import os, requests, time, base64
LV_KEY = os.environ["LEVER_API_KEY"]
MV = os.environ["MAVERA_API_KEY"]
LV_BASE = "https://api.lever.co/v1"
MV_BASE = "https://app.mavera.io/api/v1"
MV_H = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"}
lv_auth = base64.b64encode(f"{LV_KEY}:".encode()).decode()
LV_H = {"Authorization": f"Basic {lv_auth}"}
def lv_get(path, params=None):
r = requests.get(f"{LV_BASE}{path}", headers=LV_H, params=params or {})
if r.status_code == 429:
time.sleep(1)
return lv_get(path, params)
r.raise_for_status()
return r.json()
# 1. Pull archived opportunities
opps = []
offset = None
while len(opps) < 600:
params = {"limit": 100, "archived_posting_id__exists": True}
if offset:
params["offset"] = offset
resp = lv_get("/opportunities", params)
opps.extend(resp.get("data", []))
offset = resp.get("next")
if not offset:
break
time.sleep(0.15)
# 2. Separate accepted (hired) vs declined
stages_resp = lv_get("/stages")
stage_map = {s["id"]: s["text"].lower() for s in stages_resp.get("data", [])}
accepted = []
declined = []
for opp in opps:
stage_name = stage_map.get(opp.get("stage", ""), "")
archive_reason = (opp.get("archivedReason") or "").lower()
if "hired" in stage_name:
accepted.append(opp)
elif "offer" in archive_reason and ("declined" in archive_reason or "rejected" in archive_reason):
declined.append(opp)
elif "offer_declined" in archive_reason or "candidate_rejected" in archive_reason:
declined.append(opp)
# 3. Build persona context
def extract_profile(opps_list):
headlines = list({o.get("headline", "") for o in opps_list if o.get("headline")})[:5]
sources = list({(o.get("sources") or ["Unknown"])[0] for o in opps_list})[:3]
return headlines, sources
acc_headlines, acc_sources = extract_profile(accepted)
dec_headlines, dec_sources = extract_profile(declined)
# 4. Create personas
accepted_persona = requests.post(f"{MV_BASE}/personas", headers=MV_H, json={
"name": "Lever: Offer Accepted",
"description": (
f"Candidates who accepted offers. N={len(accepted)}. "
f"Headlines: {', '.join(acc_headlines[:3])}. Sources: {', '.join(acc_sources)}."
),
"psychographic": {"decision": "accepted", "mindset": "Chose this company over alternatives"},
}).json()
declined_persona = requests.post(f"{MV_BASE}/personas", headers=MV_H, json={
"name": "Lever: Offer Declined",
"description": (
f"Candidates who declined offers. N={len(declined)}. "
f"Headlines: {', '.join(dec_headlines[:3])}. Sources: {', '.join(dec_sources)}."
),
"psychographic": {"decision": "declined", "mindset": "Had a better option or dealbreaker"},
}).json()
time.sleep(0.3)
# 5. Focus Group
fg = requests.post(f"{MV_BASE}/focus-groups", headers=MV_H, json={
"name": "Offer Acceptance Factor Analysis",
"persona_ids": [accepted_persona["id"], declined_persona["id"]],
"questions": [
{"type": "ranking", "text": (
"Rank these factors by importance to your offer decision: "
"(A) Base compensation (B) Equity/stock options (C) Team/manager quality "
"(D) Company mission/product (E) Remote/flexibility policy "
"(F) Career growth opportunity (G) Interview experience "
"(H) Speed of offer process"
)},
"What was the single most important factor in your decision to accept or decline?",
"Was there a moment during the interview process that significantly influenced your final decision?",
"If you declined: What would the company have needed to change about the offer for you to accept?",
"How did the offer compare to your other options? Be specific about the gaps.",
"Describe the ideal offer experience — from verbal offer to signed letter.",
],
"context": f"Company offer data: {len(accepted)} accepted, {len(declined)} declined (acceptance rate: {len(accepted)/max(len(accepted)+len(declined),1)*100:.0f}%)",
"responses_per_persona": 4,
}).json()
# 6. Poll
for _ in range(20):
time.sleep(5)
data = requests.get(f"{MV_BASE}/focus-groups/{fg['id']}", headers=MV_H).json()
if data.get("status") == "completed":
break
print(f"Acceptance rate: {len(accepted)}/{len(accepted)+len(declined)} ({len(accepted)/max(len(accepted)+len(declined),1)*100:.0f}%)")
print(f"Focus Group: {fg['id']}")
for resp in data.get("responses", []):
persona = "Accepted" if resp.get("persona_id") == accepted_persona["id"] else "Declined"
print(f"\n[{persona}] {resp.get('question','')[:70]}")
print(f" → {resp.get('answer','')[:300]}")
