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)

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="")

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
            }
        )
    )
)