Eric Allam
07a0e4ade9
## 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" />
Build and deploy fully‑managed AI agents and workflows
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About Trigger.dev
Trigger.dev is the open-source platform for building AI workflows in TypeScript. Long-running tasks with retries, queues, observability, and elastic scaling.
The platform designed for building AI agents
Build AI agents using all the frameworks, services and LLMs you're used to, deploy them to Trigger.dev and get durable, long-running tasks with retries, queues, observability, and elastic scaling out of the box.
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Long-running without timeouts: Execute your tasks with absolutely no timeouts, unlike AWS Lambda, Vercel, and other serverless platforms.
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Durability, retries & queues: Build rock solid agents and AI applications using our durable tasks, retries, queues and idempotency.
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True runtime freedom: Customize your deployed tasks with system packages – run browsers, Python scripts, FFmpeg and more.
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Human-in-the-loop: Programmatically pause your tasks until a human can approve, reject or give feedback.
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Realtime apps & streaming: Move your background jobs to the foreground by subscribing to runs or streaming AI responses to your app.
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Observability & monitoring: Each run has full tracing and logs. Configure error alerts to catch bugs fast.
Key features:
- JavaScript and TypeScript SDK - Build background tasks using familiar programming models
- Long-running tasks - Handle resource-heavy tasks without timeouts
- Durable cron schedules - Create and attach recurring schedules of up to a year
- Trigger.dev Realtime - Trigger, subscribe to, and get real-time updates for runs, with LLM streaming support
- Build extensions - Hook directly into the build system and customize the build process. Run Python scripts, FFmpeg, browsers, and more.
- React hooks - Interact with the Trigger.dev API on your frontend using our React hooks package
- Batch triggering - Use batchTrigger() to initiate multiple runs of a task with custom payloads and options
- Structured inputs / outputs - Define precise data schemas for your tasks with runtime payload validation
- Waits - Add waits to your tasks to pause execution for a specified duration
- Preview branches - Create isolated environments for testing and development. Integrates with Vercel and git workflows
- Waitpoints - Add human-in-the-loop judgment at critical decision points without disrupting workflow
- Concurrency & queues - Set concurrency rules to manage how multiple tasks execute
- Multiple environments - Support for DEV, PREVIEW, STAGING, and PROD environments
- No infrastructure to manage - Auto-scaling infrastructure that eliminates timeouts and server management
- Automatic retries - If your task encounters an uncaught error, we automatically attempt to run it again
- Checkpointing - Tasks are inherently durable, thanks to our checkpointing feature
- Versioning - Atomic versioning allows you to deploy new versions without affecting running tasks
- Machines - Configure the number of vCPUs and GBs of RAM you want the task to use
- Observability & monitoring - Monitor every aspect of your tasks' performance with comprehensive logging and visualization tools
- Logging & tracing - Comprehensive logging and tracing for all your tasks
- Tags - Attach up to ten tags to each run, allowing you to filter via the dashboard, realtime, and the SDK
- Run metadata - Attach metadata to runs which updates as the run progresses and is available to use in your frontend for live updates
- Bulk actions - Perform actions on multiple runs simultaneously, including replaying and cancelling
- Real-time alerts - Choose your preferred notification method for run failures and deployments
Write tasks in your codebase
Create tasks where they belong: in your codebase. Version control, localhost, test and review like you're already used to.
import { task } from "@trigger.dev/sdk";
//1. You need to export each task
export const helloWorld = task({
//2. Use a unique id for each task
id: "hello-world",
//3. The run function is the main function of the task
run: async (payload: { message: string }) => {
//4. You can write code that runs for a long time here, there are no timeouts
console.log(payload.message);
},
});
Deployment
Use our SDK to write tasks in your codebase. There's no infrastructure to manage, your tasks automatically scale and connect to our cloud. Or you can always self-host.
Environments
We support Development, Staging, Preview, and Production environments, allowing you to test your tasks before deploying them to production.
Full visibility of every job run
View every task in every run so you can tell exactly what happened. We provide a full trace view of every task run so you can see what happened at every step.
Getting started
The quickest way to get started is to create an account and project in our web app, and follow the instructions in the onboarding. Build and deploy your first task in minutes.
Useful links:
- Quick start - get up and running in minutes
- How it works - understand how Trigger.dev works under the hood
- Guides and examples - walk-through guides and code examples for popular frameworks and use cases
Self-hosting
If you prefer to self-host Trigger.dev, you can follow our self-hosting guides:
- Docker self-hosting guide - use Docker Compose to spin up a Trigger.dev instance
- Kubernetes self-hosting guide - use our official Helm chart to deploy Trigger.dev to your Kubernetes cluster
Support and community
We have a large active community in our official Discord server for support, including a dedicated channel for self-hosting.
Development
To setup and develop locally or contribute to the open source project, follow our development guide.