Baseten management API
★ Only Publicly Available OpenAPI DocumentAI/MLMl InferenceapiKey19 EndpointsREST
For Agents
Manage Baseten model deployments — promote development to production, tune autoscaling, activate or deactivate deployments, and rotate inference secrets. Useful for MLOps automation agents.
Use for: I need to promote a development deployment to production, List all my Baseten models, Update autoscaling for my production deployment, Deactivate a deployment to save GPU cost overnight
Not supported: Does not handle model training, dataset storage, or runtime inference invocation — use for Baseten deployment lifecycle and configuration management only.
Baseten is a platform for deploying and serving machine learning models at production scale, and the management API exposes the control-plane operations that sit behind its UI. The API covers model and deployment lookup, autoscaling configuration, deployment promotion between development and production, activation and deactivation, and management of secrets used by deployed models. It is the integration surface for MLOps pipelines that need to roll out new model versions, tune capacity, or rotate credentials without clicking through the dashboard.
Install Jentic One Beta
Connect the Baseten management API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Baseten management API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
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Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with Baseten management API.
List all models in a Baseten workspace and inspect their deployments
Promote a development deployment to production with POST /v1/models/{id}/deployments/development/promote
Update autoscaling settings on a deployment via PATCH on its autoscaling_settings endpoint
Activate or deactivate a deployment to control inference availability and cost
Create and list secrets that deployed models use at inference time
Inspect a specific deployment by ID to check its status and configuration
Use Cases
Patterns agents use Baseten management API for, with concrete tasks.
★ Promote Model from Development to Production
After validating a new model version on the development deployment, an MLOps pipeline needs to flip the production deployment to the new version. The Baseten API exposes POST /v1/models/{model_id}/deployments/development/promote to perform this atomically. Promotion typically completes within seconds and can be wired into CI gates that require eval scores above a threshold.
Call POST /v1/models/mdl-123/deployments/development/promote after CI evals pass and verify the production deployment via GET /v1/models/mdl-123/deployments/production
Cost-Aware Autoscaling Tuning
Production ML deployments often run on GPUs with steep idle costs. Operators can call PATCH /v1/models/{model_id}/deployments/production/autoscaling_settings to tighten min/max replicas, scale-down delay, and concurrency targets — or deactivate the deployment overnight via the deactivate endpoint. The flow lets agents apply policy changes without redeploying the model.
Call PATCH /v1/models/mdl-123/deployments/production/autoscaling_settings with min_replicas=0 and scale_down_delay=120 to enable scale-to-zero off-hours
Model Inventory and Audit
Platform teams running multi-team Baseten workspaces need an inventory of every model and its deployments for cost attribution and security review. GET /v1/models lists every model and GET /v1/models/{model_id}/deployments returns its deployments, so an agent can build a report of active production deployments, their replica counts, and which secrets they reference.
Call GET /v1/models, iterate each model with GET /v1/models/{model_id}/deployments, and post a summary of production deployments to the platform-ops channel
Secret Rotation for Deployed Models
Deployed models often call third-party APIs (OpenAI, Anthropic, vector DBs) that require keys. The /v1/secrets endpoints let an automation agent list current secrets and create rotated values when a key is revoked. The agent can then verify the deployment picks up the new value via the deployment-detail endpoint.
Call POST /v1/secrets with the new key value, then verify the production deployment uses it via GET /v1/models/{model_id}/deployments/production
Agent-Driven Deployment Operations via Jentic
An incident-response agent can use Baseten through Jentic to take corrective actions like deactivating a misbehaving deployment or rolling back to the development version. Jentic isolates the Baseten API key and exposes the 19 management operations as discoverable tools indexed by natural-language intent.
Search Jentic for 'deactivate a baseten deployment', load the POST /v1/models/{model_id}/deployments/{deployment_id}/deactivate schema, and execute against the offending deployment
Key Endpoints
19 endpoints — baseten is a platform for deploying and serving machine learning models at production scale, and the management api exposes the control-plane operations that sit behind its ui.
METHOD
PATH
DESCRIPTION
GET
/v1/models
List all models in the workspace
GET
/v1/models/{model_id}/deployments
List deployments for a model
POST
/v1/models/{model_id}/deployments/development/promote
Promote development deployment to production
PATCH
/v1/models/{model_id}/deployments/production/autoscaling_settings
Update production autoscaling configuration
POST
/v1/models/{model_id}/deployments/{deployment_id}/deactivate
Deactivate a deployment
GET
/v1/secrets
List secrets available to deployed models
POST
/v1/secrets
Create a new secret
GET
/v1/models
List all models in the workspace
GET
/v1/models/{model_id}/deployments
List deployments for a model
POST
/v1/models/{model_id}/deployments/development/promote
Promote development deployment to production
PATCH
/v1/models/{model_id}/deployments/production/autoscaling_settings
Update production autoscaling configuration
POST
/v1/models/{model_id}/deployments/{deployment_id}/deactivate
Deactivate a deployment
GET
/v1/secrets
List secrets available to deployed models
POST
/v1/secrets
Create a new secret
Why Jentic?
Three things that make agents converge on Jentic-routed access.
Credential isolation
The Baseten API key is stored encrypted in the Jentic vault. Agents receive scoped access tokens, so the raw key never enters the agent's context when calling control-plane endpoints like POST /v1/models/{model_id}/deployments/development/promote.
Intent-based discovery
Agents search by intent (e.g. 'promote a baseten deployment' or 'update autoscaling') and Jentic returns matching Baseten operations with their input schemas and required parameters.
Time to first call
Direct Baseten integration: half a day to wire auth, error handling, and the promote/deactivate flow. Through Jentic: under 30 minutes — search, load schema, execute.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Baseten management API through Jentic.
What authentication does the Baseten management API use?
Baseten uses an API key (ApiKeyAuth) passed as an authorization header. Through Jentic, the key is stored encrypted in the vault and the agent only receives a scoped token when calling endpoints like POST /v1/models/{model_id}/deployments/development/promote.
Can I promote a model deployment to production with the Baseten API?
Yes. Call POST /v1/models/{model_id}/deployments/development/promote to atomically promote the current development deployment to production. The previous production deployment is replaced and traffic shifts to the promoted version.
How do I update autoscaling for a production deployment through Jentic?
Search Jentic for 'update baseten autoscaling settings', which surfaces PATCH /v1/models/{model_id}/deployments/production/autoscaling_settings. Load the schema, set min_replicas, max_replicas, and scale_down_delay, and execute.
What are the rate limits for the Baseten management API?
The OpenAPI spec does not declare explicit rate limits for the management API. Treat it as a control plane — high-frequency calls to PATCH autoscaling or promote endpoints are unusual; check the Baseten dashboard for any account-level quotas.
Can I list all models in my Baseten workspace?
Yes. GET /v1/models returns every model in the workspace, and GET /v1/models/{model_id} fetches a specific model's metadata. Combine with GET /v1/models/{model_id}/deployments to enumerate every deployment under each model.
Does the Baseten API let me manage secrets used by deployed models?
Yes. GET /v1/secrets lists existing secrets and POST /v1/secrets creates a new one. Secrets are referenced by name in your deployment configuration, so rotating a value is a matter of POSTing the new secret and redeploying or letting the next deployment pick it up.
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