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package zerfoo
import (
"context"
"math"
"strings"
"testing"
"time"
"github.com/zerfoo/zerfoo/inference"
ztoken "github.com/zerfoo/ztoken"
)
func TestLoad_pathDetection(t *testing.T) {
tests := []struct {
name string
input string
isLocal bool
}{
{"absolute path", "/models/gemma.gguf", true},
{"relative dot-slash", "./model.gguf", true},
{"relative parent", "../model.gguf", true},
{"huggingface id", "google/gemma-3-1b-it", false},
{"short alias", "gemma-3-1b-q4", false},
{"bare name", "my-model", false},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got := isLocalPath(tt.input)
if got != tt.isLocal {
t.Errorf("isLocalPath(%q) = %v, want %v", tt.input, got, tt.isLocal)
}
})
}
}
func TestLoad_missingFile(t *testing.T) {
_, err := Load("/nonexistent/path/to/model.gguf")
if err == nil {
t.Fatal("expected error for non-existent file, got nil")
}
}
func TestParseModelID(t *testing.T) {
tests := []struct {
name string
input string
wantRepo string
wantQuant string
}{
{"owner/model", "google/gemma-3-4b", "google/gemma-3-4b", defaultQuant},
{"owner/model/quant", "google/gemma-3-4b/Q8_0", "google/gemma-3-4b", "Q8_0"},
{"bare name", "my-model", "my-model", defaultQuant},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
repo, quant := parseModelID(tt.input)
if repo != tt.wantRepo {
t.Errorf("parseModelID(%q) repo = %q, want %q", tt.input, repo, tt.wantRepo)
}
if quant != tt.wantQuant {
t.Errorf("parseModelID(%q) quant = %q, want %q", tt.input, quant, tt.wantQuant)
}
})
}
}
func TestLoadFromHuggingFace_cacheMiss(t *testing.T) {
// Calling loadFromHuggingFace with a non-existent model will fail
// at the HuggingFace API call (no network in CI), confirming the
// cache-miss path reaches the client.
_, err := loadFromHuggingFace("nonexistent-org/nonexistent-model")
if err == nil {
t.Fatal("expected error for non-existent HuggingFace model, got nil")
}
}
func TestLoad_EmptyModelID(t *testing.T) {
_, err := Load("")
if err == nil {
t.Fatal("expected error for empty model ID, got nil")
}
}
func TestLoadFile_InvalidPath(t *testing.T) {
_, err := inference.LoadFile("/nonexistent/path/to/model.gguf")
if err == nil {
t.Fatal("expected error for non-existent GGUF file, got nil")
}
}
func TestLoadFile_WithOptions(t *testing.T) {
// LoadFile with options should still fail for a nonexistent file,
// confirming that options are accepted without panicking.
_, err := inference.LoadFile("/nonexistent/model.gguf", inference.WithMaxSeqLen(2048))
if err == nil {
t.Fatal("expected error for non-existent file with options, got nil")
}
}
func TestCosineSimilarity(t *testing.T) {
tests := []struct {
name string
a, b Embedding
want float32
}{
{
name: "identical vectors",
a: Embedding{Vector: []float32{1, 0, 0}},
b: Embedding{Vector: []float32{1, 0, 0}},
want: 1.0,
},
{
name: "orthogonal vectors",
a: Embedding{Vector: []float32{1, 0, 0}},
b: Embedding{Vector: []float32{0, 1, 0}},
want: 0.0,
},
{
name: "opposite vectors",
a: Embedding{Vector: []float32{1, 0, 0}},
b: Embedding{Vector: []float32{-1, 0, 0}},
want: -1.0,
},
{
name: "45 degree angle",
a: Embedding{Vector: []float32{1, 0}},
b: Embedding{Vector: []float32{1, 1}},
want: float32(1.0 / math.Sqrt(2)),
},
{
name: "empty vectors",
a: Embedding{Vector: []float32{}},
b: Embedding{Vector: []float32{}},
want: 0.0,
},
{
name: "mismatched lengths",
a: Embedding{Vector: []float32{1, 2}},
b: Embedding{Vector: []float32{1, 2, 3}},
want: 0.0,
},
{
name: "zero vector",
a: Embedding{Vector: []float32{0, 0, 0}},
b: Embedding{Vector: []float32{1, 2, 3}},
want: 0.0,
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got := tt.a.CosineSimilarity(tt.b)
if diff := math.Abs(float64(got - tt.want)); diff > 1e-6 {
