hikarilabs/local-agentic-rag-gemma4-e4b
A local agentic RAG implementation using Gemma model + embeddings
Repositories
hikarilabs/semantido
Semantic layer for SQLAlchemy that auto-generates LLM ready schema with rich semantic metadata for text-to-SQL systems and LLM powered database interactions.
hikarilabs/ai-engineering-from-scratch
Learn it. Build it. Ship it for others.
hikarilabs/cohort-004-project
Cohort 004 project
hikarilabs/ossie-website
Apache Ossie Website
hikarilabs/semantido-lenses-sandbox
hikarilabs/ossie
Apache Ossie, industry wide specification effort to standardize how we exchange semantic metadata across analytics, AI and BI platforms, providing a vendor neutral, single source of truth for semantic data
hikarilabs/Context-Engineering-for-Multi-Agent-Systems
This repository provides the companion Jupyter Notebooks for the book Context-Engineering for Multi-Agent Systems. It technically details the progressive construction of a Context Engine moving from simple prompts to foundational concepts to a production-ready system semantic blueprint. The code is a guide to building Multi-Agent Systems (MAS)
hikarilabs/trade-reporting-benchmark
Benchmarking semantic layers against a trade-reporting schema
hikarilabs/ai-from-scratch
hikarilabs/pydata-london-2026-ui
hikarilabs/pydata-london-2026-sql
hikarilabs/sqlalchemy-semantic-layer
A semantic layer implementation base on sqlalchemy
hikarilabs/learn-cicd-typescript-starter
The typescript starter code for the "Learn CICD" course on Boot.dev
hikarilabs/learn-docker
hikarilabs/learn-pub-sub-typescript-starter
learn-pub-sub-typescript-starter
hikarilabs/machine-learning-systems-design
A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems", which is `dmls-book`
hikarilabs/awesome-generative-ai-guide
A one stop repository for generative AI research updates, interview resources, notebooks and much more!
hikarilabs/d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
hikarilabs/transformers
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
hikarilabs/nn-zero-to-hero
Neural Networks: Zero to Hero
hikarilabs/Unlocking-Data-with-Generative-AI-and-RAG-Second-Edition
Unlocking Data with Generative AI and RAG, Second Edition, published by Packt
hikarilabs/Building-Natural-Language-and-LLM-Pipelines
Building RAG and Agentic Applications with Haystack 2.0, RAGAS and LangGraph 1.0 published by Packt
hikarilabs/Agentic-Design-Patterns
Agentic Design Patterns: A Hands-On Guide to Building Intelligent Systems by Antonio Gulli
hikarilabs/agentic-retail-foundations
Source code for the Foundations of Agentic AI for Retail Book
hikarilabs/Python-Machine-Learning-by-Example-Fourth-Edition
Python Machine Learning by Example, Fourth Edition
hikarilabs/basic-ai-agent
hikarilabs/hoopla
hikarilabs/python-test-driven-development
Exercises for learning TDD in Python
hikarilabs/A-Curated-List-of-ML-System-Design-Case-Studies
This repository contains a curated collection of 300+ case studies from over 80 companies, detailing practical applications and insights into machine learning (ML) system design. The contents are organized to help you easily find relevant case studies based on industry or specific ML use cases.