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server: return error when embedding contains NaN or Inf values (#13599)

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The normalize function now checks for NaN and Inf values in the
embedding vector before processing. This prevents JSON encoding
failures when models produce invalid floating-point values.

Fixes #13572

Signed-off-by: majiayu000 <1835304752@qq.com>
This commit is contained in:
lif
2026-01-03 15:20:12 +08:00
committed by GitHub
parent e1bdc23dd2
commit 37f6f3af24
2 changed files with 36 additions and 14 deletions
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18
server/routes.go
View File

@@ -752,9 +752,15 @@ func (s *Server) EmbedHandler(c *gin.Context) {
return err
}
// TODO: this first normalization should be done by the model
embedding = normalize(embedding)
embedding, err = normalize(embedding)
if err != nil {
return err
}
if req.Dimensions > 0 && req.Dimensions < len(embedding) {
embedding = normalize(embedding[:req.Dimensions])
embedding, err = normalize(embedding[:req.Dimensions])
if err != nil {
return err
}
}
embeddings[i] = embedding
atomic.AddUint64(&totalTokens, uint64(tokenCount))
@@ -787,9 +793,12 @@ func (s *Server) EmbedHandler(c *gin.Context) {
c.JSON(http.StatusOK, resp)
}
func normalize(vec []float32) []float32 {
func normalize(vec []float32) ([]float32, error) {
var sum float32
for _, v := range vec {
if math.IsNaN(float64(v)) || math.IsInf(float64(v), 0) {
return nil, errors.New("embedding contains NaN or Inf values")
}
sum += v * v
}
@@ -797,7 +806,7 @@ func normalize(vec []float32) []float32 {
for i := range vec {
vec[i] *= norm
}
return vec
return vec, nil
}
func (s *Server) EmbeddingsHandler(c *gin.Context) {
@@ -2395,4 +2404,3 @@ func filterThinkTags(msgs []api.Message, m *Model) []api.Message {
}
return msgs
}

32
server/routes_test.go
View File

@@ -723,15 +723,20 @@ func TestShow(t *testing.T) {
func TestNormalize(t *testing.T) {
type testCase struct {
input []float32
input []float32
expectError bool
}
testCases := []testCase{
{input: []float32{1}},
{input: []float32{0, 1, 2, 3}},
{input: []float32{0.1, 0.2, 0.3}},
{input: []float32{-0.1, 0.2, 0.3, -0.4}},
{input: []float32{0, 0, 0}},
{input: []float32{1}, expectError: false},
{input: []float32{0, 1, 2, 3}, expectError: false},
{input: []float32{0.1, 0.2, 0.3}, expectError: false},
{input: []float32{-0.1, 0.2, 0.3, -0.4}, expectError: false},
{input: []float32{0, 0, 0}, expectError: false},
{input: []float32{float32(math.NaN()), 0.2, 0.3}, expectError: true},
{input: []float32{0.1, float32(math.NaN()), 0.3}, expectError: true},
{input: []float32{float32(math.Inf(1)), 0.2, 0.3}, expectError: true},
{input: []float32{float32(math.Inf(-1)), 0.2, 0.3}, expectError: true},
}
isNormalized := func(vec []float32) (res bool) {
@@ -748,9 +753,18 @@ func TestNormalize(t *testing.T) {
for _, tc := range testCases {
t.Run("", func(t *testing.T) {
normalized := normalize(tc.input)
if !isNormalized(normalized) {
t.Errorf("Vector %v is not normalized", tc.input)
normalized, err := normalize(tc.input)
if tc.expectError {
if err == nil {
t.Errorf("Expected error for input %v, but got none", tc.input)
}
} else {
if err != nil {
t.Errorf("Unexpected error for input %v: %v", tc.input, err)
}
if !isNormalized(normalized) {
t.Errorf("Vector %v is not normalized", tc.input)
}
}
})
}