Anthropic

result = await generate_text(
    model=anthropic("claude-opus-4-7"),
    prompt="Analyze this carefully.",
    reasoning={"effort": "medium"},
    max_tokens=4096,
)

result = await generate_text(
    model=anthropic("claude-3-7-sonnet-20250219"),
    prompt="Think through this.",
    reasoning={"budget": 8000},
    max_tokens=16000,
)

export ANTHROPIC_API_KEY="sk-ant-..."

from ai_query import generate_text
from ai_query.providers import anthropic

result = await generate_text(
    model=anthropic("claude-4-5-sonnet-20250929"),
    prompt="Explain the theory of relativity."
)

result = await generate_text(
    model=anthropic("claude-sonnet-4-20250514"),
    prompt="Write a detailed analysis.",
    provider_options={
        "anthropic": {
            "temperature": 0.7,
            "max_tokens": 2000,
            "top_p": 0.9
        }
    }
)

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

@tool(description="Calculate a math expression")
async def calculate(
    expression: str = Field(description="Math expression to evaluate")
) -> str:
    result = eval(expression)  # Use a safe evaluator in production
    return str(result)

result = await generate_text(
    model=anthropic("claude-sonnet-4-20250514"),
    prompt="What is (15 * 8) + (42 / 6)?",
    tools={"calculate": calculate}
)

from ai_query import stream_text
from ai_query.providers import anthropic

result = stream_text(
    model=anthropic("claude-sonnet-4-20250514"),
    prompt="Explain quantum entanglement step by step."
)

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

result = await generate_text(
    model=anthropic("claude-sonnet-4-20250514"),
    system="""You are an expert Python developer.
    Always provide working code examples.
    Explain your reasoning step by step.""",
    prompt="How do I implement a binary search tree?"
)