## Summary
Triggering a run with a very large `priority` could fail run creation
outright with an opaque database error. `priority` is multiplied by 1000
and stored in a 32-bit integer column, with nothing bounding it, so a
big enough value overflowed the column and the create failed. The
trigger now caps the value to the highest supported priority instead of
erroring, so the run is still created.
## Fix
`priorityMs` (the stored `priority * 1000`) now goes through a
`clampPriorityMs` helper before the write. It rounds to a whole number
and clamps into the column range at both ends, so only a valid integer
ever reaches the column and an out-of-range priority caps rather than
failing. Single and batch triggers share the write path, so both are
covered.
## Summary
The run page could show an AI generation cost well above what the
provider actually charged, most visibly for OpenRouter and Vercel AI
Gateway requests where a heavily cache-read prompt was priced at the
full input rate. When the provider reports an exact per-request cost, we
now use that instead of catalog pricing.
## Fix
Gateway and OpenRouter include the exact per-request cost in
`ai.response.providerMetadata` (`openrouter.usage.cost` /
`gateway.cost`). That figure already reflects the cache-read discount
and the real per-provider rate, which the catalog cannot reconstruct:
cache-read counts do not arrive in `gen_ai.usage.*`, and per-model
catalog prices drift from what the provider billed, in either direction.
So provider-reported cost is now preferred, and the catalog is used only
when no provider cost is present.
Fallback routing is covered by the same change: when OpenRouter routes
to a different model, `gen_ai.response.model` already carries the served
model, so the cost follows the served model and the provider's own
figure makes it exact.
`extractProviderCost` now runs on every AI span, so it gets a cheap
`"cost"` substring guard to skip the JSON parse on reasoning-model spans
whose provider metadata carries large reasoning text and no cost field.
Regression tests cover the cache-discount overcharge, fallback
served-model pricing, gateway cost, and the catalog fallback path.
Once this is merged, oxlint is at a pretty sensible baseline.
**Enable `no-unused-vars`, `typescript/consistent-type-imports`, and
`import/no-duplicates` lint rules**
Turns on three previously-disabled oxlint rules across the monorepo and
fixes all violations:
- **`no-unused-vars`** – enabled as an error with standard ignore
patterns: unused function arguments are ignored by default (`args:
"none"`), variables/caught errors/destructured array elements prefixed
with `_` are allowed, and rest siblings are permitted.
- **`typescript/consistent-type-imports`** – enforced as an error; all
type-only imports now use the `import type` syntax.
- **`import/no-duplicates`** – enforced as an error; duplicate import
statements from the same module have been merged.
The remaining commits clean up the violations found across the codebase:
removing unused variables/imports/type aliases, adding `_` prefixes to
intentionally unused bindings, fixing duplicate imports, and converting
value imports to `import type` where appropriate.
## Summary
The Models page is now split into two tabs. **Your models** shows the
models your project has actually used in the selected time range, with
usage charts (cost over time, tokens over time, calls by model), a
per-model table of calls / cost / avg TTFC / avg tokens-per-sec, and
calls/tokens trend sparklines. **Model library** is the full catalog,
reordered from alphabetical to a relevance-based provider order
(Anthropic, OpenAI, Google, then the rest), newest models first within
each provider, with a "New" badge on models released in the last 7 days.
One time-range selector drives the whole Your models tab, so the charts,
the table, and the sparklines all share the same window. Opening a model
shows its own metrics with an independent range picker and a "View in AI
metrics" link that opens the AI metrics dashboard filtered to that
model. The active tab is kept in the URL so it survives a refresh and is
shareable.
## Prompt caching & cost accuracy
Both the Your models tab and the AI metrics dashboard now surface
prompt-cache usage: a cache-savings column plus per-model cached-tokens
and cache-hit-rate views, and a caching section on the dashboard (hit
rate, cached tokens, estimated savings, and hit rate by model).
Building this surfaced a cost bug. `input_tokens` is the total prompt
count and already includes cache-read and cache-creation tokens, but the
cost pipeline charged the full input at the input price and then added a
separate cache line, so cached tokens were billed twice (and on
Anthropic, cache reads were never discounted because their price is
keyed differently). The input price now applies only to the non-cached
remainder, with cache prices resolved across the provider-specific keys,
so LLM cost and the cache hit-rate metric are accurate. Hit rate is
computed as cached reads over total input.
