# nikivdev/flow

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21,136 stars · 833 forks · Rust · MIT

## Links

- GitHub: https://github.com/nikivdev/flow
- awesome-repositories: https://awesome-repositories.com/repository/nikivdev-flow.md

## Topics

`agents` `autonomy` `moonbit`

## Description

Flow is an orchestration framework for designing and executing complex workflows using autonomous agents powered by large language models. It serves as a toolkit for constructing agentic pipelines and a runtime for managing agent lifecycles, session states, and tool execution.

The project is distinguished by its support for hierarchical swarm management, where director agents decompose large projects into smaller tasks for specialized worker agents. It enables multiple coordination patterns, including sequential linear pipelines and concurrent execution where agents analyze tasks from different perspectives simultaneously.

The framework covers a broad range of capabilities including custom tool definition and skill assignment, event-driven lifecycle interception, and tool execution restrictions to block unauthorized operations. It also includes infrastructure utilities for state-isolated session management, socket-activation port binding for privileged ports, and connection-pooled local traffic routing for HTTP and WebSocket requests.

A command-line interface is provided to execute and visualize the interactions of autonomous agent swarms.

## Tags

### Artificial Intelligence & ML

- [Agentic Workflow Orchestration](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-architectures/orchestration-engines/ai-agent/agentic-workflow-orchestration.md) — Provides the infrastructure to design and execute complex, multi-step processes by delegating tasks to collaborating autonomous agents. ([source](https://github.com/nikivdev/flow/blob/main/Cargo.toml))
- [Autonomous Agent Orchestration](https://awesome-repositories.com/f/artificial-intelligence-ml/autonomous-agent-orchestration.md) — Implements a full orchestration framework for designing and executing complex workflows using autonomous agents with coordinated roles.
- [Agent Tool Definitions](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-architectures/ai-agents/agent-tool-definitions.md) — Allows for the definition of custom agent tools by specifying their names, parameters, and validation logic. ([source](https://github.com/nikivdev/flow/blob/main/test-extension.md))
- [Concurrent Agent Execution](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-architectures/orchestration-engines/ai-agent/multi-agent-coordination-systems/concurrent-agent-execution.md) — Enables running multiple agents in parallel to analyze tasks from different perspectives using asynchronous execution patterns. ([source](https://github.com/nikivdev/flow/blob/main/flow.py))
- [Sequential Agent Execution](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-architectures/orchestration-engines/ai-agent/multi-agent-coordination-systems/sequential-agent-execution.md) — Supports linear execution where agents process tasks in a strict sequence and pass outputs to the next agent. ([source](https://github.com/nikivdev/flow/blob/main/flow.py))
- [Agent Skill Frameworks](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/agent-capabilities-skills-tooling/agent-skill-frameworks.md) — Implements a framework for assigning specialized toolsets to agents to handle specific tasks like environment setup and inference. ([source](https://github.com/nikivdev/flow/blob/main/agents.md))
- [Tool Assigners](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/agent-capabilities-skills-tooling/agent-tooling/tool-assigners.md) — Provides interfaces for linking specific executable functions to agents to allow interaction with external systems.
- [Agent Orchestration Frameworks](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/agent-orchestration-multi-agent/autonomous-agents/agent-orchestration-frameworks.md) — Serves as a comprehensive development environment and control layer for routing and managing the lifecycle of autonomous AI agents.
- [Agentic Workflows](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/agentic-workflows.md) — Provides a toolkit for constructing iterative agentic processes and pipelines with state management.
- [Agentic Workflow Automation](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-workflow-automation.md) — Provides a framework for coordinating autonomous agents to automate complex, multi-step workflows through sequential and parallel pipelines.
- [AI Integration Tools](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-integration-tools.md) — Allows the definition and assignment of specialized custom tools and functions that enable AI agents to interact with external systems.
- [LLM Tooling Integrations](https://awesome-repositories.com/f/artificial-intelligence-ml/artificial-intelligence-tooling/language-model-integrations/llm-tooling-integrations.md) — Provides a runtime for defining custom functions and skills that agents invoke to manipulate state and perform tasks.
- [Hierarchical Agent Orchestration](https://awesome-repositories.com/f/artificial-intelligence-ml/hierarchical-agent-orchestration.md) — Implements a hierarchical architecture where director agents decompose complex goals and delegate them to worker agents. ([source](https://github.com/nikivdev/flow/blob/main/flow.py))
- [Large Language Model Connectors](https://awesome-repositories.com/f/artificial-intelligence-ml/large-language-model-connectors.md) — Provides connectors and authentication for integrating external large language model providers into the agentic framework. ([source](https://github.com/nikivdev/flow/blob/main/.env.example))
- [LLM Application Infrastructure](https://awesome-repositories.com/f/artificial-intelligence-ml/llm-application-infrastructure.md) — Manages the structural backend infrastructure required for connecting to LLM providers and powering autonomous agent reasoning.
- [Event-Driven Agent Loops](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-architectures/event-driven-agent-loops.md) — Provides control cycles that monitor agent state changes and trigger actions or validations based on events.
- [Multi-Agent Coordination Systems](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-architectures/orchestration-engines/ai-agent/multi-agent-coordination-systems.md) — Enables specialized agents to collaborate on complex tasks through delegation and shared state in a hierarchical system.
- [Agent Task Execution](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-task-execution.md) — Executes a single autonomous agent to complete a specific task within a defined model and loop limit. ([source](https://github.com/nikivdev/flow/blob/main/flow.py))
- [Agent Swarms](https://awesome-repositories.com/f/artificial-intelligence-ml/multi-model-workflow-coordinators/agent-swarms.md) — Supports hierarchical swarm management where director agents decompose projects into smaller tasks for specialized worker agents.

### Software Engineering & Architecture

- [Sequence Pipelines](https://awesome-repositories.com/f/software-engineering-architecture/modular-program-composition/function-composition/sequence-pipelines.md) — Implements sequential pipelines where the output of one agent is passed as the input to the next.

### DevOps & Infrastructure

- [Runtime Event Interception](https://awesome-repositories.com/f/devops-infrastructure/agent-lifecycle-management/runtime-event-interception.md) — Implements a runtime that intercepts agent lifecycle events to validate operations and manage session state.

### Security & Cryptography

- [LLM Session State Management](https://awesome-repositories.com/f/security-cryptography/identity-access-management/session-management/stateful-session-persistence/agentic-session-persistence/session-initializers/llm-session-state-management.md) — Manages the initialization and reset of environment variables and memory for each isolated agentic session.
- [Tool Execution Permissions](https://awesome-repositories.com/f/security-cryptography/permission-based-access-control/tool-execution-permissions.md) — Evaluates tool requests and blocks dangerous or unauthorized operations before they are executed by the agent. ([source](https://github.com/nikivdev/flow/blob/main/test-extension.md))

### User Interface & Experience

- [Agent Swarm Visualizations](https://awesome-repositories.com/f/user-interface-experience/relationship-visualizations/agent-swarm-visualizations.md) — Includes a command-line interface to visualize the structural relationships and communication paths within agent swarms. ([source](https://github.com/nikivdev/flow/blob/main/pyproject.toml))

### Web Development

- [Agent Lifecycle Hooks](https://awesome-repositories.com/f/web-development/third-party-api-integrations/model-tool-calls/standardized-tool-execution/tool-call-wrappers/agent-tool-interception/agent-lifecycle-hooks.md) — Provides event-driven hooks to execute side effects or validate operations during agent lifecycle events like tool usage. ([source](https://github.com/nikivdev/flow/blob/main/test-extension.md))