"""Injectable entry expansion protocol and deterministic P0 implementation."""

from __future__ import annotations

import re
from typing import Any, Protocol

_BULLET_PREFIX = re.compile(r"^(?:[•●▪◦]\s*|[-*]\s+|\d+[.)、]\s*)")


class EntryExpander(Protocol):
    """Produce an optimization proposal without mutating the source entry."""

    def expand(self, entry: dict[str, Any], *, context: dict[str, Any]) -> dict[str, Any]: ...


class RuleBasedEntryExpander:
    """Conservative local fallback used when no model is configured or available."""

    def expand(self, entry: dict[str, Any], *, context: dict[str, Any]) -> dict[str, Any]:
        entry_type = str(context.get("entry_type") or "")
        description = str(entry.get("description") or "").strip()
        highlights = [
            str(value).strip()
            for value in entry.get("highlights") or []
            if str(value).strip()
        ]
        material = description or "；".join(highlights)
        if material:
            optimized = _polish_text(material)
        else:
            optimized = _description_from_structured_facts(entry, entry_type)
        if not optimized:
            return {"optimized_description": "", "changes": [], "source": "rule_polish"}
        if entry_type != "education":
            optimized = normalize_bullet_description(optimized)
        changes = ["统一为简洁、正式的简历表达"]
        if not description and not highlights:
            changes = ["根据已填写的结构化事实补充经历描述"]
        return {
            "optimized_description": optimized,
            "changes": changes,
            "source": "rule_polish",
        }


def normalize_bullet_description(text: str) -> str:
    """Normalize existing lines into resume bullets without rewriting their text."""
    bullets: list[str] = []
    for raw_line in text.splitlines() or [text]:
        line = raw_line.strip()
        if not line:
            continue
        line = _BULLET_PREFIX.sub("", line).strip()
        if line:
            bullets.append(f"• {line}")
    return "\n".join(bullets)


def _polish_text(text: str) -> str:
    replacements = (
        (r"^做过", "完成"),
        (r"^做了", "完成"),
        (r"^拿了奖(?:项)?", "获得奖项"),
        (r"^参与了", "参与"),
        (r"^使用了?\s*(?=[A-Za-z0-9])", "基于 "),
        (r"^帮忙", "协助"),
        (r"^负责", "承担"),
        (r"^参加", "参与"),
        (r"，将", "，推动"),
        (r"，获得", "，并获得"),
        (r"降低了", "降低"),
        (r"提升了", "提升"),
        (r"优化了", "优化"),
    )
    parts: list[str] = []
    for raw in re.split(r"[。；;\n]+", text):
        part = raw.strip(" ，,。；;")
        if not part:
            continue
        for pattern, replacement in replacements:
            part = re.sub(pattern, replacement, part)
        parts.append(part)
    return "\n".join(parts)


def _description_from_structured_facts(entry: dict[str, Any], entry_type: str) -> str:
    if entry_type in {"work_experience", "internship_experience"}:
        company = str(entry.get("company") or "").strip()
        position = str(entry.get("position") or "").strip()
        return f"在{company}担任{position}。" if company and position else ""
    if entry_type == "project_experience":
        name = str(entry.get("project_name") or "").strip()
        role = str(entry.get("project_role") or "").strip()
        return f"参与{name}，担任{role}。" if name and role else ""
    if entry_type == "competition":
        name = str(entry.get("name") or "").strip()
        award = str(entry.get("award") or "").strip()
        return f"参加{name}并获得{award}。" if name and award else ""
    if entry_type == "campus_experience":
        organization = str(entry.get("organization") or "").strip()
        role = str(entry.get("role") or "").strip()
        return f"在{organization}担任{role}。" if organization and role else ""
    return ""