crawler

export async function embed(text: string): Promise<number[]> {
    try {
        // Point directly to LM Studio's native local server port
        const response = await fetch("http://localhost:1234/v1/embeddings", {
            method: "POST",
            headers: { "Content-Type": "application/json" },
            body: JSON.stringify({
                input: text,
                model: "text-embedding-nomic-embed-text-v1.5" // Match the exact model loaded in your LMS
            })
        });

        if (!response.ok) throw new Error(`LMS API Error: ${response.status}`);

        const data = await response.json();
        return data.data[0].embedding;
    } catch (error) {
        console.error("Embedding fallback:", error);
        return new Array(384).fill(0); // Standard safe zero-vector fallback
    }
}