mirror of https://github.com/mudler/LocalAI.git
903 lines
30 KiB
Go
903 lines
30 KiB
Go
package http_test
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import (
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"bytes"
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"context"
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"embed"
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"encoding/json"
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"errors"
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"fmt"
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"io"
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"net/http"
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"os"
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"path/filepath"
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"runtime"
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"github.com/go-skynet/LocalAI/core/config"
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. "github.com/go-skynet/LocalAI/core/http"
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"github.com/go-skynet/LocalAI/core/startup"
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"github.com/go-skynet/LocalAI/pkg/downloader"
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"github.com/go-skynet/LocalAI/pkg/gallery"
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"github.com/go-skynet/LocalAI/pkg/model"
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"github.com/gofiber/fiber/v2"
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. "github.com/onsi/ginkgo/v2"
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. "github.com/onsi/gomega"
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"gopkg.in/yaml.v3"
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openaigo "github.com/otiai10/openaigo"
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"github.com/sashabaranov/go-openai"
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"github.com/sashabaranov/go-openai/jsonschema"
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)
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const testPrompt = `### System:
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You are an AI assistant that follows instruction extremely well. Help as much as you can.
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### User:
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Can you help rephrasing sentences?
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### Response:`
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type modelApplyRequest struct {
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ID string `json:"id"`
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URL string `json:"url"`
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Name string `json:"name"`
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Overrides map[string]interface{} `json:"overrides"`
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}
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func getModelStatus(url string) (response map[string]interface{}) {
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// Create the HTTP request
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resp, err := http.Get(url)
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if err != nil {
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fmt.Println("Error creating request:", err)
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return
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}
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defer resp.Body.Close()
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body, err := io.ReadAll(resp.Body)
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if err != nil {
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fmt.Println("Error reading response body:", err)
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return
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}
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// Unmarshal the response into a map[string]interface{}
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err = json.Unmarshal(body, &response)
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if err != nil {
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fmt.Println("Error unmarshaling JSON response:", err)
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return
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}
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return
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}
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func getModels(url string) (response []gallery.GalleryModel) {
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downloader.GetURI(url, func(url string, i []byte) error {
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// Unmarshal YAML data into a struct
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return json.Unmarshal(i, &response)
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})
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return
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}
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func postModelApplyRequest(url string, request modelApplyRequest) (response map[string]interface{}) {
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//url := "http://localhost:AI/models/apply"
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// Create the request payload
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payload, err := json.Marshal(request)
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if err != nil {
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fmt.Println("Error marshaling JSON:", err)
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return
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}
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// Create the HTTP request
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req, err := http.NewRequest("POST", url, bytes.NewBuffer(payload))
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if err != nil {
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fmt.Println("Error creating request:", err)
