This library provides an interface to interact with the Nebuia API, allowing operations for document processing, custom brain searching, and batch management.
- Integrator initialization with API credentials
- Custom brain searching
- Document management (retrieve, clear, delete)
- Batch handling (create, get documents, add files)
- Document type retrieval
[Specific installation instructions for each language]
# Integrator initialization
integrator = Integrator(with_base='http://nebuia.instance/api/v1', key='api_key', secret='api_secret')
# Usage example: Custom brain search
results = integrator.search_in_brain(search_params=SearchParameters(batch="brain_id", param="flu", k=2, type_search="literal"))
# Usage example: Get documents by status
docs = integrator.get_documents_by_status(status=StatusDocument.ERROR_LINK)
# Usage example: Create a new batch
status, batch_id = integrator.create_batch("name_batch", batch_type=BatchType.TESTING)
search_in_brain(search_params: SearchParameters) -> dict
get_documents_by_status(status: StatusDocument) -> list
clear_document_by_uuid(uuid: str) -> dict
delete_document(uuid: str) -> dict
get_documents_by_batch_id(batch_id: str) -> BatchDocuments
append_to_batch(batch_id: str, files: list[File]) -> dict
get_document_types() -> list[DocumentType]
create_batch(name: str, batch_type: BatchType) -> tuple[bool, str]
File
: Represents a file to processSearchParameters
: Parameters for brain searchingStatusDocument
: Enumeration of document statusesBatchType
: Enumeration of batch types
The library uses the Loguru logger to log information and errors. Make sure to configure Loguru appropriately in your application.
- The library should handle API responses and convert them into appropriate data structures for each language.
- Input validations should be implemented for method parameters.
- Error handling should be consistent across all methods, using specific exceptions when appropriate.
[Instructions for contributing to the project]
[License information]