Projects sharing features with Openagent

Local Deep Research is an autonomous research system consisting of an LLM research agent, a local model orchestrator, and a multi-engine search aggregator. It is designed to execute deep research by decomposing complex questions into atomic facts and synthesizing cited reports from academic, technical, and private document sources. The system features an encrypted research workspace that ensures zero-knowledge privacy through isolated, per-user encrypted databases. It utilizes a local RAG knowledge base to index research sources into searchable vector stores, allowing for retrieval-augmented

Magentic-UI is an agentic UI toolkit and framework that enables large language models to interface with real-time browser environments, operating systems, and virtual machines. It provides a sandbox environment where models can execute instructions to manage local files and run shell commands. The project functions as a web interaction orchestrator and browser automation framework, allowing for the execution of end-to-end web workflows and form completions. It coordinates these actions through a system that translates natural language goals into executable sequences. The toolkit covers sever

Hermes-webui is a self-hosted AI orchestrator and web interface for managing autonomous agents. It serves as a multi-provider gateway that connects cloud and local large language models, providing a central hub to execute scheduled background jobs, run shell commands, and manage agent memory on private hardware. The system distinguishes itself through a persistent memory manager that utilizes knowledge graphs and markdown files for long-term context across sessions. It features a model context protocol host for extending agent capabilities with standardized tools and supports the orchestratio

Devika is an autonomous AI software engineering system designed to plan, write, and debug code from high-level natural language instructions. It functions as an agentic software engineer that decomposes complex objectives into actionable coding steps for autonomous execution. The system integrates cloud-based and self-hosted large language models through a provider-agnostic layer, allowing for multi-model reasoning and code completion. It distinguishes itself by combining these models with a sandboxed execution environment for running code across different operating systems and a web-browsing

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

Agency Swarm is a multi-agent orchestration framework and development kit designed to coordinate specialized AI agents through defined communication patterns and handoffs. It functions as a system for managing agent swarms, providing an API gateway to expose these coordinated collectives as production-ready HTTP endpoints. The project distinguishes itself through its Model Context Protocol integration layer, which connects agents to external data sources and capabilities. It implements specialized orchestration patterns, such as the orchestrator-worker model and role-based delegation, to tran

This is an open-source Python SDK for building and orchestrating production-grade AI agents. It provides a unified framework for creating conversational agents that can use tools, maintain state, and coordinate across multiple language model providers including OpenAI, Anthropic, Google, Amazon Bedrock, and locally-hosted models. The SDK supports multi-agent orchestration through graphs, teams, and swarms, allowing several specialized agents to collaborate on complex tasks. Agents can be composed as callable tools that other agents invoke, and the framework includes policy handlers that inspe

mi-gpt is a voice assistant bridge and agent orchestrator that connects smart speakers to large language models. It functions as an integration layer that routes audio requests from hardware speakers to AI providers and converts generated text back into speech via a customizable synthesis system. The project features a retrieval-augmented generation knowledge base that uses embeddings and external documents to provide context-aware responses. It includes a persona definition system for configuring behavioral rules, system prompts, and roleplay characteristics, alongside a plugin architecture

ACE Framework is an open-source software framework designed for building autonomous artificial intelligence agents that operate entirely on local hardware without relying on cloud services. The system executes complete cognitive loops locally, allowing agents to reason, plan, and execute complex tasks independently. The architecture separates core reasoning, planning, memory, and task execution into discrete functional modules while maintaining long-term agent memory and contextual data locally to preserve continuity across operational sessions. It includes a unified interface layer that dec

Acontext is an LLM orchestration backend and agent memory framework designed to manage session state and knowledge for AI agents. It functions as a context manager and orchestration layer that integrates model providers with a secure code sandbox and a zero-knowledge data store. The project is distinguished by its approach to knowledge distillation, capturing agent learnings as reusable Markdown skills and structured memory files. It provides a secure execution environment where shell commands and scripts run in isolated containers with the ability to mount these persistent skill files direct

AdalFlow is an autonomous AI agent framework and LLM application library designed for building modular workflows. It serves as a model-agnostic interface and RAG pipeline orchestrator, allowing users to develop ReAct agents that utilize iterative reasoning and external tool execution to solve complex tasks. The project distinguishes itself through a prompt optimization system that uses textual gradient descent to automatically refine prompt templates and few-shot examples. It treats model feedback as a differentiable signal, enabling a form of LLM backpropagation to iteratively improve output

ruby_llm is an LLM integration framework and AI agent orchestrator designed to connect applications to multiple large language model providers through a unified interface. It serves as a toolkit for building autonomous assistants with custom personas, managing structured output via JSON schemas, and implementing vector embedding engines for semantic search. The project distinguishes itself as an observability suite and multimodal toolkit. It provides specialized capabilities for tracking token usage, calculating model costs, and tracing workflows via OpenTelemetry, while supporting the proces

Superduper is an AI agent development kit and LLM application framework designed to build autonomous agents and data-driven applications. It functions as a RAG orchestration platform and vector search infrastructure, coordinating AI models with database storage to perform multi-step computations and actions using persisted data states. The project distinguishes itself by providing a database-integrated machine learning pipeline that executes training and inference tasks directly on data hosted within SQL and NoSQL databases. It allows for the deployment of self-hosted AI infrastructure on pri

