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LlamaParse is a GenAI-native document parser that can parse complex document data for any downstream LLM use case (RAG, agents). Load in 160+ data sources and data formats, from unstructured, and semi-structured, to structured data (API's, PDFs, documents, SQL, etc.) Store and index your data for different use cases. Integrate with 40+ vector stores, document stores, graph stores, and SQL db providers.
Features
- Parsing a variety of unstructured file types (.pdf, .pptx, .docx, .xlsx, .html) with text, tables, visual elements, weird layouts, and more.
- Parsing embedded tables accurately into text and semi-structured representations
- Documentation available
- Extracting visual elements (images/diagrams) into structured formats and return image chunks using the latest multimodal models
- Input custom prompt instructions to customize the output the way you want it
- Multimodal parsing and chunking
Project Samples
Categories
Artificial IntelligenceLicense
MIT LicenseFollow LlamaParse
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