# CrewAI — Multi-Agent Orchestration Framework

> Python framework for orchestrating autonomous AI agents that collaborate on complex tasks. Role-based agents with tools, memory, and delegation.

## Install

Copy the content below into your project:

# CrewAI — Multi-Agent Orchestration Framework

## Quick Use

```bash
# Install CrewAI
pip install crewai

# Create a new project
crewai create crew my-project
cd my-project

# Run your crew
crewai run
```

```python
from crewai import Agent, Task, Crew

researcher = Agent(
    role="Senior Researcher",
    goal="Find the latest AI trends",
    backstory="Expert AI researcher with 10 years experience",
    verbose=True
)

task = Task(
    description="Research the top 5 AI trends for 2026",
    expected_output="A bullet-point summary of trends",
    agent=researcher
)

crew = Crew(agents=[researcher], tasks=[task])
result = crew.kickoff()
print(result)
```

## Introduction

CrewAI is a **production-grade Python framework for building multi-agent AI systems**. Unlike single-agent approaches, CrewAI lets you define teams of specialized AI agents that collaborate, delegate, and share context to solve complex problems.

Core concepts:

- **Agents** — Autonomous units with specific roles, goals, backstories, and tool access. Each agent has a persona that guides its behavior.
- **Tasks** — Defined units of work assigned to agents, with expected outputs and optional dependencies.
- **Crews** — Teams of agents working together on a set of tasks, with configurable process flows (sequential, hierarchical, or custom).
- **Flows** — Event-driven orchestration layer for building structured, multi-step workflows that combine crews with conditional logic.
- **Tools** — 60+ built-in tools (web search, file I/O, code execution) plus easy custom tool creation.
- **Memory** — Short-term, long-term, and entity memory for agents to learn and improve across interactions.

Built from scratch (not a LangChain wrapper), optimized for performance and minimal resource usage.

## FAQ

**Q: How is CrewAI different from AutoGen or LangGraph?**
A: CrewAI focuses on role-based agent collaboration with a simpler API. It's standalone (no LangChain dependency), has built-in memory, and supports both autonomous crews and structured flows.

**Q: What LLMs does it support?**
A: Any LLM via LiteLLM — OpenAI, Anthropic Claude, Google Gemini, local models via Ollama, and 100+ others.

**Q: Can I use custom tools?**
A: Yes. Decorate any Python function with `@tool` or create a class inheriting from `BaseTool`. CrewAI also integrates with LangChain tools.

**Q: Is it production-ready?**
A: Yes. CrewAI AMP (Agent Monitoring Platform) provides enterprise features: observability, security guardrails, and deployment management.

## Works With

- Python 3.10+
- OpenAI / Anthropic / Google / Ollama / 100+ LLMs via LiteLLM
- Built-in tools: SerperDev, Browserbase, Firecrawl, code interpreter
- CrewAI AMP for production monitoring

## Source & Thanks

- GitHub: [crewAIInc/crewAI](https://github.com/crewAIInc/crewAI)
- License: MIT
- Stars: 47,000+
- Maintainer: CrewAI Inc. (@joaomdmoura)

Thanks to Joao Moura and the CrewAI team for building the most popular multi-agent framework, making collaborative AI accessible to every developer.


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Source: https://tokrepo.com/en/workflows/0db8af9b-8133-4a2e-ae19-8a56ed99a4a9
Author: Agent Toolkit