Datalake
The Datalake Library is a Python-based integration tool designed to simplify document storage, retrieval, and management within your product catalog or data repository. It provides a straightforward interface to interact with the Datalake API endpoints, enabling developers to create, fetch, and push documents with ease. This library empowers businesses to optimize their workflows for document handling, making it ideal for applications such as file-based catalog management, document chunking, and metadata-enriched operations.
By leveraging the capabilities of Datalake, businesses can efficiently manage and utilize their document repositories, enabling context-aware and structured workflows for enhanced productivity and data intelligence.
Key Features
Creating Datalake: Generate a new document entry in the system using the datalake/create method, allowing you to define and structure your data repository efficiently.
Document Fetching: Retrieve documents or their specific formats (chunked, file, JSON, or filepath) with the document/fetch method, enabling seamless integration into downstream applications and workflows.
Upload Document: Push documents (PDF, XLSX, JSON) into the system with associated metadata using the document/push method, making them readily available for future operations.
Why Choose Datalake?
Scalable: Efficiently handles large-scale document operations, accommodating growing data repositories.
Flexible: Supports multiple document types and retrieval formats, catering to diverse use cases.
AI-Ready: Prepares documents for AI/ML applications with structured, chunked, or file-based retrievals.
Developer-Friendly: Provides simple, well-documented API methods for fast and reliable integration.
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