mirror of
https://github.com/ollama/ollama.git
synced 2026-01-19 21:08:16 -05:00
Compare commits
2 Commits
v0.14.3-rc
...
main
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
c42e9d244f | ||
|
|
e98b5e8b4e |
@@ -749,7 +749,7 @@ type ShowResponse struct {
|
||||
Messages []Message `json:"messages,omitempty"`
|
||||
RemoteModel string `json:"remote_model,omitempty"`
|
||||
RemoteHost string `json:"remote_host,omitempty"`
|
||||
ModelInfo map[string]any `json:"model_info,omitempty"`
|
||||
ModelInfo map[string]any `json:"model_info"`
|
||||
ProjectorInfo map[string]any `json:"projector_info,omitempty"`
|
||||
Tensors []Tensor `json:"tensors,omitempty"`
|
||||
Capabilities []model.Capability `json:"capabilities,omitempty"`
|
||||
|
||||
174
integration/imagegen_test.go
Normal file
174
integration/imagegen_test.go
Normal file
@@ -0,0 +1,174 @@
|
||||
//go:build integration
|
||||
|
||||
package integration
|
||||
|
||||
import (
|
||||
"bytes"
|
||||
"context"
|
||||
"encoding/base64"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"net/http"
|
||||
"strings"
|
||||
"testing"
|
||||
"time"
|
||||
|
||||
"github.com/ollama/ollama/api"
|
||||
imagegenapi "github.com/ollama/ollama/x/imagegen/api"
|
||||
)
|
||||
|
||||
func TestImageGeneration(t *testing.T) {
|
||||
skipUnderMinVRAM(t, 8)
|
||||
|
||||
type testCase struct {
|
||||
imageGenModel string
|
||||
visionModel string
|
||||
prompt string
|
||||
expectedWords []string
|
||||
}
|
||||
|
||||
testCases := []testCase{
|
||||
{
|
||||
imageGenModel: "jmorgan/z-image-turbo",
|
||||
visionModel: "llama3.2-vision",
|
||||
prompt: "A cartoon style llama flying like a superhero through the air with clouds in the background",
|
||||
expectedWords: []string{"llama", "flying", "cartoon", "cloud", "sky", "superhero", "air", "animal", "camelid"},
|
||||
},
|
||||
}
|
||||
|
||||
for _, tc := range testCases {
|
||||
t.Run(fmt.Sprintf("%s->%s", tc.imageGenModel, tc.visionModel), func(t *testing.T) {
|
||||
ctx, cancel := context.WithTimeout(context.Background(), 10*time.Minute)
|
||||
defer cancel()
|
||||
|
||||
client, testEndpoint, cleanup := InitServerConnection(ctx, t)
|
||||
defer cleanup()
|
||||
|
||||
// Pull both models
|
||||
if err := PullIfMissing(ctx, client, tc.imageGenModel); err != nil {
|
||||
t.Fatalf("failed to pull image gen model: %v", err)
|
||||
}
|
||||
if err := PullIfMissing(ctx, client, tc.visionModel); err != nil {
|
||||
t.Fatalf("failed to pull vision model: %v", err)
|
||||
}
|
||||
|
||||
// Generate the image
|
||||
t.Logf("Generating image with prompt: %s", tc.prompt)
|
||||
imageBase64, err := generateImage(ctx, testEndpoint, tc.imageGenModel, tc.prompt)
|
||||
if err != nil {
|
||||
if strings.Contains(err.Error(), "image generation not available") {
|
||||
t.Skip("Target system does not support image generation")
|
||||
} else if strings.Contains(err.Error(), "executable file not found in") { // Windows pattern, not yet supported
|
||||
t.Skip("Windows does not support image generation yet")
|
||||
} else if strings.Contains(err.Error(), "CUDA driver version is insufficient") {
|
||||
t.Skip("Driver is too old")
|
||||
} else if strings.Contains(err.Error(), "insufficient memory for image generation") {
|
||||
t.Skip("insufficient memory for image generation")
|
||||
} else if strings.Contains(err.Error(), "error while loading shared libraries: libcuda.so.1") { // AMD GPU or CPU
|
||||
t.Skip("CUDA GPU is not available")
|
||||
} else if strings.Contains(err.Error(), "ollama-mlx: no such file or directory") {
|
||||
// most likely linux arm - not supported yet
|
||||
t.Skip("unsupported architecture")
|
||||
}
|
||||
t.Fatalf("failed to generate image: %v", err)
|
||||
}
|
||||
|
||||
imageData, err := base64.StdEncoding.DecodeString(imageBase64)
|
||||
if err != nil {
|
||||
t.Fatalf("failed to decode image: %v", err)
