Changelog

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All workflow endpoints are documented on api.eachlabs.ai

• Every documented workflow REST endpoint now lives on https://api.eachlabs.ai/v1, including get workflow, update workflow, and the public workflow read and trigger routes.
• Update Workflow accepts name only. The previously documented description, locked, and production fields were never honored; categories worked on the legacy host but is no longer updatable through this endpoint and is ignored if sent. A rename regenerates the workflow slug.
• The public workflow trigger returns {"execution_id": "...", "status": "queued"} on 202. The started_at field the docs claimed was never returned.
• The categories endpoint is no longer documented.
• workflows.eachlabs.run keeps serving existing callers unchanged — this is a documentation move, not a breaking change.

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Video API documentation is now public

• The Video API documentation is now listed in the navigation under each::video: overview, quickstart, capabilities reference, billing and limits, MCP setup, and the acceptable-use, takedown, and versioning policies.
• The API is in beta. It runs on https://api.eachlabs.ai as model eachlabs-video-api, covering transcoding, trimming, captions, packaging, and analysis capabilities.
• The OpenAPI reference for the submit, poll, and cancel endpoints is published alongside the guides.

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See the requested LLM in Run History

• Run History now shows the requested LLM beneath eachlabs-llm-router in both table and preview modes.
• Routed runs are easier to distinguish without opening each execution.
• API clients can read the same value from requested_model in GET /v1/executions; non-router executions return null.

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One authentication scheme and base URL across eachlabs APIs

• Authorization: Bearer YOUR_API_KEY is now the documented authentication method for all eachlabs APIs.
• Workflow create, trigger, bulk-trigger, and execution endpoints are now documented on https://api.eachlabs.ai. workflows.eachlabs.run remains supported for workflow management endpoints.

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Transcribe audio files and stream speech

• The LLM Router adds two OpenAI-compatible audio endpoints: POST /v1/audio/transcriptions for file transcription and POST /v1/audio/speech for progressively streamed text-to-speech.
• Transcription accepts files up to 25 MB — FLAC, MP3, MP4/M4A, OGG, WAV, or WebM — and returns json or verbose_json with optional word and segment timestamps. It answers in one response, with no prediction polling.
• Speech returns raw MP3 or PCM bytes as synthesis progresses, so playback can start before the full clip is ready.
• Both use the same API key and base URL as chat completions, so the OpenAI SDK works with a base URL change alone.

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Media uploads handle generic image MIME types more reliably

• File inputs can now detect supported image types from the file bytes when an origin serves a valid image as application/octet-stream.
• This fixes valid customer images being rejected by compatible image-edit models.

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Faster, fresher execution history and error analytics

• Run History and Error Analytics now use the same higher-capacity execution data path, keeping large workspaces responsive as their history grows.
• Error Analytics combines hourly summaries with the latest runs, so recent failures appear without waiting for the next full aggregation window.

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Browse supported LLMs from the console

• Signed-in users can now explore the live LLM Router catalog without leaving the console.
• Search and filter the available models, compare their capabilities, then open one preselected in the playground to start testing it immediately.

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Model pricing pages load reliably across pricing formats

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Prediction statuses now match everywhere

• The generated API schema now uses the same prediction status values as production responses, including error for failed predictions.
• Generated clients can handle terminal failures and cancellation responses without translating between conflicting status names.

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Cloned workflows start cleanly at version 1

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Build workflows with up to 40 parallel branches

• A parallel step can now contain up to 40 branches, up from 10, for wider fan-out workloads in a single workflow.
• The editor keeps large parallel steps readable with a scrollable branch list, cleaner connections, and zoom that fits very wide flows.

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See exactly what happened in a workflow run

• Workflow history now includes a builder-like flow diagram with live status updates and clear per-step inputs, outputs, errors, duration, and cost.
• Failed runs surface their error at the relevant step, and parallel workflows show the final merged output instead of an intermediate branch.
• You can switch between the new visual inspector and the classic detail view at any time.

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Top up without leaving your run

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Find current pricing for every public model

• The pricing directory now loads current public model prices from the live catalog.
• Search by model, filter by modality, sort by popularity, release date, name, or price, and inspect tiered pricing without opening each model page.

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Move from analytics to the exact runs behind them

• Request counts in Usage Analytics now open Run History already filtered to the relevant model while preserving your date range and API-key filter.
• The Webhooks page gained consistent filters, clearer status indicators, and more readable delivery details for faster investigation.

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Compare models and every output side by side

• Model Comparison now offers responsive result grids, a full-screen compare view, thumbnails, keyboard navigation, and direct downloads.
• Multi-output models display every generated result instead of showing only the first one.

