' },
|
||||
|
|
@ -511,22 +512,6 @@ describe('setup Anthropic model step', () => {
|
|||
],
|
||||
}),
|
||||
);
|
||||
expect(prompts.autocomplete).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which Anthropic model should KTX use?'),
|
||||
options: [
|
||||
{ value: 'claude-opus-4-7', label: 'Claude Opus 4.7' },
|
||||
{ value: 'claude-sonnet-4-6', label: 'Claude Sonnet 4.6' },
|
||||
{ value: 'claude-opus-4-6', label: 'Claude Opus 4.6' },
|
||||
{ value: 'claude-opus-4-5', label: 'Claude Opus 4.5' },
|
||||
{ value: 'claude-haiku-4-5', label: 'Claude Haiku 4.5' },
|
||||
{ value: 'claude-sonnet-4-5', label: 'Claude Sonnet 4.5' },
|
||||
{ value: 'claude-opus-4-1', label: 'Claude Opus 4.1' },
|
||||
{ value: 'manual', label: 'Enter a model ID manually' },
|
||||
{ value: 'back', label: 'Back' },
|
||||
],
|
||||
}),
|
||||
);
|
||||
expect(healthCheck).toHaveBeenCalledWith({
|
||||
backend: 'vertex',
|
||||
vertex: { project: 'local-gcp-project', location: 'us-east5' },
|
||||
|
|
@ -542,7 +527,7 @@ describe('setup Anthropic model step', () => {
|
|||
|
||||
it('skips the Vertex AI auth choice when Application Default Credentials are the only option', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({ selectValues: ['vertex', 'local-gcp-project', 'claude-sonnet-4-6'] });
|
||||
const prompts = makePromptAdapter({ selectValues: ['vertex', 'local-gcp-project'] });
|
||||
const healthCheck = vi.fn(async () => ({ ok: true as const }));
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
|
|
@ -578,7 +563,7 @@ describe('setup Anthropic model step', () => {
|
|||
|
||||
it('lets users choose a different visible gcloud project for Vertex AI', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({ selectValues: ['vertex', 'other-gcp-project', 'claude-sonnet-4-6'] });
|
||||
const prompts = makePromptAdapter({ selectValues: ['vertex', 'other-gcp-project'] });
|
||||
const healthCheck = vi.fn(async () => ({ ok: true as const }));
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
|
|
@ -612,10 +597,7 @@ describe('setup Anthropic model step', () => {
|
|||
|
||||
it('allows manual Vertex AI project entry when gcloud project listing is empty', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({
|
||||
selectValues: ['vertex', 'manual', 'claude-sonnet-4-6'],
|
||||
textValues: ['manual-gcp-project'],
|
||||
});
|
||||
const prompts = makePromptAdapter({ selectValues: ['vertex', 'manual'], textValues: ['manual-gcp-project'] });
|
||||
const healthCheck = vi.fn(async () => ({ ok: true as const }));
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
|
|
@ -654,7 +636,7 @@ describe('setup Anthropic model step', () => {
|
|||
|
||||
it('lets users retry Vertex AI project listing after gcloud auth fails', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({ selectValues: ['vertex', 'retry', 'other-gcp-project', 'claude-sonnet-4-6'] });
|
||||
const prompts = makePromptAdapter({ selectValues: ['vertex', 'retry', 'other-gcp-project'] });
|
||||
const listGcloudProjects = vi
|
||||
.fn()
|
||||
.mockRejectedValueOnce(new Error('Reauthentication failed. cannot prompt during non-interactive execution.'))
