Add semantic similarity score to TestEvalLLMs

.golangci.yml

@@ -0,0 +1,2 @@
+run:
+  timeout: 5m

README.md

@@ -19,7 +19,11 @@ Does your company depend on this project? [Contact me at [email protected]](mailt
 
 ## Usage
 
-This test will only run with `go test -run TestEval ./...` and otherwise be skipped:
+Evals will only run with `go test -run TestEval ./...` and otherwise be skipped.
+
+### Simple example
+
+Eval a mocked LLM, construct a sample, score it with a lexical similarity scorer, and log the result.
 
 ```go
 package examples_test
@@ -66,3 +70,138 @@ func (l *powerfulLLM) Prompt(request string) string {
 	return l.response
 }
 ```
+
+### Advanced example
+
+This eval uses real LLMs (OpenAI GPT4o mini, Google Gemini 1.5 Flash, Anthropic 3.5 Haiku)
+and compares the response to an expected response using both lexical similarity (with Levenshtein distance)
+and semantic similarity (with an OpenAI embedding model and cosine similarity comparison).
+
+```go
+package examples_test
+
+import (
+	"context"
+	"errors"
+	"fmt"
+	"strings"
+	"testing"
+
+	"github.com/anthropics/anthropic-sdk-go"
+	"github.com/google/generative-ai-go/genai"
+	"github.com/openai/openai-go"
+	"github.com/openai/openai-go/shared"
+	"maragu.dev/env"
+
+	"maragu.dev/llm"
+	"maragu.dev/llm/eval"
+)
+
+// TestEvalLLMs evaluates different LLMs with the same prompts.
+func TestEvalLLMs(t *testing.T) {
+	_ = env.Load("../../.env.test.local")
+
+	tests := []struct {
+		name     string
+		prompt   func(prompt string) string
+		expected string
+	}{
+		{
+			name:     "gpt-4o-mini",
+			prompt:   gpt4oMini,
+			expected: "Hello! How can I assist you today?",
+		},
+		{
+			name:     "gemini-1.5-flash",
+			prompt:   gemini15Flash,
+			expected: "Hi there! How can I help you today?",
+		},
+		{
+			name:     "claude-3.5-haiku",
+			prompt:   claude35Haiku,
+			expected: "Hello! How are you doing today? Is there anything I can help you with?",
+		},
+	}
+
+	for _, test := range tests {
+		eval.Run(t, test.name, func(e *eval.E) {
+			input := "Hi!"
+			output := test.prompt(input)
+
+			sample := eval.Sample{
+				Input:    input,
+				Output:   output,
+				Expected: test.expected,
+			}
+
+			result := e.Score(sample, eval.LexicalSimilarityScorer(eval.LevenshteinDistance))
+			e.Log(sample, result)
+
+			result = e.Score(sample, eval.SemanticSimilarityScorer(&embeddingGetter{}, eval.CosineSimilarity))
+			e.Log(sample, result)
+		})
+	}
+}
+
+func gpt4oMini(prompt string) string {
+	client := llm.NewOpenAIClient(llm.NewOpenAIClientOptions{Key: env.GetStringOrDefault("OPENAI_KEY", "")})
+	res, err := client.Client.Chat.Completions.New(context.Background(), openai.ChatCompletionNewParams{
+		Messages: openai.F([]openai.ChatCompletionMessageParamUnion{
+			openai.UserMessage(prompt),
+		}),
+		Model:       openai.F(openai.ChatModelGPT4oMini),
+		Temperature: openai.F(0.0),
+	})
+	if err != nil {
+		panic(err)
+	}
+	return res.Choices[0].Message.Content
+}
+
+func gemini15Flash(prompt string) string {
+	client := llm.NewGoogleClient(llm.NewGoogleClientOptions{Key: env.GetStringOrDefault("GOOGLE_KEY", "")})
+	model := client.Client.GenerativeModel("models/gemini-1.5-flash-latest")
+	var temperature float32 = 0
+	model.Temperature = &temperature
+	res, err := model.GenerateContent(context.Background(), genai.Text(prompt))
+	if err != nil {
+		panic(err)
+	}
+	return strings.TrimSpace(fmt.Sprint(res.Candidates[0].Content.Parts[0]))
+}
+
+func claude35Haiku(prompt string) string {
+	client := llm.NewAnthropicClient(llm.NewAnthropicClientOptions{Key: env.GetStringOrDefault("ANTHROPIC_KEY", "")})
+	res, err := client.Client.Messages.New(context.Background(), anthropic.MessageNewParams{
+		Messages: anthropic.F([]anthropic.MessageParam{
+			anthropic.NewUserMessage(anthropic.NewTextBlock(prompt)),
+		}),
+		Model:       anthropic.F(anthropic.ModelClaude3_5HaikuLatest),
+		MaxTokens:   anthropic.F(int64(1024)),
+		Temperature: anthropic.F(0.0),
+	})
+	if err != nil {
+		panic(err)
+	}
+	return fmt.Sprint(res.Content[0].Text)
+}
+
+type embeddingGetter struct{}
+
+func (e *embeddingGetter) GetEmbedding(v string) ([]float64, error) {
+	client := llm.NewOpenAIClient(llm.NewOpenAIClientOptions{Key: env.GetStringOrDefault("OPENAI_KEY", "")})
+	res, err := client.Client.Embeddings.New(context.Background(), openai.EmbeddingNewParams{
+		Input:          openai.F[openai.EmbeddingNewParamsInputUnion](shared.UnionString(v)),
+		Model:          openai.F(openai.EmbeddingModelTextEmbedding3Small),
+		EncodingFormat: openai.F(openai.EmbeddingNewParamsEncodingFormatFloat),
+		Dimensions:     openai.F(int64(128)),
+	})
+	if err != nil {
+		return nil, err
+	}
+	if len(res.Data) == 0 {
+		return nil, errors.New("no embeddings returned")
+	}
+	return res.Data[0].Embedding, nil
+}
+```

