-
Notifications
You must be signed in to change notification settings - Fork 5.1k
/
inference.json
537 lines (537 loc) · 21 KB
/
inference.json
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
{
"openapi": "3.0.0",
"info": {
"title": "Azure OpenAI Service API",
"description": "Azure OpenAI APIs for completions and search",
"version": "2022-12-01"
},
"servers": [
{
"url": "https://{endpoint}/openai",
"variables": {
"endpoint": {
"default": "your-resource-name.openai.azure.com"
}
}
}
],
"security": [
{
"bearer": [
"api.read"
]
},
{
"apiKey": []
}
],
"paths": {
"/deployments/{deployment-id}/completions": {
"post": {
"summary": "Creates a completion for the provided prompt, parameters and chosen model.",
"operationId": "Completions_Create",
"parameters": [
{
"in": "path",
"name": "deployment-id",
"required": true,
"schema": {
"type": "string",
"example": "davinci",
"description": "Deployment id of the model which was deployed."
}
},
{
"in": "query",
"name": "api-version",
"required": true,
"schema": {
"type": "string",
"example": "2022-12-01",
"description": "api version"
}
}
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"prompt": {
"description": "The prompt(s) to generate completions for, encoded as a string or array of strings.\nNote that <|endoftext|> is the document separator that the model sees during training, so if a prompt is not specified the model will generate as if from the beginning of a new document. Maximum allowed size of string list is 2048.",
"oneOf": [
{
"type": "string",
"default": "",
"example": "This is a test.",
"nullable": true
},
{
"type": "array",
"items": {
"type": "string",
"default": "",
"example": "This is a test.",
"nullable": false
},
"description": "Array size minimum of 1 and maximum of 2048"
}
]
},
"max_tokens": {
"description": "The token count of your prompt plus max_tokens cannot exceed the model's context length. Most models have a context length of 2048 tokens (except for the newest models, which support 4096). Has minimum of 0.",
"type": "integer",
"default": 16,
"example": 16,
"nullable": true
},
"temperature": {
"description": "What sampling temperature to use. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer.\nWe generally recommend altering this or top_p but not both.",
"type": "number",
"default": 1,
"example": 1,
"nullable": true
},
"top_p": {
"description": "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.\nWe generally recommend altering this or temperature but not both.",
"type": "number",
"default": 1,
"example": 1,
"nullable": true
},
"logit_bias": {
"description": "Defaults to null. Modify the likelihood of specified tokens appearing in the completion. Accepts a json object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this tokenizer tool (which works for both GPT-2 and GPT-3) to convert text to token IDs. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token. As an example, you can pass {\"50256\" : -100} to prevent the <|endoftext|> token from being generated.",
"type": "object",
"nullable": false
},
"user": {
"description": "A unique identifier representing your end-user, which can help monitoring and detecting abuse",
"type": "string",
"nullable": false
},
"n": {
"description": "How many completions to generate for each prompt. Minimum of 1 and maximum of 128 allowed.\nNote: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop.",
"type": "integer",
"default": 1,
"example": 1,
"nullable": true
},
"stream": {
"description": "Whether to stream back partial progress. If set, tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message.",
"type": "boolean",
"nullable": true,
"default": false
},
"logprobs": {
"description": "Include the log probabilities on the logprobs most likely tokens, as well the chosen tokens. For example, if logprobs is 5, the API will return a list of the 5 most likely tokens. The API will always return the logprob of the sampled token, so there may be up to logprobs+1 elements in the response.\nMinimum of 0 and maximum of 5 allowed.",
"type": "integer",
"default": null,
"nullable": true
},
"model": {
"type": "string",
"example": "davinci",
"nullable": true,
"description": "ID of the model to use. You can use the Models_List operation to see all of your available models, or see our Models_Get overview for descriptions of them."
},
"suffix": {
"type": "string",
"nullable": true,
"description": "The suffix that comes after a completion of inserted text."