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return
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}
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req.Header.Set("Content-Type", "application/json")
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// Make the request
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client := &http.Client{}
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resp, err := client.Do(req)
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if err != nil {
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fmt.Println("Error making request:", err)
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return
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}
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defer resp.Body.Close()
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body, err := io.ReadAll(resp.Body)
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if err != nil {
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fmt.Println("Error reading response body:", err)
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return
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}
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// Unmarshal the response into a map[string]interface{}
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err = json.Unmarshal(body, &response)
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if err != nil {
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fmt.Println("Error unmarshaling JSON response:", err)
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return
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}
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return
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}
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//go:embed backend-assets/*
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var backendAssets embed.FS
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var _ = Describe("API test", func() {
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var app *fiber.App
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var client *openai.Client
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var client2 *openaigo.Client
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var c context.Context
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var cancel context.CancelFunc
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var tmpdir string
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var modelDir string
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var bcl *config.BackendConfigLoader
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var ml *model.ModelLoader
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var applicationConfig *config.ApplicationConfig
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commonOpts := []config.AppOption{
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config.WithDebug(true),
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config.WithDisableMessage(true),
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}
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Context("API with ephemeral models", func() {
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BeforeEach(func(sc SpecContext) {
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var err error
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tmpdir, err = os.MkdirTemp("", "")
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Expect(err).ToNot(HaveOccurred())
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modelDir = filepath.Join(tmpdir, "models")
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backendAssetsDir := filepath.Join(tmpdir, "backend-assets")
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err = os.Mkdir(backendAssetsDir, 0755)
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Expect(err).ToNot(HaveOccurred())
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c, cancel = context.WithCancel(context.Background())
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g := []gallery.GalleryModel{
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{
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Name: "bert",
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URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
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},
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{
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Name: "bert2",
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URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
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Overrides: map[string]interface{}{"foo": "bar"},
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AdditionalFiles: []gallery.File{{Filename: "foo.yaml", URI: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml"}},
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},
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}
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out, err := yaml.Marshal(g)
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Expect(err).ToNot(HaveOccurred())
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err = os.WriteFile(filepath.Join(tmpdir, "gallery_simple.yaml"), out, 0644)
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Expect(err).ToNot(HaveOccurred())
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galleries := []gallery.Gallery{
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{
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Name: "test",
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URL: "file://" + filepath.Join(tmpdir, "gallery_simple.yaml"),
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},
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}
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bcl, ml, applicationConfig, err = startup.Startup(
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append(commonOpts,
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config.WithContext(c),
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config.WithGalleries(galleries),
