Outcomes

Upon successful completion, the SynthDataGen project will deliver the following tangible outcomes and assets:

1. Software Deliverables:

  • Core Python Library: A well-structured Python package containing all the logic for document processing, Q\&A generation, and database interaction.
  • Python SDK: A high-level Software Development Kit (SDK) that provides simple, programmatic access to the system's capabilities for easy integration into other applications.

2. Data & Storage Deliverables:

  • Populated PostgreSQL Database: A running database instance containing the generated Q\&A pairs, source document information, and all related metadata, structured according to the defined schema.
  • Standardized JSON Export: The system will produce a dataset in a JSON file format (e.g., JSON Lines) that is immediately compatible with standard ML fine-tuning frameworks like the Hugging Face datasets library.

3. Documentation Deliverables:

  • MkDocs Project Website: A comprehensive documentation site that includes:
  • Installation Guide: Instructions on how to set up the project environment, database, and dependencies.
  • User Guide & Tutorials: Step-by-step guides on how to use the system, from adding documents to exporting a dataset.
  • SDK API Reference: Auto-generated, detailed documentation of all public classes and functions available in the SDK.
  • Architectural Overview: A brief description of the system's components and data flow.

4. Project Artefacts:

  • Version-Controlled Source Code: The complete source code hosted in a Git repository.
  • Project Planning Documents: The suite of documents created for this project (Summary, BRD, User Stories, etc.) serves as a reference for current and future development.