package api_test import ( "bytes" "context" "embed" "encoding/json" "errors" "fmt" "io" "io/ioutil" "net/http" "os" "path/filepath" "runtime" . "github.com/go-skynet/LocalAI/api" "github.com/go-skynet/LocalAI/api/options" "github.com/go-skynet/LocalAI/pkg/gallery" "github.com/go-skynet/LocalAI/pkg/model" "github.com/go-skynet/LocalAI/pkg/utils" "github.com/gofiber/fiber/v2" . "github.com/onsi/ginkgo/v2" . "github.com/onsi/gomega" "gopkg.in/yaml.v3" openaigo "github.com/otiai10/openaigo" "github.com/sashabaranov/go-openai" "github.com/sashabaranov/go-openai/jsonschema" ) type modelApplyRequest struct { ID string `json:"id"` URL string `json:"url"` Name string `json:"name"` Overrides map[string]string `json:"overrides"` } func getModelStatus(url string) (response map[string]interface{}) { // Create the HTTP request resp, err := http.Get(url) if err != nil { fmt.Println("Error creating request:", err) return } defer resp.Body.Close() body, err := ioutil.ReadAll(resp.Body) if err != nil { fmt.Println("Error reading response body:", err) return } // Unmarshal the response into a map[string]interface{} err = json.Unmarshal(body, &response) if err != nil { fmt.Println("Error unmarshaling JSON response:", err) return } return } func getModels(url string) (response []gallery.GalleryModel) { utils.GetURI(url, func(url string, i []byte) error { // Unmarshal YAML data into a struct return json.Unmarshal(i, &response) }) return } func postModelApplyRequest(url string, request modelApplyRequest) (response map[string]interface{}) { //url := "http://localhost:AI/models/apply" // Create the request payload payload, err := json.Marshal(request) if err != nil { fmt.Println("Error marshaling JSON:", err) return } // Create the HTTP request req, err := http.NewRequest("POST", url, bytes.NewBuffer(payload)) if err != nil { fmt.Println("Error creating request:", err) return } req.Header.Set("Content-Type", "application/json") // Make the request client := &http.Client{} resp, err := client.Do(req) if err != nil { fmt.Println("Error making request:", err) return } defer resp.Body.Close() body, err := ioutil.ReadAll(resp.Body) if err != nil { fmt.Println("Error reading response body:", err) return } // Unmarshal the response into a map[string]interface{} err = json.Unmarshal(body, &response) if err != nil { fmt.Println("Error unmarshaling JSON response:", err) return } return } //go:embed backend-assets/* var backendAssets embed.FS var _ = Describe("API test", func() { var app *fiber.App var modelLoader *model.ModelLoader var client *openai.Client var client2 *openaigo.Client var c context.Context var cancel context.CancelFunc var tmpdir string commonOpts := []options.AppOption{ options.WithDebug(true), options.WithDisableMessage(true), } Context("API with ephemeral models", func() { BeforeEach(func() { var err error tmpdir, err = os.MkdirTemp("", "") Expect(err).ToNot(HaveOccurred()) modelLoader = model.NewModelLoader(tmpdir) c, cancel = context.WithCancel(context.Background()) g := []gallery.GalleryModel{ { Name: "bert", URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml", }, { Name: "bert2", URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml", Overrides: map[string]interface{}{"foo": "bar"}, AdditionalFiles: []gallery.File{{Filename: "foo.yaml", URI: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml"}}, }, } out, err := yaml.Marshal(g) Expect(err).ToNot(HaveOccurred()) err = ioutil.WriteFile(filepath.Join(tmpdir, "gallery_simple.yaml"), out, 0644) Expect(err).ToNot(HaveOccurred()) galleries := []gallery.Gallery{ { Name: "test", URL: "file://" + filepath.Join(tmpdir, "gallery_simple.yaml"), }, } app, err = App( append(commonOpts, options.WithContext(c), options.WithGalleries(galleries), options.WithModelLoader(modelLoader), options.WithBackendAssets(backendAssets), options.WithBackendAssetsOutput(tmpdir))...) 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() app.Shutdown() os.RemoveAll(tmpdir) }) Context("Applying models", func() { It("applies models from a gallery", func() { models := getModels("http://127.0.0.1:9090/models/available") Expect(len(models)).To(Equal(2), fmt.Sprint(models)) Expect(models[0].Installed).To(BeFalse(), fmt.Sprint(models)) Expect(models[1].Installed).To(BeFalse(), fmt.Sprint(models)) response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{ ID: "test@bert2", }) Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response)) uuid := response["uuid"].