Search Results for "tiny-workflow" - Page 4
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Showing 128 open source projects for "tiny-workflow"
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AWS Chalice
Python Serverless Microframework for AWS
Chalice is a Python microframework for writing and deploying serverless applications on AWS with minimal ceremony. You define routes, event handlers, and background tasks in plain Python, and Chalice turns them into AWS Lambda functions wired to API Gateway, Amazon EventBridge schedulers, S3/SNS/SQS triggers, and more. A single command builds your app, bundles dependencies, generates infrastructure templates, and deploys to your account with sensible defaults. The framework includes local... -
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Webifier
A GitHub Action to deploy Notebooks, Markdowns
Webifier is a stand-alone build tool for converting any repository into a deployable jekyll website. You can define your pages via yaml files and provide notebooks, markdown and pdf and other files for Webifier to render. It uses python markdown providing additional control over attributes and other extensive functionalities. It lets you define and direct how your web pages feel and automatically manages your assets, making it a perfect solution for fast static website development and a... -
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Prisma Client Python
Prisma Client Python is an auto-generated and fully type-safe database
prisma-client-py is an auto-generated Python ORM for Prisma schema files, bringing Prisma's developer experience to Python projects. It provides a type-safe, intuitive interface for interacting with databases like PostgreSQL and MySQL. prisma-client-py is ideal for Python developers who want static typing, code completion, and seamless integration with modern backend stacks. -
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Maestro Framework
A framework for Claude Opus to intelligently orchestrate subagents
Maestro Framework is a Python framework for orchestrating AI subagents across complex tasks. It breaks a user objective into smaller subtasks, assigns those subtasks to worker models, and refines the results into a final output. The original workflow used Claude Opus and Haiku, while newer variants support Claude 3.5 Sonnet, GPT models, Gemini, Cohere, Groq, LM Studio, and Ollama through different scripts and LiteLLM support. It can maintain context between subtasks so later steps can build on earlier work. The project can also generate exchange logs and save them as Markdown for review. ... -
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Prompt Engineering Interactive Tutorial
Anthropic's Interactive Prompt Engineering Tutorial
Prompt-eng-interactive-tutorial is a comprehensive, hands-on tutorial that teaches the craft of prompt engineering with Claude through guided, executable lessons. It starts with the anatomy of a good prompt and moves into techniques that deliver the “80/20” gains—separating instructions from data, specifying schemas, and setting evaluation criteria. The course leans heavily on realistic failure modes (ambiguity, hallucination, brittle instructions) and shows how to iteratively debug prompts... -
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Pixelization
Stable-diffusion-webui-pixelization
...For digital art, game assets, or retro aesthetic workflows, this offers a fast path from photo or high-res asset to stylized tiles or sprites. Its integration means you don’t need a separate tool or workflow; everything happens via the familiar UI of SD WebUI. -
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Termux Desktop
Setup A Beautiful Desktop/GUI In Termux
Termux Desktop is a collection of dotfiles and scripts for setting up a graphical Linux-style desktop environment inside Termux on Android. It helps users turn a phone or tablet into a more complete desktop-like workspace without needing root access. The setup uses VNC so the desktop can be opened through a VNC client after installation. It includes an Openbox-based environment with visual themes, menus, app launchers, terminal tools, file management, browser access, and system applets. The... -
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MiniChain
A tiny library for coding with large language models
MiniChain is a small Python library for building applications that combine large language models, prompts, and executable tools. Developers annotate ordinary functions to define model calls while keeping prompt templates separate from application logic. Multiple functions can be chained so the output of one model or tool becomes the input to another. The library records calls as a graph, making intermediate steps easier to inspect, debug, and retry. It includes model abstractions for... -
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BabyAGI
Experimental framework for a self-building autonomous agent
