nexent

ModelEngine-Group/nexent

Zero-code platform for auto-generating production-grade AI agents using Harness Engineering principles.

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Python MITLast pushed Jul 7, 2026

Overview

Nexent is a no-code platform that simplifies the creation of production-level AI agents through language-driven development without complex orchestration or drag-and-drop interfaces. It provides unified tools, skills, memory, and built-in control mechanisms for seamless agent generation.

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Install

pip install nexent

README

Nexent is a zero-code platform for auto-generating production-grade AI agents, built on Harness Engineering principles. It provides unified tools, skills, memory, and orchestration with built-in constraints, feedback loops, and control planes — no orchestration, no complex drag-and-drop required, using pure language to develop any agent you want.

One prompt. Endless reach.

Watch the demo video

🚀 Get Started Now

⭐ Before you get started, please star us on GitHub — your support drives us forward!

Option 1: Try Our Official Demo

No installation required — jump right in with our online demo environment to experience Nexent's capabilities instantly.

Option 2: Deploy on Your Own

If you need to run Nexent locally or in your private infrastructure, we offer two deployment options:

System Requirements

ResourceDockerKubernetes
CPU4 cores (min) / 8 cores (rec.)4 cores (min) / 8 cores (rec.)
Memory8 GiB (min) / 16 GiB (rec.)16 GiB (min) / 64 GiB (rec.)
Disk40 GiB (min) / 100 GiB (rec.)100 GiB (min) / 200 GiB (rec.)
Architecturex86_64 / ARM64x86_64 / ARM64
SoftwareDocker 24+, Docker Compose v2+Kubernetes 1.24+, Helm 3+

Note: Recommended configurations ensure optimal performance in production environments.

Docker Deployment (Recommended for Individuals/Small Teams)

Quick and straightforward for most users. Prerequisites: Docker 24+ and Docker Compose v2+:

git clone https://github.com/ModelEngine-Group/nexent.git
cd nexent
bash deploy.sh docker

The root deploy.sh only forwards to the target deploy script; the native Docker implementation is bash deploy/docker/deploy.sh. The Docker and Kubernetes deploy scripts share the same deployment configuration model. Interactive runs show Bash TUI menus for component selection, port policy, and image source. infrastructure is required; application, data-process, and supabase are selected by default and can be disabled when you want a smaller deployment. Use b/Backspace to return to the previous TUI step and q to quit. Non-interactive runs can pass the same choices with --version, --components, --port-policy development|production, and --image-source general|mainland|local-latest. Successful deployments save non-sensitive choices to each deploy directory's deploy.options for reuse on the next run.

Docker and Kubernetes both use deploy/env/.env as the runtime configuration file. Existing deploy/env/.env is kept as-is. If it does not exist, the deploy scripts first reuse docker/.env, then fall back to deploy/env/.env.example.

Docker uninstall is handled by bash uninstall.sh docker. It can preserve or delete data volumes: run it interactively, pass --delete-volumes true|false, or use bash uninstall.sh docker delete-all to remove containers and persistent data.

Offline image packages can be built with bash deploy/offline/build_offline_package.sh --target docker --compress true. The package includes image tar files, load-images.sh, root deploy/uninstall entrypoints, deployment scripts, SQL files, manifest.yaml, and checksums.txt; deploy it with bash deploy.sh --load-images docker ... on the target host.

For detailed deployment instructions, see Docker Installation.

Kubernetes Deployment (For Enterprise Production)

Ideal for enterprise scenarios requiring high availability and elastic scaling. Prerequisites: Kubernetes 1.24+ and Helm 3+:

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