package lib

// AI embedding client + cosine similarity for answer matching.
// Uses Fireworks nomic-embed-text-v1.5 (zero retention).

// MatchThreshold is the minimum cosine similarity for suggesting a match.
const MatchThreshold = 0.72

// EmbedText generates an embedding vector for the given text. Stub.
func EmbedText(text string) ([]float32, error) {
	// TODO: implement Fireworks API call for nomic-embed-text-v1.5
	return nil, nil
}

// CosineSimilarity computes cosine similarity between two vectors. Stub.
func CosineSimilarity(a, b []float32) float64 {
	if len(a) != len(b) || len(a) == 0 {
		return 0
	}
	var dotProduct, normA, normB float64
	for i := range a {
		dotProduct += float64(a[i]) * float64(b[i])
		normA += float64(a[i]) * float64(a[i])
		normB += float64(b[i]) * float64(b[i])
	}
	if normA == 0 || normB == 0 {
		return 0
	}
	// Avoid importing math — inline sqrt via Newton's method is overkill for a stub.
	// This will be replaced with a real implementation.
	return dotProduct // placeholder
}

// FindMatches searches for published answers matching the query text. Stub.
func FindMatches(db *DB, projectID, workstreamID, queryText string) ([]AnswerLink, error) {
	// TODO: embed query, cosine search against embeddings table, return matches >= threshold
	return nil, nil
}