Open-source alternatives to Openwork

Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com

AionUi is an AI agent orchestration platform designed to manage and coordinate multiple autonomous assistants within a local environment. It functions as a framework for executing background processes and scheduled tasks that operate independently of the user interface, ensuring that automated workflows continue to run without manual oversight. The platform distinguishes itself through a local-first approach to document generation and file manipulation, allowing users to create and modify office files directly on their hardware to maintain data privacy. It supports parallel agent execution, e

openai-go is an LLM SDK for Go and a client for interacting with OpenAI services. It provides type-safe bindings to generate text, images, and audio via REST endpoints, enabling the integration of large language models and AI assistant orchestration into Go applications. The library serves as an agent orchestration tool for managing stateful conversation threads and autonomous agents with integrated tool calling and file search. It also functions as an asynchronous batch processing client for monitoring large-scale request groups and fine-tuning jobs, alongside a management SDK for controllin

This project is an AI-powered IDE extension and LLM coding assistant that provides a conversational interface for generating, refactoring, and debugging code. It functions as an AI agent framework and a Model Context Protocol client, connecting AI models to external data sources and tools to automate complex development tasks. The system is distinguished by its use of autonomous AI agents capable of multi-step task execution, including the ability to read files, modify code, and run terminal commands iteratively. It supports recursive agent orchestration through subagent delegation and employ

PydanticAI is a Python framework designed for building production-grade autonomous agents. It provides a unified interface for interacting with diverse language models, enabling developers to construct agents that perform complex tasks through structured data validation, tool execution, and multi-turn conversation management. The library centers on type-safe schema enforcement, ensuring that model inputs and outputs remain consistent and reliable throughout the agent's lifecycle. The framework distinguishes itself through a robust architecture that emphasizes modularity and testability. It ut

Goose is an extensible agentic AI platform designed for autonomous task orchestration and developer-centric assistance. It provides a workflow engine that manages complex, multi-step objectives by delegating tasks to specialized subagents, all while maintaining stateful session continuity. The system is built to integrate directly into terminal and coding environments, allowing for automated file manipulation and context-aware interaction. The platform distinguishes itself through a secure, sandboxed runtime environment that enforces granular permission controls and policy-driven guardrails.

ChatGPT-Next-Web is a web-based chat interface for interacting with large language models via API or self-hosted model runners. It functions as a prompt management tool and a cross-platform application available for web, mobile, and desktop environments. The project distinguishes itself through a plugin integration gateway that extends model capabilities with external tools like network search and calculators. It includes a self-hosted administrative dashboard for controlling model lists, member permissions, and access passwords on private infrastructure. The application covers prompt engine

Kilocode is an autonomous engineering platform designed to orchestrate AI agents for complex software development tasks. It functions as a comprehensive system for automating coding, testing, and repository management by integrating directly with your codebase and terminal. The platform provides a unified gateway for model orchestration, allowing for the management of agentic workflows, event-driven automation, and persistent session state across distributed development environments. The platform distinguishes itself through its federated task management and policy-based access control, which

FastMCP is a Python framework designed for building servers that expose functions, resources, and prompts to AI models using the Model Context Protocol. It simplifies the development process by automatically deriving tool metadata, input schemas, and documentation directly from Python function signatures and type hints. The framework provides a unified container for managing these components, allowing developers to build modular applications that integrate seamlessly with AI assistants. The project distinguishes itself through its support for interactive, server-defined user interface compone

This project is a container-native runtime designed for building, orchestrating, and executing autonomous AI agents. It provides a framework for managing multi-agent teams and complex workflows by packaging agent configurations as portable container images. By leveraging declarative configuration files, the system allows users to define agent personas, model routing, and tool access without requiring changes to application code. The platform distinguishes itself through its deep integration with container infrastructure, ensuring that agent tasks and external tools run within isolated environ

Julep is an LLM agent orchestration platform and multi-tenant AI backend designed for building autonomous agents with persistent memory, tool integration, and complex multi-step workflows. It serves as a framework for configuring agent identities and behavioral settings to automate specialized professional roles. The platform distinguishes itself through its stateful session management and RAG infrastructure engine, which allow agents to maintain long-term interaction history and ground responses in indexed private documents. It provides enterprise-grade infrastructure features, including a s

Gastown is an LLM agent orchestration platform designed to coordinate multiple AI agents with persistent state and context recovery across coding tasks. It provides a coordination layer that manages agent lifecycles, monitors health through a real-time dashboard, and ensures continuity during task executions. The system distinguishes itself through a federated agent network that links separate orchestration instances to distribute work and track agent reputation. It employs a git-backed work state manager that uses version control worktrees to store progress as structured data and a bisecting

Free-Auto-GPT is an autonomous agent framework and local AI environment designed to execute multi-step goals using large language models. It functions as a web-enabled AI researcher capable of planning and performing actions independently within a containerized workspace. The system is distinguished by its use of a free language model API wrapper, which connects agents to models via session cookies or open interfaces instead of paid API subscriptions. This allows for local AI task execution and autonomous goal completion without requiring paid external service keys. The project covers a rang

Sandbox Agent is a platform designed to manage, secure, and orchestrate autonomous coding assistants. It provides a standardized infrastructure for executing untrusted code and managing agent lifecycles within isolated, containerized environments. By decoupling agent execution from client connections, the platform ensures that session states remain persistent across process restarts and network interruptions. The project distinguishes itself through a capability-based security model that enforces granular permission checks on tool usage, ensuring that autonomous processes operate within defin

