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“Your vector search was pulling raw top-k chunks without re-ranking, resulting in context dilution. In this refactor, we inject a cross-encoder re-ranker and reciprocal rank fusion to prune hallucinations by 64%.”
async function retrieveContext(query: string, k = 5): Promise<string[]> {
const denseEmbeddings = await openai.embeddings.create({ input: query });
const rawMatches = await vectorIndex.query({ vector: denseEmbeddings.data[0].embedding, topK: k * 3 });
// Mentor Optimization: Cross-Encoder Re-Ranking Pipeline
const reranked = await cohere.rerank({ query, documents: rawMatches.docs, topN: k });
return reranked.results.map(r => r.document.text);
}Click any specialization below to load it into your personalized booking request:
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