import type { BaseClientOptions, BaseRequestOptions } from "../../../../BaseClient.js";
import { type NormalizedClientOptionsWithAuth } from "../../../../BaseClient.js";
import * as core from "../../../../core/index.js";
import * as SarvamAI from "../../../index.js";
export declare namespace DocAiClient {
    type Options = BaseClientOptions;
    interface RequestOptions extends BaseRequestOptions {
    }
}
export declare class DocAiClient {
    protected readonly _options: NormalizedClientOptionsWithAuth<DocAiClient.Options>;
    constructor(options?: DocAiClient.Options);
    /**
     * Creates a direct-upload handle for a file to be processed later.
     *
     * **Flow:**
     * 1. Call this endpoint with the MIME type you will upload (e.g. `application/pdf`).
     * 2. Upload the file using the returned `method`, `url` and `headers` before `expires_at`.
     * 3. Pass the returned `upload_id` through the `upload_ids` field on a later parse or extract job request.
     *
     * When `content_type` is set, the upload's `Content-Type` header must match it.
     *
     * @param {SarvamAI.DocAiPresignUploadRequest} request
     * @param {DocAiClient.RequestOptions} requestOptions - Request-specific configuration.
     *
     * @throws {@link SarvamAI.BadRequestError}
     * @throws {@link SarvamAI.PaymentRequiredError}
     * @throws {@link SarvamAI.ForbiddenError}
     * @throws {@link SarvamAI.TooManyRequestsError}
     * @throws {@link SarvamAI.ServiceUnavailableError}
     *
     * @example
     *     await client.docAi.createUploadUrl()
     */
    createUploadUrl(request?: SarvamAI.DocAiPresignUploadRequest, requestOptions?: DocAiClient.RequestOptions): core.HttpResponsePromise<SarvamAI.DocAiPresignUploadResponse>;
    private __createUploadUrl;
    /**
     * Creates and starts a parse job from files or pre-uploaded handles. Parse converts documents into structured HTML, Markdown, or JSON while preserving layout.
     *
     * **Input:** Exactly one of `file` and `upload_ids` must be provided. Use `POST /doc-ai/v1/job/upload` to obtain upload IDs.
     *
     * **Processing:** the job runs asynchronously. Poll `GET /doc-ai/v1/job/{job_id}/status` until a terminal status (`completed`, `partially_completed`, `failed`, `rejected`), then fetch output via the results or download-url endpoints.
     *
     * Parse JSON results include blocks with text, tag and bounding box.
     *
     * @param {SarvamAI.DocAiParseRequest} request
     * @param {DocAiClient.RequestOptions} requestOptions - Request-specific configuration.
     *
     * @throws {@link SarvamAI.BadRequestError}
     * @throws {@link SarvamAI.PaymentRequiredError}
     * @throws {@link SarvamAI.ForbiddenError}
     * @throws {@link SarvamAI.ContentTooLargeError}
     * @throws {@link SarvamAI.TooManyRequestsError}
     * @throws {@link SarvamAI.ServiceUnavailableError}
     *
     * @example
     *     import { createReadStream } from "fs";
     *     await client.docAi.parse({})
     */
    parse(request: SarvamAI.DocAiParseRequest, requestOptions?: DocAiClient.RequestOptions): core.HttpResponsePromise<SarvamAI.DocAiStartJobResponse>;
    private __parse;
    /**
     * Creates and starts an extract job from files or pre-uploaded handles. Extract pulls structured fields out of documents according to a schema.
     *
     * **Input:** Exactly one of `file` and `upload_ids` must be provided.
     *
     * **Schema:** exactly one of `schema` (inline JSON schema) and `config_id` (saved extraction configuration) is required.
     *
     * **Processing:** the job runs asynchronously. Poll `GET /doc-ai/v1/job/{job_id}/status` until a terminal status (`completed`, `partially_completed`, `failed`, `rejected`), then fetch output via the results or download-url endpoints.
     *
     * Extract results include `result`, plus `annotations` mirroring the result shape where every leaf has `confidence` and `sources`.
