Webis Supports Multimodal Data

Webis is a powerful web content extraction tool that extends beyond HTML web page content extraction to support multimodal data processing, covering multiple input formats such as PDF, images, and documents (DOC). By integrating advanced tools like PyMuPDF, Tesseract, and LlamaIndex, Webis can efficiently clean and extract structured content from multimodal data, providing unified, clean output (such as JSON or plain text) to meet diverse data processing needs. This feature makes it perform excellently in complex data pipelines and cross-format content analysis scenarios.

Supporting PDF, Images, and Documents

For PDF files, Webis utilizes PyMuPDF for efficient parsing, extracting text, tables, and metadata while preserving document structure. PyMuPDF's fast parsing capabilities ensure Webis can handle large PDF files, suitable for academic papers, reports, and other scenarios. For image input, Webis integrates Tesseract OCR technology to accurately extract text content from images, supporting multilingual recognition, applicable to scanned documents, screenshots, or images containing text. For DOC format documents, Webis leverages LlamaIndex to implement intelligent content indexing and extraction, capable of processing complex document structures, extracting key information, and generating semantic output.

Integrated Unified Interface

Webis's multimodal support is implemented through a unified interface, allowing users to seamlessly process data in different formats via API or CLI. Its modular design ensures efficient collaboration between tools, with highly consistent cleaned data, suitable for data analysis, content aggregation, and other application scenarios. In the future, Webis plans to further optimize multimodal processing performance and expand support for video and audio.