Google

Integrate Google Gemini models through the Adaline Proxy for automatic telemetry and observability.

Google

Integrate Google Gemini models through the Adaline Proxy to automatically capture telemetry — requests, responses, token usage, latency, and costs — with minimal code changes.

Supported Models

Chat Models

Model	Description
gemini-3.1-pro-preview	Latest Gemini 3.1 Pro preview
gemini-3.1-pro-preview-customtools	Gemini 3.1 Pro preview with custom tools
gemini-3-pro-preview	Gemini 3 Pro preview
gemini-3-flash-preview	Gemini 3 Flash preview
gemini-2.5-pro	Gemini 2.5 Pro
gemini-2.5-pro-preview-03-25	Gemini 2.5 Pro March 2025 preview
gemini-2.5-flash	Gemini 2.5 Flash
gemini-2.5-flash-preview-04-17	Gemini 2.5 Flash April 2025 preview
gemini-2.5-flash-lite	Lightweight Gemini 2.5
gemini-2.5-flash-lite-preview-09-2025	Gemini 2.5 Flash Lite September 2025 preview
gemini-2.0-flash	Fast Gemini 2.0 model
gemini-2.0-flash-lite	Lightweight Gemini 2.0
gemini-1.5-pro	Gemini 1.5 Pro, 1M token context
gemini-1.5-pro-latest	Gemini 1.5 Pro latest
gemini-1.5-pro-002	Gemini 1.5 Pro version 002
gemini-1.5-pro-001	Gemini 1.5 Pro version 001
gemini-1.5-flash	Gemini 1.5 Flash
gemini-1.5-flash-latest	Gemini 1.5 Flash latest
gemini-1.5-flash-002	Gemini 1.5 Flash version 002
gemini-1.5-flash-001	Gemini 1.5 Flash version 001

Embedding Models

Model	Description
text-embedding-004	Latest text embedding model
text-embedding-001	Legacy embedding model

Proxy Base URL

https://gateway.adaline.ai/v1/google

Prerequisites

1. A Google AI API key
2. An Adaline API key, project ID, and prompt ID

Chat Completions

Complete Chat

Python

from google import genai
from google.genai import types

client = genai.Client(
    http_options={
        "base_url": "https://gateway.adaline.ai/v1/google",
        "headers": {
            "adaline-api-key": "your-adaline-api-key",
            "adaline-project-id": "your-project-id",
            "adaline-prompt-id": "your-prompt-id",
        },
    },
    api_key="your-google-api-key",
)

response = client.models.generate_content(
    model="gemini-1.5-pro",
    contents="What is the future of artificial intelligence?",
    config=types.GenerateContentConfig(
        http_options=types.HttpOptions(
            headers={
                "adaline-trace-name": "google-chat-completion"  # Optional
            }
        )
    )
)

print(response.text)

Google’s SDK uses http_options for base URL and headers, rather than base_url and extra_headers like OpenAI-compatible SDKs.

Stream Chat

Python

from google import genai
from google.genai import types

client = genai.Client(
    http_options={
        "base_url": "https://gateway.adaline.ai/v1/google",
        "headers": {
            "adaline-api-key": "your-adaline-api-key",
            "adaline-project-id": "your-project-id",
            "adaline-prompt-id": "your-prompt-id",
        },
    },
    api_key="your-google-api-key",
)

stream = client.models.generate_content_stream(
    model="gemini-1.5-pro",
    contents="Explain the concept of machine learning in detail.",
    config=types.GenerateContentConfig(
        http_options=types.HttpOptions(
            headers={
                "adaline-trace-name": "google-stream-chat"  # Optional
            }
        )
    )
)

for chunk in stream:
    if hasattr(chunk, 'text') and chunk.text:
        print(chunk.text, end="")

Embeddings

Python

from google import genai
from google.genai import types

client = genai.Client(
    http_options={
        "base_url": "https://gateway.adaline.ai/v1/google",
        "headers": {
            "adaline-api-key": "your-adaline-api-key",
            "adaline-project-id": "your-project-id",
            "adaline-prompt-id": "your-prompt-id",
        },
    },
    api_key="your-google-api-key",
)

response = client.models.embed_content(
    model="text-embedding-004",
    contents="The quick brown fox jumps over the lazy dog",
    config=types.EmbedContentConfig(
        http_options=types.HttpOptions(
            headers={
                "adaline-trace-name": "google-embedding"  # Optional
            }
        )
    )
)

Next Steps

• Multi-Step Workflows — RAG pipelines, multi-step generation, and conversational agents
• Headers Reference — Complete header documentation

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