t.Errorf("CosineSimilarity = %v, want %v (diff %v)", got, tt.want, diff)
}
})
}
}
func newTestModelWithEmbeddings(vocabTokens []string, dim int, weights []float32) *Model {
tok := ztoken.NewWhitespaceTokenizer()
for _, w := range vocabTokens {
tok.AddToken(w)
}
inner := inference.NewTestModel(nil, tok, nil, inference.ModelMetadata{}, nil)
inner.SetEmbeddingWeights(weights, dim)
return &Model{inner: inner}
}
func TestEmbed_returnsCorrectShape(t *testing.T) {
dim := 4
vocab := 6 // 4 special + 2 real
weights := make([]float32, vocab*dim)
weights[4*dim+0] = 1 // "hello" = ID 4
weights[5*dim+1] = 1 // "world" = ID 5
m := newTestModelWithEmbeddings([]string{"hello", "world"}, dim, weights)
results, err := m.Embed([]string{"hello", "world"})
if err != nil {
t.Fatalf("Embed returned error: %v", err)
}
if len(results) != 2 {
t.Fatalf("Embed returned %d embeddings, want 2", len(results))
}
for i, emb := range results {
if len(emb.Vector) != dim {
t.Errorf("embedding[%d] has dim %d, want %d", i, len(emb.Vector), dim)
}
}
}
func TestEmbed_identicalInputsSimilarity(t *testing.T) {
dim := 3
vocab := 5
weights := make([]float32, vocab*dim)
weights[4*dim+0] = 1
weights[4*dim+1] = 2
weights[4*dim+2] = 3
m := newTestModelWithEmbeddings([]string{"hello"}, dim, weights)
results, err := m.Embed([]string{"hello", "hello"})
if err != nil {
t.Fatalf("Embed returned error: %v", err)
}
sim := results[0].CosineSimilarity(results[1])
if diff := math.Abs(float64(sim - 1.0)); diff > 1e-6 {
t.Errorf("identical inputs: CosineSimilarity = %v, want 1.0", sim)
}
}
func TestEmbed_orthogonalTokens(t *testing.T) {
dim := 3
vocab := 6
weights := make([]float32, vocab*dim)
weights[4*dim+0] = 1 // "cat" along x-axis
weights[5*dim+1] = 1 // "dog" along y-axis
m := newTestModelWithEmbeddings([]string{"cat", "dog"}, dim, weights)
results, err := m.Embed([]string{"cat", "dog"})
if err != nil {
t.Fatalf("Embed returned error: %v", err)
}
sim := results[0].CosineSimilarity(results[1])
if diff := math.Abs(float64(sim)); diff > 1e-6 {
t.Errorf("orthogonal tokens: CosineSimilarity = %v, want 0.0", sim)
}
}
func TestEmbed_emptyInput(t *testing.T) {
inner := inference.NewTestModel(nil, nil, nil, inference.ModelMetadata{}, nil)
m := &Model{inner: inner}
results, err := m.Embed([]string{})
if err != nil {
t.Fatalf("Embed(empty) returned error: %v", err)
}
if results != nil {
t.Errorf("Embed(empty) = %v, want nil", results)
}
}
func TestEmbed_noEmbeddingWeights(t *testing.T) {
tok := ztoken.NewWhitespaceTokenizer()
inner := inference.NewTestModel(nil, tok, nil, inference.ModelMetadata{}, nil)
m := &Model{inner: inner}
_, err := m.Embed([]string{"hello"})
if err == nil {
t.Fatal("expected error when embedding weights not set")
}
}
func TestEmbed_EmptyString(t *testing.T) {
dim := 4
vocab := 5 // 4 special + 1 real
weights := make([]float32, vocab*dim)
weights[4*dim+0] = 1
m := newTestModelWithEmbeddings([]string{"hello"}, dim, weights)
// An empty string produces no tokens, so Embed should return an error.
_, err := m.Embed([]string{""})
if err == nil {
t.Fatal("expected error embedding empty string, got nil")
}
}
func TestEmbed_ValidText(t *testing.T) {
dim := 4
vocab := 6 // 4 special + 2 real
weights := make([]float32, vocab*dim)
weights[4*dim+0] = 3.0
weights[4*dim+1] = 4.0
weights[5*dim+2] = 1.0
weights[5*dim+3] = 2.0
m := newTestModelWithEmbeddings([]string{"hello", "world"}, dim, weights)
results, err := m.Embed([]string{"hello"})
if err != nil {
t.Fatalf("Embed returned error: %v", err)
}
if len(results) != 1 {
t.Fatalf("got %d embeddings, want 1", len(results))
}
if len(results[0].Vector) != dim {
t.Fatalf("embedding dim = %d, want %d", len(results[0].Vector), dim)
}
// Vector should contain non-zero float32 values.
