This enables LLM-friendly documentation for entire sections,
allowing users to copy complete documentation sections with a single click.
Lambda@Edge now generates .md files on-demand with:
- Evaluated Hugo shortcodes
- Proper YAML frontmatter with product metadata
- Clean markdown without UI elements
- Section aggregation (parent + children in single file)
The llms.txt files are now generated automatically during build from
content structure and product metadata in data/products.yml, eliminating
the need for hardcoded files and ensuring maintainability.
**Testing**:
- Automated markdown generation in test setup via cy.exec()
- Implement dynamic content validation that extracts HTML content and
verifies it appears in markdown version
**Documentation**:
Documents LLM-friendly markdown generation
**Details**:
Add gzip decompression for S3 HTML files in Lambda markdown generator
HTML files stored in S3 are gzip-compressed but the Lambda was attempting
to parse compressed data as UTF-8, causing JSDOM to fail to find article
elements. This resulted in 404 errors for .md and .section.md requests.
- Add zlib gunzip decompression in s3-utils.js fetchHtmlFromS3()
- Detect gzip via ContentEncoding header or magic bytes (0x1f 0x8b)
- Add configurable DEBUG constant for verbose logging
- Add debug logging for buffer sizes and decompression in both files
The decompression adds ~1-5ms per request but is necessary to parse
HTML correctly. CloudFront caching minimizes Lambda invocations.
Await async markdown conversion functions
The convertToMarkdown and convertSectionToMarkdown functions are async
but weren't being awaited, causing the Lambda to return a Promise object
instead of a string. This resulted in CloudFront validation errors:
"The body is not a string, is not an object, or exceeds the maximum size"
**Troubleshooting**:
- Set DEBUG for troubleshooting in lambda
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