19 个仓库
Platforms for deploying and managing autonomous agents with persistent memory and custom tool capabilities.
Distinguishing note: Focuses on the orchestration of multi-step agentic workflows rather than individual model inference.
Explore 19 awesome GitHub repositories matching artificial intelligence & ml · Agent Orchestration Frameworks. Refine with filters or upvote what's useful.
Warp is an AI-integrated terminal emulator designed to automate software development workflows directly within the command-line interface. It functions as an enterprise-grade orchestration platform that coordinates multiple artificial intelligence models and coding agents to assist with building, reviewing, and shipping code. By embedding these capabilities into the shell, the environment allows developers to prompt, plan, and refine software projects without leaving their terminal session. The platform distinguishes itself through a centralized control plane that manages, secures, and scales
Coordinates multiple automated coding agents and external services within a unified environment.
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
A structured environment for coordinating autonomous agents to perform complex software development tasks through collaborative workflows and adversarial review processes.
This repository is a collection of guides, notebooks, and recipes for implementing advanced prompting techniques and workflow patterns with large language models. It serves as a prompt engineering guide, an evaluation suite for scoring prompt quality, and a framework for orchestrating agents and integrating external tools. The project provides implementation patterns for building applications with Claude, specifically focusing on coordinating multiple models to split complex tasks between high-reasoning and high-efficiency agents. It includes technical demonstrations for multimodal data proce
Provides a framework for orchestrating multi-step agentic workflows and coordinating multiple models.
MindsDB is an AI-native database engine that treats machine learning models and autonomous agents as virtual tables. By mapping external data sources, predictive models, and third-party services directly into the database schema, it enables users to perform inference, data retrieval, and complex orchestration using standard SQL syntax. The platform distinguishes itself through an autonomous agent orchestrator that executes iterative reasoning loops, allowing agents to plan data access and synthesize natural language responses from connected knowledge bases. It functions as a federated data ga
A framework for defining and managing intelligent agents that interpret natural language to plan data retrieval and synthesize complex responses.
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
Functions as an orchestration platform to chain prompts, memory, and tools for complex agentic workflows.
LangGraph is a framework for building stateful, multi-step agentic workflows by modeling application logic as a directed graph. It provides a runtime environment where complex tasks are orchestrated through interconnected nodes and edges, allowing developers to manage state transitions, persistent memory, and control flow across long-running automated processes. The platform distinguishes itself through its native support for human-in-the-loop automation, enabling developers to define breakpoints that pause execution for manual review, modification, or approval. It also features checkpoint-ba
Builds complex, multi-step AI workflows that maintain persistent memory and handle state transitions across long-running tasks.
ChatDev is an automated software engineering platform that orchestrates the end-to-end development lifecycle through a multi-agent framework. It functions as a programmable engine that coordinates specialized autonomous agents to handle design, coding, testing, and documentation tasks by transitioning through predefined phases of a software project. The system distinguishes itself by using role-based agent specialization to simulate a professional engineering team, assigning distinct personas and knowledge bases to individual agents. It employs prompt-driven task decomposition to break high-l
Coordinates specialized autonomous agents that interact through a structured communication protocol to complete complex software development tasks.
GPT Researcher is an autonomous agent framework designed to automate the process of gathering, synthesizing, and documenting information from diverse web and local sources. It functions as a research-oriented execution environment that orchestrates specialized agents to perform complex, multi-branch research tasks, transforming raw data into structured, factual, and cited reports. The project distinguishes itself through a graph-based orchestration layer that manages state transitions and information flow between specialized agents. It employs recursive tree-search execution to explore comple
Coordinates specialized autonomous agents by managing state transitions and information flow through a structured graph of research tasks.
Semantic Kernel is an artificial intelligence orchestration framework designed to integrate large language models with existing codebases. It functions as an agentic workflow engine, providing a standardized interface that connects generative models to traditional application logic, data sources, and external tools to automate complex, multi-step business tasks. The platform distinguishes itself through a modular plugin architecture and a planner-based reasoning engine that decomposes high-level goals into executable sequences of functions. By utilizing a connector-based abstraction layer, it
Building intelligent systems that coordinate multiple language models and external tools to complete complex, multi-step business tasks.
This project is a curated repository and directory focused on the artificial intelligence agent ecosystem. It serves as a centralized knowledge base for developers and researchers to discover frameworks, platforms, and autonomous software entities designed for reasoning, planning, and executing complex tasks. The directory distinguishes itself through a community-driven curation model, where contributors maintain and update the collection via a distributed version control system. This collaborative approach ensures that the index remains current with the latest academic resources, open-source
Coordinating multiple specialized software agents to collaborate on complex tasks by delegating responsibilities and sharing information between them.
