Embedding

Parameters

Parameter	Type	Required	Description
`model`	`string`	Yes	Model ID, e.g. `text-embedding-ada-002`.
`input`	`string\|array`	Yes	Text to embed. Single string or array of strings.
`encoding_format`	`string`	No	`float` (default) or `base64`.
`dimensions`	`integer`	No	Embedding dimensions (model-dependent).

Examples

curl -X POST https://silkdock.ai/v1/embeddings \-H "Authorization: Bearer $SILKDOCK_API_KEY" \-H "Content-Type: application/json" \-d '{  "model": "text-embedding-ada-002",  "input": ["Hello world", "Goodbye world"]}'

curl -X POST https://silkdock.ai/v1/embeddings ^-H "Authorization: Bearer %SILKDOCK_API_KEY%" ^-H "Content-Type: application/json" ^-d "{"model":"text-embedding-ada-002","input":["Hello world","Goodbye world"]}"

http POST https://silkdock.ai/v1/embeddings \Authorization:"Bearer $SILKDOCK_API_KEY" \model=text-embedding-ada-002 \input:='["Hello world","Goodbye world"]'

wget -qO- https://silkdock.ai/v1/embeddings \--method=POST \--header="Authorization: Bearer $SILKDOCK_API_KEY" \--header="Content-Type: application/json" \--body-data='{"model":"text-embedding-ada-002","input":["Hello world","Goodbye world"]}'

$headers = @{  "Authorization" = "Bearer $env:SILKDOCK_API_KEY"  "Content-Type"  = "application/json"}$body = @{  model  = "text-embedding-ada-002"  input  = @("Hello world", "Goodbye world")} | ConvertTo-Json -Depth 3Invoke-RestMethod -Uri "https://silkdock.ai/v1/embeddings" -Method POST -Headers $headers -Body $body

const { OpenAI } = require("openai");const client = new OpenAI({apiKey: process.env.SILKDOCK_API_KEY,baseURL: "https://silkdock.ai/v1",});const response = await client.embeddings.create({model: "text-embedding-ada-002",input: ["Hello world", "Goodbye world"],});response.data.forEach(item => {console.log(`[${item.index}] ${item.embedding.slice(0, 3)} ...`);});

const res = await fetch("https://silkdock.ai/v1/embeddings", {method: "POST",headers: {  "Authorization": `Bearer ${process.env.SILKDOCK_API_KEY}`,  "Content-Type": "application/json",},body: JSON.stringify({  model: "text-embedding-ada-002",  input: ["Hello world", "Goodbye world"],}),});const { data } = await res.json();console.log(data[0].embedding); // float[]

import axios from "axios";const { data: result } = await axios.post("https://silkdock.ai/v1/embeddings",{  model: "text-embedding-ada-002",  input: ["Hello world", "Goodbye world"],},{  headers: {    Authorization: `Bearer ${process.env.SILKDOCK_API_KEY}`,    "Content-Type": "application/json",  },});console.log(result.data[0].embedding);

$.ajax({url: "https://silkdock.ai/v1/embeddings",method: "POST",contentType: "application/json",headers: { Authorization: `Bearer ${API_KEY}` },data: JSON.stringify({  model: "text-embedding-ada-002",  input: ["Hello world", "Goodbye world"],}),success: (result) => console.log(result.data[0].embedding),});

const xhr = new XMLHttpRequest();xhr.open("POST", "https://silkdock.ai/v1/embeddings");xhr.setRequestHeader("Authorization", `Bearer ${API_KEY}`);xhr.setRequestHeader("Content-Type", "application/json");xhr.onload = () => {const result = JSON.parse(xhr.responseText);console.log(result.data[0].embedding);};xhr.send(JSON.stringify({model: "text-embedding-ada-002",input: ["Hello world", "Goodbye world"],}));

const request = require("request");request.post({url: "https://silkdock.ai/v1/embeddings",headers: {  Authorization: `Bearer ${process.env.SILKDOCK_API_KEY}`,  "Content-Type": "application/json",},json: true,body: {  model: "text-embedding-ada-002",  input: ["Hello world", "Goodbye world"],},}, (err, res, body) => console.log(body.data[0].embedding));