## Notes
Also fixes React "invalid DOM property" console warnings from the
provider icons (the Llama and DeepSeek SVGs used raw `fill-rule` /
`clip-rule` / `clip-path` attributes), which this page surfaces by
rendering more provider icons.
## Screenshots
**Your models tab:** usage charts and a per-model table with
calls/tokens trend sparklines.
<img width="2560" height="1267" alt="1-your-models-tab"
src="https://github.com/user-attachments/assets/859bd24f-9047-4828-8bbb-83e5882846d6"
/>
**Model library:** provider-relevance ordering with a "New" badge on
models released in the last 7 days.
<img width="2560" height="1267" alt="2-model-library-tab"
src="https://github.com/user-attachments/assets/46dd54b9-80f9-4922-ade9-5935b08dfebc"
/>
**Model detail, Metrics tab:** per-model range picker and a "View in AI
metrics" link.
<img width="2560" height="1267" alt="3-model-detail-metrics"
src="https://github.com/user-attachments/assets/0f65d9d0-6142-4918-93f0-110bb277101a"
/>
**View in AI metrics:** the dashboard deep-linked and filtered to the
selected model.
<img width="2560" height="1267" alt="4-ai-metrics-filtered"
src="https://github.com/user-attachments/assets/821f256c-e305-493c-98c7-eafaf2f57f83"
/>
## Summary
Three fixes to the AI agent surface in the dashboard, all surfaced while
verifying AI SDK 7 support (the SDK side is #3833):
- **AI SDK 7 telemetry rendering.** The generation-span inspector and
run metrics now read both the v6 (`ai.*`) and v7 (`gen_ai.*`) telemetry
attribute shapes. On v7 the Messages, Provider, and Tools views showed
empty/unknown before; now they render correctly.
- **HITL approvals in the conversation view.** The agent conversation
view renders human-in-the-loop tool approvals and denials (awaiting
approval, approved, denied with reason) instead of leaving the tool part
blank. This gap predated v7.
- **Chat snapshot store mismatch.** Chat session snapshots now resolve
through a single storage-key helper shared by the SDK write and the
dashboard read. Previously the write applied the default object-store
protocol to the key while the read fell back to a different store, so
the dashboard 404'd on the snapshot and showed only a partial
conversation.
## Summary
Each scheduled-task tick previously issued **3 Prisma `UPDATE`s**
against
`TaskSchedule.lastRunTriggeredAt`,
`TaskScheduleInstance.lastScheduledTimestamp`,
and `TaskScheduleInstance.nextScheduledTimestamp`. All three were pure
denormalization — every value can be derived without persisting.
After this PR `TaskSchedule` and `TaskScheduleInstance` become **near
read-only**:
writes happen only on schedule create / update / delete (rare admin
actions),
so the per-tick autovacuum churn on these hot tables disappears.
## Design
The previous fire time travels forward through the **schedule worker
payload**,
not through the database. Concretely:
- The `schedule.triggerScheduledTask` worker payload gains an optional
`lastScheduleTime: z.coerce.date().optional()` field.
- When the engine fires a schedule, it re-enqueues the next tick with
`lastScheduleTime = scheduleTimestamp` (the just-fired time).
- When the next tick dequeues, `payload.lastTimestamp` is sourced from
`params.lastScheduleTime` directly. No DB round-trip, no cron-derivation
drift across DST boundaries, no caveats around recently-edited cron
expressions.
`payload.lastTimestamp` keeps its `Date | undefined` SDK shape.
First-ever
fires still report `undefined`, so customer `if
(!payload.lastTimestamp)`
first-run patterns keep working.
For Redis jobs that were enqueued **before** this change (which lack
`lastScheduleTime` in their payload), the engine falls back to
`instance.lastScheduledTimestamp` once. Once those drain, the column is
never read again. Revert is code-only; the columns stay in place and can
be dropped in a follow-up once the rollout is stable.
## Files
- `internal-packages/schedule-engine/*` — engine refactor,
`workerCatalog`
schema field, `TriggerScheduleParams` extension, tests updated to assert
on the worker-payload flow rather than DB readbacks.
- `internal-packages/database/prisma/schema.prisma` — `/// @deprecated`
triple-slash docstrings on the three columns. No migration.
- `apps/webapp/app/presenters/v3/ScheduleListPresenter.server.ts` —
drops
the `lastRunTriggeredAt` Prisma select; "Last run" cell is approximated
from the cron expression's previous slot, gated on `schedule.createdAt`
so brand-new schedules show "–". UI is best-effort; the runs page is the
source of truth.
- `apps/webapp/app/v3/utils/calculateNextSchedule.server.ts` — adds a
`previousScheduledTimestamp` helper for the UI cell above. Public API
responses (`api.v1.schedules.*`) already compute `nextRun` from cron and
don't expose `lastTimestamp` — no public API change.
- `references/scheduled-tasks/` — new reference project with declarative
schedules at multiple cadences and three throw-on-fail validators
(`first-fire-detector`, `interval-validator`, `upcoming-validator`) for
E2E-verifying the worker-payload flow.
Refs TRI-8891
## Test plan
- [x] `pnpm run typecheck --filter @internal/schedule-engine --filter
webapp`
- [x] `pnpm run build --filter @trigger.dev/core`
- [x] `pnpm run test --filter @internal/schedule-engine` — integration
test
asserts first-fire `lastTimestamp === undefined`, second fire carries
the previous fire's timestamp exactly.
- [x] E2E against local webapp via `references/scheduled-tasks`:
- Fresh schedules attached → all three deprecated columns stay `NULL`
after
multiple fires.
- Redis payload at second fire contains
`"lastScheduleTime":"<previous fire timestamp>"`.
- `TaskRun.payload` and the every-minute task's returned output both
confirm
`lastTimestamp = null` on first fire and `lastTimestamp = <prev fire>`
on
second fire, exactly 60s apart.
- All three throw-on-FAIL validators completed successfully on every
non-first fire.
- [x] Schedules REST API end-to-end (`POST` / `GET` / `PUT` / `activate`
/
`deactivate` / `DELETE`) — `nextRun` recomputed live from cron + tz on
every response, no reads of deprecated columns.
- Full prompt management UI: list, detail, override, and version
management for AI prompts defined with `prompts.define()`
- Rich AI span inspectors for all AI SDK operations with token usage,
messages, and prompt context
- Real-time generation tracking with live polling and filtering
## Prompt management
Define prompts in your code with `prompts.define()`, then manage
versions and overrides from the dashboard without redeploying:
```typescript
import { task, prompts } from "@trigger.dev/sdk";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
import { z } from "zod";
const supportPrompt = prompts.define({
id: "customer-support",
model: "gpt-4o",
variables: z.object({
customerName: z.string(),
plan: z.string(),
issue: z.string(),
}),
content: `You are a support agent for Acme SaaS.
Customer: {{customerName}} ({{plan}} plan)
Issue: {{issue}}
Respond with empathy and precision.`,
});
export const supportTask = task({
id: "handle-support",
run: async (payload) => {
const resolved = await supportPrompt.resolve({
customerName: payload.name,
plan: payload.plan,
issue: payload.issue,
});
const result = await generateText({
model: openai(resolved.model ?? "gpt-4o"),
system: resolved.text,
prompt: payload.issue,
...resolved.toAISDKTelemetry(),
});
return { response: result.text };
},
});
```
The prompts list page shows each prompt with its current version, model,
override status, and a usage sparkline over the last 24 hours.
From the prompt detail page you can:
- **Create overrides** to change the prompt template or model without
redeploying. Overrides take priority over the deployed version when
`prompt.resolve()` is called.
- **Promote** any code-deployed version to be the current version
- **Browse generations** across all versions with infinite scroll and
live polling for new results
- **Filter** by version, model, operation type, and provider
- **View metrics** (total generations, avg tokens, avg cost, latency)
broken down by version
## AI span inspectors
Every AI SDK operation now gets a custom inspector in the run trace
view:
- **`ai.generateText` / `ai.streamText`** — Shows model, token usage,
cost, the full message thread (system prompt, user message, assistant
response), and linked prompt details
- **`ai.generateObject` / `ai.streamObject`** — Same as above plus the
JSON schema and structured output
- **`ai.toolCall`** — Shows tool name, call ID, and input arguments
- **`ai.embed`** — Shows model and the text being embedded
For generation spans linked to a prompt, a "Prompt" tab shows the prompt
metadata, the input variables passed to `resolve()`, and the template
content from the prompt version.
All AI span inspectors include a compact timestamp and duration header.
## Other improvements
- Resizable panel sizes now persist across page refreshes (patched
`@window-splitter/state` to fix snapshot restoration)
- Run page panels also persist their sizes
- Fixed `<div>` inside `<p>` DOM nesting warnings in span titles and
chat messages
- Added Operations and Providers filters to the AI metrics dashboard
## Screenshots
<img width="3680" height="2392" alt="CleanShot 2026-03-21 at 10 14
17@2x"
src="https://github.com/user-attachments/assets/f3e59989-a2fa-4990-a9d0-3cacda431868"
/>
<img width="3680" height="2392" alt="CleanShot 2026-03-21 at 10 15
37@2x"
src="https://github.com/user-attachments/assets/2f2d02df-2d2b-44fb-ac6f-9153f6a6c387"
/>
<img width="3680" height="2392" alt="CleanShot 2026-03-21 at 10 15
54@2x"
src="https://github.com/user-attachments/assets/baa161e0-ef91-4fa4-a55f-986b71cccdf0"
/>
- Automatic LLM cost enrichment for AI SDK spans (streamText,
generateText, generateObject) or any other spans that use semantic
gen_ai attributes with support for 145+ models
- New AI span inspector sidebar showing model, tokens, cost, messages,
tool calls, and response text
- LLM metrics dual-write to ClickHouse `llm_metrics_v1` table for
analytics
- LLM metrics built-in dashboard (unlinked at the moment)
- Provider cost fallback — uses gateway/OpenRouter reported costs from
`providerMetadata` when registry pricing is unavailable
- Prefix-stripping for gateway/OpenRouter model names (e.g.
`mistral/mistral-large-3` matches `mistral-large-3` pricing)
- Admin dashboard for managing LLM model pricing (list, create, edit,
delete, search, test pattern matching)
- Missing models detection page — queries ClickHouse for unpriced models
with sample spans and Claude Code-ready prompts for adding pricing
- AI span seed script (`pnpm run db:seed:ai-spans`) with 51 spans across
12 provider systems for local dev testing
- UI fixes: `completionTokens`/`promptTokens` aliases,
`ai.response.object` display for generateObject, cache read/write token
breakdown
## Screenshots:
<img width="1030" height="104" alt="CleanShot 2026-03-17 at 16 48 54@2x"
src="https://github.com/user-attachments/assets/bc8fccda-e48b-4d0c-bfb1-e620064e5979"
/>
<img width="1094" height="1512" alt="CleanShot 2026-03-17 at 16 49
23@2x"
src="https://github.com/user-attachments/assets/c2424569-d07e-4d67-a436-e8250043a1ee"
/>
<img width="1074" height="1412" alt="CleanShot 2026-03-17 at 16 49
18@2x"
src="https://github.com/user-attachments/assets/22342ac4-4769-45d1-a328-a24fb9a82a50"
/>
<img width="1012" height="2292" alt="CleanShot 2026-03-17 at 16 39
01@2x"
src="https://github.com/user-attachments/assets/59e327d1-6652-4293-8be0-bb8326e5fbc5"
/>
<img width="3680" height="2392" alt="CleanShot 2026-03-15 at 08 29
38@2x"
src="https://github.com/user-attachments/assets/1f77beb8-de67-495b-b890-bcdb8d7f1fe8"
/>
---------
Co-authored-by: James Ritchie <james@trigger.dev>
This PR implements a new run TTL system and queue size limits to prevent
unbounded queue growth which should help prevent situations where queues
enter a "death spiral" where the queue will never be able to catch up.
The main/correct way to battle this situation is to enforce a maximum
TTL on all runs (e.g. up to 14 days) where runs that have been queued
for that maximum TTL will get auto-expired, making room for newer runs
to execute. This required creating a new TTL system that can handle
higher workloads and is now deeply integrated into the RunQueue. When
runs are enqueued with a TTL, they are added to their normal queue as
well as to the TTL queue. When runs are dequeued, they are removed from
both their normal queue and the TTL queue. If runs are dequeued by the
TTL system, they are removed from their normal queue. Both these
dequeues happen automatically so there is no race condition.
The TTL expiration system is also made reliable by expiring runs via a
Redis worker, which is enqueued to atomically inside the TTL dequeue lua
script.
