* Allow raw tokens to be used as embedding input * fix linting issues (lines too long) * add endpoint test for embedding from tokens * remove redundant comments * fix comment to match new param name * change interface to any * Rename methods and implement convert for base req * add comments to CreateEmbeddings * update tests * shorten line length * rename parameter
119 lines
3.5 KiB
Go
119 lines
3.5 KiB
Go
package openai_test
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import (
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. "github.com/sashabaranov/go-openai"
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"github.com/sashabaranov/go-openai/internal/test/checks"
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"bytes"
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"context"
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"encoding/json"
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"fmt"
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"net/http"
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"testing"
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)
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func TestEmbedding(t *testing.T) {
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embeddedModels := []EmbeddingModel{
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AdaSimilarity,
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BabbageSimilarity,
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CurieSimilarity,
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DavinciSimilarity,
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AdaSearchDocument,
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AdaSearchQuery,
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BabbageSearchDocument,
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BabbageSearchQuery,
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CurieSearchDocument,
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CurieSearchQuery,
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DavinciSearchDocument,
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DavinciSearchQuery,
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AdaCodeSearchCode,
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AdaCodeSearchText,
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BabbageCodeSearchCode,
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BabbageCodeSearchText,
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}
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for _, model := range embeddedModels {
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// test embedding request with strings (simple embedding request)
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embeddingReq := EmbeddingRequest{
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Input: []string{
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"The food was delicious and the waiter",
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"Other examples of embedding request",
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},
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Model: model,
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}
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// marshal embeddingReq to JSON and confirm that the model field equals
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// the AdaSearchQuery type
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marshaled, err := json.Marshal(embeddingReq)
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checks.NoError(t, err, "Could not marshal embedding request")
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if !bytes.Contains(marshaled, []byte(`"model":"`+model.String()+`"`)) {
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t.Fatalf("Expected embedding request to contain model field")
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}
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// test embedding request with strings
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embeddingReqStrings := EmbeddingRequestStrings{
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Input: []string{
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"The food was delicious and the waiter",
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"Other examples of embedding request",
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},
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Model: model,
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}
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marshaled, err = json.Marshal(embeddingReqStrings)
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checks.NoError(t, err, "Could not marshal embedding request")
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if !bytes.Contains(marshaled, []byte(`"model":"`+model.String()+`"`)) {
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t.Fatalf("Expected embedding request to contain model field")
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}
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// test embedding request with tokens
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embeddingReqTokens := EmbeddingRequestTokens{
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Input: [][]int{
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{464, 2057, 373, 12625, 290, 262, 46612},
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{6395, 6096, 286, 11525, 12083, 2581},
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},
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Model: model,
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}
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marshaled, err = json.Marshal(embeddingReqTokens)
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checks.NoError(t, err, "Could not marshal embedding request")
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if !bytes.Contains(marshaled, []byte(`"model":"`+model.String()+`"`)) {
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t.Fatalf("Expected embedding request to contain model field")
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}
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}
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}
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func TestEmbeddingModel(t *testing.T) {
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var em EmbeddingModel
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err := em.UnmarshalText([]byte("text-similarity-ada-001"))
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checks.NoError(t, err, "Could not marshal embedding model")
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if em != AdaSimilarity {
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t.Errorf("Model is not equal to AdaSimilarity")
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}
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err = em.UnmarshalText([]byte("some-non-existent-model"))
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checks.NoError(t, err, "Could not marshal embedding model")
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if em != Unknown {
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t.Errorf("Model is not equal to Unknown")
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}
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}
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func TestEmbeddingEndpoint(t *testing.T) {
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client, server, teardown := setupOpenAITestServer()
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defer teardown()
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server.RegisterHandler(
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"/v1/embeddings",
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func(w http.ResponseWriter, r *http.Request) {
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resBytes, _ := json.Marshal(EmbeddingResponse{})
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fmt.Fprintln(w, string(resBytes))
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},
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)
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// test create embeddings with strings (simple embedding request)
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_, err := client.CreateEmbeddings(context.Background(), EmbeddingRequest{})
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checks.NoError(t, err, "CreateEmbeddings error")
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// test create embeddings with strings
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_, err = client.CreateEmbeddings(context.Background(), EmbeddingRequestStrings{})
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checks.NoError(t, err, "CreateEmbeddings strings error")
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// test create embeddings with tokens
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_, err = client.CreateEmbeddings(context.Background(), EmbeddingRequestTokens{})
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checks.NoError(t, err, "CreateEmbeddings tokens error")
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}
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