const unirest = require("unirest");const res = await unirest.post("https://silkdock.ai/v1/embeddings").headers({  Authorization: `Bearer ${process.env.SILKDOCK_API_KEY}`,  "Content-Type": "application/json",}).send({  model: "text-embedding-ada-002",  input: ["Hello world", "Goodbye world"],});console.log(res.body.data[0].embedding);

import OpenAI from "openai";const client = new OpenAI({apiKey: process.env.SILKDOCK_API_KEY,baseURL: "https://silkdock.ai/v1",});const response = await client.embeddings.create({model: "text-embedding-ada-002",input: ["Hello world", "Goodbye world"],});response.data.forEach(item => {console.log(`[${item.index}] ${item.embedding.slice(0, 3)} ...`);});

const res = await fetch("https://silkdock.ai/v1/embeddings", {method: "POST",headers: {  "Authorization": `Bearer ${process.env.SILKDOCK_API_KEY}`,  "Content-Type": "application/json",},body: JSON.stringify({  model: "text-embedding-ada-002",  input: ["Hello world", "Goodbye world"],}),});const { data } = await res.json();console.log(data[0].embedding); // float[]

import requests, osres = requests.post(  "https://silkdock.ai/v1/embeddings",  headers={"Authorization": f"Bearer {os.getenv('SILKDOCK_API_KEY')}"},  json={      "model": "text-embedding-ada-002",      "input": ["Hello world", "Goodbye world"],  },)for item in res.json()["data"]:  print(f"[{item['index']}] {item['embedding'][:3]} ...")

import osfrom openai import OpenAIclient = OpenAI(  api_key=os.getenv("SILKDOCK_API_KEY"),  base_url="https://silkdock.ai/v1")response = client.embeddings.create(  model="text-embedding-ada-002",  input=["Hello world", "Goodbye world"])for item in response.data:  print(f"[{item.index}] {item.embedding[:3]} ...")

#include <stdio.h>#include <curl/curl.h>int main(void) {  CURL *curl = curl_easy_init();  if (!curl) return 1;  struct curl_slist *headers = NULL;  headers = curl_slist_append(headers, "Content-Type: application/json");  headers = curl_slist_append(headers,      "Authorization: Bearer " SILKDOCK_API_KEY);  const char *body =      "{"model":"text-embedding-ada-002","      ""input":["Hello world","Goodbye world"]}";  curl_easy_setopt(curl, CURLOPT_URL, "https://silkdock.ai/v1/embeddings");  curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers);  curl_easy_setopt(curl, CURLOPT_POSTFIELDS, body);  curl_easy_perform(curl);  curl_slist_free_all(headers);  curl_easy_cleanup(curl);  return 0;}/* compile: gcc main.c -lcurl -o main */

#import <Foundation/Foundation.h>NSURLSession *session = [NSURLSession sharedSession];NSURL *url = [NSURL URLWithString:@"https://silkdock.ai/v1/embeddings"];NSMutableURLRequest *request = [NSMutableURLRequest requestWithURL:url];[request setHTTPMethod:@"POST"];[request setValue:@"application/json" forHTTPHeaderField:@"Content-Type"];[request setValue:[@"Bearer " stringByAppendingString:  [NSProcessInfo.processInfo.environment objectForKey:@"SILKDOCK_API_KEY"]]  forHTTPHeaderField:@"Authorization"];NSDictionary *payload = @{  @"model": @"text-embedding-ada-002",  @"input": @[@"Hello world", @"Goodbye world"]};[request setHTTPBody:[NSJSONSerialization dataWithJSONObject:payload options:0 error:nil]];NSURLSessionDataTask *task = [session dataTaskWithRequest:request  completionHandler:^(NSData *data, NSURLResponse *response, NSError *error) {      NSDictionary *json = [NSJSONSerialization JSONObjectWithData:data options:0 error:nil];      NSLog(@"%@", json[@"data"][0][@"embedding"]);  }];[task resume];

import com.openai.client.OpenAIClient;import com.openai.client.okhttp.OpenAIOkHttpClient;import com.openai.models.*;OpenAIClient client = OpenAIOkHttpClient.builder()  .apiKey(System.getenv("SILKDOCK_API_KEY"))  .baseURL("https://silkdock.ai/v1")  .build();EmbeddingCreateResponse response = client.embeddings().create(  EmbeddingCreateParams.builder()      .model(EmbeddingModel.TEXT_EMBEDDING_ADA_002)      .input(EmbeddingCreateParams.Input.ofArrayOfStrings(          List.of("Hello world", "Goodbye world")))      .build());response.data().forEach(e -> System.out.println(e.embedding()));

import java.net.http.*;import java.net.URI;var req = HttpRequest.newBuilder()  .uri(URI.create("https://silkdock.ai/v1/embeddings"))  .header("Authorization", "Bearer " + System.getenv("SILKDOCK_API_KEY"))  .header("Content-Type", "application/json")  .POST(HttpRequest.BodyPublishers.ofString(      """{"model":"text-embedding-ada-002",           "input":["Hello world","Goodbye world"]}"""))  .build();System.out.println(HttpClient.newHttpClient().send(req, HttpResponse.BodyHandlers.ofString()).body());

import okhttp3.*;OkHttpClient client = new OkHttpClient();String json = "{"model":"text-embedding-ada-002","  + ""input":["Hello world","Goodbye world"]}";Request request = new Request.Builder()  .url("https://silkdock.ai/v1/embeddings")  .addHeader("Authorization", "Bearer " + System.getenv("SILKDOCK_API_KEY"))  .post(RequestBody.create(json, MediaType.get("application/json")))  .build();try (Response response = client.newCall(request).execute()) {  System.out.println(response.body().string());}

import kong.unirest.Unirest;HttpResponse<String> response = Unirest.post("https://silkdock.ai/v1/embeddings")  .header("Authorization", "Bearer " + System.getenv("SILKDOCK_API_KEY"))  .header("Content-Type", "application/json")  .body("{"model":"text-embedding-ada-002","      + ""input":["Hello world","Goodbye world"]}")  .asString();System.out.println(response.getBody());

package mainimport (  "context"  "fmt"  "os"  "github.com/openai/openai-go"  "github.com/openai/openai-go/option")func main() {  client := openai.NewClient(      option.WithAPIKey(os.Getenv("SILKDOCK_API_KEY")),      option.WithBaseURL("https://silkdock.ai/v1"),  )  resp, _ := client.Embeddings.New(context.Background(),      openai.EmbeddingNewParams{          Model: openai.F(openai.EmbeddingModelTextEmbeddingAda002),          Input: openai.F(openai.EmbeddingNewParamsInputUnion(              openai.EmbeddingNewParamsInputArrayOfStrings(                  []string{"Hello world", "Goodbye world"},              ),          )),      },  )  fmt.Println(resp.Data[0].Embedding)}

package mainimport (  "bytes"  "encoding/json"  "fmt"  "io"  "net/http"  "os")func main() {  body, _ := json.Marshal(map[string]any{      "model":  "text-embedding-ada-002",      "input":  []string{"Hello world", "Goodbye world"},  })  req, _ := http.NewRequest("POST", "https://silkdock.ai/v1/embeddings", bytes.NewReader(body))  req.Header.Set("Authorization", "Bearer "+os.Getenv("SILKDOCK_API_KEY"))  req.Header.Set("Content-Type", "application/json")  resp, _ := http.DefaultClient.Do(req)  defer resp.Body.Close()  data, _ := io.ReadAll(resp.Body)  fmt.Println(string(data))}

<?php$ch = curl_init("https://silkdock.ai/v1/embeddings");curl_setopt_array($ch, [  CURLOPT_POST           => true,  CURLOPT_RETURNTRANSFER => true,  CURLOPT_HTTPHEADER     => [      "Authorization: Bearer " . getenv("SILKDOCK_API_KEY"),      "Content-Type: application/json",  ],  CURLOPT_POSTFIELDS => json_encode([      "model"  => "text-embedding-ada-002",      "input"  => ["Hello world", "Goodbye world"],  ]),]);echo curl_exec($ch);

