java/resources/evals/methods/update/index.md

Update an eval

EvalUpdateResponse evals().update(EvalUpdateParamsparams = EvalUpdateParams.none(), RequestOptionsrequestOptions = RequestOptions.none())

post /evals/{eval_id}

Update an eval

Parameters

EvalUpdateParams params
- Optional<String> evalId
- Optional<Metadata> metadata
  
  Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.
  
  Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.
- Optional<String> name
  
  Rename the evaluation.

Returns

class EvalUpdateResponse:

An Eval object with a data source config and testing criteria. An Eval represents a task to be done for your LLM integration. Like:
- Improve the quality of my chatbot
- See how well my chatbot handles customer support
- Check if o4-mini is better at my usecase than gpt-4o
- String id
  
  Unique identifier for the evaluation.
- long createdAt
  
  The Unix timestamp (in seconds) for when the eval was created.
- DataSourceConfig dataSourceConfig
  
  Configuration of data sources used in runs of the evaluation.
  - class EvalCustomDataSourceConfig:
    
    A CustomDataSourceConfig which specifies the schema of your item and optionally sample namespaces. The response schema defines the shape of the data that will be:
    - Used to define your testing criteria and
    - What data is required when creating a run
    - Schema schema
      
      The json schema for the run data source items. Learn how to build JSON schemas here.
    - JsonValue; type "custom"constant
      
      The type of data source. Always custom.
      - CUSTOM("custom")
  - class Logs:
    
    A LogsDataSourceConfig which specifies the metadata property of your logs query. This is usually metadata like usecase=chatbot or prompt-version=v2, etc. The schema returned by this data source config is used to defined what variables are available in your evals. item and sample are both defined when using this data source config.
    - Schema schema
      
      The json schema for the run data source items. Learn how to build JSON schemas here.
    - JsonValue; type "logs"constant
      
      The type of data source. Always logs.
      - LOGS("logs")
    - Optional<Metadata> metadata
      
      Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.
      
      Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.
  - class EvalStoredCompletionsDataSourceConfig:
    
    Deprecated in favor of LogsDataSourceConfig.
    - Schema schema
      
      The json schema for the run data source items. Learn how to build JSON schemas here.
    - JsonValue; type "stored_completions"constant
      
      The type of data source. Always stored_completions.
      - STORED_COMPLETIONS("stored_completions")
    - Optional<Metadata> metadata
      
      Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.
      
      Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.
- Optional<Metadata> metadata
  
  Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.
  
  Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.
- String name
  
  The name of the evaluation.
- JsonValue; object_ "eval"constant
  
  The object type.
  - EVAL("eval")
- List<TestingCriterion> testingCriteria
  
  A list of testing criteria.
  - class LabelModelGrader:
    
    A LabelModelGrader object which uses a model to assign labels to each item in the evaluation.
    - List<Input> input
      - Content content
        
        Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.
        
        String
        
        class ResponseInputText:
        
        A text input to the model.
        
        String text
        
        The text input to the model.
        
        JsonValue; type "input_text"constant
        
        The type of the input item. Always input_text.
        
        INPUT_TEXT("input_text")
        
        Optional<PromptCacheBreakpoint> promptCacheBreakpoint
        
        Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
        
        JsonValue; mode "explicit"constant
        
        The breakpoint mode. Always explicit.
        
        EXPLICIT("explicit")
        
        class OutputText:
        
        A text output from the model.
        
        String text
        
        The text output from the model.
        
        JsonValue; type "output_text"constant
        
        The type of the output text. Always output_text.
        
        OUTPUT_TEXT("output_text")
        
        class InputImage:
        
        An image input block used within EvalItem content arrays.
        
        String imageUrl
        
        The URL of the image input.
        
        JsonValue; type "input_image"constant
        
        The type of the image input. Always input_image.
        
        INPUT_IMAGE("input_image")
        
        Optional<String> detail
        
        The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.
        
        class ResponseInputAudio:
        
        An audio input to the model.
        
        InputAudio inputAudio
        
        String data
        
        Base64-encoded audio data.
        
        Format format
        
        The format of the audio data. Currently supported formats are mp3 and wav.
        
        MP3("mp3")
        
        WAV("wav")
        
        JsonValue; type "input_audio"constant
        
        The type of the input item. Always input_audio.
        
        INPUT_AUDIO("input_audio")
        
        List<EvalContentItem>
        
        String
        
        class ResponseInputText:
        
        A text input to the model.
        
        OutputText
        
        String text
        
        The text output from the model.
        
        JsonValue; type "output_text"constant
        
        The type of the output text. Always output_text.
        