|
||||
}
|
||||
t.Logf("Generated image: %d bytes", len(imageData))
|
||||
|
||||
// Preload vision model and check GPU loading
|
||||
err = client.Generate(ctx, &api.GenerateRequest{Model: tc.visionModel}, func(response api.GenerateResponse) error { return nil })
|
||||
if err != nil {
|
||||
t.Fatalf("failed to load vision model: %v", err)
|
||||
}
|
||||
|
||||
// Use vision model to describe the image
|
||||
chatReq := api.ChatRequest{
|
||||
Model: tc.visionModel,
|
||||
Messages: []api.Message{
|
||||
{
|
||||
Role: "user",
|
||||
Content: "Describe this image in detail. What is shown? What style is it? What is the main subject doing?",
|
||||
Images: []api.ImageData{imageData},
|
||||
},
|
||||
},
|
||||
Stream: &stream,
|
||||
Options: map[string]any{
|
||||
"seed": 42,
|
||||
"temperature": 0.0,
|
||||
},
|
||||
}
|
||||
|
||||
// Verify the vision model's response contains expected keywords
|
||||
response := DoChat(ctx, t, client, chatReq, tc.expectedWords, 240*time.Second, 30*time.Second)
|
||||
if response != nil {
|
||||
t.Logf("Vision model response: %s", response.Content)
|
||||
|
||||
// Additional detailed check for keywords
|
||||
content := strings.ToLower(response.Content)
|
||||
foundWords := []string{}
|
||||
missingWords := []string{}
|
||||
for _, word := range tc.expectedWords {
|
||||
if strings.Contains(content, word) {
|
||||
foundWords = append(foundWords, word)
|
||||
} else {
|
||||
missingWords = append(missingWords, word)
|
||||
}
|
||||
}
|
||||
t.Logf("Found keywords: %v", foundWords)
|
||||
if len(missingWords) > 0 {
|
||||
t.Logf("Missing keywords (at least one was found so test passed): %v", missingWords)
|
||||
}
|
||||
}
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
// generateImage calls the OpenAI-compatible image generation API and returns the base64 image data
|
||||
func generateImage(ctx context.Context, endpoint, model, prompt string) (string, error) {
|
||||
reqBody := imagegenapi.ImageGenerationRequest{
|
||||
Model: model,
|
||||
Prompt: prompt,
|
||||
N: 1,
|
||||
Size: "512x512",
|
||||
ResponseFormat: "b64_json",
|
||||
}
|
||||
|
||||
jsonBody, err := json.Marshal(reqBody)
|
||||
if err != nil {
|
||||
return "", fmt.Errorf("failed to marshal request: %w", err)
|
||||
}
|
||||
|
||||
url := fmt.Sprintf("http://%s/v1/images/generations", endpoint)
|
||||
req, err := http.NewRequestWithContext(ctx, "POST", url, bytes.NewReader(jsonBody))
|
||||
if err != nil {
|
||||
return "", fmt.Errorf("failed to create request: %w", err)
|
||||
}
|
||||
req.Header.Set("Content-Type", "application/json")
|
||||
|
||||
resp, err := http.DefaultClient.Do(req)
|
||||
if err != nil {
|
||||
return "", fmt.Errorf("failed to send request: %w", err)
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
|
||||
if resp.StatusCode != http.StatusOK {
|
||||
var buf bytes.Buffer
|
||||
buf.ReadFrom(resp.Body)
|
||||
return "", fmt.Errorf("unexpected status code %d: %s", resp.StatusCode, buf.String())
|
||||
}
|
||||
|
||||
var genResp imagegenapi.ImageGenerationResponse
|
||||
if err := json.NewDecoder(resp.Body).Decode(&genResp); err != nil {
|
||||
return "", fmt.Errorf("failed to decode response: %w", err)
|
||||
}
|
||||
|
||||
if len(genResp.Data) == 0 {
|
||||
return "", fmt.Errorf("no image data in response")
|
||||
}
|
||||
|
||||
return genResp.Data[0].B64JSON, nil
|
||||
}
|
||||
@@ -1149,6 +1149,9 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
|
||||
Capabilities: m.Capabilities(),
|
||||
ModifiedAt: manifest.fi.ModTime(),
|
||||
Requires: m.Config.Requires,
|
||||
// Several integrations crash on a nil/omitempty+empty ModelInfo, so by
|
||||
// default we return an empty map.
|
||||
ModelInfo: make(map[string]any),
|
||||
}
|
||||
|
||||
if m.Config.RemoteHost != "" {
|
||||
|
||||
Reference in New Issue
Block a user