Search Results for "tasks" - Page 22
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Showing 1208 open source projects for "tasks"
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DB-GPT
Revolutionizing Database Interactions with Private LLM Technology
DB-GPT is an experimental open-source project that uses localized GPT large models to interact with your data and environment. With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private and secure. -
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Cumora
Where agent teams gather. Cross-platform team chat
Cumora is a cross-platform team chat where humans and AI agents participate as peers in conversations and shared work. Agents can maintain personas and memory, claim tasks, coordinate with one another, send and receive email, and use shared Kanban and calendar views. Teams can run agents through Cumora Cloud or bring their own Claude Code or Codex environment from a Mac or VPS. Cloud agents receive isolated runtime pods with access to tools such as shell commands, files, browsers, email, memory, and skills. ... -
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.NET Agent Skills
Repository for skills to assist AI coding agents with .NET and C#
...It provides structured knowledge packs and custom agents that guide coding assistants through common development, debugging, migration, build, package, and performance tasks. The repository covers core .NET work as well as more specialized areas such as Entity Framework, MSBuild, NuGet, .NET upgrades, .NET MAUI, and AI-related .NET development. Its purpose is to reduce trial and error by giving agents task-specific context and repeatable workflows. The project also includes evaluation and dashboard support to track skill performance over time. ... -
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clawhip
claw + whip: Event-to-channel notification router
....*) for consistent automation and routing logic. Overall, Clawhip serves as an operational backbone for developer workflows, enabling real-time visibility and control over distributed AI-driven tasks. -
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LiveKit Agents
Framework for building realtime multimodal voice AI agents apps
...It is designed to run server-side and can integrate with various AI model providers and realtime APIs to support different application requirements. LiveKit Agents also includes tools for scheduling and managing agent tasks, making it easier to connect users to automated assistants in live communication scenarios. -
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MemoryOS
MemoryOS is designed to provide a memory operating system
...These layers typically include short-term memory for immediate conversation context, mid-term memory for topic-level grouping, and long-term personal memory for persistent knowledge about users or tasks. The system dynamically updates and promotes information between these layers using structured algorithms that prioritize relevance and recency. -
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OllamaSharp
The easiest way to use Ollama in .NET
OllamaSharp is an open-source .NET library that provides strongly typed bindings for interacting with the Ollama API, making it easier for developers to integrate local large language models into C# and .NET applications. The project acts as a wrapper around the Ollama API, exposing all endpoints through asynchronous methods that allow developers to perform tasks such as generating text, creating embeddings, and managing models. It supports both local and remote Ollama instances, enabling developers to run AI models on their own hardware or connect to remote model servers. The library is designed to simplify integration by allowing developers to interact with AI models using just a few lines of code while still supporting advanced functionality. ... -
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csghub-server
csghub-server is the backend server for CSGHub
...The server acts as a centralized management layer that allows teams to store, organize, and operate AI assets such as models, datasets, and machine learning applications in a manner similar to artifact repositories used in software engineering. Built primarily in the Go programming language, the system enables organizations to run model inference, training, and fine-tuning tasks within a unified platform. It integrates capabilities similar to model repositories like Hugging Face while allowing enterprises to host and manage their AI assets internally for security and compliance purposes. -
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ModernBERT
Bringing BERT into modernity via both architecture changes and scaling
...The goal of the project is to bring BERT-style models up to date with the capabilities of modern large language models while preserving the strengths of bidirectional encoder architectures used for tasks such as classification, retrieval, and semantic search. ModernBERT introduces architectural improvements that enhance both training efficiency and inference performance, making the model more suitable for modern large-scale machine learning pipelines. The repository also includes FlexBERT, a modular framework that allows developers to experiment with different encoder building blocks and configurations when constructing new models. -
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AI Agents From Scratch
Demystify AI agents by building them yourself. Local LLMs
...The project walks through the process of constructing agents step by step, beginning with simple prompt-based interactions and gradually introducing more advanced capabilities such as planning, tool use, and memory. The repository provides example implementations that demonstrate how language models can interact with external systems, perform reasoning tasks, and execute structured workflows. It focuses on explaining the architecture of agent systems rather than simply providing finished code, making it useful for developers who want to understand how AI agents actually work internally. By building agents incrementally, the project helps learners grasp concepts such as decision loops, task decomposition, and environment interaction. -
