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Since they are written as unstructured text in most recipes, parsing products can be a challenge.\n\nThe [`backend`](https://codeberg.org/openculinary/backend/) service provides the source-of-truth for product metadata, and it makes this available at the [`/products/hierarchy`](https://codeberg.org/openculinary/backend/src/commit/cd029da0bd9caab7f490f5299018934db10ed0ec/reciperadar/api/products.py#L51-L70) endpoint.\n\nThe knowledge graph loads this data at runtime, and we build an in-process search-engine index that allows us to find candidate ingredient matches, which are then narrowed down to a single best-match per ingredient line.\n\n## Install dependencies\n\nMake sure to follow the RecipeRadar [infrastructure](https://codeberg.org/openculinary/infrastructure) setup to ensure all cluster dependencies are available in your environment.\n\n## Development\n\nTo install development tools and run linting and tests locally, execute the following commands:\n\n```sh\n$ make lint tests\n```\n\n## Local Deployment\n\nTo deploy the service to the local infrastructure environment, execute the following commands:\n\n```sh\n$ make\n$ make deploy\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopenculinary%2Fknowledge-graph","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fopenculinary%2Fknowledge-graph","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopenculinary%2Fknowledge-graph/lists"}