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
Build AI (or any) apps with scalable microservices & microfrontends.
Unoffcial documentation for Lowy Institute's Asia Power Index API
C++ port of the fastmcp Python library
The main features of 0xeb/fastmcpp are: Artificial Intelligence.
Open-source alternatives to 0xeb/fastmcpp include: 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. 40ants/mcp — 40ANTS-MCP is a framework for building Model Context Protocol servers in Common Lisp. 0x0is1/lowy-index-api-docs — Unoffcial documentation for Lowy Institute's Asia Power Index API.