@jerryjliu0: There is a massive demand for processing files *in the agent loop*. The number of users submitting agent queries with f…
Summary
Jerry Liu announces LiteParse, a fast and accurate file parser for agent loops, now integrated with Vercel's Eve framework.
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Cached at: 07/05/26, 10:36 PM
There is a massive demand for processing files in the agent loop. The number of users submitting agent queries with file attachments is exponentially increasing over time.
Our mission is to make LiteParse the best parser in terms of cost, accuracy, speed, and semantics, for any agent loop you’re using. This includes the recent Eve framework by @vercel to the Claude SDK to other frameworks.
Right now, the default behavior of every agent loop is to use a simple library (e.g. pypdf, pdftotext) to do a light pass through the file, before attempting deeper vision based approaches. This leads to hallucinated context, and bad retrieval. This also takes a long time, because the agent has to reconstruct writing the imports/postprocessing code from scratch.
LiteParse is awesome and you should check it out. Even if you don’t plan to use it as a standalone library, it is installable as a one-click skill for any agent, and of course, we now support Eve!
Template: https://github.com/run-llama/eve-liteparse…
LiteParse: https://github.com/run-llama/liteparse…
LlamaIndex 🦙 (@llama_index): The team at @vercel recently released the Eve agent framework, so we built a template that integrates LiteParse with it🦙
The template provides a set of read-only filesystem tools that let Eve resolve paths, list directories, and read text-based files. We then pair those with
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