Google GenAI (gateway)

Route Google Gen AI SDK calls through the Respan gateway. Only your RESPAN_API_KEY is needed — no separate GOOGLE_API_KEY required.

Setup

Install packages

$ pip install google-genai

Set environment variables

$ export RESPAN_API_KEY="YOUR_RESPAN_API_KEY"

No GOOGLE_API_KEY needed — the Respan gateway handles provider authentication.

Point the Gen AI client to the Respan gateway

1 import os
2 from google import genai
3 
4 client = genai.Client(
5     api_key=os.environ["RESPAN_API_KEY"],
6     http_options={"base_url": "https://api.respan.ai/api/google/gemini"},
7 )
8 
9 response = client.models.generate_content(
10     model="gemini-3.5-flash",
11     contents="Hello, world!",
12 )
13 print(response.text)

Switch models

Change the model parameter to use different Gemini models through the same gateway.

1 response = client.models.generate_content(model="gemini-3.5-flash", contents="...")
2 response = client.models.generate_content(model="gemini-3.1-flash-lite", contents="...")
3 response = client.models.generate_content(model="gemini-3.1-pro-preview", contents="...")

See the full model list.

Advanced configuration

GenerateContentConfig supports system instructions, sampling parameters, tools, safety settings, and structured output.

1 from google.genai import types
2 
3 config = types.GenerateContentConfig(
4     system_instruction="You are a helpful assistant.",
5     temperature=0.7,
6     top_p=0.95,
7     top_k=40,
8     max_output_tokens=1024,
9     safety_settings=[
10         types.SafetySetting(
11             category=types.HarmCategory.HARM_CATEGORY_HATE_SPEECH,
12             threshold=types.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,
13         ),
14     ],
15 )
16 
17 response = client.models.generate_content(
18     model="gemini-3.5-flash",
19     contents="What is the capital of France?",
20     config=config,
21 )