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Welcome to the Coyote Wiki!
A helpful way to use this wiki is to create a RAG from it and then ask questions about Coyote, with Coyote! Here's an example on how to create a RAG from this wiki and then ask a question about Coyote:
Coyote is an all-in-one, batteries-included, LLM CLI tool featuring Shell Assistant, CLI & REPL Mode, RAG, AI Tools & Agents, and More.
It is designed to include a number of useful agents, roles, macros, and more so users can get up and running with Coyote in as little time as possible.
Coming from AIChat? Follow the migration guide to get started.
- AIChat Migration Guide: Coming from AIChat? Follow the migration guide to get started.
- Installation: Install Coyote
- Getting Started: Get started with Coyote by doing first-run setup steps, and learn the basics.
- Sharing Configurations: Install bundles of agents, roles, macros, tools, and MCP servers from any git repo, and share your own.
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REPL: Interactive Read-Eval-Print Loop for conversational interactions with LLMs and Coyote.
- Custom REPL Prompt: Customize the REPL prompt to provide useful contextual information.
- Vault: Securely store and manage sensitive information such as API keys and credentials.
- Shell Integrations: Seamlessly integrate Coyote with your shell environment for enhanced command-line assistance.
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Function Calling: Leverage function calling capabilities to extend Coyote's functionality with custom tools
- Creating Custom Tools: You can create your own custom tools to enhance Coyote's capabilities.
- First-Class MCP Server Support: Easily connect and interact with MCP servers for advanced functionality.
- Macros: Automate repetitive tasks and workflows with Coyote "scripts" (macros).
- RAG: Retrieval-Augmented Generation for enhanced information retrieval and generation.
- Sessions: Manage and persist conversational contexts and settings across multiple interactions.
- Roles: Customize model behavior for specific tasks or domains.
- Skills: Modular knowledge or capability packs the LLM can load and unload mid-conversation. Multiple skills compose; instructions stack, tools and MCPs union.
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Agents: Leverage AI agents to perform complex tasks and workflows, including sub-agent spawning, teammate messaging, and user interaction tools.
- Graph Agents: Define an agent as a declarative, YAML-driven workflow. A directed graph of typed nodes (LLM calls, scripts, approvals, user input, RAG retrieval, sub-agent spawns).
- Todo System: Built-in task tracking for improved agent reliability with smaller models.
- Environment Variables: Override and customize your Coyote configuration at runtime with environment variables.
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Client Configurations: Configuration instructions for various LLM providers.
- Authentication (API Key & OAuth): Authenticate with API keys or OAuth for subscription-based access.
- Patching API Requests: Learn how to patch API requests for advanced customization.
- Custom Themes: Change the look and feel of Coyote to your preferences with custom themes.
- History: A history of how Coyote came to be.
Coyote began as a fork of AIChat CLI and has since evolved into an independent project.
See CREDITS for full attribution and background.