Update README.md

README.md

@@ -4,40 +4,16 @@ sdk_version: 1.49.1
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 # TGA Graph Interpreter
 
-A Streamlit app to analyze Thermogravimetric Analysis (TGA) data.
+This Streamlit app helps researchers analyze and describe **Thermogravimetric Analysis (TGA)** graphs.
 
-## Features
-- Upload TGA data in **CSV** or **Excel** format:
-  - First column = Temperature (°C)
-  - Remaining columns = Weight (%) for each thermogram
-  - Column headers are used as labels (legends)
-- Supports multiple thermograms in a single file
-- Provides analysis for each thermogram:
-  - Onset temperature
-  - Peak degradation temperature
-  - % weight loss
-- Optional image upload (PNG/JPG) for visualization only
+## 🔹 Features
+- Upload one or more TGA thermograms (PNG, JPG, JPEG, PDF).  
+- Enter onset temperature, peak degradation temperature, weight loss %, and residue %.  
+- The app generates a **structured discussion** for each thermogram in a research-paper style.  
+- Results are displayed under a **Discussion** section for easy copy-paste into publications.  
 
-## File Structure
-- `app.py`: Streamlit app
-- `requirements.txt`: Python dependencies
-- `Dockerfile`: Hugging Face Docker build setup
-- `README.md`: Project documentation
-
-## Usage
-1. Open the app in Hugging Face Spaces.
-2. Upload your TGA dataset:
-   - CSV or Excel file with columns as described above.
-3. View results for each thermogram separately.
-4. Optionally, upload a TGA graph image for display.
-
-## Example CSV format
-```csv
-Temperature, Sample1, Sample2
-25, 100, 100
-100, 98, 97
-200, 85, 82
-300, 60, 55
-400, 55, 50
-500, 50, 45
+## 🚀 How to Run (Locally)
+```bash
+pip install -r requirements.txt
+streamlit run app.py