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蚂蚁 inclusionAI:GitHub 新仓库更新于 10月14日 12:13

蚂蚁 inclusionAI 开源智能体工作区 Choruz,支持 Codex 与 Claude Code

GitHub - inclusionAI/Choruz · GitHub

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蚂蚁 inclusionAI 在 GitHub 开源智能体工作区 Choruz,可异步把用户交互轨迹转化为个性化基准,用于适配执行框架、减少重复错误,并支持选择性替换为自配置的小型模型。原生轨迹学习目前支持 Codex 和 Claude Code,Muse 工作区可执行但原生学习适配器尚未包含;项目处于预发布阶段,接口、配置和数据格式可能不兼容变更,采用 Apache-2.0 许可。

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蚂蚁 inclusionAI 开源 Choruz,把交互轨迹转成个性化基准来改造智能体执行框架,可据此判断其与现有编码智能体工作流的关系。

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README; Contributing; Apache-2.0 license; Security

An agent workspace for Codex, Claude Code, and Muse that asynchronously turns user interaction traces into personalized benchmarks to adapt harnesses, reduce recurring errors, and support selective substitution with smaller provider models you configure.

Native trace learning currently supports Codex and Claude Code. Muse workspace execution is supported; its native learning adapter is not included yet. Choruz evaluates task suitability, not a provider model's parameter count or billing cost.

Keep working with your agent. With background learning enabled, Choruz uses task outcomes, tool feedback, and your corrections to build evaluable tasks and test proposed improvements. The agent's instructions and execution team can change; the analysis and evaluation standards stay fixed. This adapts the harness, not the model's weights.

Choruz supports Claude Code, Codex, Muse Code, and webhook-driven external agents by default. Plugins enable Grok, Pi, OpenCode, and MathCode; see plugin configuration.

Demo

Watch the 1:57 English overview · Production and provenance

Illustrated mechanisms with one actual product-settings capture; no measured improvement or cost saving is claimed.

Developer Preview

Choruz is under pre-release development. Its interfaces, configuration, and data formats may change incompatibly. Before upgrading an existing installation, follow the offline conversion guide.

From Interaction to Improvement

Learn from your actual work. Meaningful work segments retain attempts, outcomes, and later corrections. An unsuccessful exploration is not automatically an agent mistake; Turn experience into tests. Cases carry an input, expected outcome, and an exact check or independent AI judge. Curated training, validation, and held-out cases keep evaluation separate from optimization; Improve the harness, not the scorecard. Prompt changes come first. A documented recurrence after guidance was used can unlock changes to collaborator count, role prompts, and execution order. Reviewed revisions can be restored or cleared; Use a configured smaller model selectively. When you select a smaller provider model, a validated finite-output program can complete applicable turns without native inference if you enable that capability. Abstentions and provider failures return to the original agent; this is not blanket replacement of arbitrary tasks or a guaranteed cost saving

Enable background learning, choose an analysis agent, and set the evaluation and application permissions in Experience learning. Analysis runs in separate asynchronous sessions and consumes the selected account's usage; foreground work keeps its current instructions. Provider-program execution additionally requires the configured provider and explicit transmission permission.

The same learning, evaluation, and decision libraries can be used independently of the full workspace.

Run

Requirements

Rust, pinned by rust-toolchain.toml; Node.js 24 (.nvmrc) and pnpm 10; PostgreSQL 16; At least one supported agent CLI

Run from source

Start the Web app in another terminal:

The command prints the URL to open. The main checkout uses http://127.0.0.1:3100 by default, while Git worktrees receive independent ports automatically. Choose a project in the task workbench and start a task with an installed agent CLI. Use Configure device, account or agent for additional setup; collaboration and group conversations remain available from the workspace controls.

Stop the Web app and Choruz services:

Core Capabilities

Personalized evaluation: Background trace analysis, feedback-grounded benchmark cases, fixed checks and judges, and measured prompt/team optimization; Selective provider-model execution: Use a smaller model you configure through evaluated decision programs, with confidence/applicability checks, native fallback, and recorded model attribution; A familiar workspace: Real CLI agents, persistent tasks, project files, and local or remote execution devices. Collaboration, groups, threads, and task boards remain available when needed; Composable capabilities: Shared libraries, REST APIs, WebSocket sync, webhook agents, optional plugins, and Slack/Telegram bridges

Documentation

After starting the Web app, open /docs for the user guide. Its source is under apps/web/app/docs. Continue with these engineering and integration references:

Architecture overview and subsystem index; Remote control and the CLI; OpenAPI contract and plugin development; Contributing guide, engineering rules, and security reporting

Contributors

Contributors appear in the order defined in CONTRIBUTORS.md.

License

Source code and software documentation are distributed under the Apache License 2.0, with incorporated-code notices retained in NOTICE. Dependencies and agent CLIs retain their own licenses and service terms. Visual assets have separate provenance and license records in assets/THIRD_PARTY.md and assets/brand/README.md. This license does not grant rights to the Choruz name or product identity.

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蚂蚁 inclusionAI:GitHub 新仓库