        OUTPUT_TEXT("output_text")
        
        InputImage
        
        String imageUrl
        
        The URL of the image input.
        
        JsonValue; type "input_image"constant
        
        The type of the image input. Always input_image.
        
        INPUT_IMAGE("input_image")
        
        Optional<String> detail
        
        The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.
        
        class ResponseInputAudio:
        
        An audio input to the model.
      - Role role
        
        The role of the message input. One of user, assistant, system, or developer.
        
        USER("user")
        
        ASSISTANT("assistant")
        
        SYSTEM("system")
        
        DEVELOPER("developer")
      - Optional<Type> type
        
        The type of the message input. Always message.
        
        MESSAGE("message")
    - List<String> labels
      
      The labels to assign to each item in the evaluation.
    - String model
      
      The model to use for the evaluation. Must support structured outputs.
    - String name
      
      The name of the grader.
    - List<String> passingLabels
      
      The labels that indicate a passing result. Must be a subset of labels.
    - JsonValue; type "label_model"constant
      
      The object type, which is always label_model.
      - LABEL_MODEL("label_model")
  - class StringCheckGrader:
    
    A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.
    - String input
      
      The input text. This may include template strings.
    - String name
      
      The name of the grader.
    - Operation operation
      
      The string check operation to perform. One of eq, ne, like, or ilike.
      - EQ("eq")
      - NE("ne")
      - LIKE("like")
      - ILIKE("ilike")
    - String reference
      
      The reference text. This may include template strings.
    - JsonValue; type "string_check"constant
      
      The object type, which is always string_check.
      - STRING_CHECK("string_check")
  - class EvalGraderTextSimilarity:
    
    A TextSimilarityGrader object which grades text based on similarity metrics.
    - double passThreshold
      
      The threshold for the score.
  - class EvalGraderPython:
    
    A PythonGrader object that runs a python script on the input.
    - Optional<Double> passThreshold
      
      The threshold for the score.
  - class EvalGraderScoreModel:
    
    A ScoreModelGrader object that uses a model to assign a score to the input.
    - Optional<Double> passThreshold
      
      The threshold for the score.

Example

package com.openai.example;

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.evals.EvalUpdateParams;
import com.openai.models.evals.EvalUpdateResponse;

public final class Main {
    private Main() {}

    public static void main(String[] args) {
        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

        EvalUpdateResponse eval = client.evals().update("eval_id");
    }
}

Response

{
  "id": "id",
  "created_at": 0,
  "data_source_config": {
    "schema": {
      "foo": "bar"
    },
    "type": "custom"
  },
  "metadata": {
    "foo": "string"
  },
  "name": "Chatbot effectiveness Evaluation",
  "object": "eval",
  "testing_criteria": [
    {
      "input": [
        {
          "content": "string",
          "role": "user",
          "type": "message"
        }
      ],
      "labels": [
        "string"
      ],
      "model": "model",
      "name": "name",
      "passing_labels": [
        "string"
      ],
      "type": "label_model"
    }
  ]
}

java/resources/evals/methods/update/index.md +437 −0 created

1## Update an eval

3`EvalUpdateResponse evals().update(EvalUpdateParamsparams = EvalUpdateParams.none(), RequestOptionsrequestOptions = RequestOptions.none())`

5**post** `/evals/{eval_id}`

7Update an eval

9### Parameters

11- `EvalUpdateParams params`

13 - `Optional<String> evalId`

15 - `Optional<Metadata> metadata`

17 Set of 16 key-value pairs that can be attached to an object. This can be

18 useful for storing additional information about the object in a structured

19 format, and querying for objects via API or the dashboard.

21 Keys are strings with a maximum length of 64 characters. Values are strings

22 with a maximum length of 512 characters.

