Genkit MCP

// Copyright 2025 Google LLC // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. package openai_test import ( "context" "encoding/base64" "io" "math" "net/http" "os" "strings" "testing" "github.com/firebase/genkit/go/ai" "github.com/firebase/genkit/go/genkit" compat_oai "github.com/firebase/genkit/go/plugins/compat_oai/openai" "github.com/openai/openai-go" ) func TestPlugin(t *testing.T) { apiKey := os.Getenv("OPENAI_API_KEY") if apiKey == "" { t.Skip("Skipping test: OPENAI_API_KEY environment variable not set") } ctx := context.Background() // Initialize the OpenAI plugin oai := &compat_oai.OpenAI{ APIKey: apiKey, } g := genkit.Init(context.Background(), genkit.WithDefaultModel("openai/gpt-4o-mini"), genkit.WithPlugins(oai), ) t.Log("genkit initialized") // Define a tool for calculating gablorkens gablorkenTool := genkit.DefineTool(g, "gablorken", "use when need to calculate a gablorken", func(ctx *ai.ToolContext, input struct { Value float64 Over float64 }, ) (float64, error) { return math.Pow(input.Value, input.Over), nil }, ) t.Log("openai plugin initialized") t.Run("embedder", func(t *testing.T) { // define embedder embedder := oai.Embedder(g, "text-embedding-3-small") res, err := genkit.Embed(ctx, g, ai.WithEmbedder(embedder), ai.WithTextDocs("yellow banana")) if err != nil { t.Fatal(err) } out := res.Embeddings[0].Embedding // There's not a whole lot we can test about the result. // Just do a few sanity checks. if len(out) < 100 { t.Errorf("embedding vector looks too short: len(out)=%d", len(out)) } var normSquared float32 for _, x := range out { normSquared += x * x } if normSquared < 0.9 || normSquared > 1.1 { t.Errorf("embedding vector not unit length: %f", normSquared) } }) t.Run("basic completion", func(t *testing.T) { t.Log("generating basic completion response") resp, err := genkit.Generate(ctx, g, ai.WithPrompt("What is the capital of France?"), ) if err != nil { t.Fatal("error generating basic completion response: ", err) } t.Logf("basic completion response: %+v", resp) out := resp.Message.Content[0].Text if !strings.Contains(strings.ToLower(out), "paris") { t.Errorf("got %q, expecting it to contain 'Paris'", out) } // Verify usage statistics are present if resp.Usage == nil || resp.Usage.TotalTokens == 0 { t.Error("Expected non-zero usage statistics") } }) t.Run("streaming", func(t *testing.T) { var streamedOutput string chunks := 0 final, err := genkit.Generate(ctx, g, ai.WithPrompt("Write a short paragraph about artificial intelligence."), ai.WithStreaming(func(ctx context.Context, chunk *ai.ModelResponseChunk) error { chunks++ for _, content := range chunk.Content { streamedOutput += content.Text } return nil })) if err != nil { t.Fatal(err) } // Verify streaming worked if chunks <= 1 { t.Error("Expected multiple chunks for streaming") } // Verify final output matches streamed content finalOutput := "" for _, content := range final.Message.Content { finalOutput += content.Text } if streamedOutput != finalOutput { t.Errorf("Streaming output doesn't match final output\nStreamed: %s\nFinal: %s", streamedOutput, finalOutput) } t.Logf("streaming response: %+v", finalOutput) }) t.Run("tool usage with basic completion", func(t *testing.T) { resp, err := genkit.Generate(ctx, g, ai.WithPrompt("what is a gablorken of 2 over 3.5?"), ai.WithTools(gablorkenTool)) if err != nil { t.Fatal(err) } out := resp.Message.Content[0].Text const want = "12.25" if !strings.Contains(out, want) { t.Errorf("got %q, expecting it to contain %q", out, want) } t.Logf("tool usage with basic completion response: %+v", out) }) t.Run("tool usage with streaming", func(t *testing.T) { var streamedOutput string chunks := 0 final, err := genkit.Generate(ctx, g, ai.WithPrompt("what is a gablorken of 2 over 3.5?"), ai.WithTools(gablorkenTool), ai.WithStreaming(func(ctx context.Context, chunk *ai.ModelResponseChunk) error { chunks++ for _, content := range chunk.Content { streamedOutput += content.Text } return nil })) if err != nil { t.Fatal(err) } // Verify streaming worked if chunks <= 1 { t.Error("Expected multiple chunks for