When adding AI/ML libraries to a project, carefully consider whether they belong in `dependencies` or `devDependencies`. Libraries used for examples, experimentation, or development tooling should be classified as `devDependencies` to avoid bloating production bundles. Maintain consistency by avoiding install scripts in package.json for dev-only AI...
When adding AI/ML libraries to a project, carefully consider whether they belong in dependencies
or devDependencies
. Libraries used for examples, experimentation, or development tooling should be classified as devDependencies
to avoid bloating production bundles. Maintain consistency by avoiding install scripts in package.json for dev-only AI libraries.
Example:
// Correct - AI libraries for examples/development
"devDependencies": {
"@langchain/core": "^0.3.40",
"@langchain/openai": "^0.4.4"
}
// Avoid install scripts for dev dependencies
"scripts": {
"example": "npm run build-dom-scripts && tsx examples/example.ts"
// Not: "langchain": "npm install @langchain/core @langchain/openai && ..."
}
This ensures production deployments only include necessary AI dependencies while keeping development and example code properly isolated.
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