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## 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? Bug fix for #42574 ## What is the current behavior? If you setup a self-hosted Supabase environment and ask local AI assistant it is unable to interpret the results for executed SQL queries. ## What is the new behavior? Local AI assistant can now read schemas and interpret the results for executed SQL queries. ## Additional context I tested it using ollama with a smaller model which does not support reasoning mode so It would be useful if someone can test it using an actual OpenAI API KEY. The main issue was that `executeSql` returns a wrapped `{ result: {...} }` on `fallback-tools.ts` making the model think there's no result. The solution is just to unwrap it like it's done at: `apps/studio/data/database-functions/database-functions-query.ts`: ``` export async function getDatabaseFunctions(...) { ... const { result } = await executeSql(...) ... return result as DatabaseFunction[] } ``` Also added a `false` default value in `execute_sql` tool schema so zod validation does not reject a valid LLM tool call if the model omits the field (which happened with the smaller model) <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **Refactor** * Optimized internal schema metadata query handling in AI tools. * **Chores** * Enhanced SQL execution tool robustness by providing a sensible default for query type specification when not explicitly provided. <!-- end of auto-generated comment: release notes by coderabbit.ai --> Co-authored-by: Andrey A. <56412611+aantti@users.noreply.github.com>
72 lines
2.6 KiB
TypeScript
72 lines
2.6 KiB
TypeScript
import { tool } from 'ai'
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import { z } from 'zod'
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import {
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EDGE_FUNCTION_PROMPT,
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PG_BEST_PRACTICES,
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REALTIME_PROMPT,
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RLS_PROMPT,
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} from '@/lib/ai/prompts'
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import { fixSqlBackslashEscapes } from '@/lib/ai/util'
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const KNOWLEDGE = {
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pg_best_practices: PG_BEST_PRACTICES,
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rls: RLS_PROMPT,
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edge_functions: EDGE_FUNCTION_PROMPT,
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realtime: REALTIME_PROMPT,
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} as const
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type KnowledgeName = keyof typeof KNOWLEDGE
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export const getStudioTools = () => ({
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execute_sql: tool({
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description: 'Asks the user to execute a SQL statement and return the results',
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inputSchema: z.object({
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// Transform at parse time so the corrected SQL is what gets stored in
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// toolCall.input — ensuring evals and logs reflect what actually runs.
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sql: z.string().describe('The SQL statement to execute.').transform(fixSqlBackslashEscapes),
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label: z.string().describe('A short 2-4 word label for the SQL statement.'),
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chartConfig: z
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.object({
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view: z.enum(['table', 'chart']).describe('How to render the results after execution'),
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xAxis: z.string().optional().describe('The column to use for the x-axis of the chart.'),
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yAxis: z.string().optional().describe('The column to use for the y-axis of the chart.'),
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})
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.describe('Chart configuration for rendering the results'),
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isWriteQuery: z
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.boolean()
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.default(false)
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.describe(
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'Whether the SQL statement performs a write operation of any kind instead of a read operation'
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),
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}),
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}),
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deploy_edge_function: tool({
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description:
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'Ask the user to deploy a Supabase Edge Function from provided code on the client. Client will confirm before deploying and return the result',
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inputSchema: z.object({
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name: z.string().describe('The URL-friendly name/slug of the Edge Function.'),
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code: z.string().describe('The TypeScript code for the Edge Function.'),
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}),
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}),
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rename_chat: tool({
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description: `Rename the current chat session when the current chat name doesn't describe the conversation topic.`,
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inputSchema: z.object({
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newName: z.string().describe('The new name for the chat session. Five words or less.'),
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}),
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execute: async () => {
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return { status: 'Chat request sent to client' }
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},
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}),
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load_knowledge: tool({
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description:
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'Load detailed knowledge about a Supabase topic before answering questions about it.',
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inputSchema: z.object({
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name: z
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.enum(Object.keys(KNOWLEDGE) as [KnowledgeName, ...KnowledgeName[]])
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.describe('The knowledge to load'),
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}),
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execute: ({ name }) => KNOWLEDGE[name],
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}),
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})
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