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coze-loop

coze-dev/coze-loop

Next-generation AI Agent Optimization Platform

GraphCanon updated 1mo · GitHub synced 1mo · 26 views this month

5.6k stars777 forksLast push 1mo Go Apache-2.0

Decision brief

Coze-loop provides comprehensive lifecycle management for AI agents leveraging Go, under Apache-2.0 license, ideal for robust agent optimization from development to monitoring.

Good fit when

  • When you are developing AI agents and need full-lifecycle support from initial setup through deployment
  • For users preferring Go and looking for an open-source solution with a permissive license

Avoid when

  • If your primary agent development language is not Go, or if you do not wish to use Docker or Kubernetes for deployment
  • Avoid if you are unwilling to configure the Volcengine Ark API Key and Endpoint ID manually through YAML files during setup

Observed Jul 14, 2026 · Source: enrich:decision_facts

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Maintenance and security

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Maintenance
Very active (0d since push)
As of 1mo
Provenance
Not a fork · Organization account
As of 1mo
Security (OSV)
No lockfile
As of 1mo

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Install

go get github.com/coze-dev/coze-loop
pkg.go.dev

How it fits your stack(11)

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Evidence and technical details

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Overview

Cozeloop offers full-lifecycle management for AI agents including development, debugging, evaluation, and monitoring.

Capability facts

Languages
go

Source: github.language · Jul 21, 2026

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README

Quick Start

Refer to Quick Start to learn in detail how to install and deploy the latest version of Coze Loop.


Deployment method 1: Docker deployment (Docker Compose)

Please install and start Docker Engine before you start.

Procedure:

  1. Clone the source code. Run the following command to obtain the latest version of the Coze Loop source code.

    # Clone the code
    git clone https://github.com/coze-dev/coze-loop.git
    
    # Enter the coze-loop directory
    cd coze-loop
    
  2. Configure a model.

    1. Enter the coze-loop directory.
    2. Edit the file release/deployment/docker-compose/conf/model_config.yaml.
    3. Modify the api_key and model fields. Take Volcengine Ark as an example:
  3. Start the service. Run the following commands to quickly deploy the open-source version of Coze Loop using Docker Compose.

    # Start the service (default: development mode)
    # Run in the coze-loop/ directory
    make compose-up
    
  4. Access the Coze Loop open-source version through your browser http://localhost:8082.


Deployment method 2: Kubernetes deployment using Helm Chart

  • The Kubernetes cluster has been prepared, the Nginx Ingress add-ons have been enabled, and the Kubectl and Helm tools have been installed.
  • To quickly try it out locally, you can deploy a Kubernetes cluster using Minikube. For detailed steps, refer to Quick Start.

Procedure:

  1. Run the following command to obtain the Helm Chart package.

    helm pull oci://docker.io/cozedev/coze-loop --version 1.0.0-helm
    tar -zxvf coze-loop-1.0.0-helm.tgz && cd coze-loop && rm -f ../coze-loop-1.0.0-helm.tgz
    
  2. Configure a model. Go to the coze-loop directory and edit the release/deployment/helm-chart/umbrella/conf/model_config.yaml file. Configure the following fields, using Volcengine Ark as an example:

  3. Configure Ingress rules. Ingress is used to expose services to external networks. You need to configure the templates/ingress.yaml file in the project directory according to the actual cluster situation, manually modify parameters such as ingressClassName, and configure elements such as class, instance, host, and IP allocation.

  4. Deploy and start the service. Execute the following commands to quickly deploy the open-source version of Coze Loop using Helm.

    # Run in the coze-loop/ directory
    

For agents

This page has a .md twin and JSON over the API.

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