core/interviewer.py

# core/interviewer.py
"""
🇬🇧 Interviewer logic module (no instructions)
Generates random MBTI-style questions using the fine-tuned model.

🇷🇺 Модуль интервьюера.
Использует fine-tuned модель для генерации вопросов без инструкций.
"""

import random
import re
import torch
from transformers import AutoModelForSeq2SeqLM, T5Tokenizer

# --------------------------------------------------------------
# 1️⃣ Настройки модели
# --------------------------------------------------------------
QG_MODEL = "f3nsmart/ft-flan-t5-base-qgen"

# ✅ Принудительно используем оригинальный SentencePiece-токенайзер
tokenizer = T5Tokenizer.from_pretrained(QG_MODEL, use_fast=False)
model = AutoModelForSeq2SeqLM.from_pretrained(QG_MODEL)

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device).eval()
print(f"✅ Loaded interviewer model (slow tokenizer): {QG_MODEL}")
print(f"Device set to use {device}")

# --------------------------------------------------------------
# 2️⃣ Seed-промпты (без инструкций)
# --------------------------------------------------------------

# --------------------------------------------------------------
# 2️⃣ Тематические seed-промпты (по осям MBTI, но без прямого упоминания MBTI)
# --------------------------------------------------------------

BASE_INSTRUCTION = (
    "Generate one natural, open-ended question about human thinking, emotions, or decision-making. "
    "Avoid mentioning MBTI or personality types directly. "
    "Do not ask what type the person belongs to. "
    "You may include ideas related to intuition, logic, feelings, perception, or judgment naturally."
)

PROMPTS = [
    f"{BASE_INSTRUCTION} Explore how people usually recharge their energy and interact with others.",
    f"{BASE_INSTRUCTION} Explore the difference between noticing small details and seeing the bigger picture.",
    f"{BASE_INSTRUCTION} Ask about trusting intuition versus relying on concrete evidence in daily life.",
    f"{BASE_INSTRUCTION} Ask about what typically inspires or motivates someone to take action.",
    f"{BASE_INSTRUCTION} Create a question about balancing emotions and logic when making decisions.",
    f"{BASE_INSTRUCTION} Write about preferences between careful planning and spontaneous action.",
    f"{BASE_INSTRUCTION} Explore how individuals deal with uncertainty or unexpected changes.",
    f"{BASE_INSTRUCTION} Ask about understanding other people’s emotions or empathy in relationships.",
    f"{BASE_INSTRUCTION} Create a question about staying organized versus adapting flexibly to new situations.",
    f"{BASE_INSTRUCTION} Explore curiosity, creativity, and how people find meaning in what they do."
]


# --------------------------------------------------------------
# 3️⃣ Очистка текста
# --------------------------------------------------------------
def _clean_question(text: str) -> str:
    """Берёт первую фразу с '?'"""
    text = text.strip()
    m = re.search(r"(.+?\?)", text)
    if m:
        text = m.group(1)
    text = text.replace("\n", " ").strip()
    if len(text.split()) < 3:
        text = text.capitalize()
        if not text.endswith("?"):
            text += "?"
    return text


# --------------------------------------------------------------
# 4️⃣ Генерация вопроса
# --------------------------------------------------------------
def generate_question(user_id: str = "default_user", **kwargs) -> str:
    """Генерирует один MBTI-вопрос без инструкций"""
    prompt = random.choice(PROMPTS)
    inputs = tokenizer(prompt, return_tensors="pt", truncation=True).to(device)
    with torch.no_grad():
        out = model.generate(
            **inputs,
            do_sample=True,
            top_p=0.9,
            temperature=1.1,
            repetition_penalty=1.5,
            max_new_tokens=80,
        )
    text = tokenizer.decode(out[0], skip_special_tokens=True)
    return _clean_question(text)