8000 GitHub - varun86/goose: an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to content
/ goose Public
forked from block/goose

an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM

License

Notifications You must be signed in to change notification settings

varun86/goose

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

codename goose

a local, extensible, open source AI agent that automates engineering tasks

Discord CI

goose is your on-machine AI agent, capable of automating complex development tasks from start to finish. More than just code suggestions, goose can build entire projects from scratch, write and execute code, debug failures, orchestrate workflows, and interact with external APIs - autonomously.

Whether you're prototyping an idea, refining existing code, or managing intricate engineering pipelines, goose adapts to your workflow and executes tasks with precision.

Designed for maximum flexibility, goose works with any LLM, seamlessly integrates with MCP servers, and is available as both a desktop app as well as CLI - making it the ultimate AI assistant for developers who want to move faster and focus on innovation.

Multiple Model Configuration

goose supports using different models for different purposes to optimize performance and cost, which can work across model providers as well as models.

Lead/Worker Model Pattern

Use a powerful model for initial planning and complex reasoning, then switch to a faster/cheaper model for execution, this happens automatically by goose:

# Required: Enable lead model mode
export GOOSE_LEAD_MODEL=modelY
# Optional: configure a provider for the lead model if not the default provider
export GOOSE_LEAD_PROVIDER=providerX  # Defaults to main provider

Planning Model Configuration

Use a specialized model for the /plan command in CLI mode, this is explicitly invoked when you want to plan (vs execute)

# Optional: Use different model for planning
export GOOSE_PLANNER_PROVIDER=openai
export GOOSE_PLANNER_MODEL=gpt-4

Both patterns help you balance model capabilities with cost and speed for optimal results, and switch between models and vendors as required.

Quick Links

Goose Around with Us

About

an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Rust 64.1%
  • TypeScript 25.3%
  • Python 3.7%
  • Kotlin 2.7%
  • Shell 1.6%
  • JavaScript 0.8%
  • Other 1.8%
0