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Huatuo-Llama-Med-Chinese
Instruction-tuning LLM with Chinese Medical Knowledge
...The goal of the project is to improve the reliability and domain expertise of language models when answering medical questions or assisting with healthcare-related tasks. By combining domain-specific training data with instruction-tuning techniques, the project produces models capable of generating more accurate medical responses than general-purpose models. -
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Sandstorm
One API call, pull Claude agent, completely sandboxed
...The core idea is to provide “one API call” access to a robust Claude agent loop that runs inside a secure sandbox, so you can upload files, connect tools, and run long-running tasks — all managed behind a simple REST-style interface that disappears when the work is done. This approach lowers the friction of building autonomous agents by removing the need to provision servers, orchestrate distributed agents, or manage persistent tooling; agents can be spun up in parallel without manual setup and shut down when complete. ... -
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Agent SOP
Natural language workflows for AI agents
Agent SOP is a framework that implements structured operational procedures (SOPs) for autonomous agents so that they can carry out complex multi-step tasks reliably and in a defined order. Instead of relying solely on broad language model reasoning, this project enforces explicit step sequences with checkpoints, conditional transitions, and rollback logic, making agent workflows more predictable and auditable. It defines reusable SOP templates that agents can instantiate with context-specific parameters, allowing organizations to codify best practices for customer support, data processing, document workflows, or incident response. ... -
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Step 3.5 Flash
Fast, Sharp & Reliable Agentic Intelligence
Step 3.5 Flash is a cutting-edge, open-source large language model developed by StepFun-AI that pushes the frontier of efficient reasoning and “agentic” intelligence in a way that makes powerful AI accessible beyond proprietary black boxes. Unlike dense models that activate all their parameters for every token, Step 3.5 Flash uses a sparse Mixture-of-Experts (MoE) architecture that selectively engages only about 11 billion of its roughly 196 billion total parameters per token, delivering... -
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CC Mirror
Create multiple isolated Claude Code variants with custom providers
...Rather than running a single global Claude Code installation, cc-mirror creates separate instances — each with its own config, session store, prompt packs, theme tweaks, and optional preloaded skills — so you can tailor different environments for specific tasks, teams, or experimentation without polluting your primary setup. It also includes an interactive terminal UI for discovering, creating, and launching these isolated variants with a single command, making setup and switching effortless. For teams, cc-mirror’s team mode brings shared task storage and coordinated multi-agent workflows using shared goals and task lists that agents can collaborate on; this is useful for scaling up agentic coding across complex projects. -
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AI Agents Masterclass
Follow along with my AI Agents Masterclass videos
...The project includes structured lessons, code examples, and practical exercises that cover foundational concepts like prompt engineering, chaining agents, tool usage, plan execution, evaluation, and safety considerations. It breaks down how autonomous agents interact with external systems, handle iterative reasoning, and integrate with third-party services or APIs to perform real tasks — for example, web search, browsing, scheduling, or coding assistance. Students of the masterclass can follow written modules or Jupyter notebooks that illustrate concepts step by step and progressively build more capable agents. The content is suitable for both beginners and intermediate developers because it starts with basic principles and escalates to advanced architectures like multi-agent coordination. -
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ZGI
Open-source platform for building AI applications
...It combines agent configuration, visual orchestration, retrieval, structured data, model routing, and reusable skills in one workspace. Workflows can include branches, loops, approvals, HTTP requests, database operations, code execution, and scheduled tasks. Agents can connect to approved knowledge, files, databases, and tools. Finished applications can be exposed through a WebApp, internal app center, API, or internal calls. Permissions, runtime logs, batch tests, sandboxed execution, and self-hosting support help teams govern production deployments. -
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bb
The agent IDE that builds itself
bb is an agentic development environment designed to let AI agents build, customize, and automate the environment they work inside. Users can control it through a desktop application, web interface, CLI, or HTTP API. Work is organized into live threads that people can monitor, steer, or hand off to another agent. The system uses provider CLIs that users already have authenticated instead of forcing a separate model account flow. Desktop builds are available for macOS, while Linux runs... -
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...It includes 1.8B, 7B, and 30B-A3B model sizes, giving users options for lightweight deployment, stronger general performance, or MoE-based capacity. The models support translation across 33 languages and are designed to follow detailed translation instructions in multiple languages. They can handle tasks involving terminology, style, personalization, delimiters, structured data, and background-aware translation. The repository also provides model links, inference guidance, deployment examples, training documentation, and quantization resources. Overall, Hy-MT2 is useful for developers and researchers who need flexible, instruction-following machine translation models for production, evaluation, or experimentation.
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pool
pool is Poolside’s coding agent that runs in your terminal
...It integrates with open agent specifications such as AGENTS.md, Skills, MCP, and ACP, making it adaptable to different coding environments. Developers can use it for interactive coding, scripted tasks, CI-style checks, project analysis, and agent-assisted implementation. Its main value is providing a flexible coding-agent interface that can move between terminal use, editor integration, and automated execution. -
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SkillOpt
Text-space optimizer that trains reusable natural-language skills
...The system learns from agent rollouts, reflection, bounded edits, and validation gates to produce better instructions over time. Its output is a deployable best_skill.md artifact that can be reused across agent tasks. The project is focused on making agents more effective through text-space optimization rather than traditional fine-tuning. It is most useful for AI researchers and agent developers studying self-improving workflows, skill libraries, and evaluation-driven prompt refinement. -
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OpenSwarm
Claude code for everything except coding
...Instead of relying on one general-purpose assistant, it coordinates a team of specialized agents through an orchestrator. The included agents can handle research, data analysis, slide decks, documents, images, videos, scheduling, messaging, and other productivity tasks. It is designed for outputs like pitch decks, market research, SEO content, quarterly reports, launch campaigns, visual assets, and multimedia projects. The project can connect to external services through integrations and can be customized into purpose-specific swarms for areas such as SEO, sales, marketing, finance, customer support, or research. ... -
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holaOS
An Open Agent Computer for ANY digital work
holaOSc is an AI-native operating system concept designed to integrate intelligent agents directly into the core of the computing environment. It provides a framework where AI agents manage tasks, workflows, and interactions across applications. The system emphasizes seamless automation, allowing users to interact with their computer through natural language and high-level instructions. It integrates memory, context awareness, and task orchestration into a unified environment. The architecture is designed to support extensibility, enabling developers to add new capabilities and agents. ... -
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Agentspan
Durable, Distributed runtime for ALL of your agents
...It enables agents to persist beyond process crashes, allowing workflows to continue even after interruptions or restarts. The system is built for durability, meaning tasks can pause for extended periods, including waiting for human approval, and then resume seamlessly. It supports scaling across multiple environments, making it suitable for production-grade agent orchestration. Agentspan includes a local server and visual interface that allow developers to inspect execution flows and debug agent behavior. ... -
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MedgeClaw
Open-source AI research assistant for biomedicine
...It integrates a large library of domain-specific skills, enabling it to perform complex analyses in areas such as genomics, drug discovery, and clinical research. The system connects conversational interfaces with computational environments, allowing users to initiate research tasks through messaging platforms while the backend executes analyses using tools like R and Python. It includes a real-time dashboard that displays progress, generated code, and outputs, providing transparency throughout the research process. MedgeClaw also supports reproducibility by generating structured reports and maintaining consistent environments through containerization. ...
