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db0cec8 46113f1 db0cec8 46113f1 db0cec8 46113f1 db0cec8 46113f1 db0cec8 b3704a6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 | """
Candidate Experience Expansion Vault (spec item #6).
A persistent store of everything we've learned about the candidate's usable
experience across jobs — so the system gets stronger over time and stays
consistent (a term confirmed safe on one job stays safe on the next).
Persisted to data/candidate_vault.json. Each entry:
{ term, category, source, confidence, usage_guidance, example_bullet }
source ∈ resume | inferred_plausible | user_confirmed | jd_expansion
confidence ∈ high | medium | low
usage_guidance ∈ safe_to_use | use_carefully | ask_user | blocked
The vault FEEDS the fit classifier:
- user_confirmed terms → always safe (treated as explicit)
- blocked terms (user said no)→ always blocked
"""
from __future__ import annotations
import json
import os
from typing import Dict, List
_VAULT_PATH = "data/candidate_vault.json"
# Per spec #8: only resume_original + user_confirmed are FULLY safe. Everything
# inferred/expanded stays REVIEWABLE — the vault must never silently promote a
# risky/plausible JD term to "safe" just because it appeared in past resumes.
_FIT_TO_GUIDANCE = {
"explicit": "safe_to_use", # actually present in the original resume
"plausible": "use_carefully", # reviewable until user confirms
"adjacent": "use_carefully",
"risky": "ask_user",
"blocked": "blocked",
}
_FIT_TO_SOURCE = {
"explicit": "resume_original",
"plausible": "inferred_plausible",
"adjacent": "inferred_plausible",
"risky": "risky_review",
"blocked": "blocked",
}
_FIT_TO_CONF = {"explicit": "high", "plausible": "medium", "adjacent": "medium",
"risky": "low", "blocked": "low"}
def load_vault(path: str = _VAULT_PATH) -> Dict[str, dict]:
"""Return {term_lower: entry}. Empty dict if none yet."""
try:
with open(path, encoding="utf-8") as f:
data = json.load(f)
return {e["term"].lower(): e for e in data.get("entries", []) if e.get("term")}
except Exception:
return {}
def save_vault(vault: Dict[str, dict], path: str = _VAULT_PATH) -> None:
try:
os.makedirs(os.path.dirname(path), exist_ok=True)
with open(path, "w", encoding="utf-8") as f:
json.dump({"entries": list(vault.values())}, f, ensure_ascii=False, indent=2)
except Exception as e:
print(f"[vault] save skipped: {e}")
def update_from_fit(verdicts, path: str = _VAULT_PATH) -> Dict[str, dict]:
"""Merge a job's FitVerdicts into the vault. user_confirmed entries are never
downgraded by automated runs."""
vault = load_vault(path)
for v in verdicts:
key = v.keyword.lower().strip()
if not key:
continue
existing = vault.get(key)
# Never overwrite a user_confirmed / user-blocked decision automatically.
if existing and existing.get("source") == "user_confirmed":
continue
vault[key] = {
"term": v.keyword,
"category": v.category,
"source": _FIT_TO_SOURCE.get(v.fit_status, "jd_expansion"),
"confidence": _FIT_TO_CONF.get(v.fit_status, "low"),
"usage_guidance": _FIT_TO_GUIDANCE.get(v.fit_status, "use_carefully"),
"example_bullet": (existing or {}).get("example_bullet", ""),
}
save_vault(vault, path)
return vault
def confirm_terms(terms: List[str], confirmed: bool = True,
path: str = _VAULT_PATH) -> None:
"""User explicitly confirms (or rejects) terms — the strongest signal."""
vault = load_vault(path)
for t in terms:
key = t.lower().strip()
if not key:
continue
e = vault.get(key, {"term": t, "category": "user", "example_bullet": ""})
e["source"] = "user_confirmed"
e["confidence"] = "high"
e["usage_guidance"] = "safe_to_use" if confirmed else "blocked"
vault[key] = e
save_vault(vault, path)
def user_confirmed_terms(path: str = _VAULT_PATH) -> set:
v = load_vault(path)
return {k for k, e in v.items()
if e.get("source") == "user_confirmed" and e.get("usage_guidance") == "safe_to_use"}
def user_blocked_terms(path: str = _VAULT_PATH) -> set:
v = load_vault(path)
return {k for k, e in v.items() if e.get("usage_guidance") == "blocked"}
def confirm_expansion_terms(terms: List[str], category: str = "max_ats_expansion",
path: str = _VAULT_PATH) -> List[str]:
"""Persist Maximum-ATS / user-confirmed expansion terms as user_confirmed so
future resumes treat them as safe. Returns the list of newly-stored terms.
This is the explicit-confirmation path: the user confirmed (via the extension
"Maximum ATS Mode" / "Confirm these terms") that these are interview-supportable.
Truly high-risk terms are still only stored when the user confirms them here —
nothing is silently promoted by an automated run.
"""
terms = [t for t in (terms or []) if t and t.strip()]
if not terms:
return []
vault = load_vault(path)
blocked = {k for k, e in vault.items() if e.get("usage_guidance") == "blocked"}
stored: List[str] = []
for t in terms:
key = t.lower().strip()
if not key or key in blocked:
continue # never override a user block
e = vault.get(key, {"term": t, "example_bullet": ""})
e["term"] = e.get("term") or t
e["category"] = e.get("category") or category
e["source"] = "user_confirmed"
e["confidence"] = "high"
e["usage_guidance"] = "safe_to_use"
vault[key] = e
stored.append(t)
save_vault(vault, path)
return stored
def vault_summary(path: str = _VAULT_PATH) -> dict:
"""Reporting helper: counts + the user-confirmed term list, so the UI can
show what's been added to the vault."""
v = load_vault(path)
by_source: Dict[str, int] = {}
for e in v.values():
by_source[e.get("source", "unknown")] = by_source.get(e.get("source", "unknown"), 0) + 1
return {
"total": len(v),
"by_source": by_source,
"user_confirmed": sorted(user_confirmed_terms(path)),
"blocked": sorted(user_blocked_terms(path)),
}
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