Migrate From Old Completions + Embedding Endpoint (#28)

* migrate away from deprecated OpenAI endpoints

Signed-off-by: Oleg <97077423+RobotSail@users.noreply.github.com>

* test embedding correctness

Signed-off-by: Oleg <97077423+RobotSail@users.noreply.github.com>

README.md

@@ -27,10 +27,11 @@ func main() {
 	ctx := context.Background()
 
 	req := gogpt.CompletionRequest{
+		Model: "ada",
 		MaxTokens: 5,
 		Prompt:    "Lorem ipsum",
 	}
-	resp, err := c.CreateCompletion(ctx, "ada", req)
+	resp, err := c.CreateCompletion(ctx, req)
 	if err != nil {
 		return
 	}

api_test.go

@@ -1,7 +1,9 @@
 package gogpt
 
 import (
+	"bytes"
 	"context"
+	"encoding/json"
 	"io/ioutil"
 	"testing"
 )
@@ -36,9 +38,12 @@ func TestAPI(t *testing.T) {
 		}
 	} // else skip
 
-	req := CompletionRequest{MaxTokens: 5}
+	req := CompletionRequest{
+		MaxTokens: 5,
+		Model:     "ada",
+	}
 	req.Prompt = "Lorem ipsum"
-	_, err = c.CreateCompletion(ctx, "ada", req)
+	_, err = c.CreateCompletion(ctx, req)
 	if err != nil {
 		t.Fatalf("CreateCompletion error: %v", err)
 	}
@@ -57,9 +62,49 @@ func TestAPI(t *testing.T) {
 			"The food was delicious and the waiter",
 			"Other examples of embedding request",
 		},
+		Model: AdaSearchQuery,
 	}
-	_, err = c.CreateEmbeddings(ctx, embeddingReq, AdaSearchQuery)
+	_, err = c.CreateEmbeddings(ctx, embeddingReq)
 	if err != nil {
 		t.Fatalf("Embedding error: %v", err)
 	}
 }
+
+func TestEmbedding(t *testing.T) {
+	embeddedModels := []EmbeddingModel{
+		AdaSimilarity,
+		BabbageSimilarity,
+		CurieSimilarity,
+		DavinciSimilarity,
+		AdaSearchDocument,
+		AdaSearchQuery,
+		BabbageSearchDocument,
+		BabbageSearchQuery,
+		CurieSearchDocument,
+		CurieSearchQuery,
+		DavinciSearchDocument,
+		DavinciSearchQuery,
+		AdaCodeSearchCode,
+		AdaCodeSearchText,
+		BabbageCodeSearchCode,
+		BabbageCodeSearchText,
+	}
+	for _, model := range embeddedModels {
+		embeddingReq := EmbeddingRequest{
+			Input: []string{
+				"The food was delicious and the waiter",
+				"Other examples of embedding request",
+			},
+			Model: model,
+		}
+		// marshal embeddingReq to JSON and confirm that the model field equals
+		// the AdaSearchQuery type
+		marshaled, err := json.Marshal(embeddingReq)
+		if err != nil {
+			t.Fatalf("Could not marshal embedding request: %v", err)
+		}
+		if !bytes.Contains(marshaled, []byte(`"model":"`+model.String()+`"`)) {
+			t.Fatalf("Expected embedding request to contain model field")
+		}
+	}
+}

completion.go

@@ -4,13 +4,12 @@ import (
 	"bytes"
 	"context"
 	"encoding/json"
-	"fmt"
 	"net/http"
 )
 
 // CompletionRequest represents a request structure for completion API
 type CompletionRequest struct {
-	Model            *string        `json:"model,omitempty"`
+	Model            string         `json:"model"`
 	Prompt           string         `json:"prompt,omitempty"`
 	MaxTokens        int            `json:"max_tokens,omitempty"`
 	Temperature      float32        `json:"temperature,omitempty"`
@@ -60,29 +59,12 @@ type CompletionResponse struct {
 	Usage   CompletionUsage    `json:"usage"`
 }
 
-// CreateCompletion — API call to create a completion. This is the main endpoint of the API. Returns new text as well as, if requested, the probabilities over each alternative token at each position.
+// CreateCompletion — API call to create a completion. This is the main endpoint of the API. Returns new text as well
-func (c *Client) CreateCompletion(ctx context.Context, engineID string, request CompletionRequest) (response CompletionResponse, err error) {
+// as, if requested, the probabilities over each alternative token at each position.
-	var reqBytes []byte
+//
-	reqBytes, err = json.Marshal(request)
+// If using a fine-tuned model, simply provide the model's ID in the CompletionRequest object,
-	if err != nil {
+// and the server will use the model's parameters to generate the completion.
-		return
+func (c *Client) CreateCompletion(ctx context.Context, request CompletionRequest) (response CompletionResponse, err error) {
-	}
-
-	urlSuffix := fmt.Sprintf("/engines/%s/completions", engineID)
-	req, err := http.NewRequest("POST", c.fullURL(urlSuffix), bytes.NewBuffer(reqBytes))
-	if err != nil {
-		return
-	}
-
-	req = req.WithContext(ctx)
-	err = c.sendRequest(req, &response)
-	return
-}
-
-// CreateCompletionWithFineTunedModel - API call to create a completion with a fine tuned model
-// See https://beta.openai.com/docs/guides/fine-tuning/use-a-fine-tuned-model
-// In this case, the model is specified in the CompletionRequest object.
-func (c *Client) CreateCompletionWithFineTunedModel(ctx context.Context, request CompletionRequest) (response CompletionResponse, err error) {
 	var reqBytes []byte
 	reqBytes, err = json.Marshal(request)
 	if err != nil {

embeddings.go

@@ -4,7 +4,6 @@ import (
 	"bytes"
 	"context"
 	"encoding/json"
-	"fmt"
 	"net/http"
 )
 
@@ -120,18 +119,23 @@ type EmbeddingRequest struct {
 	// E.g.
 	//	"The food was delicious and the waiter..."
 	Input []string `json:"input"`
+	// ID of the model to use. You can use the List models API to see all of your available models,
+	// or see our Model overview for descriptions of them.
+	Model EmbeddingModel `json:"model"`
+	// A unique identifier representing your end-user, which will help OpenAI to monitor and detect abuse.
+	User string `json:"user"`
 }
 
 // CreateEmbeddings returns an EmbeddingResponse which will contain an Embedding for every item in |request.Input|.
 // https://beta.openai.com/docs/api-reference/embeddings/create
-func (c *Client) CreateEmbeddings(ctx context.Context, request EmbeddingRequest, model EmbeddingModel) (resp EmbeddingResponse, err error) {
+func (c *Client) CreateEmbeddings(ctx context.Context, request EmbeddingRequest) (resp EmbeddingResponse, err error) {
 	var reqBytes []byte
 	reqBytes, err = json.Marshal(request)
 	if err != nil {
 		return
 	}
 
-	urlSuffix := fmt.Sprintf("/engines/%s/embeddings", model)
+	urlSuffix := "/embeddings"
 	req, err := http.NewRequest(http.MethodPost, c.fullURL(urlSuffix), bytes.NewBuffer(reqBytes))
 	if err != nil {
 		return

search.go

@@ -18,10 +18,10 @@ import (
 type SearchRequest struct {
 	Query          string   `json:"query"`
 	Documents      []string `json:"documents"`            // 1*
-	FileID         string   `json:"file"`       // 1*
+	FileID         string   `json:"file,omitempty"`       // 1*
-	MaxRerank      int      `json:"max_rerank"` // 2*
+	MaxRerank      int      `json:"max_rerank,omitempty"` // 2*
-	ReturnMetadata bool     `json:"return_metadata"`
+	ReturnMetadata bool     `json:"return_metadata,omitempty"`
-	User           string   `json:"user"`
+	User           string   `json:"user,omitempty"`
 }
 
 // SearchResult represents single result from search API