Files
supabase/apps/studio/components/ui/AIAssistantPanel/AIAssistant.utils.test.ts
Charis 21511042a3 feat(studio): assistant logs context and reports guard (#48514)
## I have read the
[CONTRIBUTING.md](https://github.com/supabase/supabase/blob/master/CONTRIBUTING.md)
file.

YES

## What kind of change does this PR introduce?

Feature — final PR (9/9) of the SQL editor logs-source stack.

**Base branch:** `charislam/sql-editor-inline-ai-clickhouse-dialect` (PR
8). Nothing here is user-visible: entry points stay behind
`sqlEditorLogsSource` + `otelLegacyLogs`, and flag rollout happens after
the whole stack merges.

## What is the current behavior?

- The Assistant has no idea a SQL editor snippet targets the logs
backend. Ask it about a logs snippet and it answers in Postgres, because
the attached query is fenced as ` ```sql ` and nothing tells the model
otherwise.
- Because the `sql` fence is what `MessageMarkdown` treats as runnable
Postgres, an attached ClickHouse query is rendered with a
Run-against-Postgres affordance and branded with `untrustedSql`.
- "Debug with Assistant" on a failed logs query produces a dialect-less
prompt, so both the in-app assistant and the copyable version get
debugged as Postgres.
- A report referencing a `log_sql` snippet runs its ClickHouse SQL
against the user's Postgres database and surfaces the resulting error.

## What is the new behavior?

**Assistant panel.** The "Current Query" chip records which backend the
attached query targets. That reaches the model two ways: each attachment
is fenced with its own dialect (` ```clickhouse ` vs ` ```sql `), and a
`containsLogsSnippets` flag rides on the user message as AI SDK
`metadata`. The server reads the flag off the conversation and prepends
the ClickHouse dialect rules plus the logs schema reference as a
non-cached context message.

Two design points worth calling out in review:

- The flag lives on the **message**, not the request body, so Retry and
the tool-approval continuation reproduce the context a message was
originally asked in — neither of those passes a per-call body.
- It's derived from **what's actually attached**, so detaching the chip
drops the claim rather than leaving the two able to disagree.

The `clickhouse` fence also keeps a logs query out of
`MessageMarkdown`'s `sql` branch, so it's no longer offered as runnable
Postgres or branded with `untrustedSql` — a boundary this stack's
distinct brands exist to prevent crossing.

**Debug flow.** `buildDebugChatArgs` attaches its query with a source
for the same reason, and names the dialect in the prompt text so the
copyable version stands on its own outside the app.

**Reports.** A report only stores a snippet id, so whether it queries
the logs backend is only knowable once the content loads. `ReportBlock`
guards on the fetched type and renders a `LogsSnippetReportBlock`
placeholder instead of executing. Double-guarded: no `sql` for a logs
snippet (so it's out of the query key and `queryFn` short-circuits even
on an explicit `refetch`) and `enabled` excludes it.

**Incidental cleanups.** `buildAssistantContextMessages` extracted out
of `generate-assistant-response`; a schema-access sentinel that was
duplicated as a string literal across two files (and compared against)
replaced with one exported constant; `SqlSnippet` deduplicated to a
single declaration; `resolveSnippetSource` / `isLogsSource` shared
instead of re-implemented per surface.

**Tests.** 4 new/extended suites. Notable cases pinned: a message with
no metadata must validate (`safeValidateUIMessages` applies
`metadataSchema` to *every* message, so a required schema would 400
every existing conversation); only *user* messages count, so a model
reply can't talk the server into a different dialect; a mixed-attachment
message is flagged without overclaiming a single source; and
`ReportBlock` registers no pg-meta mock for the logs cases, so an
unhandled request failing the test *is* the assertion that logs SQL
never reaches Postgres.

Verified: `pnpm typecheck`, `lint:ratchet` (no regression), Prettier,
and the full Studio suite (459 files / 4969 tests).

## Additional context

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->

## Summary by CodeRabbit

- **New Features**
- Added support for recognizing log snippets in reports, with clear
guidance to open them in the SQL editor or remove them.
- AI Assistant now understands log snippets and provides
ClickHouse-specific context, formatting, and troubleshooting guidance.
- Snippets retain their source information when shared with the AI
Assistant.

- **Bug Fixes**
- Prevented unsupported log snippets from being executed as regular
database queries.
  - Improved source detection when opening snippets directly from links.

<!-- end of auto-generated comment: release notes by coderabbit.ai -->
2026-08-04 09:02:40 -04:00

231 lines
7.8 KiB
TypeScript

import type { UIMessage } from 'ai'
import { describe, expect, test } from 'vitest'
import {
containsLogsSnippets,
formatAttachedSnippets,
hasPendingToolApproval,
isReadOnlySelect,
resolvePendingToolApprovalsAsDenied,
} from './AIAssistant.utils'
const createMessageWithPart = (
part: UIMessage['parts'][number],
role: UIMessage['role'] = 'assistant'
) =>
[
{
id: `${role}-msg-1`,
role,
parts: [part],
},
] as UIMessage[]
const pendingSqlApprovalPart = {
type: 'tool-execute_sql',
toolCallId: 'call-1',
state: 'approval-requested',
input: { sql: 'select 1', label: 'Test query' },
approval: { id: 'approval-1' },
} satisfies UIMessage['parts'][number]
describe('AIAssistant.utils.ts:isReadOnlySelect', () => {
test('Should return true for SQL that only contains SELECT operation', () => {
const sql = 'select * from countries where id > 100 order by id asc;'
const result = isReadOnlySelect(sql)
expect(result).toBe(true)
})
test('Should return false for SQL that contains INSERT operation', () => {
const sql = `insert into countries (id, name) values (1, 'hello');`
const result = isReadOnlySelect(sql)
expect(result).toBe(false)
})
test('Should return false for SQL that contains UPDATE operation', () => {
const sql = `update countries set name = 'hello' where id = 2;`
const result = isReadOnlySelect(sql)
expect(result).toBe(false)
})
test('Should return false for SQL that contains DELETE operation', () => {
const sql = `delete from countries where id = 2;`
const result = isReadOnlySelect(sql)
expect(result).toBe(false)
})
test('Should return false for SQL that contains ALTER operation', () => {
const sql = `alter table countries drop column id if exists;`
const result = isReadOnlySelect(sql)
expect(result).toBe(false)
})
test('Should return false for SQL that contains DROP operation', () => {
const sql = `drop table if exists countries;`
const result = isReadOnlySelect(sql)
expect(result).toBe(false)
})
test('Should return false for SQL that contains CREATE operation', () => {
const sql = `create schema test_schema;`
const result = isReadOnlySelect(sql)
expect(result).toBe(false)
})
test('Should return false for SQL that contains REPLACE operation', () => {
const sql = `create or replace view test_view as select * from countries where id > 500;`
const result = isReadOnlySelect(sql)
expect(result).toBe(false)
})
test('Should return false for SQL that calls a function not whitelisted', () => {
const sql = `select create_new_user();`
const result = isReadOnlySelect(sql)
expect(result).toBe(false)
})
test('Should return true for SQL that calls a function that is whitelisted', () => {
const sql = `select count(select * from countries);`
const result = isReadOnlySelect(sql)
expect(result).toBe(true)
})
test('Should return false for SQL that contains a write operation with a read operation', () => {
const sql1 = `select count(select * from countries); create schema joshen;`
const result1 = isReadOnlySelect(sql1)
expect(result1).toBe(false)
const sql2 = `create schema joshen; select count(select * from countries);`
const result2 = isReadOnlySelect(sql2)
expect(result2).toBe(false)
})
})
describe('AIAssistant.utils.ts:hasPendingToolApproval', () => {
test('Should return true when an assistant message has a pending tool approval', () => {
const messages = createMessageWithPart(pendingSqlApprovalPart)
expect(hasPendingToolApproval(messages)).toBe(true)
})
test('Should return false when approval has already been answered', () => {
const messages = createMessageWithPart({
type: 'tool-execute_sql',
toolCallId: 'call-1',
state: 'approval-responded',
input: { sql: 'select 1', label: 'Test query' },
approval: { id: 'approval-1', approved: true },
})
expect(hasPendingToolApproval(messages)).toBe(false)
})
test('Should ignore non-assistant messages', () => {
const messages = createMessageWithPart(pendingSqlApprovalPart, 'user')
expect(hasPendingToolApproval(messages)).toBe(false)
})
test('Should return true for dynamic tool approvals', () => {
const messages = createMessageWithPart({
type: 'dynamic-tool',
toolName: 'execute_sql',
toolCallId: 'call-1',
state: 'approval-requested',
input: { sql: 'select 1', label: 'Test query' },
approval: { id: 'approval-1' },
})
expect(hasPendingToolApproval(messages)).toBe(true)
})
})
describe('AIAssistant.utils.ts:resolvePendingToolApprovalsAsDenied', () => {
test('Should convert pending approvals into denied outputs', () => {
const messages = createMessageWithPart(pendingSqlApprovalPart)
const resolvedMessages = resolvePendingToolApprovalsAsDenied(messages)
const [part] = resolvedMessages[0].parts
expect(part).toMatchObject({
state: 'output-denied',
approval: {
id: 'approval-1',
approved: false,
reason: 'Skipped because the user sent a follow-up message.',
},
})
})
test('Should leave completed approvals unchanged', () => {
const messages = createMessageWithPart({
type: 'tool-execute_sql',
toolCallId: 'call-1',
state: 'output-available',
input: { sql: 'select 1', label: 'Test query' },
output: [],
approval: { id: 'approval-1', approved: true },
})
expect(resolvePendingToolApprovalsAsDenied(messages)).toEqual(messages)
})
})
describe('containsLogsSnippets', () => {
test('is true when an attached query is a logs query', () => {
expect(
containsLogsSnippets([{ label: 'Current Query', content: 'select 1', source: 'logs' }])
).toBe(true)
})
test('is false for a database query', () => {
expect(
containsLogsSnippets([{ label: 'Current Query', content: 'select 1', source: 'database' }])
).toBe(false)
})
test('is false once nothing is attached', () => {
expect(containsLogsSnippets([])).toBe(false)
expect(containsLogsSnippets(undefined)).toBe(false)
})
test('ignores plain string attachments, which carry no source', () => {
expect(containsLogsSnippets(['select 1'])).toBe(false)
})
test('is true when only some of several attachments are logs queries', () => {
expect(
containsLogsSnippets([
'select 1',
{ label: 'Current Query', content: 'select 2', source: 'database' },
{ label: 'Other', content: 'select 3', source: 'logs' },
])
).toBe(true)
})
})
describe('formatAttachedSnippets', () => {
test('fences a database query as sql', () => {
expect(
formatAttachedSnippets([{ label: 'Current Query', content: 'select 1', source: 'database' }])
).toBe('```sql\nselect 1\n```')
})
// The fence is how the model tells which attachment is ClickHouse. It also keeps a
// logs query out of MessageMarkdown's `sql` branch, which offers to run the block
// against Postgres and brands it with untrustedSql.
test('fences a logs query as clickhouse', () => {
expect(
formatAttachedSnippets([
{
label: 'Current Query',
content: "select count() from logs where source = 'edge_logs'",
source: 'logs',
},
])
).toBe("```clickhouse\nselect count() from logs where source = 'edge_logs'\n```")
})
test('labels each attachment with its own dialect', () => {
expect(
formatAttachedSnippets([
{ label: 'A', content: 'select 1', source: 'database' },
{ label: 'B', content: 'select 2', source: 'logs' },
])
).toBe('```sql\nselect 1\n```\n```clickhouse\nselect 2\n```')
})
test('falls back to sql for a plain string attachment', () => {
expect(formatAttachedSnippets(['select 1'])).toBe('```sql\nselect 1\n```')
})
})