agents/guidelines.py

from __future__ import annotations
from dataclasses import dataclass
from typing import Callable, Dict, Any, List, Tuple
import re


@dataclass
class Guideline:
	id: str
	description: str
	condition: Callable[[Dict[str, Any]], bool]
	validate: Callable[[str, Dict[str, Any]], Tuple[bool, str]]
	enforce: Callable[[str, Dict[str, Any]], str]


class GuidelineEngine:
	def __init__(self, rules: List[Guideline]) -> None:
		self.rules = rules

	def check_and_enforce(self, text: str, ctx: Dict[str, Any]) -> Tuple[str, List[str], List[str]]:
		matched: List[str] = []
		fixed: List[str] = []
		out = text or ""
		for g in self.rules:
			try:
				if not g.condition(ctx):
					continue
				matched.append(g.id)
				ok, _ = g.validate(out, ctx)
				if not ok:
					out = g.enforce(out, ctx)
					fixed.append(g.id)
			except Exception:
				# fail-safe, do not block
				continue
		return out, matched, fixed


# ---------- Helpers ----------

_BUZZWORDS = [
	"results-driven", "team player", "people person", "perfectionist",
	"multi-tasker", "multi tasker", "dynamic go-getter", "rockstar",
	"guru", "ninja"
]

_WEAK_OPENERS = [
	(re.compile(r"^\s*[-•]\s*responsible for\s+", re.I), "- Led "),
	(re.compile(r"^\s*[-•]\s*tasked with\s+", re.I), "- Executed "),
	(re.compile(r"^\s*[-•]\s*worked on\s+", re.I), "- Delivered "),
	(re.compile(r"^\s*[-•]\s*helped\s+", re.I), "- Supported "),
	(re.compile(r"^\s*[-•]\s*assisted with\s+", re.I), "- Supported "),
	(re.compile(r"^\s*[-•]\s*handled\s+", re.I), "- Managed "),
]


def _enforce_exact_length(text: str, target_len: int) -> str:
	if target_len <= 0:
		return text or ""
	txt = (text or "")
	if len(txt) == target_len:
		return txt
	if len(txt) > target_len:
		return txt[:target_len]
	return txt + (" " * (target_len - len(txt)))


def _ensure_headings(text: str) -> str:
	"""Ensure key headings exist: SUMMARY, SKILLS, EXPERIENCE, EDUCATION."""
	t = text or ""
	low = t.lower()
	out = t
	def add_heading(h: str) -> None:
		nonlocal out
		if h.lower() not in low:
			out = (out + f"\n\n{h}\n").strip()
	for h in ["SUMMARY", "SKILLS", "EXPERIENCE", "EDUCATION"]:
		if h.lower() not in low:
			add_heading(h)
	return out


def _strip_tabs(text: str) -> str:
	return (text or "").replace("\t", " ")


def _scrub_buzzwords(text: str) -> str:
	out = text or ""
	low = out.lower()
	for bw in _BUZZWORDS:
		if bw in low:
			out = re.sub(re.escape(bw), "", out, flags=re.I)
	return out


def _strengthen_action_verbs(text: str) -> str:
	lines = (text or "").splitlines()
	fixed: List[str] = []
	for ln in lines:
		new_ln = ln
		for pat, repl in _WEAK_OPENERS:
			if pat.search(new_ln):
				new_ln = pat.sub(repl, new_ln)
				break
		fixed.append(new_ln)
	return "\n".join(fixed)


def _remove_first_person(text: str) -> str:
	# Remove leading "I " / "My " in bullets only
	lines = (text or "").splitlines()
	out: List[str] = []
	for ln in lines:
		m = re.match(r"^\s*[-•]\s*(i|my|we)\b", ln, flags=re.I)
		if m:
			ln = re.sub(r"^\s*([-•]\s*)(i|my|we)\b\s*", r"\1", ln, flags=re.I)
		out.append(ln)
	return "\n".join(out)


def _ats_plain_text(text: str) -> str:
	# normalize bullets and strip odd symbols
	out = _strip_tabs(text)
	out = out.replace("•\t", "- ").replace("• ", "- ")
	out = re.sub(r"[■▪◦●○✔✦♦]", "-", out)
	return out


def _enforce_uk_habits(text: str) -> str:
	# normalize currency symbol spacing and percentages
	out = re.sub(r"\s*£\s*", " £", text or "")
	out = re.sub(r"\s*%\s*", "%", out)
	return out


def _allowed_skills_from_profile(ctx: Dict[str, Any]) -> List[str]:
	p = (ctx.get("profile_text") or "").lower()
	# naive split of alphanum skill-like tokens
	cands = re.findall(r"[a-zA-Z][a-zA-Z0-9+_.#-]{2,}", p)
	seen: Dict[str, int] = {}
	for c in cands:
		seen[c.lower()] = 1
	return list(seen.keys())


def _no_invented_skills(text: str, ctx: Dict[str, Any]) -> Tuple[bool, str]:
	allowed = set(_allowed_skills_from_profile(ctx))
	if not allowed:
		return True, "no baseline"
	skills_block = re.search(r"(?is)\n\s*(skills|core skills)[\s:]*\n(.+?)(\n\n|$)", text or "")
	if not skills_block:
		return True, "no skills block"
	block = skills_block.group(0)
	found = re.findall(r"[A-Za-z][A-Za-z0-9+_.#-]{2,}", block)
	for f in found:
		if f.lower() not in allowed:
			return False, f
	return True, "ok"


