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

# Quickstart

> Get up and running with Fibonacci in under 5 minutes

## Prerequisites

Before you begin, make sure you have:

<CardGroup cols={2}>
  <Card title="Python 3.11+" icon="python">
    Fibonacci requires Python 3.11 or higher
  </Card>

  <Card title="API Key" icon="key">
    Sign up at [fibonacci.today](https://fibonacci.today) to get your API key
  </Card>
</CardGroup>

## Installation

Install the Fibonacci SDK using pip:

<CodeGroup>
  ```bash pip theme={null}
  pip install fibonacci-sdk
  ```

  ```bash poetry theme={null}
  poetry add fibonacci-sdk
  ```

  ```bash uv theme={null}
  uv add fibonacci-sdk
  ```
</CodeGroup>

<Note>
  For secure API key storage, install with the security extras:

  ```bash theme={null}
  pip install fibonacci-sdk[security]
  ```
</Note>

## Set Up Authentication

Create a `.env` file in your project root:

```bash .env theme={null}
FIBONACCI_API_KEY=fib_live_your_api_key_here
```

<Warning>
  Never commit your `.env` file to version control. Add it to your `.gitignore`.
</Warning>

Or use secure keychain storage (recommended for production):

```python theme={null}
from fibonacci import save_api_key_secure

# Save to system keychain (macOS Keychain, Windows Credential Manager, etc.)
save_api_key_secure("fib_live_your_api_key_here")
```

## Your First Workflow

Let's create a simple workflow that uses AI to analyze text:

```python theme={null}
from fibonacci import Workflow, LLMNode
from dotenv import load_dotenv
import os

# Load environment variables
load_dotenv()

# Create a workflow
wf = Workflow(
    name="Text Analyzer",
    description="Analyzes text for sentiment and key points"
)

# Add an LLM node
analyze = LLMNode(
    id="analyze_text",
    name="Analyze Text",
    instruction="""
    Analyze the following text and provide:
    1. Overall sentiment (positive, negative, neutral)
    2. Key points (bullet list)
    3. Suggested actions
    
    Text: {{input.text}}
    """
)

wf.add_node(analyze)

# Deploy to Fibonacci
workflow_id = wf.deploy(api_key=os.getenv("FIBONACCI_API_KEY"))
print(f"✅ Deployed! Workflow ID: {workflow_id}")

# Execute the workflow
result = wf.run(input_data={
    "text": "Our Q4 sales exceeded expectations by 15%. The team did an amazing job!"
})

print(f"Status: {result.status}")
print(f"Output: {result.output_data['analyze_text']}")
```

## Expected Output

```
✅ Deployed! Workflow ID: wf_abc123xyz

Status: completed
Output: 
**Sentiment:** Positive

**Key Points:**
- Q4 sales exceeded expectations by 15%
- Team performance was exceptional

**Suggested Actions:**
- Recognize and reward the team
- Analyze what contributed to success
- Set ambitious Q1 targets
```

## What's Next?

<CardGroup cols={2}>
  <Card title="Build Your First Real Workflow" icon="hammer" href="/getting-started/your-first-workflow">
    Create a complete workflow with multiple nodes and tool integrations
  </Card>

  <Card title="Learn About Nodes" icon="sitemap" href="/guides/nodes">
    Understand the different node types and when to use each
  </Card>

  <Card title="Explore Tools" icon="toolbox" href="/guides/tool-nodes">
    Connect to Google Sheets, Slack, and 100+ other services
  </Card>

  <Card title="Security Best Practices" icon="shield" href="/guides/security">
    Learn how to secure your API keys and audit your workflows
  </Card>
</CardGroup>

<Check>
  **Congratulations!** You've just created and deployed your first Fibonacci workflow.
</Check>