24 - `Optional<String> name`

26 Rename the evaluation.

28### Returns

30- `class EvalUpdateResponse:`

32 An Eval object with a data source config and testing criteria.

33 An Eval represents a task to be done for your LLM integration.

34 Like:

36 - Improve the quality of my chatbot

37 - See how well my chatbot handles customer support

38 - Check if o4-mini is better at my usecase than gpt-4o

40 - `String id`

42 Unique identifier for the evaluation.

44 - `long createdAt`

46 The Unix timestamp (in seconds) for when the eval was created.

48 - `DataSourceConfig dataSourceConfig`

50 Configuration of data sources used in runs of the evaluation.

52 - `class EvalCustomDataSourceConfig:`

54 A CustomDataSourceConfig which specifies the schema of your `item` and optionally `sample` namespaces.

55 The response schema defines the shape of the data that will be:

57 - Used to define your testing criteria and

58 - What data is required when creating a run

60 - `Schema schema`

62 The json schema for the run data source items.

63 Learn how to build JSON schemas [here](https://json-schema.org/).

65 - `JsonValue; type "custom"constant`

67 The type of data source. Always `custom`.

69 - `CUSTOM("custom")`

71 - `class Logs:`

73 A LogsDataSourceConfig which specifies the metadata property of your logs query.

74 This is usually metadata like `usecase=chatbot` or `prompt-version=v2`, etc.

75 The schema returned by this data source config is used to defined what variables are available in your evals.

76 `item` and `sample` are both defined when using this data source config.

78 - `Schema schema`

80 The json schema for the run data source items.

81 Learn how to build JSON schemas [here](https://json-schema.org/).

83 - `JsonValue; type "logs"constant`

85 The type of data source. Always `logs`.

87 - `LOGS("logs")`

89 - `Optional<Metadata> metadata`

91 Set of 16 key-value pairs that can be attached to an object. This can be

92 useful for storing additional information about the object in a structured

93 format, and querying for objects via API or the dashboard.

95 Keys are strings with a maximum length of 64 characters. Values are strings

96 with a maximum length of 512 characters.

98 - `class EvalStoredCompletionsDataSourceConfig:`

100 Deprecated in favor of LogsDataSourceConfig.

101

102 - `Schema schema`

103

104 The json schema for the run data source items.

105 Learn how to build JSON schemas [here](https://json-schema.org/).

106

107 - `JsonValue; type "stored_completions"constant`

108

109 The type of data source. Always `stored_completions`.

110

111 - `STORED_COMPLETIONS("stored_completions")`

112

113 - `Optional<Metadata> metadata`

114

115 Set of 16 key-value pairs that can be attached to an object. This can be

116 useful for storing additional information about the object in a structured

117 format, and querying for objects via API or the dashboard.

118

119 Keys are strings with a maximum length of 64 characters. Values are strings

120 with a maximum length of 512 characters.

121

122 - `Optional<Metadata> metadata`

123

124 Set of 16 key-value pairs that can be attached to an object. This can be

125 useful for storing additional information about the object in a structured

126 format, and querying for objects via API or the dashboard.

127

128 Keys are strings with a maximum length of 64 characters. Values are strings

129 with a maximum length of 512 characters.

130

131 - `String name`

132

133 The name of the evaluation.

134

135 - `JsonValue; object_ "eval"constant`

136

137 The object type.

138

139 - `EVAL("eval")`

140

141 - `List<TestingCriterion> testingCriteria`

142

143 A list of testing criteria.

144

145 - `class LabelModelGrader:`

146

147 A LabelModelGrader object which uses a model to assign labels to each item

148 in the evaluation.

149

150 - `List<Input> input`

151

152 - `Content content`

153

154 Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.

155

156 - `String`

157

158 - `class ResponseInputText:`

159

160 A text input to the model.

161

162 - `String text`

163

164 The text input to the model.

165

166 - `JsonValue; type "input_text"constant`

167

168 The type of the input item. Always `input_text`.

169

170 - `INPUT_TEXT("input_text")`

171

172 - `Optional<PromptCacheBreakpoint> promptCacheBreakpoint`

173

174 Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block.

175

176 - `JsonValue; mode "explicit"constant`

177

178 The breakpoint mode. Always `explicit`.

179

180 - `EXPLICIT("explicit")`

181

182 - `class OutputText:`

183

184 A text output from the model.

185

186 - `String text`

187

188 The text output from the model.

189

190 - `JsonValue; type "output_text"constant`

191

192 The type of the output text. Always `output_text`.

193

194 - `OUTPUT_TEXT("output_text")`

195

196 - `class InputImage:`

197

198 An image input block used within EvalItem content arrays.

199

200 - `String imageUrl`

201

202 The URL of the image input.

203

204 - `JsonValue; type "input_image"constant`

205

206 The type of the image input. Always `input_image`.

207

208 - `INPUT_IMAGE("input_image")`

209

210 - `Optional<String> detail`

211

212 The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.

213

214 - `class ResponseInputAudio:`

215

216 An audio input to the model.

217

218 - `InputAudio inputAudio`

219

220 - `String data`

221

222 Base64-encoded audio data.

223

224 - `Format format`

225

226 The format of the audio data. Currently supported formats are `mp3` and

227 `wav`.