### Optional associated waitpoints
Additionally, this PR implements an optimization where runs that aren't
triggered with a dependent parent run will no longer create an
associated waitpoint. Associated waitpoints are then lazily created if a
dependent run wants to wait for the child run post-facto (via debounce
or idempotency), which is a rare situation but is possible. This means
fewer waitpoint creations but also fewer waitpoint completions for runs
with no dependencies.
### Environment Queue Limits
Prevents any single queue growing too large by enforcing queue size
limits at trigger time.
- Queue size checks happen at trigger time - runs are rejected if queue
would exceed limit
- Dashboard UI shows queue limits on both the Queues page and a new
Limits page
- In-memory caching for queue size checks to reduce Redis load
### Batch trigger fixes
Currently when a batch item cannot be created for whatever reason (e.g.
queue limits) the run will never get created, which means a stalled run
if using `batchTriggerAndWait`. We've updated the system to handle this
differently: now when a batch item cannot be triggered and converted
into a run, we will eventually (after retrying 8 times up to 30s) we
will create a "pre-failed" run with the error details, correctly
resolving the batchTriggerAndWait.
* Simulate "next steps" when calculating the next timestamp to prevent millions of iterations on dev schedues
* Add additional tests
* Fix typescript issue
* AI SDK sql generator and approval example WIP
* Create some nice spans and extract the tools out so we can get the type of the streams
* Enable AI SDK telemetry
* Adding ai.tool and removing toolTask, 3rd party telemetry spans now wil create partials, better ai SDK telemetry icons
* Created a separate d3-chat example, split out from the openai-agents example
* Fixed the tool options being passed to metadata in `ai.tool`
* Add a link to the run
* Slightly improved design
* Add a crawler task using crawl4ai
* Use a tool to get the userId
* Couple of tweaks
* Adding markdown rendering to assistant messages and added an e2b based chart rendering task
* Backup to anthropic
* Add changeset
* D3 demo WIP
* Agent working and completing token successfully
* Sending OpenAI Agent SDK spans through to the platform now works
* A couple of perf tweaks for enriching events
* WIP
* Get max duration working on deployed runs
* Actually set the timed out runs to status = TIMED_OUT
* The client status for TIMED_OUT is now MAX_DURATION_EXCEEDED
* New TimedOutIcon
* Added new timedout icon
* Add ability to opt-out of maxDuration with timeout.None
* MAX_DURATION_EXCEEDED -> TIMED_OUT
* changeset
* Improved styling for the status tooltip content
---------
Co-authored-by: James Ritchie <james@trigger.dev>
* upgrade @opentelemetry packages to the latest versions
* remove v2 only packages, will be moved to a dedicated repo
* remove more v2 code and run pnpm install
* use the npm yalt package in the webapp
* convert @trigger.dev/core to tshy
* Switch from jest to vitest in @trigger.dev/core
* Fixed core test
* move core-backend code into core subpath export
* convert @trigger.dev/sdk to tshy
* Removed hono
* move core-apps to core/v3/apps, remove core-apps, start converting cli-v3
* Fix up some of the commands
* cli now building and loadable
* using package-json-from-dist to get package version now in core and cli
* dev command WIP
* cleaned up some repetition and structure of the entry point stuff
* bringing back the background worker stuff
* Indexing of the v3 catalog
* getting closer to executing dev runs...
