Search Results for "ekho-data" - Page 35
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Showing 3593 open source projects for "ekho-data"
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segyio
Fast Python library for SEGY files
Segyio is a small LGPL-licensed C library for easy interaction with SEG-Y and Seismic Unix formatted seismic data, with language bindings for Python and Matlab. Segyio is an attempt to create an easy-to-use, embeddable, community-oriented library for seismic applications. Features are added as they are needed; suggestions and contributions of all kinds are very welcome. -
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Tequila
A High-Level Abstraction Framework for Quantum Algorithms
Tequila is an abstraction framework for (variational) quantum algorithms. It operates on abstract data structures allowing the formulation, combination, automatic differentiation and optimization of generalized objectives. Tequila can execute the underlying quantum expectation values on state-of-the-art simulators as well as on real quantum devices. -
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Ultralytics
Ultralytics YOLO
Ultralytics is a comprehensive computer vision framework that provides state-of-the-art implementations of the YOLO (You Only Look Once) family of models, enabling developers to perform tasks such as object detection, segmentation, classification, tracking, and pose estimation within a unified system. It is designed to be fast, accurate, and easy to use, offering both command-line and Python-based interfaces for training, validation, and deployment of machine learning models. The framework... -
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VoxelMorph
Unsupervised Learning for Image Registration
VoxelMorph is an open-source deep learning framework designed for medical image registration, a process that aligns multiple medical scans into a common spatial coordinate system. Traditional image registration techniques typically rely on optimization procedures that must be executed separately for each pair of images, which can be computationally expensive and slow. VoxelMorph approaches the problem using neural networks that learn to predict deformation fields that transform one image so... -
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Natural Language Toolkit
NLTK Source
The Natural Language Toolkit (NLTK) is a widely used open-source Python library designed for working with human language data and building natural language processing (NLP) applications. It provides a comprehensive suite of modules, datasets, and tutorials that support both symbolic and statistical approaches to language processing. The toolkit includes implementations of many foundational NLP algorithms and utilities, enabling developers to perform tasks such as tokenization, stemming, parsing, classification, and semantic reasoning. ... -
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HolmesGPT
CNCF Sandbox Project
...The system aggregates signals from observability tools such as logs, metrics, alerts, and distributed traces, then analyzes them using large language models to identify potential root causes. Rather than requiring engineers to manually correlate large volumes of monitoring data, HolmesGPT automatically synthesizes evidence and presents explanations in natural language. The project is developed by Robusta and has been accepted as a Cloud Native Computing Foundation Sandbox project, highlighting its relevance to the cloud-native ecosystem. It is designed to operate as an automated troubleshooting assistant that can analyze incidents continuously and support on-call engineers during outages. -
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RAG Anything
RAG-Anything: All-in-One RAG Framework
...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. The system uses a multi-stage pipeline (e.g., document parsing, content analysis, knowledge graph construction, intelligent retrieval) so queries can navigate across modalities with deeper understanding and relevance. -
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WYGIWYH
A simple but powerful self-hosted finance tracker
WYGIWYH (What You Get Is What You Have) is a self-hosted, principles-first personal finance tracker built for people who prefer a simple, intuitive approach to tracking money without complicated budgets or categories. Based on a philosophy that you should use what you earn each month for that month, it helps you understand where your funds go while keeping savings clearly separated so they aren’t accidentally dipped into for everyday expenses. The app supports multiple currencies,... -
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Uncertainty Baselines
High-quality implementations of standard and SOTA methods
Uncertainty Baselines is a collection of strong, well-documented training pipelines that make it straightforward to evaluate predictive uncertainty in modern machine learning models. Rather than offering toy scripts, it provides end-to-end recipes—data input, model architectures, training loops, evaluation metrics, and logging—so results are comparable across runs and research groups. The library spans canonical modalities and tasks, from image classification and NLP to tabular problems, with baselines that cover both deterministic and probabilistic approaches. Techniques include deep ensembles, Monte Carlo dropout, temperature scaling, stochastic variational inference, heteroscedastic heads, and out-of-distribution detection workflows. ... -
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Changelog CI
Changelog CI is a GitHub Action that enables a project
...First, it tries to get the latest release from the repository (If available). Then, it checks all the pull requests/commits merged after the last release using the GitHub API. After that, it parses the data and generates the changelog. It is able to use Markdown or reStructuredText to generate a Changelog. Finally, It writes the generated changelog at the beginning of the CHANGELOG.md/CHANGELOG.rst (or user-provided filename) file. In addition to that, if a user provides a configuration file (JSON/YAML), Changelog CI parses the user-provided configuration file and renders the changelog according to user's configuration. -
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Restaurant Management System
Restaurant Management System written in Python using Tkinter
...Storing the restaurant configuration: configure facility name, table/seat counts, and menu with the ability to modify them in the future. Users will have the ability to modify the data through the “Configure Facility/Menu” section of the app. Create bills for the chef (backend): The application will first send the order to the kitchen for cooks to see, prepare, and fulfill the order. -
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DeepSeed
Deep learning optimization library making distributed training easy