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config.WithModelPath(modelDir),
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config.WithBackendAssets(backendAssets),
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config.WithBackendAssetsOutput(backendAssetsDir))...)
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Expect(err).ToNot(HaveOccurred())
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app, err = App(bcl, ml, applicationConfig)
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Expect(err).ToNot(HaveOccurred())
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go app.Listen("127.0.0.1:9090")
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defaultConfig := openai.DefaultConfig("")
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defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
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client2 = openaigo.NewClient("")
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client2.BaseURL = defaultConfig.BaseURL
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// Wait for API to be ready
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client = openai.NewClientWithConfig(defaultConfig)
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Eventually(func() error {
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_, err := client.ListModels(context.TODO())
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return err
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}, "2m").ShouldNot(HaveOccurred())
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})
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AfterEach(func(sc SpecContext) {
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cancel()
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if app != nil {
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err := app.Shutdown()
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Expect(err).ToNot(HaveOccurred())
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}
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err := os.RemoveAll(tmpdir)
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Expect(err).ToNot(HaveOccurred())
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_, err = os.ReadDir(tmpdir)
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Expect(err).To(HaveOccurred())
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})
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Context("Applying models", func() {
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It("applies models from a gallery", func() {
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models := getModels("http://127.0.0.1:9090/models/available")
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Expect(len(models)).To(Equal(2), fmt.Sprint(models))
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Expect(models[0].Installed).To(BeFalse(), fmt.Sprint(models))
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Expect(models[1].Installed).To(BeFalse(), fmt.Sprint(models))
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response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
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ID: "test@bert2",
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})
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Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
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uuid := response["uuid"].(string)
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resp := map[string]interface{}{}
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Eventually(func() bool {
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response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
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fmt.Println(response)
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resp = response
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return response["processed"].(bool)
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}, "360s", "10s").Should(Equal(true))
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Expect(resp["message"]).ToNot(ContainSubstring("error"))
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dat, err := os.ReadFile(filepath.Join(modelDir, "bert2.yaml"))
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Expect(err).ToNot(HaveOccurred())
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_, err = os.ReadFile(filepath.Join(modelDir, "foo.yaml"))
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Expect(err).ToNot(HaveOccurred())
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content := map[string]interface{}{}
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err = yaml.Unmarshal(dat, &content)
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Expect(err).ToNot(HaveOccurred())
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Expect(content["backend"]).To(Equal("bert-embeddings"))
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Expect(content["foo"]).To(Equal("bar"))
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models = getModels("http://127.0.0.1:9090/models/available")
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Expect(len(models)).To(Equal(2), fmt.Sprint(models))
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Expect(models[0].Name).To(Or(Equal("bert"), Equal("bert2")))
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Expect(models[1].Name).To(Or(Equal("bert"), Equal("bert2")))
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for _, m := range models {
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if m.Name == "bert2" {
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Expect(m.Installed).To(BeTrue())
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} else {
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Expect(m.Installed).To(BeFalse())
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}
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}
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})
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It("overrides models", func() {
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response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
