Files
supabase/apps/studio/evals/assistant.eval.ts
Matt Rossman 4553f09bb5 feat(assistant): hallucination scorers + corrective measures for storage versioning answers (#41655)
* feat: "Docs Faithfulness" scorer

* feat: test case for storage object restoration

* feat: "Factuality" scorer

* feat: "Factuality" -> "Correctness"

* feat: update Storage recovery test case

* feat: finishReason in task output

* feat: encourage parallel tool calls + docs search, discourage superfluous context gathering

* prompt tuning (tool selection strategy)

* add data recovery section in chat prompt

* test: S3 versioning support correctness

* refactor: derive stepsSerialized/textOnly from shared steps data

* fix: input in correctness scorer
2026-01-15 14:22:46 +07:00

128 lines
3.1 KiB
TypeScript

import { openai } from '@ai-sdk/openai'
import { Eval } from 'braintrust'
import { generateAssistantResponse } from 'lib/ai/generate-assistant-response'
import { getMockTools } from 'lib/ai/tools/mock-tools'
import assert from 'node:assert'
import { dataset } from './dataset'
import {
completenessScorer,
concisenessScorer,
correctnessScorer,
docsFaithfulnessScorer,
goalCompletionScorer,
sqlSyntaxScorer,
toolUsageScorer,
} from './scorer'
import { ToolSet, TypedToolCall, TypedToolResult } from 'ai'
assert(process.env.BRAINTRUST_PROJECT_ID, 'BRAINTRUST_PROJECT_ID is not set')
assert(process.env.OPENAI_API_KEY, 'OPENAI_API_KEY is not set')
Eval('Assistant', {
projectId: process.env.BRAINTRUST_PROJECT_ID,
data: () => dataset,
task: async (input) => {
const result = await generateAssistantResponse({
model: openai('gpt-5-mini'),
messages: [{ id: '1', role: 'user', parts: [{ type: 'text', text: input }] }],
tools: await getMockTools(),
})
const finishReason = await result.finishReason
// `result.toolCalls` only shows the last step, instead aggregate tools across all steps
const steps = await result.steps
const simplifiedSteps = steps.map((step) => ({
text: step.text,
toolCalls: step.toolCalls.map((call) => ({
toolName: call.toolName,
input: call.input,
})),
}))
const toolNames: string[] = []
const sqlQueries: string[] = []
const docs: string[] = []
for (const step of steps) {
for (const [i, toolCall] of step.toolCalls.entries()) {
toolNames.push(toolCall.toolName)
const toolResult = step.toolResults.at(i)
if (!toolResult) {
continue
}
const parsed = parseToolCall(toolCall, toolResult)
if (parsed.sqlQuery) {
sqlQueries.push(parsed.sqlQuery)
}
if (parsed.docs) {
docs.push(...parsed.docs)
}
}
}
return {
finishReason,
steps: simplifiedSteps,
toolNames,
sqlQueries,
docs,
}
},
scores: [
toolUsageScorer,
sqlSyntaxScorer,
goalCompletionScorer,
concisenessScorer,
completenessScorer,
docsFaithfulnessScorer,
correctnessScorer,
],
})
type ParsedToolCall = {
/** Query generated by `execute_sql` */
sqlQuery?: string
/** Docs text pulled in from `search_docs` */
docs?: string[]
}
/**
* Validate and extract relevant info from a tool call/result
*/
function parseToolCall(
toolCall: TypedToolCall<ToolSet>,
toolResult: TypedToolResult<ToolSet>
): ParsedToolCall {
switch (toolCall.toolName) {
case 'execute_sql': {
const sqlQuery = toolCall.input.sql
if (typeof sqlQuery !== 'string') {
return {}
}
return { sqlQuery }
}
case 'search_docs': {
const content = toolResult.output.content
if (!content || !Array.isArray(content)) {
return {}
}
const docs = content.map((item) => item?.text).filter((text) => typeof text === 'string')
if (docs.length === 0) {
return {}
}
return { docs }
}
}
return {}
}