Install Jentic One Beta

Connect the Humanloop API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Humanloop 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.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fhumanloop.com%2Fhumanloop" | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fhumanloop.com%2Fhumanloop" | sh
jentic register       # connects your agent to your Jentic One instance

Jentic 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 Humanloop API.

Create, list, and version prompt files

Call a managed prompt and receive the model generation

Log a generation with its inputs, outputs, and feedback

Manage agents, tools, and flows as versioned files

Run evaluations of a version against a dataset and evaluators

GET STARTED

Start building with Humanloop API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use Humanloop API for, with concrete tasks.

★ Managed Prompt Execution

Rather than hard-coding prompt text in application code, an agent calls POST /prompts/call to run a prompt that is versioned in Humanloop. The prompt template, model settings, and version all live server-side, so a prompt change ships without a code deploy.

Call the checkout-support prompt with the customer message and return the generated reply

Generation Logging and Feedback

After an LLM call, an agent records the interaction with POST /prompts/log so inputs, outputs, and later user feedback are captured against the right prompt version. This builds the dataset that quality metrics and regressions are measured from.

Log the latest support generation with the user's thumbs-up feedback against its prompt

Pre-Ship Prompt Evaluation

Before promoting a new prompt version, an agent starts an evaluation with POST /evaluations to score the candidate against a fixed dataset and a set of evaluators. The scores show whether the change improved quality before any users are exposed to it.

Run an evaluation of the new summarization prompt against the review dataset and report the scores

Workspace Inventory and Cleanup

An operations agent lists the prompt files with GET /prompts to inventory what exists, and prunes stale records with DELETE on /logs. This keeps the workspace tidy and the evaluation corpus focused on relevant traffic.

List all prompts, then delete logs older than the retention window

Key Endpoints

118 endpoints — the humanloop api manages the prompts, agents, and evaluation workflows behind an llm application, and logs every call so teams can measure and improve quality.

METHOD

PATH

DESCRIPTION

GET

/prompts

List prompt files in the workspace

POST

/prompts/call

Call a managed prompt and return the generation

POST

/prompts/log

Log a generation against a prompt

POST

/evaluations

Start an evaluation run

GET

/logs

List logged generations

GET

/prompts

List prompt files in the workspace

POST

/prompts/call

Call a managed prompt and return the generation

POST

/prompts/log

Log a generation against a prompt

POST

/evaluations

Start an evaluation run

GET

/logs

List logged generations

Why Jentic?

What agents get from Jentic-routed access to this vendor.

Setup

Wiring the Humanloop API by hand means setting the `X-API-KEY` header, learning which of its file, log, and evaluation endpoints you need, and handling errors yourself. Through Jentic you install once, import the API from the API Directory, store the key once, and your agent calls prompts, logs, and evaluations.

Permission scoping

Humanloop puts the file id in the URL path, so you can scope by both operation and resource: allow an agent to call and log a specific prompt while withholding file creation, deletion, and evaluation until you add them to the allowed set.

Credential isolation

Your Humanloop API key is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'call a managed prompt' or 'run a prompt evaluation', and Jentic returns the matching Humanloop operation with its input schema so the agent calls the right endpoint.

FAQs

Specific to using Humanloop API through Jentic.

What does the Humanloop API do?

It manages the prompts, agents, tools, and flows behind an LLM application as versioned files, calls them to generate output, logs every generation with its inputs and outputs, and runs evaluations that score a version against a dataset and evaluators.

What authentication does the Humanloop API use?

Requests send an API key in the `X-API-KEY` header. Through Jentic the key is held by your own instance and supplied at execution time, so the agent calls the API without ever reading the raw key.

Can I run a managed prompt through the API?

Yes. POST /prompts/call runs a prompt that is versioned in Humanloop, so the template and model settings live server-side. You then record the result with POST /prompts/log to build up logging and feedback data.

How do I evaluate a prompt before shipping it?

Start an evaluation with POST /evaluations to score a candidate version against a fixed dataset and a set of evaluators. Compare the scores against the current version before you promote the change.

What are the rate limits for the Humanloop API?

The OpenAPI specification does not declare rate limits. Batch evaluation and logging work sensibly and back off on error responses; confirm current limits in the Humanloop documentation for your plan.

Do I need an MCP server to use the Humanloop API with an agent?

You do not. Jentic connects the API to your agent directly from the API Directory: import it, store your key once, and the agent calls prompts, logging, and evaluation operations without a separate server to run.

Can I control which Humanloop operations my agent is allowed to call?

Yes. Because you run Jentic One yourself, you decide the allowed set: an agent can be limited to calling and logging prompts while file creation, deletion, and evaluation stay excluded, and because Humanloop puts the file id in the URL path you can keep the agent to specific prompts.

Humanloop API

Name: Humanloop API
Brand: Humanloop API
Availability: InStock

Official vendor OpenAPI document · agent-readyAI/MLLanguage ModelsapiKey118 EndpointsREST

For Agents

Create and version prompts, agents, tools, and flows on Humanloop, call and log LLM generations, and run evaluations against datasets and evaluators.

Use for: I need to call a managed prompt and get its completion, Log an LLM generation with its inputs and outputs, Create a new version of a prompt on Humanloop, Run an evaluation of a prompt against a dataset

Not supported: Does not host the underlying models or handle billing. Use it to manage prompts, agents, tools, and flows, call and log generations, and run evaluations only.

The Humanloop API manages the prompts, agents, and evaluation workflows behind an LLM application, and logs every call so teams can measure and improve quality. Prompts, agents, tools, and flows are versioned files you create and update through the API, while logs capture each generation with its inputs, outputs, and feedback. Datasets and evaluators let you score versions against fixed inputs, so a change to a prompt can be compared before it ships. Product and ML teams use it to move prompt engineering, logging, and evaluation out of scattered notebooks and into a versioned, testable system.

Jentic One on Github View OpenAPI Document

Connect the Humanloop API to your agent

Capabilities

Start building with Humanloop API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Humanloop API