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| package main | |
| // This is a wrapper to statisfy the GRPC service interface | |
| // It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc) | |
| import ( | |
| "container/heap" | |
| "fmt" | |
| "math" | |
| "slices" | |
| "github.com/mudler/LocalAI/pkg/grpc/base" | |
| pb "github.com/mudler/LocalAI/pkg/grpc/proto" | |
| "github.com/rs/zerolog/log" | |
| ) | |
| type Store struct { | |
| base.SingleThread | |
| // The sorted keys | |
| keys [][]float32 | |
| // The sorted values | |
| values [][]byte | |
| // If for every K it holds that ||k||^2 = 1, then we can use the normalized distance functions | |
| // TODO: Should we normalize incoming keys if they are not instead? | |
| keysAreNormalized bool | |
| // The first key decides the length of the keys | |
| keyLen int | |
| } | |
| // TODO: Only used for sorting using Go's builtin implementation. The interfaces are columnar because | |
| // that's theoretically best for memory layout and cache locality, but this isn't optimized yet. | |
| type Pair struct { | |
| Key []float32 | |
| Value []byte | |
| } | |
| func NewStore() *Store { | |
| return &Store{ | |
| keys: make([][]float32, 0), | |
| values: make([][]byte, 0), | |
| keysAreNormalized: true, | |
| keyLen: -1, | |
| } | |
| } | |
| func compareSlices(k1, k2 []float32) int { | |
| assert(len(k1) == len(k2), fmt.Sprintf("compareSlices: len(k1) = %d, len(k2) = %d", len(k1), len(k2))) | |
| return slices.Compare(k1, k2) | |
| } | |
| func hasKey(unsortedSlice [][]float32, target []float32) bool { | |
| return slices.ContainsFunc(unsortedSlice, func(k []float32) bool { | |
| return compareSlices(k, target) == 0 | |
| }) | |
| } | |
| func findInSortedSlice(sortedSlice [][]float32, target []float32) (int, bool) { | |
| return slices.BinarySearchFunc(sortedSlice, target, func(k, t []float32) int { | |
| return compareSlices(k, t) | |
| }) | |
| } | |
| func isSortedPairs(kvs []Pair) bool { | |
| for i := 1; i < len(kvs); i++ { | |
| if compareSlices(kvs[i-1].Key, kvs[i].Key) > 0 { | |
| return false | |
| } | |
| } | |
| return true | |
| } | |
| func isSortedKeys(keys [][]float32) bool { | |
| for i := 1; i < len(keys); i++ { | |
| if compareSlices(keys[i-1], keys[i]) > 0 { | |
| return false | |
| } | |
| } | |
| return true | |
| } | |
| func sortIntoKeySlicese(keys []*pb.StoresKey) [][]float32 { | |
| ks := make([][]float32, len(keys)) | |
| for i, k := range keys { | |
| ks[i] = k.Floats | |
| } | |
| slices.SortFunc(ks, compareSlices) | |
| assert(len(ks) == len(keys), fmt.Sprintf("len(ks) = %d, len(keys) = %d", len(ks), len(keys))) | |
| assert(isSortedKeys(ks), "keys are not sorted") | |
| return ks | |
| } | |
| func (s *Store) Load(opts *pb.ModelOptions) error { | |
| return nil | |
| } | |
| // Sort the incoming kvs and merge them with the existing sorted kvs | |
| func (s *Store) StoresSet(opts *pb.StoresSetOptions) error { | |
| if len(opts.Keys) == 0 { | |
| return fmt.Errorf("no keys to add") | |
| } | |
| if len(opts.Keys) != len(opts.Values) { | |
| return fmt.Errorf("len(keys) = %d, len(values) = %d", len(opts.Keys), len(opts.Values)) | |
| } | |
| if s.keyLen == -1 { | |
| s.keyLen = len(opts.Keys[0].Floats) | |
| } else { | |
| if len(opts.Keys[0].Floats) != s.keyLen { | |
| return fmt.Errorf("Try to add key with length %d when existing length is %d", len(opts.Keys[0].Floats), s.keyLen) | |
| } | |
| } | |
| kvs := make([]Pair, len(opts.Keys)) | |
| for i, k := range opts.Keys { | |
| if s.keysAreNormalized && !isNormalized(k.Floats) { | |
| s.keysAreNormalized = false | |
| var sample []float32 | |
| if len(s.keys) > 5 { | |
| sample = k.Floats[:5] | |
| } else { | |
| sample = k.Floats | |
| } | |
| log.Debug().Msgf("Key is not normalized: %v", sample) | |
| } | |
| kvs[i] = Pair{ | |
| Key: k.Floats, | |
| Value: opts.Values[i].Bytes, | |
| } | |
| } | |
| slices.SortFunc(kvs, func(a, b Pair) int { | |
| return compareSlices(a.Key, b.Key) | |
| }) | |
| assert(len(kvs) == len(opts.Keys), fmt.Sprintf("len(kvs) = %d, len(opts.Keys) = %d", len(kvs), len(opts.Keys))) | |
| assert(isSortedPairs(kvs), "keys are not sorted") | |
| l := len(kvs) + len(s.keys) | |
| merge_ks := make([][]float32, 0, l) | |
| merge_vs := make([][]byte, 0, l) | |
| i, j := 0, 0 | |
| for { | |
| if i+j >= l { | |
| break | |
| } | |
| if i >= len(kvs) { | |
| merge_ks = append(merge_ks, s.keys[j]) | |
| merge_vs = append(merge_vs, s.values[j]) | |
| j++ | |
| continue | |
| } | |
| if j >= len(s.keys) { | |
| merge_ks = append(merge_ks, kvs[i].Key) | |
| merge_vs = append(merge_vs, kvs[i].Value) | |
| i++ | |
| continue | |
| } | |
| c := compareSlices(kvs[i].Key, s.keys[j]) | |
| if c < 0 { | |
| merge_ks = append(merge_ks, kvs[i].Key) | |
| merge_vs = append(merge_vs, kvs[i].Value) | |
| i++ | |
| } else if c > 0 { | |
| merge_ks = append(merge_ks, s.keys[j]) | |
| merge_vs = append(merge_vs, s.values[j]) | |
| j++ | |
| } else { | |
| merge_ks = append(merge_ks, kvs[i].Key) | |
| merge_vs = append(merge_vs, kvs[i].Value) | |
| i++ | |
| j++ | |
| } | |
| } | |
| assert(len(merge_ks) == l, fmt.Sprintf("len(merge_ks) = %d, l = %d", len(merge_ks), l)) | |
| assert(isSortedKeys(merge_ks), "merge keys are not sorted") | |
| s.keys = merge_ks | |
| s.values = merge_vs | |
| return nil | |
| } | |
| func (s *Store) StoresDelete(opts *pb.StoresDeleteOptions) error { | |
| if len(opts.Keys) == 0 { | |
| return fmt.Errorf("no keys to delete") | |
| } | |
| if len(opts.Keys) == 0 { | |
| return fmt.Errorf("no keys to add") | |
| } | |
| if s.keyLen == -1 { | |
| s.keyLen = len(opts.Keys[0].Floats) | |
| } else { | |
| if len(opts.Keys[0].Floats) != s.keyLen { | |
| return fmt.Errorf("Trying to delete key with length %d when existing length is %d", len(opts.Keys[0].Floats), s.keyLen) | |
| } | |
| } | |
| ks := sortIntoKeySlicese(opts.Keys) | |
| l := len(s.keys) - len(ks) | |
| merge_ks := make([][]float32, 0, l) | |
| merge_vs := make([][]byte, 0, l) | |
| tail_ks := s.keys | |
| tail_vs := s.values | |
| for _, k := range ks { | |
| j, found := findInSortedSlice(tail_ks, k) | |
| if found { | |
| merge_ks = append(merge_ks, tail_ks[:j]...) | |
| merge_vs = append(merge_vs, tail_vs[:j]...) | |
| tail_ks = tail_ks[j+1:] | |
| tail_vs = tail_vs[j+1:] | |
| } else { | |
| assert(!hasKey(s.keys, k), fmt.Sprintf("Key exists, but was not found: t=%d, %v", len(tail_ks), k)) | |
| } | |
| log.Debug().Msgf("Delete: found = %v, t = %d, j = %d, len(merge_ks) = %d, len(merge_vs) = %d", found, len(tail_ks), j, len(merge_ks), len(merge_vs)) | |
| } | |
| merge_ks = append(merge_ks, tail_ks...) | |
| merge_vs = append(merge_vs, tail_vs...) | |
| assert(len(merge_ks) <= len(s.keys), fmt.Sprintf("len(merge_ks) = %d, len(s.keys) = %d", len(merge_ks), len(s.keys))) | |
| s.keys = merge_ks | |
| s.values = merge_vs | |
| assert(len(s.keys) >= l, fmt.Sprintf("len(s.keys) = %d, l = %d", len(s.keys), l)) | |