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URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
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Name: "bert",
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Overrides: map[string]interface{}{
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"backend": "llama",
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},
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})
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Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
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uuid := response["uuid"].(string)
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Eventually(func() bool {
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response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
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return response["processed"].(bool)
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}, "360s", "10s").Should(Equal(true))
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dat, err := os.ReadFile(filepath.Join(modelDir, "bert.yaml"))
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Expect(err).ToNot(HaveOccurred())
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content := map[string]interface{}{}
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err = yaml.Unmarshal(dat, &content)
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Expect(err).ToNot(HaveOccurred())
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Expect(content["backend"]).To(Equal("llama"))
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})
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It("apply models without overrides", func() {
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response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
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URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
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Name: "bert",
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Overrides: map[string]interface{}{},
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})
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Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
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uuid := response["uuid"].(string)
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Eventually(func() bool {
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response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
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return response["processed"].(bool)
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}, "360s", "10s").Should(Equal(true))
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dat, err := os.ReadFile(filepath.Join(modelDir, "bert.yaml"))
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Expect(err).ToNot(HaveOccurred())
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content := map[string]interface{}{}
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err = yaml.Unmarshal(dat, &content)
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Expect(err).ToNot(HaveOccurred())
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Expect(content["backend"]).To(Equal("bert-embeddings"))
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})
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It("runs openllama(llama-ggml backend)", Label("llama"), func() {
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if runtime.GOOS != "linux" {
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Skip("test supported only on linux")
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}
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response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
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URL: "github:go-skynet/model-gallery/openllama_3b.yaml",
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Name: "openllama_3b",
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Overrides: map[string]interface{}{"backend": "llama-ggml", "mmap": true, "f16": true, "context_size": 128},
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})
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Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
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uuid := response["uuid"].(string)
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Eventually(func() bool {
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response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
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return response["processed"].(bool)
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}, "360s", "10s").Should(Equal(true))
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By("testing completion")
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resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "openllama_3b", Prompt: "Count up to five: one, two, three, four, "})
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Expect(err).ToNot(HaveOccurred())
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Expect(len(resp.Choices)).To(Equal(1))
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Expect(resp.Choices[0].Text).To(ContainSubstring("five"))
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By("testing functions")
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resp2, err := client.CreateChatCompletion(
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context.TODO(),
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openai.ChatCompletionRequest{
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Model: "openllama_3b",
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Messages: []openai.ChatCompletionMessage{
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{
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Role: "user",
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Content: "What is the weather like in San Francisco (celsius)?",
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},
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},
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Functions: []openai.FunctionDefinition{
