> ## Documentation Index
> Fetch the complete documentation index at: https://wavefront.rootflo.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Get started with Flo AI in minutes - from installation to your first agent

## Get started with Flo AI in three steps

Build your first AI agent and understand the core concepts of Flo AI.

### Step 1: Installation

<AccordionGroup>
  <Accordion icon="download" title="Install Flo AI">
    Install Flo AI using pip or poetry:

    ```bash theme={null}
    pip install flo-ai
    poetry add flo-ai
    uv add flo-ai
    ```

    <Tip>Flo AI requires Python 3.10 or higher.</Tip>
  </Accordion>

  <Accordion icon="key" title="Set up API keys">
    Configure your LLM provider API keys:

    ```bash theme={null}
    export OPENAI_API_KEY="your-openai-key"
    export ANTHROPIC_API_KEY="your-anthropic-key"
    export GOOGLE_API_KEY="your-google-key"
    ```
  </Accordion>
</AccordionGroup>

### Step 2: Your First Agent

<Accordion icon="robot" title="Create a simple agent">
  Create your first conversational agent:

  ```python theme={null}
  import asyncio
  from flo_ai.agent import AgentBuilder
  from flo_ai.llm import OpenAI

  async def main():
      # Create a simple conversational agent
      agent = (
          AgentBuilder()
          .with_name('Math Tutor')
          .with_prompt('You are a helpful math tutor.')
          .with_llm(OpenAI(model='gpt-4o-mini'))
          .build()
      )

      response = await agent.run('What is the formula for the area of a circle?')
      print(f'Response: {response[-1].content}')

  asyncio.run(main())
  ```

  <Warning>Make sure you have set your OpenAI API key before running this example.</Warning>
</Accordion>

### Step 3: Add Tools and Structure

<Accordion icon="wrench" title="Create a tool-using agent">
  Build an agent that can use tools:

  ```python theme={null}
  import asyncio
  from flo_ai.agent import AgentBuilder
  from flo_ai.tool import flo_tool
  from flo_ai.llm import Anthropic

  @flo_tool(description="Perform mathematical calculations")
  async def calculate(operation: str, x: float, y: float) -> float:
      """Calculate mathematical operations between two numbers."""
      operations = {
          'add': lambda: x + y,
          'subtract': lambda: x - y,
          'multiply': lambda: x * y,
          'divide': lambda: x / y if y != 0 else 0,
      }
      return operations.get(operation, lambda: 0)()

  async def main():
      agent = (
          AgentBuilder()
          .with_name('Calculator Assistant')
          .with_prompt('You are a math assistant that can perform calculations.')
          .with_llm(Anthropic(model='claude-3-5-sonnet-20240620'))
          .with_tools([calculate.tool])
          .build()
      )

      response = await agent.run('Calculate 5 plus 3')
      print(f'Response: {response[-1].content}')

  asyncio.run(main())
  ```
</Accordion>

## Next Steps

Now that you have your first agent running, explore these key features:

<CardGroup cols={2}>
  <Card title="Multi-Agent Workflows" icon="sitemap" href="/essentials/arium">
    Learn how to create complex multi-agent workflows with Arium.
  </Card>

  <Card title="YAML Configuration" icon="file-code" href="/essentials/yaml-workflows">
    Define entire agent architectures in YAML for easy management.
  </Card>

  <Card title="Visual Studio" icon="palette" href="/essentials/studio">
    Design AI workflows visually with our React-based studio.
  </Card>

  <Card title="Production Deployment" icon="rocket" href="/essentials/production">
    Learn about production-ready features and best practices.
  </Card>
</CardGroup>

<Note>
  **Need help?** Check out our
  [examples](https://github.com/rootflo/flo-ai/tree/main/flo_ai/examples) or
  join our [community](https://github.com/rootflo/flo-ai/discussions).
</Note>