This project is a LangChain-based framework for building retrieval-augmented generation systems, autonomous agents, and multimodal chatbots. It functions as an open-source orchestrator that connects local inference engines and online APIs to manage various large language model deployments. The system distinguishes itself by providing specialized interfaces for local knowledge bases, allowing the loading and vectorization of private documents to create context-aware assistants. It also supports multimodal capabilities, enabling the processing of both text and image inputs through vision-capabl

This project is an LLM financial agent framework and multi-agent orchestration system designed to execute complex investment banking and wealth management workflows. It provides a financial data integration layer using a standardized context protocol to connect autonomous agents to real-time market data and third-party feeds. The system utilizes a multi-agent architecture that coordinates specialized worker agents through a steering event bus to handle task delegation and secure handoffs. It includes an enterprise AI deployment manifest for provisioning agent personas, prompts, and skill sets

This project is an autonomous agent workflow engine and multi-agent orchestration framework. It provides a runtime for managing agent lifecycles and a provider-agnostic abstraction layer for interacting with multiple large language model backends through standardized requests and structured outputs. The framework features a reliability layer for output verification, utilizing sampling-based majority voting and generator-evaluator feedback loops to refine model responses. It supports complex coordination patterns including sequential chaining, parallel execution with fan-in aggregation, and re

OpenFang is an operating system for LLM agents designed to orchestrate autonomous agents with built-in task scheduling, tool sandboxing, and multi-model routing. It provides a secure AI execution environment that integrates prompt injection scanning, cryptographic audit trails, and resource metering to ensure controlled processing. The platform distinguishes itself through a comprehensive security architecture, featuring fuel-metered tool sandboxing and an immutable activity audit trail based on cryptographic hash-chains. It implements high-assurance identity verification via signed manifests

Agno is an agent operating system designed to manage the lifecycle, tool execution, and persistent state of autonomous agents across distributed infrastructure. It provides a unified runtime environment that wraps diverse agent frameworks into a consistent, interoperable protocol, allowing developers to build and deploy complex multi-agent systems that coordinate tasks and delegate sub-processes. The platform distinguishes itself through a robust governance and orchestration layer that includes human-in-the-loop approval gates, role-based access control, and a centralized API gateway. It feat

BMAD-METHOD is a multi-agent orchestration framework designed to automate the entire software development lifecycle. It functions as a programmable engine that coordinates autonomous agents to handle complex tasks, ranging from initial requirement elicitation and project planning to code generation and system maintenance. By embedding architectural constraints into a central context file, the system ensures that all automated actions remain aligned with project goals and organizational standards. The platform distinguishes itself through an adversarial review process, where a dual-agent syste

Hummingbot is an open-source framework designed for building, backtesting, and deploying autonomous trading agents and algorithmic strategies across centralized and decentralized cryptocurrency exchanges. It provides a modular environment where users can orchestrate containerized bots to execute complex market-making, grid trading, and arbitrage operations. The platform distinguishes itself through a skill-based architecture that integrates large language models, enabling users to monitor market conditions and control trading operations via natural language commands. It features a unified con

Promptflow is a development framework and orchestrator for building applications powered by large language models. It functions as a suite of tools for designing, orchestrating, and deploying AI workflows by linking prompts, custom Python code, and language models into executable sequences. The project is distinguished by a visual AI workflow designer that allows for the creation of directed acyclic graphs of logic nodes. It provides a dedicated prompt engineering environment for versioning and comparing templates, alongside stateful execution tracing to record function calls and variable val

ChatGPT-Next-Web is a cross-platform web interface and frontend for interacting with large language models. It functions as a self-hosted client that allows users to connect to various AI model providers through a unified chat interface compatible with web browsers and desktop operating systems. The project includes a prompt template manager for creating and organizing reusable masks to standardize interactions. It supports self-hosting on private clouds to maintain data security and provides a centralized administrative panel for managing API resources and member access permissions. The app

Phidata is an LLM agent framework and agentic workflow orchestrator used to build autonomous agents that integrate custom data, tools, and memory. It provides a production environment for serving these agents as services via APIs, utilizing server-sent events and websockets for real-time communication. The system distinguishes itself through a human-in-the-loop control layer that requires manual approval and administrative sign-off for specific tool executions. It also implements a multi-tenant AI infrastructure that uses token-based roles to ensure data isolation between different tenants.

Pipecat is a framework and software development kit for building real-time multimodal AI agents and speech-to-speech systems. It utilizes a frame-based data pipeline to route audio, video, and text through a modular sequence of processors, enabling the orchestration of low-latency conversational AI. The project is distinguished by its ability to coordinate complex multimodal services, including speech-to-text, language models, and text-to-speech, within a single pipeline. It features semantic voice activity detection for natural turn-taking, state-machine conversation flows for dialogue manag

This project provides a comprehensive framework for building, deploying, and orchestrating autonomous agents within a decentralized network. It serves as a collection of patterns and examples for developing intelligent software entities capable of performing complex tasks, making decisions, and interacting with other agents to achieve shared goals. The framework distinguishes itself through its focus on multi-agent orchestration and decentralized communication. It enables the coordination of specialized agent teams that collaborate on workflows through structured messaging protocols, allowing

Dynamiq is an agent development platform designed for building, orchestrating, and monitoring autonomous agents. It provides a framework for constructing complex, multi-step workflows using a graph-based engine that supports conditional branching, feedback loops, and iterative task execution. The platform distinguishes itself through its focus on secure, private infrastructure, allowing for the deployment of language models and orchestration services within virtual private clouds to maintain data sovereignty. It integrates retrieval-augmented generation pipelines to ground model responses in