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openai.FunctionDefinition{
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Name: "get_current_weather",
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Description: "Get the current weather",
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Parameters: jsonschema.Definition{
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Type: jsonschema.Object,
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Properties: map[string]jsonschema.Definition{
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"location": {
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Type: jsonschema.String,
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Description: "The city and state, e.g. San Francisco, CA",
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},
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"unit": {
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Type: jsonschema.String,
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Enum: []string{"celcius", "fahrenheit"},
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},
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},
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Required: []string{"location"},
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},
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},
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},
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})
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Expect(err).ToNot(HaveOccurred())
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Expect(len(resp2.Choices)).To(Equal(1))
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Expect(resp2.Choices[0].Message.FunctionCall).ToNot(BeNil())
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Expect(resp2.Choices[0].Message.FunctionCall.Name).To(Equal("get_current_weather"), resp2.Choices[0].Message.FunctionCall.Name)
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var res map[string]string
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err = json.Unmarshal([]byte(resp2.Choices[0].Message.FunctionCall.Arguments), &res)
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Expect(err).ToNot(HaveOccurred())
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Expect(res["location"]).To(Equal("San Francisco, California, United States"), fmt.Sprint(res))
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Expect(res["unit"]).To(Equal("celcius"), fmt.Sprint(res))
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Expect(string(resp2.Choices[0].FinishReason)).To(Equal("function_call"), fmt.Sprint(resp2.Choices[0].FinishReason))
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})
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It("runs openllama gguf(llama-cpp)", Label("llama-gguf"), func() {
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if runtime.GOOS != "linux" {
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Skip("test supported only on linux")
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}
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modelName := "codellama"
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response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
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URL: "github:go-skynet/model-gallery/codellama-7b-instruct.yaml",
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Name: modelName,
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Overrides: map[string]interface{}{"backend": "llama", "mmap": true, "f16": true, "context_size": 128},
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})
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Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
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uuid := response["uuid"].(string)
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Eventually(func() bool {
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response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
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return response["processed"].(bool)
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}, "360s", "10s").Should(Equal(true))
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By("testing chat")
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resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: modelName, Messages: []openai.ChatCompletionMessage{
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{
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Role: "user",
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Content: "How much is 2+2?",
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},
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}})
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Expect(err).ToNot(HaveOccurred())
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Expect(len(resp.Choices)).To(Equal(1))
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Expect(resp.Choices[0].Message.Content).To(Or(ContainSubstring("4"), ContainSubstring("four")))
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By("testing functions")
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resp2, err := client.CreateChatCompletion(
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context.TODO(),
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openai.ChatCompletionRequest{
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Model: modelName,
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Messages: []openai.ChatCompletionMessage{
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{
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Role: "user",
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Content: "What is the weather like in San Francisco (celsius)?",
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},
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},
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Functions: []openai.FunctionDefinition{
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openai.FunctionDefinition{
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Name: "get_current_weather",
