Search Results for "state-thread"
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Showing 27 open source projects for "state-thread"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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LangGraph Studio
Desktop app for prototyping and debugging LangGraph applications
LangGraph Studio offers a new way to develop LLM applications by providing a specialized agent IDE that enables visualization, interaction, and debugging of complex agentic applications. With visual graphs and the ability to edit state, you can better understand agent workflows and iterate faster. LangGraph Studio integrates with LangSmith so you can collaborate with teammates to debug failure modes. While in Beta, LangGraph Studio is available for free to all LangSmith users on any plan tier. LangGraph Studio requires docker-compose version 2.22.0+ or higher. ... -
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Suna
Suna - Open Source Generalist AI Agent
...It serves as a digital companion for research, data analysis, and everyday challenges, integrating tools like browser automation, file management, web crawling, command-line execution, website deployment, and API integration. Suna's architecture comprises a FastAPI-based backend, a Next.js/React frontend, an agent Docker environment, and a Supabase database for state management. This modular design allows for seamless interaction and task execution through simple conversations. -
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CopilotKit
Build in-app AI chatbots, and AI-powered Text areas
A bridge between your copilot and your app. A programmable 2-way bridge between your copilot, and your application state (client & cloud). Supports 3rd party integrations (e.g. Salesforce, Zendesk, etc.). Plug-and-play, fully customizable, copilot infrastructure. Build in-app AI chatbots that can "see" the current app state + take action inside your app. The AI chatbot can talk to your app frontend & backend, and to 3rd party services (Salesforce, Dropbox, etc.) via plugins. ... -
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AnythingLLM
The all-in-one Desktop & Docker AI application with full RAG and AI
...AnythingLLM is a full-stack application where you can use commercial off-the-shelf LLMs or popular open-source LLMs and vectorDB solutions to build a private ChatGPT with no compromises that you can run locally as well as host remotely and be able to chat intelligently with any documents you provide it. AnythingLLM divides your documents into objects called workspaces. A Workspace functions a lot like a thread, but with the addition of containerization of your documents. Workspaces can share documents, but they do not talk to each other so you can keep your context for each workspace clean. -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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AgentScript
Build AI agents that think in code
AgentScript is a TypeScript SDK for building reliable AI agents that express their plans as code, enabling stop/start workflows, tool-level state management, and enhanced observability. -
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LangGraph
Build resilient language agents as graphs
...LangGraph allows you to define flows that involve cycles, essential for most agentic architectures, differentiating it from DAG-based solutions. As a very low-level framework, it provides fine-grained control over both the flow and state of your application, crucial for creating reliable agents. Additionally, LangGraph includes built-in persistence, enabling advanced human-in-the-loop and memory features. -
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forkd
Fork() for AI agent microVMs
...Instead of cold-booting a separate virtual machine for every worker, it forks children from a warmed parent snapshot and uses copy-on-write behavior to share the initial memory state. This makes it useful for spawning many isolated agent environments quickly during parallel research, testing, or code execution. The project is focused on runtime performance, sandbox isolation, and efficient branching from a live or prepared VM state. It is especially relevant for developers building agent infrastructure where many short-lived execution branches need to run safely. forkd is best understood as a low-level systems tool for scalable, isolated AI-agent workloads. -
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Flutter Agent Skills
Agent skills for Flutter, maintained by the Flutter team
...The project focuses on practical learning through guided coding challenges, interactive examples, and real-world mobile application scenarios rather than purely theoretical documentation. It covers topics such as UI construction, state management, animations, asynchronous programming, architecture patterns, and testing workflows within Flutter applications. The repository is designed for developers at different experience levels, offering incremental progression from foundational concepts to more advanced mobile engineering techniques. It emphasizes clean coding practices, reusable components, and modern Flutter development patterns. ... -
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OpenAI Realtime Agents
This is a simple demonstration of more advanced, agentic patterns
This repository demonstrates how to build low-latency, streaming “voice + chat” agents using OpenAI’s Realtime API combined with the OpenAI Agents SDK. The demo shows patterns for connecting a realtime voice stream (audio in/out) with agents that can use tools, maintain state, and orchestrate multi-agent workflows. The SDK offers abstractions such as agent orchestration, event handling, handoffs, state management, and guardrails, tailored to support realtime, conversational systems. The demo includes a Next.js frontend for browser interaction and likely a backend component to orchestrate realtime sessions and agent logic. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Beads
A memory upgrade for your coding agent
Beads is an open-source project providing a distributed, structured memory system for AI coding agents, replacing ad-hoc text plans with a git-backed graph that represents tasks, dependencies, and progress in a persistent, queryable format. Instead of storing plans as unstructured Markdown or ephemeral notes, Beads organizes agent state, task artifacts, and relationships as nodes and edges in a version-controlled graph so that long-horizon projects don’t lose context or coherence as the agent proceeds. This approach helps coding agents — and human collaborators — track which tasks depend on others, what has been done, and where workflows branch or reunify without losing important data. ... -
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SWE-agent
SWE-agent takes a GitHub issue and tries to automatically fix it
SWE-agent turns LMs (e.g. GPT-4) into software engineering agents that can resolve issues in real GitHub repositories. On the SWE-bench, the SWE-agent resolves 12.47% of issues, achieving state-of-the-art performance on the full test set. We accomplish our results by designing simple LM-centric commands and feedback formats to make it easier for the LM to browse the repository, and view, edit, and execute code files. We call this an Agent-Computer Interface (ACI). -
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Agent S
Agent S: an open agentic framework that uses computers like a human
...Built to operate graphical user interfaces like a human, it allows AI agents to perceive screens, reason about tasks, and execute actions across macOS, Windows, and Linux systems. The latest version, Agent S3, surpasses human-level performance on the OSWorld benchmark, demonstrating state-of-the-art results in complex multi-step computer tasks. Agent S combines powerful foundation models (such as GPT-5) with grounding models like UI-TARS to translate visual inputs into precise executable actions. It supports flexible deployment via CLI, SDK, or cloud, and integrates with multiple model providers including OpenAI, Anthropic, Gemini, Azure, and Hugging Face endpoints. ... -
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InsForge
InsForge is the backend built for AI-assisted development
...Rather than forcing developers to manually cobble together authentication flows, database schemas, storage buckets, and cloud functions, InsForge provides a semantic layer and toolchain that let agents configured with Model Context Protocol (MCP) understand the backend state, available operations, and how to manipulate these resources end to end. This enables AI coding assistants to complement human engineers by self-configuring backend components, connecting services, and evolving apps autonomously from prompts without switching contexts or manually provisioning infrastructure. -
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InfiAgent
Build your own Cowork, AI Scientist and other SoTA Agents
infiAgent is an open-source AI agent framework for building powerful, long-running autonomous agents capable of tackling complex tasks without collapsing under growing context or tool invocation histories. Designed as a “Multi-Level Agent” (MLA) system, it externalizes persistent state to the file system so that agents can operate over unlimited runtime without the need for token-intensive context compression, enabling workflows such as research paper drafting, experiments, coding, and document generation to run reliably. The framework uses a serial multi-agent hierarchy where specialized agents coordinate in tree-structured paths for clear task delegation and minimal tool conflicts, while batch file operations and persistent workspaces ensure reproducibility and traceability. ... -
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OpenAI CS Agents Demo
Demo of a customer service use case implemented with the OpenAI Agents
...It consists of two major parts: a Python backend that orchestrates agent logic (tool calls, handoffs, memory, routing) and a Next.js UI for chat interaction and visualizing agent state. The demo covers tasks you’d expect in customer service: changing flights, checking status, answering FAQs, etc. It shows how multiple subagents can be coordinated under a triage agent that decides which specialized agent should handle a given request. The UI includes visualization of which agent is active, routing logic, and conversation tracking. ... -
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Letta Code
The memory-first coding agent
Letta Code is a memory-first CLI coding agent built on the Letta platform that offers developers a persistent AI assistant capable of learning and improving over time rather than resetting state each session, giving agents a sense of continuity and context across coding tasks. Unlike traditional session-based coding tools, Letta Code attaches a long-lived agent to a working directory so that the agent accumulates memory about a project’s structure, preferences, and history, effectively acting as a collaborative partner rather than a stateless helper. ... -
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Android Use
Automate native Android apps with AI using accessibility APIs
