Stars
10 Lessons to Get Started Building AI Agents
code and resources used in the Going Meta sessions
This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
Letta (formerly MemGPT) is the stateful agents framework with memory, reasoning, and context management.
Hands on lab for Neo4j and Amazon Bedrock
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
This repository includes the IFCWebServer scripts to convert IFC models into Neo4j graph database.
A modular graph-based Retrieval-Augmented Generation (RAG) system
In this project I designed a knowledge graph focused on Napoleon's history. I built a RAG application using this data and improved the output of LLM using the relationship between nodes
Practical Gremlin - An Apache TinkerPop Tutorial
End to end solution for migrating CSV data into a Neo4j graph using an LLM for the data discovery and graph data modeling stages.
Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.
A Python client for the Unstructured Platform API
Library extending Jupyter notebooks to integrate with Apache TinkerPop, openCypher, and RDF SPARQL.
Chronos: Pretrained Models for Probabilistic Time Series Forecasting
img2table is a table identification and extraction Python Library for PDF and images, based on OpenCV image processing
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its go…
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
A playbook for systematically maximizing the performance of deep learning models.
3X speedup over Apple’s TensorFlow plugin by using Apache TVM on M1