(string) resp := map[string]interface{}{} Eventually(func() bool { response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid) fmt.Println(response) resp = response return response["processed"].(bool) }, "360s", "10s").Should(Equal(true)) Expect(resp["message"]).ToNot(ContainSubstring("error")) dat, err := os.ReadFile(filepath.Join(tmpdir, "bert2.yaml")) Expect(err).ToNot(HaveOccurred()) _, err = os.ReadFile(filepath.Join(tmpdir, "foo.yaml")) Expect(err).ToNot(HaveOccurred()) content := map[string]interface{}{} err = yaml.Unmarshal(dat, &content) Expect(err).ToNot(HaveOccurred()) Expect(content["backend"]).To(Equal("bert-embeddings")) Expect(content["foo"]).To(Equal("bar")) models = getModels("http://127.0.0.1:9090/models/available") Expect(len(models)).To(Equal(2), fmt.Sprint(models)) Expect(models[0].Name).To(Or(Equal("bert"), Equal("bert2"))) Expect(models[1].Name).To(Or(Equal("bert"), Equal("bert2"))) for _, m := range models { if m.Name == "bert2" { Expect(m.Installed).To(BeTrue()) } else { Expect(m.Installed).To(BeFalse()) } } }) It("overrides models", func() { response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{ URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml", Name: "bert", Overrides: map[string]string{ "backend": "llama", }, }) 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) return response["processed"].(bool) }, "360s", "10s").Should(Equal(true)) dat, err := os.ReadFile(filepath.Join(tmpdir, "bert.yaml")) Expect(err).ToNot(HaveOccurred()) content := map[string]interface{}{} err = yaml.Unmarshal(dat, &content) Expect(err).ToNot(HaveOccurred()) Expect(content["backend"]).To(Equal("llama")) }) It("apply models without overrides", func() { response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{ URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml", Name: "bert", Overrides: map[string]string{}, }) 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) return response["processed"].(bool) }, "360s", "10s").Should(Equal(true)) dat, err := os.ReadFile(filepath.Join(tmpdir, "bert.yaml")) Expect(err).ToNot(HaveOccurred()) content := map[string]interface{}{} err = yaml.Unmarshal(dat, &content) Expect(err).ToNot(HaveOccurred()) Expect(content["backend"]).To(Equal("bert-embeddings")) }) It("runs openllama", Label("llama"), func() { if runtime.GOOS != "linux" { Skip("test supported only on linux") } response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{ URL: "github:go-skynet/model-gallery/openllama_3b.yaml", Name: "openllama_3b", Overrides: map[string]string{"backend": "llama-grammar"}, }) 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) return response["processed"].(bool) }, "360s", "10s").Should(Equal(true)) By("testing completion") resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "openllama_3b", Prompt: "Count up to five: one, two, three, four, "}) Expect(err).ToNot(HaveOccurred()) Expect(len(resp.Choices)).To(Equal(1)) Expect(resp.Choices[0].Text).To(ContainSubstring("five")) By("testing functions") resp2, err := client.CreateChatCompletion( context.TODO(), openai.ChatCompletionRequest{ Model: "openllama_3b", Messages: []openai.ChatCompletionMessage{ { Role: "user", Content: "What is the weather like in San Francisco (celsius)?", }, }, Functions: []openai.FunctionDefinition{ openai.FunctionDefinition{ Name: "get_current_weather", Description: "Get the current weather", Parameters: jsonschema.Definition{ Type: jsonschema.Object, Properties: map[string]jsonschema.Definition{ "location": { Type: jsonschema.String, Description: "The city and state, e.g. San Francisco, CA", }, "unit": { Type: jsonschema.String, Enum: []string{"celcius", "fahrenheit"}, }, }, Required: []string{"location"}, }, }, }, }) Expect(err).ToNot(HaveOccurred()) Expect(len(resp2.Choices)).To(Equal(1)) Expect(resp2.Choices[0].Message.FunctionCall).ToNot(BeNil()) Expect(resp2.Choices[0].Message.FunctionCall.Name).To(Equal("get_current_weather"), resp2.Choices[0].Message.FunctionCall.Name) var res map[string]string err = json.Unmarshal([]byte(resp2.Choices[0].Message.FunctionCall.Arguments), &res) Expect(err).ToNot(HaveOccurred()) Expect(res["location"]).To(Equal("San Francisco"), fmt.Sprint(res)) Expect(res["unit"]).To(Equal("celcius"), fmt.Sprint(res)) Expect(string(resp2.Choices[0].FinishReason)).To(Equal("function_call"), fmt.Sprint(resp2.Choices[0].FinishReason)) }) It("runs gpt4all", Label("gpt4all"), func() { if runtime.GOOS != "linux" { Skip("test supported only on linux") } response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{ URL: "github:go-skynet/model-gallery/gpt4all-j.yaml", Name: "gpt4all-j", Overrides: map[string]string{}, }) 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) return response["processed"].