Rootflo is an alternative to Langgraph, and CrewAI. It lets you easily build composable agentic workflows from using simple components to any size, unlocking the full potential of LLMs.
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Build production-ready AI agents and teams with minimal code
Flo AI is a Python framework that makes building production-ready AI agents and teams as easy as writing YAML. Think "Kubernetes for AI Agents" - compose complex AI architectures using pre-built components while maintaining the flexibility to create your own.
- π Truly Composable: Build complex AI systems by combining smaller, reusable components
- ποΈ Production-Ready: Built-in best practices and optimizations for production deployments
- π YAML-First: Define your entire agent architecture in simple YAML
- π§ Flexible: Use pre-built components or create your own
- π€ Team-Oriented: Create and manage teams of AI agents working together
- π RAG Support: Built-in support for Retrieval-Augmented Generation
- π Langchain Compatible: Works with all your favorite Langchain tools
pip install flo-ai
# or using poetry
poetry add flo-ai
from flo_ai import Flo, FloSession
from langchain_openai import ChatOpenAI
# Define your team in YAML
yaml_config = """
apiVersion: flo/alpha-v1
kind: FloRoutedTeam
name: research-team
team:
name: ResearchTeam
router:
name: TeamLead
kind: supervisor
agents:
- name: Researcher
role: Research Specialist
job: Research latest information on given topics
tools:
- name: TavilySearchResults
- name: Writer
role: Content Creator
job: Create engaging content from research
"""
# Set up and run
llm = ChatOpenAI(temperature=0)
session = FloSession(llm).register_tool(name="TavilySearchResults", tool=TavilySearchResults())
flo = Flo.build(session, yaml=yaml_config)
# Start streaming results
for response in flo.stream("Write about recent AI developments"):
print(response)
Visit our comprehensive documentation for:
- Detailed tutorials
- Architecture deep-dives
- API reference
- Best practices
- Advanced examples
- Faster Development: Build complex AI systems in minutes, not days
- Production Focus: Built-in optimizations and best practices
- Flexibility: Use our components or build your own
- Maintainable: YAML-first approach makes systems easy to understand and modify
- Scalable: From single agents to complex team hierarchies
- Testable: Each component can be tested independently
- π€ Customer Service Automation
- π Data Analysis Pipelines
- π Content Generation
- π Research Automation
- π― Task-Specific AI Teams
We love your input! Check out our Contributing Guide to get started. Ways to contribute:
- π Report bugs
- π‘ Propose new features
- π Improve documentation
- π§ Submit PRs
Flo AI is MIT Licensed.
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