Search Results for "augmented" - Page 6
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Showing 150 open source projects for "augmented"
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RAGs
Build ChatGPT over your data, all with natural language
RAGs is an open-source application designed to simplify the creation of retrieval-augmented generation pipelines through an interactive interface. Built with Streamlit and powered by the LlamaIndex ecosystem, the tool allows users to construct AI assistants that answer questions using their own data sources. Instead of requiring extensive programming knowledge, the application allows users to configure and build a RAG system using natural language instructions. -
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LLM Applications
A comprehensive guide to building RAG-based LLM applications
LLM Applications is a practical reference repository that demonstrates how to build production-grade applications powered by large language models. The project focuses particularly on Retrieval-Augmented Generation architectures, which combine language models with external knowledge sources to improve accuracy and reliability. It provides step-by-step guidance for constructing systems that ingest documents, split them into chunks, generate embeddings, index them in vector databases, and retrieve relevant context during inference. ... -
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Kanaries RATH
Next generation of automated data exploratory analysis visualization
RATH is not just an open-source alternative to Data Analysis and Visualization tools such as Tableau, but it automates your Exploratory Data Analysis workflow with an Augmented Analytic engine by discovering patterns, insights, causals and presents those insights with powerful auto-generated multi-dimensional data visualization. -
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LLM Cookbook
LLM Introduction Tutorial for Developers, Chinese version
...The project adapts and reproduces content from widely known LLM developer courses and reorganizes it into a structured learning path tailored for developers who want to build real AI applications. It covers the essential topics required to start working with LLM APIs and frameworks, including prompt engineering, application architecture, retrieval-augmented generation, and system evaluation. The repository includes practical coding examples that demonstrate how to integrate language models with tools such as LangChain and other common AI development frameworks. It also provides curated learning modules that guide users from introductory concepts to more advanced topics like building conversational systems or knowledge-based assistants. -
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SOD
An Embedded Computer Vision & Machine Learning Library
SOD is an embedded, modern cross-platform computer vision and machine learning software library that expose a set of APIs for deep-learning, advanced media analysis & processing including real-time, multi-class object detection and model training on embedded systems with limited computational resource and IoT devices. SOD was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in open source as well as commercial products.... -
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ParlAI
A framework for training and evaluating AI models
...It provides a unified interface—agents, teachers, and worlds—so the same model can be trained on multi-turn chit-chat, question answering, task-oriented dialogue, retrieval, or safety-focused datasets without changing core code. The library integrates tightly with PyTorch and supports both generative and retrieval-augmented models, along with utilities for multitask training and model selection. A large set of built-in tasks and dataset loaders (with consistent preprocessing and metrics) makes it easy to compare methods under shared conditions. Tools for distributed training, mixed precision, and model zoos help scale experiments from laptops to multi-GPU clusters. -
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Paul Graham GPT
RAG on Paul Graham's essays
...The repo stores the full text of his essays (chunked), uses embeddings (e.g. via OpenAI embeddings) to allow semantic search over that corpus, and hosts a chat interface that combines retrieval results with LLM-based answering — enabling RAG (retrieval-augmented generation) over a fixed dataset. The app uses a Postgres database (with pgvector) hosted on Supabase for its embedding store, making the backend relatively simple and accessible, and the frontend is again built with Next.js/TypeScript for a modern responsive UI. By pulling together search and chat, it creates a useful tool both for readers who want to revisit or explore Paul Graham’s ideas thematically, and for learners or researchers who want to query specific essays or concepts quickly. -
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Clarity AI
A Perplexity clone
Clarity AI is an AI-powered “search + chat” tool (similar in spirit to a simplified “AI-powered search engine / assistant”) created by Mckay Wrigley — intended to let users ask questions, get answers, and explore information via conversational interface rather than traditional search. The codebase (TypeScript) leverages LLMs / embeddings to process user queries, retrieve relevant data or context, and respond conversationally; this makes it useful as a personal knowledge assistant, research... -
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GPT-NeoX
Implementation of model parallel autoregressive transformers on GPUs
This repository records EleutherAI's library for training large-scale language models on GPUs. Our current framework is based on NVIDIA's Megatron Language Model and has been augmented with techniques from DeepSpeed as well as some novel optimizations. We aim to make this repo a centralized and accessible place to gather techniques for training large-scale autoregressive language models, and accelerate research into large-scale training. For those looking for a TPU-centric codebase, we recommend Mesh Transformer JAX. ... -
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Bullet Physics SDK
Real-time collision detection and multi-physics simulation for VR
...TDS can be trained using Deep Reinforcement Learning, or using Gradient based optimization (for example LFBGS). In addition, the simulator can be entirely run on CUDA for fast rollouts, in combination with Augmented Random Search. This allows for 1 million simulation steps per second. It is highly recommended to use PyBullet Python bindings for improved support for robotics, reinforcement learning and VR. Use pip install pybullet and checkout the PyBullet Quickstart Guide. -
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SimSiam
PyTorch implementation of SimSiam
...The project introduces a minimalist approach to self-supervised learning that avoids negative pairs, momentum encoders, or large memory banks—key complexities of prior contrastive methods. SimSiam learns image representations by maximizing similarity between two augmented views of the same image through a Siamese neural network with a stop-gradient operation, preventing feature collapse. This elegant yet effective design achieves strong results in unsupervised learning benchmarks such as ImageNet without requiring contrastive losses. The repository provides scripts for both unsupervised pre-training and linear evaluation, using a ResNet-50 backbone by default. ... -
