Why Your RAG Chatbot Gives Wrong Answers (And How to Fix It)

Описание и применение

Чат‑боты RAG часто дают неверные ответы из‑за плохой выборки текста. Корректировка размера чанков, добавление перекрытия, очистка извлечённого текста и OCR для сканированных PDF решают проблему.

Задача

RAG chatbots often return incorrect or fabricated answers because the retrieval step fails to provide the correct document excerpts.

Результат

By tuning chunk size, adding overlap, cleaning extracted text, and handling scanned PDFs, the RAG chatbot’s retrieval accuracy improved, leading to more correct answers.

Рабочий процесс

• 1. Print the retrieved chunks to inspect their content.
• 2. Adjust chunk size to 300‑500 words and test multiple sizes.
• 3. Add overlap of ~50 words between chunks to avoid sentence splits.
• 4. Extract text from PDF using pdfplumber and inspect for noise.
• 5. Remove repeated header/footer lines using a frequency counter.
• 6. Detect empty or short pages and flag potential scanned PDFs.
• 7. If scanned, apply OCR (e.g., pytesseract) before extraction.
• 8. Rebuild the index with cleaned chunks and retest queries.

Доказательства

If the answer is not in those pieces, fix retrieval (problems 1 to 4 and 7 below).

Источник

Fix: start with about 300 to 500 words per chunk.

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let each chunk repeat the last 50 words or so of the one before it.

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If the text you extract is bad, everything after it is bad too.

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