Fix endpoint to use user-provided budget_amount even when has_previous_data is true

Add debug logging to track budget_amount usage and ensure user-provided amount is used

Fix average_expense to use user-provided budget_amount and enhance OpenAI prompt to recommend decrease when budget is too high

Enhance OpenAI prompt to explicitly mention user's budget amount and base recommendations on it

Fix undefined variable error and ensure user-provided budget_amount is used for OpenAI recommendations

Prioritize user-provided budget_amount over budget's maxAmount when category_id is a budget _id

Fix get_recommendation_for_category to generate recommendations when category_id is a budget _id

Add logic to handle budget _id in get_recommendation_for_category - extract categories and generate recommendations

Fix remaining indentation syntax errors

Fix syntax errors: indentation issues

Remove all excessive debug logs from check_user_has_category_data

Fix budget _id check logic and remove excessive debug logs

Add check for budget _id when category_id is provided - handle case where user passes budget ID instead of category ID

Add multiple nested query patterns to check_user_has_category_data for better MongoDB compatibility

Prioritize nested category structure check in check_user_has_category_data

Add comprehensive debug logging for expense checking in check_user_has_category_data

Add detailed debug logging to understand budget category structure and why category_ids are not being matched

Add new endpoint /recommendations/by-name to accept Head Category names instead of category_id for easier frontend integration

Fix UnboundLocalError: calculate monthly statistics from budgets when data variable doesn't exist

Improve check_user_has_category_data to comprehensively search budgets collection and fix logic to prioritize historical data over budget_amount

Add explicit instructions and system message to ensure OpenAI provides unique reasons for each recommendation

Remove simulated data creation - recommendations for new budgets now based on provided budget_amount and category knowledge only, not fake trends

Change budget_amount validation to auto-cap corrupted data instead of rejecting requests

Enhance OpenAI prompt to analyze actual spending data (trends, variability) for intelligent recommendations

Add API-level validation for budget_amount to catch corrupted data early and provide clear error messages

Add aggressive final validation to ALWAYS prevent lazy 'keep' recommendations and handle data corruption

Add validation to prevent always 'keep' recommendations - override lazy OpenAI responses with intelligent analysis

Update OpenAI prompt to be global/worldwide instead of India-specific for international users

Improve OpenAI prompt to provide varied recommendations (increase/decrease/keep) based on spending trends and patterns

Add test.py and enhanced debug logging for recommendation generation

Fix recommendation generation when user has data but no recommendations found - Fixed MongoDB query structure for budget lookup - Added fallback logic to generate recommendations from budget data - Added debug logging

Add budget_amount parameter to recommendations/check endpoint to generate recommendations based on provided budget

Fix: Add missing List import in models.py

Fix route order: Move POST /recommendations/check before GET /recommendations/{user_id} to prevent 405 error

Add POST endpoint to check user category data and return recommendations

Handle category field as string name (not ObjectId) in budgets

Change response to show category name and category_id instead of budget_name

Improve category name lookup with better logging and fallback searches

Use category ID from budgets and lookup names from headCategories and categories collections

Add enhanced logging to track OpenAI API usage vs rule-based recommendations

Clean up code: Remove commented duplicate code, fix category filtering logic, improve exception handling

Resolve merge conflicts - keep latest improvements

Fix bugs and improve budget recommendation system: Add API logging, fix OpenAI integration, enhance budget query patterns, add category extraction from headCategories, improve error handling

Update app/smart_recommendation.py

Update app/smart_recommendation.py

Update app/main.py

Update app/main.py

Update app/smart_recommendation.py

Disable write endpoints; read-only analytics

Match budgets by createdBy ObjectId