mirror of
https://github.com/supabase/supabase.git
synced 2026-10-11 04:15:04 +03:00
## Motivation When Assistant runs a potentially destructive tool like `execute_sql`, it stops the LLM request and prompts for client-side approval and execution of the tool. After approval, a second request kicks off under a separate trace. This has made scoring and [Topics](https://www.braintrust.dev/blog/topics) classification challenging, as the generated `output` is split across stateless requests. The [span-level scoring](https://www.braintrust.dev/docs/evaluate/custom-code#score-spans) approach we've used thusfar (after the LLM call, we massage the result into an `output` payload that's stuck onto the root span) has been cumbersome and led to invalid scores / topics where only part of the assistant response is considered. It's also inefficient, as we're duplicating potentially large info (like the `search_docs` output) that already exists within the trace. An alternative to scoring spans is to [score traces](https://www.braintrust.dev/docs/evaluate/custom-code#score-traces). Braintrust [best practices](https://www.braintrust.dev/docs/evaluate/score-online#best-practices) advise: > Use span scope for evaluating individual operations or outputs. Use trace scope for evaluating multi-turn conversations, overall workflow completion, or when your scorer needs access to the full execution context. We've also received [direct guidance](https://supabase.slack.com/archives/C05QYJBLX89/p1777925770927149?thread_ts=1777905716.911979&cid=C05QYJBLX89) from their team to use this approach. ## Changes Migrates eval scorers from custom `AssistantEvalOutput` shape to trace-level scoring via `trace.getThread()` / `trace.getSpans()`, with thread parsing that scores the full latest Assistant turn and passes prior conversation separately where relevant. Moves `execute_sql` and `deploy_edge_function` from client-side execution after approval to AI SDK `needsApproval` + server-side `execute()`. SQL results returned to the model are gated by AI opt-in level, so row data is only included with `schema_and_log_and_data`; otherwise the tool returns the no-data-permissions sentinel. Adds `metadata.isFinalStep` to disambiguate multiple LLM requests within an "assistant" turn due to tool call requests/responses. For online evals, this means we should configure automations to only score traces with `metadata.isFinalStep = true` to ensure we're judging the complete generated response. Other minor kaizen changes: - Renamed `promptProviderOptions` to `systemProviderOptions` to clarify that this is associated with the "system" message and disambiguate from the root `providerOptions` - Adds `evals/trace-utils.ts` to handle Zod validation of the `unknown` span shapes from Braintrust, to more easily access typed inputs/output on tool spans. - Bumps AI SDK floor version `^6.0.116` → `^6.0.174` - Tweaked the "Conciseness" scorer to not unfairly dock points for the new `[called tool_name]` labels in serialized assistant response ## Verification In the studio staging build, I asked Assistant to create a todos table with 3 sample todos. I manually approved the `execute_sql` call and saw Assistant generate text before & after the call. In Braintrust I verified two traces were produced (see [filtered logs](https://www.braintrust.dev/app/supabase.io/p/Assistant/logs?v=Staging&tvt=trace&search={%22filter%22:[{%22text%22:%22metadata.environment%2520%253D%2520%27staging%27%22,%22label%22:%22metadata.environment%2520%253D%2520%27staging%27%22,%22originType%22:%22btql%22},{%22text%22:%22%2560Chat%2520ID%2560%2520%253D%2520%25221cb2ac45-e5e7-458c-9da4-3bf6863b8842%2522%22,%22label%22:%22Chat%2520ID%2520equals%25201cb2ac45-e5e7-458c-9da4-3bf6863b8842%22,%22originType%22:%22form%22}]})), the first with `metadata.isFinalStep = false` and the second with `metadata.isFinalStep = true`. In the Braintrust staging scorers, I ran the preview Completeness scorer on the second trace and verified it sees the complete Assistant response including markers for tool calls ([link to trace](https://www.braintrust.dev/app/supabase.io/p/Assistant%20(Staging%20Scorers)/trace?object_type=project_logs&object_id=b5214b62-ad1e-4929-9d5b-40b1daebe948&r=0ed0a4f8-8aff-4a34-bb1d-1df1d88a5070&s=ff9015f8-6bf7-4ab3-83a9-ca4e69e27e82)) <img width="1193" height="960" alt="CleanShot 2026-05-07 at 11 27 10@2x" src="https://github.com/user-attachments/assets/509d4858-c3a1-4068-986d-3aa4d5617d1a" /> I also tested the `deploy_edge_function` workflow and verified it still prompts for permission and warns on deployment of existing functions. **References** - https://www.braintrust.dev/docs/evaluate/custom-code#score-traces - https://ai-sdk.dev/docs/ai-sdk-core/tools-and-tool-calling#tool-execution-approval Supercedes https://github.com/supabase/supabase/pull/45556 and https://github.com/supabase/supabase/pull/45339 Closes AI-473 <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * Tool actions (SQL execution, edge-function deploy) now require explicit user Approve/Deny before proceeding. * **Improvements** * Assistant pauses for approval responses before sending follow-ups, giving clearer control over risky actions. * Deploy/replace flows show confirmation and clearer replace warnings. * Evaluation/scoring updated to use richer trace data for more accurate assistant performance signals. <!-- end of auto-generated comment: release notes by coderabbit.ai -->
139 lines
4.6 KiB
TypeScript
139 lines
4.6 KiB
TypeScript
import { UIMessage as VercelMessage } from '@ai-sdk/react'
|
|
import { useState } from 'react'
|
|
import { toast } from 'sonner'
|
|
import { cn } from 'ui'
|
|
|
|
import { DeleteMessageConfirmModal } from './DeleteMessageConfirmModal'
|
|
import { MessageActions } from './Message.Actions'
|
|
import type { AddToolApprovalResponse, MessageInfo } from './Message.Context'
|
|
import { MessageProvider, useMessageActionsContext, useMessageInfoContext } from './Message.Context'
|
|
import { MessageDisplay } from './Message.Display'
|
|
|
|
function AssistantMessage({ message }: { message: VercelMessage }) {
|
|
const { id, variant, state, isLastMessage, readOnly, rating, isLoading } = useMessageInfoContext()
|
|
const { onCancelEdit, onRate } = useMessageActionsContext()
|
|
|
|
const handleRate = (newRating: 'positive' | 'negative', reason?: string) => {
|
|
onRate?.(id, newRating, reason)
|
|
}
|
|
|
|
return (
|
|
<MessageDisplay.Container
|
|
className={cn(
|
|
variant === 'warning' && 'bg-warning-200',
|
|
state === 'predecessor-editing' && 'opacity-50 transition-opacity cursor-pointer'
|
|
)}
|
|
onClick={state === 'predecessor-editing' ? onCancelEdit : undefined}
|
|
>
|
|
<MessageDisplay.MainArea>
|
|
<MessageDisplay.Content message={message} />
|
|
</MessageDisplay.MainArea>
|
|
{!readOnly && isLastMessage && onRate && !isLoading && (
|
|
<MessageActions alwaysShow>
|
|
<MessageActions.ThumbsUp
|
|
onClick={() => handleRate('positive')}
|
|
isActive={rating === 'positive'}
|
|
disabled={!!rating}
|
|
/>
|
|
<MessageActions.ThumbsDown
|
|
onClick={(reason) => handleRate('negative', reason)}
|
|
isActive={rating === 'negative'}
|
|
disabled={!!rating}
|
|
/>
|
|
</MessageActions>
|
|
)}
|
|
</MessageDisplay.Container>
|
|
)
|
|
}
|
|
|
|
function UserMessage({ message }: { message: VercelMessage }) {
|
|
const { id, variant, state } = useMessageInfoContext()
|
|
const { onCancelEdit, onEdit, onDelete } = useMessageActionsContext()
|
|
const [showDeleteConfirmModal, setShowDeleteConfirmModal] = useState(false)
|
|
|
|
return (
|
|
<>
|
|
<MessageDisplay.Container
|
|
className={cn(
|
|
'mt-6 text-foreground',
|
|
variant === 'warning' && 'bg-warning-200',
|
|
state === 'predecessor-editing' && 'opacity-50 transition-opacity cursor-pointer'
|
|
)}
|
|
onClick={state === 'predecessor-editing' ? onCancelEdit : undefined}
|
|
>
|
|
<MessageDisplay.MainArea>
|
|
<MessageDisplay.ProfileImage />
|
|
<MessageDisplay.Content message={message} />
|
|
</MessageDisplay.MainArea>
|
|
<MessageActions>
|
|
<MessageActions.Edit
|
|
onClick={state === 'idle' ? () => onEdit(id) : onCancelEdit}
|
|
tooltip={state === 'idle' ? 'Edit message' : 'Cancel editing'}
|
|
/>
|
|
<MessageActions.Delete onClick={() => setShowDeleteConfirmModal(true)} />
|
|
</MessageActions>
|
|
</MessageDisplay.Container>
|
|
<DeleteMessageConfirmModal
|
|
visible={showDeleteConfirmModal}
|
|
onConfirm={() => {
|
|
onDelete(id)
|
|
setShowDeleteConfirmModal(false)
|
|
toast.success('Message deleted successfully')
|
|
}}
|
|
onCancel={() => setShowDeleteConfirmModal(false)}
|
|
/>
|
|
</>
|
|
)
|
|
}
|
|
|
|
interface MessageProps {
|
|
id: string
|
|
message: VercelMessage
|
|
isLoading: boolean
|
|
readOnly?: boolean
|
|
variant?: 'default' | 'warning'
|
|
addToolApprovalResponse?: AddToolApprovalResponse
|
|
onDelete: (id: string) => void
|
|
onEdit: (id: string) => void
|
|
isAfterEditedMessage: boolean
|
|
isBeingEdited: boolean
|
|
onCancelEdit: () => void
|
|
isLastMessage?: boolean
|
|
onRate?: (id: string, rating: 'positive' | 'negative', reason?: string) => void
|
|
rating?: 'positive' | 'negative' | null
|
|
}
|
|
|
|
export function Message(props: MessageProps) {
|
|
const message = props.message
|
|
const { role } = message
|
|
const isUserMessage = role === 'user'
|
|
|
|
const messageInfo = {
|
|
id: props.id,
|
|
isLoading: props.isLoading,
|
|
readOnly: props.readOnly,
|
|
variant: props.variant,
|
|
state: props.isBeingEdited
|
|
? 'editing'
|
|
: props.isAfterEditedMessage
|
|
? 'predecessor-editing'
|
|
: 'idle',
|
|
isLastMessage: props.isLastMessage,
|
|
rating: props.rating,
|
|
} satisfies MessageInfo
|
|
|
|
const messageActions = {
|
|
addToolApprovalResponse: props.addToolApprovalResponse,
|
|
onDelete: props.onDelete,
|
|
onEdit: props.onEdit,
|
|
onCancelEdit: props.onCancelEdit,
|
|
onRate: props.onRate,
|
|
}
|
|
|
|
return (
|
|
<MessageProvider messageInfo={messageInfo} messageActions={messageActions}>
|
|
{isUserMessage ? <UserMessage message={message} /> : <AssistantMessage message={message} />}
|
|
</MessageProvider>
|
|
)
|
|
}
|