GenAI_Agents is a development framework and orchestration engine designed for building autonomous, multi-agent systems. It provides the infrastructure to construct complex, state-managed workflows where specialized agents collaborate to execute multi-step tasks, manage long-term memory, and perform iterative reasoning. The platform distinguishes itself through its graph-based orchestration model, which allows developers to define intricate agentic processes with explicit state transitions. It supports advanced control mechanisms such as human-in-the-loop intervention for manual oversight and
Serves as a framework for orchestrating autonomous agents that use large language models to execute complex, multi-step workflows.
Parlant is an agentic workflow engine and orchestration framework designed for building conversational AI that adheres to strict behavioral guidelines. It provides a platform for managing multi-turn interactions through state-machine-based logic, allowing developers to define complex, hierarchical conversational flows that can adapt, skip, or revisit steps based on real-time user input. The framework distinguishes itself through its focus on behavioral governance and observability. It enables developers to define precise domain terminology and enforce instruction compliance through prioritize
Builds conversational agents that enforce behavioral guidelines, manage interaction flows, and integrate external tools.
This project is an orchestration framework designed to automate creative and research workflows by managing specialized artificial intelligence agents. It functions as a content generation system that delegates complex, multi-step tasks to model instances, ensuring that each agent operates within defined behavioral constraints and design methodologies. The framework distinguishes itself through its focus on structural integrity and brand consistency. It employs schema-driven validation to ensure that all generated content adheres to predefined templates and data formats. By utilizing custom s
Offers a platform for defining and managing specialized agents that follow custom instructions for branding and design workflows.
This project is a terminal-based command line interface client and agent orchestrator for interacting with multiple large language model providers. It functions as an OpenAI API client and a local API gateway that exposes chat completions and embeddings through an HTTP server. The system distinguishes itself by providing a retrieval-augmented generation tool for indexing local files and URLs into a vector database to provide custom document context. It allows for the creation of specialized AI agents that combine custom system prompts with tool calling and external function execution. The to
Provides a framework for orchestrating specialized AI agents with custom prompts and tool-calling capabilities.
UFO is a multi-device task orchestrator and LLM agent orchestration framework designed to decompose natural language requests into executable task graphs. It functions as a cross-platform UI automation tool capable of performing interactions on Windows and mobile devices while routing tasks to distributed agents based on their hardware and software capabilities. The system is distinguished by its RAG-enhanced agent architecture, which integrates external documentation and previous execution traces to improve decision-making. It employs a hybrid UI detection approach that combines computer vis
Decomposes natural language requests into executable task graphs for distributed agent execution.
This project is an AI content automation pipeline and LLM agent orchestration framework. It provides a system for generating research-backed text, images, and videos, and scheduling their distribution to social platforms. The framework allows for the development of specialized AI agents and custom tool servers. These servers expose capabilities such as video editing and story generation as API endpoints, enabling agents to execute complex tasks through a combination of AI models and custom tooling. The system covers automated content creation across text, image, and video media, utilizing hu
Provides a framework for deploying and managing autonomous agents with persistent memory and custom tool capabilities.
PromptX is an LLM agent orchestration framework designed to execute multi-step workflows using autonomous agents. It features a sandboxed tool execution environment for secure filesystem operations and external API integrations, alongside a persona management system that defines professional roles and domain expertise to control agent behavior. The system implements a semantic memory network for persistent knowledge storage, utilizing graph-based memory and engrams to retain information across sessions. This cognitive memory includes specialized tools for knowledge graph visualization, allowi
Provides a platform for deploying and managing autonomous agents with persistent memory and custom tool capabilities.
This project is an extension framework and orchestration system for Claude Code that uses lifecycle hooks to intercept and augment the execution flow of agents. It serves as a management layer for automating session startup, handling project context loading, and performing cleanup routines during AI coding sessions. The framework provides an orchestration system to spawn and manage specialized sub-agents with distinct prompts and toolsets to decompose complex technical tasks. It functions as a prompt engineering middleware to validate and inject context into user requests and as a tool guardr
Provides a framework for managing specialized sub-agents with custom prompts and tools to decompose complex development tasks.
Claude-Code-Workflow is a development workflow engine and command-line orchestration framework that coordinates specialized artificial intelligence agents to automate multi-step software development tasks. The system executes structured processes through natural language command routing, analyzing user intent to select workflows and invoke command-line tools automatically. The platform includes embedded hybrid code search combining full-text and semantic embedding methods over local repositories, along with persistent session management that tracks development steps across multiple execution
Coordinates multiple specialized agents and pipelines through a command-line orchestration framework to automate development tasks.