Quickstart
Install 💻
$ pip install crowe-b
Crowe Chat
$ crowe /
# Say hello
crowe /hi
# Ask a question
crowe /how is the weather today?
Using uv (Recommended)
uv is a fast Python package installer and resolver, written in Rust.
# Install uv
$ curl -LsSf https://astral.sh/uv/install.sh | sh
# Install crowe using uv
$ uv pip install crowe
Using poetry
# Install poetry if you haven't already
$ curl -sSL https://install.python-poetry.org | python3 -
# Add crowe to your project
$ poetry add crowe
Environment Configuration
OPENAI_API_KEY=""
WORKSPACE_DIR="agent_workspace"
ANTHROPIC_API_KEY=""
GROQ_API_KEY=""
🤖 Your First Agent¶
An Agent is the fundamental building block of a croweo—an autonomous entity powered by an LLM + Tools + Memory.
from crowe import Agent
# Initialize a new agent
agent = Agent(
model_name="gpt-4o-mini", # Specify the LLM
max_loops=1, # Set the number of interactions
interactive=True, # Enable interactive mode for real-time feedback
)
# Run the agent with a task
agent.run("What are the primary advantages of adopting a multi-agent system?")
🤝 Your First Crowe: Multi-Agent Collaboration A Crowe consists of multiple agents working together. This simple example creates a two-agent workflow for researching and writing a blog post.
from crowe import Agent, SequentialWorkflow
# Agent 1: The Market Analyst
analyst = Agent(
agent_name="Market Analyst",
system_prompt="Analyze the target audience and recent market trends, then produce a concise insights report.",
model_name="gpt-5",
)
# Agent 2: The Content Strategist
strategist = Agent(
agent_name="Content Strategist",
system_prompt="Using the insights report, craft a persuasive and creative product launch announcement.",
model_name="gpt-5",
)
# Create a sequential workflow where the analyst's output becomes the strategist's input
workflow = SequentialWorkflow(agents=[analyst, strategist])
# Execute the workflow for a given task
launch_announcement = workflow.run("Launch of an eco-friendly smart home assistant")
print(launch_announcement)
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