Remove test and setup files

setup.bat

@@ -1,89 +0,0 @@
-@echo off
-REM Geospatial AI Query System - Quick Start Script (Windows)
-REM This script helps you set up and run the application locally
-
-echo ================================
-echo Geospatial AI Query System - Setup
-echo ================================
-echo.
-
-REM Check Python version
-echo Checking Python version...
-python --version >nul 2>&1
-if errorlevel 1 (
-    echo [ERROR] Python 3 is not installed. Please install Python 3.8 or higher.
-    pause
-    exit /b 1
-)
-python --version
-echo [OK] Python found
-echo.
-
-REM Create virtual environment
-echo Creating virtual environment...
-if not exist "venv" (
-    python -m venv venv
-    echo [OK] Virtual environment created
-) else (
-    echo [OK] Virtual environment already exists
-)
-echo.
-
-REM Activate virtual environment
-echo Activating virtual environment...
-call venv\Scripts\activate.bat
-echo [OK] Virtual environment activated
-echo.
-
-REM Upgrade pip
-echo Upgrading pip...
-python -m pip install --upgrade pip >nul 2>&1
-echo [OK] Pip upgraded
-echo.
-
-REM Install requirements
-echo Installing dependencies...
-echo This may take a few minutes...
-pip install -r requirements.txt
-if errorlevel 1 (
-    echo [ERROR] Failed to install dependencies
-    pause
-    exit /b 1
-)
-echo [OK] All dependencies installed successfully
-echo.
-
-REM Check for HF_TOKEN
-echo Checking for Hugging Face token...
-if "%HF_TOKEN%"=="" (
-    echo [WARNING] HF_TOKEN not set (optional for testing)
-    echo    To enable LLM features, get a token from:
-    echo    https://huggingface.co/settings/tokens
-    echo    Then run: set HF_TOKEN=your_token_here
-) else (
-    echo [OK] HF_TOKEN found
-)
-echo.
-
-REM Run tests
-echo Running tests...
-pytest test_app.py -v
-if errorlevel 1 (
-    echo [WARNING] Some tests failed (app may still work)
-) else (
-    echo [OK] All tests passed
-)
-echo.
-
-REM Start application
-echo ================================
-echo Starting application...
-echo ================================
-echo.
-echo The app will be available at:
-echo http://localhost:7860
-echo.
-echo Press Ctrl+C to stop the application
-echo.
-
-python app.py

setup.sh

@@ -1,87 +0,0 @@
-#!/bin/bash
-
-# Geospatial AI Query System - Quick Start Script
-# This script helps you set up and run the application locally
-
-echo "🌍 Geospatial AI Query System - Setup"
-echo "======================================"
-echo ""
-
-# Check Python version
-echo "Checking Python version..."
-python_version=$(python3 --version 2>&1)
-if [[ $? -ne 0 ]]; then
-    echo "❌ Python 3 is not installed. Please install Python 3.8 or higher."
-    exit 1
-fi
-echo "✅ Found: $python_version"
-echo ""
-
-# Create virtual environment
-echo "Creating virtual environment..."
-if [ ! -d "venv" ]; then
-    python3 -m venv venv
-    echo "✅ Virtual environment created"
-else
-    echo "✅ Virtual environment already exists"
-fi
-echo ""
-
-# Activate virtual environment
-echo "Activating virtual environment..."
-source venv/bin/activate
-echo "✅ Virtual environment activated"
-echo ""
-
-# Upgrade pip
-echo "Upgrading pip..."
-pip install --upgrade pip > /dev/null 2>&1
-echo "✅ Pip upgraded"
-echo ""
-
-# Install requirements
-echo "Installing dependencies..."
-echo "This may take a few minutes..."
-pip install -r requirements.txt
-if [[ $? -eq 0 ]]; then
-    echo "✅ All dependencies installed successfully"
-else
-    echo "❌ Failed to install dependencies"
-    exit 1
-fi
-echo ""
-
-# Check for HF_TOKEN
-echo "Checking for Hugging Face token..."
-if [ -z "$HF_TOKEN" ]; then
-    echo "⚠️  HF_TOKEN not set (optional for testing)"
-    echo "   To enable LLM features, get a token from:"
-    echo "   https://huggingface.co/settings/tokens"
-    echo "   Then run: export HF_TOKEN=your_token_here"
-else
-    echo "✅ HF_TOKEN found"
-fi
-echo ""
-
-# Run tests
-echo "Running tests..."
-pytest test_app.py -v
-if [[ $? -eq 0 ]]; then
-    echo "✅ All tests passed"
-else
-    echo "⚠️  Some tests failed (app may still work)"
-fi
-echo ""
-
-# Start application
-echo "======================================"
-echo "🚀 Starting application..."
-echo "======================================"
-echo ""
-echo "The app will be available at:"
-echo "http://localhost:7860"
-echo ""
-echo "Press Ctrl+C to stop the application"
-echo ""
-
-python app.py

