---
title: rainfall
emoji: 👀
colorFrom: purple
colorTo: red
sdk: gradio
sdk_version: 5.27.1
app_file: app.py
pinned: false
hf_oauth: true
---
# Rainfall Prediction with LSTM and Gemma 2 Interpretation

This application predicts daily rainfall based on weather features (temperature, humidity, and sunshine duration) using an LSTM model, and provides a natural language interpretation of the prediction using the Gemma 2-27B language model from Google via Hugging Face Inference API.

---

## 📊 Features

- ✅ Predicts daily **rainfall (mm)** from 3 key weather inputs.
- 🧠 Uses an **LSTM neural network** trained on historical weather data.
- 💬 Generates **automatic explanation and recommendations** using **Gemma 2-27B** (`google/gemma-2-27b-it`) via Hugging Face `InferenceClient`.
- 🌐 Built with **Gradio UI** for easy interaction.

---

## 🧪 Input Parameters

| Parameter                  | Description                              |
|---------------------------|------------------------------------------|
| Average Temperature (°C)  | Daily mean temperature in Celsius        |
| Relative Humidity (%)     | Average daily relative humidity          |
| Sunshine Duration (hours) | Total sunlight duration during the day   |

---

## 🧮 Output

- **Predicted Rainfall (mm)**: Estimated rainfall amount based on inputs.
- **Interpretation**: AI-generated weather explanation using LLM (Gemma 2-27B), including suggestions for outdoor activities.

---

## 🚀 Getting Started (for Deployment)

1. **Prepare the required files**:
   - `app.py` — main app
   - `retrained_lstm_model.h5` — trained LSTM model
   - `scaler_X.joblib`, `scaler_y.joblib` — scalers used for input/output normalization

2. **Add Hugging Face token to Space secrets**:
   - Go to your Hugging Face Space → **Settings > Secrets**
   - Add a secret:
     - **Name**: `HF_TOKEN`
     - **Value**: *your Hugging Face API token*

3. **Install dependencies** using `requirements.txt`:
   ```txt
   tensorflow>=2.8.0
   numpy>=1.19.5
   pandas>=1.3.5
   scikit-learn>=1.0.2
   joblib>=1.1.0
   gradio>=3.20.0
   huggingface_hub>=0.18.0

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference