Search Results for "task" - Page 18
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Showing 1769 open source projects for "task"
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Trellis AI
All-in-one AI framework & toolkit for Claude Code & Cursor
Trellis is an advanced workflow and agent orchestration framework designed for building, managing, and scaling intelligent applications that coordinate numerous autonomous components. At its core, Trellis lets developers define units of work — called tasks or agents — and compose them into rich workflows that can operate with concurrency, conditional logic, and dynamic branching, all without sacrificing readability or control. It emphasizes modular design, encouraging users to encapsulate... -
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TensorFlow Model Optimization Toolkit
A toolkit to optimize ML models for deployment for Keras & TensorFlow
...Deploy models to edge devices with restrictions on processing, memory, power consumption, network usage, and model storage space. Enable execution on and optimize for existing hardware or new special purpose accelerators. Choose the model and optimization tool depending on your task. In many cases, pre-optimized models can improve the efficiency of your application. Try the post-training tools to optimize an already-trained TensorFlow model. Use training-time optimization tools and learn about the techniques. -
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Conductor
Conductor is an event driven agentic workflow engine for AI agents
Conductor is an open-source, durable workflow orchestration engine designed to manage distributed systems, microservices, and AI-driven applications at internet scale. Originally built at Netflix and actively maintained by Orkes and the open-source community, Conductor simplifies complex workflow management by handling retries, failures, state persistence, and long-running process execution automatically. The platform enables developers to orchestrate AI agents, APIs, human approvals, and... -
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Super Magic
All-in-one AI productivity platform with agents, workflows, and IM
Magic is an open source all-in-one AI productivity platform designed to help organizations build, deploy, and scale AI-driven applications efficiently. It is not a single tool but a complete product ecosystem composed of multiple integrated systems that work together to enhance productivity across different business scenarios. Magic centers around a general-purpose AI agent system called Super Magic, which can autonomously understand tasks, plan actions, execute workflows, and perform error... -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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CogAgent
An open sourced end-to-end VLM-based GUI Agent
...The model is designed for agent-style execution rather than freeform chat, maintaining a continuous execution history across steps while requiring a fresh session for each new task. Inference supports BF16 on NVIDIA GPUs, with optional INT8 and INT4 modes available but with noted performance loss at INT4; example CLIs and a web demo illustrate bounding-box outputs and operation categories. -
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Whenever
Cron jobs in Ruby
Whenever (javan/whenever) is a Ruby gem that provides a clean, Ruby DSL for defining and managing cron jobs within your application. Rather than editing system cron tables by hand, you describe scheduled tasks in a schedule.rb file using methods like every, runner, command, or rake. The gem then compiles this schedule into a standard crontab format and installs it for you, handling all the necessary quoting, environment setup, and command path resolution. It supports specifying execution... -
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SageMaker Hugging Face Inference Toolkit
Library for serving Transformers models on Amazon SageMaker
SageMaker Hugging Face Inference Toolkit is an open-source library for serving Transformers models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain Transformers models and tasks. It utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. For the Dockerfiles used for building SageMaker Hugging Face Containers, see AWS Deep Learning Containers. The SageMaker Hugging... -
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Resque
Ruby library for creating background jobs and processing them
...Or, you can do both. Resque is heavily inspired by DelayedJob (which rocks) and comprises three parts, a Ruby library for creating, querying, and processing jobs, a Rake task for starting a worker which processes jobs, a Sinatra app for monitoring queues, jobs, and workers. Resque workers can be distributed between multiple machines, support priorities, are resilient to memory bloat / "leaks," are optimized for REE (but work on MRI and JRuby), tell you what they're doing, and expect failure. -
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amazon-connect-wisdomjs
Gives you the power to build your own Wisdom widget
Amazon Connect Wisdom, a feature of Amazon Connect, delivers agents the information they need, reducing the time spent searching for answers. Today, knowledge articles, wikis, and FAQs are spread across separate repositories. Agents lose a lot of time trying to navigate all those different sources of information, and in the meantime, the customer waits for an answer. Amazon Connect Wisdom connects relevant knowledge repositories with built-in connectors for third-party applications like... -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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DeepSeek-Reasonix
DeepSeek-native AI coding agent for your terminal
...It is built around prefix-cache stability, which helps reduce token costs during long sessions and allows users to leave the agent running across extended workflows. Reasonix includes a coding mode with filesystem and shell tools, a lighter chat mode, one-shot task execution, health checks, session utilities, and project-scoped memory. It supports reviewed SEARCH/REPLACE edits, plan mode, MCP servers, web search, hooks, skills, semantic indexing, transcript replay, event logs, and cost or cache tracking. The project is especially useful for developers who want an open, terminal-first coding agent optimized for DeepSeek’s cache mechanics. ... -
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DeepCTR-Torch
Easy-to-use,Modular and Extendible package of deep-learning models
DeepCTR-Torch is an easy-to-use, Modular and Extendible package of deep-learning-based CTR models along with lots of core components layers that can be used to build your own custom model easily.It is compatible with PyTorch.You can use any complex model with model.fit() and model.predict(). With the great success of deep learning, DNN-based techniques have been widely used in CTR estimation tasks. The data in the CTR estimation task usually includes high sparse,high cardinality categorical features and some dense numerical features. Low-order Extractor learns feature interaction through product between vectors. Factorization-Machine and it’s variants are widely used to learn the low-order feature interaction. High-order Extractor learns feature combination through complex neural network functions like MLP, Cross Net, etc. -
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Flock
Flock is a workflow-based low-code platform for building chatbots
Flock is a workflow-based low-code platform designed for building AI applications such as chatbots, retrieval-augmented generation systems, and multi-agent workflows. The platform uses a visual workflow architecture where different nodes represent processing steps such as input processing, model inference, retrieval operations, and tool execution. Developers can connect these nodes to create complex pipelines that orchestrate multiple language models and external services. Built on... -
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Perl 5
The Perl programming language
...Development emphasizes robust tests (t/), meticulous changelogs, and tooling like perldoc to keep the language approachable and dependable. In practice, Perl 5 remains a workhorse for sysadmin automation, data munging, web services, and any task where flexible, expressive text handling is paramount. -
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nextflow
A DSL for data-driven computational pipelines
Nextflow is a powerful workflow orchestration tool designed for the development and execution of data-intensive pipelines, especially in the field of bioinformatics. It enables reproducible and portable workflows that can run seamlessly across different environments including local, HPC clusters, and cloud platforms. With support for containers and software package managers, Nextflow makes it easy to define complex data processes using a concise DSL and manage dependencies efficiently. -
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DeerFlow
Deep Research framework, combining language models with tools
...“planner,” “searcher,” “coder,” “report generator”) that collaborate in a structured workflow, allowing tasks like literature reviews, data gathering, data analysis, code execution, and final report generation to be largely automated. It supports asynchronous task coordination, modular tool integration, and orchestrates the data flow between agents — making it suitable for large-scale or multi-stage research pipelines. Users can deploy it locally or on server infrastructure, integrate custom tools, and benefit from its flexible configuration. -
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reverse-skill
Reverse Engineering and Authorized Penetration Testing
reverse-skill is a cybersecurity skill router for AI coding agents working on authorized reverse engineering, penetration testing, CTF, and security research tasks. It analyzes the target type and directs the agent to an appropriate methodology instead of relying on improvised commands. Its playbooks cover Android and iOS applications, native binaries, .NET, JavaScript, firmware, malware, APIs, supply chains, and other specialized scenarios. The package checks locally available tools and can... -
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Context Hub
Makes coding agents get smarter with every task
Context Hub is a curated documentation system built to help coding agents write more accurate code. It gives agents versioned, language-specific reference material instead of forcing them to rely on noisy web searches or stale model memory. The project includes a CLI called chub that agents can use to search for available docs, fetch specific API guidance, and request only the files they need. It also supports local annotations, allowing an agent to remember project-specific notes, pitfalls,... -
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CoStrict
Strict AI coder for enterprises, quality first
...Unlike typical AI coding tools that prioritize speed over rigor, CoStrict introduces a “strict mode” methodology that enforces disciplined processes such as requirements analysis, architecture planning, task decomposition, and test generation before producing code. This makes it particularly suitable for organizations that require consistency, auditability, and reliability in AI-assisted development. The system integrates repository-wide analysis using retrieval-augmented generation, allowing it to understand large codebases and provide context-aware suggestions, reviews, and modifications. ... -
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OptScale
FinOps and MLOps platform to run ML/AI and regular cloud workloads
Run ML/AI or any type of workload with optimal performance and infrastructure cost. OptScale allows ML teams to multiply the number of ML/AI experiments running in parallel while efficiently managing and minimizing costs associated with cloud and infrastructure resources. OptScale MLOps capabilities include ML model leaderboards, performance bottleneck identification and optimization, bulk run of ML/AI experiments, experiment tracking, and more. The solution enables ML/AI engineers to run... -
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Oh My OpenAgent
The best agent harness
Oh My OpenAgent is a large-scale, open-source agent orchestration framework that aims to provide a fully unified and extensible environment for AI-powered software development and automation. It builds on the idea that no single model is sufficient, instead enabling coordinated use of multiple models for reasoning, creativity, speed, and cost efficiency within a single workflow. The system is designed as a comprehensive agent harness where tasks are automatically decomposed, delegated, and... -
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Solace Agent Mesh
An event-driven framework designed to build multi-agent AI systems
Solace Agent Mesh is an event-driven framework designed to build, orchestrate, and scale multi-agent AI systems where specialized agents collaborate to solve complex tasks across distributed environments. It addresses one of the main challenges in modern AI systems, which is connecting isolated agents, data sources, and enterprise systems into a cohesive and interoperable ecosystem. The framework uses an asynchronous messaging architecture powered by an event broker, enabling agents to... -
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OpenAI Agent Skills
Skills Catalog for Codex
OpenAI Agent Skills is an open-source repository that serves as a broad catalog of agent skills designed to extend the capabilities of OpenAI Codex and other AI coding agents. It organizes reusable, task-specific workflows, instructions, scripts, and resources into modular skill folders so that an AI agent can reliably perform complex tasks without repeated custom prompting, making agent behavior more predictable and composable. Each skill is defined with clear metadata and instructions organizing how an AI assistant should complete specific tasks ranging from project management to code generation and documentation assistance. ... -
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Open X-Embodiment
Unified open dataset enabling cross-embodiment learning for robotics
Open X-Embodiment is a large-scale collaborative initiative led by Google DeepMind to unify robotic learning datasets into a consistent and standardized format, simplifying access and usage across the robotics research community. Its primary goal is to make all available open-source robotic data interoperable by representing them using the RLDS (Reinforcement Learning Dataset Structure) episode format. This enables seamless integration for training, evaluation, and model development across... -
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Akavache
An asynchronous, persistent key-value store
...Akavache is great for both storing important data as well as cached local data that expires. Downloading and storing remote data from the internet while still keeping the UI responsive is a task that nearly every modern application needs to do. However, many applications that don't take the consideration of caching into the design from the start often end up with inconsistent, duplicated code for caching different types of objects. Akavache is a library that makes common app patterns easy, and unifies caching of different object types (i.e. ... -
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OpenVINO Training Extensions
Trainable models and NN optimization tools
OpenVINO™ Training Extensions provide a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference. When ote_cli is installed in the virtual environment, you can use the ote command line interface to perform various actions for templates related to the chosen task type, such as running, training, evaluating, exporting, etc. ote train trains a model (a particular model template) on a dataset and saves results in two files. ote optimize optimizes a pre-trained model using NNCF or POT depending on the model format. NNCF optimization used for trained snapshots in a framework-specific format. POT optimization used for models exported in the OpenVINO IR format.
