doc: Add proposal of AgentRun CLI.#28
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Welcome @LaynePeng! It looks like this is your first PR to volcano-sh/agentcube 🎉 |
Summary of ChangesHello @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
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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>
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Pull Request Overview
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Signed-off-by: Layne Peng <appamail@hotmail.com>
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Signed-off-by: Layne Peng <appamail@hotmail.com>
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Pull request overview
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Signed-off-by: Zhou Zihang <z@mcac.cc>
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| - **Provider: k8s**: Deploys a standard Kubernetes `Deployment` and `Service` (NodePort). | ||
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| **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.
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| #### Key Fields | ||
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| |Field|Description| |
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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 |
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[APPROVALNOTIFIER] This PR is APPROVED Approval requirements bypassed by manually added approval. This pull-request has been approved by: hzxuzhonghu The full list of commands accepted by this bot can be found here. The pull request process is described here DetailsNeeds approval from an approver in each of these files:Approvers can indicate their approval by writing |
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: