mirror of
https://github.com/Kaelio/ktx.git
synced 2026-06-28 08:49:38 +02:00
refactor: enforce ktx naming and AGENTS.md compliance sweep (#289)
Align the tree with AGENTS.md/CLAUDE.md conventions: - Rewrite user-facing strings, docs, and tests to lowercase `ktx` (no bare uppercase `KTX` tokens remain outside literal identifiers). - Drop the legacy `historicSql` migration path and its now-unused helpers, per the no-backward-compat rule. - Remove `as unknown as` / `any` casts: narrow `BaseTool` generics to `z.ZodObject`, add a typed `createLookerClient`, and delete the dead `getParametersSchema`/`toAnthropicFormat` pre-AI-SDK helpers. - Use `InvalidArgumentError` for Commander parse failures. - Finish the adapter→connector prose conversion in the `ktx.yaml` docs while keeping the literal `adapters` config key.
This commit is contained in:
Andrey Avtomonov
GitHub
parent
005c5fc860
commit
00cdf2de90
237 changed files with 844 additions and 974 deletions
|
|
@ -146,7 +146,7 @@ describe('setup Anthropic model step', () => {
|
|||
expect(result.status).toBe('back');
|
||||
expect(prompts.select).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which LLM provider should KTX use?'),
|
||||
message: expect.stringContaining('Which LLM provider should ktx use?'),
|
||||
options: [
|
||||
{ value: 'claude-code', label: 'Claude subscription (Pro/Max)' },
|
||||
{ value: 'codex', label: 'Codex subscription' },
|
||||
|
|
@ -199,12 +199,12 @@ describe('setup Anthropic model step', () => {
|
|||
expect(result.status).toBe('ready');
|
||||
expect(prompts.select).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which LLM provider should KTX use?'),
|
||||
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?'),
|
||||
message: expect.stringContaining('Which Claude Code model should ktx use?'),
|
||||
}),
|
||||
);
|
||||
const config = parseKtxProjectConfig(await readFile(join(tempDir, 'ktx.yaml'), 'utf-8'));
|
||||
|
|
@ -299,7 +299,7 @@ describe('setup Anthropic model step', () => {
|
|||
|
||||
expect(result.status).toBe('ready');
|
||||
expect(io.stderr()).toContain('claude-code ignores llm.promptCaching.systemTtl');
|
||||
expect(io.stderr()).toContain('Claude Agent SDK does not expose KTX prompt-cache TTL, tool, or history markers');
|
||||
expect(io.stderr()).toContain('Claude Agent SDK does not expose ktx prompt-cache TTL, tool, or history markers');
|
||||
});
|
||||
|
||||
it('returns from Anthropic credential Back to provider selection', async () => {
|
||||
|
|
@ -315,7 +315,7 @@ describe('setup Anthropic model step', () => {
|
|||
expect(prompts.select).toHaveBeenNthCalledWith(
|
||||
3,
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which LLM provider should KTX use?'),
|
||||
message: expect.stringContaining('Which LLM provider should ktx use?'),
|
||||
}),
|
||||
);
|
||||
});
|
||||
|
|
@ -495,7 +495,7 @@ describe('setup Anthropic model step', () => {
|
|||
expect(result.status).toBe('ready');
|
||||
expect(prompts.select).not.toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('How should KTX authenticate with Google Vertex AI?'),
|
||||
message: expect.stringContaining('How should ktx authenticate with Google Vertex AI?'),
|
||||
}),
|
||||
);
|
||||
expect(readGcloudProject).toHaveBeenCalled();
|
||||
|
|
@ -503,7 +503,7 @@ describe('setup Anthropic model step', () => {
|
|||
expect(prompts.text).not.toHaveBeenCalled();
|
||||
expect(prompts.autocomplete).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which Google Cloud project should KTX use for Vertex AI?'),
|
||||
message: expect.stringContaining('Which Google Cloud project should ktx use for Vertex AI?'),
|
||||
options: [
|
||||