...It fills a gap in automation tooling by focusing on mobile-first workflows where traditional browser or desktop-based automation doesn’t work; such as logistics, gig work, field operations, and other industries reliant on phones or tablets. The project works by using Android’s accessibility API to extract structured UI state (as XML) from the device, which is then fed to a large language model (LLM) like OpenAI’s models for decision-making, and actions are executed via the Android Debug Bridge (ADB). This approach bypasses expensive vision-based models and provides faster, cheaper automation with fine-grained interaction capabilities (for example, tapping buttons, typing text, navigating screens). -
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AutoGen
An Open-Source Programming Framework for Agentic AI
AutoGen is an open-source programming framework for building AI agents and facilitating cooperation among multiple agents to solve tasks. AutoGen aims to provide an easy-to-use and flexible framework for accelerating development and research on agentic AI, like PyTorch for Deep Learning. It offers features such as agents that can converse with other agents, LLM and tool use support, autonomous and human-in-the-loop workflows, and multi-agent conversation patterns. AutoGen provides... -
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Pi Agent
AI agent toolkit: coding agent CLI, unified LLM API, TUI & web UI
Pi is an open-source AI agent toolkit and coding agent framework designed to help developers build, run, and extend intelligent AI-powered workflows. Developed by Earendil Works, the project includes a coding agent CLI, unified multi-provider LLM API, agent runtime, terminal UI library, and web UI components. Pi supports multiple AI providers such as OpenAI, Anthropic, and Google through a single consistent API layer, making it easier to integrate different models into applications and... -
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Agent SOP
Natural language workflows for AI agents
...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. The framework supports monitoring and state tracking, so external systems can observe progress, intervene if necessary, and log outcomes for compliance or auditing. Integrations with common messaging and task orchestration systems enable SOP agents to interact with email, ticket queues, and databases as part of their workflows. -
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React Doctor
Your agent writes bad React
React Doctor is a developer tool that scans React codebases and identifies problems that commonly appear in AI-generated or poorly maintained frontend code. It gives projects a clear health score from 0 to 100, making technical issues easier to understand, prioritize, and communicate. The scanner checks areas such as state management, effects, performance, architecture, accessibility, security, and dead code. It works across popular React environments, including Next.js, Vite, and React Native. It can also be installed into coding agents so they learn better React practices before generating new code. For teams, it supports GitHub Actions workflows that can comment on pull requests and expose scores for automated quality gates. -
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Inkeep
Create AI Agents in a No-Code Visual Builder or TypeScript SDK
...Agents built with this framework can act as real-time conversational assistants — for example, handling help desk inquiries, providing internal support to teams, or driving in-app experiences — and they can be extended to automate multi-step tasks that interact with external systems like CRMs, knowledge bases, or ticketing systems. The project includes support for designing rich workflows where agents communicate with each other (agent-to-agent communication) and maintain state. -
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MAI-UI
Real-World Centric Foundation GUI Agents
...Unlike traditional UI frameworks, MAI-UI emphasizes realistic deployment by supporting agent–user interaction (clarifying ambiguous instructions), integration with external tool APIs using MCP calls, and a device–cloud collaboration mechanism that dynamically routes computation to on-device or cloud models based on task state and privacy constraints. -
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KaibanJS
JS-native framework for building and managing multi-agent systems
JavaScript-native framework for building multi-agent AI systems. Multi-agent AI systems promise to revolutionize how we build interactive and intelligent applications. However, most AI frameworks cater to Python, leaving JavaScript developers at a disadvantage. KaibanJS fills this void by providing a first-of-its-kind, JavaScript-native framework designed specifically for building and integrating AI Agents. Harness the power of specialization by configuring AI agents to excel in distinct,... -
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VoltAgent
Open Source TypeScript AI Agent Framework
...These agents, often driven by Large Language Models (LLMs), can perceive their environment, make decisions, and take actions to achieve specific goals. Building such agents from scratch involves managing complex interactions with LLMs, handling state, connecting to external tools and data, and orchestrating workflows. VoltAgent is an open source TypeScript framework that acts as this essential toolkit. It simplifies the development of AI agent applications by providing modular building blocks, standardized patterns, and abstractions. Whether you're creating chatbots, virtual assistants, automated workflows, or complex multi-agent systems, VoltAgent handles the underlying complexity, allowing you to focus on defining your agents' capabilities and logic.
