text-extract-api vs Xberg
Side-by-side comparison of two AI agent tools
text-extract-apiopen-source
Document (PDF, Word, PPTX ...) extraction and parse API using state of the art modern OCRs + Ollama supported models. Anonymize documents. Remove PII. Convert any document or picture to structured JSO
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Xbergopen-source
Polyglot document intelligence with a Rust core: extract text, metadata, images, tables, and structured data from 106 formats across 140 file extensions, plus c
Metrics
| text-extract-api | Xberg | |
|---|---|---|
| Stars | 3.2k | 9.4k |
| Star velocity /mo | 16.844919786096256 | 779.9166666666666 |
| Commits (90d) | 0 | 3.1k |
| Releases (6m) | 0 | 10 |
| Overall score | 0.2138090027860015 | 0.8100951718666431 |
Pros
- +完全本地化处理,无外部依赖,确保数据隐私和安全性
- +支持多种先进OCR策略(LLaMA Vision、EasyOCR等),识别精度极高
- +集成分布式队列和缓存机制,支持大规模文档批量处理
Cons
- -需要安装多个依赖组件(Docker、Ollama),初始设置较为复杂
- -本地运行PyTorch模型需要较大计算资源和存储空间
Use Cases
- •医疗机构将MRI报告、病历等医疗文档转换为结构化数据
- •企业财务部门处理发票、合同等文档并自动移除敏感信息
- •法律机构批量数字化和分析大量合规文档或法律条文
FAQ
- Which is more popular, text-extract-api or Xberg?
- Xberg has more GitHub stars (9,359 vs 3,182).
- Which is more actively developed, text-extract-api or Xberg?
- Xberg had more commits in the last 90 days (3,122 vs 0).
- Should I use text-extract-api or Xberg?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.