Normalized the natural language input of the recipe

[jiyak2804]

Previously, the recipe converter required users to enter ingredients in a strict, predefined format.
This update introduces an improved natural language preprocessing and normalization layer that
automatically extracts structured ingredient data (quantities, units, and items) from free-form
user input.
Now users can write recipes naturally (e.g. “Add one and a half cups of flour and 2 tablespoons sugar”)
and the system will convert them into the standardized format required for accurate unit conversion.

Please include a summary of the changes and the related issue:

1. Enhanced Recipe Normalization System
   New Functions Added:
   normalizeRecipeText() - Main normalization function
   normalizeIngredientLine() - Processes individual lines
   normalizeNumbers() - Converts word numbers to digits/fractions
   normalizeUnits() - Standardizes unit abbreviations
   parseIngredientQuantity() - Extracts quantity, unit, and ingredient
   cleanIngredientName() - Removes instruction words from ingredients
   splitMultipleIngredients() - Handles lines with multiple ingredients

Key Improvements:
Handles multiple input formats:
"2 cups flour" (standard)
"flour 2 tbsp sugar" (ingredient-first)
"Sugar - 1 cup" (punctuation formats)
"mix 2 cups flour" (instruction lines)
"1-2 cups flour" (range quantities)
"one and a half cups milk" (word numbers)

2. Fixed Instruction Detection
   Changes:
   Separated instructions into two categories:
   Mixing instructions (mix, stir, combine, add) - extract ingredients from these
   Cooking instructions (bake, preheat, cook) - skip these completely
   Added recursive processing to remove instruction words and extract ingredients

3. Enhanced Pattern Matching
   Added Patterns For:
   Range quantities: "1-2 cups" → "1 cup"
   Ingredient-first format: "flour 2 tbsp" → "2 tbsp flour"
   Instruction lines: "mix 2 cups flour" → "2 cups flour"
   Punctuation formats: "Sugar - 1 cup" → "1 cup sugar"
   Large ingredients: "2 large eggs" → "2 eggs"
   Word numbers: "one and a half" → "1 1/2"
   Mixed numbers: "1 1/2 cups" proper parsing

4. Improved Conversion Database
   Added Entries:
   Egg variations: 'egg', 'eggs', 'large egg', 'large eggs'
   ML conversions: 'ml water', 'ml milk', 'ml oil', 'ml vanilla extract'
   Small quantities: Proper teaspoon-based weights for spices
   Common ingredients: Added missing entries for better matching

Enhanced Unit Conversions:
Added ML direct conversion (no cup conversion needed)
'milliliter': 'direct', 'milliliters': 'direct', 'ml': 'direct'
5. Better Ingredient Matching Logic
Multiple Matching Strategies:
Exact match - Direct database lookup
Singular version - Remove 's' and try again
Contains match - Database key contained in ingredient
Reverse contains - Ingredient contained in database key
Word-based matching - Split into words and match individually

6. Comprehensive Error Handling
   Added Features:
   Debug functions for troubleshooting
   Warning system for ambiguous conversions
   Better error messages for failed parsing
   Fallback logic for unknown ingredients

7. Test Suite & Debugging
   Added Test Functions:
   runCompleteTestSuite() - Comprehensive testing
   testSpecificCase() - Individual case testing
   debugEggIssue(), debugMilkIssue(), debugMLConversion() - Specific debugging
   quickProblemTest() - Quick validation of known issues

8. Key Bug Fixes
   Fixed Issues: "flour 2 tbsp sugar mix well" → "2 tbsp flour"
   "2-3 eggs" → "2 eggs" (range handling)
   "2 large eggs" → proper conversion
   "one and a half cups milk" → "1 1/2 cups milk"
   "mix 2 cups flour" → "2 cups flour"
   "15 ml oil" → proper ML conversion
   Punctuation formats (colons, dashes, commas)
   Instruction word filtering
   Plural/singular matching

9. Enhanced User Experience
   Improvements:
   Better normalization - Users can input recipes in various formats
   Clearer warnings - Specific information about conversion issues
   Comprehensive testing - Ensures all edge cases work
   Debug tools - Easy troubleshooting for developers

Result:
The recipe converter now handles virtually any input format users might throw at it, from perfectly structured recipes to messy copy-pasted text with instructions, punctuation, and various formatting styles. The system gracefully normalizes everything into a standard format for accurate conversion.

Type of change

• Bug fix
• New feature
• [done ] Improvement
• Documentation update

How Has This Been Tested?

Added testing function at the end as well as check by entering on the webpage :

Checklist:

• [done ] My code follows the style guidelines of this project
• [done ] I have performed a self-review of my code
• [done ] I have commented my code where necessary
• [done ] I have added tests that prove my fix is effective or that my feature works
• I have made corresponding changes to the documentation

[github-actions]

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