tolo
Follow
Stars
The RAG Experiment Accelerator is a versatile tool designed to expedite and facilitate the process of conducting experiments and evaluations using Azure Cognitive Search and RAG pattern.
Render Jinja2 template block as HTML page fragments on Python web frameworks.
A suite of tools to develop RAG, semantic search, and other AI applications more easily with PostgreSQL
Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.
Background Music, a macOS audio utility: automatically pause your music, set individual apps' volumes and record system audio.
A curated list for Efficient Large Language Models
A toolkit to create optimal Production-readyRetrieval Augmented Generation(RAG) setup for your data
A simple CLI for interacting with macOS reminders
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and cont…
Home Office Digital repository of posters covering different topics - research, access needs, accessibility, design.
DSPy: The framework for programming—not prompting—language models
The RAG Genie, an LLM RAG prototype to test and evaluate your embeddings, chunk splitting strategies using Q&A and evaluations.
TinyChatEngine: On-Device LLM Inference Library
An input-component for controlling your app in natural language using an LLM though LangChain.dart
Convert a screenshot to a working Flutter app.
A collection of resources for learning DDD. All are free to access.
😎 Awesome list of tools and projects with the awesome LangChain framework
🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
Build LLM-powered Dart/Flutter applications.
Pragmatic and magic-free state management for Flutter
🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
Flutter Movies app with Riverpod (TMDB API)
Asteroids Game generated by Scott and Mark Learn to Code, commited directly as written, just after BUILD 2023 keynote. Many many thanks to Yanan Cai for her help and prompt engineering.
Nightly release of ControlNet 1.1