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SAP Finance Dashboard with RPT-1-OSS Model

A comprehensive financial dashboard application built with Gradio that integrates the SAP-RPT-1-OSS model for predictive analysis on SAP finance datasets. Features include synthetic data generation, interactive visualizations, OData connectivity, AI-powered insights, and a playground for training custom models.

Features

  • Multiple Synthetic SAP Finance Datasets: General Ledger accounts, Financial Statements (P&L, Balance Sheet), and Sales Orders
  • Data Upload: Upload custom CSV, Parquet, or JSON datasets for analysis
  • Interactive Visualizations: Financial charts and graphs using Plotly
  • SAP-RPT-1-OSS Model Integration: AI-powered predictions and analysis
  • Live OData Connection: Connect to SAP systems to fetch real-time sales order data
  • Playground Tab: Upload datasets, configure model parameters, train, and download predictions
  • Modern UI: Built with Gradio, a Python-based web framework

Installation

Prerequisites

  • Python 3.11 or higher
  • Hugging Face account (for model access)
  • SAP OData credentials (optional, for live data connection)

Setup Steps

  1. Clone the repository:

    git clone <repository-url>
cd SAP-RPT-1-OSS-App

  2. Create a virtual environment:

    python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

  3. Install dependencies:

    pip install -r requirements.txt

  4. Install SAP-RPT-OSS package:

    pip install git+https://github.com/SAP-samples/sap-rpt-1-oss

  5. Set up environment variables:

    • Copy .env.example to .env
    • Fill in your SAP OData credentials
    • Add your Hugging Face token for model access

  6. Authenticate with Hugging Face:

    pip install huggingface_hub
huggingface-cli login

    Or set the HUGGINGFACE_TOKEN in your .env file.

  7. Generate synthetic data (optional, if not already generated):

    python -c "from utils.data_generator import generate_all_datasets; generate_all_datasets()"

Usage

Running the Application

Start the Gradio application:

python app_gradio.py

The application will be available at http://localhost:7862 (default Gradio port).

Application Tabs

  1. Dashboard: Overview with key financial metrics and visualizations
  2. Data Explorer: Browse and filter datasets (GL, Financial Statements, Sales Orders)
  3. Upload: Upload custom CSV datasets for analysis
  4. Predictions: Use SAP-RPT-1-OSS model for predictions and analysis with pre-configured scenarios
  5. OData: Connect to SAP OData services and fetch live data
  6. Playground: Upload datasets, configure model parameters (task type, target column, test split, context size, bagging, GPU), train models, and download predictions

SAP OData Connection Setup

  1. Set the following environment variables in your .env file:

    • SAP_USERNAME: Your SAP username
    • SAP_PASSWORD: Your SAP password
    • SAP_SERVER: SAP server URL (default: https://sapes5.sapdevcenter.com/)
    • SAP_CLIENT: SAP client number (default: 002)

  2. The OData connector uses the base URL: https://sapes5.sapdevcenter.com/sap/opu/odata/IWBEP/GWSAMPLE_BASIC

  3. Available endpoints:

    • Sales Orders: SalesOrderSet
    • Products: ProductSet
    • Line Items: SalesOrderLineItemSet
    • Business Partners: BusinessPartnerSet

Model Configuration

The SAP-RPT-1-OSS model supports both classification and regression tasks. For best performance:

  • Recommended: GPU with at least 80 GB memory, context size 8192, bagging factor 8
  • Lightweight: CPU with context size 2048, bagging factor 1

The application automatically detects available resources and adjusts settings accordingly.

Deployment

GitHub Pages

Since Gradio requires a Python backend, GitHub Pages deployment requires alternative approaches:

  1. GitHub Actions: Set up a workflow to run the Gradio app as a service
  2. Alternative Hosting: Deploy to platforms that support Python web apps:
    • Hugging Face Spaces (recommended for Gradio apps)
    • Streamlit Cloud
    • Heroku
    • Railway
    • Render

Deploy to Hugging Face Spaces

The easiest way to deploy this Gradio app is using Hugging Face Spaces:

  1. Create a new Space on Hugging Face Spaces
  2. Select "Gradio" as the SDK
  3. Push this repository to your Space
  4. Add your HUGGINGFACE_TOKEN as a secret in Space settings
  5. The app will automatically deploy

See .github/workflows/deploy.yml for deployment configuration examples.

Project Structure 

SAP-RPT-1-OSS-App/
├── app_gradio.py         # Main Gradio application
├── models/
│   └── rpt_model.py      # SAP-RPT-1-OSS model wrapper
├── data/
│   ├── synthetic_gl_accounts.csv
│   ├── synthetic_financial_statements.csv
│   └── synthetic_sales_orders.csv
├── utils/
│   ├── data_generator.py # Generate synthetic SAP finance data
│   ├── visualizations.py # Chart generation functions
│   ├── odata_connector.py # OData connection utilities
│   └── playground.py     # Playground utilities for model training
├── requirements.txt
├── README.md
└── .env.example

License

This project is licensed under the Apache Software License, version 2.0.

Support

For issues or questions, please create an issue in this repository.

Acknowledgments