# Quick Start Guide

Get up and running with NeuraAI in minutes. This guide will walk you through making your first API call.

## Installation

Since NeuraAI is fully compatible with the OpenAI interface, you can use the official OpenAI Python client:

```bash
pip install openai
```

## Get Your API Key

1. Sign up at [neura-ai.app](https://neura-ai.app)
2. Navigate to your dashboard
3. Generate a new API key
4. Store it securely as an environment variable

```bash
export NEURA_API_KEY='your-api-key-here'
```

## Your First Request

Here's a simple example to get started with text generation:

```python
from openai import OpenAI

# Initialize the client
client = OpenAI(
    base_url="https://api.neura-ai.app/v1",
    api_key="your-api-key-here"  # Or use environment variable
)

# Create a chat completion
response = client.chat.completions.create(
    model="gpt-5",
    messages=[
        {
            "role": "user",
            "content": "Write me a haiku about artificial intelligence"
        }
    ]
)

# Print the response
print(response.choices[0].message.content)
```

## List Available Models

Discover which models are available for your use case:

```python
from openai import OpenAI

client = OpenAI(
    base_url="https://api.neura-ai.app/v1"
)

# Fetch all available models
models = client.models.list()

# Display model IDs
for model in models.data:
    print(model.id)
```

## Common Parameters

When making requests, you'll frequently use these parameters:

* **model** - The AI model to use (e.g., `gpt-5`, `gemini-2.5-pro`)
* **messages** - Array of conversation messages with role and content
* **temperature** - Controls randomness (0.0 = deterministic, 2.0 = very random)
* **max\_tokens** - Maximum length of the generated response
* **stream** - Enable streaming responses for real-time output

## Next Steps

Now that you've made your first request:

* Explore [Text Generation](/text-generation) for more advanced examples
* Learn about [Different Models](/models) and their capabilities
* Try [Image Generation](/image-generation) or [Audio Processing](/speech-to-text)
* Implement [Function Calling](/function-calling) for dynamic interactions