Yes, it evaluate using frontier model for parsing from all 3 major provider (google, anthropic and openai). It is also easy to extend to evaluaye new model (code/dataset is available)
Build a benchmark to evaluate how good document parser work on a dataset of 2000 PDFs manually annotated, trying to evaluate accross multiple dimensions: charts, tables, text styling, text correctness, and attribution.
The benchmark evaluate performance on full page (not selected part of the pages), and evaluaye different OSS / crobtier model / commercial approach.
For transparency it is available as a HF leaderbaord.
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If you want to try agentic parsing we added support for sonnet-3.7 agentic parse and gemini 2.0 in llamaParse. cloud.llamaindex.ai/parse (select advanced options / parse with agent then a model)
However this come at a high cost in token and latency, but result in way better parse quality. Hopefully with new model this can be improved.
This is a nice UI for end users, however it seems to be a seems wrapper on top of mutool, which is distributed as AGPL. If you want to process PDF locally, legally and safely you should use their CLI instead.
Good article, but what is the alternative? What can you build today as a software engineer that can have impact? Nothing seems to come close to AI / AI infra, even of its hard / risky / a moving landscape.
Performance depend on the language / type of docs. Main reason for contemplating switching is that easyOCR seems to not be maintained anymore (no commit in the repo in last 5 months)