BabyAGI is an experimental prototype framework for building self-building autonomous agents. The project became known for exploring how AI agents can manage functions, dependencies, executions, and configurations as part of a more autonomous workflow. Its newer dashboard-oriented structure provides tools for registering, updating, and managing functions through a user-friendly interface. It also supports dependency visualization so users can understand how functions relate to each other. Secret management and execution monitoring make it more practical for agent experimentation than a simple script alone. ... -
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CARTOframes
CARTO Python package for data scientists
A Python package for integrating CARTO maps, analysis, and data services into data science workflows. Python data analysis workflows often rely on the de facto standards pandas and Jupyter notebooks. Integrating CARTO into this workflow saves data scientists time and energy by not having to export datasets as files or retain multiple copies of the data. Instead, CARTOframes give the ability to communicate reproducible analysis while providing the ability to gain from CARTO's services like hosted, dynamic or static maps and Data Observatory augmentation. -
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Vimspector
A multi-language debugging system for Vim
...Once configured you can run, pause, step into/out/over, set and clear breakpoints and inspect variables directly in Vim splits or floating windows. The UI is heavy compared to typical Vim plugins (multiple panes, layouts) but it fills the gap for users who want an integrated debug workflow without leaving the editor. -
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Komodo Edit
Komodo Edit is a fast and free multi-language code editor
...Tons of add-ons for customizing and extending features. Great tools for pair programming and collaboration. Python, PHP, Perl, Go, Ruby, Node.js, JavaScript, and more. Define your own workflow with easy file and project navigation. Backed by ActiveState, trusted by developers and enterprises. -
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Kanbanara
Web-based Project Management System using the Kanban methodology
...It also features a hierarchical workflow, global filter, backlog pyramid, force-directed graphs utilising d3.js, report generator, routine card manager, pair programming, support for continuing cards from one project to another. Full documentation in HTML and EPUB formats. -
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albert_zh
Implementation of A Lite Bert For Self-Supervised Learning Language
...It implements ALBERT with TensorFlow and provides Chinese pretrained models designed to reduce parameter size while preserving strong language understanding performance. The project includes several model variants, such as tiny, small, base, large, and xlarge-style releases, giving users options for speed, size, and accuracy tradeoffs. It also provides guidance for fine-tuning downstream tasks such as sentence-pair semantic similarity and Chinese classification benchmarks. The repository includes support paths for TensorFlow, PyTorch conversion, Keras loading, TensorFlow 2.0 loading, and TensorFlow Lite deployment for mobile scenarios. ... -
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rust.vim
Vim configuration for Rust
...It provides file-detection (so .rs files are recognised), syntax highlighting tuned for Rust’s syntax and macros, and supports formatting via rustfmt and other language-specific tooling. The plugin also integrates with other Vim tools and linters, helping you build a full Rust-editing workflow in Vim. Because Rust’s macro system and language features are more complex than many languages, rust.vim handles special tokens and highlights accordingly. Though it doesn’t itself provide full language-server (LSP) capabilities, it lays the foundation so you can plug in LSP or other completion/diagnostic plugins. Many Rust users say that rust.vim is a reliable baseline for making Vim feel like a competent Rust editor rather than a bare text editor. -
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YOLOV3 Pytorch
This is a source code for yolo3-pytorch
YOLOV3 Pytorch is a PyTorch implementation of the YOLOv3 object detection model built for training, prediction, and evaluation. The repository provides a complete workflow for users who want to train their own object detector with VOC-style data or use pretrained weights. It includes utilities for annotation conversion, anchor generation, image prediction, video prediction, batch prediction, FPS measurement, heatmap output, and mAP evaluation. The project added multi-GPU training, target count statistics, learning rate scheduling with step and cosine options, and optimizer selection between Adam and SGD. ... -
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YOLOV4 Pytorch
This is a source code for YoloV4-pytorch that can be used to train you
YOLOV4 Pytorch is a PyTorch implementation of the YOLOv4 object detection model for training and running custom detection systems. The repository is structured around practical workflows, including training, prediction, evaluation, anchor generation, model configuration, and dataset annotation utilities. It supports VOC-style datasets and includes scripts for prediction, mAP evaluation, FPS testing, video prediction, batch prediction, and heatmap generation. The project added multi-GPU... -
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SharPyShell
Tiny and obfuscated ASP.NET webshell for C# web applications
SharPyShell is a tiny and obfuscated ASP.NET web shell that executes commands received by an encrypted channel compiling them in memory at runtime. SharPyShell supports only C# web applications that run on .NET Framework >= 2.0. SharPyShell is a post-exploitation framework written in Python. The main aim of this framework is to provide the penetration tester with a series of tools to ease the post-exploitation phase once exploitation has been successful against an IIS webserver. ... -
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Faster-Rcnn
This is a pytorch implementation library of faster-rcnn
...The project also includes learning rate scheduling through step and cosine methods, optimizer choices between Adam and SGD, adaptive learning rate behavior based on batch size, image cropping, FPS testing, video prediction, and batch prediction. It is a practical reference for users who want a more classical two-stage detector workflow in PyTorch. -
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DeepLabv3 Plus
Encoder-Decoder with Atrous Separable Convolution
DeepLabv3 Plus is a PyTorch implementation of DeepLabv3+ for semantic segmentation. It implements the encoder-decoder architecture with atrous separable convolution and provides a practical workflow for training, prediction, and mIoU evaluation. The repository supports VOC-style segmentation datasets and includes utilities for annotation generation, JSON dataset conversion, model summary inspection, prediction, and metric calculation. It provides pretrained weight workflows for MobileNetV2 and Xception backbones and notes that the correct backbone should be selected during training and prediction. ... -
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Unet
Source code for unet-pytorch, which can train its own model
Unet-pytorch is a PyTorch implementation of U-Net for semantic segmentation workflows. The repository is built around training, prediction, and mIoU evaluation for VOC-style segmentation data and medical-style datasets. It includes scripts for general training, medical dataset training, prediction, annotation handling, model summaries, and evaluation. The project supports multiple backbones, data processing utilities, extensive comments, and adjustable training parameters. Its README notes... -
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YOLOR
implementation of paper - You Only Learn One Representation
YOLOR is the implementation of “You Only Learn One Representation,” a unified network approach for learning explicit and implicit knowledge together. The project focuses on object detection while exploring how a shared representation can support multiple tasks. It builds on the YOLO family and related PyTorch detection work, combining practical detector training with a research idea about unified representations. YOLOR includes model configurations, training code, evaluation scripts,... -
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DockStream
A Docking Wrapper to Enhance De Novo Molecular Design
DockStream is a docking wrapper providing access to a collection of ligand embedders and docking backends. Docking execution and post hoc analysis can be automated via the benchmarking and analysis workflow. The flexilibity to specifiy a large variety of docking configurations allows tailored protocols for diverse end applications. DockStream can also parallelize docking across CPU cores, increasing throughput. DockStream is integrated with the de novo design platform, REINVENT, allowing one to incorporate docking into the generative process, thus providing the agent with 3D structural information. -
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scikit-opt
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing
...It includes genetic algorithms, particle swarm optimization, differential evolution, simulated annealing, ant colony optimization, immune algorithms, and artificial fish swarms. The package can address continuous objectives, constrained problems, and combinatorial tasks such as the traveling salesman problem. A consistent workflow lets users define an objective, configure an optimizer, run iterations, and inspect the best solution. Genetic algorithm operators can be replaced through user-defined functions or subclassing. Runs may continue from earlier iterations instead of restarting. Vectorization, threading, multiprocessing, caching, examples, and plotting support help users experiment with performance and convergence. -
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nbdev template
Template for nbdev projects
Write, test, document, and distribute software packages and technical articles, all in one place, your notebook. Traditional programming environments throw away the result of your exploration in REPLs or notebooks. nbdev makes exploration an integral part of your workflow, all while promoting software engineering best practices.
