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feat(ai): smart recommendation engine for culinary and storage advice (#8)#166

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saidai-bhuvanesh:feat/recommendation-engine
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feat(ai): smart recommendation engine for culinary and storage advice (#8)#166
saidai-bhuvanesh wants to merge 9 commits into
jpdevhub:mainfrom
saidai-bhuvanesh:feat/recommendation-engine

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@saidai-bhuvanesh

@saidai-bhuvanesh saidai-bhuvanesh commented Jul 3, 2026 •
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🔗 Upstream Issue Connection

Closes #165

This Pull Request is officially linked to and resolves Issue #165 (Feature 8: Smart Recommendation Engine for Safety & Culinary Use) in the upstream repository.

Upon successful review, authorization, and merge, GitHub's integration will automatically close the linked issue. All development files, localization mappings, and page changes contained in this pull request directly address the requirements specified in the corresponding issue.

What changes are made?

  1. Interactive Smart Kitchen Engine (src/pages/AnalysisDashboard.tsx): Upgraded the static recommendations panel on the analysis dashboard into a comprehensive smart advisory system.
  2. Dynamic Culinary Advice: Classifies culinary potential based on the calculated freshness index. Highly fresh specimens (>85%) suggest raw/sushi preparation, moderate freshness recommends curries or baking, and lower freshness indexes suggest deep-frying or spicy dishes.
  3. Adaptive Species Preservation Protocols: Displays customized biological storage advice mapped to the specific species (e.g. Rohu: rubbing with turmeric paste to keep skin hydrated; Catla: steak-portioning to drop temperatures uniformly; Mrigal: flat ice-packing to prevent muscle bruising).
  4. Alternative Storage Scenarios: Integrated details on preservation durations under vacuum-sealed freezing vs ice-box vs room temp conditions.
  5. Localization Mappings: Localized all culinary advices, species-specific preservation rules, and engine headers across English, Hindi, and Bengali locales.

Technical Depth and Verification

This bridges the gap between raw machine learning percentages and everyday kitchen usage. We formulated specific rules that map scores to food-safety and culinary recommendations, and combined this with custom conservation tips for different freshwater fish species.

Verified recommendations on the scan results page. Scanned carps show appropriate storage times and species-specific preservation instructions.

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Someone is attempting to deploy a commit to the karan3431's projects Team on Vercel.

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⚠️ No linked issue found!
This PR cannot be reviewed until a related issue is linked.
Please add Closes #issue_number in your PR description.

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📥 Commits

Reviewing files that changed from the base of the PR and between 97c6f33 and 291ec99.

📒 Files selected for processing (13)
  • backend/main.py
  • backend/vendors.py
  • src/components/AnalyticsTrends.tsx
  • src/fusionInference.js
  • src/i18n/locales/bn.json
  • src/i18n/locales/en.json
  • src/i18n/locales/hi.json
  • src/lib/api.ts
  • src/lib/offlineDb.ts
  • src/pages/AnalysisDashboard.tsx
  • src/pages/Leaderboard.tsx
  • src/pages/ResultsPage.tsx
  • src/pages/ScannerPage.tsx
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  • Create PR with unit tests

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Feature 8: Smart Recommendation Engine for Safety & Culinary Use

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