     *
     * @param {SarvamAI.DocAiExtractRequest} request
     * @param {DocAiClient.RequestOptions} requestOptions - Request-specific configuration.
     *
     * @throws {@link SarvamAI.BadRequestError}
     * @throws {@link SarvamAI.PaymentRequiredError}
     * @throws {@link SarvamAI.ForbiddenError}
     * @throws {@link SarvamAI.ContentTooLargeError}
     * @throws {@link SarvamAI.TooManyRequestsError}
     * @throws {@link SarvamAI.ServiceUnavailableError}
     *
     * @example
     *     import { createReadStream } from "fs";
     *     await client.docAi.extract({
     *         schema: "{\"type\":\"object\",\"properties\":{\"policy_number\":{\"type\":\"string\",\"description\":\"Insurance policy number\"},\"insured_name\":{\"type\":\"string\",\"description\":\"Name of the insured person\"},\"sum_insured\":{\"type\":\"number\",\"description\":\"Total sum insured, in INR\"}}}",
     *         output_format: "json"
     *     })
     */
    extract(request: SarvamAI.DocAiExtractRequest, requestOptions?: DocAiClient.RequestOptions): core.HttpResponsePromise<SarvamAI.DocAiStartJobResponse>;
    private __extract;
    /**
     * Creates a Classify job. Classify labels a document, or each page, against the categories you define, or suggests a document type when you supply none.
     *
     * **Input:** send `file` (PDF, PNG, JPEG or TIFF; repeat the field for up to 10 documents) or `upload_ids`, plus a JSON `request` with the options below. You can also send a JSON body with `input` set to `{"document_ref": "..."}` to classify a child document returned by Split.
     *
     * **Processing:** the job runs asynchronously. Poll `GET /doc-ai/v1/job/{job_id}/status` until it is `completed`, then fetch `GET /doc-ai/v1/job/{job_id}/results`. Add `?include=details` to the results for inspected pages, provenance and evidence.
     *
     * **Review:** `review_required` tells you whether a person should check the answer. `confidence` can be `null`; it is a token-based score, not a measured probability.
     *
     * @param {SarvamAI.DocAiClassifyRequest} request
     * @param {DocAiClient.RequestOptions} requestOptions - Request-specific configuration.
     *
     * @throws {@link SarvamAI.BadRequestError}
     * @throws {@link SarvamAI.UnauthorizedError}
     * @throws {@link SarvamAI.NotFoundError}
     * @throws {@link SarvamAI.ConflictError}
     * @throws {@link SarvamAI.UnprocessableEntityError}
     *
     * @example
     *     import { createReadStream } from "fs";
     *     await client.docAi.classify({
     *         request: {}
     *     })
     */
    classify(request: SarvamAI.DocAiClassifyRequest, requestOptions?: DocAiClient.RequestOptions): core.HttpResponsePromise<SarvamAI.DocAiJobAcceptedResponse>;
    private __classify;
    /**
     * Creates a Split job. Split divides a bundle of pages into separate child documents, each with its original page numbers and a `document_ref` you can reuse in other requests.
     *
     * **Methods:** `fixed_pages` (equal page groups), `page_ranges` (you give the boundaries), `triggers` (split at QR codes, barcodes, blank pages, text or photos) and `semantic` (the model finds the boundaries).
     *
     * **Input:** send `file` (PDF, PNG, JPEG or TIFF; repeat the field for up to 10 documents) or `upload_ids`, plus a JSON `request`.
     *
     * **Processing:** the job runs asynchronously. Poll `GET /doc-ai/v1/job/{job_id}/status` until it is `completed`, then fetch `GET /doc-ai/v1/job/{job_id}/results`. `completed` means processing finished, not that every segment passed review: check each segment's `review.required`.
     *
     * @param {SarvamAI.DocAiSplitRequest} request
     * @param {DocAiClient.RequestOptions} requestOptions - Request-specific configuration.
