"""LinkedIn profile recipe — the first supported site.

Target page: a person's profile (linkedin.com/in/...), typically reached from
search. Anything else on LinkedIn (feed, search results, messaging) is not a
target; non-LinkedIn pages don't match at all.
"""
from __future__ import annotations

import re
from typing import Any, Optional

from core.models import Lead, PageContext, PageMatch
from .base import SiteRecipe

_PROFILE_RE = re.compile(r"linkedin\.com/in/[^/?#]+", re.I)
_LINKEDIN_RE = re.compile(r"linkedin\.com", re.I)


class LinkedInRecipe(SiteRecipe):
    site_id = "linkedin"
    display_name = "LinkedIn"
    enabled = True
    target_page_type = "profile"

    def matches(self, ctx: PageContext) -> Optional[PageMatch]:
        url = ctx.best_url
        if url:
            if _PROFILE_RE.search(url):
                return PageMatch(self.site_id, "profile", is_target=True)
            if _LINKEDIN_RE.search(url):
                return PageMatch(self.site_id, "other", is_target=False)
            return None
        # No URL available: fall back to the AI's visual read.
        if (ctx.ai_site or "").lower() == "linkedin":
            page_type = (ctx.ai_page_type or "other").lower()
            return PageMatch(self.site_id, page_type, is_target=(page_type == "profile"))
        return None

    @property
    def extraction_schema(self) -> dict[str, Any]:
        str_fields = [
            "full_name", "headline", "current_title", "current_company",
            "location", "about", "email", "phone", "website",
        ]
        props: dict[str, Any] = {f: {"type": "string"} for f in str_fields}
        props["other_profiles"] = {"type": "array", "items": {"type": "string"}}
        props["confidence"] = {"type": "number"}
        return {
            "type": "object",
            "properties": props,
            "required": str_fields + ["other_profiles", "confidence"],
            "additionalProperties": False,
        }

    @property
    def extraction_prompt(self) -> str:
        return (
            "These screenshots are a single LinkedIn profile page, captured top "
            "to bottom. Extract the person's details into the required JSON. "
            "Rules: use an empty string \"\" for any field not visible; do NOT "
            "guess or invent contact details. Email, phone and website usually "
            "only appear if the user opened the 'Contact info' panel — extract "
            "them only if they are actually shown. 'other_profiles' is any other "
            "social/web links visible (Twitter/X, GitHub, personal site). "
            "'confidence' is 0-1 for how legible the profile was."
        )

    def to_canonical(self, raw: dict[str, Any]) -> Lead:
        socials: dict[str, str] = {}
        for link in raw.get("other_profiles") or []:
            low = link.lower()
            if "github.com" in low:
                socials["github"] = link
            elif "twitter.com" in low or "x.com" in low:
                socials["twitter"] = link
            else:
                socials.setdefault("other", link)
        return Lead(
            full_name=raw.get("full_name", "") or "",
            headline=raw.get("headline", "") or "",
            title=raw.get("current_title", "") or "",
            company=raw.get("current_company", "") or "",
            location=raw.get("location", "") or "",
            about=raw.get("about", "") or "",
            email=raw.get("email", "") or "",
            phone=raw.get("phone", "") or "",
            website=raw.get("website", "") or "",
            social_handles=socials,
            source_site=self.site_id,
            confidence=float(raw.get("confidence", 0) or 0),
        )