Compare aparté with Loquix, assistant-ui, AI Elements & more (2026)

If you are choosing a chat UI library for an LLM product, the libraries below are the ones you will shortlist. This page says what each is good at and where aparté differs — including the cases where you should pick the other one. Claims about other projects were checked against their public docs in August 2026; they move fast, so verify before deciding.

The short version: aparté is the one that is a complete runtime and framework-agnostic and free of third-party dependencies. The React kits have more components. The other web-component kits are presentational — you bring the loop. If you need neither framework freedom nor a runtime, you have better options than aparté, and they are named below.

The matrix

	aparté	assistant-ui	AI Elements	deep-chat	Loquix	kitn
Frameworks	Web Components + React, Vue, Svelte, Angular wrappers	React	React	Web Component (+ React wrapper)	Web Component (Lit)	Web Component
Runtime included (streaming, agent loop, tool calls)	Yes — core + headless engine	Runtime adapters (AI SDK, LangGraph, …)	Via the Vercel AI SDK	Built in, config-driven	No — presentational	No — presentational
Framework you must adopt	None — and no third-party dependency in @aparte/core	React	React + the AI SDK	None	None (Lit is bundled)	None
Human-in-the-loop: tool approval, typed questions	Approval at the composer, typed elicitation panel	Generic tool UI	Confirmation component	—	Rendered, not run	Rendered, not run
Edit / retry / branch a conversation	Yes, with a version picker	Yes	Partial	—	Partial	—
Persistence	A storage interface you implement	A hosted cloud service (paid)	Your own	—	—	—
Theming	CSS variables, light DOM, no fork	Tailwind / shadcn — fork the markup	shadcn — the code lives in your app	Config object	CSS variables	CSS variables + online editor
Run a model in the browser	Yes — the transformers provider	—	—	Yes (Web LLM)	—	—
Scripted demo/test provider	Yes — the scenario provider (deterministic turns: thinking, tools, artifacts)	—	—	Demo mode (canned)	—	—
Markdown, code, reasoning	Yes (opt-in plugins)	Yes	Yes	Yes	Yes	Yes
Mermaid, KaTeX	—	Yes	Yes	—	—	—
Voice	—	Yes (realtime)	Yes	Yes	—	—
Citations / sources	—	Partial	Yes	—	Yes	—
Floating / modal chat	—	Yes	—	Yes (embed)	Partial	—
Best fit for	Multi-framework teams that want the runtime included	React teams, all-in on React	Apps already on the Vercel AI SDK	A config-driven embed, fast	A polished presentational kit (Lit)	A minimal presentational kit
Licence	MIT	MIT	Apache-2.0	MIT	MIT	MIT

The rows read left to right as what aparté is for: the top half is the runtime, the bottom half is the catalogue. aparté wins the top half and loses the bottom half, and both halves are true.

assistant-ui

The React reference. A composable primitives kit (thread, composer, message, action bar, branch picker, chain of thought, attachments) with the widest set of runtime integrations in the category — the Vercel AI SDK, LangGraph, LangChain, Mastra, AG-UI, A2A and more — plus realtime voice, Mermaid and KaTeX rendering, and a hosted cloud for thread persistence.

Pick assistant-ui when you are on React for good, want its idioms end to end, and want to plug into one of those runtimes rather than run a loop of your own. Its ecosystem is larger than aparté’s and will stay so.

Pick aparté when the same chat has to ship in more than one framework (or none), when you do not want a UI kit to dictate your styling system, or when you want a runtime in the library rather than an adapter to someone else’s. Theming is the other line: assistant-ui is Tailwind/shadcn, so a visual change is a fork of markup; aparté is CSS variables on light DOM, so it is a stylesheet.

Vercel AI Elements

The largest catalogue. Fifty-odd shadcn components — chatbot, code (artifact, file tree, terminal, sandbox, web preview), voice and workflow-graph families — installed by CLI, so the source lands in your app. Requires React and the Vercel AI SDK.

Pick AI Elements when you build on Next.js and the AI SDK and want a finished part for every screen an agent product has. Nobody else has that breadth.

Pick aparté when you are not on React, or when you want the parts to update as a dependency rather than as copied source. One thing to know: AI Elements’ file tree, terminal and test results are app-fed views, not message types — the same conclusion aparté reached when it removed those segment kinds. A tool result rendered richly — generative UI, in the term the field settled on — is the seam both libraries converge on.

deep-chat

The fastest time-to-chat. One <deep-chat> element, configured by attributes and objects, connects directly to twenty-odd vendor APIs, does files, camera, microphone, speech in and out, and can run a model in the browser.

Pick deep-chat when you want one tag and a config object and you are done — it is the best of the category at that, and the only other one that runs a model client-side.

Pick aparté when you need composable parts rather than one element (aparté is a viewport, a composer, bubbles and a status line you place yourself), token-level theming, an agent loop with tool approval, or the same chat in four frameworks with typed wrappers. deep-chat’s customisation is a large config surface; aparté’s is CSS and render hooks.

Loquix

A presentational web-component kit. A few dozen Lit components across reasoning, trust, search and template categories, with accessibility as its headline. By design it ships no provider, no loop and no transport: it is a type-only interface you feed.

Pick Loquix when you already have a chat runtime you like and want a broad, accessible set of views to render its output.

Pick aparté when you want the runtime too. aparté’s core has no third-party dependency (Loquix carries Lit), and its engine runs the agent loop, the tool calls, the approval gate and the conversation compactor — the parts a presentational kit leaves to you. Loquix’s catalogue is wider than aparté’s; its roadmap points at provider integrations, which is the ground aparté already covers.

kitn

The presentational twin. A single custom element that renders tool calls, reasoning traces and typed cards (confirmations, choices, forms) — “you bring the model” is the stated contract. Its theming is its strength: a small token set, dozens of presets and an online theme editor that exports CSS.

Pick kitn when you want a drop-in view over a loop you run elsewhere, and a theme in five minutes.

Pick aparté when the typed cards have to be honoured, not just drawn: aparté’s elicitation pauses the run, collects the answer and resumes it, and the approval step gates a real tool call. kitn draws the same vocabulary without the runtime under it.

OpenAI ChatKit

The platform drop-in. A web component (with a React wrapper) served by the OpenAI platform through a client token — streaming, tools, attachments and chain-of-thought visualisation without writing the front end. Self-hosting goes through their Python SDK.

Pick ChatKit when you build on the OpenAI platform and want their hosted chat experience with the least code.

Pick aparté when the model is not OpenAI’s, when the key must stay yours (browser-direct BYOK or your own endpoint), when a model runs locally, or when you need theming beyond what a hosted surface exposes. The lock-in there is the vendor; aparté’s transport is the seam that keeps it out.

Also in the field

• CopilotKit — a category above: app-state sync with agents, generative UI, LangGraph co-agents. Not a chat component; if that is what you need, aparté is not it.
• NLUX — React and vanilla, with a modified MPL licence to read before adopting.
• TanStack AI — type-safe, framework-agnostic hooks with no UI (alpha). Closer to aparté’s engine than to its components.
• Chainlit — Python full-stack; a different stack entirely.

How to read this page

aparté is alpha (0.x, released in lockstep, renames land as renames — see Why aparté). The comparison is written against that version; the catalogue rows will change as components land, and the runtime rows are the ones that define the project. If a claim above is wrong or out of date, open an issue — a comparison that flatters the author is worth nothing to the reader.