c2ca90c255d50de51907fe48ba8e52804ed9cd6b
45 Commits
| Author | SHA1 | Message | Date | |
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c2ca90c255 |
feat(sdk): add runAgent() to run app agents from logic functions (#21157)
<img width="948" height="593" alt="image" src="https://github.com/user-attachments/assets/d990fa98-3cfd-469d-ab7f-0b2d4ccf3afc" /> <img width="1361" height="802" alt="image" src="https://github.com/user-attachments/assets/1091f598-49f3-4c16-92ea-1e1c200181e2" /> ## Add `runAgent()` to the Logic Function SDK Lets an app's logic function run one of its own AI agents server-side and get the result back synchronously — reusing the existing agent executor instead of a new bespoke transport. ### Backend - New **`runAgent` GraphQL mutation** (metadata schema) in `ai-agent-execution`, wrapping the existing `AgentAsyncExecutorService.executeAgent`. Scopes the agent lookup to the calling application and runs it under an application auth context. - New `@AuthApplication()` param decorator (mirrors `@AuthWorkspace()`) — first GraphQL resolver authenticated by an **application access token**. - Guarded by `WorkspaceAuthGuard` + `SettingsPermissionGuard(PermissionFlagType.AI)`: the app's role must grant the `AI` permission flag. ### SDK - `runAgent({ agentUniversalIdentifier, prompt })` posts the mutation to `/metadata` with the app token via a new runtime GraphQL transport. Returns `{ result, hasNoMoreAvailableCredits }`. - Refactored the connections helpers onto a shared `postAppEndpoint` util (removes duplicated transport logic). ### Frontend - App install permission modal now shows an explicit consent line — _"Run AI agents and bill AI credits to your workspace"_ — when the app's role requests the `AI` flag. ### Docs - Documented `runAgent` and its `AI` permission-flag requirement in _Skills & Agents_. - Fixed outdated role-permission examples in _Roles & Permissions_ (`permissionFlags` → `permissionFlagUniversalIdentifiers`, `PermissionFlag` → `SystemPermissionFlag`). ### Test plan - [x] SDK unit tests (`run-agent.spec.ts`) — request shape, GraphQL/HTTP error handling, missing env vars - [x] `twenty-server`, `twenty-front`, `twenty-shared` typecheck + lint - [ ] Manual: install an app granting the `AI` flag, call `runAgent()` from a logic function, confirm the agent runs and credits are billed --------- Co-authored-by: cubic-dev-ai[bot] <191113872+cubic-dev-ai[bot]@users.noreply.github.com> |
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4b15b949f3 |
Provide additional logsobservability to workflow runs (per node) (#21142)
Surfaces per-step "Logs" tabs in the workflow run side panel so users can see what each step actually did (model + tokens + tool calls for AI, console output for serverless functions, request/response for HTTP, recipients/body for Email). <img width="546" height="501" alt="ai_agent_without_websearch" src="https://github.com/user-attachments/assets/c6ca3518-9489-4484-a570-3d0569ff3b03" /> ## Storage - New `stepLogs` JSONB column on the `workflowRun` workspace entity, typed as `Record<string, WorkflowRunStepLog>` (keyed by step id). - Schema lives in `twenty-shared`: `workflowRunStepLogSchema` with a discriminated `details.type` union for `AI_AGENT | CODE | HTTP_REQUEST | EMAIL` — frontends and backends consume the same Zod-inferred type. - Field is added to existing workspaces via a workspace upgrade command (`2-9 add-workflow-run-step-logs-field`); the standard-object metadata declares it for new workspaces. - Writes happen atomically per step in `WorkflowRunStepLogWorkspaceService.setStepLog` using `jsonb_set`. That lets concurrent steps in the same run write their own keys without contending with the existing lock around `workflowRun.state`. - Per-step payload is hard-capped at 256 KB; anything larger is dropped with a `logger.warn`, so a pathological tool call can never bloat a row. See below for more information. ## How logs are produced **Aalmost everything was already being collected; this PR mostly persists and renders it.** - **AI agent** — `AgentAsyncExecutorService` already tracked token usage, model id, native web-search count, and the AI SDK's `steps[]`. We map those into the log via `mapAiStepsToToolCallLogs` (`searchVector` stripped from record outputs, per-call input/output capped at 32/64 KB, max 200 tool calls per step). The only new measurement is a wall-clock `durationMs` taken around `executeAgent`, and we now fold native web-search cost into the displayed `totalCostInDollars` (it was already billed, just not shown). - **Code / serverless function** — reuses the `console.log` output the function runner already returns (`logsByLevel`); `build-code-step-log.util` only repackages it. - **HTTP request** — built from the action's existing input/output via `build-http-request-step-log.util`. No new signals collected. - **Email (send / draft)** — added `sanitizedHtmlBody` + `plainTextBody` to the existing tool outputs (a small additive change), then `build-email-step-log.util` consumes them. No additional AI inference or external calls are made for logging — the cost is a small CPU overhead per step plus the JSONB write. ## Security The log surface intentionally shows whatever the workflow touched, which made redaction and sanitization the main design concern. - **HTTP — secrets in headers**: existing `SENSITIVE_HEADER_NAMES` set (Authorization, Cookie, …) replaced with `[redacted]` in both request and response. - **HTTP — secrets in URLs**: `SENSITIVE_URL_PARAM_NAMES` (e.g. `api_key`, `token`, `access_token`) replaced in the query string via `URL`-based parsing. - **HTTP — secrets in bodies**: `SENSITIVE_BODY_KEY_REGEX` deep-walks JSON request/response bodies (object input or stringified JSON) and redacts matching keys. Applied to the `error` field too, since transport-layer errors sometimes embed structured payloads. - **Email — XSS risk in body preview**: tool outputs now expose a server-side `sanitizedHtmlBody`; the log builder prefers it over the raw user-authored `input.body`, with `plainTextBody` as a second fallback. The original raw body is only used if sanitization didn't happen (e.g. tool failed before composing). - **AI — internal/noisy data**: `searchVector` (Postgres tsvector strings) is stripped from record outputs returned by Twenty tools to avoid leaking internal full-text-search payloads. - **DB bloat / runaway agents**: 256 KB per-step cap + 32 KB / 64 KB per-tool-call input/output cap + 200 tool calls per step. <img width="547" height="307" alt="logic_function" src="https://github.com/user-attachments/assets/dd4a3d16-67f2-434b-95b3-bdcaf9ed053d" /> ## More details on Log size & truncation Logs are stored in `workflowRun.stepLogs` (JSONB), keyed by `stepId`. ### Per-step cap Each step's log is hard-capped at **256 KB** (`MAX_STEP_LOG_BYTES` in `WorkflowRunStepLogWorkspaceService.setStepLog`). For ~99% of workflows this is roomy — typical real-world sizes: - Code / serverless function: 1–20 KB - HTTP request: 5–70 KB - Email: 5–30 KB - AI agent (a handful of tool calls): 5–50 KB ### Two layers of bounding 1. **Per-field truncation** in each builder (before writing): - **Code**: ≤ 500 entries, ≤ 4 KB per message, ≤ 8 KB stack trace - **HTTP**: ≤ 32 KB per body (request + response), UTF-8 byte-aware - **Email**: ≤ 8 KB body preview, UTF-8 byte-aware - **AI agent**: ≤ 32 KB tool input, ≤ 64 KB tool output, ≤ 200 tool calls/step 2. **Global per-step safety net** at write time: if the assembled `stepLog` still exceeds 256 KB, the write is **dropped entirely** with a `logger.warn`. The workflow itself keeps running unaffected. ### What this means in practice - **Safe**: workflow execution, step results, downstream steps — never blocked by log size. - **Safe**: iterators (each iteration overwrites the previous log for that `stepId`, so they can't accumulate). - **Safe**: step retries (same `stepId` is overwritten, not appended). - **Possible**: an AI agent step with many large tool outputs (e.g., 50+ heavy `web_search` calls) can exceed 256 KB → the **entire** step's log is dropped, side panel shows "No logs were recorded for this step". The user has no explicit signal that the log was dropped due to size (only server-side warn). - **Possible** (theoretical): a workflow with hundreds of distinct steps could push the row toward Postgres's internal ~256 MB jsonb limit. Beyond that, individual `jsonb_set` writes would error and be swallowed by the action's try/catch — workflow still completes. ### Possible future hardening (not in this PR) - Replace "drop entire log" with a stub that preserves the summary card (cost, duration, status) and marks `truncated.reason = 'size_cap'`. - Surface size-drops in the UI (similar to the existing `<StyledTruncatedNotice>`). - Emit a metric so dropped logs are observable in dashboards. |
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e430e4ea0a |
fix(ai): route xAI search through Responses API as native tools (#21037)
xAI deprecated Live Search, so the `searchParameters` provider option now returns 410. This routes all xAI models through the Responses API and binds web/X search as native agent tools, matching how Anthropic/OpenAI expose search. - xAI provider now uses `provider.responses()` — its `webSearch()`/`xSearch()` tools only run against the Responses endpoint, not chat completions - web/X search migrated from the `provider-option` variant to `sdk-tool` (`web_search`/`x_search`); deleted the dead `searchParameters` path, the `provider-option` variant, and `providerOptions` on `NativeModelBinding` - dropped a dead `rolePermissionConfig` param on `getAgentRoleId`, left over from #20331 --------- Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com> Co-authored-by: Félix Malfait <FelixMalfait@users.noreply.github.com> |
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996cdaf3ff |
refactor(agents): split tool resolution into native and action rails (#20331)
## Summary
Splits AI agent tool resolution into two independent rails:
- **Native tools** — capabilities baked into the model SDK
(Anthropic/OpenAI `web_search`, xAI `web`/`x` provider options). Bound
by `NativeToolBinderService`, controlled by per-agent
`modelConfiguration` toggles. Opaque to Twenty — executed on the model
provider's servers.
- **Action tools** — registry-scoped tools from `ToolRegistryService`
(code interpreter, send email, record CRUD, etc.). Permission-gated via
the agent's role. Executed on Twenty's server.
Both rails merge into a single `ToolSet` at call time. When both
surfaces expose a search tool the model picks at runtime — coexistence
is intentional (relevant once Exa returns as an action, see below).
## Notable changes worth calling out
**Contract change: `AgentAsyncExecutorService.executeAgent` no longer
accepts `rolePermissionConfig`.** Workflow agents now scope exclusively
by the agent's own permission-tab role (`unionOf: [agentRoleId]`). The
previous role-merging path (caller role intersected with agent role) is
removed. No agent role → no registry tools (fail-closed by design).
