Python SDK

Use the official OpenAI Python SDK with GonkaGate. No custom SDK required.

Installation

Install the official OpenAI Python SDK:

terminal

pip install openai

Configuration

Configure the client to use GonkaGate's API endpoint:

config.py

from openai import OpenAI

client = OpenAI(
    base_url="https://api.gonkagate.com/v1",
    api_key="gp-your-api-key"  # Get from dashboard
)

Basic Usage

Make your first chat completion request:

basic_usage.py

from openai import OpenAI

client = OpenAI(
    base_url="https://api.gonkagate.com/v1",
    api_key="gp-your-api-key"
)

response = client.chat.completions.create(
    model="Qwen/Qwen3-235B-A22B-Instruct-2507-FP8",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello, how are you?"}
    ],
    temperature=0.7,
    max_tokens=1000
)

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

Streaming

Stream responses for real-time output:

streaming.py

from openai import OpenAI

client = OpenAI(
    base_url="https://api.gonkagate.com/v1",
    api_key="gp-your-api-key"
)

stream = client.chat.completions.create(
    model="Qwen/Qwen3-235B-A22B-Instruct-2507-FP8",
    messages=[{"role": "user", "content": "Write a poem about AI"}],
    stream=True
)

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

    # Final chunk contains usage
    if chunk.usage:
        print(f"\n\nCost: ${chunk.usage.total_cost_usd:.6f}")

Cost Tracking

Track usage and costs per request:

Extended Usage Fields — GonkaGate adds base_cost_usd, platform_fee_usd, and total_cost_usd to the standard usage object.

cost_tracking.py

response = client.chat.completions.create(
    model="Qwen/Qwen3-235B-A22B-Instruct-2507-FP8",
    messages=[{"role": "user", "content": "Hello!"}]
)

# Access cost information
usage = response.usage
print(f"Prompt tokens: {usage.prompt_tokens}")
print(f"Completion tokens: {usage.completion_tokens}")
print(f"Total tokens: {usage.total_tokens}")
print(f"Base cost: ${usage.base_cost_usd:.6f}")
print(f"Platform fee: ${usage.platform_fee_usd:.6f}")
print(f"Total cost: ${usage.total_cost_usd:.6f}")

Error Handling

Handle common API errors gracefully:

error_handling.py

from openai import OpenAI, APIError, RateLimitError, AuthenticationError

client = OpenAI(
    base_url="https://api.gonkagate.com/v1",
    api_key="gp-your-api-key"
)

try:
    response = client.chat.completions.create(
        model="Qwen/Qwen3-235B-A22B-Instruct-2507-FP8",
        messages=[{"role": "user", "content": "Hello!"}]
    )
except AuthenticationError as e:
    print(f"Invalid API key: {e}")
except RateLimitError as e:
    print(f"Rate limited. Retry after: {e.response.headers.get('Retry-After')} seconds")
except APIError as e:
    if e.status_code == 402:
        print("Insufficient balance. Please add funds.")
    else:
        print(f"API error: {e}")

Async Usage

Use async/await for non-blocking requests:

async_usage.py

import asyncio
from openai import AsyncOpenAI

async def main():
    client = AsyncOpenAI(
        base_url="https://api.gonkagate.com/v1",
        api_key="gp-your-api-key"
    )

    response = await client.chat.completions.create(
        model="Qwen/Qwen3-235B-A22B-Instruct-2507-FP8",
        messages=[{"role": "user", "content": "Hello!"}]
    )

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

asyncio.run(main())