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Description: "Get the current weather",
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Parameters: jsonschema.Definition{
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Type: jsonschema.Object,
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Properties: map[string]jsonschema.Definition{
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"location": {
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Type: jsonschema.String,
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Description: "The city and state, e.g. San Francisco, CA",
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},
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"unit": {
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Type: jsonschema.String,
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Enum: []string{"celcius", "fahrenheit"},
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},
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},
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Required: []string{"location"},
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},
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},
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},
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})
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Expect(err).ToNot(HaveOccurred())
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Expect(len(resp2.Choices)).To(Equal(1))
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Expect(resp2.Choices[0].Message.FunctionCall).ToNot(BeNil())
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Expect(resp2.Choices[0].Message.FunctionCall.Name).To(Equal("get_current_weather"), resp2.Choices[0].Message.FunctionCall.Name)
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var res map[string]string
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err = json.Unmarshal([]byte(resp2.Choices[0].Message.FunctionCall.Arguments), &res)
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Expect(err).ToNot(HaveOccurred())
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Expect(res["location"]).To(Equal("San Francisco"), fmt.Sprint(res))
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Expect(res["unit"]).To(Equal("celcius"), fmt.Sprint(res))
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Expect(string(resp2.Choices[0].FinishReason)).To(Equal("function_call"), fmt.Sprint(resp2.Choices[0].FinishReason))
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})
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It("runs gpt4all", Label("gpt4all"), func() {
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if runtime.GOOS != "linux" {
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Skip("test supported only on linux")
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}
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response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
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URL: "github:go-skynet/model-gallery/gpt4all-j.yaml",
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Name: "gpt4all-j",
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})
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Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
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uuid := response["uuid"].(string)
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Eventually(func() bool {
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response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
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return response["processed"].(bool)
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}, "960s", "10s").Should(Equal(true))
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|
|
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "gpt4all-j", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "How are you?"}}})
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(len(resp.Choices)).To(Equal(1))
|
|
Expect(resp.Choices[0].Message.Content).To(ContainSubstring("well"))
|
|
})
|
|
|
|
})
|
|
})
|
|
|
|
Context("Model gallery", func() {
|
|
BeforeEach(func() {
|
|
var err error
|
|
tmpdir, err = os.MkdirTemp("", "")
|
|
Expect(err).ToNot(HaveOccurred())
|
|
modelDir = filepath.Join(tmpdir, "models")
|
|
backendAssetsDir := filepath.Join(tmpdir, "backend-assets")
|
|
err = os.Mkdir(backendAssetsDir, 0755)
|
|
Expect(err).ToNot(HaveOccurred())
|
|
|
|
c, cancel = context.WithCancel(context.Background())
|
|
|
|
galleries := []gallery.Gallery{
|
|
{
|
|
Name: "model-gallery",
|
|
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/index.yaml",
|
|
},
|
|
}
|
|
|
|
bcl, ml, applicationConfig, err = startup.Startup(
|
|
append(commonOpts,
|
|
config.WithContext(c),
|
|
config.WithAudioDir(tmpdir),
|
|
config.WithImageDir(tmpdir),
|
|
config.WithGalleries(galleries),
|
|
config.WithModelPath(modelDir),
|
|
config.WithBackendAssets(backendAssets),
|
|
config.WithBackendAssetsOutput(tmpdir))...,
|
|
)
|
|
Expect(err).ToNot(HaveOccurred())
|
|
app, err = App(bcl, ml, applicationConfig)
|
|
Expect(err).ToNot(HaveOccurred())
|
|
|
|
go app.Listen("127.0.0.1:9090")
|
|
|
|
defaultConfig := openai.DefaultConfig("")
|
|
defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
|
|
|
|
client2 = openaigo.NewClient("")
|
|
client2.BaseURL = defaultConfig.BaseURL
|
|
|
|
// Wait for API to be ready
|
|
client = openai.NewClientWithConfig(defaultConfig)
|
|
Eventually(func() error {
|
|
_, err := client.ListModels(context.TODO())
|
|
return err
|
|
}, "2m").ShouldNot(HaveOccurred())
|
|
})
|
|
|
|
AfterEach(func() {
|
|
cancel()
|
|
if app != nil {
|
|
err := app.Shutdown()
|
|
Expect(err).ToNot(HaveOccurred())
|
|
}
|
|
err := os.RemoveAll(tmpdir)
|
|
Expect(err).ToNot(HaveOccurred())
|
|
_, err = os.ReadDir(tmpdir)
|
|
Expect(err).To(HaveOccurred())
|
|
})
|
|
It("installs and is capable to run tts", Label("tts"), func() {
|
|
if runtime.GOOS != "linux" {
|
|
Skip("test supported only on linux")
|
|
}
|
|
|
|
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
|
ID: "model-gallery@voice-en-us-kathleen-low",
|
|
})
|
|
|
|