PyCaret is a Python AutoML platform and MLOps lifecycle manager designed to automate machine learning workflows. It functions as a low-code environment that leverages a scikit-learn native engine to execute preprocessing, training, and evaluation for tabular data. The platform distinguishes itself as an LLM-powered ML copilot, using large language model agents to analyze datasets, design experiment configurations, and explain model results. It also serves as a Kubernetes ML orchestrator and model registry, enabling the versioning of trained pipelines and their promotion to production API endp

Miroflow is an agent orchestration framework designed to coordinate multiple large language models and autonomous agents to perform complex research and reasoning tasks. It functions as a hierarchical workflow manager that distributes workloads across specialized agents using intent recognition and structured planning to gather deep information and solve challenging queries. The system distinguishes itself through a multi-model integration gateway and a provider-agnostic interface, allowing it to unify various language model providers. It extends these models via a tool-augmented framework th

This project is an LLM browser automation framework and AI agent browser interface. It serves as a control layer that translates natural language instructions into browser interactions using large language models, enabling AI agents to navigate and interact with web pages through standardized browser-control functions. The system functions as an RPA workflow orchestrator and headless browser management tool, capable of recording and replaying deterministic browser sequences to automate repetitive tasks. It distinguishes itself through stealth configurations, including residential proxies and

gptel is an LLM Emacs client and multi-backend AI integration system that allows users to interact with large language models directly inside the Emacs text editor. It serves as an AI-powered text refactoring tool and a context-aware prompt manager, providing a unified interface to connect with various AI providers, including local Ollama instances, AWS Bedrock, and Gemini. The project distinguishes itself as a Model Context Protocol client, connecting to MCP servers to provide language models with external tools and data sources. It enables context-augmented prompting by aggregating text fro

OpenGpt is an agent orchestration platform and multimodal interface designed for building and deploying specialized AI personas. It allows users to create task-oriented agents with custom system prompts and behavioral constraints to automate professional, creative, and technical workflows. The project features a prompt engineering workflow that transforms simple user inputs into structured instructions to improve model accuracy. It integrates retrieval-augmented generation by connecting vector databases to the chat interface, enabling context-aware responses from private datasets. The platfo

Cognita is a retrieval augmented generation orchestration framework used to build pipelines that connect document stores and language models to provide grounded answers. It functions as a document ingestion pipeline and a vector database integrator, managing the process of loading, parsing, and indexing files into a searchable knowledge base. The system includes a language model gateway proxy that provides a unified API to interact with multiple different model providers. This routing layer decouples the application from specific vendors, allowing requests to be proxied through a provider-agn

Ruoyi AI is a multi-agent orchestration platform that coordinates specialized AI agents through a supervisor-based delegation pattern, allowing complex requests to be broken into subtasks that are assigned, executed, and merged under centralized control. It provides a unified abstraction layer that connects multiple AI model providers behind a single interface, so switching between providers requires no application code changes. The platform also includes a retrieval-augmented generation engine that indexes internal documents into vector stores and retrieves relevant context at query time to g

gptme is a multi-agent orchestration platform designed for autonomous software engineering, terminal-based AI integration, and RAG-enhanced code navigation. It enables the deployment of persistent agents and specialized subagents to decompose complex tasks and execute parallel technical workflows. The system distinguishes itself through a combination of vision-based GUI automation for controlling desktop applications and surgical patching mechanisms for targeted source code modifications. It utilizes git-based memory management to maintain a versioned history of agent identities, lessons, and

OpenClawChineseTranslation is a framework for building conversational assistants that functions as a cross-platform chat gateway. It synchronizes conversational data between multiple external messaging applications and a centralized core, allowing users to interact with an assistant across different platforms. The system utilizes a plugin-based extension architecture to integrate external services such as note-taking and password managers. It features a model-agnostic provider interface, which enables the underlying intelligence to be swapped by selecting different large language model provid

LaVague is an LLM web agent framework and large action model designed to translate natural language instructions into executable browser automation scripts. It functions as a multi-modal orchestrator that reasons over web page states and HTML content to automate multi-step tasks via a Selenium-based automation engine. The framework features a modular model provider layer, allowing users to swap between different language and vision models from providers such as Anthropic, Gemini, and Azure OpenAI. It employs a multi-modal world model to process screenshots and HTML structures, utilizing retri

PraisonAI is an autonomous AI agent platform that coordinates multiple LLM-powered agents for research, planning, and execution of complex workflows. It functions as a multi-agent orchestration framework, a workflow builder, and a Model Context Protocol server, while also providing retrieval-augmented generation through vector knowledge bases. Agents can interact via CLI, web, or standardized protocols with sandboxed code execution. The platform distinguishes itself with a rich set of agent communication protocols, including A2A, REST, WebSocket, voice and telephony integration, and MCP, allo

Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention. The framework distinguishes itself through its focus on observability and secure, isolated execut

FreeAskInternet is a self-hosted AI search aggregator and answer generation platform. It uses a language model to synthesize results from multiple web search engines into a single, comprehensive response, integrating with SearXNG to gather raw web data. The system is designed for local deployment through Docker containerization, allowing the search aggregator and user interface to run in isolated environments. It supports local language model integration and provides a provider-agnostic interface to switch between different local or remote model backends. The platform handles search and synt