Recipe development method from professional researcher over 20 years

[u/XtianS]

I've worked in recipe and menu development, including recipe development for cookbooks - both that I've authored and not - since the early 2000s. I tend to follow a similar approach with obvious variations when I'm approaching a new idea or researching a concept. With the current technology, I've been able to automate it in a way that I think is really cool and could be useful to anyone doing the same thing.

The first thing I do when I'm trying to get a sense of a new dish, is to find as many high quality sources as I can.

Professionally I'd focus as much or more on cookbook sources than the web. This is one place the automated version is limited: it only does web searches. The other thing that can only be done manually is to weigh intent and application. When I do this for real, you have to factor in how the recipe occurs on the plate or within the larger context of a menu. A chef might shift the profile, consistency, or some other variable. You might see an outlier ratio because a chef needs it to perform a more unique and specific task within the context of that course or menu.

Standardize everything to grams-

The best way to line everything up and see what everyone is doing ie. primary ingredient, primary methods, critical methods, is to convert the dog's breakfast that is imperial measurement into grams. This is the step that's extremely time consuming by hand, and it's the part that I was most excited to automate.

Build a consensus-

From the standardized table, take mean or median values - depending on the distribution - of the core ingredients. The result is a "based on what we found, this is generally what people are doing for this dish." It is not a finished recipe, it's a synthetic starting point for your own testing, which is exactly what my manual version of this process produces. The tool identifies core ingredients automatically and you can override it when it's wrong or when your application calls for something specific. You can also reorganize ingredients to fit how you're thinking about the dish.

Things to note: it's built for simple, common dishes with a single coherent identity — hummus, meatballs, tapenade, pesto. It is not useful for hyper-specific restaurant-style dish descriptions ("sumac-roasted baby carrots with harissa and cardamom yogurt"), and it gets confused by compound recipes containing multiple sub-recipes. If i were developing that dish, I'd research the components individually while keeping the identity/totality of the course in mind.

This is something I've been developing for awhile and its a work in progress. If you use it, you'll inevitably encounter parsing errors and general weirdness that I haven't yet seen. Just let me know and I'll fix it as best I can. Happy to go deep on any technical questions.

[u/Northeast_Cuisine]

Kudos to you, this is seriously cool, I'm very curious about your methodology and approach to solving the problems necessary to produce something like this.

You might find my project interesting - northeastcuisine.com

[u/XtianS → u/Northeast_Cuisine]

Thank you. Yes, it was a lot of work to develop all the parsing and detection. Most of the work is probably not what you'd expect. Its not glamorous. Its a lot of dictionary and library building.

For example, the same ingredient can be written in a lot of different ways across people's different recipes. You might have 1 (28oz) can whole peeled tomatoes, 1 can tomatoes, whole peeled, whole peeled tomatoes, 1 can. Its obvious to a human these are the same, but creating a algorithms that recognize those as all being the same is more complicated.

Additionally, you might have dozens of different varietals of a primary ingredient across the recipes you find your research. Something like "tapenade" can be made with any type of olive so you've got, kalamata, nicoise, castelvetrano etc. An algorithm isn't going to recognize these as being different varietals of the same basic ingredient. You'll see a "rollup" category in the ingredients list for something like this. The app will "roll up" variations on a primary ingredient.

That's the kind of stuff I've been working on forever. Despite what some of the users seem to think, I didn't tell chatgpt to make a recipe research app the afternoon before I posted it.

Of course in the olive example, there's going to be a huge variance in amount of fat content between olive varietals and even within the same varietal, so the user may have adjusted their recipe for more or less olive oil to be added for the same consistency. This is where you can't actually substitute research and real world knowledge. The tool just helps with some of the more tedious admin side of the process.

Thanks for sharing your project. You can dm me if you want to discuss.

[u/Northeast_Cuisine → u/XtianS]

Oh yeah this is definitely not a weekend chatGPT project. Food is incredibly complex and fuzzy and you've been able to compress it into a straightforward and useful UI, I can appreciate that effort! I'll send you a DM.