Search Results for "oorexx source code" - Page 27
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Showing 2294 open source projects for "oorexx source code"
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Add Two Lines of Code. Get Full APM.Works out of the box for Rails, Django, Express, Phoenix, and more. Monitoring exceptions and performance in no time.
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Covalent workflow
Pythonic tool for running machine-learning/high performance workflows
Covalent is a Pythonic workflow tool for computational scientists, AI/ML software engineers, and anyone who needs to run experiments on limited or expensive computing resources including quantum computers, HPC clusters, GPU arrays, and cloud services. Covalent enables a researcher to run computation tasks on an advanced hardware platform – such as a quantum computer or serverless HPC cluster – using a single line of code. Covalent overcomes computational and operational challenges inherent... -
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nbstripout
strip output from Jupyter and IPython notebooks
Opens a notebook, strips its output, and writes the outputless version to the original file. Useful mainly as a git filter or pre-commit hook for users who don't want to track output in VCS. This does mostly the same thing as the Clear All Output command in the notebook UI. You can download and install the latest version of nbstripout from PyPI, the Python package index. Strip output from IPython / Jupyter / Zeppelin notebook (modifies the file in-place). Usually, nbstripout is installed per... -
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pre-commit-hooks
Some out-of-the-box hooks for pre-commit
Some out-of-the-box hooks for pre-commit. Using pre-commit-hooks with pre-commit. Instead of loading the files, simply parse them for syntax. A syntax-only check enables extensions and unsafe constructs which would otherwise be forbidden. Using this option removes all guarantees of portability to other yaml implementations. Detect symlinks which are changed to regular files with a content of a path that that symlink was pointing to. This usually happens on Windows when a user clones a... -
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pep484 stubs for Django
PEP-484 stubs for Django
This package contains type stubs and a custom mypy plugin to provide more precise static types and type inference for Django framework. Django uses some Python "magic" that makes having precise types for some code patterns problematic. This is why we need this project. The final goal is to be able to get precise types for the most common patterns. We are independent from Django at the moment. There's a proposal to merge our project into the Django itself. You can show your support by liking... -
Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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Django Lifecycle Hooks
Declarative model lifecycle hooks, an alternative to Signals
This project provides a @hook decorator as well as a base model and mixin to add lifecycle hooks to your Django models. Django's built-in approach to offering lifecycle hooks is Signals. However, my team often finds that Signals introduce unnecessary indirection and are at odds with Django's "fat models" approach. Django Lifecycle Hooks supports Python 3.7, 3.8 and 3.9, Django 2.0.x, 2.1.x, 2.2.x, 3.0.x, 3.1.x, and 3.2.x. For simple cases, you might always want something to happen at a... -
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django-helpdesk
A Django application to manage tickets for an internal helpdesk
A Django application to manage tickets for an internal helpdesk. Formerly known as Jutda Helpdesk. django-helpdesk was formerly known as Jutda Helpdesk, named after the company which originally created it. As of January 2011 the name has been changed to reflect what it really is: a Django-powered ticket tracker with contributors reaching far beyond Jutda. django-helpdesk includes a basic demo Django project so that you may easily get started with testing or developing django-helpdesk. The... -
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Determined
Determined, deep learning training platform
The fastest and easiest way to build deep learning models. Distributed training without changing your model code. Determined takes care of provisioning machines, networking, data loading, and fault tolerance. Build more accurate models faster with scalable hyperparameter search, seamlessly orchestrated by Determined. Use state-of-the-art algorithms and explore results with our hyperparameter search visualizations. Interpret your experiment results using the Determined UI and TensorBoard, and... -
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BentoML
Unified Model Serving Framework
BentoML simplifies ML model deployment and serves your models at a production scale. Support multiple ML frameworks natively: Tensorflow, PyTorch, XGBoost, Scikit-Learn and many more! Define custom serving pipeline with pre-processing, post-processing and ensemble models. Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference... -
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scikit-image
Image processing in Python
scikit-image is a collection of algorithms for image processing. It is available free of charge and free of restriction. We pride ourselves on high-quality, peer-reviewed code, written by an active community of volunteers. scikit-image builds on scipy.ndimage to provide a versatile set of image processing routines in Python. This library is developed by its community, and contributions are most welcome! Read about our mission, vision, and values and how we govern the project. Major proposals... -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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Google Spreadsheets Python
Google Sheets Python API
gspread is a Python API for Google Sheets. A service account is a special type of Google account intended to represent a non-human user that needs to authenticate and be authorized to access data in Google APIs [sic]. Since it’s a separate account, by default it does not have access to any spreadsheet until you share it with this account. Just like any other Google account. To access spreadsheets via Google Sheets API you need to authenticate and authorize your application. Older versions of... -
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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,... -
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Faker for Python
Python package that generates fake data for you
Faker is a Python package that generates fake data for you. Whether you need to bootstrap your database, create good-looking XML documents, fill-in your persistence to stress test it, or anonymize data taken from a production service, Faker is for you. Starting from version 4.0.0, Faker dropped support for Python 2 and from version 5.0.0 only supports Python 3.6 and above. If you still need Python 2 compatibility, please install version 3.0.1 in the meantime, and please consider updating... -
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TaskingAI
Open platform for building, deploying, and managing LLM agents