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
|
|
|
uuid := response["uuid"].(string)
|
|
|
|
Eventually(func() bool {
|
|
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
|
fmt.Println(response)
|
|
return response["processed"].(bool)
|
|
}, "360s", "10s").Should(Equal(true))
|
|
|
|
// An HTTP Post to the /tts endpoint should return a wav audio file
|
|
resp, err := http.Post("http://127.0.0.1:9090/tts", "application/json", bytes.NewBuffer([]byte(`{"input": "Hello world", "model": "en-us-kathleen-low.onnx"}`)))
|
|
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
|
|
dat, err := io.ReadAll(resp.Body)
|
|
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
|
|
|
|
Expect(resp.StatusCode).To(Equal(200), fmt.Sprint(string(dat)))
|
|
Expect(resp.Header.Get("Content-Type")).To(Equal("audio/x-wav"))
|
|
})
|
|
It("installs and is capable to generate images", Label("stablediffusion"), func() {
|
|
if runtime.GOOS != "linux" {
|
|
Skip("test supported only on linux")
|
|
}
|
|
|
|
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
|
ID: "model-gallery@stablediffusion",
|
|
Overrides: map[string]interface{}{
|
|
"parameters": map[string]interface{}{"model": "stablediffusion_assets"},
|
|
},
|
|
})
|
|
|
|
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
|
|
|
uuid := response["uuid"].(string)
|
|
|
|
Eventually(func() bool {
|
|
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
|
fmt.Println(response)
|
|
return response["processed"].(bool)
|
|
}, "360s", "10s").Should(Equal(true))
|
|
|
|
resp, err := http.Post(
|
|
"http://127.0.0.1:9090/v1/images/generations",
|
|
"application/json",
|
|
bytes.NewBuffer([]byte(`{
|
|
"prompt": "floating hair, portrait, ((loli)), ((one girl)), cute face, hidden hands, asymmetrical bangs, beautiful detailed eyes, eye shadow, hair ornament, ribbons, bowties, buttons, pleated skirt, (((masterpiece))), ((best quality)), colorful|((part of the head)), ((((mutated hands and fingers)))), deformed, blurry, bad anatomy, disfigured, poorly drawn face, mutation, mutated, extra limb, ugly, poorly drawn hands, missing limb, blurry, floating limbs, disconnected limbs, malformed hands, blur, out of focus, long neck, long body, Octane renderer, lowres, bad anatomy, bad hands, text",
|
|
"mode": 2, "seed":9000,
|
|
"size": "256x256", "n":2}`)))
|
|
// The response should contain an URL
|
|
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
|
|
dat, err := io.ReadAll(resp.Body)
|
|
Expect(err).ToNot(HaveOccurred(), string(dat))
|
|
Expect(string(dat)).To(ContainSubstring("http://127.0.0.1:9090/"), string(dat))
|
|
Expect(string(dat)).To(ContainSubstring(".png"), string(dat))
|
|
|
|
})
|
|
})
|
|
|
|
Context("API query", func() {
|
|
BeforeEach(func() {
|
|
modelPath := os.Getenv("MODELS_PATH")
|
|
c, cancel = context.WithCancel(context.Background())
|
|
|
|
var err error
|
|
|
|
bcl, ml, applicationConfig, err = startup.Startup(
|
|
append(commonOpts,
|
|
config.WithExternalBackend("huggingface", os.Getenv("HUGGINGFACE_GRPC")),
|
|
config.WithContext(c),
|
|
config.WithModelPath(modelPath),
|
|
)...)
|
|
Expect(err).ToNot(HaveOccurred())
|
|
app, err = App(bcl, ml, applicationConfig)
|
|
Expect(err).ToNot(HaveOccurred())
|
|
go app.Listen("127.0.0.1:9090")
|
|
|
|
defaultConfig := openai.DefaultConfig("")
|
|
defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
|
|
|
|
client2 = openaigo.NewClient("")
|
|
client2.BaseURL = defaultConfig.BaseURL
|
|
|
|
// Wait for API to be ready
|
|
client = openai.NewClientWithConfig(defaultConfig)
|
|
Eventually(func() error {
|
|
_, err := client.ListModels(context.TODO())
|
|
return err
|
|
}, "2m").ShouldNot(HaveOccurred())
|
|
})
|
|
AfterEach(func() {
|
|
cancel()
|
|
if app != nil {
|
|
err := app.Shutdown()
|
|
Expect(err).ToNot(HaveOccurred())
|
|
}
|
|
})
|
|
It("returns the models list", func() {
|
|
models, err := client.ListModels(context.TODO())
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(len(models.Models)).To(Equal(6)) // If "config.yaml" should be included, this should be 8?
|
|
})
|
|
It("can generate completions", func() {
|
|
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "testmodel", Prompt: testPrompt})
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(len(resp.Choices)).To(Equal(1))
|
|
Expect(resp.Choices[0].Text).ToNot(BeEmpty())
|
|
})
|
|
|
|
It("can generate chat completions ", func() {
|
|
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "testmodel", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: testPrompt}}})
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(len(resp.Choices)).To(Equal(1))
|
|
Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
|
|
})
|
|
|
|
It("can generate completions from model configs", func() {
|
|
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "gpt4all", Prompt: testPrompt})
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(len(resp.Choices)).To(Equal(1))
|
|
Expect(resp.Choices[0].Text).ToNot(BeEmpty())
|
|
})
|
|
|
|
It("can generate chat completions from model configs", func() {
|
|
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "gpt4all-2", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: testPrompt}}})
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(len(resp.Choices)).To(Equal(1))
|
|
Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
|
|
})
|
|
|
|
It("returns errors", func() {
|
|
backends := len(model.AutoLoadBackends) + 1 // +1 for huggingface
|
|
_, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "foomodel", Prompt: testPrompt})
|
|
Expect(err).To(HaveOccurred())
|
|
Expect(err.Error()).To(ContainSubstring(fmt.Sprintf("error, status code: 500, message: could not load model - all backends returned error: %d errors occurred:", backends)))
|
|
})
|
|
It("transcribes audio", func() {
|
|
if runtime.GOOS != "linux" {
|
|
Skip("test supported only on linux")
|
|
}
|
|
resp, err := client.CreateTranscription(
|
|
context.Background(),
|
|
openai.AudioRequest{
|
|
Model: openai.Whisper1,
|
|
FilePath: filepath.Join(os.Getenv("TEST_DIR"), "audio.wav"),
|
|
},
|
|
)
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(resp.Text).To(ContainSubstring("This is the Micro Machine Man presenting"))
|
|
})
|
|
|
|
It("calculate embeddings", func() {
|
|
