"""CLI tool to parse raw log lines into typed ApiEvent objects using LangChain structured output.

Usage:
    python parse_log.py [--log FILE]

If --log is omitted, a built‑in example log is used.
"""

from __future__ import annotations

import argparse
import sys
from pathlib import Path
from typing import Iterable, List

from langchain_core.output_parsers import PydanticOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_openai import ChatOpenAI

from models import ApiEvent

# Example log with mixed OK and error events
EXAMPLE_LOG = """
GET /api/users 200 123ms
POST /api/login 404 Not Found
GET /api/data 200 456ms
GET /api/health 500 Internal Server Error
"""

# Prompt template that instructs LLM to output a single ApiEvent in JSON
PROMPT = ChatPromptTemplate.from_messages(
    [
        ("system", "You are a helpful assistant that parses a single log line into a structured event.")
    ]
)

# Create a parser for the ApiEvent union
parser = PydanticOutputParser(pydantic_object=ApiEvent)

# LLM model – replace with your own key or use a local model
llm = ChatOpenAI(temperature=0, model="gpt-4o-mini")


def parse_line(line: str) -> ApiEvent:
    """Parse a single log line using the LLM and the structured output parser."""
    # Build a prompt that includes the line and asks for JSON
    prompt = PROMPT.format_messages(user=line)
    # Get raw response
    raw = llm.invoke(prompt)
    # Parse into ApiEvent
    return parser.parse(raw.content)


def parse_log(lines: Iterable[str]) -> List[ApiEvent]:
    return [parse_line(line) for line in lines if line.strip()]


def main() -> None:
    parser_cli = argparse.ArgumentParser(description="Parse raw log into typed events")
    parser_cli.add_argument("--log", type=Path, help="Path to a log file; if omitted, example log is used")
    args = parser_cli.parse_args()

    if args.log and args.log.exists():
        raw_lines = args.log.read_text().splitlines()
    else:
        raw_lines = EXAMPLE_LOG.strip().splitlines()

    events = parse_log(raw_lines)

    # Print each event as JSON
    for ev in events:
        print(ev.model_dump_json(indent=2))

    # Simple table
    print("\nParsed events table:\n")
    print("{:<6} {:<20} {:<6} {}".format("kind", "path", "status", "details"))
    for ev in events:
        if ev.kind == "ok":
            print(f"{ev.kind:<6} {ev.path:<20} {ev.status:<6} duration={ev.duration_ms}ms")
        else:
            print(f"{ev.kind:<6} {ev.path:<20} {ev.status:<6} error={ev.error_message}")


if __name__ == "__main__":
    main()