Model Selection & Mini Mode

class OllamaModelSelector:
    """Smart model selection layered over OllamaAdapter."""

    def __init__(self, adapter: OllamaAdapter):
        self.adapter = adapter

    async def installed(self) -> list[dict]:
        r = await self.adapter.client.get(f"{self.adapter.base_url}/api/tags")
        r.raise_for_status()
        return r.json().get("models", [])

    def classify(self, model_info: dict) -> str:
        size = model_info.get("details", {}).get("parameter_size", "")
        try:
            params_b = float(size.replace("B", "").strip())
        except ValueError:
            params_b = 0.0
        if params_b <= 3:
            return "mini"
        if params_b <= 14:
            return "standard"
        return "large"

    def system_prompt_for(self, klass: str) -> str:
        if klass == "mini":
            # Small models: stripped down — plan + format only
            return (
                "You are a helpful assistant. Be concise. "
                "If asked to use a tool, call it directly without commentary."
            )
        # standard + large can handle the full prompt
        return (
            "You are a knowledgeable AI assistant with expertise in software "
            "engineering, data analysis, and creative work. Think step by step. "
            "Provide detailed, accurate responses. When using tools, explain "
            "your plan in one sentence before calling them."
        )

    async def system_prompt_for_active(self) -> str:
        """Look up the active model's class and return the right prompt."""
        models = await self.installed()
        info = next((m for m in models if m["name"] == self.adapter.model), {})
        return self.system_prompt_for(self.classify(info))