if runtime.GOOS != "linux" {
|
|
Skip("test supported only on linux")
|
|
}
|
|
resp, err := client.CreateEmbeddings(
|
|
context.Background(),
|
|
openai.EmbeddingRequest{
|
|
Model: openai.AdaEmbeddingV2,
|
|
Input: []string{"sun", "cat"},
|
|
},
|
|
)
|
|
Expect(err).ToNot(HaveOccurred(), err)
|
|
Expect(len(resp.Data[0].Embedding)).To(BeNumerically("==", 384))
|
|
Expect(len(resp.Data[1].Embedding)).To(BeNumerically("==", 384))
|
|
|
|
sunEmbedding := resp.Data[0].Embedding
|
|
resp2, err := client.CreateEmbeddings(
|
|
context.Background(),
|
|
openai.EmbeddingRequest{
|
|
Model: openai.AdaEmbeddingV2,
|
|
Input: []string{"sun"},
|
|
},
|
|
)
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(resp2.Data[0].Embedding).To(Equal(sunEmbedding))
|
|
})
|
|
|
|
Context("External gRPC calls", func() {
|
|
It("calculate embeddings with sentencetransformers", func() {
|
|
if runtime.GOOS != "linux" {
|
|
Skip("test supported only on linux")
|
|
}
|
|
resp, err := client.CreateEmbeddings(
|
|
context.Background(),
|
|
openai.EmbeddingRequest{
|
|
Model: openai.AdaCodeSearchCode,
|
|
Input: []string{"sun", "cat"},
|
|
},
|
|
)
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(len(resp.Data[0].Embedding)).To(BeNumerically("==", 384))
|
|
Expect(len(resp.Data[1].Embedding)).To(BeNumerically("==", 384))
|
|
|
|
sunEmbedding := resp.Data[0].Embedding
|
|
resp2, err := client.CreateEmbeddings(
|
|
context.Background(),
|
|
openai.EmbeddingRequest{
|
|
Model: openai.AdaCodeSearchCode,
|
|
Input: []string{"sun"},
|
|
},
|
|
)
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(resp2.Data[0].Embedding).To(Equal(sunEmbedding))
|
|
Expect(resp2.Data[0].Embedding).ToNot(Equal(resp.Data[1].Embedding))
|
|
})
|
|
})
|
|
|
|
Context("backends", func() {
|
|
It("runs rwkv completion", func() {
|
|
if runtime.GOOS != "linux" {
|
|
Skip("test supported only on linux")
|
|
}
|
|
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "rwkv_test", Prompt: "Count up to five: one, two, three, four,"})
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(len(resp.Choices) > 0).To(BeTrue())
|
|
Expect(resp.Choices[0].Text).To(ContainSubstring("five"))
|
|
|
|
stream, err := client.CreateCompletionStream(context.TODO(), openai.CompletionRequest{
|
|
Model: "rwkv_test", Prompt: "Count up to five: one, two, three, four,", Stream: true,
|
|
})
|
|
Expect(err).ToNot(HaveOccurred())
|
|
defer stream.Close()
|
|
|
|
tokens := 0
|
|
text := ""
|
|
for {
|
|
response, err := stream.Recv()
|
|
if errors.Is(err, io.EOF) {
|
|
break
|
|
}
|
|
|
|
Expect(err).ToNot(HaveOccurred())
|
|
text += response.Choices[0].Text
|
|
tokens++
|
|
}
|
|
Expect(text).ToNot(BeEmpty())
|
|
Expect(text).To(ContainSubstring("five"))
|
|
Expect(tokens).ToNot(Or(Equal(1), Equal(0)))
|
|
})
|
|
It("runs rwkv chat completion", func() {
|
|
if runtime.GOOS != "linux" {
|
|
Skip("test supported only on linux")
|
|
}
|
|
resp, err := client.CreateChatCompletion(context.TODO(),
|
|
openai.ChatCompletionRequest{Model: "rwkv_test", Messages: []openai.ChatCompletionMessage{{Content: "Can you count up to five?", Role: "user"}}})
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(len(resp.Choices) > 0).To(BeTrue())
|
|
Expect(resp.Choices[0].Message.Content).To(Or(ContainSubstring("Sure"), ContainSubstring("five")))
|
|
|
|
stream, err := client.CreateChatCompletionStream(context.TODO(), openai.ChatCompletionRequest{Model: "rwkv_test", Messages: []openai.ChatCompletionMessage{{Content: "Can you count up to five?", Role: "user"}}})
|
|
Expect(err).ToNot(HaveOccurred())
|
|
defer stream.Close()
|
|
|
|
tokens := 0
|
|
text := ""
|
|
for {
|
|
response, err := stream.Recv()
|
|
if errors.Is(err, io.EOF) {
|
|
break
|
|
}
|
|
|
|
Expect(err).ToNot(HaveOccurred())
|
|
text += response.Choices[0].Delta.Content
|
|
tokens++
|
|
}
|
|
Expect(text).ToNot(BeEmpty())
|
|
Expect(text).To(Or(ContainSubstring("Sure"), ContainSubstring("five")))
|
|
|
|
Expect(tokens).ToNot(Or(Equal(1), Equal(0)))
|
|
})
|
|
})
|
|
})
|
|
|
|
Context("Config file", func() {
|
|
BeforeEach(func() {
|
|
modelPath := os.Getenv("MODELS_PATH")
|
|
c, cancel = context.WithCancel(context.Background())
|
|
|
|
var err error
|
|
bcl, ml, applicationConfig, err = startup.Startup(
|
|
append(commonOpts,
|
|
config.WithContext(c),
|
|
config.WithModelPath(modelPath),
|
|
config.WithConfigFile(os.Getenv("CONFIG_FILE")))...,
|
|
)
|
|
Expect(err).ToNot(HaveOccurred())
|
|
app, err = App(bcl, ml, applicationConfig)
|
|
Expect(err).ToNot(HaveOccurred())
|
|
|
|
go app.Listen("127.0.0.1:9090")
|
|
|
|
defaultConfig := openai.DefaultConfig("")
|
|
defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
|
|
client2 = openaigo.NewClient("")
|
|
client2.BaseURL = defaultConfig.BaseURL
|
|
// Wait for API to be ready
|
|
client = openai.NewClientWithConfig(defaultConfig)
|
|
Eventually(func() error {
|
|
_, err := client.ListModels(context.TODO())
|
|
return err
|
|
}, "2m").ShouldNot(HaveOccurred())
|
|
})
|
|
AfterEach(func() {
|
|
cancel()
|
|
if app != nil {
|
|
err := app.Shutdown()
|
|
Expect(err).ToNot(HaveOccurred())
|
|
}
|
|
})
|
|
It("can generate chat completions from config file (list1)", func() {
|
|
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list1", Messages: []openai.ChatCompletionMessage{{Role: "user", Content: testPrompt}}})
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(len(resp.Choices)).To(Equal(1))
|
|
Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
|
|
})
|
|
It("can generate chat completions from config file (list2)", func() {
|
|
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list2", Messages: []openai.ChatCompletionMessage{{Role: "user", Content: testPrompt}}})
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(len(resp.Choices)).To(Equal(1))
|
|
Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
|
|
})
|
|
It("can generate edit completions from config file", func() {
|
|
request := openaigo.EditCreateRequestBody{
|
|
Model: "list2",
|
|
Instruction: "foo",
|
|
Input: "bar",
|
|
}
|
|
resp, err := client2.CreateEdit(context.Background(), request)
|
|
Expect(err).ToNot(HaveOccurred())
|
|
Expect(len(resp.Choices)).To(Equal(1))
|
|
Expect(resp.Choices[0].Text).ToNot(BeEmpty())
|
|
})
|
|
|
|
})
|
|
})
|