**`NativeToolBinderService` relocated** from
`core-modules/tool-provider/native/` →
`metadata-modules/ai/ai-models/services/`. The binder needs SDK-package
knowledge, which lives in `ai-models`. Old location created a backwards
module dependency.
**`NATIVE_MODEL_TOOLS_BY_SDK_PACKAGE` is exhaustive over
`AiSdkPackage`** (`Record<>`, not `Partial<Record<>>`). Adding a new SDK
without thinking about native tools now fails the build. SDKs without
native tools (Bedrock, Google, Mistral, Azure, OpenAI-compatible) get
explicit `{}` entries.
**Discriminated union `kind: 'sdk-tool' | 'provider-option'`** lets one
registry describe both function tools (Anthropic/OpenAI) and runtime
sources (xAI). Follows the local `tool-provider` convention from #19321.
## Deferred to follow-ups
- **Exa web search is dropped from this PR** (along with its
`WEB_SEARCH_TOOL` permission flag and the Exa-specific gating). Exa
comes back as an **action/app tool** once apps can define permission
flags through the SDK — ongoing work in #20481.
- **xAI native search currently errors.** xAI deprecated its Live Search
API (the `web`/`x` provider-option sources this rail maps to), so xAI
returns `410` when native search is actually exercised. The code path
itself is clear — it's only hit if you test xAI native tools. Fixed
separately alongside the broader xAI model fixes.
## Conscious non-decisions
- **No "twenty-native" category.** `native` is reserved for
model/provider SDK features; everything Twenty-owned is just a
tool/action.
- **Coexistence over precedence.** No rule forcing an action search tool
to override native search (or vice-versa) — when both exist, it's the
user's choice in workflow agents and the model's choice in chat.
---------
Co-authored-by: Félix Malfait <felix.malfait@gmail.com>
Co-authored-by: Félix Malfait <felix@twenty.com>
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f4ead89956 |
refactor(twenty-orm): migrate 23 grandfathered entities to WorkspaceScopedRepository (#20987)
## Summary Follow-up to #20953. Migrates 23 of the 30 entities that were left in `WORKSPACE_SCOPED_EXEMPTIONS` last time, so the lint rule's workspaceId-enforcement default now covers most of the core/metadata schema. ### Migrated (23 entities, 88 files, 22 commits) | Family | Entities | |---|---| | Trivial caches | `NavigationMenuItem`, `Skill`, `DataSource`, `Webhook`, `CommandMenuItem`, `IndexMetadata` | | Views | `View`, `ViewField`, `ViewFieldGroup`, `ViewFilter`, `ViewFilterGroup`, `ViewGroup`, `ViewSort` | | Layouts | `PageLayout`, `PageLayoutTab`, `PageLayoutWidget` | | Roles & permissions | `Role`, `RoleTarget`, `PermissionFlag`, `ObjectPermission`, `FieldPermission`, `RowLevelPermissionPredicate`, `RowLevelPermissionPredicateGroup` | For each entity: swap `@InjectRepository(X)` → `@InjectWorkspaceScopedRepository(X)` (and the field type → `WorkspaceScopedRepository<X>`); rewrite every call site to pass `workspaceId` as the first arg (stripped from `where`/criteria — the wrapper throws if you include it now); register `provideWorkspaceScopedRepository(X)` in every owning NestJS module; update affected spec providers to `getWorkspaceScopedRepositoryToken(X)`. ### Rule update - `ApplicationRegistrationVariableEntity` was misclassified — moved to `STRUCTURAL_EXEMPTIONS` (no `workspaceId` column; it's keyed on `applicationRegistrationId` at the instance level). - 22 of the 23 migrated entities removed from `WORKSPACE_SCOPED_EXEMPTIONS` entirely (zero remaining raw `@InjectRepository` sites). - `RoleTargetEntity` also removed; one call site in `user-workspace.service.ts` keeps a raw injection with an `eslint-disable` + reason because `softRemove(...)` is not on the wrapper API yet (the migration would require threading `workspaceId` through `deleteUserWorkspace`'s three callers). ### Still exempted (7 entities, follow-up PRs) | Entity | Why deferred | |---|---| | `ApplicationEntity` | ~50 sites with several cross-workspace lookups by id (auth, OAuth, file-storage, cleanup) | | `CalendarChannelEntity` / `MessageChannelEntity` | Use `.increment(...)` (not on wrapper) and `repository.manager.transaction(...)` — wrapper needs to grow `.increment` + the transaction sites need `withManager` or dual-inject | | `FieldMetadataEntity` / `ObjectMetadataEntity` | The metadata services `extends TypeOrmQueryService<X>` and `super(rawRepo)` — requires dual-inject or reworking the inheritance | | `KeyValuePairEntity` | Allows `workspaceId: IsNull()` for instance-level config; wrapper rejects null | | `UpgradeMigrationEntity` | Same — instance-level + cross-workspace ledger | ## Test plan - [x] `npx nx typecheck twenty-server` — clean - [x] `npx nx lint twenty-server` — clean (0/0) - [x] All 10 affected unit specs pass (115 tests) — api-key, agent-role, permissions, workspace-roles-permissions-cache, view-filter-group, workflow-version-step-operations, two-factor-authentication (service + resolver), user-workspace, file - [ ] Server integration tests in CI |
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aecfe699f4 |
feat(ai-chat) - Stop ai thinking if credits exhausted (#20526)
Billing is now decremented per-step, not per-turn. The onStepFinish callback in chat-execution.service.ts calls a new decrementAndCheckAvailableCredits method on each model step, so Redis is debited incrementally as the agent runs rather than all at once at the end. Credit exhaustion stops the stream mid-run. When a step depletes the remaining credits, a hasNoMoreAvailableCredits flag is set and passed into the stopWhen predicate of streamText, causing the agent to halt before starting the next step. A new credits-exhausted event is introduced. After the stream drains and the response is persisted, if credits ran out the job publishes a dedicated credits-exhausted event to the frontend instead of the normal message-persisted event. The frontend handles this new event. useAgentChatSubscription has a new credits-exhausted case that sets a BILLING_CREDITS_EXHAUSTED-coded error on the atom, closes the writer, and stops the streaming state — triggering the existing AiChatCreditsExhaustedMessage UI. |
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ac653182b2 |
feat(server): migrate all remaining JWT token types to ES256 (#20513)
## Summary Extends the asymmetric signing work from #20467 to cover **every remaining `JwtTokenTypeEnum` value**: `LOGIN`, `WORKSPACE_AGNOSTIC`, `FILE`, `API_KEY`, `APPLICATION_ACCESS`, `APPLICATION_REFRESH`, `APP_OAUTH_STATE`, plus the ACCESS-shaped session token issued by the code interpreter tool. After this PR, every JWT the server signs is ES256 with a `kid` pointing at the current `core."signingKey"` row, while legacy HS256 tokens (no `kid` header) remain verifiable indefinitely through the existing fallback in `JwtWrapperService.resolveVerificationKey`. No new entity / migration / config: this is a pure routing change on top of the infrastructure that already shipped. ## Why `#20467` only flipped `ACCESS` and `REFRESH` to ES256. Every other JWT type was still HS256-signed against the global `APP_SECRET`, which kept the original blast radius (a leaked `APP_SECRET` invalidates *every* JWT type forever). Migrating the rest unifies the sign path on rotatable per-server private keys without forcing any token reissue. ## Mechanical changes ### Sign side (8 services) - `LoginTokenService.generateLoginToken` - `TransientTokenService.generateTransientToken` - `WorkspaceAgnosticTokenService.generateWorkspaceAgnosticToken` - `ApplicationTokenService.signApplicationToken` (`APPLICATION_ACCESS` + `APPLICATION_REFRESH`) - `ApiKeyService.generateApiKeyToken` - `FileUrlService.signFileByIdUrl` / `signWorkspaceLogoUrl` - `ConnectionProviderOAuthFlowService.signState` (`APP_OAUTH_STATE`) - `CodeInterpreterTool.generateSessionToken` Each call site swaps `jwtWrapperService.sign(payload, { secret: generateAppSecret(...), ... })` for `await jwtWrapperService.signAsync(payload, { expiresIn, [jwtid] })`. The `generateAppSecret` calls on the sign side are dropped (verifier-side `generateAppSecret` stays in `resolveVerificationKey` for the HS256 fallback). ### Verifier side - `WorkspaceAgnosticTokenService.validateToken` now goes through `verifyJwtToken` instead of the bespoke `verify({ secret })` path, so new ES256 tokens are accepted while the legacy HS256 fallback inside `resolveVerificationKey` still serves the old shape. - `JwtWrapperService.sign()` is kept (legacy compat / tests) but is now strictly deprecated — there are no remaining production callers. ### Async ripple (`signFileByIdUrl` was synchronous) - `FileUrlService.signFileByIdUrl` and `signWorkspaceLogoUrl` are now `async`; the `signUrl` callback used by `getRecordImageIdentifier` is widened to accept `Promise<string | null>`. - Every direct/indirect caller is updated: admin panel (user lookup + statistics + top workspaces), search service (`computeSearchObjectResults`, `getImageIdentifierValue`), workspace resolver (`logo` resolver, public workspace by domain/id), `WorkspaceMemberTranspiler` (now `async toWorkspaceMemberDto[s]` / `toDeletedWorkspaceMemberDto[s]` / `generateSignedAvatarUrl`), `UserService.loadSignedAvatarUrlsByUserId`, `UserWorkspaceService.castWorkspaceToAvailableWorkspace`, workspace-invitation, approved-access-domain, agent-chat-streaming, agent-message-part resolver, navigation-menu-item record identifier, file-ai-chat / file-core-picture / file-email-attachment / file-workflow / files-field services, rich-text & files-field query result getters, and the code-interpreter tool. ## Backward compatibility - **Legacy HS256 tokens (no `kid`)** keep verifying via `resolveVerificationKey` → `extractAppSecretBody` → `generateAppSecret` for both `workspaceId`-bearing and `userId`-bearing payloads. - The `API_KEY` HS256-via-ACCESS-secret fallback (#16504) still kicks in inside `verifyJwtToken` for pre-2025-12-12 API keys. - No payload shape changes, no DB writes, no env var changes — old tokens issued by `main` continue to authenticate. ## Tests ### Unit (all green locally — 63/63) Updated specs for every migrated service to mock `signAsync` instead of `sign` and assert the new option shape: - `login-token.service.spec.ts`, `transient-token.service.spec.ts`, `workspace-agnostic-token.service.spec.ts`, `application-token.service.spec.ts`, `api-key.service.spec.ts`, `connection-provider-oauth-flow.service.spec.ts`. ### Integration (`jwt-key-rotation.integration-spec.ts`) - Existing ACCESS coverage (current key, legacy HS256 fallback, rotated-out key, revoked key, unknown kid) is preserved. - New `it.each` assertion: `REFRESH`, `WORKSPACE_AGNOSTIC`, and `LOGIN` tokens emitted by the real signUp → signUpInNewWorkspace → getAuthTokensFromLoginToken pipeline are ES256 with a `kid` matching the current signing key — proves end-to-end that the migration didn't regress those flows. ## Open question (separate decision) This PR keeps the legacy HS256 verification fallback **forever**. We may eventually want to sunset it for `API_KEY` once telemetry shows pre-migration tokens are gone, but that's a separate product/security decision and not part of this change. ## Test plan - [ ] CI green - [ ] `npx nx lint:diff-with-main twenty-server` passes - [ ] `npx nx typecheck twenty-server` passes - [ ] `jwt-key-rotation` integration suite passes (new + existing assertions) - [ ] Manually verify: signing in issues an ES256 ACCESS / REFRESH token, generating an API key issues an ES256 token with `kid`, signed file URL JWT is ES256 with `kid` - [ ] Pre-existing HS256 tokens still authenticate (covered by integration test, but worth a manual check with a token from `main`) |
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a159a68e2c |
[twenty-server] no floating promises lint rule (#20499)
## Introduction
That's an audit + RFC
## Fire-and-forget (`void`) -- Intentional, correct
These are telemetry, metrics, and audit logging in hot paths or
non-critical contexts. `void` is the right choice.
| File | What was voided |
|---|---|
| `sign-in-up.service.ts` | `metricsService.incrementCounter` (sign-up
metric) + `auditService.insertWorkspaceEvent` (workspace created) |
| `use-graphql-error-handler.hook.ts` | 5x
`metricsService.incrementCounter` (GraphQL operation metrics) |
| `bullmq.driver.ts` | 2x `metricsService.incrementCounter` (job
completed/failed metrics) |
| `call-webhook.job.ts` | 2x `auditService.insertWorkspaceEvent` + 1x
`metricsService.incrementCounter` |
| `custom-domain-manager.service.ts` | `analytics.insertWorkspaceEvent`
(domain activation event) |
| `logic-function-executor.service.ts` |
`auditService.insertWorkspaceEvent` (function execution) |
| `workflow-runner.workspace-service.ts` |
`metricsService.incrementCounter` (throttle metric) |
| `cleaner.workspace-service.ts` | `metricsService.incrementCounter`
(deleted workspace metric) |
| `stream-agent-chat.job.ts` | Detached IIFE for streaming chunks
(intentional concurrent pipeline) |
| `workspace-auth-context.middleware.ts` |
`withWorkspaceAuthContext(...)` (AsyncLocalStorage, returns void anyway)
|
## Top-level script entry points (`void bootstrap()`)
These are module-level calls where the promise has no consumer. `void`
makes the lint rule happy and documents the intent.
| File | What changed |
|---|---|
| `main.ts` | `void bootstrap()` |
| `command.ts` | `void bootstrap()` |
| `queue-worker.ts` | `void bootstrap()` |
| `truncate-db.ts` | `void dropSchemasSequentially()` |
| `codegen/index.ts` | `void generateTests(forceArg)` |
## Now properly awaited -- Real bug fixes
These were floating promises that could silently fail, lose data, or
cause race conditions.
| File | What was fixed |
|---|---|
| `billing-sync-plans-data.command.ts` | `meters.map(async ...)` wrapped
in `Promise.all` -- was returning before upserts finished |
| `cache-storage.service.ts` | `setAdd` and `setPop` had `.then()`
chains that weren't returned/awaited |
| `create-audit-log-from-internal-event.ts` | 4x
`auditService.createObjectEvent` now awaited inside a job |
| `cleaner.workspace-service.ts` | 2x `emailService.send(...)` now
awaited -- emails could silently fail |
| `agent-async-executor.service.ts` | `calculateAndBillUsage` +
`billNativeWebSearchUsage` in `finally` block now awaited |
| `repair-tool-call.util.ts` | `calculateAndBillUsage` now awaited |
| `agent-title-generation.service.ts` | `calculateAndBillUsage` now
awaited |
| `chat-execution.service.ts` | `billNativeWebSearchUsage` now awaited |
| `ai-generate-text.controller.ts` | `calculateAndBillUsage` in
`finally` block now awaited |
| `agent-turn.resolver.ts` | `messageQueueService.add(...)` now awaited
|
| `command.ts` | `app.close()` now awaited (was exiting before graceful
shutdown) |
| `i18n.service.ts` | `loadTranslations()` in `onModuleInit` now awaited
|
| `workspace-query-hook.explorer.ts` | `explore()` in `onModuleInit` now
awaited |
| `message-queue.explorer.ts` | `handleProcessorGroupCollection` in
`onModuleInit` now awaited |
| `ai-billing.service.spec.ts` | Test now properly `await`s the async
call |
| `messaging-messages-import.service.spec.ts` | `expect(...)` now
properly `await`ed for async assertion |
| `archive.finalize()` (3 files) | Voided -- promise resolution already
handled by `pipeline()` / `on('end')` |
## Impersonation & security audit trail -- Upgraded from `void` to
`await`
These were previously fire-and-forget but are
security/compliance-critical events that must be reliably persisted.
| File | What was fixed |
|---|---|
| `impersonation.service.ts` | 4x `auditService.insertWorkspaceEvent`
now awaited (impersonation attempt, token generation
attempt/success/failure) |
| `auth.resolver.ts` | 5x `auditService.insertWorkspaceEvent` now
awaited (impersonation token exchange attempt/success/failure at server
and workspace levels) |
| `auth.service.ts` | 2x `analytics.insertWorkspaceEvent` now awaited
(impersonation attempted/issued) |
## Billing audit -- Upgraded from `void` to `await`
Payment events should be reliably persisted for financial/compliance
reporting.
| File | What was fixed |
|---|---|
| `billing-webhook-invoice.service.ts` |
`auditService.insertWorkspaceEvent(PAYMENT_RECEIVED_EVENT)` now awaited
inside Stripe webhook handler |
## Fire-and-forget with proper error handling -- Upgraded from bare
`void`
These remain non-blocking but now catch and log errors instead of
risking unhandled rejections.
| File | What was fixed |
|---|---|
| `logic-function-executor.service.ts` |
`applicationLogsService.writeLogs` now uses `.catch()` instead of bare
`void` -- user-facing logs should surface errors |
## Systemic infrastructure fixes
| File | What was fixed |
|---|---|
| `metrics.service.ts` | `incrementCounter`: Redis cache write
(`metricsCacheService.updateCounter`) now uses `.catch()` internally
instead of raw `await` -- prevents unhandled rejections across all `void
metricsService.incrementCounter(...)` call sites when Redis is unhealthy
|
| `audit.service.ts` | `preventIfDisabled`: made properly `async` with
`await` and consistent `Promise<{ success: boolean }>` return type.
Removed broken `catch` that returned an `AuditException` as a value
(wrong constructor args, unreachable dead code). Removed unused
`AuditException` import |
## Fixed in this session (beyond original PR)
| File | What changed |
|---|---|
| `telemetry.listener.ts` | Removed misleading `Promise.all` + `void`
combo; replaced with simple `for...of` + `void` |
| `message-queue.explorer.ts` | Changed from `void` to `await` so
startup crashes on registration failure |
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842e679cc6 |
fix(billing): gate AI credit-cap at entry points instead of workflow executor (#20096)
## Background The 2026-04-26 incident saw 716M Sonnet 4.6 tokens consumed in a single trial workspace. Two causes: failed agent executions weren't billed (addressed by #20065) and the credit-cap gate had been removed from `WorkflowExecutorWorkspaceService.executeStep` in #19904, leaving no enforcement point at all. ## Why not just revert #19904 #19904 was right that gating at the workflow executor is too coarse. When one user exhausted a workspace's credits via chat, *all* workflows hard-failed mid-run — including cheap DB/CRUD/branch automations costing essentially nothing. Reverting would re-introduce that cliff. ## New design: gate at the AI entry points The chat resolver already gates this way (`agent-chat.resolver.ts:137-148`). This PR replicates the same pattern at every other point where the workspace can incur real AI cost: - `executeAgent` in `agent-async-executor.service.ts` - the REST handler in `ai-generate-text.controller.ts` - `generateThreadTitle` in `agent-title-generation.service.ts` In each, after auth/validation: skip if `IS_BILLING_ENABLED` is false; otherwise call `BillingService.canBillMeteredProduct(workspaceId, BillingProductKey.WORKFLOW_NODE_EXECUTION)`; on `false`, throw `BillingException(BILLING_CREDITS_EXHAUSTED)`. No new method, no new exception code, no new product key. This matches industry convention (Lovable/Replit also gate at the expensive-operation boundary, not at every cheap step). ## Deliberately not gated - `WorkflowExecutorWorkspaceService.executeStep` — the design choice is now intentional, so the #19904 TODO is replaced by a one-line absolute-behavior comment explaining why the gate isn't here. Cheap workflow steps (DB CRUD, branching, action steps) are not gated, so a chat-driven cap exhaustion does not block non-AI automations. - `repair-tool-call.util` — repair is a sub-call inside an already-gated AI flow. If the parent is gated, repair will naturally not run. Adding a gate here adds complexity without value. ## Net effect A workspace that exhausts credits via chat or AI agent stops making AI calls. Its non-AI workflows continue running normally. A workflow with both AI and non-AI steps fails at the AI step with `BILLING_CREDITS_EXHAUSTED`, but downstream non-AI steps that don't depend on the AI output still run. ## Conflicts This PR overlaps with three other in-flight PRs in the same files. None of them touch the gate logic; rebasing on top of any of them is trivial: - #20065 (agent-async-executor): adds `workspaceId` to `executeAgent` args and bills in `finally`. The gate at the top of `executeAgent` from this PR sits naturally above that. - #20066 (REST controller): adds usage billing to the controller. - #20067 (title gen): adds usage billing to title generation and tool-call repair. Recommend landing #20065/#20066/#20067 first; this PR rebases trivially on top. ## Tests Out of scope per the PR series convention. The existing chat-resolver gate isn't unit-tested either; this PR follows the same precedent. Follow-up: add integration coverage that exercises a workspace at `hasReachedCurrentPeriodCap=true` against each of the three new gates plus the pre-existing chat-resolver gate. ## Future follow-ups - Per-user soft cap inside a workspace (the Lovable Business-tier pattern), so one user can't exhaust the workspace's cap. - Pre-flight cost estimate so the user sees an "approaching cap" warning before the hard stop. - Rename `BillingProductKey.WORKFLOW_NODE_EXECUTION` — the name predates this design choice and is misleading now that it gates AI entry points rather than workflow nodes. ## Test plan - [ ] Trigger a workspace into `hasReachedCurrentPeriodCap=true`. - [ ] Send a chat message — expect failure with `BILLING_CREDITS_EXHAUSTED`. - [ ] Run a workflow whose only AI step is an `ai-agent` action — expect that step to fail with `BILLING_CREDITS_EXHAUSTED`, downstream non-AI steps still run. - [ ] POST to `/rest/ai/generate-text` — expect `BILLING_CREDITS_EXHAUSTED`. - [ ] Create a new chat thread (which kicks off `generateThreadTitle`) — expect `BILLING_CREDITS_EXHAUSTED`. - [ ] Run a workflow with no AI step (only DB CRUD/branching/actions) — expect it to run unaffected. --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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df3e217d64 |
fix(ai-billing): bill executeAgent in a finally block so failed runs don't leak (#20065)
## Summary
`AgentAsyncExecutorService.executeAgent` consumes Anthropic tokens at
two points (the main `generateText` and the optional structured-output
sub-call). Billing was previously the **caller's** responsibility,
executed only after `executeAgent` returned. If `executeAgent` threw —
e.g. when `structuredResult.output == null` for a schema-mismatched
response, or anything caught by the catch-and-rethrow — we paid
Anthropic but never recorded a `usageEvent`. Likely the dominant source
of the 716M-token-vs-3.27-credits discrepancy seen on the affected
workspace in the 2026-04-26 incident.
## What changed
- Inject `AiBillingService` into `AgentAsyncExecutorService`. Add
`workspaceId` (required), `userWorkspaceId`, and `operationType`
(default `AI_WORKFLOW_TOKEN`) to `executeAgent`'s args.
- Capture `accumulatedUsage`, `cacheCreationTokens`, and
`nativeWebSearchCallCount` into mutable locals as each `generateText`
resolves. A throw between the main and structured-output calls still
bills the first call's tokens; the schema-validation throw still bills
the merged usage.
- Wrap the body in `try { ... } finally { ... }`. The finally calls
`calculateAndBillUsage` and `billNativeWebSearchUsage`, each guarded by
its own `try/catch + logger.error` so a billing exception can't mask the
original execution error or block the second emit.
- `ai-agent.workflow-action.ts`: pass the new args; drop the
now-redundant billing calls and `AiBillingService` injection.
`AiBillingModule` removed from this action's module imports.
- `run-evaluation-input.job.ts`: pass `workspaceId` (already in `data`)
and `userWorkspaceId: null`. **As a side effect, the eval pipeline now
bills correctly** — closing an additional billing leak from the audit
(`RunEvaluationInputJob` previously called `executeAgent` and discarded
`executionResult.usage`).
## Behavior change worth calling out
Previously, failed agent executions were silently free. They will now be
billed for the tokens Anthropic charged us. This is intentional and
correct.
## Test plan
- [ ] Trigger a workflow agent action that succeeds — `usageEvent` count
should match what was previously emitted.
- [ ] Trigger a workflow agent with a JSON response schema and ambiguous
input that produces a non-schema-conforming output
(`structuredResult.output == null`) — verify a `usageEvent` row is now
written for the consumed tokens (was 0 rows previously).
- [ ] Trigger a `runEvaluationInput` GraphQL mutation — verify a
`usageEvent` row is written (was 0 rows previously).
## Notes for review
- Conflicts trivially with the Sentry-context PR on
`run-evaluation-input.job.ts`. Recommend merging Sentry-context first;
this PR's 2-line argument addition rebases inside that PR's
`aiCallContextService.run(...)` callback wrapper.
- A small follow-up after this lands: thread `billingContext` through
the `experimental_repairToolCall` callback in
`agent-async-executor.service.ts:198` (currently marked with a TODO from
the title-gen+repair-tool PR).
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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bb5f294c5a |
[AI] Collapse NativeToolBinder to a single bind() entry (#20051)
The binder doesnt need an agent or full tool context -- just a model and options. Single `bind(model, options)` entry! Builds on #20022. |
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6c1c0737b0 |
Clarify registry tools vs native model tool binding (#20022)
## Intent This is a small foundation cleanup for the tool architecture. The main decision is: registry tools and native SDK/model tools are different things. - Registry tools have descriptors, schemas, catalog entries, and execute through `ToolExecutorService` - Native model tools are opaque AI SDK objects, bound directly into the model `ToolSet` - Surfaces still own their policy: chat, MCP, and workflow agents decide what they expose ## What changed - Removed `NATIVE_MODEL` from `ToolCategory` - Kept `ToolRegistryService` focused on registry-backed tools only - Moved native model tool binding through `NativeToolBinderService` - Reused native binding from chat instead of duplicating provider-specific web-search logic - Kept MCP local execution exclusions in a dedicated constant - Moved surface-specific constants into dedicated constant files ## What comes next - Move hardcoded chat app preloads, like Exa web search, into app/manifest metadata - Decide a clearer policy for local runtime tools like code interpreter and HTTP request - Gradually document the three tool shapes: registry tools, native model tools, and local runtime tools --------- Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com> Co-authored-by: Félix Malfait <FelixMalfait@users.noreply.github.com> Co-authored-by: Félix Malfait <felix.malfait@gmail.com> |
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251f5deab6 |
[breaking, deploy server first] fix(ai-chat): persist providerExecuted flag on tool parts (#20030)
## Summary Fixes Sentry errors of the form: > \`messages.3: \`tool_use\` ids were found without \`tool_result\` blocks immediately after: srvtoolu_…. Each \`tool_use\` block must have a corresponding \`tool_result\` block in the next message.\` ### Root cause When the model invokes a **provider-hosted tool** (e.g. Anthropic's native \`web_search\` — note the \`srvtoolu_\` ID prefix), the AI SDK marks the resulting \`UIMessagePart\` with \`providerExecuted: true\`. \`convertToModelMessages\` uses that flag to emit the tool_use/tool_result pair *inside the same assistant message* — the format Anthropic requires for server-side tools. Our \`AgentMessagePart\` persistence was dropping \`providerExecuted\` on the way to the DB (and re-hydration didn't know to set it). On the next turn, \`convertToModelMessages\` treated the rehydrated part as a client-side tool call, splitting it into \`assistant(tool_use)\` + \`user(tool_result)\` — which Anthropic then rejects with the error above. ### Fix - Add nullable \`providerExecuted BOOLEAN\` column on \`core.agentMessagePart\` via a fast instance command. - Surface the field on \`AgentMessagePartDTO\` (GraphQL). - Preserve it through \`mapUIMessagePartsToDBParts\` (server) and both \`mapDBPartToUIMessagePart\` mappers (server + frontend). - Include it in \`GET_CHAT_MESSAGES\` and \`GET_AGENT_TURNS\` selections. - Regenerate \`generated-metadata/graphql.ts\`. ### Backwards compatibility Existing rows have \`NULL providerExecuted\` and round-trip as the omitted flag — which is exactly the pre-fix behaviour for tool parts that were never provider-executed. Only *new* assistant messages using \`web_search\` (or other provider-hosted tools) will write \`true\`, and those are the only ones that were breaking. ## Test plan - [x] \`npx tsgo\` typecheck — server + front clean - [x] \`oxlint\` + \`prettier --check\` on all touched files — clean - [x] \`npx nx run twenty-server:database:migrate:prod\` runs the new instance command locally; \`providerExecuted\` column present on \`core.agentMessagePart\` - [x] Regenerated \`generated-metadata/graphql.ts\` — \`providerExecuted\` wired into both queries and \`AgentMessagePart\` type - [ ] Manual: start a chat with Anthropic web_search enabled, invoke the tool in turn 1, reply in turn 2 — should not throw the srvtoolu error 🤖 Generated with [Claude Code](https://claude.com/claude-code) --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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6117a1d6c0 |
refactor: standardize AI acronym to Ai (PascalCase) across internal identifiers (#19837)
## Summary
The "AI" acronym was rendered inconsistently across the codebase. The
backend AI module had settled on PascalCase `Ai` (`AiAgentModule`,
`AiBillingService`, `AiChatModule`, `AiModelRegistryService`, etc.),
while frontend components, several DTOs, a few types, and shared
identifiers still used all-caps `AI` (`AIChatTab`,
`AISystemPromptPreviewDTO`, `SettingsPath.AIPrompts`, ...). CLAUDE.md
specifies PascalCase for classes; this PR normalizes everything internal
to `Ai`.
**This is a pure internal rename.** The GraphQL schema is untouched —
`@ObjectType` decorator string arguments, resolver method names (which
become Query/Mutation field names), gql template contents, and the
`generated-metadata/graphql.ts` file are preserved verbatim. The only
visible change is TypeScript identifiers and file names.
## Also folded in (adjacent cleanups)
- **`AgentModelConfigService` → `AiModelConfigService`**. Lives in
`ai-models/` and is used by multiple AI code paths, not just the Agent
entity. The "Agent" prefix was misleading.
- **`generate-text-input.dto.ts` → `generate-text.input.ts`**. The
`ai-agent/dtos/` folder already uses `<entity>.input.ts` convention for
Input classes (`create-agent.input.ts` etc.); the old path mixed
`.dto.ts` file extension with a class that has no DTO suffix. File
rename only; class stays `GenerateTextInput`.
- **Removed stale TODO** in `ai-model-config.type.ts` that asked for the
`AiModelConfig` rename that this PR performs.
## Rename methodology
Bulk rename via perl with anchored regex
`(?<!['"])(?<![A-Z.])AI([A-Z])(?=[a-z])/Ai$1/g`:
- **Lookbehind for non-uppercase** skips adjacent acronyms (`MOSAIC`,
`OIDCSSO`) and leaves `AIRBNB_ID` alone.
- **Lookbehind for non-quote** protects most string literals.
- **Lookahead for lowercase** restricts matches to PascalCase
identifiers (`AIChatTab`), leaving SCREAMING_SNAKE constants untouched.
Strict file-scope exclusions: `generated-metadata/**`, `generated/**`,
`locales/**`, `migrations/**`, `illustrations/**`, `halftone/**`, and
the two gql template files (`queries/getAISystemPromptPreview.ts`,
`mutations/uploadAIChatFile.ts`).
Post-rename reverts for identifiers where the regex was too eager:
- Backend resolver method names kept: `getAISystemPromptPreview`,
`uploadAIChatFile` (they are GraphQL field names).
- `@ObjectType('AdminAIModels')` / `('AISystemPromptPreview')` /
`('AISystemPromptSection')` kept as-is.
- Backend classes `ClientAIModelConfig` / `AdminAIModelConfig` kept
as-is (they use `@ObjectType()` with no argument, so the class name IS
the schema name).
- External-library symbols restored: `OpenAIProvider`,
`createOpenAICompatible`, `vercelAIIntegration`.
File renames use a two-step rename to work on macOS case-insensitive
filesystems: `git mv X.tsx X.tsx.tmp && git mv X.tsx.tmp renamed.tsx`.
## Diff audit
- 0 changes to migrations
- 0 changes to locale `.po` / `.ts` files
- 0 changes to `generated-metadata/graphql.ts`
- 0 changes to website illustration files (base64 blobs preserved)
- 0 renames inside user-facing translation strings (`t\`…\``,
`msg\`…\``, `<Trans>…</Trans>`)
## Test plan
- [x] `npx nx typecheck twenty-server` — PASS
- [x] `npx nx typecheck twenty-front` — PASS
- [x] `npx jest ai-model admin agent-role` — 79/79 PASS
- [x] `npx oxlint --type-aware` on 118 changed files — 0 errors
- [x] `npx prettier --check` on 118 changed files — clean
- [ ] CI
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c28c20143b |
refactor(server): rename Agent exception to Ai; add THREAD_NOT_FOUND / MESSAGE_NOT_FOUND codes (fixes 500s) (#19831)
## Summary - The exception class under `ai-agent/` was serving every AI surface (agent, chat, role, models, generate-text), so `Agent` was a misnomer. Promoted to the `ai/` namespace; renamed `AgentException` → `AiException`, `AgentExceptionCode` → `AiExceptionCode`, and related interceptor / filter / handler / file names accordingly. - Split the single `AGENT_NOT_FOUND` code into entity-specific codes. Chat-thread lookups no longer reuse the agent identifier. - **Fixes Sentry 500s on `GetChatMessages` / `chatThread`.** Every "Thread not found" and "Queued message not found" throw site in ai-chat was previously wired to `AGENT_EXECUTION_FAILED`, which maps to `InternalServerError` (HTTP 500). They now use `THREAD_NOT_FOUND` / `MESSAGE_NOT_FOUND`, both of which map to `NotFoundError` (HTTP 404) in the GraphQL and REST handlers. The underlying cause of *why* clients are asking for threads that no longer resolve for them — per-user chat-thread create events being broadcast workspace-wide — is addressed separately in a follow-up PR. ### Code map - Added: `ai/ai.exception.ts`, `ai/utils/ai-graphql-api-exception-handler.util.ts` (+ spec with new THREAD/MESSAGE cases), `ai/interceptors/ai-graphql-api-exception.interceptor.ts`, `ai/filters/ai-api-exception.filter.ts` - Deleted: `ai/ai-agent/agent.exception.ts`, `ai/ai-agent/utils/agent-graphql-api-exception-handler.util.ts` (+ spec), `ai/ai-agent/interceptors/agent-graphql-api-exception.interceptor.ts`, `ai/ai-agent/filters/agent-api-exception.filter.ts` - Updated: 21 call sites across ai-agent, ai-agent-execution, ai-agent-role, ai-chat, ai-generate-text, ai-models, role, and workspace-migration validators. ## Test plan - [x] `npx nx typecheck twenty-server` - [x] `npx jest ai-graphql-api-exception-handler` (3/3 including new THREAD_NOT_FOUND and MESSAGE_NOT_FOUND cases) - [x] `npx jest agent-role.service` (9/9) - [x] `npx oxlint --type-aware` on all changed files (0 warnings/errors) - [x] `npx prettier --check` on all changed files - [ ] CI |
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2bb939b4b5 |
Add file attachment support to agent chat messaging (#19517)
## Summary This PR adds support for attaching files to agent chat messages. Users can now upload files when sending messages to the AI agent, and these files are properly processed, stored, and made available to the agent with signed URLs. ## Key Changes - **File attachment input**: Added `fileIds` parameter to the `sendChatMessage` GraphQL mutation to accept file IDs from the client - **File processing**: Implemented `buildFilePartsFromIds()` method to convert file IDs into file UI parts with signed URLs - **Message composition**: Updated user messages to include both text and file parts when files are attached - **File URL signing**: Integrated `FileUrlService` to generate signed URLs for files in the AgentChat folder, ensuring secure access - **Message persistence**: Files are now included in the message parts stored in the database and retrieved when loading conversation history - **File metadata mapping**: Enhanced `mapDBPartToUIMessagePart()` to properly extract MIME types from file entities and include file IDs ## Implementation Details - Files are fetched from the database using the provided file IDs and workspace context - Each file is converted to an `ExtendedFileUIPart` with proper metadata (filename, MIME type, signed URL, and file ID) - When loading messages from the database, file parts are enhanced with signed URLs to ensure they remain accessible - The `loadMessagesFromDB()` method now requires the workspace ID to properly sign file URLs - File attachments are seamlessly integrated into the existing message part system alongside text content https://claude.ai/code/session_01TAdN1gBzeiYELX4XDrrYY1 --------- Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com> |
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8a10071253 |
add workspaceId to indirect entities (#19522)
Required for `workspace:export` command --------- Co-authored-by: Charles Bochet <charles@twenty.com> |
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ea572975d8 |
feat: generic web search driver abstraction with Exa support and billing (#19341)
## Summary - Introduces a pluggable `WebSearchDriver` abstraction (interface, factory, service, module) so web search is no longer tied to native provider tools (Anthropic/OpenAI) - **Exa** is the first driver implementation with support for category-filtered search (company, people, news, research paper, etc.) — particularly useful for CRM workflows - Per-query billing for both Exa ($0.007/query) and native provider surcharges ($0.01/query for Anthropic/OpenAI) via the existing `USAGE_RECORDED` pipeline - New config variables: `WEB_SEARCH_DRIVER` (EXA/DISABLED), `EXA_API_KEY`, `WEB_SEARCH_PREFER_NATIVE` (default false — prefers Exa over native when both available) - `WEB_SEARCH` operation type added for usage tracking and Stripe metering ### Architecture ``` WebSearchDriver (interface) ├── ExaDriver — Exa neural search with category support └── DisabledDriver — throws when search is disabled WebSearchDriverFactory (extends DriverFactoryBase) └── creates driver based on WEB_SEARCH_DRIVER config WebSearchService (facade) ├── search(query, options?, billingContext?) ├── isEnabled() └── emits USAGE_RECORDED events per query WebSearchTool (Tool implementation) └── registered in ActionToolProvider, available via tool catalog ``` ### Native search billing gap fixed Anthropic and OpenAI both charge $0.01/search on top of token costs. The token costs were already billed, but the per-call surcharge was not. Added `countNativeWebSearchCallsFromSteps` utility + `billNativeWebSearchUsage` to `AiBillingService`, wired into both chat and workflow agent paths. ## Test plan - [ ] Set `WEB_SEARCH_DRIVER=EXA` + `EXA_API_KEY=...` and verify AI chat can search the web - [ ] Verify category parameter works (ask about a specific company/person) - [ ] Set `WEB_SEARCH_DRIVER=DISABLED` and verify search tool is not exposed - [ ] Set `WEB_SEARCH_PREFER_NATIVE=true` with Anthropic model and verify native search is used - [ ] Verify usage events are emitted in ClickHouse for both Exa and native search paths - [ ] Verify existing billing tests pass (`npx jest ai-billing.service.spec.ts`) Made with [Cursor](https://cursor.com) --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com> |
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563e27831b |
Clean up tool output architecture: remove wrappers, enforce ToolOutput everywhere (#19321)
## Summary
- **Remove `ExecuteToolResult` wrapper** — `execute_tool` is now a
transparent dispatcher that returns the raw `ToolOutput` from underlying
tools. No more `{ toolName, result }` envelope.
- **Type the entire execution chain as `Promise<ToolOutput>`** — from
`ToolExecutorService.dispatch()` through `resolveAndExecute()` to
`execute_tool.execute()`. Zero `Promise<unknown>` remaining in the tool
layer.
- **Use `Extract<ToolExecutionRef, ...>`** for dispatch methods,
enabling exhaustive switch checking and removing `as never` casts.
- **Relax `ToolOutput.result` to accept `null`** — removes `??
undefined` hacks at the boundary with logic function results.
- **Enforce 1-export-per-file** across tool type/interface files (split
`tool-descriptor.type.ts`, `tool-provider.interface.ts`, `tool.type.ts`,
`tool-output.type.ts`, `tool-executor.service.ts`).
- **Simplify error handling** — `wrapWithErrorHandler` and all
meta-errors (tool not found, tool excluded) now return consistent
`ToolOutput` shape with `error` as a plain string.
- **Frontend reads output directly** — removed `unwrapToolOutput`
utility; `ToolStepRenderer` and `ThinkingStepsDisplay` extract
`message`/`error` from the raw output with simple type guards.
- **Add permission error detection** for email tools via
`isInsufficientPermissionsError`, guiding the AI model to suggest
account reconnection instead of hallucinating about visibility settings.
## Test plan
- [ ] AI chat tool calls return visible output (not "null") in the UI
- [ ] Tool errors display correctly in the JSON tree
- [ ] Email draft/send tools return actionable permission errors
- [ ] Code interpreter output renders correctly
- [ ] Thinking steps display tool outputs properly
Made with [Cursor](https://cursor.com)
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
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7f2b853ae1 | feat: add message compaction for AI chats (#19205) | ||
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3c067f072c | [AI] Improve tools tab (#19221) | ||
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fd7387928c |
feat: queue messages + replace AI SDK with GraphQL SSE subscription (#19203)
## Summary - **Queue messages while streaming**: Messages sent during active AI streaming are queued server-side and auto-flushed when the current stream completes. Frontend renders queued messages optimistically in a dedicated queue UI. - **Drop `@ai-sdk/react` + `resumable-stream`**: Replace the dual HTTP SSE + AI SDK client architecture with a single GraphQL SSE subscription per thread. All events (token chunks, message persistence, queue updates, errors) flow through Redis PubSub → GraphQL subscription. - **Server-driven architecture**: The server decides whether to queue or stream (via `POST /:threadId/message`). The frontend mirrors this decision for optimistic rendering but defers to the server response. - **Reuse AI SDK accumulation logic**: `readUIMessageStream` from the `ai` package handles chunk-to-message accumulation on the frontend, avoiding a custom 780-line accumulator. ## Key files **Backend:** - `agent-chat-event-publisher.service.ts` — publishes events to Redis PubSub - `agent-chat-subscription.resolver.ts` — GraphQL subscription resolver - `stream-agent-chat.job.ts` — publishes chunks via PubSub instead of resumable-stream - `agent-chat.controller.ts` — unified `POST /:threadId/message` endpoint **Frontend:** - `useAgentChatSubscription.ts` — subscribes to `onAgentChatEvent`, bridges to `readUIMessageStream` - `useAgentChat.ts` — send/stop/optimistic rendering (no more AI SDK) - `AgentChatStreamSubscriptionEffect.tsx` — replaces `AgentChatAiSdkStreamEffect.tsx` ## Test plan - [ ] Send message on new thread → optimistic render, streaming response appears - [ ] Send message while streaming → queued instantly (no flash in main thread) - [ ] Queued message auto-flushes after current stream completes - [ ] Remove queued message via queue UI - [ ] Stop streaming mid-response - [ ] Leave chat idle for several minutes → streaming still works after (SSE client recycling) - [ ] Token refresh during session → requests succeed (authenticated fetch) - [ ] Switch threads while streaming → clean subscription handoff Made with [Cursor](https://cursor.com) --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> |
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9d57bc39e5 |
Migrate from ESLint to OxLint (#18443)
## Summary Fully replaces ESLint with OxLint across the entire monorepo: - **Replaced all ESLint configs** (`eslint.config.mjs`) with OxLint configs (`.oxlintrc.json`) for every package: `twenty-front`, `twenty-server`, `twenty-emails`, `twenty-ui`, `twenty-shared`, `twenty-sdk`, `twenty-zapier`, `twenty-docs`, `twenty-website`, `twenty-apps/*`, `create-twenty-app` - **Migrated custom lint rules** from ESLint plugin format to OxLint JS plugin system (`@oxlint/plugins`), including `styled-components-prefixed-with-styled`, `no-hardcoded-colors`, `sort-css-properties-alphabetically`, `graphql-resolvers-should-be-guarded`, `rest-api-methods-should-be-guarded`, `max-consts-per-file`, and Jotai-related rules - **Migrated custom rule tests** from ESLint `RuleTester` + Jest to `oxlint/plugins-dev` `RuleTester` + Vitest - **Removed all ESLint dependencies** from `package.json` files and regenerated lockfiles - **Updated Nx targets** (`lint`, `lint:diff-with-main`, `fmt`) in `nx.json` and per-project `project.json` to use `oxlint` commands with proper `dependsOn` for plugin builds - **Updated CI workflows** (`.github/workflows/ci-*.yaml`) — no more ESLint executor - **Updated IDE setup**: replaced `dbaeumer.vscode-eslint` with `oxc.oxc-vscode` extension, configured `source.fixAll.oxc` and format-on-save with Prettier - **Replaced all `eslint-disable` comments** with `oxlint-disable` equivalents across the codebase - **Updated docs** (`twenty-docs`) to reference OxLint instead of ESLint - **Renamed** `twenty-eslint-rules` package to `twenty-oxlint-rules` ### Temporarily disabled rules (tracked in `OXLINT_MIGRATION_TODO.md`) | Rule | Package | Violations | Auto-fixable | |------|---------|-----------|-------------| | `twenty/sort-css-properties-alphabetically` | twenty-front | 578 | Yes | | `typescript/consistent-type-imports` | twenty-server | 3814 | Yes | | `twenty/max-consts-per-file` | twenty-server | 94 | No | ### Dropped plugins (no OxLint equivalent) `eslint-plugin-project-structure`, `lingui/*`, `@stylistic/*`, `import/order`, `prefer-arrow/prefer-arrow-functions`, `eslint-plugin-mdx`, `@next/eslint-plugin-next`, `eslint-plugin-storybook`, `eslint-plugin-react-refresh`. Partial coverage for `jsx-a11y` and `unused-imports`. ### Additional fixes (pre-existing issues exposed by merge) - Fixed `EmailThreadPreview.tsx` broken import from main rename (`useOpenEmailThreadInSidePanel`) - Restored truthiness guard in `getActivityTargetObjectRecords.ts` - Fixed `AgentTurnResolver` return types to match entity (virtual `fileMediaType`/`fileUrl` are resolved via `@ResolveField()`) ## Test plan - [x] `npx nx lint twenty-front` passes - [x] `npx nx lint twenty-server` passes - [x] `npx nx lint twenty-docs` passes - [x] Custom oxlint rules validated with Vitest: `npx nx test twenty-oxlint-rules` - [x] `npx nx typecheck twenty-front` passes - [x] `npx nx typecheck twenty-server` passes - [x] CI workflows trigger correctly with `dependsOn: ["twenty-oxlint-rules:build"]` - [x] IDE linting works with `oxc.oxc-vscode` extension |
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26f0a416a1 |
File storage cleaning (#18381)
- Remove feature flag - Remove legacy methods in file-upload and file-service - Migrate AI Chat to new file management --------- Co-authored-by: Charles Bochet <charles@twenty.com> |
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e806d36099 |
Navbar with AI chats (#18161)
## Summary Add Home/Chat tabs and a dedicated threads list in the navigation drawer. ## Changes - **Navbar tabs:** Tabs in the drawer to switch between Home and Chat (with “New chat” button). Shown on desktop when expanded and on mobile below the workspace selector. - **Navbar threads list:** New `NavigationDrawerAIChatThreadsList` for the Chat tab with date groups (Today / Yesterday / Older), thread rows as `NavigationDrawerItem` (IconComment, title, timestamp). Shared `useAIChatThreadClick` hook used by navbar and command menu; navbar passes `resetNavigationStack: true`. - **NavigationDrawerItem:** New `alwaysShowRightOptions` prop so the timestamp is always visible (no hover-only). --------- Co-authored-by: Etienne <45695613+etiennejouan@users.noreply.github.com> Co-authored-by: Félix Malfait <felix@twenty.com> Co-authored-by: Charles Bochet <charles@twenty.com> |
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9107f5bbc7 |
feat: upgrade ai package to version six and the corresponding @ai-sdk/* packages to compatible versions (#18172)
Used the migration guide to carry out this upgrade: https://ai-sdk.dev/docs/migration-guides/migration-guide-6-0 I have not been able to test locally due to credits. <img width="220" height="450" alt="image" src="https://github.com/user-attachments/assets/050b34b9-3239-4010-8c47-b43d44571994" /> --------- Co-authored-by: Félix Malfait <felix.malfait@gmail.com> |
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9a3852bf04 |
feat: add two-layer AI model availability filtering (#18170)
## Summary - **Admin-level filtering**: New AI tab in admin panel with server-wide model availability controls (whitelist/blacklist via `AI_AUTO_ENABLE_NEW_MODELS`, `AI_DISABLED_MODEL_IDS`, `AI_ENABLED_MODEL_IDS` config variables). Dedicated `setAdminAiModelEnabled` mutation replaces frontend config-variable manipulation. Filter dropdown to show/hide unconfigured and deprecated models. - **Workspace-level filtering**: Per-workspace controls with "Use best models only" mode (curated list backed by `isRecommended` flag), or custom whitelist/blacklist. Separate Smart/Fast model selectors with "Best (...)" virtual options. - **Security enforcement**: Both layers enforced at every backend execution point — workspace update, agent create/update, chat execution. Model ID validated against known models before config mutation. All admin endpoints protected by `AdminPanelGuard`. ## Changes ### Backend (`twenty-server`) - New config variables for admin-level model filtering - `AiModelRegistryService`: `getAllModelsWithStatus()`, `setModelAdminEnabled()` with model ID validation, `isModelAdminAllowed()` - `AdminPanelResolver`: `getAdminAiModels` query, `setAdminAiModelEnabled` mutation - `WorkspaceEntity`: new fields (`autoEnableNewAiModels`, `disabledAiModelIds`, `enabledAiModelIds`, `useRecommendedModels`) - `WorkspaceService`: model validation on `smartModel`/`fastModel` updates - `AgentResolver`: model availability checks on create/update - `isModelAllowedByWorkspace` centralized utility - `isRecommended` flag on model definitions - Two TypeORM migrations ### Frontend (`twenty-front`) - New `SettingsAdminAI` component with search, filter dropdown (unconfigured/deprecated), and model toggle cards - AI tab added to admin panel navigation - `useWorkspaceAiModelAvailability` hook for workspace-level filtering - `SettingsAIModelsTab` redesigned: merged sections, "Use best models only" toggle, conditional available models list - `getModelIcon`/`getModelProviderLabel` shared utilities with GraphQL enum casing normalization - Updated generated GraphQL types and mock data ## Test plan - [ ] Toggle models on/off in admin panel AI tab and verify they appear/disappear in workspace settings - [ ] Enable "Use best models only" in workspace settings and verify only recommended models are selectable - [ ] Disable recommended mode and verify whitelist/blacklist toggles work correctly - [ ] Verify deprecated models hidden by default, shown greyed out when filter enabled - [ ] Verify unconfigured models hidden by default, shown disabled when filter enabled - [ ] Try setting a disabled model as Smart/Fast model — should be rejected - [ ] Try creating an agent with a disabled model — should be rejected - [ ] Verify admin panel AI tab requires admin access Made with [Cursor](https://cursor.com) --------- Co-authored-by: Cursor <cursoragent@cursor.com> |
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41f09c5a4c |
Add AI model pricing, Bedrock provider, and InferenceProvider/ModelFamily split (#18155)
## Summary - **Model pricing overhaul**: All model constants updated with accurate pricing in dollars per 1M tokens, including cached input rates, cache creation rates, and tiered >200k context pricing - **New providers**: Added Google (Gemini 3.x), Mistral, and AWS Bedrock as inference providers. Bedrock serves Claude Opus 4.6 and Sonnet 4.6 via AWS, with proper credential handling following the existing S3/SES pattern - **InferenceProvider/ModelFamily split**: Refactored `ModelProvider` into two orthogonal enums — `InferenceProvider` (who serves the model: auth, SDK, metadata format) and `ModelFamily` (who created it: token counting semantics). This eliminates growing `||` chains for token normalization checks like `excludesCachedTokens` - **Billing improvements**: Reasoning tokens charged at output rate, cache token discounts applied accurately, real errors thrown to Sentry on billing failures ## Test plan - [x] All existing unit tests updated and passing (23 tests across 3 test files) - [x] Lint passes for both twenty-server and twenty-front - [ ] CI checks pass Made with [Cursor](https://cursor.com) --------- Co-authored-by: Cursor <cursoragent@cursor.com> |
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09e1684300 |
feat: show auto-generated conversation title for AI chat. (#17922)
## Summary Replaces the static "Ask AI" header in the command menu with the conversation’s auto-generated title once it’s set after the first message. ## Changes - **Backend:** Title is generated after the first user message (existing behavior). - **Frontend:** After the first stream completes, we fetch the thread title and sync it to: - `currentAIChatThreadTitleState` (persists across command menu close/reopen) - Command menu page info and navigation stack (so the title survives back navigation) - **Entry points:** Opening Ask AI from the left nav or command center uses the same title resolution (explicit `pageTitle` → current thread title → "Ask AI" fallback). - **Race fix:** Title sync only runs when the thread that finished streaming is still the active thread, so switching threads mid-stream doesn’t overwrite the current thread’s title. --------- Co-authored-by: Félix Malfait <felix@twenty.com> Co-authored-by: Cursor <cursoragent@cursor.com> |
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3216b634a3 |
feat: improve AI chat - system prompt, tool output, context window display (#17769)
⚠️ **AI-generated PR — not ready for review** ⚠️ cc @FelixMalfait --- ## Changes ### System prompt improvements - Explicit skill-before-tools workflow to prevent the model from calling tools without loading the matching skill first - Data efficiency guidance (default small limits, use filters) - Pluralized `load_skill` → `load_skills` for consistency with `load_tools` ### Token usage reduction - Output serialization layer: strips null/undefined/empty values from tool results - Lowered default `find_*` limit from 100 → 10, max from 1000 → 100 ### System object tool generation - System objects (calendar events, messages, etc.) now generate AI tools - Only workflow-related and favorite-related objects are excluded ### Context window display fix - **Bug**: UI compared cumulative tokens (sum of all turns) against single-request context window → showed 100% after a few turns - **Fix**: Track `conversationSize` (last step's `inputTokens`) which represents the actual conversation history size sent to the model - New `conversationSize` column on thread entity with migration ### Workspace AI instructions - Support for custom workspace-level AI instructions --------- Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com> |
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fc908e9d87 |
Refactor WorkspaceAuthContext to use discriminated union types (#17491)
## Context The previous WorkspaceAuthContext was a single interface with many optional fields, making it unclear which fields are available in different authentication scenarios. This made the code harder to reason about and required runtime checks scattered throughout the codebase. ## Changes - Introduced a discriminated union type for WorkspaceAuthContext with four specific variants: -> UserWorkspaceAuthContext - for authenticated users -> ApiKeyWorkspaceAuthContext - for API key authentication -> ApplicationWorkspaceAuthContext - for application-based auth -> SystemWorkspaceAuthContext - for system/internal operations - Added type guard functions (isUserAuthContext, isApiKeyAuthContext, etc.) for safe type narrowing - Added builder utilities (buildUserAuthContext, buildApiKeyAuthContext, etc.) to construct each context variant with proper type safety - Refactored WorkspaceAuthContextMiddleware to use the new builders instead of constructing a loosely-typed object - Moved the type definition from twenty-orm/interfaces/ to core-modules/auth/types/ for better organization - Updated all consumers across query runners, tool providers, and modules to use the new type location ## Notes - I had to query User and WorkspaceMember in some parts of tool module that were expecting userWorkspaceId but not the rest of UserWorkspaceAuthContext (that should be required with the new proper type otherwise it would break a lot of logic and mostly permissions with the newly added RLS -> This is what we expect from UserWorkspaceAuthContext and how it's done in the "normal" path in HTTP middleware) - WorkspaceMember is in the cache already but ideally we should move User (And Workspace?) in the cache as well to avoid querying the DB after each request (this is also valid for HTTP middleware when we hydrate the Request object btw) |
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2daebc6d0f |
Add WorkspaceAuthContextMiddleware (#17487)
## Context
Introduces a middleware that automatically sets the workspace auth
context in AsyncLocalStorage for HTTP requests, making it available
throughout the request lifecycle without explicit parameter passing.
The motivation behind this change is to reduce boilerplate and simplify
the developer experience when working with workspace data in HTTP
request handlers.
The Problem (Before)
Every HTTP request handler that needed to access workspace data had to:
- Extract auth-related info from decorators (@AuthWorkspace(),
@AuthUserWorkspaceId(), etc.) in controller/resolver and pass down to
services
- Build or pass the authContext explicitly (sometimes with type
assertion which was flaky)
Then call executeInWorkspaceContext(authContext, async () => { ... })
## Changes
- Add WorkspaceAuthContextMiddleware that extracts auth context from the
request and stores it in AsyncLocalStorage
- Register middleware for GraphQL, metadata, and REST routes (runs after
hydration middlewares)
- Simplify executeInWorkspaceContext signature: fn is now the first
parameter, authContext is optional second
- If authContext is not provided, it's automatically retrieved from the
storage (set by middleware)
- Update all callers (~120 files) to use the new parameter order
- Fixes a bug in search where system auth context was used, bypassing
RLS feature.
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c737028dd6 |
Move tools/eslint-rules to packages/twenty-eslint-rules (#17203)
## Summary Moves the custom ESLint rules from `tools/eslint-rules` to `packages/twenty-eslint-rules` for better organization within the monorepo packages structure. ## Changes - Move `eslint-rules` from `tools/` to `packages/twenty-eslint-rules` - Use `loadWorkspaceRules` from `@nx/eslint-plugin` to load custom rules - Update all ESLint configs to use the `twenty/` rule prefix instead of `@nx/workspace-` - Update `project.json`, `jest.config.mjs` with new paths - Update `package.json` workspaces and `nx.json` cache inputs - Update Dockerfile reference ## Technical Details The custom ESLint rules are now loaded using Nx's `loadWorkspaceRules` utility which: - Handles TypeScript transpilation automatically - Allows loading workspace rules from any directory - Provides a cleaner approach than the previous `@nx/workspace-` convention ## Testing - Verified all 17 custom ESLint rules load correctly from the new location - Verified linting works on dependent packages (twenty-front, twenty-server, etc.) |
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0173e40a20 |
feat: Serverless Functions as AI Tools (#16919)
## Summary This PR enables serverless functions to be exposed as AI tools, allowing them to be used by AI agents. ### Changes - Added new `SERVERLESS_FUNCTION` tool category - Added `toolDescription`, `toolInputSchema`, and `toolOutputSchema` fields to serverless functions - Created database migration for the new schema columns - Added tool index query and resolver for fetching available tools - Added Settings AI page tabs (Skills, Tools, Settings) with new tools table - Added utility to convert tool schema to JSON schema format - Updated frontend to display tools in the settings page ### Implementation Details - Serverless functions can now define tool metadata (description, input/output schemas) - These functions are automatically registered in the tool registry - The tool index endpoint allows querying available tools with their schemas - Settings page now has a dedicated Tools tab showing all available tools |
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009e7e05f2 |
feat(workflow): use authContext in CRUD services for Common API migration (#16857)
## Summary This PR migrates workflow CRUD operations to properly use the Common API layer's authentication context, addressing the issues from the reverted PR #15875. The original PR was reverted because the Common API required passing either a User or an API Key for authentication, which was problematic for workflows. Since then, the "Application" concept was introduced in the Common API layer, allowing for token injection in serverless functions. This PR leverages the "Twenty Standard Application" concept for non-manual workflow triggers, providing a clean authentication path without the issues of user impersonation. ## Changes ### Core Infrastructure - **RecordCrudExecutionContext**: Replace `workspaceId` with full `authContext` - **WorkflowExecutionContext**: Add `authContext` field to carry authentication info - **ToolGeneratorContext/ToolSpecification**: Add optional `authContext` support for tool generation ### Authentication Flow - **WorkflowExecutionContextService**: Build appropriate auth context based on trigger type: - **Manual triggers**: Use user's workspace auth context with their role permissions - **Non-manual triggers**: Use Twenty Standard Application auth context (bypasses permission checks or uses default serverless function role) - **ApplicationService**: Add `findTwentyStandardApplicationOrThrow` method to retrieve the system application - **UserWorkspaceService**: Make relations configurable in `getUserWorkspaceForUserOrThrow` to load only what's needed ### CRUD Services Migration All 5 record CRUD services now receive `authContext` instead of `workspaceId`: - `CreateRecordService` - `UpdateRecordService` - `DeleteRecordService` - `FindRecordsService` - `UpsertRecordService` ### Workflow Actions All record CRUD workflow actions pass `executionContext.authContext` to the services: - `CreateRecordWorkflowAction` - `UpdateRecordWorkflowAction` - `DeleteRecordWorkflowAction` - `FindRecordsWorkflowAction` - `UpsertRecordWorkflowAction` ### AI Agent Integration - AI agent workflow action passes auth context to agent executor - Tool provider and MCP protocol service support auth context propagation ## Benefits - ✅ Proper authentication for workflow CRUD operations via Common API - ✅ Non-manual triggers use system application context (no user impersonation issues) - ✅ Manual triggers preserve user permissions correctly - ✅ Foundation for better permission handling in automated workflows - ✅ Cleaner separation between user-initiated and system-initiated operations ## Related - Reverted PR: #15875 |
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2e104c8e76 |
feat(ai): add code interpreter for AI data analysis (#16559)
## Summary - Add code interpreter tool that enables AI to execute Python code for data analysis, CSV processing, and chart generation - Support for both local (development) and E2B (sandboxed production) execution drivers - Real-time streaming of stdout/stderr and generated files - Frontend components for displaying code execution results with expandable sections ## Code Quality Improvements - Extract `getMimeType` to shared utility to reduce code duplication between drivers - Fix security issue: escape single quotes/backslashes in E2B driver env variable injection - Add `buildExecutionState` helper to reduce duplicated state object construction - Add `DEFAULT_CODE_INTERPRETER_TIMEOUT_MS` constant for consistency - Fix lingui linting warning and TypeScript theme errors in frontend ## Test Plan - [ ] Test code interpreter with local driver in development - [ ] Test code interpreter with E2B driver in production environment - [ ] Verify streaming output displays correctly in chat UI - [ ] Verify generated files (charts, CSVs) are uploaded and downloadable - [ ] Test file upload flow (CSV, Excel) triggers code interpreter <!-- CURSOR_SUMMARY --> --- > [!NOTE] > Updates generated i18n catalogs for Polish and pseudo-English, adding strings for code execution/output (code interpreter) and various UI messages, with minor text adjustments. > > - **Localization**: > - **Generated catalogs**: Refresh `locales/generated/pl-PL.ts` and `locales/generated/pseudo-en.ts`. > - Add strings for code execution/output (e.g., code, copy code/output, running/waiting states, download files, generated files, Python code execution). > - Include new UI texts (errors, prompts, menus) and minor text corrections. > - No changes to `pt-BR`; other files unchanged functionally. > > <sup>Written by [Cursor Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit befc13d02c21e5a6647bc1aa6daa2a89f60b7ef8. This will update automatically on new commits. Configure [here](https://cursor.com/dashboard?tab=bugbot).</sup> <!-- /CURSOR_SUMMARY --> |
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9bd8f94b3a |
Refactor global datasource part 3 (#16447)
## Context Following https://github.com/twentyhq/twenty/pull/16399 Now using the new global orm manager everywhere and returning a GlobalDatasource/WorkspaceDatasource based on a feature flag. This means we now need to wrap all our ORM calls within executeInWorkspaceContext callback (at least for now) so the global datasource can dynamically hydrate its context via the new store (the global datasource does not store anything related to workspaces as it is now a unique singleton). If feature flag is off it still uses local data stored in the workspace datasource. |
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5df8fd90c3 |
feat: simplify AI chat architecture and add record links (#16463)
## Summary This PR significantly simplifies the AI chat architecture by removing complex routing/planning mechanisms and introduces clickable record links in AI responses. ## Changes ### AI Chat Architecture Simplification - **Removed** the entire `ai-chat-router` module (~850 lines) including: - Strategy decider service - Plan generator service - Complex routing logic - **Removed** agent execution planning services (~700 lines): - `agent-execution.service.ts` - `agent-plan-executor.service.ts` - `agent-tool-generator.service.ts` - **Added** centralized `ToolRegistryService` for tool management: - Builds searchable tool index (database, action, workflow tools) - Provides tool lookup by name - Supports agent search for loading expertise - **Added** `ChatExecutionService` as simple replacement: - Includes full tool catalog in system prompt - Pre-loads common tools (find/create/update for company, person, opportunity, task, note) - Uses `load_tools` mechanism for dynamic tool activation - Enables native web search by default ### Record References in AI Responses - Added `recordReferences` field to tool outputs for create, find, and update operations - Implemented `[[record:objectName:recordId:displayName]]` syntax for AI to reference records - Created `RecordLink` component that renders clickable chips with object icons - Integrated record link parsing into the markdown renderer - Users can now click directly on created/found records in AI responses ### Workflow Agent Fixes - Fixed cache invalidation issue when creating agents in workflows - Added default prompt for workflow-created agents to prevent validation errors - Relaxed agent validation to only check properties being updated (not all required properties) ### Code Quality Improvements - Extracted `getRecordDisplayName` utility that mirrors frontend's `getLabelIdentifierFieldValue` logic - Uses object metadata to determine the correct label identifier field - Handles `FULL_NAME` composite type for person/workspaceMember objects - Shared across create, find, and update record services ## Net Impact - **~1,200 lines deleted** (complex routing/planning code) - **~500 lines added** (simpler tool registry + record links) - Significantly reduced code complexity - Better tool discovery through full catalog in system prompt - Improved UX with clickable record references ## Testing - Typecheck passes - Lint passes - Manual testing of AI chat with record creation and linking |
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859004f4fc |
Refactor global datasource part 2 (#16399)
## Context Deprecating TwentyORMManager in favor of TwentyORMGlobalManager (temporarily, as this will simplify the ultimate goal to later replace all usages with the new TwentyORMGlobalManagerV2 which will have a similar signature) This means this PR had to refactor a bit of code to pass down the workspaceId when not available directly as it is now a requirement, meaning we also deprecated scopedWorkspaceContextFactory to have a less obscure way to fetch the workspaceId and have something more declarative. Step 3 will be to update TwentyORMGlobalManager to use a featureFlag toggling and use the new GlobalWorkspaceOrmManager internally using the new cache service Step 4 will be to remove the feature flag and pg_pool patch |
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223082a4da |
refactor(twenty-server): consolidate AI tool provider architecture (#16355)
## Summary Consolidates the AI tool provider architecture by creating a single `ToolProviderService` as the entry point for all tool generation. This removes multiple intermediate services and simplifies the codebase. ## Changes ### New Architecture - **`ToolProviderService`**: Single service for all tool generation with: - `getTools(spec)` - Get tools by category with permissions - `getToolByType(type)` - Get specific tool for workflow execution - **`ToolCategory` enum**: Declarative specification of tool types: - `DATABASE_CRUD` - Record CRUD operations - `ACTION` - HTTP requests, email sending, article search - `WORKFLOW` - Workflow management tools - `METADATA` - Object/field metadata tools - `NATIVE_MODEL` - Model-specific tools (e.g., web search) - **`ToolSpecification` type**: Clean API for requesting tools with permissions ### Removed - `AiToolsModule` - No longer needed - `ToolService` - Logic inlined into ToolProviderService - `ToolAdapterService` - Logic inlined into ToolProviderService - `ToolRegistryService` - Logic inlined into ToolProviderService ### Updated - All consumers (agents, chat, MCP, workflows) now use `ToolProviderService` - Test files updated accordingly ## Stats - **547 insertions, 1146 deletions** (net ~600 lines removed) - 4 services deleted - 1 module deleted ## Testing - [x] Typecheck passes - [x] Lint passes |
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2803292521 |
feat: add Metadata Builder agent for data model management (#16350)
## Summary This PR adds a new **Metadata Builder** AI agent that specializes in managing the workspace data model (creating objects, adding fields, etc.). ## Changes ### New Files - `data-model-manager-role.ts` - New standard role with `DATA_MODEL` permission flag - `metadata-builder-agent.ts` - New standard agent for data model management ### Modified Files - **ChatToolsProviderService**: Refactored to consolidate all permission-based tools into a single `getChatTools()` method. Now injects both workflow tools and metadata tools based on permissions. - **AgentChatRoutingService**: Updated to use the new consolidated `getChatTools()` method - **AiChatModule**: Added imports for `ObjectMetadataModule` and `FieldMetadataModule` - **Router system prompt**: Added metadata-builder agent selection rules with clear distinction between schema operations vs data operations - **Metadata tools factories**: Improved error messages to show detailed validation errors instead of generic messages ### Refactoring - Renamed `index.ts` files to `standard-agent-definitions.ts` and `standard-role-definitions.ts` to follow naming conventions - Renamed exports from `standardAgentDefinitions` to `STANDARD_AGENT_DEFINITIONS` (SCREAMING_SNAKE_CASE) ## Key Features 1. **Metadata Builder Agent** can: - Create new custom objects - Add fields to existing objects - Update object and field properties - Create relations between objects 2. **Permission-based tool injection**: Tools are automatically injected based on the `DATA_MODEL` permission flag 3. **Improved routing**: The router now correctly distinguishes between: - "Create an object called Project" → metadata-builder (schema) - "Create a company called Acme" → data-manipulator (data) 4. **Better error messages**: Validation errors now show detailed messages like: ``` Validation errors: [objectMetadata] Name must be in camelCase format [objectMetadata] Label is required ``` |
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9cecbaebc3 |
refactor(workflow-tools): reorganize to one file per tool with co-located schemas (#16313)
## Summary Reorganizes workflow tools to improve maintainability and discoverability by having one file per tool with co-located input schemas. ## Changes - Create individual tool files in `tools/` directory (11 files) - Co-locate input schemas with their tool implementations - Add shared types file for dependencies and context - Simplify workspace service to aggregate tool factories - Remove centralized `schemas/` directory ## New Structure ``` workflow-tools/ ├── services/ │ └── workflow-tool.workspace-service.ts ├── tools/ │ ├── activate-workflow-version.tool.ts │ ├── compute-step-output-schema.tool.ts │ ├── create-complete-workflow.tool.ts │ ├── create-draft-from-workflow-version.tool.ts │ ├── create-workflow-version-edge.tool.ts │ ├── create-workflow-version-step.tool.ts │ ├── deactivate-workflow-version.tool.ts │ ├── delete-workflow-version-edge.tool.ts │ ├── delete-workflow-version-step.tool.ts │ ├── update-workflow-version-positions.tool.ts │ └── update-workflow-version-step.tool.ts ├── types/ │ └── workflow-tool-dependencies.type.ts └── workflow-tools.module.ts ``` ## Benefits - **Co-location**: Schema and tool logic are in the same file - **Single responsibility**: Each file handles one tool - **Easier maintenance**: Changes to a tool only touch one file - **Better discoverability**: File names match tool names |
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f248b3f7f4 | refactor: move agent evaluation to background jobs for non-blocking execution (#16234) | ||
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13e283fc3a | Rename roleTargets -> roleTarget (#16247) | ||
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4f20fd35c5 |
feat: Add Agent Evaluation System and Refactor AI Modules (#16111)
## Summary This PR introduces a comprehensive agent evaluation system and refactors the AI module structure for better organization. ## Key Changes ### 🎯 Agent Evaluation System - Added **Agent Turn Evaluation** entities, DTOs, and database schema - New GraphQL mutations: `evaluateAgentTurn` and `runEvaluationInput` - Added `evaluationInputs` field to Agent entity for storing test inputs - New `AgentTurnGraderService` for automatic turn evaluation - Added evaluation UI with new **Evals** and **Logs** tabs in agent detail pages ### 🏗️ Entity & Module Refactoring - Renamed `AgentChatMessage` → `AgentMessage` for clarity - Consolidated chat entities: `AgentMessage`, `AgentTurn`, and `AgentChatThread` - Reorganized AI modules under `ai/` subdirectory structure - Updated imports across codebase to reflect new module paths ### 🤖 New Agents & Roles - Added **Dashboard Builder Agent** for dashboard creation and management - Added **Dashboard Manager Role** with appropriate permissions - Updated role permissions to be more granular (users vs agents vs API keys) ### 🔐 Permission System Updates - Added `HTTP_REQUEST_TOOL` permission flag - Updated Workflow Manager role permissions (restricted tool access) - Enhanced permission flag types to differentiate between user/agent/API key contexts - Added `isRelevantForAgents`, `isRelevantForApiKeys`, `isRelevantForUsers` to permission flags ### 📨 Message Role Enhancement - Added `system` role to `AgentMessageRole` enum (alongside user/assistant) - Updated message handling to support system prompts ### 🎨 UI/UX Improvements - New tabs in agent detail: **Evals** and **Logs** - Added turn detail page: `/ai/agents/:agentId/turns/:turnId` - Fixed text overflow in `SettingsListItemCardContent` - Updated role applicability labels ("Assignable to Workspace Members") ### 🛠️ Technical Improvements - Fixed Zod schema validation for UUID and Date fields (use string validators) - Updated `ToolRegistryService` to properly register HTTP tool with permission flag - Enhanced error handling in agent execution services - Updated database migrations for new entity schema ## Database Migrations - `1764210000000-add-system-role-to-agent-message.ts` - `1764220000000-add-evaluation-inputs-to-agent.ts` - `1764200000000-add-agent-turn-evaluation.ts` - `1764100000000-refactor-agent-chat-entities.ts` ## Testing - [ ] Agent evaluation flow tested - [ ] Dashboard Builder agent tested - [ ] Permission system validated - [ ] UI tabs and navigation tested - [ ] Database migrations run successfully ## Breaking Changes ⚠️ **Entity Rename**: `AgentChatMessage` renamed to `AgentMessage` - GraphQL queries need updating ## Related Issues <!-- Link any related issues here --> ## Screenshots <!-- Add screenshots if applicable --> |