metadata

title: Delay Predictor
emoji: 🚀
colorFrom: indigo
colorTo: indigo
sdk: docker
app_port: 8501
tags:
  - streamlit
  - distilbart
  - project-delay
pinned: false
short_description: Streamlit app for project delay prediction using DistilBART

Project Delay Predictor

This Streamlit app predicts project delays based on task data, workforce, and weather conditions, using DistilBART (sshleifer/distilbart-cnn-6-6) for AI-generated insights. It runs on the free CPU tier of Hugging Face Spaces, generating delay probabilities, insights, and a downloadable PDF report, with integration to Salesforce.

Features

Input project details via a Streamlit interface.
Predict delay probability and generate AI insights.
Visualize delay risk with an interactive Chart.js heatmap.
Save results and PDF to Salesforce.
Download a PDF report.

Setup

Ensure Salesforce credentials are set as environment variables (SF_USERNAME, SF_PASSWORD, SF_SECURITY_TOKEN, SF_INSTANCE_URL).
Deploy on a Hugging Face Space with the free CPU tier.
Access the app at the Space's URL.

Notes

Uses DistilBART for CPU-friendly inference (~5-10 seconds per prediction).
Secure model loading with safetensors and trust_remote_code=False.
Includes logging for debugging and rule-based fallback insights if the model fails.

Troubleshooting

AI Insights Unavailable: Check Space logs for errors (e.g., memory issues, network failures). Restart the Space or reduce max_new_tokens in model.py.
Slow Inference: CPU inference may take ~5-10 seconds. Consider switching to t5-small for faster performance.
Dependency Errors: Ensure all dependencies in requirements.txt are installed correctly.

For questions, refer to Streamlit documentation or Hugging Face forums.