Search Results for "augmented"
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Showing 56 open source projects for "augmented"
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Raglite
RAGLite is a Python toolkit for Retrieval-Augmented Generation
Raglite is a lightweight framework for building Retrieval-Augmented Generation (RAG) pipelines with minimal configuration. It connects large language models to vector databases for context-aware responses, enabling developers to prototype and deploy RAG systems quickly. Raglite focuses on simplicity and modularity for fast experimentation. -
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Spring AI
An Application Framework for AI Engineering
...It focuses on production readiness by offering features such as configuration management, observability, and integration with Spring Boot applications. Spring AI also includes support for retrieval-augmented generation, enabling applications to connect language models with structured and unstructured data sources. Its architecture encourages modular design, making it easier to extend or swap components without rewriting large parts of the system. -
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go-datastructures
A collection of useful, performant, and threadsafe Go datastructures
Go-datastructures is a collection of useful, performant, and threadsafe Go datastructures. Interval tree for collision in n-dimensional ranges. Implemented via a red-black augmented tree. Extra dimensions are handled in simultaneous inserts/queries to save space although this may result in suboptimal time complexity. Intersection determined using bit arrays. In a single dimension, inserts, deletes, and queries should be in O(log n) time. Bitarray used to detect existence without having to resort to hashing with hashmaps. ... -
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KnowNote
A local-first AI knowledge base & NotebookLM alternative
...Unlike many NotebookLM alternatives that rely on Docker or cloud deployments, KnowNote runs natively on desktop platforms without complex setup, meaning all data stays local unless the user opts to integrate with self-managed or private LLM APIs. Its retrieval-augmented generation (RAG) system offers semantic search and traceable source references, and it supports multiple LLM providers through a flexible plugin-style provider architecture. -
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LLPhant
A comprehensive PHP Generative AI Framework
...The framework focuses on usability by offering straightforward APIs for tasks like embeddings, question answering, and vector search, which are commonly required in real-world applications. It includes support for vector stores, enabling developers to build retrieval-augmented generation systems using structured or unstructured data. LLPhant also allows integration with external services and tools, making it possible to extend model capabilities beyond text generation into actionable workflows. -
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Generative AI Examples
Generative AI Examples is a collection of GenAI examples
...Detailed framework of composable building blocks for state-of-the-art generative AI systems including LLMs, data stores, and prompt engines. Architectural blueprints of retrieval-augmented generative AI component stack structure and end-to-end workflows. A four-step assessment for grading generative AI systems around performance, features, trustworthiness and enterprise-grade readiness. -
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Watchdog
Python library and shell utilities to monitor filesystem events
...You can use the shell-command subcommand to execute shell commands in response to events. watchmedo can read tricks.yaml files and execute tricks within them in response to file system events. Tricks are actually event handlers that subclass watchdog.tricks.Trick and are written by plugin authors. Trick classes are augmented with a few additional features that regular event handlers don't need. The directory containing the tricks.yaml file will be monitored. Each trick class is initialized with its corresponding keys in the tricks.yaml file as arguments and events are fed to an instance of this class as they arrive. -
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LangChain for .NET
C# implementation of LangChain
...It also provides both low-level async APIs and higher-level chain abstractions, giving developers flexibility in how they structure their applications. With built-in support for retrieval-augmented generation and structured pipelines, LangChain .NET is designed for production-ready AI systems. -
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LangChainGo
LangChain for Go, the easiest way to write LLM-based programs in Go
...It supports multiple providers including OpenAI, Anthropic, Google, and local models, offering a unified interface for interacting with different backends. LangChainGo also includes support for embeddings, semantic search, and retrieval-augmented generation, enabling developers to build data-aware applications. With built-in abstractions for agents and tool usage, it enables the creation of systems that can reason, take actions, and interact with their environment. -
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Claude Cookbooks
A collection of notebooks/recipes showcasing ways of using Claude
...It serves as both a learning resource and a reference library, helping developers understand how to apply AI capabilities such as classification, summarization, and retrieval-augmented generation in real-world scenarios. The repository includes structured examples for integrating Claude with external tools, databases, and APIs, showcasing how to extend its functionality beyond basic text generation. It also covers advanced techniques like sub-agent orchestration, prompt optimization, and automated evaluation workflows. ... -
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PageIndex
Document Index for Vectorless, Reasoning-based RAG
PageIndex is an innovative open-source framework that reimagines retrieval-augmented generation (RAG) by eliminating conventional vector similarity search and instead building hierarchical semantic indexes that mirror a document’s natural structure. Rather than chunking text and embedding it into a vector database, PageIndex constructs a tree-structured index — similar to a detailed, AI-enhanced table of contents — that a large language model can traverse to locate the most relevant sections of long documents. ... -
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RAG Anything
RAG-Anything: All-in-One RAG Framework
RAG-Anything is an open-source unified framework that extends the Retrieval-Augmented Generation (RAG) paradigm to fully multimodal document and knowledge retrieval, enabling systems to ingest, parse, represent, and query rich content that includes text, images, tables, formulas, and other structured or visual elements. Traditional RAG systems are typically limited to text and cannot effectively work across heterogeneous document layouts, but RAG-Anything addresses this by modeling multimodal content in ways that preserve cross-modal relationships and semantic context, often treating content elements as interconnected knowledge entities rather than separate data silos. ... -
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OpenAI Agents JS
A lightweight, powerful framework for multi-agent workflows
openai-agents-js is the JavaScript/TypeScript version of the OpenAI Agents SDK, designed to give developers a lightweight but powerful framework for building agentic workflows, voice agents, and tool-augmented LLM systems in JS/TS environments. The SDK is provider-agnostic, meaning while it’s deeply compatible with OpenAI’s APIs, you can also adapt it to use other backends or extension layers. At its core, it introduces primitives like Agents, Tools, Guardrails, and Handoffs, letting you define structured multi-agent systems in a modular way. ... -
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ArUco
Augmented reality library based on OpenCV
ArUco is a minimal library for Augmented Reality applications based exclusively on OpenCV. Relies on b/w markers with codes that are detected by calling a single function. Trivial integration of your augmented reality applications with OpenGL and OGRE. See documentation at https://drive.google.com/file/d/1OiavRVYVJ-WH88sQg1LUsh8CuJZUQyrX/view?usp=sharing -
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OpenAI .NET
The official .NET library for the OpenAI API
...It supports tool/function calling, structured outputs via JSON schema, audio input/output, image generation, embeddings, Whisper transcription, and assistants with retrieval augmented generation. -
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Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
...Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before they pass into a neural network (if you use augmentation). The general recommendation is to use suitable augs for your data and as many as possible, then after some time of training disable the most destructive (for image) augs. You can turn on automatic mixed precision with one flag --amp. You should expect it to be 33% faster and save up to 40% memory. ... -
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ATOMIC is a Cross-platform Authoring Tool software for Augmented Reality Applications Is a Front-end for the ARToolKit library , developed for non-programmers, for create small and simple, AR applications. + info: www.sologicolibre.org/en/
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Ox: Attribute Grammar Compiling System
Ox is an attribute-grammar evaluator generator.
Ox is an attribute grammar compiling system that augments Lex and Yacc specifications with definitions of synthesized and inherited attributes written in a combination of Ox and C/C++ syntax. From these augmented specifications, Ox generates ordinary Lex and Yacc specifications that build and decorate attributed parse trees. The user can specify parse-tree traversals for easy ordering of side effects such as code generation. Ox handles the tedious and error-prone details of writing code for parse-tree management, so its use eases problems of security and maintainability associated with that aspect of translator development. -
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Rawdog
Generate and auto-execute Python scripts in the cli
An CLI assistant that responds by generating and auto-executing a Python script. Rawdog (Recursive Augmentation With Deterministic Output Generations) is a novel alternative to RAG (Retrieval Augmented Generation). Rawdog can self-select context by running scripts to print things, adding the output to the conversation, and then calling itself again. -
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Sceneform Maintained SDK for Android
Sceneform Maintained is an ARCore Android SDK with Google Filament
Sceneform Maintained is an ARCore Android SDK with Google Filament as 3D engine. This is the continuation of the Archived Sceneform. Android Augmented Reality library: AR Model Viewer, Augmented Images, Augmented Faces, Video, Depth, Cloud Anchors, Instant Placement, Light Estimation and much more in Kotlin and Java. -
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NatML
High performance, cross-platform machine learning for Unity Engine
NatML allows developers to integrate machine learning into their Unity applications in under five lines of code with zero infrastructure. NatML completely removes the need to have any experience with machine learning in order to take advantage of the features it can provide. NatML takes advantage of hardware machine learning accelerators, like CoreML on iOS and macOS, NNAPI on Android, and DirectML on Windows. As a result, it is multiple times faster than Unity's own Barracuda engine. NatML... -
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Lullaby
A collection of C++ libraries designed to help teams
Lullaby is a modular collection of high-performance C++ libraries developed by Google for creating immersive virtual and augmented reality (VR/AR) experiences. It provides a flexible framework built around an Entity-Component-System (ECS) architecture, enabling developers to design efficient, scalable, and data-driven 3D applications. The framework includes tools and APIs for rendering full 3D environments, managing spatial audio, handling animations, and constructing interactive UI elements optimized for VR interfaces. ... -
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LR Parser and Lexer Generators: Fortran
LR parser generator and lexer generator for use in Fortran
The generator for LR parsers uses Pager's method, augmented with Tom Pennello's Forward Move Algorithm for error recovery. The grammar specifies identifiers for nodes in the abstract syntax tree, and the identifiers for tokens. It generates Fortran declarations for tree node identifiers and named constants that represent the PDA. The lexer generator accepts regular expressions and generates a DFA. -
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jeelizFaceFilter
Javascript/WebGL lightweight face tracking library
This JavaScript library detects and tracks the face in real time from the camera video feed captured with WebRTC. Then it is possible to overlay 3D content for augmented reality applications. We provide various demonstrations using main WebGL 3D engines. We have included in this repository the release versions of the 3D engines to work with a determined version (they are in /libs/<name of the engine>/). This library is lightweight and it does not include any 3D engine or third-party library. We want to keep it framework agnostic so the outputs of the library are raw, if the face is detected or not, the position and the scale of the detected face and the rotation Euler angles. ... -
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DockerSelenium
Selenium in Docker with Chrome and Firefox
The purpose of this project is to have Selenium running as simple and as fast as possible. This purpose is augmented by Zalenium a project which uses this one to provide docker-selenium(s) on-demand. Zalenium also forwards tests to a Cloud Provider (Sauce Labs, BrowserStack, TestingBot & LambdaTest) when necessary. Note SeleniumHQ/docker-selenium and this one share the same purpose however both projects have diverged considerably in the last two years.
