Getting Started with GauGau AI

Welcome to GauGau AI! This guide will walk you through everything you need to know to start using our unified API for accessing 700+ AI models from 60+ providers.

Why Choose GauGau AI?

GauGau AI provides a single, standardized API that works with every major AI model. Instead of managing multiple API keys and learning different APIs for each provider, you get:

• One API for everything - OpenAI-compatible interface for all models
• Automatic failover - Never experience downtime when providers go offline
• Smart routing - Get the best price and latency automatically
• Simple pricing - Pay only for what you use, no subscriptions required

Step 1: Get Your API Key

Getting started is incredibly simple:

1. Contact us on Telegram at @gaugauai
2. Choose your credit package (starting from $9)
3. Make payment via bank transfer or e-wallet (Momo, ZaloPay, ViettelPay)
4. Receive your API key within minutes

No account creation needed. No international credit card required.

Step 2: Make Your First API Call

Once you have your API key, making your first request is straightforward. Here's a simple example using Python:

import openai

client = openai.OpenAI(
    api_key="YOUR_GAUGAU_API_KEY",
    base_url="https://api.gaugauai.com/v1"
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "user", "content": "Hello, how are you?"}
    ]
)

print(response.choices[0].message.content)

That's it! You're now using GPT-4o through GauGau AI.

Step 3: Try Different Models

The beauty of GauGau AI is that switching models is as simple as changing one parameter:

# Use Claude 3.5 Sonnet
response = client.chat.completions.create(
    model="claude-3.5-sonnet",
    messages=[{"role": "user", "content": "Explain quantum computing"}]
)

# Use Gemini Pro
response = client.chat.completions.create(
    model="gemini-pro",
    messages=[{"role": "user", "content": "Write a poem about AI"}]
)

# Use DeepSeek for cost-effective tasks
response = client.chat.completions.create(
    model="deepseek-chat",
    messages=[{"role": "user", "content": "Summarize this text"}]
)

Understanding Token Pricing

GauGau AI uses a simple credit system:

• $1 = 500,000 base tokens
• Different models have different ratio multipliers
• Budget models (0.22 ratio): DeepSeek, Qwen, Gemma
• Standard models (0.3 ratio): Llama, Mistral, Phi
• Advanced models (0.5 ratio): GPT-4o mini, Claude Haiku
• Premium models (1.0 ratio): GPT-4o, Claude Opus, Gemini Pro

All ratios give you the same token count - higher ratios simply mean more capable models.

Best Practices

1. Choose the Right Model for the Task

Don't use premium models for simple tasks. Use budget models for:

• Text summarization
• Simple Q&A
• Content classification
• Data extraction

Reserve premium models for:

• Complex reasoning
• Creative writing
• Code generation
• Multi-step problem solving

2. Implement Error Handling

Always handle potential errors in your code:

try:
    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": "Hello"}]
    )
except openai.APIError as e:
    print(f"API error: {e}")
except openai.RateLimitError as e:
    print(f"Rate limit exceeded: {e}")

3. Monitor Your Usage

Keep track of your token consumption to optimize costs:

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello"}]
)

print(f"Tokens used: {response.usage.total_tokens}")
print(f"Prompt tokens: {response.usage.prompt_tokens}")
print(f"Completion tokens: {response.usage.completion_tokens}")

Advanced Features

Streaming Responses

Get responses as they're generated for better UX:

stream = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Write a story"}],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

Function Calling

Enable models to call your functions:

functions = [
    {
        "name": "get_weather",
        "description": "Get current weather",
        "parameters": {
            "type": "object",
            "properties": {
                "location": {"type": "string"}
            }
        }
    }
]

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "What's the weather in Tokyo?"}],
    functions=functions
)

Next Steps

Now that you're up and running, explore:

• Browse our model catalog to discover 700+ available models
• Check out pricing options to find the best package for your needs
• Join our community on Telegram for support and updates

Need Help?

If you run into any issues or have questions:

• Contact us on Telegram: @gaugauai
• Email support: support@gaugauai.com
• Check our documentation for detailed API references

Happy building with GauGau AI!