go.mod

@@ -9,7 +9,7 @@ require (
 	github.com/openai/openai-go v0.1.0-alpha.46
 	google.golang.org/api v0.217.0
 	maragu.dev/env v0.2.0
-	maragu.dev/evals v0.0.0-20250114114008-6c73fea1551c
+	maragu.dev/evals v0.0.0-20250121095818-455e49387b21
 	maragu.dev/is v0.2.0
 )
 

go.sum

@@ -128,8 +128,8 @@ maragu.dev/env v0.2.0 h1:nQKitDEB65ArZsh6E7vxzodOqY9bxEVFdBg+tskS1ys=
 maragu.dev/env v0.2.0/go.mod h1:t5CCbaEnjCM5mewiAVVzTS4N+oXTus2+SRnzKQbQVME=
 maragu.dev/errors v0.3.0 h1:huI+n+ddMfVgQFD+cEqIPaozUlfz3TkfgpkssNip5G0=
 maragu.dev/errors v0.3.0/go.mod h1:cygLiyNnq4ofF3whYscilo2ecUADCaUQXwvwFrMOhmM=
-maragu.dev/evals v0.0.0-20250114114008-6c73fea1551c h1:huPj1S5RhqgpbBAd3aCLfdVie3ZsU8Du7kepL2ZtDUQ=
-maragu.dev/evals v0.0.0-20250114114008-6c73fea1551c/go.mod h1:+2Y3dYZ6oANM+cL88kFxaPD1H7rq3FXOrI3NOeNKaZ8=
+maragu.dev/evals v0.0.0-20250121095818-455e49387b21 h1:Eg2DvonBz4eOPIhN+/aL1BXQAlNla4o+aBY+03e/6mA=
+maragu.dev/evals v0.0.0-20250121095818-455e49387b21/go.mod h1:uLfBl7/FhUJULS4PjmpMdNG+joMRYAxgMJbzGWhQhWE=
 maragu.dev/is v0.2.0 h1:poeuVEA5GG3vrDpGmzo2KjWtIMZmqUyvGnOB0/pemig=
 maragu.dev/is v0.2.0/go.mod h1:bviaM5S0fBshCw7wuumFGTju/izopZ/Yvq4g7Klc7y8=
 maragu.dev/migrate v0.6.0 h1:gJLAIVaRh9z9sN55Q2sWwScpEH+JsT6N0L1DnzedXFE=

internal/examples/hi_test.go

@@ -2,13 +2,15 @@ package examples_test
 
 import (
 	"context"
+	"errors"
 	"fmt"
 	"strings"
 	"testing"
 
 	"github.com/anthropics/anthropic-sdk-go"
 	"github.com/google/generative-ai-go/genai"
 	"github.com/openai/openai-go"
+	"github.com/openai/openai-go/shared"
 	"maragu.dev/env"
 
 	"maragu.dev/llm"
@@ -53,7 +55,9 @@ func TestEvalLLMs(t *testing.T) {
 			}
 
 			result := e.Score(sample, eval.LexicalSimilarityScorer(eval.LevenshteinDistance))
+			e.Log(sample, result)
 
+			result = e.Score(sample, eval.SemanticSimilarityScorer(&embeddingGetter{}, eval.CosineSimilarity))
 			e.Log(sample, result)
 		})
 	}
@@ -101,3 +105,22 @@ func claude35Haiku(prompt string) string {
 	}
 	return fmt.Sprint(res.Content[0].Text)
 }
+
+type embeddingGetter struct{}
+
+func (e *embeddingGetter) GetEmbedding(v string) ([]float64, error) {
+	client := llm.NewOpenAIClient(llm.NewOpenAIClientOptions{Key: env.GetStringOrDefault("OPENAI_KEY", "")})
+	res, err := client.Client.Embeddings.New(context.Background(), openai.EmbeddingNewParams{
+		Input:          openai.F[openai.EmbeddingNewParamsInputUnion](shared.UnionString(v)),
+		Model:          openai.F(openai.EmbeddingModelTextEmbedding3Small),
+		EncodingFormat: openai.F(openai.EmbeddingNewParamsEncodingFormatFloat),
+		Dimensions:     openai.F(int64(128)),
+	})
+	if err != nil {
+		return nil, err
+	}
+	if len(res.Data) == 0 {
+		return nil, errors.New("no embeddings returned")
+	}
+	return res.Data[0].Embedding, nil
+}