Update README.md

README.md

@@ -20,7 +20,7 @@ This Streamlit app predicts project delays based on task data, workforce, and we
 ## Features
 - Input project details via a Streamlit interface.
 - Predict delay probability and generate AI insights.
-- Visualize delay risk with a heatmap.
+- Visualize delay risk with an interactive Chart.js heatmap.
 - Save results and PDF to Salesforce.
 - Download a PDF report.
 
@@ -32,5 +32,11 @@ This Streamlit app predicts project delays based on task data, workforce, and we
 ## 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).