Build LLM-powered AI agents in Go with DAG and loop orchestration.
npx skills add https://github.com/tiltwind/note-md --skill vagent
Please help me install this Agent Skill. Skill: vagent Source: https://github.com/tiltwind/note-md/tree/main/ai/vagent Command: npx skills add https://github.com/tiltwind/note-md --skill vagent
This Skill provides a comprehensive framework for developing and deploying Large Language Model (LLM)-powered AI agents in Go, simplifying complex agent orchestration and integration.
Use the vagent skill to generate a basic agent configuration file.
High-intent search queries and answers about installing and using this skill.
You can build LLM-powered AI agents in Go using a framework that supports diverse agent types, orchestration patterns like DAGs and loops, and integrates external tools for efficient agent development.
AI agent workflows support Sequence, DAG, and Loop orchestration patterns. These patterns allow you to coordinate multiple agent types, such as TaskAgent and WorkflowAgent, to handle complex execution flows.
Yes, you can integrate multiple LLM providers into a single Go chatbot framework through a unified interface. This LLM agnostic approach allows seamless switching between different models for your agents.
Yes, the Go agent framework supports external tool integration via APIs and implements multi-level memory management. This ensures context retention and allows agents to perform actions through integrated tools.
The best way to configure a customer support agent in Go is to generate a basic agent configuration file. You can use RouterAgent and CustomAgent types to understand queries, access knowledge bases, and perform actions.
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