     *
     * @throws {@link SarvamAI.BadRequestError}
     * @throws {@link SarvamAI.UnauthorizedError}
     * @throws {@link SarvamAI.NotFoundError}
     * @throws {@link SarvamAI.ConflictError}
     * @throws {@link SarvamAI.UnprocessableEntityError}
     *
     * @example
     *     import { createReadStream } from "fs";
     *     await client.docAi.split({
     *         request: {}
     *     })
     */
    split(request: SarvamAI.DocAiSplitRequest, requestOptions?: DocAiClient.RequestOptions): core.HttpResponsePromise<SarvamAI.DocAiJobAcceptedResponse>;
    private __split;
    /**
     * Returns a job's status and page-level usage.
     *
     * **Terminal statuses:** `completed`, `partially_completed`, `failed`, `rejected`. Results and download URLs are only available after the job reaches a terminal status.
     *
     * @param {string} job_id - The unique identifier of the job
     * @param {DocAiClient.RequestOptions} requestOptions - Request-specific configuration.
     *
     * @throws {@link SarvamAI.NotFoundError}
     *
     * @example
     *     await client.docAi.getStatus("job_id")
     */
    getStatus(job_id: string, requestOptions?: DocAiClient.RequestOptions): core.HttpResponsePromise<SarvamAI.DocAiJobStatusResponse>;
    private __getStatus;
    /**
     * Returns terminal job results. Results are never available while a job is running; requesting them before a terminal status returns `409`.
     *
     * **Parse results** include `job_id`, `type`, `status`, `usage` and `documents`.
     *
     * **Extract results** include `job_id`, `type`, `status`, `usage`, `result`, `annotations` and `version`. `annotations` mirrors the result shape; every leaf has `confidence` and `sources`.
     *
     * @param {string} job_id - The unique identifier of the job.
     * @param {SarvamAI.DocAiGetResultsRequest} request
     * @param {DocAiClient.RequestOptions} requestOptions - Request-specific configuration.
     *
     * @throws {@link SarvamAI.NotFoundError}
     * @throws {@link SarvamAI.ConflictError}
     *
     * @example
     *     await client.docAi.getResults("20260707_6eb74174-e2c3-490d-afe5-d2e7e9e2b6c7", {
     *         format: "json"
     *     })
     *
     * @example
     *     await client.docAi.getResults("20260707_9f1c2b3a-4d5e-6f70-8a9b-c0d1e2f3a4b5", {
     *         format: "json"
     *     })
     *
     * @example
     *     await client.docAi.getResults("01a17998-120b-73dc-ad42-5cd66e0fe0ff")
     *
     * @example
     *     await client.docAi.getResults("01a17998-07ef-7040-800d-745a95140cf5")
     */
    getResults(job_id: string, request?: SarvamAI.DocAiGetResultsRequest, requestOptions?: DocAiClient.RequestOptions): core.HttpResponsePromise<SarvamAI.DocAiGetResultsResponse>;
    private __getResults;
    /**
     * Creates a download URL for a completed job's output. Download the output using the returned `method`, `url` and `headers` before `expires_at`.
     *
     * Requesting a download URL before the job reaches a terminal status returns `409`.
     *
     * @param {string} job_id - The unique identifier of the job
     * @param {DocAiClient.RequestOptions} requestOptions - Request-specific configuration.
     *
     * @throws {@link SarvamAI.NotFoundError}
     * @throws {@link SarvamAI.ConflictError}
     *
     * @example
     *     await client.docAi.getDownloadUrl("job_id")
     */
    getDownloadUrl(job_id: string, requestOptions?: DocAiClient.RequestOptions): core.HttpResponsePromise<SarvamAI.DocAiDownloadUrlResponse>;
    private __getDownloadUrl;
    /**
     * Returns the Classify and Split features, input formats, limits and options enabled on this deployment. Check it before using options such as `reasoning_input` image modes or photo triggers.
     *
     * @param {DocAiClient.RequestOptions} requestOptions - Request-specific configuration.
     *
     * @throws {@link SarvamAI.UnauthorizedError}
     *
     * @example
     *     await client.docAi.getCapabilities()
     */
    getCapabilities(requestOptions?: DocAiClient.RequestOptions): core.HttpResponsePromise<SarvamAI.DocAiCapabilitiesResponse>;
    private __getCapabilities;
}