ToolSift
Report No. 026MAY 18, 2026

Best AI Tools for Video in 2026: Open-Source Frameworks, Automation & Agents

The top AI video tools trending on GitHub in 2026 — covering programmatic video generation, short-form automation, background removal, and realtime agent frameworks.

AI for video
pillar
HyperFrames / ShortGPT / BackgroundRemover / LiveKit Agents / TEN Framework
Fig 01: Best AI Tools for Video in 2026: Open-So...MAY 2026

The Analysis

AI video tooling has split into two distinct camps in 2026: polished SaaS platforms aimed at creators, and a fast-growing ecosystem of open-source frameworks built for developers and agents. The latter is where momentum currently lives. The five tools below are the most-starred AI video repositories on GitHub as of May 2026 — all actively maintained, all shipping real capabilities.

Best AI Video Tools: Quick Picks by Use Case

Use CaseBest ToolGitHub Stars
Programmatic / agent-driven video renderingHyperFrames19,306
Short-form social video automationShortGPT7,333
Background removal from videoBackgroundRemover7,878
Realtime video & voice AI agentsLiveKit Agents10,525
Conversational voice/video agentsTEN Framework10,589

1. HyperFrames — Write HTML, Render Video

GitHub: heygen-com/hyperframes · 19,306 stars · Updated 2026-05-18

HyperFrames is the most-watched AI video repository on GitHub right now by a significant margin. Developed by HeyGen, its pitch is deceptively simple: write HTML, render video. The framework is explicitly described as "built for agents," meaning it is designed to be driven programmatically — by LLM pipelines, automation workflows, or other software — rather than requiring a human to sit in front of a timeline editor.

What it does

HyperFrames treats video frames as HTML documents. You define layout, text, images, and animations using web standards, and the framework handles the rendering pipeline to produce video output. This makes it straightforward to template dynamic content — product demos, personalized outreach clips, data-driven reports — without manual editing per variant.

Who it's for

  • Developers building agentic workflows that need a video output step
  • Teams producing high volumes of templated video (e.g., personalized sales outreach, automated social content)
  • Anyone already comfortable with HTML/CSS who wants to skip learning a video editing API

Pros and Cons

Pros

  • Uses web standards (HTML/CSS) — low learning curve for frontend developers
  • Purpose-built for agent integration, not retrofitted
  • Backed by HeyGen's production infrastructure experience
  • Fastest-growing AI video repo on GitHub in May 2026

Cons

  • Relatively new (still accumulating ecosystem maturity)
  • Focused on structured/templated video — not suited for generative or live-action footage

2. TEN Framework — Conversational Voice AI Agents

GitHub: TEN-framework/ten-framework · 10,589 stars · Updated 2026-05-18

The TEN Framework is an open-source platform for building conversational voice AI agents. While primarily voice-focused, its architecture supports multimodal agent pipelines that include video channels — making it relevant for anyone building interactive video agent experiences, virtual assistants with a visual component, or real-time presentation bots.

What it does

TEN provides the runtime and tooling to compose AI agents that converse over audio and video streams. It abstracts the low-level plumbing of real-time media handling so developers can focus on agent logic and conversation design.

Who it's for

  • Developers building interactive AI avatars or virtual assistants
  • Teams adding conversational AI to video conferencing or streaming products
  • Researchers prototyping multimodal agent pipelines

Pros and Cons

Pros

  • Open-source with strong community traction (10.5k+ stars)
  • Handles the hard parts of real-time media in agent contexts
  • Actively maintained as of May 2026

Cons

  • Primarily a framework — requires integration work, not a turnkey product
  • Documentation and ecosystem still maturing relative to commercial alternatives

3. LiveKit Agents — Realtime Voice and Video AI

GitHub: livekit/agents · 10,525 stars · Updated 2026-05-18

LiveKit Agents is a framework for building realtime voice and video AI agents. LiveKit is a well-established open-source WebRTC infrastructure project, and its agents library extends that foundation with first-class support for AI-powered participants — bots that can speak, listen, see, and respond in real time inside a live video session.

What it does

The framework lets you build AI agents that join live rooms alongside human participants. Agents can process audio and video streams, respond with synthesized speech, and interact with participants in real time. Common applications include AI meeting assistants, live coaching bots, and automated video moderation.

Who it's for

  • Developers building AI participants for video calls or live streams
  • Teams adding real-time AI features to telehealth, education, or customer support products
  • Anyone building on top of LiveKit's existing WebRTC infrastructure

Pros and Cons

Pros

  • Built on LiveKit's proven, production-grade WebRTC stack
  • Real-time performance is a first-class design goal
  • Active development and strong open-source community
  • Supports both voice and video modalities

Cons

  • Requires familiarity with LiveKit's broader ecosystem for full deployment
  • Real-time infrastructure adds operational complexity versus batch processing approaches

4. BackgroundRemover — AI Background Removal for Video

GitHub: nadermx/backgroundremover · 7,878 stars · Updated 2026-05-17

BackgroundRemover is a free, open-source tool that removes backgrounds from both images and video using AI. It ships with a command-line interface, making it easy to integrate into existing pipelines without building a GUI or calling a paid API.

What it does

Given a video file, BackgroundRemover segments the foreground subject from the background on a per-frame basis and outputs a version of the video with the background removed or replaced. The CLI interface means it can be scripted, batched, and integrated into automated workflows straightforwardly.

Who it's for

  • Video creators who want background removal without a subscription to a SaaS editor
  • Developers building automated video processing pipelines
  • Anyone who needs a self-hostable, privacy-preserving alternative to cloud-based background removal

Pros and Cons

Pros

  • Free and open-source — no API costs or usage limits
  • CLI-first design makes automation easy
  • Handles both images and video in one tool
  • Self-hostable for privacy-sensitive workloads

Cons

  • Processing speed depends on local hardware (GPU strongly recommended for video)
  • No GUI — requires comfort with the command line
  • Quality may trail specialized commercial offerings on complex footage

5. ShortGPT — YouTube Shorts and TikTok Automation

GitHub: RayVentura/ShortGPT · 7,333 stars · Updated 2026-05-18

ShortGPT is an experimental AI framework for automating the creation of short-form video content — specifically YouTube Shorts and TikTok-style clips. It handles the pipeline from script generation through to finished video, reducing a multi-step manual process to a single automated workflow.

What it does

ShortGPT takes a topic or script input and automates the steps involved in producing a short-form video: generating narration, sourcing or generating visuals, adding captions, and assembling the final clip. The framework is designed for channel operators who need to produce short videos at volume.

Who it's for

  • Content creators running high-output short-form video channels
  • Developers building automated video content pipelines
  • Teams experimenting with AI-generated social media content at scale

Pros and Cons

Pros

  • End-to-end pipeline from idea to video — not just one step
  • Open-source with no per-video API costs (beyond underlying AI service calls)
  • Targets the highest-volume video format (Shorts/Reels/TikTok)
  • Active community interest (7.3k+ GitHub stars)

Cons

  • Described as experimental — production stability may vary
  • Output quality depends heavily on the underlying AI models configured
  • Automated content creation at scale raises platform policy considerations

Side-by-Side Comparison

ToolPrimary FocusInterfaceOpen SourceAgent-Ready
HyperFramesProgrammatic video renderingAPI / codeYesYes — explicitly built for agents
TEN FrameworkConversational voice/video agentsFrameworkYesYes
LiveKit AgentsRealtime video & voiceFrameworkYesYes
BackgroundRemoverBackground removalCLIYesVia scripting
ShortGPTShort-form video automationFrameworkYesPartial

How to Choose

If you're building an agentic pipeline that needs to output video — marketing personalization, automated demos, data-driven clips — start with HyperFrames. Its HTML-to-video model is the most developer-native approach in the current landscape and is explicitly designed for agent use.

If you need realtime AI in a live video session — a meeting bot, a coaching assistant, an interactive avatar — LiveKit Agents is the most production-ready option given LiveKit's established WebRTC infrastructure. TEN Framework is a strong alternative if you are building from scratch and want a purpose-built conversational agent runtime.

If your need is video post-processing — removing backgrounds from existing footage as part of an automated pipeline — BackgroundRemover is the clearest choice: free, open-source, and CLI-scriptable.

If short-form social automation is the goal — producing YouTube Shorts or TikTok content at volume — ShortGPT covers the most of the pipeline in one framework, though its experimental status means production deployments warrant testing.


The Bigger Picture

What the GitHub trending data from May 2026 reveals is that the most active development in AI video is happening in the agentic and infrastructure layers. HyperFrames topping the chart with nearly 20,000 stars reflects a market that is moving beyond "generate a video" toward "embed video generation inside automated systems." The strong showings from LiveKit Agents and TEN Framework reinforce the same theme: real-time, programmable, agent-compatible video tooling is where developer attention is focused.

For creators and non-developers, the SaaS layer (Runway, Pika, HeyGen's commercial platform, Synthesia) remains the more accessible path. But for builders, the open-source tools above represent the current frontier — and the ones most worth watching as the space develops through 2026.