|
||||
|
|
@ -743,7 +725,6 @@ describe('setup Anthropic model step', () => {
|
|||
llmBackend: 'vertex',
|
||||
vertexProject: 'kaelio-orbit-looker-20260430',
|
||||
vertexLocation: 'us-east5',
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
},
|
||||
io.io,
|
||||
|
|
@ -771,7 +752,6 @@ describe('setup Anthropic model step', () => {
|
|||
projectDir: tempDir,
|
||||
inputMode: 'disabled',
|
||||
anthropicApiKeyFile: secretPath,
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
},
|
||||
io.io,
|
||||
|
|
@ -779,19 +759,34 @@ describe('setup Anthropic model step', () => {
|
|||
);
|
||||
|
||||
expect(result.status).toBe('ready');
|
||||
expect(healthCheck).toHaveBeenCalledWith(
|
||||
expect(healthCheck).toHaveBeenNthCalledWith(
|
||||
1,
|
||||
expect.objectContaining({
|
||||
anthropic: { apiKey: 'sk-ant-file' }, // pragma: allowlist secret
|
||||
modelSlots: { default: 'claude-sonnet-4-6' },
|
||||
}),
|
||||
);
|
||||
expect(healthCheck).toHaveBeenNthCalledWith(
|
||||
2,
|
||||
expect.objectContaining({
|
||||
anthropic: { apiKey: 'sk-ant-file' }, // pragma: allowlist secret
|
||||
modelSlots: { default: 'claude-haiku-4-5' },
|
||||
}),
|
||||
);
|
||||
expect(healthCheck).toHaveBeenNthCalledWith(
|
||||
3,
|
||||
expect.objectContaining({
|
||||
anthropic: { apiKey: 'sk-ant-file' }, // pragma: allowlist secret
|
||||
modelSlots: { default: 'claude-opus-4-7' },
|
||||
}),
|
||||
);
|
||||
const config = parseKtxProjectConfig(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8'));
|
||||
expect(config.llm).toMatchObject({
|
||||
provider: {
|
||||
backend: 'anthropic',
|
||||
anthropic: { api_key: `file:${secretPath}` }, // pragma: allowlist secret
|
||||
},
|
||||
models: { default: 'claude-sonnet-4-6' },
|
||||
models: anthropicPreset,
|
||||
});
|
||||
expect(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8')).not.toContain('completed_steps:');
|
||||
expect((await readKtxSetupState(tempDir)).completed_steps).toContain('llm');
|
||||
|
|
@ -808,7 +803,6 @@ describe('setup Anthropic model step', () => {
|
|||
projectDir: tempDir,
|
||||
inputMode: 'disabled',
|
||||
anthropicApiKeyFile: missingSecretPath,
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
},
|
||||
io.io,
|
||||
|
|
@ -835,32 +829,10 @@ describe('setup Anthropic model step', () => {
|
|||
expect(io.stderr()).not.toContain('--skip-llm');
|
||||
});
|
||||
|
||||
it('does not recommend skipping when non-interactive setup is missing an LLM model', async () => {
|
||||
const io = makeIo();
|
||||
const healthCheck = vi.fn(async () => ({ ok: true as const }));
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
{
|
||||
projectDir: tempDir,
|
||||
inputMode: 'disabled',
|
||||
anthropicApiKeyEnv: 'ANTHROPIC_API_KEY', // pragma: allowlist secret
|
||||
skipLlm: false,
|
||||
},
|
||||
io.io,
|
||||
{ env: { ANTHROPIC_API_KEY: 'sk-ant-test' }, healthCheck }, // pragma: allowlist secret
|
||||
);
|
||||
|
||||
expect(result.status).toBe('missing-input');
|
||||
expect(healthCheck).not.toHaveBeenCalled();
|
||||
expect(io.stderr()).toContain('Missing LLM model: pass --llm-model.');
|
||||
expect(io.stderr()).not.toContain('--skip-llm');
|
||||
});
|
||||
|
||||
it('writes pasted keys to .ktx/secrets and never prints the key', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({
|
||||
credentialChoice: 'paste',
|
||||
modelChoice: 'claude-sonnet-4-6',
|
||||
passwordValue: 'sk-ant-pasted', // pragma: allowlist secret
|
||||
});
|
||||
|
||||
|
|
@ -870,7 +842,6 @@ describe('setup Anthropic model step', () => {
|
|||
{
|
||||
prompts,
|
||||
env: {},
|
||||
listModels: vi.fn(async () => [{ id: 'claude-sonnet-4-6', label: 'Claude Sonnet 4.6', recommended: true }]),
|
||||
healthCheck: vi.fn(async () => ({ ok: true as const })),
|
||||
},
|
||||
);
|
||||
|
|
@ -888,7 +859,7 @@ describe('setup Anthropic model step', () => {
|
|||
|
||||
it('opens pasted key entry directly and tells users Escape goes back', async () => {
|
||||
const prompts = makePromptAdapter({
|
||||
selectValues: ['paste', 'claude-sonnet-4-6'],
|
||||
selectValues: ['paste'],
|
||||
passwordValue: 'sk-ant-pasted', // pragma: allowlist secret
|
||||
});
|
||||
|
||||
|
|
@ -898,7 +869,6 @@ describe('setup Anthropic model step', () => {
|
|||
{
|
||||
prompts,
|
||||
env: {},
|
||||
listModels: vi.fn(async () => [{ id: 'claude-sonnet-4-6', label: 'Claude Sonnet 4.6', recommended: true }]),
|
||||
healthCheck: vi.fn(async () => ({ ok: true as const })),
|
||||
},
|
||||
);
|
||||
|
|
@ -956,142 +926,6 @@ describe('setup Anthropic model step', () => {
|
|||
expect(io.stdout()).not.toContain('KTX uses the key');
|
||||
});
|
||||
|
||||
it('does not offer skipping while choosing an Anthropic model', async () => {
|
||||
const prompts = makePromptAdapter({ selectValues: ['env', 'back', 'back'] });
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
{ projectDir: tempDir, inputMode: 'auto', skipLlm: false },
|
||||
makeIo().io,
|
||||
{
|
||||
prompts,
|
||||
env: { ANTHROPIC_API_KEY: 'sk-ant-test' }, // pragma: allowlist secret
|
||||
listModels: vi.fn(async () => [{ id: 'claude-sonnet-4-6', label: 'Claude Sonnet 4.6', recommended: true }]),
|
||||
},
|
||||
);
|
||||
|
||||
expect(result.status).toBe('back');
|
||||
expect(prompts.autocomplete).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which Anthropic model should KTX use?'),
|
||||
options: expect.not.arrayContaining([expect.objectContaining({ value: 'skip' })]),
|
||||
}),
|
||||
);
|
||||
});
|
||||
|
||||
it('explains why KTX asks for an Anthropic model', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({ credentialChoice: 'env', modelChoice: 'claude-sonnet-4-6' });
|
||||
const expectedPromptMessage = [
|
||||
'Which Anthropic model should KTX use?',
|
||||
'',
|
||||
[
|
||||
'KTX uses this as the default model for ingest agents that turn schemas, SQL, BI metadata, and docs',
|
||||
'into semantic-layer sources and wiki context.',
|
||||
].join(' '),
|
||||
].join('\n');
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
{ projectDir: tempDir, inputMode: 'auto', skipLlm: false },
|
||||
io.io,
|
||||
{
|
||||
prompts,
|
||||
env: { ANTHROPIC_API_KEY: 'sk-ant-test' }, // pragma: allowlist secret
|
||||
listModels: vi.fn(async () => [{ id: 'claude-sonnet-4-6', label: 'Claude Sonnet 4.6', recommended: true }]),
|
||||
healthCheck: vi.fn(async () => ({ ok: true as const })),
|
||||
},
|
||||
);
|
||||
|
||||
expect(result.status).toBe('ready');
|
||||
expect(prompts.autocomplete).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expectedPromptMessage,
|
||||
}),
|
||||
);
|
||||
expect(io.stdout()).not.toContain('KTX uses this as the default model');
|
||||
expect(io.stdout()).not.toContain('Setup verifies the selected model now');
|
||||
});
|
||||
|
||||
it('uses the bundled fallback registry when live discovery fails', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({ credentialChoice: 'env', modelChoice: 'claude-sonnet-4-6' });
|
||||
|
||||
await expect(
|
||||
runKtxSetupAnthropicModelStep({ projectDir: tempDir, inputMode: 'auto', skipLlm: false }, io.io, {
|
||||
prompts,
|
||||
env: { ANTHROPIC_API_KEY: 'sk-ant-test' }, // pragma: allowlist secret
|
||||
listModels: vi.fn(async () => {
|
||||
throw new Error('network unavailable');
|
