"""Call an OpenAI-compatible chat completions endpoint to generate jokes."""
import json
import re

import httpx

from .config import settings

SYSTEM_PROMPT = (
    "You are a comedian. You will receive the text of Wikipedia's featured article "
    "of the day. Write exactly 5 short, clean, family-friendly jokes inspired by "
    "facts from the article. Vary the style (one-liners, puns, observational). "
    "The jokes must be understandable on their own without reading the article. "
    "Respond with ONLY a JSON array of 5 strings and nothing else. "
    "Example: [\"joke one\", \"joke two\", \"joke three\", \"joke four\", \"joke five\"]"
)


def _extract_json_array(text: str) -> list[str]:
    """Pull a JSON array of strings out of a possibly messy LLM response."""
    text = text.strip()
    # Strip markdown fences if present.
    fence = re.search(r"```(?:json)?\s*(.*?)```", text, re.DOTALL)
    if fence:
        text = fence.group(1).strip()
    # Find the outermost [...] span.
    start = text.find("[")
    end = text.rfind("]")
    if start == -1 or end == -1 or end <= start:
        raise ValueError(f"No JSON array found in LLM response: {text[:200]!r}")
    data = json.loads(text[start : end + 1])
    if not isinstance(data, list):
        raise ValueError("Parsed JSON is not a list")
    jokes = [str(j).strip() for j in data if str(j).strip()]
    if len(jokes) < 5:
        raise ValueError(f"Only {len(jokes)} jokes returned, expected 5")
    return jokes[:5]


def generate_jokes(article_title: str, article_extract: str) -> list[str]:
    url = f"{settings.openai_base_url}/chat/completions"
    headers = {"Content-Type": "application/json"}
    if settings.openai_api_key:
        headers["Authorization"] = f"Bearer {settings.openai_api_key}"

    user_prompt = (
        f"Today's Wikipedia featured article: \"{article_title}\"\n\n"
        f"Article text:\n{article_extract}\n\n"
        "Now write exactly 5 jokes as a JSON array of 5 strings."
    )

    body = {
        "model": settings.openai_model,
        "messages": [
            {"role": "system", "content": SYSTEM_PROMPT},
            {"role": "user", "content": user_prompt},
        ],
        "temperature": 0.9,
        "max_tokens": 800,
    }

    resp = httpx.post(url, headers=headers, json=body, timeout=120)
    resp.raise_for_status()
    payload = resp.json()
    content = payload["choices"][0]["message"]["content"]
    return _extract_json_array(content)