Build AI applications with a provider-agnostic Rust API for agents and RAG pipelines.
npx skills add https://github.com/yoogoc/xcraw --skill rig-yoogoc
Please help me install this Agent Skill. Skill: rig Source: https://github.com/yoogoc/xcraw/tree/main/.opencode/skills/rig Command: npx skills add https://github.com/yoogoc/xcraw --skill rig-yoogoc
Rig provides a provider-agnostic Rust framework to rapidly compose and deploy LLM-powered applications, removing the friction of integrating multiple providers and patterns.
Instantiate a Rig client and build a simple agent with a provider to handle a basic prompt.
High-intent search queries and answers about installing and using this skill.
You can build a Rust AI app with a provider-agnostic API by instantiating a client to compose agents, RAG pipelines, and tool-calling workflows. This framework abstracts multiple LLM providers, allowing rapid deployment of unified AI applications.
Yes, you can use Rust to create streaming completions and agents across multiple LLM providers. The framework provides a unified API for building agents, RAG pipelines, and tool-calling workflows that seamlessly operate across different providers.
The best way to implement tool-calling workflows and structured extraction in Rust is using ready-made patterns like Agent with Tools and Structured Extraction. These patterns accelerate development by providing built-in compositions for async tokio operations.
Yes, you need async tokio patterns and Rust proficiency to use this AI framework. Building agents, RAG pipelines, and tool-calling workflows requires experience with agent builders, tools, and optional vector-store integration in async Rust environments.
Yes, this Rust AI framework supports optional vector-store integration for RAG pipelines. You can build retrieval-augmented generation pipelines that fetch context, call tools, and stream responses across a unified provider-agnostic API.
A provider-agnostic Rust framework handles multi-provider AI assistants by offering a unified API that removes integration friction. It allows you to compose agents that fetch context, call tools, and stream responses seamlessly across different LLM providers.
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