rag

Open Executive is an open-source AI system that acts as a virtual executive team, routing requests through a single executive persona backed by eight specialist Claude agents. The repo includes architecture notes, tech stack details, repo layout, and quick-start steps for running the FastAPI backend and Next.js UI.

Open-source local-first contract layer and runtime for canonical data, retrieval, durable execution, and agent-facing AI. The repo includes a quick start, capability boundaries, client/runtime notes, and examples for running locally and inspecting providers.

CacheCore is an agent infrastructure tool that sits between LLM clients and the API to cache exact and near-identical prompts, cutting repeat calls and latency. The page shows OpenAI-compatible integration, support for common agent frameworks, and use cases for RAG and multi-agent workflows.

Community edition of Merlin, a local-first deduplication tool for LLM context and RAG pipelines. The repo includes quick-start install steps, MCP and editor integrations, savings claims, and rollback guidance.

A side-by-side comparison of 15 AI agent frameworks, including LangGraph, CrewAI, AutoGen, Pydantic AI, OpenAI Agents SDK, Mastra, Vercel AI SDK, LangChain, LlamaIndex, Haystack, Dify, Flowise, n8n, Semantic Kernel, and smolagents. The page highlights use-case fit, control style, language support, GitHub stars, and fra

A zero-budget research search engine and RAG pipeline for 5,600 arXiv papers, built with free Colab processing, Qdrant free tier, and hybrid dense+sparse retrieval.

Lens AI is an embedded knowledge assistant that connects docs, help content, and published sites to provide consistent AI answers across websites, internal tools, and support surfaces.

A blog post about verifiable RAG that benchmarks open-source NLI verifiers against Claude on RAGTruth and describes a Python library for sentence-level citation and claim verification.

A GitHub example that audits LangChain’s RAG quickstart with retrieval-quality metrics, flags off-topic and out-of-distribution queries, and surfaces ranking and calibration issues with charts and results files.

An essay about why AI agents should use project documentation instead of conversation memory, with a description of the author’s Operator Memory system for markdown-based agent memory.

A GitHub repository for a latency-separated AI memory retrieval and RAG system. The README describes fetch, compute, and ANN search stages, includes benchmark ranges, and exposes a public test endpoint.