attachments vs PaddleOCR
File ingestion and OCR toolkits compared
attachments turns a broad range of files and sources into structured text and image artifacts for LLM workflows. PaddleOCR focuses on recognizing text and parsing document structure in images and PDFs, with multiple OCR and document-understanding pipelines.
attachments: Turn Files Into LLM-Ready Context
attachments is a Python library and CLI that turns documents, images, audio, and other inputs into structured text and image artifacts for LLM workflows. It supports local processing, optional service fallback, and adapters for prompts, chat APIs, and RAG chunks.
PaddleOCR: Extract Text and Structure from Images and PDFs
PaddleOCR is a Python toolkit for recognizing text and parsing document layouts in images and PDFs. It suits developers building OCR, document-processing, and retrieval workflows who need structured output and multilingual recognition.
| attachments | PaddleOCR | |
|---|---|---|
| Language | Python | Python |
| License | MIT | Apache-2.0 |
| Stars | 368 | 90.6k |
| Forks | 31 | 11.4k |
| Last analyzed | Oct 3, 2026 | Oct 3, 2026 |
Key differences
- attachments handles sources including local files, directories, archives, URLs, and GitHub repositories; PaddleOCR focuses on images and PDFs.
- attachments provides adapters for prompts, chat APIs, and RAG chunks; PaddleOCR provides OCR and document-parsing outputs such as Markdown and JSON.
- attachments can process locally or use a configured remote service or self-hosted server; PaddleOCR offers CPU and accelerator inference, with deployment options including ONNX Runtime and OpenVINO.
- attachments is licensed under MIT; PaddleOCR is licensed under Apache-2.0.
- attachments is a Python library and CLI with optional format-specific dependencies; PaddleOCR is a Python toolkit with multiple model and pipeline choices to evaluate.
Choose attachments if you…
- need one interface to ingest varied file types and sources for LLM workflows.
- want artifacts that can be adapted into prompts, chat messages, or segment-aware RAG chunks.
- prefer local processing with the option to configure a service or self-hosted server.
Choose PaddleOCR if you…
- need OCR for images or PDFs, including multilingual text recognition.
- want document structure parsed into Markdown or JSON, including complex elements such as tables, formulas, and charts.
- need to evaluate CPU or accelerator inference and deployment options such as ONNX Runtime or OpenVINO.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.