| assert(isSortedKeys(s.keys), "keys are not sorted") | |
| assert(func() bool { | |
| for _, k := range ks { | |
| if _, found := findInSortedSlice(s.keys, k); found { | |
| return false | |
| } | |
| } | |
| return true | |
| }(), "Keys to delete still present") | |
| if len(s.keys) != l { | |
| log.Debug().Msgf("Delete: Some keys not found: len(s.keys) = %d, l = %d", len(s.keys), l) | |
| } | |
| return nil | |
| } | |
| func (s *Store) StoresGet(opts *pb.StoresGetOptions) (pb.StoresGetResult, error) { | |
| pbKeys := make([]*pb.StoresKey, 0, len(opts.Keys)) | |
| pbValues := make([]*pb.StoresValue, 0, len(opts.Keys)) | |
| ks := sortIntoKeySlicese(opts.Keys) | |
| if len(s.keys) == 0 { | |
| log.Debug().Msgf("Get: No keys in store") | |
| } | |
| if s.keyLen == -1 { | |
| s.keyLen = len(opts.Keys[0].Floats) | |
| } else { | |
| if len(opts.Keys[0].Floats) != s.keyLen { | |
| return pb.StoresGetResult{}, fmt.Errorf("Try to get a key with length %d when existing length is %d", len(opts.Keys[0].Floats), s.keyLen) | |
| } | |
| } | |
| tail_k := s.keys | |
| tail_v := s.values | |
| for i, k := range ks { | |
| j, found := findInSortedSlice(tail_k, k) | |
| if found { | |
| pbKeys = append(pbKeys, &pb.StoresKey{ | |
| Floats: k, | |
| }) | |
| pbValues = append(pbValues, &pb.StoresValue{ | |
| Bytes: tail_v[j], | |
| }) | |
| tail_k = tail_k[j+1:] | |
| tail_v = tail_v[j+1:] | |
| } else { | |
| assert(!hasKey(s.keys, k), fmt.Sprintf("Key exists, but was not found: i=%d, %v", i, k)) | |
| } | |
| } | |
| if len(pbKeys) != len(opts.Keys) { | |
| log.Debug().Msgf("Get: Some keys not found: len(pbKeys) = %d, len(opts.Keys) = %d, len(s.Keys) = %d", len(pbKeys), len(opts.Keys), len(s.keys)) | |
| } | |
| return pb.StoresGetResult{ | |
| Keys: pbKeys, | |
| Values: pbValues, | |
| }, nil | |
| } | |
| func isNormalized(k []float32) bool { | |
| var sum float32 | |
| for _, v := range k { | |
| sum += v | |
| } | |
| return sum == 1.0 | |
| } | |
| // TODO: This we could replace with handwritten SIMD code | |
| func normalizedCosineSimilarity(k1, k2 []float32) float32 { | |
| assert(len(k1) == len(k2), fmt.Sprintf("normalizedCosineSimilarity: len(k1) = %d, len(k2) = %d", len(k1), len(k2))) | |
| var dot float32 | |
| for i := 0; i < len(k1); i++ { | |
| dot += k1[i] * k2[i] | |
| } | |
| assert(dot >= -1 && dot <= 1, fmt.Sprintf("dot = %f", dot)) | |
| // 2.0 * (1.0 - dot) would be the Euclidean distance | |
| return dot | |
| } | |
| type PriorityItem struct { | |
| Similarity float32 | |
| Key []float32 | |
| Value []byte | |
| } | |
| type PriorityQueue []*PriorityItem | |
| func (pq PriorityQueue) Len() int { return len(pq) } | |
| func (pq PriorityQueue) Less(i, j int) bool { | |
| // Inverted because the most similar should be at the top | |
| return pq[i].Similarity < pq[j].Similarity | |
| } | |
| func (pq PriorityQueue) Swap(i, j int) { | |
| pq[i], pq[j] = pq[j], pq[i] | |
| } | |
| func (pq *PriorityQueue) Push(x any) { | |
| item := x.(*PriorityItem) | |
| *pq = append(*pq, item) | |
| } | |
| func (pq *PriorityQueue) Pop() any { | |
| old := *pq | |
| n := len(old) | |
| item := old[n-1] | |
| *pq = old[0 : n-1] | |
| return item | |
| } | |
| func (s *Store) StoresFindNormalized(opts *pb.StoresFindOptions) (pb.StoresFindResult, error) { | |
| tk := opts.Key.Floats | |
| top_ks := make(PriorityQueue, 0, int(opts.TopK)) | |
| heap.Init(&top_ks) | |
| for i, k := range s.keys { | |
| sim := normalizedCosineSimilarity(tk, k) | |
| heap.Push(&top_ks, &PriorityItem{ | |
| Similarity: sim, | |
| Key: k, | |
| Value: s.values[i], | |
| }) | |
| if top_ks.Len() > int(opts.TopK) { | |
| heap.Pop(&top_ks) | |
| } | |
| } | |
| similarities := make([]float32, top_ks.Len()) | |
| pbKeys := make([]*pb.StoresKey, top_ks.Len()) | |
| pbValues := make([]*pb.StoresValue, top_ks.Len()) | |
| for i := top_ks.Len() - 1; i >= 0; i-- { | |
| item := heap.Pop(&top_ks).(*PriorityItem) | |
| similarities[i] = item.Similarity | |
| pbKeys[i] = &pb.StoresKey{ | |
| Floats: item.Key, | |
| } | |
| pbValues[i] = &pb.StoresValue{ | |
| Bytes: item.Value, | |
| } | |
| } | |
| return pb.StoresFindResult{ | |
| Keys: pbKeys, | |
| Values: pbValues, | |
| Similarities: similarities, | |
| }, nil | |
| } | |
| func cosineSimilarity(k1, k2 []float32, mag1 float64) float32 { | |
| assert(len(k1) == len(k2), fmt.Sprintf("cosineSimilarity: len(k1) = %d, len(k2) = %d", len(k1), len(k2))) | |
| var dot, mag2 float64 | |
| for i := 0; i < len(k1); i++ { | |
| dot += float64(k1[i] * k2[i]) | |
| mag2 += float64(k2[i] * k2[i]) | |
| } | |
| sim := float32(dot / (mag1 * math.Sqrt(mag2))) | |
| assert(sim >= -1 && sim <= 1, fmt.Sprintf("sim = %f", sim)) | |
| return sim | |
| } | |
| func (s *Store) StoresFindFallback(opts *pb.StoresFindOptions) (pb.StoresFindResult, error) { | |
| tk := opts.Key.Floats | |
| top_ks := make(PriorityQueue, 0, int(opts.TopK)) | |
| heap.Init(&top_ks) | |
| var mag1 float64 | |
| for _, v := range tk { | |
| mag1 += float64(v * v) | |
| } | |
| mag1 = math.Sqrt(mag1) | |
| for i, k := range s.keys { | |
| dist := cosineSimilarity(tk, k, mag1) | |
| heap.Push(&top_ks, &PriorityItem{ | |
| Similarity: dist, | |
| Key: k, | |
| Value: s.values[i], | |
| }) | |
| if top_ks.Len() > int(opts.TopK) { | |
| heap.Pop(&top_ks) | |
| } | |
| } | |
| similarities := make([]float32, top_ks.Len()) | |
| pbKeys := make([]*pb.StoresKey, top_ks.Len()) | |
| pbValues := make([]*pb.StoresValue, top_ks.Len()) | |
| for i := top_ks.Len() - 1; i >= 0; i-- { | |
| item := heap.Pop(&top_ks).(*PriorityItem) | |
| similarities[i] = item.Similarity | |
| pbKeys[i] = &pb.StoresKey{ | |
| Floats: item.Key, | |
| } | |
| pbValues[i] = &pb.StoresValue{ | |
| Bytes: item.Value, | |
| } | |
| } | |
| return pb.StoresFindResult{ | |
| Keys: pbKeys, | |
| Values: pbValues, | |
| Similarities: similarities, | |
| }, nil | |
| } | |
| func (s *Store) StoresFind(opts *pb.StoresFindOptions) (pb.StoresFindResult, error) { | |
| tk := opts.Key.Floats | |
| if len(tk) != s.keyLen { | |
| return pb.StoresFindResult{}, fmt.Errorf("Try to find key with length %d when existing length is %d", len(tk), s.keyLen) | |
| } | |
| if opts.TopK < 1 { | |
| return pb.StoresFindResult{}, fmt.Errorf("opts.TopK = %d, must be >= 1", opts.TopK) | |
| } | |
| if s.keyLen == -1 { | |
| s.keyLen = len(opts.Key.Floats) | |
| } else { | |
| if len(opts.Key.Floats) != s.keyLen { | |
| return pb.StoresFindResult{}, fmt.Errorf("Try to add key with length %d when existing length is %d", len(opts.Key.Floats), s.keyLen) | |
| } | |
| } | |
| if s.keysAreNormalized && isNormalized(tk) { | |
| return s.StoresFindNormalized(opts) | |
| } else { | |
| if s.keysAreNormalized { | |
| var sample []float32 | |
| if len(s.keys) > 5 { | |
| sample = tk[:5] | |
| } else { | |
| sample = tk | |
| } | |
| log.Debug().Msgf("Trying to compare non-normalized key with normalized keys: %v", sample) | |
| } | |
| return s.StoresFindFallback(opts) | |
| } | |
| } | |