test_app.py

@@ -1,173 +0,0 @@
-"""
-Test suite for Geospatial AI Query System
-Run: pytest test_app.py
-"""
-
-import pytest
-import pandas as pd
-import geopandas as gpd
-from pathlib import Path
-from data_utils import DataEnhancer, QueryEnhancer, GeoStats
-
-# Path to local Natural Earth data (geopandas.datasets was deprecated in GeoPandas 1.0)
-DATA_DIR = Path(__file__).parent / "data" / "ne_110m_admin_0_countries"
-NATURAL_EARTH_SHP = DATA_DIR / "ne_110m_admin_0_countries.shp"
-
-class TestDataEnhancer:
-    """Test data enhancement utilities"""
-    
-    def test_economic_data_structure(self):
-        """Test economic data has correct structure"""
-        data = DataEnhancer.get_sample_economic_data()
-        assert isinstance(data, dict)
-        assert 'United States' in data
-        assert 'gdp_growth' in data['United States']
-        assert 'unemployment' in data['United States']
-        assert 'inflation' in data['United States']
-    
-    def test_environmental_data_structure(self):
-        """Test environmental data has correct structure"""
-        data = DataEnhancer.get_sample_environmental_data()
-        assert isinstance(data, dict)
-        assert 'China' in data
-        assert 'co2_per_capita' in data['China']
-        assert 'renewable_energy' in data['China']
-    
-    def test_enrich_dataframe(self):
-        """Test dataframe enrichment"""
-        # Create sample dataframe
-        df = pd.DataFrame({
-            'name': ['United States', 'China', 'Germany'],
-            'pop_est': [331000000, 1440000000, 83000000],
-            'gdp_md_est': [21000000, 14000000, 3800000]
-        })
-        
-        enriched = DataEnhancer.enrich_dataframe(df, 'economic')
-        assert 'gdp_growth' in enriched.columns
-        assert enriched.loc[enriched['name'] == 'United States', 'gdp_growth'].iloc[0] == 2.1
-
-class TestQueryEnhancer:
-    """Test query enhancement utilities"""
-    
-    def test_expand_continent(self):
-        """Test continent expansion"""
-        result = QueryEnhancer.expand_location('asia')
-        assert result == ['Asia']
-        
-    def test_expand_country_group_brics(self):
-        """Test BRICS expansion"""
-        result = QueryEnhancer.expand_location('brics')
-        assert 'Brazil' in result
-        assert 'India' in result
-        assert 'China' in result
-        assert len(result) == 5
-    
-    def test_expand_country_group_g7(self):
-        """Test G7 expansion"""
-        result = QueryEnhancer.expand_location('g7')
-        assert 'United States of America' in result
-        assert 'Japan' in result
-        assert len(result) == 7
-    
-    def test_validate_indicators(self):
-        """Test indicator validation"""
-        indicators = ['GDP', 'Population', 'CO2 emissions']
-        result = QueryEnhancer.validate_indicators(indicators)
-        assert 'gdp_md_est' in result
-        assert 'pop_est' in result
-
-class TestGeoStats:
-    """Test statistical utilities"""
-    
-    def test_calculate_correlation(self):
-        """Test correlation calculation"""
-        df = pd.DataFrame({
-            'col1': [1, 2, 3, 4, 5],
-            'col2': [2, 4, 6, 8, 10]
-        })
-        corr = GeoStats.calculate_correlation(df, 'col1', 'col2')
-        assert corr == 1.0  # Perfect positive correlation
-    
-    def test_summary_stats(self):
-        """Test summary statistics"""
-        df = pd.DataFrame({
-            'values': [10, 20, 30, 40, 50]
-        })
-        stats = GeoStats.generate_summary_stats(df, 'values')
-        assert stats['mean'] == 30.0
-        assert stats['median'] == 30.0
-        assert stats['min'] == 10
-        assert stats['max'] == 50
-
-class TestIntegration:
-    """Integration tests"""
-    
-    def test_world_data_loading(self):
-        """Test loading world data"""
-        world = gpd.read_file(NATURAL_EARTH_SHP)
-        assert not world.empty
-        assert 'NAME' in world.columns or 'name' in world.columns
-        assert 'CONTINENT' in world.columns or 'continent' in world.columns
-        assert 'POP_EST' in world.columns or 'pop_est' in world.columns
-    
-    def test_query_to_data_pipeline(self):
-        """Test complete query to data pipeline"""
-        # Load data
-        world = gpd.read_file(NATURAL_EARTH_SHP)
-        
-        # Normalize column names to lowercase
-        world.columns = world.columns.str.lower()
-        
-        # Expand query
-        locations = QueryEnhancer.expand_location('brics')
-        
-        # Filter data (try both 'name' and 'admin' columns)
-        name_col = 'name' if 'name' in world.columns else 'admin'
-        filtered = world[world[name_col].isin(locations)]
-        
-        assert not filtered.empty
-        assert len(filtered) > 0
-        
-    def test_data_enrichment_pipeline(self):
-        """Test data enrichment pipeline"""
-        # Load data
-        world = gpd.read_file(NATURAL_EARTH_SHP)
-        
-        # Normalize column names to lowercase
-        world.columns = world.columns.str.lower()
-        
-        # Take sample
-        sample = world.head(10)
-        
-        # Enrich
-        enriched = DataEnhancer.enrich_dataframe(sample, 'economic')
-        
-        assert 'gdp_growth' in enriched.columns
-        assert 'unemployment' in enriched.columns
-
-# Sample query test cases
-SAMPLE_QUERIES = [
-    "Show me population of Asian countries",
-    "Compare GDP of European nations",
-    "What's the population density in Africa?",
-    "Display economic indicators for South American countries",
-    "Show me top 10 countries by GDP",
-    "Compare BRICS nations",
-    "Environmental data for G7 countries"
-]
-
-class TestQueryParsing:
-    """Test query parsing (mock LLM responses)"""
-    
-    def test_query_keywords(self):
-        """Test that queries contain expected keywords"""
-        for query in SAMPLE_QUERIES:
-            assert len(query) > 0
-            assert any(continent in query.lower() for continent in 
-                        ['asian', 'european', 'africa', 'south american', 'brics', 'g7']) or \
-                   any(indicator in query.lower() for indicator in 
-                        ['population', 'gdp', 'economic', 'environmental'])
-
-if __name__ == "__main__":
-    # Run tests
-    pytest.main([__file__, '-v'])