streaming") } // Verify final output matches streamed content finalOutput := "" for _, content := range final.Message.Content { finalOutput += content.Text } if streamedOutput != finalOutput { t.Errorf("Streaming output doesn't match final output\nStreamed: %s\nFinal: %s", streamedOutput, finalOutput) } const want = "12.25" if !strings.Contains(finalOutput, want) { t.Errorf("got %q, expecting it to contain %q", finalOutput, want) } t.Logf("tool usage with streaming response: %+v", finalOutput) }) t.Run("system message", func(t *testing.T) { resp, err := genkit.Generate(ctx, g, ai.WithPrompt("What are you?"), ai.WithSystem("You are a helpful math tutor who loves numbers."), ) if err != nil { t.Fatal(err) } out := resp.Message.Content[0].Text if !strings.Contains(strings.ToLower(out), "math") { t.Errorf("got %q, expecting response to mention being a math tutor", out) } t.Logf("system message response: %+v", out) }) t.Run("generation config", func(t *testing.T) { // Create a config with specific parameters config := &openai.ChatCompletionNewParams{ Temperature: openai.Float(0.2), MaxCompletionTokens: openai.Int(50), TopP: openai.Float(0.5), Stop: openai.ChatCompletionNewParamsStopUnion{ OfStringArray: []string{".", "!", "?"}, }, } resp, err := genkit.Generate(ctx, g, ai.WithPrompt("Write a short sentence about artificial intelligence."), ai.WithConfig(config), ) if err != nil { t.Fatal(err) } out := resp.Message.Content[0].Text t.Logf("generation config response: %+v", out) }) t.Run("invalid config type", func(t *testing.T) { // Try to use a string as config instead of *ai.GenerationCommonConfig config := "not a config" _, err := genkit.Generate(ctx, g, ai.WithPrompt("Write a short sentence about artificial intelligence."), ai.WithConfig(config), ) if err == nil { t.Fatal("expected error for invalid config type") } if !strings.Contains(err.Error(), "unexpected config type: string") { t.Errorf("got error %q, want error containing 'unexpected config type: string'", err.Error()) } t.Logf("invalid config type error: %v", err) }) t.Run("check history", func(t *testing.T) { resp, err := genkit.Generate(ctx, g, ai.WithPrompt("Tell me a joke")) if err != nil { t.Fatal("got error: %w", err) } if resp.Request == nil { t.Fatal("unexpected nil pointer for request") } if len(resp.Request.Messages) == 0 { t.Fatal("expecting user messages in request") } resp, err = genkit.Generate(ctx, g, ai.WithMessages(resp.History()...), ai.WithPrompt("explain the joke that you just provided me")) if err != nil { t.Fatal("got error: %w", err) } userMsgCount := 0 for _, m := range resp.History() { if m.Role == ai.RoleUser { userMsgCount += 1 } } if userMsgCount != 2 { t.Fatalf("expecting 2 user messages, got: %d", userMsgCount) } }) t.Run("image", func(t *testing.T) { image, err := fetchImgAsBase64() if err != nil { t.Fatalf("failed to fetch image: %v", err) } resp, err := genkit.Generate(ctx, g, ai.WithModelName("openai/gpt-4.1-nano"), ai.WithMessages( ai.NewUserMessage( ai.NewMediaPart("image/jpeg", "data:image/jpeg;base64,"+image), ai.NewTextPart("What's in the image?."), ), ), ) if err != nil { t.Fatalf("failed to generate: %v", err) } if !strings.Contains(resp.Text(), "cat") { t.Fatalf("image detection failed, want: cat, got: %s", resp.Text()) } mediaMessages := 0 textMessages := 0 for _, m := range resp.Request.Messages { for _, p := range m.Content { if p.IsText() { textMessages += 1 } if p.IsMedia() { mediaMessages += 1 } } } if mediaMessages > 1 { t.Fatalf("unwanted media message, want: 1, got: %d", mediaMessages) } if textMessages > 1 { t.Fatalf("unwanted text message, want: 1, got %d", textMessages) } }) } func fetchImgAsBase64() (string, error) { // CC0 license image imgURL := "https://pd.w.org/2025/07/896686fbbcd9990c9.84605288-2048x1365.jpg" resp, err := http.Get(imgURL) if err != nil { return "", err } defer resp.Body.Close() if resp.StatusCode != http.StatusOK { return "", err } imageBytes, err := io.ReadAll(resp.Body) if err != nil { return "", err } base64string := base64.StdEncoding.EncodeToString(imageBytes) return base64string, nil }