Install Jentic One Beta

Connect the bitHuman to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the bitHuman, 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%2Fbithuman.ai%2Fbithuman" | 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%2Fbithuman.ai%2Fbithuman" | 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 bitHuman API.

Generate a talking AI avatar agent from a prompt and provider configuration

Make an avatar agent speak a line of text

Render a talking video and poll its job status

Generate gesture animations for an avatar through the dynamics endpoint

Start a WebRTC realtime call with a cloud avatar

GET STARTED

Start building with bitHuman API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use bitHuman API for, with concrete tasks.

★ Agent-driven avatar video

An AI agent turns a script into a talking-avatar video. Through Jentic the agent generates an avatar from a prompt, submits the text through the speak operation, and renders a talking video as a job whose status it polls until the render finishes. This produces a presenter video without a human opening a studio UI.

Generate an avatar from a prompt, make it speak a short script, and poll the video job until it returns a finished talking video

Live avatar sessions

A product embeds a live, conversational avatar. The realtime-connect operation starts a WebRTC session with a cloud avatar, and runtime tokens scope access to one agent, so a browser or app streams a lip-synced avatar in real time rather than rendering a file. Sessions can be listed and terminated when the conversation ends.

Mint a runtime token for one avatar and start a WebRTC realtime session, then end the session when the call finishes

Knowledge-grounded avatars

A support avatar answers from a company's own content. The API ingests files or URLs into a knowledge base and rebuilds it, so the avatar's responses draw on that material. An agent can create the knowledge base, add sources, and trigger a rebuild before putting the avatar live.

Create a knowledge base, ingest a product-docs URL, and rebuild the knowledge base so the avatar answers from it

Key Endpoints

52 endpoints — the bithuman api generates real-time, lip-synced ai avatars that turn audio into talking video, in the cloud, on your own hardware, or in the browser.

METHOD

PATH

DESCRIPTION

POST

/v1/agent/generate

Generate a new avatar agent

POST

/v1/agent/{code}/speak

Make an avatar agent speak

POST

/v1/video/generate

Generate a talking video

GET

/v1/video/{job_id}

Get talking-video status

POST

/v1/dynamics/generate

Generate gesture animations

POST

/v1/realtime/connect

Start or end a WebRTC Realtime call

POST

/v1/knowledge/kbs

Create a knowledge base

POST

/v1/webhooks

Create a webhook

POST

/v1/agent/generate

Generate a new avatar agent

POST

/v1/agent/{code}/speak

Make an avatar agent speak

POST

/v1/video/generate

Generate a talking video

GET

/v1/video/{job_id}

Get talking-video status

POST

/v1/dynamics/generate

Generate gesture animations

POST

/v1/realtime/connect

Start or end a WebRTC Realtime call

POST

/v1/knowledge/kbs

Create a knowledge base

POST

/v1/webhooks

Create a webhook

Why Jentic?

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

Setup

Wiring the bitHuman API by hand means handling its api-secret header auth (self-hosted runtimes send the same secret as a bearer token), polling video and agent-generation jobs for status, and managing runtime and embed tokens yourself. Through Jentic you install once, import it from the API Directory, store the secret once, and your agent calls it.

Permission scoping

The bitHuman API puts the agent code in the URL path (/v1/agent/{code}), so a rule can pin your agent to one bitHuman avatar: it can make that avatar speak and read its sessions without touching account-level api-secret management. You choose the operations it may call, so deleting an avatar or revoking runtime keys is not included unless you add it.

Credential isolation

Your bitHuman api-secret is held 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 'generate a talking avatar' or 'make an avatar speak', and Jentic returns the matching bitHuman operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using bitHuman API through Jentic.

What authentication does the bitHuman API use?

The bitHuman API authenticates with an api-secret sent in the api-secret header per its OpenAPI spec; self-hosted runtimes may send the same secret as a bearer token in the Authorization header. A few endpoints, such as the showcase models and the readiness check, need no credential. Through Jentic the secret is injected at call time by your own Jentic One instance, so it never enters the agent's prompt or logs.

Can I generate a talking video with the bitHuman API?

Yes. The video-generate operation renders a talking video and returns a job id whose status you poll until the render finishes. For live use, the realtime-connect operation starts a WebRTC session with a cloud avatar instead of rendering a file.

What are the rate limits for the bitHuman API?

The OpenAPI spec does not specify rate limits. Check the bitHuman documentation at https://docs.bithuman.ai for current limits and credit pricing before running high-volume renders.

Is there a bitHuman MCP server?

You don't need an MCP server to give your agent the bitHuman API. Jentic connects it directly from the API Directory: import it, store your api-secret once, and your agent calls it, so you skip installing and syncing a separate server.

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

Yes. Write a rule that allows only the speak and video-generate operations for one avatar code, so your agent can produce talking video for that avatar but cannot delete agents or create new api-secrets. Every call it makes is logged.

How do I make an avatar speak with the bitHuman API through Jentic?

Search Jentic for 'make an avatar speak' and it returns the speak operation with its input schema; the agent passes the avatar code and the text, then reads the session or video job it produces. To run it on your own infrastructure, install Jentic One from its GitHub repo.

bitHuman

AI ReadinessAI-Aware (B-)62/100

See full scorecard

Official vendor OpenAPI document · agent-readyMediaVideo ProcessingapiKey, bearer52 EndpointsREST

For Agents

Create talking AI avatars: generate an avatar agent, make it speak, render a talking video, or start a live WebRTC session, plus build knowledge bases and generate gesture animations.

Use for: Generate a talking AI avatar from a prompt, Make my avatar speak a welcome message, Render a talking video and check when it is ready, Start a live WebRTC call with a cloud avatar

Not supported: Does not handle text chat models, video editing, or live-stream distribution. Use for AI avatar generation and real-time avatar sessions only.

The bitHuman API generates real-time, lip-synced AI avatars that turn audio into talking video, in the cloud, on your own hardware, or in the browser. An agent generates an avatar agent from a prompt and provider configuration, makes it speak, renders a talking video as a pollable job, and starts a WebRTC realtime call for live sessions. It also builds knowledge bases for an avatar, generates gesture animations, and manages runtime tokens, webhooks, and API secrets.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: DSignals: 4

81%

Lint Results

Aggregated quality score from linter diagnostics, weighted by severity.

100%

Resolution Completeness

Percentage of `$ref` references that resolve successfully.

Specification Validity

Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).

Structural Integrity

Structural correctness score based on schema issues using logarithmic dampening.

Developer Experience & Jentic Compatibility

Clarity, completeness, and ingestion readiness for developers and tooling.

Grade: A-Signals: 4

30%

Example Density

How richly the API is illustrated with examples.

99%

Example Validity

Percentage of examples that conform to their schemas.

53%

Response Coverage

Percentage of operations with complete response definitions (success, client error, server error).

100%

Tooling Readiness

Health of API ingestion, bundling, and resolution within Jentic pipelines.

AI-Readiness & Agent Experience

Semantic breadth, depth, and agent comprehension for AI systems.

Grade: CSignals: 4

54%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

100%

OperationId Quality

Coverage, uniqueness, and casing consistency of operationIds for AI inference.

59%

Summary Coverage

Coverage of summaries across operations/tags/info.

Agent Usability

Functional utility, complexity comfort, and AI orchestration readiness.

Grade: A+Signals: 1

93%

Complexity Comfort

Agent comfort level based on API operational and structural complexity.

Security

Trust, risk posture, and security compliance.

Grade: CSignals: 1

55%

Authentication Strength

Average quality of security schemes based on authentication method strength (weakest link for OAuth2).

AI Discoverability

Findability, semantic richness, and reasoning readiness.

Grade: A-Signals: 1

79%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the bitHuman to your agent

Capabilities

Start building with bitHuman API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

bitHuman

Jentic AI Readiness Score

bitHuman

Foundational Compliance

Lint Results

Resolution Completeness

Specification Validity

Structural Integrity

Developer Experience & Jentic Compatibility

Example Density

Example Validity

Response Coverage

Tooling Readiness

AI-Readiness & Agent Experience

Description Coverage

Error Standardization

OperationId Quality

Summary Coverage

Agent Usability

Complexity Comfort

Security

Authentication Strength

AI Discoverability

Descriptive Richness