Google

export GOOGLE_API_KEY="..."

from ai_query import generate_text
from ai_query.providers import google

result = await generate_text(
    model=google("gemini-2.5-flash"),
    prompt="Summarize the key features of Python."
)

result = await generate_text(
    model=google("gemini-2.0-flash"),
    prompt="Write a story.",
    provider_options={
        "google": {
            "temperature": 0.7,
            "top_p": 0.95,
            "top_k": 40,
            "max_output_tokens": 2048,
            "presence_penalty": 0.0,
            "frequency_penalty": 0.0,
            "seed": 42
        }
    }
)

result = await generate_text(
    model=google("gemini-2.5-pro"),
    prompt="Solve this carefully.",
    reasoning={"budget": 1024},
)

result = await generate_text(
    model=google("gemini-3-flash"),
    prompt="Solve this complex math problem...",
    provider_options={
        "google": {
            "thinking_config": {
                "include_thoughts": True,
                "thinking_budget": 1024
            }
        }
    }
)

# Dict format (shorthand)
result = await generate_text(
    model=google("gemini-2.0-flash"),
    prompt="Write a thriller story.",
    provider_options={
        "google": {
            "safety_settings": {
                "HARM_CATEGORY_VIOLENCE": "BLOCK_ONLY_HIGH",
                "HARM_CATEGORY_HATE_SPEECH": "BLOCK_MEDIUM_AND_ABOVE"
            }
        }
    }
)

# List format (official API format)
result = await generate_text(
    model=google("gemini-2.0-flash"),
    prompt="Write a thriller story.",
    provider_options={
        "google": {
            "safety_settings": [
                {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_LOW_AND_ABOVE"},
                {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_MEDIUM_AND_ABOVE"},
                {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_ONLY_HIGH"},
                {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"}
            ]
        }
    }
)

from ai_query import generate_text
from ai_query.providers import google, tool, Field

@tool(description="Get current stock price")
async def get_stock_price(
    symbol: str = Field(description="Stock ticker symbol")
) -> str:
    # Simulated stock data
    prices = {"GOOGL": 175.50, "AAPL": 150.25}
    price = prices.get(symbol.upper(), 0)
    return f"${price:.2f}"

result = await generate_text(
    model=google("gemini-2.0-flash"),
    prompt="What's the stock price of Google?",
    tools={"get_stock_price": get_stock_price}
)

from ai_query import stream_text
from ai_query.providers import google

result = stream_text(
    model=google("gemini-2.0-flash"),
    prompt="Explain how neural networks learn."
)

async for chunk in result.text_stream:
    print(chunk, end="", flush=True)