knowledge-retrieval

CrawlLama 🦙 is an local AI agent that answers questions via Ollama and integrates web- and RAG-based research.

AI-powered multi-agent medical assistant with a deterministic safety layer — crisis detection, refused-topic hard-stops, dosage grounding, and post-generation diagnosis verification running before and after every LLM call, backed by parallel RAG, Wikipedia, and Tavily retrieval with symptom and drug-question routing.

Stateful AI Agent for Knowledge Extraction

One memory, every terminal — a shared memory layer for any MCP client.

Terminal based chat implementation of ARK agent

GenPark skill: Automate enterprise project management and query workspace knowledge bases using ClickUp's hierarchy APIs.

PromptWeaver: RAG Edition helps design effective prompts for Traditional, Hybrid, and Agentic RAG systems. It offers templates, system prompts, and best practices to improve accuracy, context use, and LLM reasoning.

AgriIR: Configurable RAG framework for domain-specific knowledge retrieval in agriculture. Features 6-stage pipeline, deterministic citations, and domain-specific agents. ECIR'26.

(ACL 2026 Main) Mitigating Legal Hallucinations via Symbolic Constraints and Analogical Precedents

Self-healing RAG system that retrieves, verifies, and grades its own answers. Automatically rewrites queries and retries when outputs are weak, ensuring accurate, hallucination-free responses.

Sub-linear knowledge retrieval via quantum-inspired hyperdimensional folded space (0.88ms @ 100% accuracy)

A local Retrieval-Augmented Generation (RAG) system for answering questions about TouchDesigner using wiki pages, tutorials, and other structured or semi-structured content. Powered by FAISS and local LLMs via Ollama.

Notebook examples for using OpenAI's Assistants API with the file search (knowledge retrieval) functionality.

Code to make any AI have unlimited context persistent memory. In the example, a software for any AI to read the Uniform Commercial Code of Michigan. A document of 220,000 tokens

Project context and memory for coding agents.

Knowledge retrieval control plane for scoped and governed context delivery.

Corrective RAG with LangGraph: evaluates retrieval quality, routes to web search when needed, refines context, and generates grounded answers.

QueryVault is a robust RAG system for structured Q&A data. It ingests JSON files, embeds content via ChromaDB, and serves context-aware answers using FastAPI and Google Gemini. With a modular design and CLI tools, it's built for scalable, secure AI-powered knowledge retrieval.

⚡️ Local RAG API using FastAPI + LangChain + Ollama | Upload PDFs, DOCX, CSVs, XLSX and ask questions using your own documents — fully offline!

Self-RAG chatbot with LangGraph that retrieves from internal PDFs, verifies grounding (IsSUP), checks usefulness (IsUSE), and iteratively rewrites queries to improve answer quality.