TaskingAI is an open source platform designed to simplify the development and deployment of applications powered by large language models. It follows a Backend as a Service approach, allowing developers to separate AI logic from frontend product development while maintaining a structured and scalable workflow. TaskingAI integrates hundreds of language models from multiple providers into a unified system, enabling developers to switch models or combine capabilities without major reconfiguration. ... -
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Advanced NLP with spaCy
Advanced NLP with spaCy: A free online course
...It also demonstrates how spaCy pipelines work and how developers can extend them with custom components and training data. The course is structured as a hands-on learning environment where students can run code examples, experiment with NLP techniques, and build practical language processing applications. Because spaCy is widely used in production environments, the course emphasizes industrial-strength NLP workflows and best practices. -
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Dagger
Containerized automation engine for programmable CI/CD workflows
Dagger is an open source automation engine designed to build, test, and deliver software in a consistent and programmable way. It enables developers to define software delivery workflows using code instead of complex shell scripts or configuration files. Dagger executes tasks inside containers, ensuring that automation runs in identical environments across local machines, CI servers, or cloud infrastructure. -
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seq2seq-couplet
Play couplet with seq2seq model
...The repository also points users to an external dataset source and documents vocabulary formatting requirements for custom datasets, showing that it is meant for both experimentation and extension. -
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Lagent
A lightweight framework for building LLM-based agents
Lagent is a lightweight open-source framework designed to help developers build autonomous agents powered by large language models. The framework provides tools and abstractions that allow language models to interact with external tools, execute tasks, and perform multi-step reasoning processes. Instead of using LLMs only for text generation, Lagent enables developers to transform models into agents capable of performing actions such as retrieving data, executing code, or interacting with APIs. ... -
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NExT-GPT
Code and models for ICML 2024 paper, NExT-GPT
NExT-GPT is an open-source research framework that implements an advanced multimodal large language model capable of understanding and generating content across multiple modalities. Unlike traditional models that primarily handle text, NExT-GPT supports input and output combinations involving text, images, video, and audio in a unified architecture. The system connects a large language model with multimodal encoders and diffusion-based decoders so it can interpret information from different... -
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AI Engineering Hub
In-depth tutorials on LLMs, RAGs and real-world AI agent applications
...Projects range from OCR applications and local chatbot UIs to multimodal RAG systems and multi-agent automation pipelines, making the hub valuable both as a learning resource and as a practical reference. The repository provides in-depth notebooks, example code, and integration patterns that illustrate how to implement, adapt, and scale AI features in real applications. -
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Awesome LLM Apps
Collection of awesome LLM apps with AI Agents and RAG using OpenAI
...The list spans a wide range of categories including productivity tools, creative assistants, utilities, education platforms, research frameworks, and niche vertical apps, showcasing how generative models are being used across domains. Each entry includes a brief description, language model dependencies, technology stack notes, and sometimes links to demos or source code, making it easy to explore ideas and reuse concepts for your own projects. Because the landscape of LLM-powered applications changes quickly, the repository is designed to be updated regularly through community contributions, ensuring it stays current with new tools and releases. -
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LLM TLDR
95% token savings. 155x faster queries. 16 languages
LLM TLDR is a tool that leverages large language models (LLMs) to generate concise, coherent summaries (TL;DRs) of long documents, articles, or text files, helping users quickly understand large amounts of content without reading every word. It integrates with LLM APIs to handle input texts of varying lengths and complexity, applying techniques like chunking, context management, and multi-pass summarization to preserve accuracy even when the source is very large. The system supports both... -
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Scientific Visualization
An open access book on scientific visualization using python
The Scientific Visualization book is a freely available open-access textbook that introduces how to produce effective scientific visualizations using Python, focusing especially on leveraging the popular plotting library Matplotlib (and related tools). It goes beyond simple plotting tutorials and emphasizes design principles: how to choose colors, layout subplots, annotate graphs, and present data in a way that is both accurate and visually compelling. As such, it serves as a guide for... -
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Omnilingual ASR
Omnilingual ASR Open-Source Multilingual SpeechRecognition
Omnilingual-ASR is a research codebase exploring automatic speech recognition that generalizes across a very large number of languages using shared modeling and training recipes. It focuses on leveraging self-supervised audio pretraining and scalable fine-tuning so low-resource languages can benefit from high-resource data. The project provides data preparation pipelines, training scripts, decoding utilities, and evaluation tools so researchers can reproduce results and extend to new... -
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MoCo (Momentum Contrast)
Self-supervised visual learning using momentum contrast in PyTorch
MoCo is an open source PyTorch implementation developed by Facebook AI Research (FAIR) for the papers “Momentum Contrast for Unsupervised Visual Representation Learning” (He et al., 2019) and “Improved Baselines with Momentum Contrastive Learning” (Chen et al., 2020). It introduces Momentum Contrast (MoCo), a scalable approach to self-supervised learning that enables visual representation learning without labeled data. The core idea of MoCo is to maintain a dynamic dictionary with a... -
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marimo
A reactive notebook for Python
marimo is an open-source reactive notebook for Python, reproducible, git-friendly, executable as a script, and shareable as an app. marimo notebooks are reproducible, extremely interactive, designed for collaboration (git-friendly!), deployable as scripts or apps, and fit for modern Pythonista. Run one cell and marimo reacts by automatically running affected cells, eliminating the error-prone chore of managing the notebook state. marimo's reactive UI elements, like data frame GUIs and plots,...
