Building a Robust Ingestion System for Any File of Any Size

Mixedbread rebuilt its file-ingestion pipeline to handle arbitrarily large and diverse user uploads, after its original approach failed on unexpectedly common gigabyte-scale text collections and hundreds-of-gigabytes video files. Its architecture separates coarse, bounded slicing from semantic parsing: a slicer divides each file into type-appropriate units such as PDF pages, video seconds, or text characters, while parsers process one slice at a time to generate meaningful search chunks at logical boundaries, scene changes, or low-energy audio regions. Small continuation states passed through a task queue allow fixed-size workers to process files sequentially without holding entire files in memory, making individual slices retryable and protecting the rest of a job from worker failures. The system addresses unreliable input-size estimates, potentially explosive rendering costs, and unsafe real-world office documents through streaming media access, page-rendering pixel limits, and lazy chunk iteration. Before ingestion, it estimates quotas using low-cost metadata such as page counts, media duration, or byte-based approximations, then reconciles totals during processing. Although the current design prioritizes semantic integrity over within-file parallelism, Mixedbread plans a future version that can process independent slices concurrently while preserving chunk quality.

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