allZero := true
for _, v := range results[0].Vector {
if v != 0 {
allZero = false
break
}
}
if allZero {
t.Error("expected non-zero embedding vector")
}
}
func TestEmbed_L2Normalized(t *testing.T) {
dim := 4
vocab := 6 // 4 special + 2 real
weights := make([]float32, vocab*dim)
// Set non-trivial weights so normalization is meaningful.
weights[4*dim+0] = 3.0
weights[4*dim+1] = 4.0
weights[5*dim+2] = 5.0
weights[5*dim+3] = 6.0
m := newTestModelWithEmbeddings([]string{"foo", "bar"}, dim, weights)
// Test single-token and multi-token inputs.
inputs := []string{"foo", "bar", "foo bar"}
results, err := m.Embed(inputs)
if err != nil {
t.Fatalf("Embed returned error: %v", err)
}
if len(results) != len(inputs) {
t.Fatalf("got %d embeddings, want %d", len(results), len(inputs))
}
for i, emb := range results {
var magnitude float64
for _, v := range emb.Vector {
magnitude += float64(v) * float64(v)
}
magnitude = math.Sqrt(magnitude)
if diff := math.Abs(magnitude - 1.0); diff > 1e-5 {
t.Errorf("embedding[%d] (%q): L2 magnitude = %v, want ~1.0 (diff %v)",
i, inputs[i], magnitude, diff)
}
}
}
func TestChat_returnsGeneratedText(t *testing.T) {
m := &Model{
generateFunc: func(ctx context.Context, prompt string) (string, error) {
return "Hello, I am a language model.", nil
},
}
text, err := m.Chat("hi")
if err != nil {
t.Fatalf("Chat returned error: %v", err)
}
if text != "Hello, I am a language model." {
t.Errorf("Chat = %q, want %q", text, "Hello, I am a language model.")
}
}
func TestChat_emptyPrompt(t *testing.T) {
m := &Model{
generateFunc: func(ctx context.Context, prompt string) (string, error) {
return "response to empty", nil
},
}
text, err := m.Chat("")
if err != nil {
t.Fatalf("Chat returned error: %v", err)
}
if text != "response to empty" {
t.Errorf("Chat = %q, want %q", text, "response to empty")
}
}
func TestChat_propagatesError(t *testing.T) {
m := &Model{
generateFunc: func(ctx context.Context, prompt string) (string, error) {
return "", context.Canceled
},
}
_, err := m.Chat("hello")
if err == nil {
t.Fatal("expected error, got nil")
}
}
func TestGenerate_returnsResult(t *testing.T) {
m := &Model{
generateFunc: func(ctx context.Context, prompt string) (string, error) {
time.Sleep(time.Millisecond) // ensure Duration > 0 on fast hardware
return "generated text", nil
},
}
result, err := m.Generate(context.Background(), "test prompt")
if err != nil {
t.Fatalf("Generate returned error: %v", err)
}
if result == nil {
t.Fatal("Generate returned nil result")
}
if result.Text != "generated text" {
t.Errorf("result.Text = %q, want %q", result.Text, "generated text")
}
if result.Duration <= 0 {
t.Errorf("result.Duration = %v, want > 0", result.Duration)
}
}
func TestGenerate_nilContext(t *testing.T) {
m := &Model{
generateFunc: func(ctx context.Context, prompt string) (string, error) {
if ctx == nil {
return "", context.Canceled
}
return "ok", nil
},
}
//nolint:staticcheck // SA1012: deliberately passing nil context to test behavior
_, err := m.Generate(nil, "test")
if err == nil {
t.Log("Generate with nil context succeeded (generateFunc handled it)")
}
_ = err
}
func TestGenerate_withOptions(t *testing.T) {
m := &Model{
generateFunc: func(ctx context.Context, prompt string) (string, error) {
return "options applied", nil
},
}
result, err := m.Generate(context.Background(), "test",
WithGenMaxTokens(100),
WithGenTemperature(0.7),
WithGenTopP(0.9),
)
if err != nil {
t.Fatalf("Generate returned error: %v", err)
}
if result.Text != "options applied" {
t.Errorf("result.Text = %q, want %q", result.Text, "options applied")
}
}
func TestGenerate_emptyPrompt(t *testing.T) {
m := &Model{
generateFunc: func(ctx context.Context, prompt string) (string, error) {
if prompt == "" {
return "empty prompt response", nil
}
return "non-empty", nil
},
}
result, err := m.Generate(context.Background(), "")
if err != nil {
t.Fatalf("Generate returned error: %v", err)
}
if result.Text != "empty prompt response" {
t.Errorf("result.Text = %q, want %q", result.Text, "empty prompt response")
}
}
func TestGenerate_contextCancellation(t *testing.T) {
ctx, cancel := context.WithCancel(context.Background())
cancel() // Cancel immediately.