* centralize dev logging using event emitter
* Move indexing to it’s own entry point, simplify code
* dev runs working
* Get instrumentation to work with openai
* debugging achieved internally
* provide worker files as part of the worker creation on the server
* support for cjs and esm javascript
* Fixed timeout
* worker manifest now has the config path
* auto-upgrade config to non-deprecated alternatives
* Adding package preview release
* deployment WIP
* improve the syncEnvVars output and adapt resolveEnvVars
* WIP bun runtime
* WIP bun support
* seed tasks with the machine preset if listed in the config
* deploy run executions WIP, extracted TaskRunProcess into 1 place
* deployed tasks running and executing 🎉
* support for waits and better flushing & process cleanup
* Fixed the heartbeating
* Better warning messages
* Improve and unify the indexing between dev and deploy
* Support for external deps that need node-gyp to build
* build extensions can now install custom packages and run instructions in the image. Also prisma extension now works and also works with multiple schema files
* Add back in the main/types/module to sdk
* dev no longer is Ink/React, grace period for disconnections in dev
* Fix the changeset config
* More changeset fixes
* Remove config packages
* More changeset fixes
* Fixed typescript issues (needed to revert back to zod 3.22.3
* Fix pr_checks workflow
* Remove the prepare script
* Fixed tests and package versions
* Remove cli test script
* Remove packages from tailwind watch paths
* Add repo to public packages
* Just commit the generated files and do the building at dev time
* Try and get pkg.pr.new working
* Try again
* Fix emitDecoratorMetadata importing named export from typescript
* config file backwards compat with export const config
* Fixed issue where import errors weren’t coming through
* p-retry is a prod dep
* typescript needs to be a prod dependency for emitDecoratorMetadata
* Add better debug logging to help track down import-in-the-middle bug
* An external is only considered resolvable if it resolves to the same path as the collected external
* Fix runtime checks to allow >=18.20
* Move extensions to a new build package
* Fixed building packages in dockerfile
* Remove the e2e test from publish workflow for now
* Don’t treat pkg.pr.new versions has needing upgrading
* making sure config handleError works, and discovered path aliases don’t work in config files
* Strip empty string env vars so they accidentally override real values
* Couple of things
* Update version to use preview instead of beta
* Hopefully fix re-attempts with >30s delay
* Match socket emit messages to current latest in main
* Initial guide
* Go back to beta
* Go back to the preview, and update guide to use pr preview tags
* Go back to beta
---------
Co-authored-by: Matt Aitken <matt@mattaitken.com>
* Added maximumScheduleInstancesLimit column to Org, default to 20
* Docs on the schedule limits and improved soft-limit communication
* Added limit info to the schedules list page
* Created a task that creates schedules, useful for testing
* Make deduplicationKey required when creating/updating a schedule using the SDK
* New schedule button shows an alert if you’re over the limit
* Added timezone to the form and db
* WIP on the timezone dropdown for the create/edit schedule form
* Use the new filter search for timezones
* Made the timezone dropdown faster by fixing the virtualization
* The preview table is working and added a nice message about daylight savings
* Created a page where you can view the full list of timezones
The URL is included in the error message if you send an invalid time using the SDK
* Creating tasks with the timezone
* Added timezone support the the scheduler and the schedules list
* Added timezone support to more of the schedules UI
* The timezone comes through to scheduled runs with nice JSDocs
* Allow setting the timezone from the SDK
* Always have a timezone on a schedule
* Updated jsdocs
* Updated catalog example
* Changed the column to be a string, not null. Added the timezone across the SDK
* API endpoint for getting the timezones
* Added an SDK function to get the list of timezones
* Added timezones to the docs
* Changeset: Added timezone support to schedules
* Added support for testing timezone
* Tidied up imports
* Imports
* Imports
* Update limits.mdx
* Fixed a couple type issues and use the already exported zodfetch
---------
Co-authored-by: Eric Allam <eallam@icloud.com>
* Fixes an issue that was treating v2 trigger directories as v3
* Make msw a normal dependency (for now) to fix Module Not Found error in Next.js.