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. DeepSpeed delivers extreme-scale model training for everyone, from data scientists training on massive supercomputers to those training on low-end clusters or even on a single GPU. Using current generation of GPU clusters with hundreds of devices, 3D parallelism of DeepSpeed can efficiently train deep learning models with trillions of parameters. With just a single GPU, ZeRO-Offload of DeepSpeed can train models with over 10B parameters, 10x bigger than the state of arts, democratizing multi-billion-parameter model training such that many deep learning scientists can explore bigger and better models. ... -
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Piccolo
A fast, user friendly ORM and query builder which supports asyncio
Piccolo is a modern, fast, and type-safe ORM for Python, designed with developer ergonomics in mind. It provides a clean syntax for defining schemas and building queries while supporting both sync and async execution. With built-in admin tools and rich introspection, Piccolo is suitable for web apps, APIs, and small-to-medium scale backends that prioritize clarity and speed. -
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pgai
A suite of tools to develop RAG, semantic search, and other AI apps
pgai is a suite of PostgreSQL extensions developed by Timescale to empower developers in building AI applications directly within their databases. It integrates tools for vector storage, advanced indexing, and AI model interactions, facilitating the development of applications like semantic search and Retrieval-Augmented Generation (RAG) without leaving the SQL environment. -
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Xiyan MCP Server
A Model Context Protocol (MCP) server
The XiYan MCP Server is a Model Context Protocol (MCP) server that enables natural language queries to databases, powered by XiYan-SQL, a state-of-the-art text-to-SQL model. It allows users to interact with databases using conversational language, simplifying data retrieval processes. -
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AutoPkg
Automating packaging and software distribution on macOS
AutoPkg is a system that automatically prepares software for distribution to managed clients. Recipes allow you to specify a series of simple actions which combined together can perform complex tasks, similar to Automator workflows or Unix pipes. -
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fugue
A unified interface for distributed computing
Fugue is a unified interface for distributed computing that lets users execute Python, Pandas, and SQL code on Spark, Dask, and Ray with minimal rewrites. -
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DrissionPage
Python based web automation tool. Powerful and elegant
DrissionPage is a Python-based automation framework that blends the capabilities of Selenium for browser automation with Requests-HTML for fast, headless web data extraction. It enables seamless switching between browser-controlled and headless HTTP sessions within the same interface. Ideal for web scraping, testing, and automation, DrissionPage is lightweight and highly efficient, offering more flexibility than standard Selenium or Requests usage alone. -
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OpenLLMetry
Open-source observability for your LLM application
The repo contains standard OpenTelemetry instrumentations for LLM providers and Vector DBs, as well as a Traceloop SDK that makes it easy to get started with OpenLLMetry, while still outputting standard OpenTelemetry data that can be connected to your observability stack. If you already have OpenTelemetry instrumented, you can just add any of our instrumentations directly. -
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AgentOps
Python SDK for agent monitoring, LLM cost tracking, benchmarking, etc.
...We built the tools so you don't have to. Visually track events such as LLM calls, tools, and multi-agent interactions. Rewind and replay agent runs with point-in-time precision. Keep a full data trail of logs, errors, and prompt injection attacks from prototype to production. Native integrations with the top agent frameworks. -
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LangKit
An open-source toolkit for monitoring Language Learning Models (LLMs)
LangKit is an open-source text metrics toolkit for monitoring language models. It offers an array of methods for extracting relevant signals from the input and/or output text, which are compatible with the open-source data logging library whylogs. Productionizing language models, including LLMs, comes with a range of risks due to the infinite amount of input combinations, which can elicit an infinite amount of outputs. The unstructured nature of text poses a challenge in the ML observability space - a challenge worth solving, since the lack of visibility on the model's behavior can have serious consequences. -
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Google Gen AI SDK
Google Gen AI Python SDK provides an interface for developers
...It is intended to replace older Gemini Python SDK patterns with a more unified and actively maintained API surface. The project is useful for application developers, data scientists, AI engineers, and backend teams building Gemini-powered features. Its main value is providing a supported, production-ready Python interface for Google’s current generative AI ecosystem. -
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Claw Compactor
14-stage Fusion Pipeline for LLM token compression
...It addresses the challenge of finite context windows in language models by compressing or summarizing historical interactions while preserving essential information. The system works by transforming older conversation data into condensed representations that maintain continuity without exceeding token limits. This approach allows long-running agent sessions to continue operating efficiently without losing critical context. It is especially useful in autonomous workflows where agents accumulate large volumes of interaction history over time. The project aligns with broader strategies in AI systems that balance memory retention with computational constraints. ... -
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GitDiagram
AI tool that converts GitHub repositories into interactive diagrams
...Users can interact with the generated diagrams by clicking components to navigate directly to related files or directories within the repository. GitDiagram combines a modern web frontend with a backend service that processes repository data and generates diagrams dynamically. -
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OpenVINO Notebooks
Jupyter notebook tutorials for OpenVINO
...The tutorials also illustrate how OpenVINO integrates with models from frameworks like PyTorch, TensorFlow, and ONNX to accelerate inference workloads. Many notebooks include end-to-end examples that show how to prepare input data, load optimized models, run inference, and visualize results. The project is particularly useful for developers who want to learn how to optimize machine learning inference pipelines for production environments.