招聘与 HR 助手

import json
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.tutujin.com/v1", api_key=os.environ["TUTUJIN_API_KEY"])

FIELDS = {
    "name": "", "phone": "", "email": "",
    "education": [{"school": "", "degree": "", "major": "", "graduated": "YYYY-MM"}],
    "experience": [{"company": "", "title": "", "start": "YYYY-MM", "end": "YYYY-MM or now", "highlights": [""]}],
    "skills": [""],
    "certificates": [""],
}
# Written by the hiring manager; every candidate for this job is judged on the same list.
CRITERIA = [
    {"id": "C1", "must": True, "text": "At least 3 years of B2B sales experience"},
    {"id": "C2", "must": True, "text": "Has owned key accounts or a sales territory"},
    {"id": "C3", "must": False, "text": "Has sold software or SaaS"},
    {"id": "C4", "must": False, "text": "Has worked with overseas clients in English"},
]
NOT_FOR_SCREENING = ("name", "phone", "email")


def ask_json(model, system, user):
    resp = client.chat.completions.create(
        model=model,
        messages=[{"role": "system", "content": system}, {"role": "user", "content": user}],
        temperature=0,
    )
    raw = resp.choices[0].message.content
    return json.loads(raw[raw.find("{"): raw.rfind("}") + 1])


def parse_resume(text):
    return ask_json(
        "qwen-flash",
        "Copy the resume into JSON with exactly this shape: " + json.dumps(FIELDS)
        + ". Use empty values when something is not in the resume; never guess. Reply with JSON only.",
        text,
    )


def screen(profile):
    facts = {k: v for k, v in profile.items() if k not in NOT_FOR_SCREENING}
    result = ask_json(
        "deepseek-v4.1-flash",
        "You help a recruiter. For each criterion answer met, not_met or unclear, and quote the resume text "
        "that supports it. Judge only the listed criteria. "
        'Reply with JSON only: {"criteria": [{"id": "C1", "verdict": "met", "evidence": ""}]}',
        "Criteria:\n" + json.dumps(CRITERIA) + "\n\nCandidate:\n" + json.dumps(facts, ensure_ascii=False),
    )
    verdicts = {c["id"]: c["verdict"] for c in result["criteria"]}
    gaps = [c["id"] for c in CRITERIA if c["must"] and verdicts.get(c["id"]) != "met"]
    # The model never rejects anyone: it only sorts the queue, and a recruiter reviews every candidate.
    return {"queue": "review_gaps" if gaps else "review_first", "must_have_gaps": gaps, "criteria": result["criteria"]}


with open("resume.txt", encoding="utf-8") as f:
    profile = parse_resume(f.read())
print(json.dumps(screen(profile), ensure_ascii=False, indent=2))