DeepSeek Harness: Building and Extending AI Coding Agents Training Course
DeepSeek Harness (dsh) is an open-source framework developed by DeepSeek AI, designed specifically for the creation and execution of AI coding agents. Rooted in the Cordis plugin framework, it adheres to an "everything is a plugin" architectural philosophy, where core components such as the model adapter, tool registry, session log, and agent loop are modular and can be swapped out during the initialization process.
This live, instructor-led training session, available either online or on-site, is tailored for software developers and AI engineers looking to leverage DeepSeek Harness to construct, manage, and enhance AI coding agents within their own projects.
Upon completion of this course, participants will be equipped to:
- Install and launch DeepSeek Harness while configuring various models.
- Execute coding tasks efficiently via both the Web UI and the command line interface.
- Describe the Cordis plugin architecture and identify its key extension points.
- Create and release custom plugins tailored for the harness.
- Automate harness operations using the SDK and headless mode.
Course Structure
- Engaging lectures complemented by open discussions.
- Extensive practical exercises and hands-on practice.
- Real-world implementation exercises in a live-lab setting.
Customization Options
- Please reach out to us if you require a customized training program.
Course Outline
DeepSeek Harness Introduction
- Defining DeepSeek Harness and its role in the ecosystem.
- The "everything is a plugin" design philosophy.
- Overview of Web UI, CLI, and headless operational modes.
Setup and Initial Execution
- Node.js prerequisites and package installation steps.
- Launching the Web UI using npx.
- Building the application from source code and running it.
Configuring Models
- Configuring the DeepSeek API key.
- Methods for selecting and switching between models.
- Integration with OpenAI-compatible endpoints.
Managing Workspaces and Sessions
- Selecting and navigating between different workspaces.
- Understanding the session composer and conversation dynamics.
- Operations for reading, editing, and generating files.
Executing Coding Tasks
- Techniques for summarizing repositories and navigating codebases.
- Running commands and delegating specific workloads.
- Maintaining an organized task plan.
Permissions and Sandboxing
- Understanding approval and permission policies.
- Restricting file and command access for security.
- Utilizing local and remote sandbox backends.
Native Tools and Integrations
- Tools for filesystem, terminal, and shell operations.
- Support for the Model Context Protocol.
- Integration with the Language Server Protocol.
Subagents and Delegation Strategies
- Creating and forking subagents.
- Using product providers for external coding agents.
- Distributing work across an active session.
The Cordis Plugin Model
- Viewing plugins as services, events, and effects.
- Understanding shared context and lifecycle management.
- The rationale behind having no privileged core.
Profiles, Bundles, and Setup
- Layering profiles and bundles.
- Modifying configuration via cordis.patch.yml.
- Reviewing the initialized system tree.
Essential Subsystems
- The append-only nature of the session log.
- Assembly of system prompts and tool schemas.
- The mechanics of the agent loop and turn flow.
Events and Extension Capabilities
- Handling session, agent, and capability events.
- Implementing waterfall and interceptor events.
- Aligning specific behaviors with extension points.
Plugin Development
- Registering services using context keys.
- Incorporating new tools and model adapters.
- Publishing and discovering new plugins.
SDK, Headless Mode, and Automation
- Controlling the harness from external processes.
- Utilizing TypeScript and Python SDKs.
- Implementing CLI and headless automation workflows.
Requirements
- A solid grasp of fundamental software development concepts.
- Proficiency in using the command line and Git.
- Basic knowledge of JavaScript or TypeScript.
Target Audience
- Software developers.
- AI and machine learning engineers.
- DevOps and platform engineers.
Open Training Courses require 5+ participants.
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