"""Step 3 (SPEC L-13, L-16): the LLM turns the question into an `AgentLogQuery`. It never sees the logs."""

from dataclasses import dataclass
from datetime import datetime

from pydantic import ValidationError

from app.agent.log_query import AgentLogQuery, json_schema
from app.llm.provider import ChatMessage, JsonSchema, LLMProvider

SCHEMA = JsonSchema(name="log_query", schema=json_schema())


@dataclass(frozen=True)
class Plan:
    query: AgentLogQuery | None  # None — the reply didn't pass validation
    error: str
    tokens: int


def system_prompt(template: str, containers: list[str], default: str, now: datetime) -> str:
    # str.replace, not format: the template contains JSON braces
    return (
        template.replace("{containers}", ", ".join(containers))
        .replace("{default}", default)
        .replace("{now}", now.strftime("%Y-%m-%d %H:%M"))
    )


async def plan(
    llm: LLMProvider, template: str, prompt: str, containers: list[str], default: str, now: datetime
) -> Plan:
    messages = [ChatMessage("system", system_prompt(template, containers, default, now)), ChatMessage("user", prompt)]
    result = await llm.complete(messages, SCHEMA)
    if result.data is None:
        return Plan(None, "not JSON", result.tokens)
    try:
        query = AgentLogQuery.model_validate(result.data, context={"containers": containers})
    except ValidationError as e:
        return Plan(
            None,
            "; ".join(f"{'.'.join(map(str, err['loc']))}: {err['msg']}" for err in e.errors())[:300],
            result.tokens,
        )
    return Plan(query, "", result.tokens)