(query: string)
| 48 | const queryCache = new Map<string, number[]>(); |
| 49 | |
| 50 | async function getQueryEmbedding(query: string): Promise<number[]> { |
| 51 | const key = query.slice(0, 8000); |
| 52 | if (queryCache.has(key)) { |
| 53 | return queryCache.get(key)!; |
| 54 | } |
| 55 | |
| 56 | const response = await openai.embeddings.create({ |
| 57 | model: 'text-embedding-3-small', |
| 58 | input: key, |
| 59 | }); |
| 60 | |
| 61 | const embedding = response.data[0].embedding; |
| 62 | queryCache.set(key, embedding); |
| 63 | return embedding; |
| 64 | } |
| 65 | |
| 66 | // Cosine similarity |
| 67 | function cosineSimilarity( |