Practical reporting on AI systems, tools, and engineering execution.
A collection of 30 runnable Jupyter notebooks that demonstrate how to add persistent memory to LLM‑driven agents, covering buffers, vector stores, and production patterns.
A plugin that brings Gemini Helper's workflow automation to Obsidian using any local LLM, with a visual node editor and AI‑assisted creation.
A collection of 22 Jupyter Notebook tutorials covering prompt engineering techniques, from basic templates to advanced methods like chain-of-thought and tree-of-thought, designed for developers and AI practitioners.
Starcat syncs starred repos into a local SQLite cache, adds tags and notes, and layers a RAG workspace on top — all running locally on macOS 15+.
This GitHub bibliography organizes long-context LLM research by technique, with a companion survey and category-specific reading lists for engineers evaluating context architectures.
AgentMemory gives AI agents persistent, structured memory across sessions — with team isolation, multi-level distillation, and a self-hosted stack that runs on your infrastructure.
A comprehensive repository offering 50+ GenAI agent tutorials and implementations, plus a structured course that guides builders from prototype to production‑grade systems.
A widely cited pointer list of AI agent frameworks and tools; useful for discovery, but not for production build decisions without verifying each entry's maintenance and claims.
A self-hosted canvas for generating and refining diagrams through conversation, with direct drawing tools, automatic saves, and Excalidraw export.
By replacing PyTorch with the ONNX Runtime, Qdrant's FastEmbed provides a lightweight Python library for generating dense, sparse, and multimodal embeddings on CPU-constrained production runtimes.
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