ControlFlow is a Python framework for building agentic AI workflows. It provides a structured, developer-focused framework for defining workflows and delegating work to LLMs without sacrificing control or transparency.
One-Minute Overview#
ControlFlow is a Python framework for building controllable AI agent workflows. It allows you to break down complex AI tasks into observable steps, assign specialized AI agents to each task, and combine tasks into workflows to orchestrate complex behaviors.
Core Value: A development framework that balances AI capabilities with predictability, making AI workflows both powerful and controllable.
Quick Start#
Installation Difficulty: Medium - Requires Python environment and LLM API configuration
pip install controlflow
export OPENAI_API_KEY=your-api-key
Core Capabilities#
1. Task-Centric Architecture#
Break complex AI workflows into observable, manageable individual tasks with clear definitions and boundaries for easier debugging and monitoring.
2. Structured Results#
Bridge AI and traditional software with type-safe, validated outputs using tools like Pydantic to define strict output formats.
3. Specialized Agents#
Assign specialized AI agents to each task, selecting the most suitable AI model based on task characteristics.
4. Multi-Agent Orchestration#
Coordinate multiple AI agents within a single workflow, managing interactions and data flow between agents.