Update README.md

README.md

@@ -1,26 +1,26 @@
 ---
-title: SmartFit AI Biological Engine
+title: SmartFit
 emoji: 🏋️
 colorFrom: blue
 colorTo: green
 sdk: gradio
-sdk_version: 6.3.0
+sdk_version: 5.0.0
 app_file: app.py
 pinned: false
 license: mit
 ---
 
-# SmartFit AI - Biological Engine
+# SmartFit
 
-This is an advanced AI workout generator powered by a Random Forest model trained on synthetic data.
-It takes into account age, gender, injuries, and goals to build a personalized routine.
+This application utilizes a Random Forest machine learning model trained on a synthetic dataset of 10,000 user profiles to generate personalized workout routines. The system analyzes biological factors including age, gender, weight, and injuries to construct a tailored training regimen customized to the user's specific goals and equipment availability.
 
-### How to use
-1. Enter your biological details (Age, Gender, Weight).
-2. Select your Goal and Available Equipment.
-3. **Click Submit** to get a full workout plan!
+## Usage Instructions
+1. **Input Details:** Enter your biological metrics (Age, Gender, Weight, Height).
+2. **Configuration:** Select your desired Fitness Goal, Available Equipment, and Experience Level.
+3. **Safety:** Indicate any active injuries to adjust the exercise selection logic.
+4. **Generate:** Click Submit to receive a full, step-by-step workout plan.
 
-###  Model Info
-* **Type:** Random Forest Classifier
-* **Training Data:** 10,000 Synthetic User Profiles
-* **Accuracy:** ~90% on test set
+## Model Specifications
+* **Architecture:** Random Forest Classifier
+* **Training Data:** 10,000 Synthetic User Profiles (SmartFit Dataset)
+* **Logic Engine:** Python-based rule engine for load calculation and injury management.