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doc: Add proposal of AgentRun CLI.#28

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volcano-sh-bot merged 7 commits intovolcano-sh:mainfrom
LaynePeng:proposal/agentrun-cli-design
Dec 18, 2025
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doc: Add proposal of AgentRun CLI.#28
volcano-sh-bot merged 7 commits intovolcano-sh:mainfrom
LaynePeng:proposal/agentrun-cli-design

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@LaynePeng LaynePeng commented Nov 17, 2025

What type of PR is this?
/kind documentation
/kind feature

What this PR does / why we need it:
This design proposal addresses friction in modern AI agent development workflows, where developers must manage configurations, dependencies, runtime environments, and deployment targets across heterogeneous platforms. Currently, agent frameworks lack a unified interface, forcing developers to juggle multiple tools and environments, which slows iteration and increases operational overhead.

This proposal introduces an opt-in Command Line Interface (CLI) that orchestrates the agent lifecycle — from initialization and packaging to building, testing, and publishing. By leveraging Kubernetes and multi-cloud integration, the CLI hides infrastructure complexity from developers, ensuring scale-up operations and deployments are triggered only when necessary. This prevents wasted effort, reduces infrastructure costs, and accelerates innovation.

Which issue(s) this PR fixes:

Copilot AI review requested due to automatic review settings November 17, 2025 03:57
@volcano-sh-bot volcano-sh-bot added kind/documentation Improvements or additions to documentation kind/feature labels Nov 17, 2025
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Welcome @LaynePeng! It looks like this is your first PR to volcano-sh/agentcube 🎉

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Summary of Changes

Hello @LaynePeng, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces the design proposal for AgentRun, a new Command Line Interface (CLI) intended to simplify and standardize the development and deployment of AI agents. The AgentRun CLI aims to abstract away the complexities of managing configurations, dependencies, and runtime environments across diverse platforms, from local development to multi-cloud deployments. By providing a unified set of commands for packaging, building, publishing, and interacting with AI agents, it seeks to accelerate iteration, reduce operational overhead, and empower developers to focus on innovation within the AgentCube ecosystem.

Highlights

  • Introduction of AgentRun CLI: Proposes a new Command Line Interface (CLI) named "AgentRun" to streamline the development, deployment, and management of AI agents, addressing complexities in modern AI agent workflows.
  • Unified Agent Lifecycle Management: The CLI orchestrates the entire agent lifecycle, including packaging, building, publishing, checking status, and invoking agents, providing a consistent interface across different environments.
  • Extensible Architecture: Designed with a modular, layered architecture (Command Line, Runtimes, Operations, Services) to support local environments, Kubernetes, and multi-cloud build/deployment targets, with Python SDK bindings for CI/CD integration.
  • Standardized Metadata Configuration: Introduces "agent_metadata.yaml" as a single source of truth for agent identity, runtime behavior, build strategy, and deployment settings, ensuring consistency throughout the agent's lifecycle.
  • Core CLI Commands: Details the functionality and API design for key commands: "pack" (packages agent), "build" (creates container image), "publish" (registers with AgentCube), "status" (checks agent state), and "invoke" (triggers agent execution).
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Code Review

This is a well-written and comprehensive design document for the new AgentRun CLI. The proposal clearly outlines the motivation, use cases, and implementation architecture. My review focuses on enhancing the document's clarity, consistency, and correctness. I've identified several minor issues, including typos, inconsistencies in naming conventions (e.g., metadata filename), and potentially problematic command-line examples. Addressing these points will improve the overall quality and usability of the design document for developers who will build and use this CLI.

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Pull Request Overview

This PR introduces a comprehensive design proposal for an AgentRun CLI tool that streamlines AI agent development workflows. The proposal addresses friction in managing configurations, dependencies, runtime environments, and deployment targets across heterogeneous platforms by providing a unified command-line interface.

Key changes:

  • Adds a complete CLI design document covering architecture, use cases, and implementation details
  • Defines commands for the full agent lifecycle: pack, build, publish, status, and invoke
  • Proposes a four-layer architecture with support for both local and cloud build modes

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Signed-off-by: Layne Peng <appamail@hotmail.com>
@LaynePeng LaynePeng force-pushed the proposal/agentrun-cli-design branch from cd0ee8f to 8ea9a5a Compare November 17, 2025 04:56
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Pull Request Overview

Copilot reviewed 1 out of 1 changed files in this pull request and generated 6 comments.


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Signed-off-by: Layne Peng <appamail@hotmail.com>
Signed-off-by: Layne Peng <appamail@hotmail.com>
Copilot AI review requested due to automatic review settings November 24, 2025 06:39
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Pull request overview

Copilot reviewed 1 out of 1 changed files in this pull request and generated 32 comments.


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Signed-off-by: Zhou Zihang <z@mcac.cc>
Copilot AI review requested due to automatic review settings December 10, 2025 07:33
@acsoto acsoto force-pushed the proposal/agentrun-cli-design branch from 06d77c3 to 3c8375f Compare December 10, 2025 07:33
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Pull request overview

Copilot reviewed 1 out of 1 changed files in this pull request and generated 6 comments.


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- **Provider: k8s**: Deploys a standard Kubernetes `Deployment` and `Service` (NodePort).

**Step 3.4** Await Deployment Status
The CLI monitors the deployment status (readiness probes, pod status) until the agent is ready or a timeout occurs.
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Status check: Kubernetes provider only? AgentCube provider unsupported (no agent sandbox created).

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Yes. This should be within k8s provider.
For agentcube: It submits the AgentRuntime CR to the cluster and does not wait for the agent to become ready during the publish command.

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Update the design doc for greater clarity.


#### Key Fields

|Field|Description|
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@MahaoAlex MahaoAlex Dec 15, 2025

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Some fields apply only to Kubernetes or AgentCube provider --- better to distinguish them explicitly

Signed-off-by: Layne Peng <appamail@hotmail.com>
Signed-off-by: Layne Peng <appamail@hotmail.com>
Signed-off-by: Layne Peng <appamail@hotmail.com>
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/lgtm
/approve

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[APPROVALNOTIFIER] This PR is APPROVED

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This pull-request has been approved by: hzxuzhonghu

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@volcano-sh-bot volcano-sh-bot merged commit 28b017d into volcano-sh:main Dec 18, 2025
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6 participants