# 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

1. **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.
2. **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.
3. **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.

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### Why Choose Datalake?

1. **Scalable:**\
   Efficiently handles large-scale document operations, accommodating growing data repositories.
2. **Flexible:**\
   Supports multiple document types and retrieval formats, catering to diverse use cases.
3. **AI-Ready:**\
   Prepares documents for AI/ML applications with structured, chunked, or file-based retrievals.
4. **Developer-Friendly:**\
   Provides simple, well-documented API methods for fast and reliable integration.


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