},
"echo": {
"description": "Echo back the prompt in addition to the completion",
"type": "boolean",
"default": false,
"nullable": true
},
"stop": {
"description": "Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.",
"oneOf": [
{
"type": "string",
"default": "<|endoftext|>",
"example": "\n",
"nullable": true
},
{
"type": "array",
"items": {
"type": "string",
"example": [
"\n"
],
"nullable": false
},
"description": "Array minimum size of 1 and maximum of 4"
}
]
},
"completion_config": {
"type": "string",
"nullable": true
},
"presence_penalty": {
"description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.",
"type": "number",
"default": 0
},
"frequency_penalty": {
"description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.",
"type": "number",
"default": 0
},
"best_of": {
"description": "Generates best_of completions server-side and returns the \"best\" (the one with the highest log probability per token). Results cannot be streamed.\nWhen used with n, best_of controls the number of candidate completions and n specifies how many to return – best_of must be greater than n.\nNote: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop. Has maximum value of 128.",
"type": "integer"
}
}
},
"example": {
"prompt": "Negate the following sentence.The price for bubblegum increased on thursday.\n\n Negated Sentence:",
"max_tokens": 50
}
}
}
},
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"object": {
"type": "string"
},
"created": {
"type": "integer"
},
"model": {
"type": "string"
},
"choices": {
"type": "array",
"items": {
"type": "object",
"properties": {
"text": {
"type": "string"
},
"index": {
"type": "integer"
},
"logprobs": {
"type": "object",
"properties": {
"tokens": {
"type": "array",
"items": {
"type": "string"
}
},
"token_logprobs": {
"type": "array",
"items": {
"type": "number"
}
},
"top_logprobs": {
"type": "array",
"items": {
"type": "object",
"additionalProperties": {
"type": "number"
}
}
},
"text_offset": {
"type": "array",
"items": {
"type": "integer"
}
}
}
},
"finish_reason": {
"type": "string"
}
}
}
},
"usage": {
"type": "object",
"properties": {
"completion_tokens": {
"type": "number",
"format": "int32"
},
"prompt_tokens": {
"type": "number",
"format": "int32"
},
"total_tokens": {
"type": "number",
"format": "int32"
}
},
"required": [
"prompt_tokens",
"total_tokens",
"completion_tokens"
]
}
},
"required": [
"id",
"object",
"created",
"model",
"choices"
]
},
"example": {
"model": "davinci",
"object": "text_completion",
"id": "cmpl-4509KAos68kxOqpE2uYGw81j6m7uo",
"created": 1637097562,
"choices": [
{
"index": 0,
"text": "The price for bubblegum decreased on thursday.",
"logprobs": null,
"finish_reason": "stop"
}
]
}
}
},
"headers": {
"apim-request-id": {
"description": "Request ID for troubleshooting purposes",
"schema": {
"type": "string"
}
}
}
},
"default": {
"description": "Service unavailable",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/errorResponse"
}
}
},
"headers": {
"apim-request-id": {
"description": "Request ID for troubleshooting purposes",
"schema": {
"type": "string"
}
}
}
}
}
}
},
"/deployments/{deployment-id}/embeddings": {
"post": {
"summary": "Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.",
"operationId": "embeddings_create",
"parameters": [
{
"in": "path",
"name": "deployment-id",
"required": true,
"schema": {
"type": "string",
"example": "ada-search-index-v1"
},
"description": "The deployment id of the model which was deployed."
},
{
"in": "query",
"name": "api-version",
"required": true,
"schema": {
"type": "string",
"example": "2022-12-01",
"description": "api version"
}
}
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"type": "object",
"additionalProperties": true,
"properties": {
"input": {
"description": "Input text to get embeddings for, encoded as a string. To get embeddings for multiple inputs in a single request, pass an array of strings. Each input must not exceed 2048 tokens in length.\nUnless you are embedding code, we suggest replacing newlines (\\n) in your input with a single space, as we have observed inferior results when newlines are present.",
"oneOf": [
{
"type": "string",
"default": "",
"example": "This is a test.",
"nullable": true
},
{
"type": "array",
"minItems": 1,
"maxItems": 2048,
"items": {
"type": "string",
"minLength": 1,
"example": "This is a test.",
"nullable": false
}
}
]
},
"user": {
"description": "A unique identifier representing your end-user, which can help monitoring and detecting abuse.",
"type": "string",
"nullable": false
},
"input_type": {
"description": "input type of embedding search to use",
"type": "string",
"example": "query"
},
"model": {
"type": "string",
"description": "ID of the model to use. You can use the Models_List operation to see all of your available models, or see our Models_Get overview for descriptions of them.",
"nullable": false
}
},
"required": [
"input"
]
}
}
}
},
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"object": {
"type": "string"
},
"model": {
"type": "string"
},
"data": {
"type": "array",
"items": {
"type": "object",
"properties": {
"index": {
"type": "integer"
},
"object": {
"type": "string"
},
"embedding": {
"type": "array",
"items": {
"type": "number"
}
}
},
"required": [
"index",
"object",
"embedding"
]
}
},
"usage": {
"type": "object",
"properties": {
"prompt_tokens": {
"type": "integer"
},
"total_tokens": {
"type": "integer"
}
},
"required": [
"prompt_tokens",
"total_tokens"
]
}
},
"required": [
"object",
"model",
"data",
"usage"
]
}
}
}
}
}
}
}
},
"components": {
"schemas": {
"errorResponse": {
"type": "object",
"properties": {
"error": {
"type": "object",
"properties": {
"code": {
"type": "string"
},
"message": {
"type": "string"
},
"param": {
"type": "string"
},
"type": {
"type": "string"
}
}
}
}
}
},
"securitySchemes": {
"bearer": {
"type": "oauth2",
"flows": {
"implicit": {
"authorizationUrl": "https://login.microsoftonline.com/common/oauth2/v2.0/authorize",
"scopes": {}
}
},
"x-tokenInfoFunc": "api.middleware.auth.bearer_auth",
"x-scopeValidateFunc": "api.middleware.auth.validate_scopes"
},
"apiKey": {
"type": "apiKey",
"name": "api-key",
"in": "header"
}
}
}
}