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Showing 5551 open source projects for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files"
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Get full visibility and control over your tasks and projects with Wrike.Wrike offers world-class features that empower cross-functional, distributed, or growing teams take their projects from the initial request stage all the way to tracking work progress and reporting results.
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Securden Privileged Account ManagerDiscover and manage administrator, service, and web app passwords, keys, and identities. Automate management with approval workflows. Centrally control, audit, monitor, and record all access to critical IT assets.
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Klavis AI
MCP integration platforms for AI agents to use tools at any scale
Klavis AI is a Y Combinator X25-backed open-source infrastructure platform that enables AI agents to reliably connect with external tools and services at scale through Model Context Protocol (MCP). Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher... -
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NiceGUI
Create web-based user interfaces with Python
...It abstracts away the complexities of HTML, CSS, and JavaScript, allowing for rapid development of web interfaces directly from Python scripts. NiceGUI is suitable for building dashboards, control panels, and other web-based tools, especially in contexts like robotics and data visualization. -
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Orca Core
Core Python Controller of the ORCA Hand
...The software includes a suite of scripts for calibration, tensioning, and positioning, ensuring that the physical hand operates accurately and consistently across different configurations. It is designed to integrate seamlessly with hardware models defined through configuration files, enabling flexible deployment across variations of the ORCA Hand. The framework also supports real-time control and testing, allowing users to connect to the device, enable torque, and issue precise joint movement commands programmatically. -
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secator
Automated framework for running pentesting tools and workflows
Secator is a task and workflow runner designed to streamline security assessments by integrating many well-known penetration testing and reconnaissance tools into a unified framework. It acts as a centralized automation platform that helps security professionals run tasks, workflows, and scans more efficiently from a single command-line interface. It supports dozens of established security tools and organizes them into structured workflows, enabling users to perform complex reconnaissance... -
Data management solutions for confident marketingVerify, deduplicate, manipulate, and assign records automatically to keep your CRM data accurate, complete, and ready for business.
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PowerTrader_AI
Fully automated crypto trading powered by a custom price prediction AI
PowerTrader_AI is a fully open-source, automated cryptocurrency trading bot that combines a custom price prediction AI with a structured and tiered dollar-cost averaging (DCA) strategy to make real trading decisions on behalf of users. It continuously analyzes market data to forecast high and low price levels across multiple timeframes, using those predictions to determine when to open, scale into, or close positions automatically, which aims to take emotion out of trading and enforce discipline. The bot integrates with popular exchange APIs so it can execute real buy and sell orders, manage risk, and maintain position sizing without manual intervention, making it suitable for algorithmic traders who want hands-off operations. ... -
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EasyR1
An Efficient, Scalable, Multi-Modality RL Training Framework
EasyR1 is a streamlined training framework for building “R1-style” reasoning models from open-source LLMs with minimal boilerplate. It focuses on the full reasoning stack—data preparation, supervised fine-tuning, preference or outcome-based optimization, and lightweight evaluation—so you can iterate quickly on chain-of-thought–heavy tasks. The project’s philosophy is practicality: sensible defaults, one-command recipes, and compatibility with popular base models let you stand up experiments without wrestling infrastructure. ... -
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CAMEL AI
Finding the Scaling Law of Agents. A multi-agent framework
...Our approach involves using inception prompting to guide chat agents toward task completion while maintaining consistency with human intentions. We showcase how role-playing can be used to generate conversational data for studying the behaviors and capabilities of chat agents, providing a valuable resource for investigating conversational language models. -
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Mentat
Mentat - The AI Coding Assistant
Mentat is the AI tool that assists you with any coding task, right from your command line. Unlike Copilot, Mentat coordinates edits across multiple locations and files. And unlike ChatGPT, Mentat already has the context of your project, no copy and pasting is required. Run Mentat from within your project directory. Mentat uses Git, so if your project doesn't already have Git set up, run git init. List the files you would like Mentat to read and edit as arguments. Mentat will add each of them to context, so be careful not to exceed the GPT-4 token context limit. -
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Tweepy
Twitter for Python
...Each method can accept various parameters and return responses. When we invoke an API method most of the time returned back to us will be a Tweepy model class instance. This will contain the data returned from Twitter which we can then use inside our application. Models contain the data and some helper methods which we can then use. Tweepy supports both OAuth 1a (application-user) and OAuth 2 (application-only) authentication. Authentication is handled by the tweepy.AuthHandler class. -
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Darts
A python library for easy manipulation and forecasting of time series
...The models can all be used in the same way, using fit() and predict() functions, similar to scikit-learn. The library also makes it easy to backtest models, combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models can be trained on potentially large datasets containing multiple time series, and some of the models offer a rich support for probabilistic forecasting. We recommend to first setup a clean Python environment for your project with at least Python 3.7 using your favorite tool (conda, venv, virtualenv with or without virtualenvwrapper). -
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mac code
Claude Code, but it runs on your Mac for free
mac code is a local AI coding agent designed to run large language models directly on Apple Silicon machines without relying on cloud services, effectively transforming a Mac into a self-contained AI development environment. The project focuses on enabling models that traditionally exceed available RAM to run efficiently by streaming model weights from SSD storage, thereby overcoming hardware limitations through innovative memory management techniques. It operates as a CLI-based assistant that routes user prompts into different execution paths such as chat, shell commands, or web search, functioning as a multi-purpose development agent. The system integrates with inference engines like llama.cpp and Apple’s MLX framework, allowing users to run models up to 35B parameters locally with varying performance trade-offs. -
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Spack
A flexible package manager that supports multiple versions
...Spack isn’t tied to a particular language; you can build a software stack in Python or R, link to libraries written in C, C++, or Fortran, and easily swap compilers or target specific microarchitectures. Spack offers a simple "spec" syntax that allows users to specify versions and configuration options. Package files are written in pure Python, and specs allow package authors to write a single script for many different builds of the same package. With Spack, you can build your software all the ways you want to. -
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VectorVein
No-code AI workflow
...After the software is opened normally, click on the set button. Please fill in API Key of OpenAI to use the AI function and select the output folder for storing the files during workflow output. If you need to use the function of mail delivery, please fill in the mailbox information on the set page. A workflow represents a work task process that includes input, output, and workflow triggering methods. You can arbitrarily define what the input is, what the output is, and how the input is processed and reaches the output result. -
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MkDocs
Project documentation with Markdown
MkDocs is a fast, simple and downright gorgeous static site generator that's geared towards building project documentation. Documentation source files are written in Markdown, and configured with a single YAML configuration file. Start by reading the introductory tutorial, then check the User Guide for more information. There's a stack of good-looking themes available for MkDocs. Choose between the built in themes: mkdocs and readthedocs, select one of the third-party themes listed on the MkDocs Themes wiki page, or build your own. ... -
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ComfyUI-3D-Pack
An extensive node suite that enables ComfyUI to process 3D inputs
...ComfyUI itself is a node-based interface for designing and executing generative AI pipelines, and this extension expands its capabilities by introducing nodes specifically designed for working with three-dimensional data. The package allows the platform to process inputs such as meshes and UV textures and integrate them into generative workflows similar to those used for image and video generation. It incorporates modern 3D generation technologies including neural radiance fields, Gaussian splatting, and other AI-driven reconstruction techniques. ... -
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StatsForecast
Fast forecasting with statistical and econometric models
...The library implements a broad set of models, including AutoARIMA, ETS, CES, Theta, plus a battery of benchmarking and baseline methods, giving users flexibility in selecting forecasting approaches depending on data characteristics (trend, seasonality, intermittent demand, etc.). Its internal implementation leverages numba to compile performance-critical code to optimized machine-level instructions, which makes the models much faster than many traditional Python counterparts. -
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Pysheeet
Python Cheat Sheet
Pysheeet is a community-driven collection of Python code snippets covering common patterns and tasks like sockets, file I/O, data structures, and more. Each snippet is concise and battle-tested, designed to save coding time and reduce boilerplate. With documentation hosted on Read the Docs and an active GitHub repo, it’s a go-to resource for Python developers. -
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Instructor Python
Structured outputs for llms
Instructor is a Python library that bridges OpenAI responses with structured data validation using Pydantic models. It lets developers specify expected output schemas and ensures that the responses from OpenAI APIs are automatically parsed and validated against those models. This makes integrating LLMs into structured workflows safer and more predictable, especially in production applications. -
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Kor
LLM
This is a half-baked prototype that “helps” you extract structured data from text using LLMs. Specify the schema of what should be extracted and provide some examples. Kor will generate a prompt, send it to the specified LLM and parse out the output. You might even get results back. -
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Tandoor Recipes
Application for managing recipes, planning meals, building shopping
...That said earning some money with the project allows us to spend more time on it and thus make improvements we otherwise couldn't. Powerful & customizable search with fulltext support and TrigramSimilarity. Create and search for tags, assign them in batch to all files matching certain filters. Import recipes from thousands of websites supporting ld+json or microdata. Easy setup with Docker and included examples for Kubernetes, Unraid and Synology. -
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pycm
Multi-class confusion matrix library in Python
PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most classes and overall statistics parameters. PyCM is the swiss-army knife of confusion matrices, targeted mainly at data scientists that need a broad array of metrics for predictive models and an accurate evaluation of large variety of classifiers. -
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Streamlink
Streamlink is a CLI utility which pipes video streams
...The main purpose of Streamlink is to avoid resource-heavy and unoptimized websites, while still allowing the user to enjoy various streamed content. There is also an API available for developers who want access to the stream data. Streamlink is built upon a plugin system that allows support for new services to be easily added. Most of the big streaming services are supported. Streamlink is made up of two parts, a cli and a library API. See their respective sections for more information on how to use them. The default behavior of Streamlink is to playback streams in the VLC player. ... -
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Ariadne
Python library for implementing GraphQL servers
...Asynchronous resolvers and query execution. Subscriptions. Custom scalars, enums, and schema directives. Unions and interfaces. File uploads. Defining schema using SDL strings. Loading schema from .graphql files. WSGI middleware for implementing GraphQL in existing sites. -
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NVIDIA Isaac GR00T
NVIDIA Isaac GR00T N1.5 is the world's first open foundation model
...It accepts multimodal inputs—such as language and images—and uses a diffusion transformer architecture built upon vision-language encoders, enabling adaptive robot behaviors across diverse environments. It is designed to be customizable via post-training with real or synthetic data. The vision-language model remains frozen during both pretraining and finetuning, preserving language understanding and improving generalization. Streamlined MLP connection between vision encoder and LLM with added layer normalization. -
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waitress
A WSGI server for Python 3
...Waitress now validates that chunked encoding extensions are valid, and don't contain invalid characters that are not allowed. They are still skipped/not processed, but if they contain invalid data we no longer continue in and return a 400 Bad Request. This stops potential HTTP desync/HTTP request smuggling.
