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README.md

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----
-title: Test Space
-emoji: 🚀
-colorFrom: green
-colorTo: yellow
-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
-1. Ensure Salesforce credentials are set as environment variables (`SF_USERNAME`, `SF_PASSWORD`, `SF_SECURITY_TOKEN`, `SF_INSTANCE_URL`).
-2. Deploy on a Hugging Face Space with the free CPU tier.
-3. 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](https://docs.streamlit.io) or [Hugging Face forums](https://discuss.huggingface.co).