Search Results for "tasks" - Page 16
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Showing 1120 open source projects for "tasks"
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OWASP Maryam
Modular OSINT framework for automated open-source intelligence gatheri
...Written in Python, Maryam is built to provide a flexible and extensible framework for harvesting information quickly and efficiently from open sources. Maryam helps security researchers and analysts streamline routine data-gathering tasks that typically involve searching multiple sources such as Google, Bing, or other online platforms. Maryam organizes its functionality into several modules that focus on different aspects of intelligence gathering, including footprint analysis, OSINT data extraction, and general search operations. -
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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 and vulnerability discovery processes with minimal manual effort. By standardizing input parameters and output formats across different tools, Secator simplifies how results are collected and processed during security testing. ... -
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LongCat-Video
Foundational video generation model with 13.6B parameters
LongCat-Video is a 13.6-billion-parameter foundation model for generating and extending video. A unified architecture handles text-to-video, image-to-video, and video-continuation tasks without separate models. It is pretrained for continuation, allowing it to create minutes-long sequences while limiting color drift and quality loss. A coarse-to-fine strategy operates across time and space to produce 720p video at 30 frames per second efficiently. Block Sparse Attention reduces high-resolution inference costs, while multi-reward GRPO training improves visual quality and prompt alignment. ... -
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OpenOCR
An Open-Source Toolkit for General-OCR Research and Applications
...The toolkit supports both Chinese and English content, making it suitable for multilingual document analysis. OpenOCR includes training, evaluation, fine-tuning, and deployment tools, allowing users to customize models for specific OCR tasks. Its comprehensive ecosystem bridges academic research and industrial applications through reproducible benchmarks and commercial-grade OCR solutions. -
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Medeo Video Generator
AI-powered video generation skill for OpenClaw
...The project focuses on bridging the gap between language-based AI systems and multimedia outputs by enabling models to produce structured video content as part of their workflows. It supports tasks such as video generation, editing, and transformation, making it useful for applications in content creation, marketing, and automated media production. The framework is designed to be modular, allowing developers to plug video capabilities into larger AI pipelines or agent systems. It emphasizes ease of integration and scalability, enabling both simple use cases and more complex multimedia workflows. -
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Python Code Tutorials
The Python Code Tutorials
Python Code Tutorials is a large educational repository that aggregates programming tutorials from the “The Python Code” website into a structured collection of Python projects and learning materials. The repository covers a wide range of programming topics including cybersecurity, networking, web scraping, machine learning, GUI development, and automation scripts. Each tutorial typically includes complete Python code examples and explanations that demonstrate how to build real tools and... -
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Agent Behavior Monitoring
The open source post-building layer for agents
Agent Behavior Monitoring is an open-source framework designed to monitor, evaluate, and improve the behavior of AI agents operating in real or simulated environments. The system focuses on agent behavior monitoring by collecting interaction data and analyzing how agents perform across different scenarios and tasks. Developers can use the framework to observe agent actions in both online production environments and offline evaluation settings, making it useful for debugging and performance analysis. Judgeval transforms agent interaction trajectories into structured evaluation datasets that can be used for reinforcement learning, supervised fine-tuning, or other forms of post-training improvement. ... -
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Xteam
All-in-one command-line toolkit for security testing and OSINT tools
Xteam is a command-line security toolkit designed to provide multiple penetration testing and information-gathering utilities in a single interface. It combines several modules and external tools to help users perform security research tasks related to mobile devices, wireless networks, and online services. It acts as a centralized launcher that integrates scripts and third-party tools, allowing users to access different testing functions through a menu-based command line workflow. Xteam includes features such as Instagram information gathering, phishing utilities, wireless attack tools, and Android security testing capabilities. ... -
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FinGPT
Open-Source Financial Large Language Models
...It extends traditional GPT-style models by connecting them to live or historical financial datasets, news APIs, and economic indicators so that outputs are grounded in relevant and recent market conditions rather than generic knowledge alone. The platform typically includes tools for fine-tuning, context engineering, and prompt templating, enabling users to build specialized assistants for tasks like sentiment analysis, earnings summary generation, risk profiling, trading signal interpretation, and document extraction from financial reports. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Mathematics Dataset
This dataset code generates mathematical question and answer pairs
The Mathematics Dataset, developed by Google DeepMind, is a synthetic dataset designed to evaluate and train machine learning models on mathematical reasoning and symbolic manipulation. It generates question-and-answer pairs across a wide range of mathematical topics typically found in school-level curricula, testing a model’s ability to reason about algebra, arithmetic, calculus, probability, and more. Each question is programmatically generated with structured templates to ensure clear... -
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PyTorch3D
PyTorch3D is FAIR's library of reusable components for deep learning
...The library provides fast GPU-accelerated implementations of rendering pipelines, transformations, rasterization, and lighting—making it possible to compute gradients through full 3D rendering processes. Researchers use it for tasks like shape generation, reconstruction, view synthesis, and visual reasoning. PyTorch3D also includes utilities for loading, transforming, and sampling 3D assets, so models can be trained end-to-end from 2D supervision or partial data. Its modular design allows easy extension—components like differentiable rasterizers, mesh blending, or signed distance field (SDF) modules can be swapped or combined to test new architectures quickly. -
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Amazon Braket Python SDK
A python SDK for interacting with quantum devices on Amazon Braket
The Amazon Braket Python SDK is an open-source library to design and build quantum circuits, submit them to Amazon Braket devices as quantum tasks, and monitor their execution. Before you begin working with the Amazon Braket SDK, make sure that you've installed or configured the following prerequisites. Download and install Python 3.7.2 or greater from Python.org. As a managed service, Amazon Braket performs operations on your behalf on the AWS hardware that is managed by Amazon Braket. ... -
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ContextGem
ContextGem: Effortless LLM extraction from documents
...It provides a flexible, intuitive API that minimizes boilerplate code, enabling developers to build complex extraction workflows efficiently. ContextGem supports various document formats and integrates with multiple LLM providers, making it a versatile tool for tasks like contract analysis, anomaly detection, and information retrieval. -
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FullTClash
General proxy performance testing tool based on Clash using Telegram
...The front end part uses Telegram API as the interactive interface, which needs to be used in conjunction with Telegram, that is, a Telegram robot (bot), FullTClash bot is a Telegram robot (hereinafter referred to as bot) carrying its test tasks. -
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UI-TARS
UI-TARS-desktop version that can operate on your local personal device
...Rather than relying on rigid, manually scripted UI automation, UI-TARS uses a unified vision-language model (VLM) that integrates perception, reasoning, grounding, and action into one end-to-end framework: it “thinks before acting,” enabling flexible, general-purpose automation. This allows it to perform complex, multi-step tasks such as filling forms, downloading files, navigating applications, and even controlling in-game actions — all by understanding the UI as a human would. The project is open-source, supports deployment locally or remotely, and offers a foundation for building GUI automation agents that are more robust, and adaptable. -
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ShellOracle
A terminal utility for intelligent shell command generation
...It integrates with multiple large language model providers, including local and cloud-based systems, to generate accurate and context-aware command suggestions. The tool operates directly within the terminal and can be triggered through keyboard shortcuts, allowing users to describe tasks in plain English and receive ready-to-run commands. It maintains a history of prompts and generated commands, enabling users to revisit previous queries and refine workflows over time. The system also supports advanced shell features such as piping, allowing generated commands to be chained into more complex operations. Designed to be self-hosted, it gives users full control over their environment and data, making it suitable for privacy-sensitive use cases. -
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VOID
Video Object and Interaction Deletion
...Unlike traditional inpainting methods that only erase pixels or simple artifacts, VOID models the full interaction dynamics between objects and their environment, including shadows, reflections, and even physical consequences such as movement or balance changes. Built on top of transformer-based architectures and fine-tuned for video inpainting tasks, the system uses interaction-aware mask conditioning to ensure temporal consistency across frames. One of its most notable capabilities is its ability to simulate realistic scene behavior after object removal, such as causing an object to fall naturally if its support is removed, which significantly enhances realism. -
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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 supports a full end-to-end workflow, including dataset preparation, model training, evaluation, and export to various deployment formats. ... -
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Text Embeddings Inference
High-performance inference server for text embeddings models API layer
...It focuses on delivering fast and scalable embedding generation by leveraging optimized inference techniques and modern hardware acceleration. It is built to support transformer-based embedding models, making it suitable for tasks such as semantic search, clustering, and retrieval-augmented systems. It provides an API interface that allows developers to integrate embedding capabilities into applications without managing model internals directly. Text Embeddings Inference is optimized for throughput and low latency, enabling it to handle large volumes of requests reliably. ... -
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QuantDinger
AI-driven, local-first quantitative trading platform for research
...Traders and researchers can develop custom strategies in Python, run historical backtests, analyze performance, and connect to supported exchanges for live trading, making it suitable for equities, crypto, forex, and futures markets in a local environment. QuantDinger also incorporates optional AI features via external APIs, assisting in tasks like strategy ideation or interpreting market indicators, but strategy logic remains inspectable and transparent in code. -
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NovaSR
A lightning fast audio upsampler
...At only about 50 KB in size, the model is orders of magnitude smaller than typical audio super-resolution networks, yet it achieves high quality and realtime performance thanks to its compact architecture and efficient convolutional design. NovaSR is especially valuable for post-processing tasks in speech enhancement, TTS pipelines, and dataset restoration where low sampling rates degrade perceived audio clarity; the minimal model size also makes it suitable for edge and embedded use cases where memory is at a premium. Its performance can reach thousands of times realtime on modern GPUs, allowing massive audio batches to be processed with negligible compute overhead. -
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OpenAgents
AI Agent Networks for Open Collaboration
OpenAgents is an ambitious open-source framework for building AI Agent Networks where multiple autonomous AI agents can discover, connect, and collaborate on shared tasks within an extensible, protocol-agnostic ecosystem. The project’s goal is to provide foundational networking infrastructure that lets diverse agents—built using different large language models or tools—interoperate and work together toward complex goals. Agents on OpenAgents can exchange information, share capabilities, execute collaborative workflows, and grow networks without being tied to a single vendor or model provider. ... -
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Google CTF
Google CTF
Google CTF is the public repository that houses most of the challenges from Google’s Capture-the-Flag competitions since 2017 and the infrastructure used to run them. It’s a learning and practice archive: competitors and educators can replay tasks across categories like pwn, reversing, crypto, web, sandboxing, and forensics. The code and binaries intentionally contain vulnerabilities—by design—so users can explore exploit chains and patching in realistic settings. The repo also includes infrastructure components and links to a scoreboard implementation, giving organizers reference material for hosting their own events. ... -
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VMZ (Video Model Zoo)
VMZ: Model Zoo for Video Modeling
The codebase was designed to help researchers and practitioners quickly reproduce FAIR’s results and leverage robust pre-trained backbones for downstream tasks. It also integrates Gradient Blending, an audio-visual modeling method that fuses modalities effectively (available in the Caffe2 implementation). Although VMZ is now archived and no longer actively maintained, it remains a valuable reference for understanding early large-scale video model training, transfer learning, and multimodal integration strategies that influenced modern architectures like SlowFast and X3D. -
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Gemini Fullstack LangGraph Quickstart
Get started w/ building Fullstack Agents using Gemini 2.5 & LangGraph
gemini-fullstack-langgraph-quickstart is a fullstack reference application from Google DeepMind’s Gemini team that demonstrates how to build a research-augmented conversational AI system using LangGraph and Google Gemini models. The project features a React (Vite) frontend and a LangGraph/FastAPI backend designed to work together seamlessly for real-time research and reasoning tasks. The backend agent dynamically generates search queries based on user input, retrieves information via the Google Search API, and performs reflective reasoning to identify knowledge gaps. It then iteratively refines its search until it produces a comprehensive, well-cited answer synthesized by the Gemini model. The repository provides both a browser-based chat interface and a command-line script (cli_research.py) for executing research queries directly. ...