m := &Model{
generateFunc: func(ctx context.Context, prompt string) (string, error) {
return "", ctx.Err()
},
}
_, err := m.Generate(ctx, "test")
if err == nil {
t.Fatal("expected error for cancelled context, got nil")
}
}
func TestGenerate_withTokenizer(t *testing.T) {
tok := ztoken.NewWhitespaceTokenizer()
tok.AddToken("hello")
tok.AddToken("world")
inner := inference.NewTestModel(nil, tok, nil, inference.ModelMetadata{}, nil)
m := &Model{
inner: inner,
generateFunc: func(ctx context.Context, prompt string) (string, error) {
return "hello world", nil
},
}
result, err := m.Generate(context.Background(), "test")
if err != nil {
t.Fatalf("Generate returned error: %v", err)
}
if result.TokenCount == 0 {
t.Error("expected non-zero TokenCount when tokenizer is available")
}
}
func TestChatStream_nilModel(t *testing.T) {
m := &Model{}
ch, err := m.ChatStream(context.Background(), "hello")
if err == nil {
t.Fatal("expected error for nil model, got nil")
}
if ch != nil {
t.Errorf("expected nil channel, got %v", ch)
}
}
func TestChatStream_yieldsTokens(t *testing.T) {
m := &Model{
generateFunc: func(ctx context.Context, prompt string) (string, error) {
return "hello world foo", nil
},
}
ch, err := m.ChatStream(context.Background(), "test prompt")
if err != nil {
t.Fatalf("ChatStream returned error: %v", err)
}
if ch == nil {
t.Fatal("expected non-nil channel")
}
var tokens []StreamToken
for tok := range ch {
tokens = append(tokens, tok)
}
// Expect 3 word tokens + 1 done token.
if len(tokens) != 4 {
t.Fatalf("got %d tokens, want 4: %v", len(tokens), tokens)
}
// Verify words are streamed with spaces between them.
if tokens[0].Text != "hello " {
t.Errorf("token[0] = %q, want %q", tokens[0].Text, "hello ")
}
if tokens[1].Text != "world " {
t.Errorf("token[1] = %q, want %q", tokens[1].Text, "world ")
}
if tokens[2].Text != "foo" {
t.Errorf("token[2] = %q, want %q", tokens[2].Text, "foo")
}
// Last token should be done signal.
if !tokens[3].Done {
t.Error("last token should have Done=true")
}
// Reconstructed text should match original.
var sb strings.Builder
for _, tok := range tokens {
sb.WriteString(tok.Text)
}
if got := sb.String(); got != "hello world foo" {
t.Errorf("reconstructed text = %q, want %q", got, "hello world foo")
}
}
func TestChatStream_channelCloses(t *testing.T) {
m := &Model{
generateFunc: func(ctx context.Context, prompt string) (string, error) {
return "done", nil
},
}
ch, err := m.ChatStream(context.Background(), "test")
if err != nil {
t.Fatalf("ChatStream returned error: %v", err)
}
// Drain channel and verify it closes.
count := 0
for range ch {
count++
}
if count != 2 { // 1 word + 1 done
t.Errorf("got %d tokens, want 2", count)
}
}
func TestChatStream_contextCancellation(t *testing.T) {
ctx, cancel := context.WithCancel(context.Background())
m := &Model{
generateFunc: func(ctx context.Context, prompt string) (string, error) {
// Simulate a slow generation that respects context.
select {
case <-ctx.Done():
return "", ctx.Err()
case <-time.After(5 * time.Second):
return "this should not appear", nil
}
},
}
ch, err := m.ChatStream(ctx, "test")
if err != nil {
t.Fatalf("ChatStream returned error: %v", err)
}
// Cancel context immediately.
cancel()
// Channel should close without delivering the full result.
timer := time.NewTimer(2 * time.Second)
defer timer.Stop()
select {
case _, ok := <-ch:
if ok {
// May get some tokens before cancellation is noticed; drain.
for range ch {
}
}
case <-timer.C:
t.Fatal("channel did not close after context cancellation")
}
}
func TestChatStream_emptyResult(t *testing.T) {
m := &Model{
generateFunc: func(ctx context.Context, prompt string) (string, error) {
return "", nil
},
}
ch, err := m.ChatStream(context.Background(), "test")
if err != nil {
t.Fatalf("ChatStream returned error: %v", err)
}
var tokens []StreamToken
for tok := range ch {
tokens = append(tokens, tok)
}
// Empty string has no words, only a done signal.
if len(tokens) != 1 {
t.Fatalf("got %d tokens, want 1: %v", len(tokens), tokens)
}
if !tokens[0].Done {
t.Error("expected done signal")
}
}