The model wrote six sentences about a grandmother. Two were allowed on the altar.
Описание и применение
Инструмент генерирует памятные предложения, проверяя каждое на наличие корректных цитат и фактической поддержки, чтобы избежать вымышленных деталей.
Задача
A language model can hallucinate personal details when generating memorial text, risking false memories in a sensitive context.
Результат
The tool produces a single HTML altar file with six sentences, of which two are fully verified and the rest are either repaired or omitted, eliminating hallucinated personal details.
Рабочий процесс
- Pull local model with
ollama pull llama3.2:1b - Run
python3 ofrenda.py --memories examples/memories.json --out altar.html - Model generates sentences with numbered citations
- Python script validates each sentence: checks citations exist, matches numbers, names, and content words
- If a sentence fails, it is repaired using only cited facts or dropped
- Output is a single self‑contained HTML file with verified sentences
Доказательства
One command, one self‑contained HTML file, no API key, no account, no network.
The rule: a sentence must cite the memory it came from
Anything that fails gets one repair attempt against only the facts it cited, and then it is dropped.
- Дата записи: 2026-11-01T05:59:15.666Z