Rig is a framework for building large language model applications, featuring a multi-provider client and a workflow builder for retrieval-augmented generation systems. It serves as an orchestrator for creating autonomous agents that can maintain conversation state and execute complex tasks through custom prompting and plugins. The project provides standardized interfaces for both completion and embedding model providers, allowing for unified request and response patterns across different engines. It also includes a vector database integration layer that defines a common interface for indexing
Lecture notes and assignments for coursera machine learning class
Unoffcial documentation for Lowy Institute's Asia Power Index API
C# behaviour tree library with a fluent API
The main features of codecapers/fluent-behaviour-tree are: Artificial Intelligence.
Open-source alternatives to codecapers/fluent-behaviour-tree include: 0xeb/fastmcpp — C++ port of the fastmcp Python library. 0xplaygrounds/rig — Rig is a framework for building large language model applications, featuring a multi-provider client and a workflow… 1094401996/machine-learning-coursera — Lecture notes and assignments for coursera machine learning class. 1backend/1backend — Build AI (or any) apps with scalable microservices & microfrontends. 3lf/llm-for-humans — برای آدمیزاد LLM آموزش / Teaching LLM in Persian. 0x0is1/lowy-index-api-docs — Unoffcial documentation for Lowy Institute's Asia Power Index API.