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Ciphey
Decrypt encryptions without knowing the key or cipher
Fully automated decryption/decoding/cracking tool using natural language processing & artificial intelligence, along with some common sense. You don't know, you just know it's possibly encrypted. Ciphey will figure it out for you. Ciphey can solve most things in 3 seconds or less. Ciphey aims to be a tool to automate a lot of decryptions & decodings such as multiple base encodings, classical ciphers, hashes or more advanced cryptography. If you don't know much about cryptography, or you want... -
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DensePose
A real-time approach for mapping all human pixels of 2D RGB images
...The repository includes the DensePose network architecture, training code, pretrained models, and dataset tools for annotation and visualization. DensePose is widely used in augmented reality, motion capture, virtual try-on, and visual effects applications because it enables real-time 3D human mapping from 2D inputs. The model architecture builds on Mask R-CNN, using additional regression heads to predict UV coordinates that map image pixels to 3D surfaces. -
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InfoGAN
Code for reproducing key results in the paper
The InfoGAN repository contains the original implementation used to reproduce the results in the paper “InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets”. InfoGAN is a variant of the GAN (Generative Adversarial Network) architecture that aims to learn disentangled and interpretable latent representations by maximizing the mutual information between a subset of the latent codes and the generated outputs. That extra incentive encourages the... -
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OSAR Appliances
The OSAR Linux Image for Augmented Reality and Computer Vision
The OpenSUSE Augmented Reality (OSAR) distribution is the first GNU / Linux appliance created for the exclusive development of applications with augmented reality technology and games with computer vision. -
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QVision: Computer Vision Library for Qt
Computer vision and image processing library for Qt.
This library contains among other things a set of graphical widgets for video output, performance evaluation and augmented reality. The library also provides classes for several data types usually required by computer vision and image processing applications such as vectors, matrices, quaternions and images. Thanks to a large number of wrapper functions these objects can be used with highly efficient functionality from third party libraries such as OpenCV, GNU Scientific Library, Computational Geometry Algorithms Library, Intel's Math Kernel Library and Integrated Performance Primitives, the Octave library, etc... -
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asdnetworks
Framework used to represents English grammars graphically
Augmented Syntax Diagrams (ASDs) provide a framework to represent grammars of natural languages as directed graphs -- that is, as networks of nodes and edges. Nodes represent instances (or usages) of words and phrase types in a language such as English. -
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Swarm Wars
Safety in numbers.
...They can attack and repair other organisms. They can select mates, and they can gather and distribute food and material. This behavior is controlled by a genetically evolved neural net augmented with online back propagation learning. The back propagation learning uses a reward vector and plasticity matrix that is evolved as part of the genome. Long story short, the AI is pretty frickin' sophisticated. Players can take control of organisms, trade resources and organisms in a market, and aid evolution by selective breeding. -
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OpenCV-AR is a software library used for Augmented Reality development. It is targeted on Linux, though it is also able to work on Windows platform. It is an alternative to ARToolKit for Augmented Reality application development.
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Augmented Syntax Diagrams (ASD) provide a way to represent grammars of natural languages as directed graphs
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Augmented Syntax Diagrams are an alternative to natural language grammar rules expressed as strings. They are also suitable for left-corner bottom-up parsing. Prof. Jim Mason developed an editor (ASDEditor) in Java to create and edit ASD grammars.
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Unlimited-OCR
Layout-aware OCR model for multilingual document understanding
...It supports multilingual recognition, robust handling of noisy or distorted images, and integration into document AI pipelines. Built for practical deployment, Unlimited-OCR can serve as the foundation for document indexing, retrieval-augmented generation, knowledge extraction, and intelligent document processing. -
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NuMarkdown-8B-Thinking
Reasoning-powered OCR VLM for converting complex documents to Markdown
NuMarkdown-8B-Thinking is the first reasoning OCR vision-language model (VLM) designed to convert documents into clean Markdown optimized for retrieval-augmented generation (RAG). Built on Qwen 2.5-VL-7B and fine-tuned with synthetic Doc → Reasoning → Markdown examples, it generates thinking tokens before producing the final Markdown to better handle complex layouts and tables. It uses a two-phase training process: supervised fine-tuning (SFT) followed by reinforcement learning (GRPO) with a layout-centric reward for accuracy on challenging documents. ... -
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bge-large-en-v1.5
BGE-Large v1.5: High-accuracy English embedding model for retrieval
BAAI/bge-large-en-v1.5 is a powerful English sentence embedding model designed by the Beijing Academy of Artificial Intelligence to enhance retrieval-augmented language model systems. It uses a BERT-based architecture fine-tuned to produce high-quality dense vector representations optimized for sentence similarity, search, and retrieval. This model is part of the BGE (BAAI General Embedding) family and delivers improved similarity distribution and state-of-the-art results on the MTEB benchmark. ... -
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Mistral Large 3 675B Instruct 2512 Eagle
Speculative-decoding accelerator for the 675B Mistral Large 3
...The Eagle variant is specialized rather than standalone, serving as a performance accelerator for production-grade assistants, agentic workflows, long-context applications, and retrieval-augmented reasoning pipelines. It supports the same multilingual, system-prompt-aligned, and function-calling behavior as the main instruct model when used in the recommended server-client configuration.
