教育与培训

import json
import os
from openai import OpenAI

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


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 write_questions(material, topic, n=5):
    return ask_json(
        "deepseek-v4.1-flash",
        "You write multiple-choice questions for a course. Use only facts stated in the material. "
        'Reply with JSON only: {"questions": [{"stem": "", "options": {"A": "", "B": "", "C": "", "D": ""}, '
        '"answer": "A", "explanation": "", "difficulty": "easy|medium|hard"}]}',
        "Topic: " + topic + "\nWrite " + str(n) + " questions.\n\nMaterial:\n" + material,
    )["questions"]


def solve(q):
    """A model from another vendor answers without seeing the key."""
    options = "\n".join(k + ". " + v for k, v in q["options"].items())
    return ask_json("gpt-5.4-mini", 'Answer the question. Reply with JSON only: {"answer": "A"}', q["stem"] + "\n" + options)["answer"]


def suggest_score(question, rubric, answer):
    """Rubric-based suggestion for a written answer; the teacher confirms or changes it."""
    result = ask_json(
        "gpt-5.4-mini",
        "Score the student answer against each rubric item and quote the words that earn the points. "
        'Reply with JSON only: {"items": [{"id": "R1", "points": 0, "evidence": "", "comment": ""}]}',
        "Question:\n" + question + "\n\nRubric:\n" + json.dumps(rubric, ensure_ascii=False) + "\n\nAnswer:\n" + answer,
    )
    cap = {r["id"]: r["max"] for r in rubric}
    total = sum(min(max(float(i.get("points", 0)), 0), cap.get(i.get("id"), 0)) for i in result["items"])
    return {"suggested": total, "out_of": sum(cap.values()), "items": result["items"], "status": "teacher_to_confirm"}


with open("chapter-3.txt", encoding="utf-8") as f:
    questions = write_questions(f.read(), "Reading a cash flow statement")
for q in questions:
    # every question is reviewed by a teacher; disagreements are reviewed first
    q["status"] = "teacher_review" if solve(q) == q["answer"] else "answer_disputed"
print(json.dumps(questions, ensure_ascii=False, indent=2))

rubric = [
    {"id": "R1", "max": 2, "text": "Names operating, investing and financing activities"},
    {"id": "R2", "max": 2, "text": "Explains why profit and operating cash flow can differ"},
]
print(suggest_score("Why can a profitable company run out of cash?", rubric, "Customers pay late, so..."))