||||
}),
|
||||
healthCheck: vi.fn(async () => ({ ok: true as const })),
|
||||
}),
|
||||
).resolves.toMatchObject({ status: 'ready' });
|
||||
|
||||
expect(io.stderr()).toContain('Could not fetch live Anthropic models. Showing bundled defaults.');
|
||||
});
|
||||
|
||||
it('shows bundled model choices when live discovery fails', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({ selectValues: ['env', 'manual'], textValues: [''] });
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
{ projectDir: tempDir, inputMode: 'auto', skipLlm: false },
|
||||
io.io,
|
||||
{
|
||||
prompts,
|
||||
env: { ANTHROPIC_API_KEY: 'sk-ant-test' }, // pragma: allowlist secret
|
||||
listModels: vi.fn(async () => {
|
||||
throw new Error('network unavailable');
|
||||
}),
|
||||
healthCheck: vi.fn(async () => ({ ok: true as const })),
|
||||
},
|
||||
);
|
||||
|
||||
expect(result.status).toBe('missing-input');
|
||||
expect(BUNDLED_ANTHROPIC_MODELS.length).toBeGreaterThan(0);
|
||||
expect(prompts.autocomplete).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which Anthropic model should KTX use?'),
|
||||
options: expect.arrayContaining([
|
||||
{ value: 'claude-sonnet-4-6', label: 'Claude Sonnet 4.6', hint: 'recommended' },
|
||||
]),
|
||||
}),
|
||||
);
|
||||
expect(prompts.text).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: 'Anthropic model ID\n│ Press Escape to go back.\n│',
|
||||
placeholder: 'claude-sonnet-4-6',
|
||||
}),
|
||||
);
|
||||
});
|
||||
|
||||
it('reports invalid Anthropic API keys during live discovery instead of showing bundled defaults', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({ selectValues: ['env', 'back'] });
|
||||
const fetchModels = vi.fn(
|
||||
async () => new Response(JSON.stringify({ error: { message: 'invalid x-api-key' } }), { status: 401 }),
|
||||
);
|
||||
const healthCheck = vi.fn(async () => ({ ok: true as const }));
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
{ projectDir: tempDir, inputMode: 'auto', skipLlm: false },
|
||||
io.io,
|
||||
{
|
||||
prompts,
|
||||
env: { ANTHROPIC_API_KEY: 'sk-ant-invalid' }, // pragma: allowlist secret
|
||||
fetch: fetchModels,
|
||||
healthCheck,
|
||||
},
|
||||
);
|
||||
|
||||
expect(result.status).toBe('back');
|
||||
expect(fetchModels).toHaveBeenCalledTimes(1);
|
||||
expect(healthCheck).not.toHaveBeenCalled();
|
||||
expect(io.stderr()).toContain('Anthropic API key is invalid or unauthorized');
|
||||
expect(io.stderr()).toContain('Choose a different credential source or Back.');
|
||||
expect(io.stderr()).not.toContain('Could not fetch live Anthropic models. Showing bundled defaults.');
|
||||
expect(io.stderr()).not.toContain('sk-ant-invalid');
|
||||
});
|
||||
|
||||
it('does not persist llm completion when the health check fails', async () => {
|
||||
const io = makeIo();
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
|
|
@ -1099,7 +933,6 @@ describe('setup Anthropic model step', () => {
|
|||
projectDir: tempDir,
|
||||
inputMode: 'disabled',
|
||||
anthropicApiKeyEnv: 'ANTHROPIC_API_KEY', // pragma: allowlist secret
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
},
|
||||
io.io,
|
||||
|
|
@ -1117,12 +950,12 @@ describe('setup Anthropic model step', () => {
|
|||
|
||||
it('re-prompts after an interactive health-check failure and saves after retry success', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({
|
||||
selectValues: ['env', 'claude-haiku-3-5', 'env', 'claude-sonnet-4-6'],
|
||||
});
|
||||
const prompts = makePromptAdapter({ selectValues: ['env', 'env'] });
|
||||
const healthCheck = vi
|
||||
.fn()
|
||||
