A Python/Prolog project for generating and validating sandwich recipes using LLMs, semantic embeddings, and logic programming. Demonstrates a simple neurosymbolic pipeline.

Code generated by GPT-4.1, refined manually.

• Generates sandwich ideas using Google Gemini LLM.
• Canonicalizes ingredients with semantic similarity (embeddings).
• Validates sandwich combinations using Prolog rules.
• Ingredients and rules are managed from a shared YAML file.
• Embedding caching for efficiency.

• Python 3.8+
• Prolog (GProlog or SWI-Prolog)
• Google GenerativeAI Python SDK
• NumPy, PyYAML, pyswip

1. Set your GOOGLE_API_KEY environment variable.
2. Install dependencies: pip install -r requirements.txt
3. Run: python main_wich_doctor.py

• main_wich_doctor.py — Main application logic
• ingredients.yaml — Ingredient knowledge base
• wich_doctor.pl — Auto-generated Prolog facts
• canonical_embeddings.npy — Cached embeddings

MIT License

Copyright (c) 2025 Erno Szabados

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

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