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src/Custom/Embeddings/EmbeddingGenerationOptions.cs

97lines · modecode

1using System;
2using System.Collections.Generic;
3
4namespace OpenAI.Embeddings;
5
6[CodeGenModel("CreateEmbeddingRequest")]
7[CodeGenSuppress("EmbeddingGenerationOptions", typeof(BinaryData), typeof(InternalCreateEmbeddingRequestModel))]
8public partial class EmbeddingGenerationOptions
9{
10 // CUSTOM:
11 // - Made internal. This value comes from a parameter on the client method.
12 // - Added setter.
13 /// <summary>
14 /// Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a
15 /// single request, pass an array of strings or array of token arrays. Each input must not exceed
16 /// the max input tokens for the model (8191 tokens for `text-embedding-ada-002`) and cannot be an
17 /// empty string.
18 /// [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb)
19 /// for counting tokens.
20 /// <para>
21 /// To assign an object to this property use <see cref="BinaryData.FromObjectAsJson{T}(T, System.Text.Json.JsonSerializerOptions?)"/>.
22 /// </para>
23 /// <para>
24 /// To assign an already formatted json string to this property use <see cref="BinaryData.FromString(string)"/>.
25 /// </para>
26 /// <para>
27 /// <remarks>
28 /// Supported types:
29 /// <list type="bullet">
30 /// <item>
31 /// <description><see cref="string"/></description>
32 /// </item>
33 /// <item>
34 /// <description><see cref="IList{T}"/> where <c>T</c> is of type <see cref="string"/></description>
35 /// </item>
36 /// <item>
37 /// <description><see cref="IList{T}"/> where <c>T</c> is of type <see cref="long"/></description>
38 /// </item>
39 /// <item>
40 /// <description><see cref="IList{T}"/> where <c>T</c> is of type <c>IList{long}</c></description>
41 /// </item>
42 /// </list>
43 /// </remarks>
44 /// Examples:
45 /// <list type="bullet">
46 /// <item>
47 /// <term>BinaryData.FromObjectAsJson("foo")</term>
48 /// <description>Creates a payload of "foo".</description>
49 /// </item>
50 /// <item>
51 /// <term>BinaryData.FromString("\"foo\"")</term>
52 /// <description>Creates a payload of "foo".</description>
53 /// </item>
54 /// <item>
55 /// <term>BinaryData.FromObjectAsJson(new { key = "value" })</term>
56 /// <description>Creates a payload of { "key": "value" }.</description>
57 /// </item>
58 /// <item>
59 /// <term>BinaryData.FromString("{\"key\": \"value\"}")</term>
60 /// <description>Creates a payload of { "key": "value" }.</description>
61 /// </item>
62 /// </list>
63 /// </para>
64 /// </summary>
65 internal BinaryData Input { get; set; }
66
67 // CUSTOM:
68 // - Made internal. The model is specified by the client.
69 // - Added setter.
70 /// <summary>
71 /// ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to
72 /// see all of your available models, or see our [Model overview](/docs/models/overview) for
73 /// descriptions of them.
74 /// </summary>
75 internal InternalCreateEmbeddingRequestModel Model { get; set; }
76
77 // CUSTOM: Made internal. We always request the embedding as a base64-encoded string for better performance.
78 /// <summary>
79 /// The format to return the embeddings in. Can be either `float` or
80 /// [`base64`](https://pypi.org/project/pybase64/).
81 /// </summary>
82 internal InternalCreateEmbeddingRequestEncodingFormat? EncodingFormat { get; set; }
83
84 // CUSTOM: Made public now that there are no required properties.
85 /// <summary> Initializes a new instance of <see cref="EmbeddingGenerationOptions"/>. </summary>
86 public EmbeddingGenerationOptions()
87 {
88 }
89
90 // CUSTOM: Renamed.
91 /// <summary>
92 /// A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
93 /// <see href="https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids">Learn more</see>.
94 /// </summary>
95 [CodeGenMember("User")]
96 public string EndUserId { get; set; }
97}