"""Claude prompt step — call LLM via LiteLLM proxy."""

import logging

logger = logging.getLogger(__name__)


async def execute_claude_prompt(
    config: dict,
    llm=None,
    default_model: str = "claude-haiku",
    escalation_model: str = "claude-sonnet",
    **_kwargs,
) -> str:
    """Send a prompt to Claude and return the response."""
    if not llm:
        raise RuntimeError("LLM client not configured")

    prompt = config.get("prompt", "")
    if not prompt:
        raise ValueError("claude_prompt step requires 'prompt' field")

    model_name = config.get("model", "default")
    model = escalation_model if model_name == "escalation" else default_model

    response = await llm.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": prompt}],
        max_tokens=4096,
    )

    return response.choices[0].message.content or ""