(bool) }, "360s", "10s").Should(Equal(true)) 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("External gRPCs", func() { BeforeEach(func() { modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH")) c, cancel = context.WithCancel(context.Background()) app, err := App( append(commonOpts, options.WithContext(c), options.WithAudioDir(tmpdir), options.WithImageDir(tmpdir), options.WithModelLoader(modelLoader), options.WithBackendAssets(backendAssets), options.WithExternalBackend("huggingface", os.Getenv("HUGGINGFACE_GRPC")), options.WithBackendAssetsOutput(tmpdir))..., ) Expect(err).ToNot(HaveOccurred()) go app.Listen("127.0.0.1:9090") defaultConfig := openai.DefaultConfig("") defaultConfig.BaseURL = "http://127.0.0.1:9090/v1" // 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() app.Shutdown() os.RemoveAll(tmpdir) }) It("calculate embeddings with huggingface", 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("Model gallery", func() { BeforeEach(func() { var err error tmpdir, err = os.MkdirTemp("", "") Expect(err).ToNot(HaveOccurred()) modelLoader = model.NewModelLoader(tmpdir) c, cancel = context.WithCancel(context.Background()) galleries := []gallery.Gallery{ { Name: "model-gallery", URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/index.yaml", }, } app, err = App( append(commonOpts, options.WithContext(c), options.WithAudioDir(tmpdir), options.WithImageDir(tmpdir), options.WithGalleries(galleries), options.WithModelLoader(modelLoader), options.WithBackendAssets(backendAssets), options.WithBackendAssetsOutput(tmpdir))..., ) 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() app.Shutdown() os.RemoveAll(tmpdir) }) 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", }) 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() { modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH")) c, cancel = context.WithCancel(context.Background()) var err error app, err = App( append(commonOpts, options.WithContext(c), options.WithModelLoader(modelLoader))...) 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() app.Shutdown() }) It("returns the models list", func() { models, err := client.ListModels(context.TODO()) Expect(err).ToNot(HaveOccurred()) Expect(len(models.Models)).To(Equal(11)) }) It("can generate completions", func() { resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "testmodel", Prompt: "abcdedfghikl"}) 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: "abcdedfghikl"}}}) 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: "abcdedfghikl"}) 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: "abcdedfghikl"}}}) 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) _, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "foomodel", Prompt: "abcdedfghikl"}) 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()) 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("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() { modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH")) c, cancel = context.WithCancel(context.Background()) var err error app, err = App( append(commonOpts, options.WithContext(c), options.WithModelLoader(modelLoader), options.WithConfigFile(os.Getenv("CONFIG_FILE")))..., ) 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() app.Shutdown() }) It("can generate chat completions from config file", func() { models, err := client.ListModels(context.TODO()) Expect(err).ToNot(HaveOccurred()) Expect(len(models.Models)).To(Equal(13)) }) It("can generate chat completions from config file", func() { resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list1", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}}) 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", func() { resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list2", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}}) 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()) }) }) })