Update README.md

README.md

@@ -1,62 +1,73 @@
-# ModelSmith AI
-
-An intelligent ML platform that automates tabular classification and regression tasks. It analyzes datasets, recommends optimal strategies, trains models, and provides explanations.
-
-## Features
-
-- **Dataset Analysis**: Automatic detection of data types, missing values, and potential issues
-- **Strategy Reasoning**: Intelligent model selection based on dataset characteristics
-- **Automated Training**: End-to-end model training with preprocessing pipelines
-- **Explainability**: SHAP-based feature importance explanations
-- **FastAPI Backend**: RESTful API for seamless integration
-
-## Supported Scope
-
-- **Task**: Tabular classification and regression
-- **Input**: CSV files with ≥1200 rows
-- **Target**: Binary or multiclass classification, regression
-- **Features**: At least 2 usable features after preprocessing
-
-## API Endpoints
-
-- `POST /analyze`: Analyze dataset and get strategy recommendations
-- `POST /train`: Train a model on the dataset
-- `POST /explain`: Get model explanations and feature importance
-- `POST /predict`: Make predictions with trained model
-- `GET /health`: Health check
-
-## Deployment
-
-This project is designed for deployment on Hugging Face Spaces using Docker.
-
-### Files for Deployment
-
-- `Dockerfile`
-- `requirements.txt`
-- `backend/` (entire directory)
-
-### Running Locally
-
-```bash
-pip install -r requirements.txt
-uvicorn backend.api.main:app --host 0.0.0.0 --port 7860
-```
-
-## Limitations
-
-- NLP functionality is disabled
-- Requires datasets with ≥1200 rows
-- CPU-only, no GPU support
-- Stateless API (models saved temporarily)
-
-## Architecture
-
-- **Orchestrator**: Main workflow coordinator
-- **Dataset Analyzer**: Data profiling and preprocessing
-- **Strategy Reasoner**: Model selection logic
-- **Model Factory**: Training and evaluation
-- **Explainability Engine**: SHAP explanations
-
-## License
-
-MIT License
+---
+title: ModelSmith AI
+emoji: 🤖
+colorFrom: blue
+colorTo: green
+sdk: gradio
+sdk_version: "4.0.0"
+app_file: app.py
+pinned: false
+---
+
+# ModelSmith AI
+
+An intelligent ML platform that automates tabular classification and regression tasks. It analyzes datasets, recommends optimal strategies, trains models, and provides explanations.
+
+## Features
+
+- **Dataset Analysis**: Automatic detection of data types, missing values, and potential issues
+- **Strategy Reasoning**: Intelligent model selection based on dataset characteristics
+- **Automated Training**: End-to-end model training with preprocessing pipelines
+- **Explainability**: SHAP-based feature importance explanations
+- **FastAPI Backend**: RESTful API for seamless integration
+
+## Supported Scope
+
+- **Task**: Tabular classification and regression
+- **Input**: CSV files with ≥1200 rows
+- **Target**: Binary or multiclass classification, regression
+- **Features**: At least 2 usable features after preprocessing
+
+## API Endpoints
+
+- `POST /analyze`: Analyze dataset and get strategy recommendations
+- `POST /train`: Train a model on the dataset
+- `POST /explain`: Get model explanations and feature importance
+- `POST /predict`: Make predictions with trained model
+- `GET /health`: Health check
+
+## Deployment
+
+This project is designed for deployment on Hugging Face Spaces using Docker.
+
+### Files for Deployment
+
+- `Dockerfile`
+- `requirements.txt`
+- `backend/` (entire directory)
+
+### Running Locally
+
+```bash
+pip install -r requirements.txt
+uvicorn backend.api.main:app --host 0.0.0.0 --port 7860
+```
+
+## Limitations
+
+- NLP functionality is disabled
+- Requires datasets with ≥1200 rows
+- CPU-only, no GPU support
+- Stateless API (models saved temporarily)
+
+## Architecture
+
+- **Orchestrator**: Main workflow coordinator
+- **Dataset Analyzer**: Data profiling and preprocessing
+- **Strategy Reasoner**: Model selection logic
+- **Model Factory**: Training and evaluation
+- **Explainability Engine**: SHAP explanations
+
+## License
+
+MIT License