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Filter your executions by error type

• GET /v1/executions now accepts an error_classification query parameter, so you can narrow a listing to just the executions that failed for a specific reason — for example provider_rate_limit or content_moderation.
• Pass a comma-separated list to match any of several types (e.g. error_classification=provider_rate_limit,provider_unavailable); an unrecognized value returns a 400 so typos surface immediately.
• The canonical values are content_moderation, execution_timeout, invalid_user_input, invalid_model_config, provider_auth, provider_error, provider_rate_limit, provider_unavailable, internal_error, and unknown.

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Filter your files by model

• The storage page now lets you filter your files by the model that generated them, so you can pull up everything a given model produced in one view.
• You can also filter by source — separate the files you uploaded via the API from the outputs each::labs auto-saved from your executions.
• These join the existing date-range, execution, and file-type filters on the same page.

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See whether a model’s error rate is normal, or just yours

• Error Analytics now lets you filter to a single model and see your workspace’s error rate for it next to the each::labs platform-wide average for the same model, so you can tell at a glance whether a failure spike is something on your side or the model itself.
• The comparison is color-coded — green when you’re beating the platform average, red when you’re worse — and the benchmark window is labeled so you know what it’s averaged over.
• The page also gained quality-of-life upgrades alongside it: sortable columns, CSV export, error-type tooltips, and a “Yesterday” quick range.

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Set how long an uploaded file is kept

• When you upload a file you can now pass expires_in_seconds to control how long it’s retained. Once that window passes the file is removed automatically, so there’s no manual cleanup to schedule.
• Leave it out and files keep the default retention, so nothing changes for existing integrations.
• An expired file drops out of list, download, and storage totals exactly like a manual delete, and is purged from the CDN.

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Create workflows straight from the API

• You can now create a workflow programmatically with POST /v1/workflows/create (API-key auth), so a whole pipeline can be provisioned from code instead of only being assembled by hand in the dashboard.
• It’s the same workflow object either way: anything you create over the API shows up in the dashboard and runs through the existing trigger flow.
• This is the first half of full workflow management over the API — create now, with more lifecycle operations to follow.

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A new Error Analytics view shows why your executions fail

• The dashboard now has an Error Analytics page that surfaces your workspace’s error rate and breaks failures down by type, so you can see at a glance what’s going wrong instead of opening runs one at a time.
• Failures are also broken down per model, so you can tell which model is driving your errors.
• It builds on the clearer, provider-side failure messages shipped earlier, now aggregated into rates you can actually act on.

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Every model now ships an OpenAPI schema

• Every model exposes an OpenAPI 3.0 schema at GET /v1/models/{slug}/schemas/openapi, and its inputs and outputs render as a typed reference in the model page’s API tab.
• The machine-readable schema plugs straight into code generators, validators, and API explorers, while the same schema drives the human-readable reference (types, required flags, defaults, enum values, ranges).
• Coverage is automatic and always in sync: both the endpoint and the API tab are derived from each model’s request schema, so there’s nothing to author or maintain per model.

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Delete an uploaded file over the API

• API customers can now delete an uploaded file with DELETE /v1/files/:id (API-key auth, returns 204). Files uploaded through the presign flow had no delete path before, so once stored there was no way to remove the object or its record. This closes that gap for storage cleanup and data-deletion or privacy requests.
• A delete removes the S3 object and soft-deletes the record, so the file drops out of list, download, and storage totals immediately.
• Deletes are org-scoped: callers can only delete files their own org owns.

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New image models in the catalog

• MAI-Image-2.5 Edit is now available for image editing, through both the API and the dashboard.
• Ideogram v4 is available too, with a rendering-speed selector so you can trade quality against latency on each run.

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Your API key can no longer leak from the browser

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Keys are owned by the organization, so they survive people coming and going

• Keys belong to the organization, not the person who created them. So when a teammate leaves, their keys keep working and your integrations don’t break.
• Any API Key Manager or the organization’s primary Owner can delete any of the org’s keys: one place of control, no orphaned keys.
• Every key records who created it, for audit and accountability.
• A new “Can manage API keys” permission (shown as “API key access” in the UI) controls who can create and delete keys, and only that. It doesn’t touch billing, model access, or whether existing keys work.
• Removing that permission from someone never breaks their existing keys. They keep working; the person just can no longer create or delete keys.
• A Manager manages all of the org’s keys; there’s no per-key granularity today.

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You hold your key, we don’t, so copy it when you create it

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You can finally tell dashboard runs apart from API runs

• Executions, usage, and per-model request history now filter by source (Dashboard vs API), by specific key, and by teammate, so you can attribute every run and every dollar of spend to the right key or person. You can even recover history from keys that were later deleted. This came straight from customer feedback.
• The selected view is deep-linkable, so you can share a URL that lands on exactly the breakdown you’re looking at.
• Reported usage is more accurate: internal dashboard traffic no longer inflates your API usage totals.

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Keys are recognizable at a glance: they start with smk_

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New accounts start clean, no confusing unused key

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Faster model browsing

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A home for all your files

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Clearer failure messages