The most widely used framework for building LLM applications.
Frameworks for Knowledge
The 23 frameworks in the runchr registry that do knowledge work. Ground answers in your own documents.
23 of 23 tools · Metrics as of 2026-11-06
21-lesson course teaching how to build generative AI applications.
Compresses tool outputs, logs, files, and RAG chunks before they reach the LLM.
Open-source book on AI agent design with 109 hands-on experiment projects.
Connect your own documents to a model, with retrieval built in.
Lightweight self-hosted Python framework for building personal AI agents.
Open-source AI memory platform giving agents persistent knowledge-graph memory.
Python framework for building RAG pipelines and agent workflows.
Turns docs, repos, and PDFs into AI skills and RAG knowledge assets.
Open-source platform and SDK for building and deploying LLM chatbots and agents.
100-line minimalist LLM framework for building agents and workflows.
TypeScript framework for building agents with memory, tools, workflows, and MCP.
Open-source Python framework for building private, offline-capable AI agents.
Open-source Python and TypeScript SDK for building production AI agents.
Java framework for building multi-agent AI apps with RAG and workflows.
Local-first healthcare AI SDK for clinical NER and HIPAA PII de-identification.
Ruby framework for building AI agents with tools, MCP, and 23 providers.
Python framework for building multi-agent LLM applications with tools and RAG.
Open source .NET framework for building multi-agent AI applications.
Python framework for extracting structured data from documents with LLMs.
Python framework for building reliable GenAI agent backends with structured
Scala library for building LLM agents with tool calling, RAG, and MCP.
Python library unifying 11 LLM providers with failover, structured output