# Core install (lightweight, ~27 deps, installs in seconds)
pip install agenticx

# Verify
agx --version

export OPENAI_API_KEY="sk-..."
# Optional
export ANTHROPIC_API_KEY="sk-ant-..."

agx project create my-first-agent --template basic
cd my-first-agent
agx project info

from agenticx import Agent, Task, AgentExecutor
from agenticx.llms import OpenAIProvider

agent = Agent(
    id="data-analyst",
    name="Data Analyst",
    role="Data Analysis Expert",
    goal="Help users analyze and understand data",
    organization_id="my-org"
)

task = Task(
    id="analysis-task",
    description="Analyze sales data trends",
    expected_output="Detailed analysis report"
)

llm = OpenAIProvider(model="gpt-4")
executor = AgentExecutor(agent=agent, llm=llm)
result = executor.run(task)
print(result)

# Scaffold an agent
agx agent create researcher --role "Senior Research Analyst"
agx agent list

# Scaffold a workflow
agx workflow create research-pipeline --agents "researcher"

# Run it
agx run workflows/research-pipeline.py --verbose

from agenticx.tools import tool

@tool
def calculate_sum(x: int, y: int) -> int:
    """Calculate the sum of two numbers."""
    return x + y

# Pass tools when creating agent or executor