---
title: Algae Yield Predictor
emoji: 🌱
colorFrom: green
colorTo: blue
sdk: gradio
sdk_version: 5.46.1
app_file: app.py
pinned: false
license: cc-by-nc-nd-4.0
python_version: "3.11"
---

# Algae Yield Predictor

This Space provides an interactive interface to predict algal biomass, lipid, protein, and carbohydrate yields under different culture conditions.

The app uses real experimental data, augmented target-specific datasets, and saved ensemble models to provide model predictions, local uncertainty intervals, response plots, species-medium constraints, and optional DOI-based literature matches.

## Main features

- Targets: biomass, lipid, protein, carbohydrate
- Species-medium aware dropdowns
- Curated suggested conditions by species and target
- Selectable model: STACK, XGB, LGBM, CAT, MLP
- Local uncertainty intervals from augmented-data nearest neighbors
- Response plots for light, days, pH, temperature, day exposure, and night exposure
- Optional DOI matching from `doi.csv`
- Literature-range clamping for biologically plausible outputs

## Required repository files

The following files/folders must be present in the Space repository root:

```text
app.py
README.md
requirements.txt
pre-requirements.txt
runtime.txt
ai_al.csv
doi.csv                         # optional
augmented_biomass_200k.csv       # or augmented_biomass_20k.csv
augmented_lipid_200k.csv         # or augmented_lipid_20k.csv
augmented_protein_200k.csv       # or augmented_protein_20k.csv
augmented_carb_200k.csv          # or augmented_carb_20k.csv
models/
  biomass/
  lipid/
  protein/
  carb/
```

Each target model folder should contain the saved model artifacts expected by `app.py`, including encoders, imputer, config, base learners, MLP model, and meta model.

## Deployment notes

This Space is pinned to Python 3.11 because the scientific stack used here is much more reliable on Python 3.11 than Python 3.13. Python 3.13 may force source builds for packages such as pandas or create compatibility issues with TensorFlow and compiled ML libraries.

After uploading these fixed files, use **Factory reboot** in Hugging Face Spaces to clear the old build cache.

## Citation

If you use this predictor or dataset, please cite:

Tiwari, A., Dubey, S., Sumathi, Y., Patel, A. K., & Kuo, T.-R. (2025). *Augmented and Real Microalgae Datasets for Biomass and Biochemical Composition Prediction* [Data set]. Zenodo. https://doi.org/10.5281/zenodo.17177597