mirror of
https://github.com/supabase/supabase.git
synced 2026-10-05 09:25:06 +03:00
7798e42435d480ead46cee9f2e39e0ee4bdecd3e
10
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Charis
|
7798e42435 |
feat(studio): notebook read tools (#48908)
## Summary - Adds `list_notebooks` (cursor-paginated) and `get_notebook` AI tools in `lib/ai/tools/notebook-tools.ts`, modeled directly on `report-tools.ts`: server-side `getContent`/`getNotebook` with the `authorization` header forwarded, zod-validated input. - `get_notebook` resolves every cell and exposes `unchecked_sql` as a plain `sql` field for the agent to read — display only, per the `safe-sql-execution` skill; nothing here executes SQL. - Registers both tools in `lib/ai/tools/index.ts` (same platform branch as reports) and in `lib/ai/tool-filter.ts`'s `toolSetValidationSchema` + `TOOL_CATEGORY_MAP` (`SCHEMA` tier). - Adds an optional `headers` param to `content-infinite-query.ts`'s `getContent`, mirroring the sibling `content-query.ts`, so the cursor-paginated fetch can carry the `Authorization` header from a server context. - New tools are behind the Explorer feature flag. Stacked on #48907 (1.4 — notebook query and mutation hooks), per the Notebooks implementation plan (stack 2.1). Resolves FE-4081 Resolves FE-4080 ## Test plan - [x] `pnpm exec tsc --noEmit` — no new errors - [x] `pnpm exec vitest run lib/ai/tools/notebook-tools.test.ts lib/ai/tools/index.test.ts lib/ai/tools/report-tools.test.ts data/content/notebooks` — 36/36 passing - [x] `pnpm --filter studio run lint` — no new warnings - [x] `pnpm exec prettier --check` on changed files — clean <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * Added AI tools to list project notebooks with pagination. * Added AI support for retrieving notebook markdown and resolved SQL cell content. * Notebook tools now respect project and authorization context. * Notebook features are available only when Explorer access is enabled. * Content requests can forward custom request headers. * **Tests** * Added coverage for notebook tools, Explorer access, feature flags, authorization, pagination, and error handling. <!-- end of auto-generated comment: release notes by coderabbit.ai --> |
||
|
Joshen Lim
|
2c53ca4a79 |
Support listing and reading custom reports from Assistant (#48530)
## Context This is pre-requisite work for adding support to managing custom reports from the Assistant. Planning to break this into a number of PRs, briefly - Adding read support for custom reports - Adding write support for custom reports - Adding run support for custom reports - Should be able to infer data from the results then This PR starts with adding support for listing and reading custom reports from the Assistant ## Other changes involved - Updates setting up of the home page report to have better title and description - Swaps the variant of the ToggleGroup in the SQL block for custom reports as the default variant blends into the background color of the PopoverContent ## To test - [ ] Assistant should be able to list custom reports + read its contents <img width="428" height="755" alt="image" src="https://github.com/user-attachments/assets/6a15b660-c0ee-4a06-984c-87eff3943eec" /> <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **New Features** - Added AI-assisted tools to list reports and retrieve report details, including chart counts, layouts, configurations, and SQL-backed chart information. - Added clearer empty-state messaging when no snippets are available. - **Improvements** - New homepage reports now use the name “Homepage Report” and include a descriptive project-home summary. - Updated query controls with refreshed visual styling. - Improved content requests to support additional request context. <!-- end of auto-generated comment: release notes by coderabbit.ai --> |
||
|
Joshen Lim
|
4901f081e5 |
Migrate remaining requests to pg-meta API to use query endpoint (#47758)
## Context Migrates the remaining API requests to the pg-meta endpoint to use the query endpoint directly with the SQL from the pg-meta package. This touches the following: - policies - publications - triggers - views - materialized views - types ## To test Just need to verify that we're still fetching the data correctly on these pages - Database policies - Database publications - Database triggers - Database tables (views + materialized views) - Database types <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **Bug Fixes** * Improved and stabilized loading of database metadata (views, triggers, RLS policies, publications, materialized views, and enum types), including more reliable schema-scoped filtering. * Updated policy loading behavior and related UI queries to consistently use schema arrays, improving cache correctness and consistency. * **Tests** * Updated end-to-end test synchronization to wait for the correct metadata responses using more specific request identifiers. <!-- end of auto-generated comment: release notes by coderabbit.ai --> |
||
|
Carel de WaalandAlaister Young
|
0acc0eb8b3 |
feat: Support Form - Sync AI assistant conversation to Front (#46778)
# Sync AI assistant conversation to Front ## What & why When a user submits a support ticket, an AI assistant chat opens so they get help immediately while waiting for a human agent. This PR mirrors every turn of that chat into the Front conversation the support form already created, so the support team sees the full context and Front automations (routing, emails, CSAT) can act on it. Studio holds no Front credentials — it calls the platform endpoints (see the platform PR) to do the syncing. The assistant card is gated behind the `supportAssistantFollowUp` ConfigCat flag. ## How it works 1. **Submit** — `SupportFormV3` generates a stable `threadRef` (via the `uuid` package — `crypto.randomUUID()` is `undefined` in insecure contexts like non-localhost HTTP and would throw, silently aborting the submit) and sends it on `/platform/feedback/send`. The response returns the Front `conversationId`. Both are stored on `SubmittedSupportRequest`. 2. **Open chat** — `SupportAssistantSuccessCardContent` opens a chat seeded with `supportMetadata` (`threadRef`, `frontConversationId`, subject, category, severity, …). The first message is a `<support>…</support>` XML block. 3. **First user message** — the chat is tagged `isSupportChat = true`; the `onFinish` hook fires `syncSupportChatToFront`. 4. **Subsequent turns** — each `onFinish` slices the unsynced delta, strips the XML metadata block from the seed message, and posts to the platform messages endpoint. 5. **Escalation / resolve** — the `escalate_to_human` / `resolve_support_conversation` tools (and manual **Escalate**/**Resolve** buttons in the assistant input) flip lifecycle status via `setSupportLifecycleStatus` → `syncSupportLifecycleToFront`, which calls the escalation/resolve endpoints. Front rules act on `ai_support_status`. The assistant only resolves after the user explicitly confirms the issue is fixed. ## Key design decisions - **`threadRef` as the shared key** — one UUID travels as `threadRef` on submit and as `chatId` on every sync, so all messages thread into a single Front conversation. - **`conversationId` from the form response** — passed to all sync/lifecycle calls so the platform skips lazy derivation and PATCHes custom fields directly. - **Delta-only sync** — `lastSyncedMessageCount` tracks what's been sent; the boundary is snapshotted before the async call to avoid skipping messages that arrive mid-flight. - **Server-side de-dup** — stable `external_id` (`chatId:msg.id`) means retries don't duplicate in Front. - **Fire-and-forget** — sync failures log to Sentry, never break the chat; `isSyncing` resets on rehydration so the next `onFinish` retries the same delta. Message and lifecycle syncs use separate guards (`isSyncing` / `isLifecycleSyncing`) so an in-flight message sync can't drop an escalate/resolve. - **Lifecycle queued until the conversation exists** — if a lifecycle transition is requested before the initial message sync has returned a `frontConversationId`, it's stored as `pendingLifecycleStatus` and flushed once the id is assigned, rather than dropped. - **Tools return immediately** — the lifecycle tools return a stub to the AI SDK; the real Front call happens in `onFinish`, keeping async I/O out of the tool execute path. - **XML seed stripped before sync** — only the user's actual `<message>` is sent to Front (or dropped entirely if the form already created the conversation). ## Changes | Area | File(s) | | --- | --- | | Support form state | `SupportForm.state.ts` — `threadRef` / `frontConversationId` on `SubmittedSupportRequest` | | Support form submit | `support-ticket-send.ts` — sends `threadRef`, reads `conversationId` | | Support form UI | `SupportFormV3.tsx` — generates `threadRef`, stores `conversationId` | | AI assistant state | `ai-assistant-state.tsx` — `SupportChatMetadata`, `setSupportLifecycleStatus`, `onFinish` wiring, tool handling | | Message sync | `state/ai-chat-front-sync.ts` — delta tracking, message filtering, initial vs. incremental | | API data layer | `data/feedback/ai-chat-front-sync.ts` — typed platform-client wrappers for the three conversation endpoints | | Support tools | `lib/ai/tools/support-tools.ts` — `escalate_to_human`, `resolve_support_conversation` | | Tool integration | `lib/ai/tool-filter.ts`, `tools/index.ts`, `generate-assistant-response.ts` | | Success card | `SupportAssistantSuccessCardContent.tsx` — tags chat on first engagement | | Assistant panel UI | `AIAssistant.tsx` — Escalate/Resolve buttons, disabled input on closed chats, support placeholders | <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit ## Summary by CodeRabbit - **New Features** - Support chats now include “Escalate to human” and “Resolve” actions. - Support submissions can be associated with a stable Front thread via a generated `threadRef`, preserving linkage across follow-ups. - AI assistant responses and input hints adapt when support mode is active. - **Bug Fixes** - Improved support chat state management and lifecycle handling to keep conversation metadata and message history synchronized more reliably with Front. - **Chores** - Added/updated coverage to reflect the new support-chat state and syncing behavior. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: Alaister Young <10985857+alaister@users.noreply.github.com> |
||
|
Pedro RodriguesandClaude Opus 4.8
|
c4c213ce3d |
feat(studio): switch dashboard assistant to remote MCP server (#47479)
## 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 / refactor. ## What is the current behavior? The dashboard assistant runs `@supabase/mcp-server-supabase` in-process over an in-memory transport (`lib/ai/supabase-mcp.ts`). ## What is the new behavior? The assistant connects to the **remote MCP server** over HTTP (`@ai-sdk/mcp`), forwarding the dashboard session token as a bearer. URL comes from `NEXT_PUBLIC_MCP_URL` with a local-dev fallback; platform-only, and Nimbus works via the same env var. * **Tool model unchanged:** UI-controlled `execute_sql` (with `needsApproval`) and `deploy_edge_function` still come from Studio; the allowlist (`TOOL_CATEGORY_MAP`) remains the gate keeping the remote's write tools away from the assistant (`read_only` is defense-in-depth). * **Attribution:** sends `x-source-name: supabase-studio` (+ `x-source-version`) → logged as `source_name`/`client_name`. * **Connection lifecycle:** the HTTP client is closed via the request's `AbortSignal` (tools execute later during streaming); `signal` is required on `getTools`/`getMcpTools`. * **Resilience:** a remote-MCP failure degrades to the remaining tools instead of failing the assistant. * **Drift protection:** relied-upon tools are typed against `keyof typeof supabaseMcpToolSchemas`, so a package bump that renames/removes one fails `pnpm typecheck`; a runtime check also warns if the deployed server returns fewer tools. * Adds unit tests for the above. ## Additional context * Verified end-to-end against a local remote MCP server with a dashboard token: `initialize` 200, tools listed, a tool executed, client closed cleanly. * The remote MCP (mgmt-api) already accepts dashboard session tokens (GoTrue-JWT auth path) — no backend change needed. `NEXT_PUBLIC_MCP_URL` must point at each env's `/mcp`. * `@supabase/mcp-server-supabase` is kept — still used by the self-hosted `/api/mcp` routes. Closes [AI-137](https://linear.app/supabase/issue/AI-137/switch-dashboard-assistant-to-remote-mcp) ## Rollout * **Rollout:** merges with `USE_REMOTE_MCP` off (in-process); flip it to `true` per environment (staging → prod → Nimbus) once each one's prerequisites land. * **Rollback:** unset `USE_REMOTE_MCP` and redeploy to fall back to the in-process client — no revert needed. ## Summary by CodeRabbit * **Bug Fixes** * Improved AI request handling so tool loading and generation clean up properly when a request is cancelled or the browser connection closes. * Added safer fallback behavior when remote tool loading fails, so AI features can continue with available tools instead of stopping entirely. * Updated remote tool access to use the current project reference and preserve the correct access headers. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * AI tools now connect more reliably to remote services and stop cleanly when requests end or are canceled. * Tool loading is more resilient, continuing with available tools if remote access is unavailable. * **Bug Fixes** * Improved cleanup to prevent lingering connections during SQL generation and policy workflows. * Added safer handling for remote tool changes and invalid responses. * **Tests** * Expanded automated coverage for remote tool setup, cancellation, and fallback behavior. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
Matt Rossman
|
d143571586 |
feat(assistant): trace-level scorers + server-side tool execution with needsApproval (#45654)
## 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 --> |
||
|
Charis
|
205cbe7d26 | chore(studio}: enforce import order, remove bare import specifiers (#44585) | ||
|
Matt Rossman
|
82deff37de |
feat(assistant): lazy load topic knowledge via load_knowledge tool (#44296)
Moves knowledge (RLS, Edge Functions, PostgreSQL best practices, Realtime) out of the static system prompt and into a `load_knowledge` tool the model calls on demand, reducing prompt bloat. This is a temporary stopgap until the [standard Supabase agent-skills](https://github.com/supabase/agent-skills) are ready for integration in Assistant. - New always-available `load_knowledge` tool added to `rendering-tools.ts` - Updated `Message.Parts.tsx` so the "Ran load_knowledge" chip renders in chat - System prompt replaces the four knowledge blobs with an `## Available Knowledge` block and is hardened to load knowledge for given topics - New "Knowledge Usage" scorer and `requiredKnowledge` assertions check that knowledge loads as expected in test scenarios - Filters GraphQL error responses out of `output.docs` before faithfulness scoring to reduce noise See "Knowledge Usage" scoring 100% in evals with no major regressions: https://github.com/supabase/supabase/pull/44296#issuecomment-4145760236 Sample trace showing the tool in action ([Braintrust](https://www.braintrust.dev/app/supabase.io/p/Assistant/trace?object_type=project_logs&object_id=5a8d02e5-b3b6-40cc-ba76-ecee286478f4&r=351a11c8-9cb7-4945-93ad-d11e8cc2e3e1&s=351a11c8-9cb7-4945-93ad-d11e8cc2e3e1)) <img width="2192" height="1730" alt="CleanShot 2026-03-30 at 13 53 59@2x" src="https://github.com/user-attachments/assets/f483767c-34e0-401c-8089-5b9834fe696a" /> **References** - https://ai-sdk.dev/cookbook/guides/agent-skills Closes AI-508 <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * Added dynamic knowledge loading capability enabling the AI assistant to retrieve on-demand information about PostgreSQL best practices, Row Level Security, Edge Functions, and Realtime. * **Bug Fixes** * Improved search results filtering to exclude error responses in tool outputs. * **Tests** * Enhanced evaluation metrics with knowledge usage scoring. * Expanded test dataset cases to validate knowledge requirement handling. <!-- end of auto-generated comment: release notes by coderabbit.ai --> |
||
|
Danny WhiteandCharis Lam
|
05dc676d36 |
feat(studio): incident-aware AI assistant (#41603)
* handling and mock data support * admonition * only show in empty state * rabbit * mock without local overrides * remove admonition * make incident banner more prominent * remove mock data * move to tool * prettier * fix(studio): get_active_incidents tool --------- Co-authored-by: Charis Lam <26616127+charislam@users.noreply.github.com> |
||
|
|
d60aceb562 |
Prompt and tool refactoring (#37500)
* try a really long context window to maximize caching
* update examples
* attempt to update packages and useChat
* update endpoints
* update zod
* zod
* update to v5
* message update
* Revert "zod"
This reverts commit
|