* Extract out all the zod* stuff from core so the SDK does not import it
* Add a changeset
* Fixing typecheck errors in the webapp
* Export the Task and TaskOptions types
* Extract additional exports from core/v3 that aren’t used in the SDK
* Move to our global system from AsyncLocalStorage for the current task context storage
* Update the esbuild core bundling plugin for the new core v3 exports
* Fix v3 CLI telemetry
* Add support for tasks located in subdirectories inside trigger dirs
* Remove the env var check during deploy (too many false negatives)
* Fixes various issues with triggerAndWait and batchTriggerAndWait
When using idempotency keys, triggerAndWait and batchTriggerAndWait will still work even if the existing runs have already been completed (or even partially completed, in the case of batchTriggerAndWait)
- TaskRunExecutionResult.id is now the run friendlyId, not the attempt friendlyId
- A single TaskRun can now have many batchItems, in the case of batchTriggerAndWait while using idempotency keys
- A run’s idempotencyKey is now added to the ctx as well as the TaskEvent and displayed in the span view
- When resolving batchTriggerAndWait, the runtimes no longer reject promises, leading to an error in the parent task
* Remove the default queue concurrency limit as we now have env and org concurrency limits
* Use the run friendlyId in the completion result id
* Added some error logging
* Database schema and migrations for schedules
* Added schedules to the side menu
* The pagination can optionally hide the page numbers for a compactive mode
* Filters for the schedule page
* Added triggerSource (“STANDARD”, “SCHEDULED”) to BackgroundWorkerTask
* Added the ability to disabled a LinkButton
* Started work on the schedule page
* Environment buttons
* The new schedule form styles
* Added a cxouple of extra fields
* Allow a checkbox to have a rich label
* Added cronstrue package to the webapp
* WIP creating tasks using the form
* Improved the form styling
* Creating schedules is working in the UI
* Minor improvements
* Basic schedule table is displaying
* Creating tasks with triggerSource = scheduled. Refactored how task metadata is stored and accessed to be cleaner
* Resource route
* Fixes in the form
* Added a gap between the environments
* WIP on OpenAI generating CRON expressions
* AI generated CRON expressions is working
* Fix for the CRON field being uneditable after an AI generation
* Improvements
* Table padding
* useThrottle now behaves correctly
* Added filtering to the schedules list
* Improved the layout and fixed CRON search
* Fixed pagination for the schedules list. Just use a regular Prisma query
* Page size of 20
* Added links to the schedule rows
* Get rid of the Last run column for now
* Implement triggered scheduled tasks
Also implemented superjson payloads and dev runtime environment “presence” with RuntimeEnvironmentSession
* Move CronPattern and CreateSchedule into a common client-accessible file
* Latest UI changes
* Fix for creating a task schedule with a blank dedup key
* Refactor the human to cron stuff into a separate file and use json_object OpenAI response format
* Fix for trying to use a hook on the server-side…
* A couple of fixes to the new schedule form
* WIP on viewing a scheduled run
* Make the filters all optional
* Use the RunListPresenter from the schedule presenter
* Display a table of runs… the wrong runs but still
* Runs from the schedule
* Deleting schedules from the UI
* Tidied imports and fixed name of options object
* Disabling a schedule
* Editing schedules
* Tidied imports
* Added icons to the task list, needs some design love
* Added a tooltip for CRON pattersn
* Show the last run in the schedules table
* Some tweaks
* Added a placeholder to the CRON AI field
* Improved the trigger source icon
* Dim out disabled schedules
* Scheduled tasks have the correct icon in a run
* Added the task source icon to the test task list
* Added the date field component to storybook
* Style improvements to the date field
* Implement Task Schedule API
* added a medium sized variant to the date field
* Fixed replay run for superjson payload types
Also now linking from the replaying run to the original run (using span links)
Also added a project metrics prometheus endpoint to detect the state of the queues
* WIP on allowing different forms for testing
* If you pass a string to prettyPrintPacket which is json or superjson, safeParse it first
* Test page, deal json and superjson. Started splitting UI for schedules
* WIP on schedule form
* Removed the Label from the DateField
* WIP on test schedule form
* Fix for the runs page showing the wrong message when there are no runs from time filtering
* Removed labels from the DateField
* Fixes for the form
* Test runs are working for schedules
* Fix for nextScheduledTimestamps in triggerScheduledTask
* Implement idempotency key support and fix issue with cancelled runs causing concurrency usage
* Added API documentation for the schedule API
* Remove log
* Removed console log from runs page
* Transform the recent runs test data on the server
* Fix for hydration mismatch
* Current date as the default for the test form
* Recent payloads working
* Delete schedule modal
* Deal with empty strings from the form
* Set the initial value for the scheduled test form
* Add option to print console logs in the dev CLI locally (issue #1014)
* Export queue from the SDK
* Fix for schedules list when you have no schedule tasks
* Blank states improved
* Make task schedules more generic, to support additional schedule generators in the future
* Removed log from maqrs
* Removed “v3/schedules” export from the SDK
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Co-authored-by: Eric Allam <eallam@icloud.com>
Co-authored-by: James Ritchie <james@jamesritchie.co.uk>
* WIP proxy/deploy
* WIP, registry proxy in express working
* A couple of notes, preparing for indexing
* Move the changes to prod-worker into the new file
* Deploy command working with indexing and runs (docker provider only for now)
* Removed ts-expect-error directive
* Fixed build command
Eric Allam