Agentset API

Name: Agentset API
Brand: Agentset API
Availability: InStock

★ Only Publicly Available OpenAPI DocumentAI/MLEmbeddings Searchbearer11 EndpointsREST

For Agents

Build retrieval-augmented generation pipelines: create namespaces, ingest documents, and run semantic search with reranking - without managing a vector store.

Install Jentic One Beta

Connect the Agentset API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Agentset 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://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

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 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 Agentset API.

Provision an isolated namespace per knowledge base or per tenant via POST /v1/namespace

Submit ingest jobs that chunk, embed, and index source documents into a namespace via POST /v1/namespace/{namespaceId}/ingest

Run semantic search with metadata filters and built-in reranking via POST /v1/namespace/{namespaceId}/search

GET STARTED

Start building with Agentset API

Explore with Jentic

View OpenAPI Document

Use Cases

Patterns agents use Agentset API for, with concrete tasks.

★ Customer Support Knowledge Base

Create a namespace per product line, ingest help articles and PDF manuals, then query the namespace from a support chatbot to retrieve grounding chunks. Agentset handles chunking, embeddings, and reranking - the agent only needs to call /v1/namespace/{id}/search with the user query. Suited to teams that want RAG without operating a vector database.

Create a namespace 'support-v1', ingest 200 help articles, then search with query='how do I reset my password' and top_k=5

Internal Document Search for Agents

Index company policies, runbooks, and meeting notes in dedicated namespaces so a Jentic agent can pull grounded answers during longer plans. The agent calls /v1/namespace/{id}/search and feeds the returned chunks into its prompt before responding. This replaces hand-built retrieval pipelines on top of Pinecone or Weaviate.

Search the 'eng-runbooks' namespace for chunks about 'database failover' and feed the top 3 into the model context

Per-Tenant RAG in a SaaS Product

Map each end customer to its own Agentset namespace so a multi-tenant SaaS app can offer search and Q&A over the customer's uploaded documents. The agent provisions a namespace on signup, ingests files as the customer uploads them, and scopes searches by namespace id. This is a faster path than running per-tenant vector indexes in-house.

On user signup, POST /v1/namespace with name=user_id; on each upload, POST an ingest job; on each query, search the user's namespace

Agent Memory and Tool Result Indexing

Use a Jentic-connected agent to write its own intermediate findings and tool results into Agentset, then search that namespace later in long-running plans to recover earlier context. The agent treats Agentset as an external memory store with semantic recall, removing the need to keep all prior steps in the model's context window.

After each tool call, ingest the result as a new document in the 'agent-memory' namespace; before the next step, search the namespace for related prior results

Key Endpoints

11 endpoints — jentic publishes the only available openapi specification for agentset api, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

POST

/v1/namespace

Create a namespace

POST

/v1/namespace/{namespaceId}/ingest

Submit an ingest job

POST

/v1/namespace/{namespaceId}/search

Run semantic search inside a namespace

GET

/v1/namespace/{namespaceId}/document

List indexed documents

DELETE

/v1/namespace/{namespaceId}/document/{documentId}

Remove a document from the index

POST

/v1/namespace

Create a namespace

POST

/v1/namespace/{namespaceId}/ingest

Submit an ingest job

POST

/v1/namespace/{namespaceId}/search

Run semantic search inside a namespace

GET

/v1/namespace/{namespaceId}/document

List indexed documents

DELETE

/v1/namespace/{namespaceId}/document/{documentId}

Remove a document from the index

Why Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Your Agentset bearer token is stored once, encrypted, by your own Jentic One instance and injected as the Authorization header at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'search a knowledge base' or 'ingest documents', and Jentic returns the matching Agentset operation with its input schema, including the namespace path parameter, so the agent calls the right endpoint without browsing the reference docs.

Time to first call

FAQs

Specific to using Agentset API through Jentic.

Why is there no official OpenAPI spec for Agentset API?

Agentset does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Agentset API via structured tooling. It is validated against the live API and kept up to date. Get started with Jentic One, the self-hosted execution layer.

What authentication does the Agentset API use?

Agentset uses HTTP bearer token authentication - pass your token in the Authorization header as 'Bearer <token>'. Through Jentic the token is stored in the credential vault and injected at execution time, so the raw value never enters the agent's context.

Can I run RAG without operating my own vector database with the Agentset API?

Yes. Agentset handles chunking, embeddings, vector storage, and reranking. The agent only calls POST /v1/namespace to create a knowledge base, POST /v1/namespace/{id}/ingest to add documents, and POST /v1/namespace/{id}/search to retrieve relevant chunks.

What are the rate limits for the Agentset API?

Limits depend on the Agentset plan and apply to ingest job throughput and search QPS rather than a single fixed cap. Watch for 429 responses and retry with exponential backoff; long ingest jobs are processed asynchronously and tracked via /v1/namespace/{id}/ingest.

How do I run a semantic search through Jentic?

Use the Jentic search 'search a knowledge base'. Jentic returns POST /v1/namespace/{namespaceId}/search; load its schema, supply the namespace id and your query string, and execute. The response contains ranked chunks with source document references.

Does Agentset support metadata filtering on search?

Yes. The /v1/namespace/{id}/search endpoint accepts filter and rerank options in the request body so the agent can constrain results by document type, source, or other metadata attached at ingest time.

Can I limit what my agent is allowed to do with the Agentset API?

Yes. Because you run Jentic One yourself, your own rules decide which Agentset operations and credentials the agent may use. Agentset puts the namespace id in the URL path (/v1/namespace/{namespaceId}/...), so you can pin the agent to a single namespace and still control which calls it makes. For example, you can allow searching (POST /v1/namespace/{namespaceId}/search) and ingesting documents while leaving document deletion (DELETE /v1/namespace/{namespaceId}/document/{documentId}) off the allowed list.

Agentset API

Connect the Agentset API to your agent

Capabilities

Start building with Agentset API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs