Search that understands what you meant.

import { db, knowledge } from 'hatchable';

export const methods = ['POST'];
export const access = 'member';

export default async function (req, res) {
  const docs = knowledge.base('help_docs', {
    dimensions: 1536,
  });
  const { title, body } = req.body;

  const { rows } = await db.query(
    `INSERT INTO articles (title, body)
          VALUES ($1, $2) RETURNING id`,
    [title, body]
  );

  // chunkText is your own helper
  await docs.add(chunkText(body).map((text, i) => ({
    id: `article:${rows[0].id}:chunk:${i}`,
    text,
    metadata: { articleId: rows[0].id, title },
  })));

  res.json({ id: rows[0].id });
}

import { knowledge, ai } from 'hatchable';

export const methods = ['POST'];
export const access = 'member';

export default async function (req, res) {
  const docs = knowledge.base('help_docs', {
    dimensions: 1536,
  });

  // nearest six by meaning, not by keyword
  const hits = await docs.search(
    req.body.question, { topK: 6 }
  );

  const context = hits
    .map((h, i) => `[${i + 1}] ${h.metadata._text}`)
    .join('\n\n');

  const { text } = await ai.generateText({
    model: 'sonnet',
    system: `Answer using ONLY the context below.
              Cite sources by number.\n\n${context}`,
    prompt: req.body.question,
    purpose: 'rag-answer',
  });

  res.json({
    answer: text,
    sources: hits.map(h => h.metadata.title),
  });
}