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Copy file name to clipboardExpand all lines: docs/guides/example-projects/batch-llm-evaluator.mdx
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@@ -39,11 +39,11 @@ This demo is a full stack example that uses the following:
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- View the Trigger.dev task code in the [src/trigger/batch.ts](https://github.com/triggerdotdev/examples/blob/main/batch-llm-evaluator/src/trigger/batch.ts) file.
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- The `evaluateModels` task uses the `batch.triggerByTaskAndWait` method to distribute the task to the different LLM models.
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- It then passes the results through to a `summarizeEvals` task that calculates some dummy "tags" for each LLM response.
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- We use a [useRealtimeRunsWithTag](https://trigger.dev/docs/frontend/react-hooks/realtime#userealtimerunswithtag) hook to subscribe to the different evaluation tasks runs in the [src/components/llm-evaluator.tsx](https://github.com/triggerdotdev/examples/blob/main/batch-llm-evaluator/src/components/llm-evaluator.tsx) file.
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- We use a [useRealtimeRunsWithTag](/realtime/react-hooks/realtime#userealtimerunswithtag) hook to subscribe to the different evaluation tasks runs in the [src/components/llm-evaluator.tsx](https://github.com/triggerdotdev/examples/blob/main/batch-llm-evaluator/src/components/llm-evaluator.tsx) file.
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- We then pass the relevant run down into three different components for the different models:
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- The `AnthropicEval` component: [src/components/evals/Anthropic.tsx](https://github.com/triggerdotdev/examples/blob/main/batch-llm-evaluator/src/components/evals/Anthropic.tsx)
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- The `XAIEval` component: [src/components/evals/XAI.tsx](https://github.com/triggerdotdev/examples/blob/main/batch-llm-evaluator/src/components/evals/XAI.tsx)
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- The `OpenAIEval` component: [src/components/evals/OpenAI.tsx](https://github.com/triggerdotdev/examples/blob/main/batch-llm-evaluator/src/components/evals/OpenAI.tsx)
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- Each of these components then uses [useRealtimeRunWithStreams](https://trigger.dev/docs/frontend/react-hooks/realtime#userealtimerunwithstreams) to subscribe to the different LLM responses.
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- Each of these components then uses [useRealtimeRunWithStreams](/realtime/react-hooks/streams) to subscribe to the different LLM responses.
While the workflow in this example is static and does not allow changing the connections between nodes in the UI, it serves as a good baseline for understanding how to build completely custom workflow builders using Trigger.dev and ReactFlow.
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## Learn more about Trigger.dev Realtime and waitpoint tokens
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To learn more, take a look at the following resources:
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-[Trigger.dev Realtime](/realtime) - learn more about how to subscribe to runs and get real-time updates
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-[Realtime streaming](/realtime/streams) - learn more about streaming data from your tasks
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-[React hooks](/frontend/react-hooks) - learn more about using React hooks to interact with the Trigger.dev API
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-[Realtime streaming](/realtime/react-hooks/streams) - learn more about streaming data from your tasks
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-[React hooks](/realtime/react-hooks) - learn more about using React hooks to interact with the Trigger.dev API
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-[Waitpoint tokens](/wait-for-token) - learn about waitpoint tokens in Trigger.dev and human-in-the-loop flows
### Using Trigger.dev Realtime to trigger and subscribe to the deep research task
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We use the [`useRealtimeTaskTrigger`](/frontend/react-hooks/triggering#userealtimetasktrigger) React hook to trigger the `deep-research` task and subscribe to it's updates.
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We use the [`useRealtimeTaskTrigger`](/realtime/react-hooks/triggering#userealtimetasktrigger) React hook to trigger the `deep-research` task and subscribe to it's updates.
Copy file name to clipboardExpand all lines: docs/guides/example-projects/vercel-ai-sdk-image-generator.mdx
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This demo is a full stack example that uses the following:
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- A [Next.js](https://nextjs.org/) app using [shadcn](https://ui.shadcn.com/) for the UI
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- Our 'useRealtimeRun' [React hook](https://trigger.dev/docs/frontend/react-hooks/realtime) to subscribe to the run and show updates on the frontend
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- Our 'useRealtimeRun' [React hook](/realtime/react-hooks/realtime) to subscribe to the run and show updates on the frontend
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- The [Vercel AI SDK](https://sdk.vercel.ai/docs/introduction) to [generate images](https://sdk.vercel.ai/docs/ai-sdk-core/image-generation) using OpenAI's DALL-E models
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## GitHub repo
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## Relevant code
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- View the Trigger.dev task code which generates the image using the Vercel AI SDK in [src/trigger/realtime-generate-image.ts](https://github.com/triggerdotdev/examples/tree/main/vercel-ai-sdk-image-generator/src/trigger/realtime-generate-image.ts).
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- We use a [useRealtimeRun](https://trigger.dev/docs/frontend/react-hooks/realtime#userealtimerun) hook to subscribe to the run in [src/app/processing/[id]/ProcessingContent.tsx](https://github.com/triggerdotdev/examples/tree/main/vercel-ai-sdk-image-generator/src/app/processing/[id]/ProcessingContent.tsx).
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- We use a [useRealtimeRun](/realtime/react-hooks/realtime#userealtimerun) hook to subscribe to the run in [src/app/processing/[id]/ProcessingContent.tsx](https://github.com/triggerdotdev/examples/tree/main/vercel-ai-sdk-image-generator/src/app/processing/[id]/ProcessingContent.tsx).
Trigger.dev is an open source background jobs framework that lets you write reliable workflows in plain async code. Run long-running AI tasks, handle complex background jobs, and build AI agents with built-in queuing, automatic retries, and real-time monitoring. No timeouts, elastic scaling, and zero infrastructure management required.
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We provide everything you need to build and manage background tasks: a CLI and SDK for writing tasks in your existing codebase, support for both [regular](/tasks/overview) and [scheduled](/tasks/scheduled) tasks, full observability through our dashboard, and a [Realtime API](/realtime) with [React hooks](/frontend/react-hooks#realtime-hooks) for showing task status in your frontend. You can use [Trigger.dev Cloud](https://cloud.trigger.dev) or [self-host](/open-source-self-hosting) on your own infrastructure.
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We provide everything you need to build and manage background tasks: a CLI and SDK for writing tasks in your existing codebase, support for both [regular](/tasks/overview) and [scheduled](/tasks/scheduled) tasks, full observability through our dashboard, and a [Realtime API](/realtime) with [React hooks](/realtime/react-hooks#realtime-hooks) for showing task status in your frontend. You can use [Trigger.dev Cloud](https://cloud.trigger.dev) or [self-host](/open-source-self-hosting) on your own infrastructure.
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## Learn the concepts
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Runs are the instances of tasks that are executed. Learn how they work.
Copy file name to clipboardExpand all lines: docs/runs/metadata.mdx
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### stream
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Capture a stream of values and make the stream available when using Realtime. See our [Realtime streams](/realtime/streams) documentation for more information.
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Capture a stream of values and make the stream available when using Realtime. See our [Realtime streams](/realtime/react-hooks/streams) documentation for more information.
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