# ---------- Rule sets ----------

def build_resume_rules() -> List[Guideline]:
	return [
		Guideline(
			id="exact_length",
			description="Enforce exact target length when provided",
			condition=lambda ctx: bool(ctx.get("target_len")),
			validate=lambda txt, ctx: (len(txt or "") == int(ctx.get("target_len", 0)), "len"),
			enforce=lambda txt, ctx: _enforce_exact_length(txt, int(ctx.get("target_len", 0))),
		),
		Guideline(
			id="headings_present",
			description="Ensure key headings exist",
			condition=lambda ctx: True,
			validate=lambda txt, ctx: (all(h.lower() in (txt or "").lower() for h in ["summary", "experience", "education", "skills"]), "headings"),
			enforce=lambda txt, ctx: _ensure_headings(txt),
		),
		Guideline(
			id="ats_plain_text",
			description="Normalize bullets/tabs for ATS",
			condition=lambda ctx: True,
			validate=lambda txt, ctx: ("\t" not in (txt or ""), "tabs"),
			enforce=lambda txt, ctx: _ats_plain_text(txt),
		),
		Guideline(
			id="buzzword_scrub",
			description="Remove common buzzwords",
			condition=lambda ctx: True,
			validate=lambda txt, ctx: (not any(bw in (txt or "").lower() for bw in _BUZZWORDS), "buzz"),
			enforce=lambda txt, ctx: _scrub_buzzwords(txt),
		),
		Guideline(
			id="verb_strengthen",
			description="Strengthen weak bullet openers",
			condition=lambda ctx: True,
			validate=lambda txt, ctx: (True, "noop"),
			enforce=lambda txt, ctx: _strengthen_action_verbs(txt),
		),
		Guideline(
			id="remove_first_person",
			description="Remove first-person pronouns on bullets",
			condition=lambda ctx: True,
			validate=lambda txt, ctx: (not re.search(r"^\s*[-•]\s*(i|my|we)\b", txt or "", re.I | re.M), "pronouns"),
			enforce=lambda txt, ctx: _remove_first_person(txt),
		),
		Guideline(
			id="uk_normalization",
			description="Normalize UK currency/percent spacing",
			condition=lambda ctx: True,
			validate=lambda txt, ctx: (True, "noop"),
			enforce=lambda txt, ctx: _enforce_uk_habits(txt),
		),
		Guideline(
			id="no_invented_skills",
			description="Prevent skills not evidenced in profile",
			condition=lambda ctx: True,
			validate=_no_invented_skills,
			enforce=lambda txt, ctx: txt,  # log-only to avoid false positives
		),
	]


def build_cover_rules() -> List[Guideline]:
	return [
		Guideline(
			id="exact_length",
			description="Enforce exact target length when provided",
			condition=lambda ctx: bool(ctx.get("target_len")),
			validate=lambda txt, ctx: (len(txt or "") == int(ctx.get("target_len", 0)), "len"),
			enforce=lambda txt, ctx: _enforce_exact_length(txt, int(ctx.get("target_len", 0))),
		),
		Guideline(
			id="ats_plain_text",
			description="Normalize bullets/tabs for ATS",
			condition=lambda ctx: True,
			validate=lambda txt, ctx: ("\t" not in (txt or ""), "tabs"),
			enforce=lambda txt, ctx: _ats_plain_text(txt),
		),
		Guideline(
			id="buzzword_scrub",
			description="Remove common buzzwords",
			condition=lambda ctx: True,
			validate=lambda txt, ctx: (not any(bw in (txt or "").lower() for bw in _BUZZWORDS), "buzz"),
			enforce=lambda txt, ctx: _scrub_buzzwords(txt),
		),
	]


def apply_resume_guidelines(text: str, ctx: Dict[str, Any]) -> Tuple[str, List[str], List[str]]:
	engine = GuidelineEngine(build_resume_rules())
	return engine.check_and_enforce(text, ctx)


def apply_cover_guidelines(text: str, ctx: Dict[str, Any]) -> Tuple[str, List[str], List[str]]:
	engine = GuidelineEngine(build_cover_rules())
	return engine.check_and_enforce(text, ctx)