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@llama_index

A problem we see often: long documents with different pieces of repeating content. Example: a resume book with a cover page, a few pages about student curriculums, then back to back resumes Build an intelligent resume processing agent that automatically extracts structured data from repeating content using LlamaSplit to identify where each individual content starts and ends and LlamaExtract to extract structured data: πŸ“„ Upload PDF resume books to LlamaCloud and automatically categorize pages using LlamaSplit to separate individual resumes from curriculum and cover pages πŸ€– Extract structured information from each resume using LlamaExtract with custom schemas to capture names, contact info, education, work experience, and skills etc (your choice) ⚑ Orchestrate the entire process with LlamaAgent Workflows πŸ” Process real resume data with confidence scores and structured output ready for filtering, searching, and candidate matching systems The tutorial uses an NYU Resume Book as an example and shows both individual API calls and a complete automated workflow implementation. Check out the full tutorial: https://t.co/snaWXuoHq8

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