AI Skill Hub 强烈推荐:Coze Loop 是一款优质的AI工具。已获得 5.5k 颗 GitHub Star,AI 综合评分 8.0 分,在同类工具中表现稳健。如果你正在寻找可靠的AI工具解决方案,这是一个值得深入了解的选择。
下一代AI代理优化平台,专注于AI Agent工作流构建与评估。提供Agent可观测性、性能评估等核心能力,适合AI开发者、企业应用构建者优化Agent系统。
Coze Loop 是一款基于 Go 开发的开源工具,专注于 AI Agent、工作流编排、Agent评估 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
下一代AI代理优化平台,专注于AI Agent工作流构建与评估。提供Agent可观测性、性能评估等核心能力,适合AI开发者、企业应用构建者优化Agent系统。
Coze Loop 是一款基于 Go 开发的开源工具,专注于 AI Agent、工作流编排、Agent评估 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
# 方式一:go install(推荐) go install github.com/coze-dev/coze-loop@latest # 方式二:从源码编译 git clone https://github.com/coze-dev/coze-loop cd coze-loop go build -o coze-loop . # 方式三:下载预编译二进制 # 访问 Releases 页面下载对应平台二进制文件 # https://github.com/coze-dev/coze-loop/releases
# 查看帮助 coze-loop --help # 基本运行 coze-loop [options] <input> # 详细使用说明请查阅文档 # https://github.com/coze-dev/coze-loop
# coze-loop 配置说明 # 查看配置选项 coze-loop --config-example > config.yml # 常见配置项 # output_dir: ./output # log_level: info # workers: 4 # 环境变量(覆盖配置文件) export COZE_LOOP_CONFIG="/path/to/config.yml"
English | 中文
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| **Feature** | **Functional points** |
|---|---|
| Prompt debugging | *Playground debugging and comparison <br>* Prompt version management |
| Evaluation | *Manage evaluation sets <br> Management evaluator <br>* Manage experiments |
| Observation | SDK trace reporting <br> * Trace data observation |
| Model | Support integration with OpenAI, Volcengine Ark, and other models |
To efficiently track and resolve issues while ensuring transparency and collaboration, we recommend participating through:
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: api_key: Volcengine Ark API Key. Users in China can refer to the Volcengine Ark documentation, while users outside China can refer to the BytePlus ModelArk documentation. model: The Endpoint ID of the Volcengine Ark model access point. Users within China can refer to the Volcengine Ark documentation; users outside China can refer to the BytePlus ModelArk documentation. 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
http://localhost:8082.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:
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: api_key: Volcengine Ark API Key. Users in mainland China can refer to the Volcengine Ark documentation, while users outside mainland China can refer to the BytePlus ModelArk documentation. model: The Endpoint ID of the Volcengine Ark model access point. Users in China can refer to the Volcengine Ark documentation, while users outside China can refer to the BytePlus ModelArk documentation. 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
make helm-up
# After the service deployment is complete, check the status of the cluster pods
make helm-pod
# Check the service startup logs. If both the app and nginx are running normally, the deployment is successful
make helm-logf-app
make helm-logf-nginx
5. Access the Coze Loop open source edition via a browser. The access domain name and URL depend on the domain name and URL assigned to your cluster. 6. Start customizing your Coze Loop project. Refer to the examples in the examples/ directory. Modify values.yaml to override the default settings. After making changes, rerun make helm-up for the changes to take effect.
[!WARNING] If you want to deploy Coze Loop in a public network environment, it is recommended to assess security risks before you begin, and take corresponding protection measures. Possible security risks include account registration functions, Coze Server listening address configurations, SSRF (Server - Side Request Forgery), and some horizontal privilege escalations in APIs. For more details, refer to Quickstart.
Refer to Quick Start to learn in detail how to install and deploy the latest version of Coze Loop.
���熟的Agent优化平台,5.5k Stars表明社区认可度高。Go语言实现保证性能,Agent评估能力突出,适合企业级应用。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ Apache 2.0 — 宽松开源协议,可商用,需保留版权声明和 NOTICE 文件,含专利授权条款。
总体来看,Coze Loop 是一款质量优秀的AI工具,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | coze-loop |
| 原始描述 | 开源AI工作流:Next-generation AI Agent Optimization Platform: Cozeloop addresses challenges in。⭐5.5k · Go |
| Topics | AI Agent工作流编排Agent评估可观测性Go语言 |
| GitHub | https://github.com/coze-dev/coze-loop |
| License | Apache-2.0 |
| 语言 | Go |
收录时间:2026-05-21 · 更新时间:2026-05-30 · License:Apache-2.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。