{ value: 'local-gcp-project', label: 'local-gcp-project - Local project (current gcloud project)' },
|
||||
{ value: 'other-gcp-project', label: 'other-gcp-project - Other project' },
|
||||
|
|
@ -545,12 +545,12 @@ describe('setup Anthropic model step', () => {
|
|||
expect(result.status).toBe('ready');
|
||||
expect(prompts.select).not.toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('How should KTX authenticate with Google Vertex AI?'),
|
||||
message: expect.stringContaining('How should ktx authenticate with Google Vertex AI?'),
|
||||
}),
|
||||
);
|
||||
expect(prompts.autocomplete).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which Google Cloud project should KTX use for Vertex AI?'),
|
||||
message: expect.stringContaining('Which Google Cloud project should ktx use for Vertex AI?'),
|
||||
}),
|
||||
);
|
||||
expect(healthCheck).toHaveBeenCalledWith(
|
||||
|
|
@ -615,7 +615,7 @@ describe('setup Anthropic model step', () => {
|
|||
expect(result.status).toBe('ready');
|
||||
expect(prompts.autocomplete).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which Google Cloud project should KTX use for Vertex AI?'),
|
||||
message: expect.stringContaining('Which Google Cloud project should ktx use for Vertex AI?'),
|
||||
options: [
|
||||
{ value: 'manual', label: 'Enter a project ID manually' },
|
||||
{ value: 'back', label: 'Back' },
|
||||
|
|
@ -710,7 +710,7 @@ describe('setup Anthropic model step', () => {
|
|||
expect(prompts.select).toHaveBeenNthCalledWith(
|
||||
2,
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which LLM provider should KTX use?'),
|
||||
message: expect.stringContaining('Which LLM provider should ktx use?'),
|
||||
}),
|
||||
);
|
||||
});
|
||||
|
|
@ -899,20 +899,20 @@ describe('setup Anthropic model step', () => {
|
|||
expect(result.status).toBe('back');
|
||||
expect(prompts.select).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('How should KTX find your Anthropic API key?'),
|
||||
message: expect.stringContaining('How should ktx find your Anthropic API key?'),
|
||||
options: expect.not.arrayContaining([expect.objectContaining({ value: 'skip' })]),
|
||||
}),
|
||||
);
|
||||
});
|
||||
|
||||
it('explains why KTX asks for an Anthropic API key', async () => {
|
||||
it('explains why ktx asks for an Anthropic API key', async () => {
|
||||
const io = makeIo();
|
||||
const prompts = makePromptAdapter({ credentialChoice: 'back' });
|
||||
const expectedPromptMessage = [
|
||||
'How should KTX find your Anthropic API key?',
|
||||
'How should ktx find your Anthropic API key?',
|
||||
'',
|
||||
[
|
||||
'KTX uses the key to verify Anthropic model access now and to run ingest agents that turn schemas, SQL,',
|
||||
'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.',
|
||||
].join(' '),
|
||||
|
|
@ -930,7 +930,7 @@ describe('setup Anthropic model step', () => {
|
|||
message: expectedPromptMessage,
|
||||
}),
|
||||
);
|
||||
expect(io.stdout()).not.toContain('KTX uses the key');
|
||||
expect(io.stdout()).not.toContain('ktx uses the key');
|
||||
});
|
||||
|
||||
it('does not persist llm completion when the health check fails', async () => {
|
||||
|
|
@ -980,7 +980,7 @@ describe('setup Anthropic model step', () => {
|
|||
expect(prompts.select).toHaveBeenCalledTimes(3);
|
||||
expect(prompts.autocomplete).not.toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
message: expect.stringContaining('Which Anthropic model should KTX use?'),
|
||||
message: expect.stringContaining('Which Anthropic model should ktx use?'),
|
||||
}),
|
||||
);
|
||||
expect(io.stderr()).toContain('Anthropic model health check failed: model not found');
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue