CrawlLama 🦙 is an local AI agent that answers questions via Ollama and integrates web- and RAG-based research.
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Updated
Aug 7, 2026 - Python
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. Shared memory layer for any MCP client — Claude Code, Codex, Kimi, Antigravity (agy). Hybrid retrieval, session continuity, 43 MCP tools. Local-first, LanceDB-backed.
Terminal based chat implementation of ARK agent
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
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.
Sub-linear knowledge retrieval via quantum-inspired hyperdimensional folded space (0.88ms @ 100% accuracy)
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.
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
Notebook examples for using OpenAI's Assistants API with the file search (knowledge retrieval) functionality.
⚡️ Local RAG API using FastAPI + LangChain + Ollama | Upload PDFs, DOCX, CSVs, XLSX and ask questions using your own documents — fully offline!
KakaoBank public-document corpus and manual tau3-style banking knowledge tasks.
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-first, multilingual evidence-backed memory sidecar for AI agents.
OllamaMulti-RAG 🚀 is a multimodal AI chat app combining Whisper AI for audio, LLaVA for images, and Chroma DB for PDFs, enhanced with Ollama and OpenAI API. 📄 Built for AI enthusiasts, it welcomes contributions—features, bug fixes, or optimizations—to advance practical multimodal AI research and development collaboratively.
Visualize and diagnose OpenClaw context windows to identify token usage, file health, and available space for conversation.
Wenmai Search — self-hosted, traceable hybrid document retrieval with REST, MCP, and Web UI
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