Package ai.extend

Class AsyncExtendClient

  • public class AsyncExtendClient
extends java.lang.Object

    • Constructor Detail

      • AsyncExtendClient

        public AsyncExtendClient​(ClientOptions clientOptions)

    • Method Detail

      • withRawResponse

        public AsyncRawExtendClient withRawResponse()
        Get responses with HTTP metadata like headers

      • parse

        public java.util.concurrent.CompletableFuture<ParseRun> parse​(ParseRequest request)
        Parse a file synchronously, waiting for the result before returning. This endpoint has a 5-minute timeout — if processing takes longer, the request will fail.

        Note: This endpoint is intended for onboarding and testing only. For production workloads, use POST /parse_runs with polling or webhooks instead, as it provides better reliability for large files and avoids timeout issues.

        The Parse endpoint allows you to convert documents into structured, machine-readable formats with fine-grained control over the parsing process. This endpoint is ideal for extracting cleaned document content to be used as context for downstream processing, e.g. RAG pipelines, custom ingestion pipelines, embeddings classification, etc.

        For more details, see the Parse File guide.

      • parse

        public java.util.concurrent.CompletableFuture<ParseRun> parse​(ParseRequest request,
                                                              RequestOptions requestOptions)
        Parse a file synchronously, waiting for the result before returning. This endpoint has a 5-minute timeout — if processing takes longer, the request will fail.

        Note: This endpoint is intended for onboarding and testing only. For production workloads, use POST /parse_runs with polling or webhooks instead, as it provides better reliability for large files and avoids timeout issues.

        The Parse endpoint allows you to convert documents into structured, machine-readable formats with fine-grained control over the parsing process. This endpoint is ideal for extracting cleaned document content to be used as context for downstream processing, e.g. RAG pipelines, custom ingestion pipelines, embeddings classification, etc.

        For more details, see the Parse File guide.

      • edit

        public java.util.concurrent.CompletableFuture<EditRun> edit​(EditRequest request)
        Edit a file synchronously, waiting for the result before returning. This endpoint has a 5-minute timeout — if processing takes longer, the request will fail.

        Note: This endpoint is intended for onboarding and testing only. For production workloads, use POST /edit_runs with polling or webhooks instead, as it provides better reliability for large files and avoids timeout issues.

        The Edit endpoint allows you to detect and fill form fields in PDF documents.

        For more details, see the Edit File guide.

      • edit

        public java.util.concurrent.CompletableFuture<EditRun> edit​(EditRequest request,
                                                            RequestOptions requestOptions)
        Edit a file synchronously, waiting for the result before returning. This endpoint has a 5-minute timeout — if processing takes longer, the request will fail.

        Note: This endpoint is intended for onboarding and testing only. For production workloads, use POST /edit_runs with polling or webhooks instead, as it provides better reliability for large files and avoids timeout issues.

        The Edit endpoint allows you to detect and fill form fields in PDF documents.

        For more details, see the Edit File guide.

      • extract

        public java.util.concurrent.CompletableFuture<ExtractRun> extract​(ExtractRequest request)
        Extract structured data from a file synchronously, waiting for the result before returning. This endpoint has a 5-minute timeout — if processing takes longer, the request will fail.

        Note: This endpoint is intended for onboarding and testing only. For production workloads, use POST /extract_runs with polling or webhooks instead, as it provides better reliability for large files and avoids timeout issues.

        The Extract endpoint allows you to extract structured data from files using an existing extractor, an inline configuration, or no configuration at all. When neither is provided, Extend automatically infers a schema from the document before extraction — no extractor or schema is required.

        For more details, see the Extract File guide.

      • extract

        public java.util.concurrent.CompletableFuture<ExtractRun> extract​(ExtractRequest request,
                                                                  RequestOptions requestOptions)
        Extract structured data from a file synchronously, waiting for the result before returning. This endpoint has a 5-minute timeout — if processing takes longer, the request will fail.

        Note: This endpoint is intended for onboarding and testing only. For production workloads, use POST /extract_runs with polling or webhooks instead, as it provides better reliability for large files and avoids timeout issues.

        The Extract endpoint allows you to extract structured data from files using an existing extractor, an inline configuration, or no configuration at all. When neither is provided, Extend automatically infers a schema from the document before extraction — no extractor or schema is required.

        For more details, see the Extract File guide.

      • classify

        public java.util.concurrent.CompletableFuture<ClassifyRun> classify​(ClassifyRequest request)
        Classify a document synchronously, waiting for the result before returning. This endpoint has a 5-minute timeout — if processing takes longer, the request will fail.

        Note: This endpoint is intended for onboarding and testing only. For production workloads, use POST /classify_runs with polling or webhooks instead, as it provides better reliability for large files and avoids timeout issues.

        The Classify endpoint allows you to classify documents using an existing classifier or an inline configuration.

        For more details, see the Classify File guide.

      • classify

        public java.util.concurrent.CompletableFuture<ClassifyRun> classify​(ClassifyRequest request,
                                                                    RequestOptions requestOptions)
        Classify a document synchronously, waiting for the result before returning. This endpoint has a 5-minute timeout — if processing takes longer, the request will fail.

        Note: This endpoint is intended for onboarding and testing only. For production workloads, use POST /classify_runs with polling or webhooks instead, as it provides better reliability for large files and avoids timeout issues.

        The Classify endpoint allows you to classify documents using an existing classifier or an inline configuration.

        For more details, see the Classify File guide.

      • split

        public java.util.concurrent.CompletableFuture<SplitRun> split​(SplitRequest request)
        Split a document synchronously, waiting for the result before returning. This endpoint has a 5-minute timeout — if processing takes longer, the request will fail.

        Note: This endpoint is intended for onboarding and testing only. For production workloads, use POST /split_runs with polling or webhooks instead, as it provides better reliability for large files and avoids timeout issues.

        The Split endpoint allows you to split documents into multiple parts using an existing splitter or an inline configuration.

        For more details, see the Split File guide.

      • split

        public java.util.concurrent.CompletableFuture<SplitRun> split​(SplitRequest request,
                                                              RequestOptions requestOptions)
        Split a document synchronously, waiting for the result before returning. This endpoint has a 5-minute timeout — if processing takes longer, the request will fail.

        Note: This endpoint is intended for onboarding and testing only. For production workloads, use POST /split_runs with polling or webhooks instead, as it provides better reliability for large files and avoids timeout issues.

        The Split endpoint allows you to split documents into multiple parts using an existing splitter or an inline configuration.

        For more details, see the Split File guide.