228

229 - `MP3("mp3")`

230

231 - `WAV("wav")`

232

233 - `JsonValue; type "input_audio"constant`

234

235 The type of the input item. Always `input_audio`.

236

237 - `INPUT_AUDIO("input_audio")`

238

239 - `List<EvalContentItem>`

240

241 - `String`

242

243 - `class ResponseInputText:`

244

245 A text input to the model.

246

247 - `OutputText`

248

249 - `String text`

250

251 The text output from the model.

252

253 - `JsonValue; type "output_text"constant`

254

255 The type of the output text. Always `output_text`.

256

257 - `OUTPUT_TEXT("output_text")`

258

259 - `InputImage`

260

261 - `String imageUrl`

262

263 The URL of the image input.

264

265 - `JsonValue; type "input_image"constant`

266

267 The type of the image input. Always `input_image`.

268

269 - `INPUT_IMAGE("input_image")`

270

271 - `Optional<String> detail`

272

273 The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.

274

275 - `class ResponseInputAudio:`

276

277 An audio input to the model.

278

279 - `Role role`

280

281 The role of the message input. One of `user`, `assistant`, `system`, or

282 `developer`.

283

284 - `USER("user")`

285

286 - `ASSISTANT("assistant")`

287

288 - `SYSTEM("system")`

289

290 - `DEVELOPER("developer")`

291

292 - `Optional<Type> type`

293

294 The type of the message input. Always `message`.

295

296 - `MESSAGE("message")`

297

298 - `List<String> labels`

299

300 The labels to assign to each item in the evaluation.

301

302 - `String model`

303

304 The model to use for the evaluation. Must support structured outputs.

305

306 - `String name`

307

308 The name of the grader.

309

310 - `List<String> passingLabels`

311

312 The labels that indicate a passing result. Must be a subset of labels.

313

314 - `JsonValue; type "label_model"constant`

315

316 The object type, which is always `label_model`.

317

318 - `LABEL_MODEL("label_model")`

319

320 - `class StringCheckGrader:`

321

322 A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.

323

324 - `String input`

325

326 The input text. This may include template strings.

327

328 - `String name`

329

330 The name of the grader.

331

332 - `Operation operation`

333

334 The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.

335

336 - `EQ("eq")`

337

338 - `NE("ne")`

339

340 - `LIKE("like")`

341

342 - `ILIKE("ilike")`

343

344 - `String reference`

345

346 The reference text. This may include template strings.

347

348 - `JsonValue; type "string_check"constant`

349

350 The object type, which is always `string_check`.

351

352 - `STRING_CHECK("string_check")`

353

354 - `class EvalGraderTextSimilarity:`

355

356 A TextSimilarityGrader object which grades text based on similarity metrics.

357

358 - `double passThreshold`

359

360 The threshold for the score.

361

362 - `class EvalGraderPython:`

363

364 A PythonGrader object that runs a python script on the input.

365

366 - `Optional<Double> passThreshold`

367

368 The threshold for the score.

369

370 - `class EvalGraderScoreModel:`

371

372 A ScoreModelGrader object that uses a model to assign a score to the input.

373

374 - `Optional<Double> passThreshold`

375

376 The threshold for the score.

377

378### Example

379

380```java

381package com.openai.example;

382

383import com.openai.client.OpenAIClient;

384import com.openai.client.okhttp.OpenAIOkHttpClient;

385import com.openai.models.evals.EvalUpdateParams;

386import com.openai.models.evals.EvalUpdateResponse;

387

388public final class Main {

389 private Main() {}

390

391 public static void main(String[] args) {

392 OpenAIClient client = OpenAIOkHttpClient.fromEnv();

393

394 EvalUpdateResponse eval = client.evals().update("eval_id");

395 }

396}

397```

398

399#### Response

400

401```json

402{

403 "id": "id",

404 "created_at": 0,

405 "data_source_config": {

406 "schema": {

407 "foo": "bar"

408 },

409 "type": "custom"

410 },

411 "metadata": {

412 "foo": "string"

413 },

414 "name": "Chatbot effectiveness Evaluation",

415 "object": "eval",

416 "testing_criteria": [

417 {

418 "input": [

419 {

420 "content": "string",

421 "role": "user",

422 "type": "message"

423 }

424 ],

425 "labels": [

426 "string"

427 ],

428 "model": "model",

429 "name": "name",

430 "passing_labels": [

431 "string"

432 ],

433 "type": "label_model"

434 }

435 ]

436}

437```

java/resources/evals/methods/update/index.md 2026-07-07 08:02 UTC to 2026-07-09 20:58 UTC

Update an eval

Parameters

Returns

Example

Response