rag

PageIndex is a vectorless, reasoning-based RAG engine for long documents. The repository shows a Python SDK, quickstart code, model recommendations, and benchmark claims for document retrieval without vector DBs or chunking.

A self-hosted Docker Compose stack for running local AI services including Ollama, LiteLLM, Whisper, Kokoro, embeddings, and an MCP Gateway.

Docker Agent is Docker’s AI agent builder and runtime for creating, running, and sharing agents from YAML. It supports multi-agent orchestration, MCP tools, several model providers, and packaging agents into OCI registries.

Self-hosted, OpenAI-compatible AI gateway for private RAG, natural-language data access, and tool-calling agents. It connects files, databases, vector stores, APIs, and MCP tools through one backend with auth, observability, and governance features.

Omnesis is a private, local knowledge layer that indexes a person’s digital life so AI agents and users can search email, messages, notes, calendar, files, health data, and more. The page shows a real product with setup flow, source integrations, privacy controls, and multi-surface access through CLI, web, iOS, and And

Enterprise Postgres platform for AI apps, with managed, BYO cloud, and on-prem deployment options. It adds built-in MCP access for agents, pgvector and hybrid search for RAG, branching for isolated experiments, and a path from prototype to production.

A Python GraphRAG library for PostgreSQL that combines entity/relation extraction, pgvector embeddings, graph traversal, and full-text search to answer questions with time-aware updates.

오픈소스 AI 인프라 산정 도구로, 보유 GPU나 목표 워크로드를 입력해 실행 가능한 모델, 필요 장비, 배치안, TCO 비교까지 계산합니다. LLM, RAG, VLM, 아바타, 음성 워크로드를 다루며 한국어/영어 UI와 여러 추천 경로를 제공합니다.

A local-first backend for AI agents that bundles documents, vector search, cache, queues, and cron jobs into one SQLite file, with optional Postgres support.

A 150M ModernBERT-based token classification model that extracts verbatim evidence spans for RAG and related pipelines, reducing the need for an LLM call to highlight answers.

JetBrains introduces Mellum2, an open-source 12B model built for software engineering workflows, routing, Q&A, RAG, sub-agents, and private deployment.

A two-part self-study course for building a tiny LLM stack from scalar autograd to a working chat assistant, with modules covering transformers, pretraining, instruction tuning, retrieval, tool use, and agent loops.

TokenPath is an API for token-level citations and attribution for LLM outputs. It resolves claims in generated answers back to source spans, uses attention-based tracing, and includes an endpoint for raw heatmaps.

ForthWrite is a Chrome extension for Gmail that learns a user’s email voice from sent messages and edits. This page explains its retrieval-and-feedback loop in detail, including pgvector-based RAG, edit-distance scoring, a phrasing miner, and the stack behind the product.

ContextIQ is a suite of AI engineering tools for inspecting context, agent workflows, protocol support, and payment or identity checks for AI systems. It includes inspectors for MCP/A2A/ARD, RAG chunking, traces, memory architecture, OIDC, DNS, x402, and ERC-8004.

A Go-based crawler for scraping documentation sites into clean Markdown and JSONL for LLM ingestion, RAG pipelines, and offline searchable doc corpora.

Hubmesh is a Python library for multi-hop GraphRAG retrieval planning on top of existing vector databases. It adds centrality-aware seed selection, budget-aware context packing, entity graph building, and an MCP server for agent/tool integrations.

A Python package and CLI for checking how closely an AI-generated answer reuses its source text, with support for verbatim matching, subsequence matching, quotation verification, and pipeline gating.

SmolSignal is an AI signal copilot for Flipper Zero files. It explains common capture formats, classifies safety risk, supports local and cloud model backends, and can generate safe consumer IR files.

Open-source SDK and libraries for building local-first, peer-to-peer AI apps. It supports local LLM inference, embeddings, translation, transcription, TTS, OCR, image generation, and an OpenAI-compatible API across desktop and mobile platforms.

A pure-Python LLM inference engine and server with CUDA/HIP/Metal code generation, OpenAI-compatible API support, built-in RAG, and multi-GPU backend support.

Dream Server is an open-source stack that turns a PC, Mac, or Linux machine into a private AI server with local model inference, chat UI, voice, agents, workflows, RAG, and image generation. The page shows setup instructions, platform support, release notes, and a clear positioning for self-hosted use.

A desktop and web app with 51 interactive labs that teaches how modern AI works through hands-on exercises, lessons in plain or technical language, and optional local or cloud AI guidance.

AI-powered knowledge base for Terraform modules that supports semantic search, agentic composition, audit checks, and optimization from indexed repositories and conventions.