“RAG”

Implement local Retrieval-Augmented Generation using Room and Vector embeddings.

Augment model context with external factual retrieval through query reformulation, hybrid dense-sparse indexing, re-ranking, and citation grounding.

Knowledge base assistant with document retrieval and citation

deciding whether to stuff documents into a long window.

first end-to-end chain after chunks exist.

Semantic boundary preserving text chunker maintaining markdown headers, code fences, and paragraphs

Answer a factual question from institutional docs, memory, and ingested history.

Design and evaluate retrieval-augmented generation systems end-to-end.

Retrieves grounded answers from an approved Obsidian vault using bounded search, source citations, and explicit uncertainty.

Lightweight self-hosted RAG knowledge base with hybrid retrieval and cited answers.

Finalize guard for review, verification, anchoring, and metrics, including RAG/skills change branch.

Implement retrieval-augmented generation with document indexing and search.

Grok FAF

faf.one

Persistent project context for xAI Grok.

Databricks Vector Search endpoints and indexes for RAG and semantic search; covers index types, search modes, end-to-end RAG patterns

Design Retrieval-Augmented Generation systems for private data.

Ingest, manage, and retrieve documents for RAG-powered AI applications

MCP RAG: index PDFs, repos, YouTube, Discord, text; optional YouTube vision; query with citations.

Open-source, GPL-3.0 platform for building agents with RAG pipelines, a workflow engine and MCP tool use, run from a Docker container

给定 PMID / PMCID 取结构化全文（BioC XML/JSON）。封装 NLM BioC PubMed API（标题+摘要）和 BioC PMC OA API（开放获取全文），输出按章节切分的段落、表格上下文、RAG 友好 chunk。适合大批量入向量库。触发词：全文抽取 / BioC / RAG 入库…

AI Readiness Kit

silverbackmarketing

Generate 18 AI readiness files (llms.txt, ai.txt, RAG indexes, schema) for any website.

Local web search with multi-engine deep research and on-device re-ranking.

Cross-session memory and hybrid RAG over your notes and docs.

AI 系统数据安全测试方法论。当需要评估 LLM/AI 系统的数据泄露风险、训练数据安全、 或 RAG/向量库数据完整性时触发。覆盖: System Prompt 泄露(元 Prompt/角色扮演/关键字定位)、 训练数据推导与提取、成员推断攻击、模型反演攻击、RAG 数据投毒、API 信息泄露、…

Web 与 AI 跨域攻击链方法论。当目标系统同时包含传统 Web 应用和 AI/LLM 组件、 需要评估 Web 漏洞对 AI 系统的影响或 AI 漏洞对 Web 系统的影响时触发。 覆盖双向攻击链: Web→AI(XSS 窃取对话/SSRF 调用模型 API/SQLi 污染 RAG/文件上传 RAG 投毒) 和…