.mockResolvedValueOnce({ ok: false as const, message: 'model not found' })
|
||||
.mockResolvedValueOnce({ ok: true as const })
|
||||
.mockResolvedValueOnce({ ok: true as const })
|
||||
.mockResolvedValueOnce({ ok: true as const });
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
|
|
@ -1131,22 +964,22 @@ describe('setup Anthropic model step', () => {
|
|||
{
|
||||
prompts,
|
||||
env: { ANTHROPIC_API_KEY: 'sk-ant-test' }, // pragma: allowlist secret
|
||||
listModels: vi.fn(async () => [
|
||||
{ id: 'claude-haiku-3-5', label: 'Claude Haiku 3.5', recommended: false },
|
||||
{ id: 'claude-sonnet-4-6', label: 'Claude Sonnet 4.6', recommended: true },
|
||||
]),
|
||||
healthCheck,
|
||||
},
|
||||
);
|
||||
|
||||
expect(result.status).toBe('ready');
|
||||
expect(healthCheck).toHaveBeenCalledTimes(2);
|
||||
expect(healthCheck).toHaveBeenCalledTimes(4);
|
||||
expect(prompts.select).toHaveBeenCalledTimes(3);
|
||||
expect(prompts.autocomplete).toHaveBeenCalledTimes(2);
|
||||
expect(prompts.autocomplete).not.toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which Anthropic model should KTX use?'),
|
||||
}),
|
||||
);
|
||||
expect(io.stderr()).toContain('Anthropic model health check failed: model not found');
|
||||
expect(io.stderr()).toContain('Choose a different credential source or model, or Back.');
|
||||
expect(io.stderr()).toContain('Choose a different credential source or Back.');
|
||||
const config = parseKtxProjectConfig(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8'));
|
||||
expect(config.llm.models.default).toBe('claude-sonnet-4-6');
|
||||
expect(config.llm.models).toMatchObject(anthropicPreset);
|
||||
expect(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8')).not.toContain('completed_steps:');
|
||||
expect((await readKtxSetupState(tempDir)).completed_steps).toContain('llm');
|
||||
expect(io.stderr()).not.toContain('sk-ant-test');
|
||||
|
|
@ -1175,39 +1008,8 @@ describe('setup Anthropic model step', () => {
|
|||
expect(config.llm.provider.backend).toBe('none');
|
||||
});
|
||||
|
||||
it('returns from model selection Back to credential selection instead of exiting setup', async () => {
|
||||
const prompts = makePromptAdapter({
|
||||
selectValues: ['paste', 'back', 'back'],
|
||||
passwordValue: 'sk-ant-pasted', // pragma: allowlist secret
|
||||
});
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
{ projectDir: tempDir, inputMode: 'auto', skipLlm: false },
|
||||
makeIo().io,
|
||||
{
|
||||
prompts,
|
||||
env: {},
|
||||
listModels: vi.fn(async () => [{ id: 'claude-sonnet-4-6', label: 'Claude Sonnet 4.6', recommended: true }]),
|
||||
healthCheck: vi.fn(async () => ({ ok: true as const })),
|
||||
},
|
||||
);
|
||||
|
||||
expect(result.status).toBe('back');
|
||||
expect(prompts.select).toHaveBeenNthCalledWith(
|
||||
3,
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('How should KTX find your Anthropic API key?'),
|
||||
}),
|
||||
);
|
||||
const config = parseKtxProjectConfig(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8'));
|
||||
expect(config.llm.provider.backend).toBe('none');
|
||||
});
|
||||
|
||||
it('returns from pasted key entry Escape to credential selection and can use env credentials', async () => {
|
||||
const prompts = makePromptAdapter({
|
||||
selectValues: ['paste', 'env', 'claude-sonnet-4-6'],
|
||||
passwordValues: [undefined],
|
||||
});
|
||||
const prompts = makePromptAdapter({ selectValues: ['paste', 'env'], passwordValues: [undefined] });
|
||||
|
||||
const result = await runKtxSetupAnthropicModelStep(
|
||||
{ projectDir: tempDir, inputMode: 'auto', skipLlm: false },
|
||||
|
|
@ -1215,7 +1017,6 @@ describe('setup Anthropic model step', () => {
|
|||
{
|
||||
prompts,
|
||||
env: { ANTHROPIC_API_KEY: 'sk-ant-env' }, // pragma: allowlist secret
|
||||
listModels: vi.fn(async () => [{ id: 'claude-sonnet-4-6', label: 'Claude Sonnet 4.6', recommended: true }]),
|
||||
healthCheck: vi.fn(async () => ({ ok: true as const })),
|
||||
},
|
||||
);
|
||||
|
|
|
|||
|
|
@ -1305,7 +1305,6 @@ describe('setup status', () => {
|
|||
yes: true,
|
||||
cliVersion: '0.2.0',
|
||||
anthropicApiKeyEnv: 'ANTHROPIC_API_KEY', // pragma: allowlist secret
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
skipEmbeddings: true,
|
||||
databaseSchemas: [],
|
||||
|
|
@ -1322,7 +1321,6 @@ describe('setup status', () => {
|
|||
projectDir: tempDir,
|
||||
inputMode: 'disabled',
|
||||
anthropicApiKeyEnv: 'ANTHROPIC_API_KEY', // pragma: allowlist secret
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
}),
|
||||
testIo.io,
|
||||
|
|
@ -1347,7 +1345,6 @@ describe('setup status', () => {
|
|||
llmBackend: 'vertex',
|
||||
vertexProject: 'local-gcp-project',
|
||||
vertexLocation: 'us-east5',
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
skipEmbeddings: true,
|
||||
databaseSchemas: [],
|
||||
|
|
@ -1366,7 +1363,6 @@ describe('setup status', () => {
|
|||
llmBackend: 'vertex',
|
||||
vertexProject: 'local-gcp-project',
|
||||
vertexLocation: 'us-east5',
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
}),
|
||||
testIo.io,
|
||||
|
|
@ -1390,7 +1386,6 @@ describe('setup status', () => {
|
|||
yes: true,
|
||||
cliVersion: '0.2.0',
|
||||
anthropicApiKeyEnv: 'ANTHROPIC_API_KEY', // pragma: allowlist secret
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
embeddingBackend: 'openai',
|
||||
embeddingApiKeyEnv: 'OPENAI_API_KEY', // pragma: allowlist secret
|
||||
|
|
@ -1658,7 +1653,6 @@ describe('setup status', () => {
|
|||
yes: true,
|
||||
cliVersion: '0.2.0',
|
||||
anthropicApiKeyEnv: 'ANTHROPIC_API_KEY', // pragma: allowlist secret
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
embeddingBackend: 'openai',
|
||||
embeddingApiKeyEnv: 'OPENAI_API_KEY', // pragma: allowlist secret
|
||||
|
|
@ -2657,7 +2651,6 @@ describe('setup status', () => {
|
|||
yes: true,
|
||||
cliVersion: '0.2.0',
|
||||
anthropicApiKeyEnv: 'ANTHROPIC_API_KEY', // pragma: allowlist secret
|
||||
llmModel: 'claude-sonnet-4-6',
|
||||
skipLlm: false,
|
||||
skipEmbeddings: false,
|
||||
databaseSchemas: [],
|
||||
|
|
|
|||
|
|
@ -68,8 +68,6 @@ async function runSetupSmoke(projectDir) {
|
|||
projectDir,
|
||||
'--llm-backend',
|
||||
'codex',
|
||||
'--llm-model',
|
||||
'gpt-5.3-codex',
|
||||
'--no-input',
|
||||
'--yes',
|
||||
'--skip-databases',
|
||||
|
|
@ -79,7 +77,7 @@ async function runSetupSmoke(projectDir) {
|
|||
{ timeoutMs: 600_000 },
|
||||
);
|
||||
requireSuccess('ktx setup codex backend', result);
|
||||
if (!result.stdout.includes('LLM ready: yes (codex, gpt-5.3-codex)')) {
|
||||
if (!result.stdout.includes('LLM ready: yes (codex, gpt-5.5)')) {
|
||||
throw new Error(`setup did not report Codex LLM readiness\nstdout:\n${result.stdout}`);
|
||||
}
|
||||
}
|
||||
|
|
@ -91,7 +89,14 @@ async function runRuntimeSmoke(projectDir) {
|
|||
const { z } = await import(zodUrl);
|
||||
const runtime = new CodexKtxLlmRuntime({
|
||||
projectDir,
|
||||
modelSlots: { default: 'gpt-5.3-codex' },
|
||||
modelSlots: {
|
||||
default: 'gpt-5.5',
|
||||
triage: 'gpt-5.5',
|
||||
candidateExtraction: 'gpt-5.5',
|
||||
curator: 'gpt-5.5',
|
||||
reconcile: 'gpt-5.5',
|
||||
repair: 'gpt-5.5',
|
||||
},
|
||||
});
|
||||
|
||||
const text = await runtime.generateText({
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue