## Summary
`sendMessage` from `useChat` gives no feedback about whether a message
actually reached the backend, and the `fetch` override is wire-level: it
requires knowing endpoint semantics, cannot attribute requests to
messages, and misses the headStart first-turn POST entirely. This adds a
typed `onEvent` observability callback to `TriggerChatTransport` /
`useTriggerChatTransport` so send-success metrics, time-to-first-token,
and "sent but never answered" watchdogs become a few lines of client
code.
## Example
```ts
const transport = useTriggerChatTransport({
task: "my-chat",
accessToken: ({ chatId }) => mintChatAccessToken(chatId),
onEvent: (event) => {
switch (event.type) {
case "message-sent":
// Durably acknowledged by the session's input stream, not just "request accepted".
metrics.increment("chat.message_sent", { source: event.source });
metrics.timing("chat.send_duration_ms", event.durationMs);
break;
case "message-send-failed":
metrics.increment("chat.message_send_failed", { status: event.status });
break;
case "first-chunk":
metrics.timing("chat.ttft_ms", event.sinceSendMs ?? 0);
break;
case "turn-completed":
metrics.timing("chat.turn_duration_ms", event.sinceSendMs ?? 0);
break;
}
},
});
```
## Design
One callback, one discriminated union (`ChatTransportEvent`):
- `message-sent` / `message-send-failed`: terminal send outcomes with
`messageId`, a `source` discriminator (submit, regenerate, steer,
action, stop, head-start), `durationMs`, `bodyBytes`, the append's
idempotency key (`partId`, also stored on the server-side record), and
error + HTTP status on failure. `message-sent` means the append was
durably acknowledged, after any internal token-refresh retries.
- `stream-connected` (with a `resumed` flag and the cursor it connected
from), `first-chunk` (chunk type plus `sinceSendMs` for
time-to-first-token), `turn-completed` (`sinceSendMs` full-turn latency
and the agent's committed input cursor), and `stream-error` follow the
response side, so a send can be paired with the answer that should
follow it. `messageId` on response events is client-side attribution
from the last turn-producing send on that chat.
Emissions sit at the transport's existing choke points, covering every
send path uniformly (including steering and headStart, which the fetch
override cannot observe). Exceptions thrown by the callback are
swallowed: observability can never break the chat. The React hook keeps
the callback live across renders instead of freezing the first-render
closure.
## Verification
Unit tests drive the transport directly with the `fetch` override as the
network stub (send success/failure per source, stream lifecycle, resumed
flag, field enrichment, callback exceptions swallowed). Verified
end-to-end against a realistic metrics setup in the ai-chat reference
app (counters, send-duration and TTFT histograms, and both watchdogs
built purely on these events): a healthy two-turn chat produces exactly
the expected event sequence and TTFT values; an oversized append records
`message_send_failed` with status 413; and killing the worker after a
durable send fires both `sent_but_no_stream` and `sent_but_unanswered`,
reproducing and detecting the "message disappeared" failure mode that
motivated this feature.
## Summary
Sending a message to a chat whose run had ended could make the message
vanish: the continuation run replayed already-answered messages, never
processed the new one, and a page refresh lost it entirely. Chasing that
report surfaced four composing message-loss bugs in the chat session
runtime; this PR fixes all of them, each with a regression test.
## The fixes
1. **Stale resume cursor.** Records delivered while a run was suspended
(the waitpoint path) advanced the SSE resume counter but not the
committed-consume cursor, so the `session-in-event-id` header stamped on
turn-completes went stale by one record per suspended turn. Continuation
boots seed from that header, which is what made them replay
already-processed messages. `session.in.wait()` now advances both
cursors.
2. **Only the first buffered message dispatched.** Messages arriving
during a turn are consumed into a buffer whose end-of-turn pickup
dispatched only the first entry; the buffer was recreated each turn, so
the rest were discarded, and since consuming a record commits the cursor
the loss was permanent. A continuation boot's replay delivers several
records back-to-back, which put the user's new message at index 1 or
later. The buffer now outlives the turn and drains one message per turn
in both `chat.agent` and `chat.createSession` (whose equivalent buffer
was never read at all).
3. **Post-stop window in `chat.createSession`.** The turn's message
listener stayed attached through the stopped turn's post-stream work, so
a message sent shortly after stopping a turn was consumed into the dead
steering queue and lost. The listener now detaches when the stream
settles, matching the `chat.agent` loop.
4. **Handler leak on errored turns.** A turn that threw outside the
streaming section (for example from an `onTurnStart` hook) leaked its
message listener. Previously that silently lost mid-turn messages; with
the loop-level buffer it would have duplicated them instead. The
subscription handle is now detached by the turn's catch/finally, and
`chat.createSession` defensively detaches its prior turn's listener when
user code exits a turn without `complete()`/`done()`.
## Verification
Reproduced end-to-end with the ai-chat reference project before the fix
(message consumed but never answered, two replayed turns, gone on
refresh) and verified after (single clean turn, survives refresh,
turn-complete cursors strictly advancing). Regression tests in
`packages/trigger-sdk/test/pending-message-drain.test.ts` cover all
four, each verified red against the unfixed behavior. A smoke sweep of
the standard chat scenarios (basic send, multi-turn, suspend/resume,
mid-stream refresh, stop, steering, cancel + continue, and the
`createSession` variant) passes on the final branch state.
Removes the release-candidate framing from the docs for the 4.5 GA: the
`@rc` install caveats on the `skills` CLI command, and the AI Agents and
Prompts release-candidate banner (a shared snippet used across the
ai-chat and prompts pages) plus the `>=4.5.0-rc.0` compatibility pin in
the AI reference.
## Summary
Adds the `4.5.0` GA entry to the AI chat agents changelog covering the
`chat.agent` changes in that release: a new `apiClient` option on
`chat.headStart` and `chat.createStartSessionAction` for pointing chat
sessions at a different project or environment, the fix for messaging
chat agents deployed to a preview branch, and the fix for Head Start
handovers when the agent also defines a `prepareMessages` hook.
All four changes are from
[#4018](https://github.com/triggerdotdev/trigger.dev/pull/4018).
## Summary
Adds an in-dashboard AI agent: a chat panel, reachable from any
environment
page, that answers questions about your runs, errors, tasks, and
analytics,
diagnoses why a run failed, charts your data, reads your connected
repo's
source, and answers product and how-to questions. It is gated behind the
`hasDashboardAgentAccess` feature flag (global or per-org, default off),
so
this PR ships disabled: the launcher is hidden unless the flag is
enabled.
## Design
The agent runs as a standalone `chat.agent` Trigger task in its own
internal
package, with no access to the webapp database, Prisma, or ClickHouse.
It reads
the user's data over the public API, acting as the user via a
short-lived
delegated user-actor token minted server-side each turn (never in the
browser),
building on
[#3997](https://github.com/triggerdotdev/trigger.dev/pull/3997). The
error and analytics tools use
[#4005](https://github.com/triggerdotdev/trigger.dev/pull/4005)
and the TRQL query API.
The first turn of a new chat streams from a warm webapp route (Head
Start) while
the durable agent boots in parallel. Structured answers (a run-failure
diagnosis
card, a live chart) render through a small typed view catalog rather
than
arbitrary markup. A knowledge lane forwards product and how-to questions
to the
support assistant.
Conversation history lives in a separate Drizzle-backed store on its own
Postgres schema, kept as a display read-model so it can never corrupt
the
agent's model context.
The SDK changes add an `apiClient` option to
`chat.createStartSessionAction` and
`chat.headStart`, and keep the Head Start tool-approval tail intact
across a
custom `prepareMessages` hook so prompt caching and Head Start compose.
## Summary
Adds the `4.5.0-rc.7` entry to the AI chat changelog, covering the
agent-facing changes in
[v4.5.0-rc.7](https://github.com/triggerdotdev/trigger.dev/releases/tag/v4.5.0-rc.7):
- `chat.headStart` now works with the `chat.customAgent` and
`chat.createSession` backends, not just `chat.agent`
- Opt-in Anthropic system-prompt caching via
`chat.toStreamTextOptions()`
- Three custom-agent-loop fixes: continuation replay, mid-stream
steering, and task-backed tools
- `trigger skills` follow-ups: `trigger-` namespacing, SDK-bundled docs,
and a new cost-savings skill
Generic, non-agent rc.7 items (the CLI uninitialized-project error
message, run-span cost fields) are intentionally left out to keep this
changelog scoped to AI chat agents.
## Summary
Adds a "Stopping generation" section to the Custom agents page. It
documents how stop works when you drop down from `chat.agent` to
`chat.createSession`: pass `turn.signal` (a combined stop-and-cancel
`AbortSignal`) to `streamText`, and `turn.complete()` cleans up the
aborted partial, accumulates it as its own assistant message, and keeps
the run alive for the next turn. `turn.stopped` distinguishes a user
stop from a full run cancel.
Until now the createSession stop story only existed as scattered fields
in the reference table; the client side (`transport.stopGeneration`) and
the `chat.agent` run-callback signals were documented, but not the
custom-agent turn loop. Steering for these backends is already covered
on the pending messages page, which this page links to.
## Summary
Adds a "Duration and cost while paused" section to the human-in-the-loop
page. It explains that a HITL pause (a no-execute tool waiting on
`addToolOutput`) suspends the run and frees compute, so the human's
thinking time does not count against `maxDuration` (which measures
active CPU time and excludes suspended waitpoint time, the same as
`wait.for`). Customers don't need to raise `maxDuration` or end the run
to support long human waits.
This was a recurring point of confusion: readers assumed the pause holds
the run open and burns the budget. Also updates the how-it-works
pseudocode ("Agent suspends (compute freed)") and links `wait.for` and
`maxDuration` on first mention.
## Summary
The "What extractNewToolResults returns" reference in the
tool-result-auditing guide did not match the SDK. It listed an `input`
field that `chat.history.extractNewToolResults()` never returns, and
marked `output` as optional when it is always present.
This corrects the block to the real `ChatNewToolResult` shape
(`toolCallId`, `toolName`, `output`, optional `errorText`). Every usage
example in the same guide already reads only those fields, so the
reference now matches both the examples and the code.
## Summary
New `/ai-chat/prompt-caching` guide covering how to cache a chat agent's
prompt prefix with Anthropic prompt caching: the system prompt, the
conversation history (a `prepareMessages` breakpoint), and how caching
interacts with compaction. It also shows how to verify cache hits via
usage and the dashboard, the prefix-stability footguns, and an "Other
providers" section (OpenAI and Google cache automatically; Amazon
Bedrock uses `cachePoint` through `systemProviderOptions`).
Registered under Features in the AI Agents nav, next to Compaction.
---------
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Eric Allam <ericallam@users.noreply.github.com>
## Summary
`chat.headStart` now works with the `chat.customAgent` and
`chat.createSession` backends (not just `chat.agent`), and takes a
`triggerConfig` option. These docs cover both.
The Fast starts guide gets a "Handover with custom agents" section
showing how each backend consumes the handover (`consumeHandover`
returning `{ isFinal, skipped }` for custom agents, `turn.handover` for
createSession), including threading `originalMessages` so a resumed tool
round merges into the handed-over assistant. The `chat.headStart` API
section documents `triggerConfig` (tags, queue, machine, and the rest)
on the auto-triggered run.
The reference picks up `ChatTurn.handover`, `turn.complete()` with no
source, `chat.waitForHandover`, and a new `HeadStartHandlerOptions`
table.
Docs for the SDK changes in
[#3963](https://github.com/triggerdotdev/trigger.dev/pull/3963).
## Summary
Documents the Sessions HTTP API for non-SDK and server-to-server
callers, which until now appeared only in the conceptual
[ai-chat/sessions](https://trigger.dev/docs/ai-chat/sessions) page.
## What's covered
- **Sessions API reference** —
`create`/`list`/`retrieve`/`update`/`close` added to the OpenAPI spec
and a new "Sessions API" group (`management/sessions/*`), mirroring the
Runs API.
- **Channel endpoints** — a reference page for the `.in`/`.out` realtime
HTTP endpoints (append, SSE read, records drain), the wire protocol,
`Last-Event-ID` resume, and the per-direction auth boundary (`.out`
append is secret-key only).
- **Session scopes** — `read:sessions:{id}` / `write:sessions:{id}` in
the authentication docs, with the capability boundary and the 1h token
TTL.
Cross-linked with the SDK-side `ai-chat/sessions` page. Verified by
rendering each page on the Mintlify dev server.
## Summary
Adds the 4.5.0-rc.6 entry to the AI chat changelog, covering the
chat-facing items shipping in
[#3870](https://github.com/triggerdotdev/trigger.dev/pull/3870): the
chat.agent reliability batch, the continuation boot latency fix, the
chat.headStart hydration and reasoning fixes, the chat.createSession
stop and continuation fixes, and the new trigger skills installer.
Should merge alongside the release so the changelog matches the
published version.
## Summary
Documents the two lower-level chat backend APIs and restructures the
Building agents section so it has a sane reading order.
**Custom agents page.** `chat.customAgent()` was effectively
undocumented (one passing mention) and `chat.createSession()` was buried
at the bottom of the Backend page, prompted by a customer asking whether
dropping down a level was supported at all. Both now live on one
dedicated page framed as a composition: register with `customAgent`,
then drive turns with the managed `createSession` iterator or a
hand-rolled primitives loop. The page covers the patterns the managed
lifecycle otherwise handles for you, each verified against a running
agent: seeding history on continuation runs (and why the seed must go
through the turn-0 `addIncoming`, which replaces the accumulator),
persisting the user message before streaming so a mid-stream reload
keeps it, racing `totalUsage` after a stop so the loop cannot wedge, and
the single-message wire shape.
**Backend page.** Now leads with a decision table across the three
abstraction levels and focuses on `chat.agent()`, routing to the new
page. Stale examples that read a plural `messages` field off the wire
payload are fixed (copy-pasting them broke turn accumulation), and the
ChatSessionOptions / ChatTurn reference tables gain their missing rows
(`compaction`, `pendingMessages`, usage fields, `setMessages`,
`prepareStep`).
**Anatomy page + reorder.** The Building agents group opened with the
long How it works mechanics page, a wall right after the Quick Start. A
short Anatomy page now leads the group: the three moving parts, one
annotated example where each region names the page that covers it, and a
routing table. How it works moves to the end of the group as the depth
payoff, matching where peer docs put their internals pages.
All pages visually verified against a local Mintlify build; cross-links
and anchors updated across the section.
## Summary
Two documentation improvements for the AI chat docs.
**Head-start persistence contract.** The fast starts page now documents
what your hooks can rely on across a head-start handover: one stable
assistant `messageId` for the whole turn, `onTurnComplete` as the
canonical persistence point, reasoning parts flowing into durable
history, and how Head Start composes with `hydrateMessages` (the
first-turn history arrives as `incomingMessages`, and the runtime
splices the warm partial onto the hydrated chain, deduplicated by id).
The hydrate examples on the lifecycle hooks and database persistence
pages now upsert their conversation row, since head-start first turns
run without a preload to create it.
**Sessions page.** The page opened with "a durable, task-bound,
bi-directional I/O channel pair", which reads as jargon and omitted run
orchestration entirely. It now leads with the plain mental model (a pair
of durable streams: input carries user messages, output carries
everything the agent produces) plus the Session's role orchestrating
runs, a diagram, a minimal runnable example, and a section on the
one-session-many-runs lifecycle.
Documents behavior shipping in
[#3907](https://github.com/triggerdotdev/trigger.dev/pull/3907).
## Summary
Accuracy fixes across the AI chat docs: drop the non-existent per-call
option from `transport.preload`, clarify that `onValidateMessages` only
fires on turns carrying incoming messages, soften the turn-complete
token-refresh wording (the header is optional), document the new
`onTurnComplete` `error` field and `finishReason`, and correct the
idle-timeout default to 30 seconds.
## Summary
A new guide for connecting a database to your tasks: where to create the
client, how to size the connection pool against your provider's limit,
when to reach for a pooler, and how to release connections at waits so
you don't hit "too many connections" or crash on resume.
It covers node-postgres, Prisma, Drizzle, and MongoDB, with researched
direct and pooled connection limits for the common Postgres providers
(Supabase, Neon, RDS, PlanetScale) and MongoDB Atlas. The page lives
under Documentation, Troubleshooting, and is linked from the chat agent
docs (overview, lifecycle hooks, chat.local, and the database
persistence pattern).
## Summary
Documents AI SDK 7 support in the AI Chat docs. Pairs with the SDK
change in #3833.
- The reference compatibility matrix now lists the v7 peer range and
adds an `@ai-sdk/otel` row.
- A new "AI SDK 7 telemetry" section covers the `@ai-sdk/otel` install,
the automatic registration, and the `TRIGGER_AI_SDK_OTEL_AUTOREGISTER`
opt-out.
- The quick start surfaces the supported `ai` versions (v5/v6/v7) up
front, near where you install.
The reference/example projects (`references/`) now live in their own
repo, https://github.com/triggerdotdev/references, so their heavy,
frequently-changing dependencies are no longer part of this repo's
lockfile and tooling. This removes them here and repoints everything
that referenced them.
- Deletes `references/`; updates the pnpm workspace + lockfile.
- Clears the references-only CI rules and `.vscode` configs.
- Repoints the docs (contributor/agent + one public page) to the new
repo.
- `seed.mts` keeps the local-dev projects (hello-world, d3-chat,
realtime-streams).
## Summary
Documents the new `tools` option on `chat.agent` (companion to #3790).
Adds a dedicated [Tools](/ai-chat/tools) guide: the three places tools
show up (config, `toStreamTextOptions`, `streamText`), why declaring
them on the config matters for `toModelOutput` across turns, static vs
per-turn tools, the typed `run()` payload,
`InferChatUIMessageFromTools`, the relationship to skills, and the
manual `convertToModelMessages` path for `customAgent` loops.
Threads the option through the rest of the guide: the reference tables,
a happy-path section on the backend page, the types page, and the HITL /
skills / tool-result-auditing patterns. Corrects the sub-agents guide,
where the `toModelOutput` compression was implied to work across turns
but silently degraded from turn 2 without config tools.
Also unstacks the three callouts that were piled under the
`chat.agent()` header on the backend page, and adds a changelog entry.
## Summary
Updates the AI chat docs to match the slim-wire + field-level merge
behavior shipped in #3719 and the precise `.in/append` cap +
CORS-readable 413 shipped in #3720. No behavior changes here — code is
correct in `main`; the docs were lagging on three patterns customers
copy out of the page.
## What changed
- **`hydrateMessages` examples upsert by id** (in `lifecycle-hooks.mdx`,
`patterns/database-persistence.mdx`, and
`patterns/persistence-and-replay.mdx`). The previous
`stored.push(newMsg)` pattern duplicated the assistant id on HITL
continuations and caused the LLM to receive a tool call with no
`arguments`. The new examples include the rationale inline.
- **`onValidateMessages` example filters to user messages**
(`lifecycle-hooks.mdx`). The previous example called
`validateUIMessages({ messages, tools })` directly, which now throws on
HITL slim wires (the AI SDK schema requires `input` on resolved tool
parts). New example shows the filter pattern, with a Warning callout
explaining why.
- **Merge contract description updated** (`lifecycle-hooks.mdx`). The
old wording said incoming messages are "auto-merged" / "replaced"; the
new description explains the actual field-level overlay (state advances
only).
- **Approval-responded wire example slimmed** (`client-protocol.mdx`).
Shows the minimum shape the agent reads — `state` + `approval` (or
`output` / `errorText` for HITL). Notes that the built-in transports
ship this slim shape by default and that fuller shapes are still
accepted.
- **`/in/append` 413 row and FAQ updated** (`client-protocol.mdx`,
`patterns/trusted-edge-signals.mdx`). Reflects the new precise S2 cap
and the CORS-readable 413.
- **New changelog entry** at the top of `changelog.mdx` covering all of
the above.
The historical `## 512 KiB ceiling removed` entry further down the
changelog is left as-is (it's a snapshot of the prior transition), and
the v4.5 upgrade-guide section is skipped — the merge contract is
backwards compatible.
## Test plan
- Mintlify dev preview renders cleanly with no broken anchors
- Linked references resolve (`/ai-chat/lifecycle-hooks#hydratemessages`,
`/ai-chat/lifecycle-hooks#onvalidatemessages`,
`/ai-chat/patterns/database-persistence#alternative-hydratemessages`,
`/ai-chat/client-protocol#step-3-send-messages-stops-and-actions`,
`/ai-chat/patterns/large-payloads`)
## Summary
Two docs edits that close a footgun customers persisting transport state
can hit. Clearing `lastEventId` on `chat.endRun()` looks intuitive — the
Run ended, the cursor must be stale — but the cursor is sessionId-keyed,
not runId-keyed. Clearing it forces the next `sendMessages` to subscribe
from `seq_num=0`, which may hit the prior turn's still-durable
`turn-complete` record and close the SSE empty before the new Run's
chunks arrive.
Spells out the invariant in the frontend transport persistence table and
adds a Warning in the `chat.endRun()` reference.
## Test plan
- [x] Mintlify preview renders
- [x] No callout stacking
## Summary
Three post-merge fixes for the AI Agents docs (#3226), all caught by
review after merge.
## Fixes
- **`onTurnComplete` examples now use `db.$transaction`** — both the
Database persistence "Complete example" and the Lifecycle hooks
reference example were doing two separate `await` calls
(`db.chat.update` then `db.chatSession.upsert`). That's the exact
non-atomic pattern the warning earlier on the persistence page calls out
as ❌: a refresh between the two writes reads a stale `lastEventId` and
duplicates the assistant message on resume. Both examples now use the
recommended atomic form.
- **Background injection self-review prose aligned with the code** — the
prose said "gpt-4o-mini" but the example above it had been swapped to
`claude-haiku-4-5`. The Anthropic-sweep script only touched code blocks;
this prose line wasn't picked up.
## Test plan
- [x] Both updated examples use `db.$transaction([...])`
- [x] Prose matches the model used in the code block
- [ ] Mintlify deployment passes
## Summary
Lands the full AI Agents documentation surface alongside the v4.5
release candidate of `@trigger.dev/sdk`. Covers `chat.agent` end to end
— defining agents, lifecycle hooks, the frontend transport, sub-agents,
recovery from cancel/crash/OOM, AI Prompts integration — and the
Sessions primitive that backs it.
## Coverage
- **Conceptual**: Overview, Quick Start, How it works.
- **Building agents**: Backend (`chat.agent` / `chat.createSession` /
raw primitives), Lifecycle hooks, Frontend transport, Server-side
`AgentChat`, Sessions reference, `chat.local` state primitive,
TypeScript types.
- **Features**: AI Prompts integration, Fast starts (Preload + Head
Start), Compaction, Pending Messages (steering), Background Injection
(`chat.inject` + `chat.defer`), Actions (undo / regenerate / edit),
Error handling.
- **Patterns (13)**: Sub-agents, Branching conversations, Code sandbox,
Database persistence, Persistence and replay, HITL, Tool result
auditing, Large payloads, Agent skills, OOM resilience, Recovery boot,
Trusted edge signals, Version upgrades.
- **Reference**: API Reference, Client Protocol (wire format), Testing
harness (`mockChatAgent`), MCP server tools, Upgrade guide, Changelog.
## Structure changes
- Top-level nav: AI → **Agents**, with sub-groups for *Building agents /
Features / Patterns / Reference*.
- New RC banner snippet on every page links to the supported AI SDK
versions table on the API Reference.
- All examples use Anthropic with `stopWhen: stepCountIs(15)`.
---------
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Eric Allam