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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1 +1 @@ | ||
| { "engineHash": "2efc8ab", "specHash": "e798cb1", "version": "1.7.0" } | ||
| { "engineHash": "2efc8ab", "specHash": "90cf4e4", "version": "1.7.0" } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,166 @@ | ||
| import { BoxSdkError } from '../box/errors.js'; | ||
| import { SerializedData } from '../serialization/json.js'; | ||
| import { sdIsEmpty } from '../serialization/json.js'; | ||
| import { sdIsBoolean } from '../serialization/json.js'; | ||
| import { sdIsNumber } from '../serialization/json.js'; | ||
| import { sdIsString } from '../serialization/json.js'; | ||
| import { sdIsList } from '../serialization/json.js'; | ||
| import { sdIsMap } from '../serialization/json.js'; | ||
| export type AiLlmEndpointParamsAwsTypeField = 'aws_params'; | ||
| export class AiLlmEndpointParamsAws { | ||
| /** | ||
| * The type of the AI LLM endpoint params object for AWS. | ||
| * This parameter is **required**. */ | ||
| readonly type: AiLlmEndpointParamsAwsTypeField = | ||
| 'aws_params' as AiLlmEndpointParamsAwsTypeField; | ||
| /** | ||
| * What sampling temperature to use, between 0 and 1. Higher values like 0.8 will make the output more random, | ||
| * while lower values like 0.2 will make it more focused and deterministic. | ||
| * We generally recommend altering this or `top_p` but not both. */ | ||
| readonly temperature?: number; | ||
| /** | ||
| * 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. We generally recommend altering this or temperature but not both. */ | ||
| readonly topP?: number; | ||
| readonly rawData?: SerializedData; | ||
| constructor( | ||
| fields: Omit<AiLlmEndpointParamsAws, 'type'> & | ||
| Partial<Pick<AiLlmEndpointParamsAws, 'type'>> | ||
| ) { | ||
| if (fields.type) { | ||
| this.type = fields.type; | ||
| } | ||
| if (fields.temperature) { | ||
| this.temperature = fields.temperature; | ||
| } | ||
| if (fields.topP) { | ||
| this.topP = fields.topP; | ||
| } | ||
| if (fields.rawData) { | ||
| this.rawData = fields.rawData; | ||
| } | ||
| } | ||
| } | ||
| export interface AiLlmEndpointParamsAwsInput { | ||
| /** | ||
| * The type of the AI LLM endpoint params object for AWS. | ||
| * This parameter is **required**. */ | ||
| readonly type?: AiLlmEndpointParamsAwsTypeField; | ||
| /** | ||
| * What sampling temperature to use, between 0 and 1. Higher values like 0.8 will make the output more random, | ||
| * while lower values like 0.2 will make it more focused and deterministic. | ||
| * We generally recommend altering this or `top_p` but not both. */ | ||
| readonly temperature?: number; | ||
| /** | ||
| * 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. We generally recommend altering this or temperature but not both. */ | ||
| readonly topP?: number; | ||
| readonly rawData?: SerializedData; | ||
| } | ||
| export function serializeAiLlmEndpointParamsAwsTypeField( | ||
| val: AiLlmEndpointParamsAwsTypeField | ||
| ): SerializedData { | ||
| return val; | ||
| } | ||
| export function deserializeAiLlmEndpointParamsAwsTypeField( | ||
| val: SerializedData | ||
| ): AiLlmEndpointParamsAwsTypeField { | ||
| if (val == 'aws_params') { | ||
| return val; | ||
| } | ||
| throw new BoxSdkError({ | ||
| message: "Can't deserialize AiLlmEndpointParamsAwsTypeField", | ||
| }); | ||
| } | ||
| export function serializeAiLlmEndpointParamsAws( | ||
| val: AiLlmEndpointParamsAws | ||
| ): SerializedData { | ||
| return { | ||
| ['type']: serializeAiLlmEndpointParamsAwsTypeField(val.type), | ||
| ['temperature']: val.temperature == void 0 ? void 0 : val.temperature, | ||
| ['top_p']: val.topP == void 0 ? void 0 : val.topP, | ||
| }; | ||
| } | ||
| export function deserializeAiLlmEndpointParamsAws( | ||
| val: SerializedData | ||
| ): AiLlmEndpointParamsAws { | ||
| if (!sdIsMap(val)) { | ||
| throw new BoxSdkError({ | ||
| message: 'Expecting a map for "AiLlmEndpointParamsAws"', | ||
| }); | ||
| } | ||
| if (val.type == void 0) { | ||
| throw new BoxSdkError({ | ||
| message: | ||
| 'Expecting "type" of type "AiLlmEndpointParamsAws" to be defined', | ||
| }); | ||
| } | ||
| const type: AiLlmEndpointParamsAwsTypeField = | ||
| deserializeAiLlmEndpointParamsAwsTypeField(val.type); | ||
| if (!(val.temperature == void 0) && !sdIsNumber(val.temperature)) { | ||
| throw new BoxSdkError({ | ||
| message: | ||
| 'Expecting number for "temperature" of type "AiLlmEndpointParamsAws"', | ||
| }); | ||
| } | ||
| const temperature: undefined | number = | ||
| val.temperature == void 0 ? void 0 : val.temperature; | ||
| if (!(val.top_p == void 0) && !sdIsNumber(val.top_p)) { | ||
| throw new BoxSdkError({ | ||
| message: 'Expecting number for "top_p" of type "AiLlmEndpointParamsAws"', | ||
| }); | ||
| } | ||
| const topP: undefined | number = val.top_p == void 0 ? void 0 : val.top_p; | ||
| return { | ||
| type: type, | ||
| temperature: temperature, | ||
| topP: topP, | ||
| } satisfies AiLlmEndpointParamsAws; | ||
| } | ||
| export function serializeAiLlmEndpointParamsAwsInput( | ||
| val: AiLlmEndpointParamsAwsInput | ||
| ): SerializedData { | ||
| return { | ||
| ['type']: | ||
| val.type == void 0 | ||
| ? void 0 | ||
| : serializeAiLlmEndpointParamsAwsTypeField(val.type), | ||
| ['temperature']: val.temperature == void 0 ? void 0 : val.temperature, | ||
| ['top_p']: val.topP == void 0 ? void 0 : val.topP, | ||
| }; | ||
| } | ||
| export function deserializeAiLlmEndpointParamsAwsInput( | ||
| val: SerializedData | ||
| ): AiLlmEndpointParamsAwsInput { | ||
| if (!sdIsMap(val)) { | ||
| throw new BoxSdkError({ | ||
| message: 'Expecting a map for "AiLlmEndpointParamsAwsInput"', | ||
| }); | ||
| } | ||
| const type: undefined | AiLlmEndpointParamsAwsTypeField = | ||
| val.type == void 0 | ||
| ? void 0 | ||
| : deserializeAiLlmEndpointParamsAwsTypeField(val.type); | ||
| if (!(val.temperature == void 0) && !sdIsNumber(val.temperature)) { | ||
| throw new BoxSdkError({ | ||
| message: | ||
| 'Expecting number for "temperature" of type "AiLlmEndpointParamsAwsInput"', | ||
| }); | ||
| } | ||
| const temperature: undefined | number = | ||
| val.temperature == void 0 ? void 0 : val.temperature; | ||
| if (!(val.top_p == void 0) && !sdIsNumber(val.top_p)) { | ||
| throw new BoxSdkError({ | ||
| message: | ||
| 'Expecting number for "top_p" of type "AiLlmEndpointParamsAwsInput"', | ||
| }); | ||
| } | ||
| const topP: undefined | number = val.top_p == void 0 ? void 0 : val.top_p; | ||
| return { | ||
| type: type, | ||
| temperature: temperature, | ||
| topP: topP, | ||
| } satisfies AiLlmEndpointParamsAwsInput; | ||
| } |
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