<?phprequire_once "HTTP/Request2.php";$request = new HTTP_Request2("https://silkdock.ai/v1/embeddings", HTTP_Request2::METHOD_POST);$request->setHeader("Authorization", "Bearer " . getenv("SILKDOCK_API_KEY"));$request->setHeader("Content-Type", "application/json");$request->setBody(json_encode([  "model"  => "text-embedding-ada-002",  "input"  => ["Hello world", "Goodbye world"],]));echo $request->send()->getBody();

<?phprequire "vendor/autoload.php";use GuzzleHttpClient;$client = new Client();$response = $client->post("https://silkdock.ai/v1/embeddings", [  "headers" => [      "Authorization" => "Bearer " . getenv("SILKDOCK_API_KEY"),      "Content-Type"  => "application/json",  ],  "json" => [      "model"  => "text-embedding-ada-002",      "input"  => ["Hello world", "Goodbye world"],  ],]);echo $response->getBody();

<?php$client = new httpClient;$request = new httpClientRequest("POST", "https://silkdock.ai/v1/embeddings");$request->setHeaders([  "Authorization" => "Bearer " . getenv("SILKDOCK_API_KEY"),  "Content-Type"  => "application/json",]);$body = new httpMessageBody;$body->append(json_encode([  "model"  => "text-embedding-ada-002",  "input"  => ["Hello world", "Goodbye world"],]));$request->setBody($body);$client->enqueue($request)->send();echo $client->getResponse()->getBody();

import OpenAIlet client = OpenAI(configuration: .init(  token: ProcessInfo.processInfo.environment["SILKDOCK_API_KEY"]!,  host: "silkdock.ai",  scheme: "https"))let query = EmbeddingsQuery(  model: "text-embedding-ada-002",  input: "Hello world")let result = try await client.embeddings(query: query)print(result.data.first?.embedding ?? [])

import Foundationvar req = URLRequest(url: URL(string: "https://silkdock.ai/v1/embeddings")!)req.httpMethod = "POST"req.setValue("Bearer \(ProcessInfo.processInfo.environment["SILKDOCK_API_KEY"]!)",           forHTTPHeaderField: "Authorization")req.setValue("application/json", forHTTPHeaderField: "Content-Type")req.httpBody = try! JSONSerialization.data(withJSONObject: [  "model": "text-embedding-ada-002",  "input": ["Hello world", "Goodbye world"],])let (data, _) = try! await URLSession.shared.data(for: req)print(String(data: data, encoding: .utf8)!)

using OpenAI;using OpenAI.Embeddings;var client = new EmbeddingClient(  model: "text-embedding-ada-002",  credential: new System.ClientModel.ApiKeyCredential(      Environment.GetEnvironmentVariable("SILKDOCK_API_KEY")!),  options: new OpenAIClientOptions {      Endpoint = new Uri("https://silkdock.ai/v1")  });var result = await client.GenerateEmbeddingAsync("Hello world");Console.WriteLine(string.Join(", ", result.Value.ToFloats().ToArray()));

using System.Net.Http;using System.Net.Http.Json;var client = new HttpClient();client.DefaultRequestHeaders.Add("Authorization",  $"Bearer {Environment.GetEnvironmentVariable("SILKDOCK_API_KEY")}");var res = await client.PostAsJsonAsync("https://silkdock.ai/v1/embeddings", new {  model  = "text-embedding-ada-002",  input  = new[] { "Hello world", "Goodbye world" },});Console.WriteLine(await res.Content.ReadAsStringAsync());

require "openai"client = OpenAI::Client.new(access_token: ENV["SILKDOCK_API_KEY"],uri_base: "https://silkdock.ai/v1")response = client.embeddings(parameters: {  model: "text-embedding-ada-002",  input: ["Hello world", "Goodbye world"]})puts response.dig("data", 0, "embedding")

