diff --git a/README.md b/README.md
index f6b159a..4fdb45d 100644
--- a/README.md
+++ b/README.md
@@ -2,7 +2,7 @@
 
 [![Go Reference](https://pkg.go.dev/badge/github.com/philippgille/chromem-go.svg)](https://pkg.go.dev/github.com/philippgille/chromem-go)
 
-In-memory vector database for Go with Chroma-like interface.
+In-memory vector database for Go with Chroma-like interface and zero third-party dependencies.
 
 It's not a library to connect to the Chroma database. It's an in-memory database on its own, meant to enable retrieval augmented generation (RAG) applications in Go *without having to run a separate database*.  
 As such, the focus is not scale or performance, but simplicity.
@@ -74,6 +74,7 @@ Initially, only a minimal subset of all of Chroma's interface is implemented or
 
 ## Features
 
+- [X] Zero dependencies on third party libraries
 - Embedding creators:
   - [X] [OpenAI ada v2](https://platform.openai.com/docs/guides/embeddings/embedding-models) (default)
   - [X] Bring your own
diff --git a/embedding.go b/embedding.go
index 53619f5..bde1e84 100644
--- a/embedding.go
+++ b/embedding.go
@@ -1,14 +1,30 @@
 package chromem
 
 import (
+	"bytes"
 	"context"
+	"encoding/json"
+	"errors"
+	"fmt"
+	"io"
+	"net/http"
 	"os"
+)
 
-	"github.com/sashabaranov/go-openai"
+const (
+	baseURLOpenAI        = "https://api.openai.com/v1"
+	embeddingModelOpenAI = "text-embedding-ada-002"
 )
 
+type openAIResponse struct {
+	Data []struct {
+		Embedding []float32 `json:"embedding"`
+	} `json:"data"`
+}
+
 // CreateEmbeddingsDefault returns a function that creates embeddings for a document using using
 // OpenAI`s ada v2 model via their API.
+// The model supports a maximum document length of 8192 tokens.
 // The API key is read from the environment variable "OPENAI_API_KEY".
 func CreateEmbeddingsDefault() EmbeddingFunc {
 	apiKey := os.Getenv("OPENAI_API_KEY")
@@ -17,19 +33,65 @@ func CreateEmbeddingsDefault() EmbeddingFunc {
 
 // CreateEmbeddingsOpenAI returns a function that creates the embeddings for a document
 // using OpenAI`s ada v2 model via their API.
+// The model supports a maximum document length of 8192 tokens.
 func CreateEmbeddingsOpenAI(apiKey string) EmbeddingFunc {
-	client := openai.NewClient(apiKey)
+	// We don't set a default timeout here, although it's usually a good idea.
+	// In our case though, the library user can set the timeout on the context,
+	// and it might have to be a long timeout, depending on the document size.
+	client := &http.Client{}
+
 	return func(ctx context.Context, document string) ([]float32, error) {
-		req := openai.EmbeddingRequest{
-			Input: document,
-			Model: openai.AdaEmbeddingV2,
+		// Prepare the request body.
+		reqBody, err := json.Marshal(map[string]string{
+			"input": document,
+			"model": embeddingModelOpenAI,
+		})
+		if err != nil {
+			return nil, fmt.Errorf("couldn't marshal request body: %w", err)
 		}
 
-		res, err := client.CreateEmbeddings(ctx, req)
+		// Create the request. Creating it with context is important for a timeout
+		// to be possible, because the client is configured without a timeout.
+		req, err := http.NewRequestWithContext(ctx, "POST", baseURLOpenAI+"/embeddings", bytes.NewBuffer(reqBody))
 		if err != nil {
-			return nil, err
+			return nil, fmt.Errorf("couldn't create request: %w", err)
+		}
+		req.Header.Set("Content-Type", "application/json")
+		req.Header.Set("Authorization", "Bearer "+apiKey)
+
+		// Send the request.
+		resp, err := client.Do(req)
+		if err != nil {
+			return nil, fmt.Errorf("couldn't send request: %w", err)
+		}
+		defer resp.Body.Close()
+
+		// Check the response status.
+		if resp.StatusCode != http.StatusOK {
+			body, err := io.ReadAll(resp.Body)
+			if err != nil {
+				panic(err)
+			}
+			fmt.Println("========", string(body))
+			return nil, errors.New("error response from the OpenAI API: " + resp.Status)
+		}
+
+		// Read and decode the response body.
+		body, err := io.ReadAll(resp.Body)
+		if err != nil {
+			return nil, fmt.Errorf("couldn't read response body: %w", err)
+		}
+		var embeddingResponse openAIResponse
+		err = json.Unmarshal(body, &embeddingResponse)
+		if err != nil {
+			return nil, fmt.Errorf("couldn't unmarshal response body: %w", err)
+		}
+
+		// Check if the response contains embeddings.
+		if len(embeddingResponse.Data) == 0 || len(embeddingResponse.Data[0].Embedding) == 0 {
+			return nil, errors.New("no embeddings found in the response")
 		}
 
-		return res.Data[0].Embedding, nil
+		return embeddingResponse.Data[0].Embedding, nil
 	}
 }
diff --git a/example/go.mod b/example/go.mod
new file mode 100644
index 0000000..e9238e8
--- /dev/null
+++ b/example/go.mod
@@ -0,0 +1,10 @@
+module github.com/philippgille/chromem-go/example
+
+go 1.21
+
+require (
+	github.com/philippgille/chromem-go v0.0.0
+	github.com/sashabaranov/go-openai v1.17.9
+)
+
+replace github.com/philippgille/chromem-go => ./..
diff --git a/example/go.sum b/example/go.sum
new file mode 100644
index 0000000..45f7040
--- /dev/null
+++ b/example/go.sum
@@ -0,0 +1,2 @@
+github.com/sashabaranov/go-openai v1.17.9 h1:QEoBiGKWW68W79YIfXWEFZ7l5cEgZBV4/Ow3uy+5hNY=
+github.com/sashabaranov/go-openai v1.17.9/go.mod h1:lj5b/K+zjTSFxVLijLSTDZuP7adOgerWeFyZLUhAKRg=
diff --git a/go.mod b/go.mod
index 60b1bc8..c135bd3 100644
--- a/go.mod
+++ b/go.mod
@@ -1,5 +1,3 @@
 module github.com/philippgille/chromem-go
 
 go 1.21
-
-require github.com/sashabaranov/go-openai v1.17.9
diff --git a/go.sum b/go.sum
index 45f7040..e69de29 100644
--- a/go.sum
+++ b/go.sum
@@ -1,2 +0,0 @@
-github.com/sashabaranov/go-openai v1.17.9 h1:QEoBiGKWW68W79YIfXWEFZ7l5cEgZBV4/Ow3uy+5hNY=
-github.com/sashabaranov/go-openai v1.17.9/go.mod h1:lj5b/K+zjTSFxVLijLSTDZuP7adOgerWeFyZLUhAKRg=