@emergentmethods/asknews-typescript-sdk
Version:
Typescript SDK for AskNews API
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text/typescript
/* tslint:disable */
/* eslint-disable */
/**
* AskNews API
* AskNews API [](https://status.asknews.app/status/prod)
*
* The version of the OpenAPI document: 0.24.22
* Contact: contact@emergentmethods.ai
*
* NOTE: This class is auto generated by OpenAPI Generator (https://openapi-generator.tech).
* https://openapi-generator.tech
* Do not edit the class manually.
*/
import * as runtime from '../runtime';
import type {
AbcAPIErrorModel105,
AbcAPIErrorModel106,
AbcAPIErrorModel107,
AbcAPIErrorModel108,
AsknewsApiErrorsAPIErrorModel,
ValidationErrorModel,
WikiSearchResponse,
} from '../models/index';
import {
AbcAPIErrorModel105FromJSON,
AbcAPIErrorModel105ToJSON,
AbcAPIErrorModel106FromJSON,
AbcAPIErrorModel106ToJSON,
AbcAPIErrorModel107FromJSON,
AbcAPIErrorModel107ToJSON,
AbcAPIErrorModel108FromJSON,
AbcAPIErrorModel108ToJSON,
AsknewsApiErrorsAPIErrorModelFromJSON,
AsknewsApiErrorsAPIErrorModelToJSON,
ValidationErrorModelFromJSON,
ValidationErrorModelToJSON,
WikiSearchResponseFromJSON,
WikiSearchResponseToJSON,
} from '../models/index';
export interface SearchWikiRequest {
query?: string;
neighborChunks?: number;
nDocuments?: number;
fullArticles?: boolean;
hybridSearch?: boolean;
stringGuarantee?: Array<string>;
diversify?: number;
includeMainSection?: boolean;
}
/**
*
*/
export class WikiApi extends runtime.BaseAPI {
/**
* Search on Wikipedia content with natural language. Find exactly relevant chunks, with contextual neighbor chunks, and the full articles they came from.
* Search for Wikipedia context with natural language
*/
async searchWikiRaw(requestParameters: SearchWikiRequest, initOverrides?: RequestInit | runtime.InitOverrideFunction): Promise<runtime.ApiResponse<WikiSearchResponse> > {
const queryParameters: any = {};
if (requestParameters['query'] != null) {
queryParameters['query'] = requestParameters['query'];
}
if (requestParameters['neighborChunks'] != null) {
queryParameters['neighbor_chunks'] = requestParameters['neighborChunks'];
}
if (requestParameters['nDocuments'] != null) {
queryParameters['n_documents'] = requestParameters['nDocuments'];
}
if (requestParameters['fullArticles'] != null) {
queryParameters['full_articles'] = requestParameters['fullArticles'];
}
if (requestParameters['hybridSearch'] != null) {
queryParameters['hybrid_search'] = requestParameters['hybridSearch'];
}
if (requestParameters['stringGuarantee'] != null) {
queryParameters['string_guarantee'] = requestParameters['stringGuarantee'];
}
if (requestParameters['diversify'] != null) {
queryParameters['diversify'] = requestParameters['diversify'];
}
if (requestParameters['includeMainSection'] != null) {
queryParameters['include_main_section'] = requestParameters['includeMainSection'];
}
const headerParameters: runtime.HTTPHeaders = {};
const response = await this.request({
path: `/v1/wiki/search`,
method: 'GET',
headers: headerParameters,
query: queryParameters,
}, initOverrides);
return new runtime.JSONApiResponse(response, (jsonValue) => WikiSearchResponseFromJSON(jsonValue));
}
/**
* Search on Wikipedia content with natural language. Find exactly relevant chunks, with contextual neighbor chunks, and the full articles they came from.
* Search for Wikipedia context with natural language
*/
async searchWiki(requestParameters: SearchWikiRequest = {}, initOverrides?: RequestInit | runtime.InitOverrideFunction): Promise<WikiSearchResponse> {
const response = await this.searchWikiRaw(requestParameters, initOverrides);
return await response.value();
}
}