require "net/http"require "json"uri = URI("https://silkdock.ai/v1/embeddings")req = Net::HTTP::Post.new(uri)req["Authorization"] = "Bearer #{ENV['SILKDOCK_API_KEY']}"req["Content-Type"]  = "application/json"req.body = {model: "text-embedding-ada-002",input: ["Hello world", "Goodbye world"]}.to_jsonres = Net::HTTP.start(uri.host, uri.port, use_ssl: true) { |h| h.request(req) }puts res.body

import com.openai.client.OpenAIClientimport com.openai.client.okhttp.OpenAIOkHttpClientimport com.openai.models.*val client: OpenAIClient = OpenAIOkHttpClient.builder()  .apiKey(System.getenv("SILKDOCK_API_KEY"))  .baseURL("https://silkdock.ai/v1")  .build()val response = client.embeddings().create(  EmbeddingCreateParams.builder()      .model(EmbeddingModel.TEXT_EMBEDDING_ADA_002)      .input(EmbeddingCreateParams.Input.ofArrayOfStrings(          listOf("Hello world", "Goodbye world")))      .build())println(response.data()[0].embedding())

import java.net.http.*import java.net.URIval req = HttpRequest.newBuilder()  .uri(URI.create("https://silkdock.ai/v1/embeddings"))  .header("Authorization", "Bearer ${System.getenv("SILKDOCK_API_KEY")}")  .header("Content-Type", "application/json")  .POST(HttpRequest.BodyPublishers.ofString(      """{"model":"text-embedding-ada-002",           "input":["Hello world","Goodbye world"]}"""))  .build()println(HttpClient.newHttpClient().send(req, HttpResponse.BodyHandlers.ofString()).body())

use reqwest::blocking::Client;use serde_json::json;fn main() -> Result<(), Box<dyn std::error::Error>> {  let res = Client::new()      .post("https://silkdock.ai/v1/embeddings")      .header("Authorization", format!("Bearer {}", std::env::var("SILKDOCK_API_KEY")?))      .json(&json!({          "model": "text-embedding-ada-002",          "input": ["Hello world", "Goodbye world"]      }))      .send()?;  println!("{}", res.text()?);  Ok(())}

POST /v1/embeddings HTTP/1.1Host: silkdock.aiAuthorization: Bearer <YOUR_API_KEY>Content-Type: application/json{"model": "text-embedding-ada-002","input": ["Hello world", "Goodbye world"]}

import 'dart:convert';import 'package:http/http.dart' as http;void main() async {final res = await http.post(  Uri.parse('https://silkdock.ai/v1/embeddings'),  headers: {    'Authorization': 'Bearer ${const String.fromEnvironment("SILKDOCK_API_KEY")}',    'Content-Type': 'application/json',  },  body: jsonEncode({    'model': 'text-embedding-ada-002',    'input': ['Hello world', 'Goodbye world'],  }),);print(res.body);}

library(httr2)req <- request("https://silkdock.ai/v1/embeddings") |>req_headers(  Authorization = paste("Bearer", Sys.getenv("SILKDOCK_API_KEY")),  "Content-Type" = "application/json") |>req_body_json(list(  model  = "text-embedding-ada-002",  input  = list("Hello world", "Goodbye world")))resp <- req_perform(req)cat(resp_body_string(resp))

(* requires cohttp-lwt-unix *)open Cohttp_lwt_unixopen Cohttpopen Lwtlet () =let body = {|{"model":"text-embedding-ada-002",    "input":["Hello world","Goodbye world"]}|} inlet headers = Header.of_list [  "Authorization", "Bearer " ^ Sys.getenv "SILKDOCK_API_KEY";  "Content-Type", "application/json";] inLwt_main.run (  Client.post ~headers ~body:(Cohttp_lwt.Body.of_string body)    (Uri.of_string "https://silkdock.ai/v1/embeddings")  >>= fun (_, body) -> Cohttp_lwt.Body.to_string body  >>= fun s -> print_string s; return_unit)

Response

{
  "object": "list",
  "data": [
    { "object": "embedding", "index": 0, "embedding": [0.0023064255, -0.009327292, "..."] }
  ],
  "model": "text-embedding-ada-002",
  "usage": { "prompt_tokens": 8, "total_tokens": 8 }
}

Embedding

Parameters

Examples

Response

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