Spaces:
Sleeping
Sleeping
File size: 845 Bytes
5660dc0 83728f4 8fe90da 73b49a2 8fe90da ca919d4 73b49a2 ca919d4 8fe90da ca919d4 73b49a2 8fe90da 73b49a2 8fe90da 73b49a2 8fe90da ca919d4 8fe90da ca919d4 8fe90da ca919d4 8fe90da ca919d4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 |
---
title: Everycure Ner Pdf
emoji: 🐢
colorFrom: indigo
colorTo: purple
sdk: docker
pinned: false
---
Extract named entities from PDF documents.
## Quick Start
### Installation
```sh
uv venv
UV_PYTHON=3.12 uv pip install -r pyproject.toml
```
### Running Locally
Start the server:
```sh
uv run src/everycure/app.py
```
### Usage
Process a PDF file (assuming your PDFs are in a `pdfs/` folder):
```sh
curl -X POST -F "file=@pdfs/MECFS systematic review.pdf" http://localhost:8000/api/v1/extract
```
### Remote API
The service is also available remotely:
```sh
curl -X POST -F "file=@pdfs/MECFS systematic review.pdf" https://lucharo-everycure-ner-pdf.hf.space/api/v1/extract
```
API documentation: <https://lucharo-everycure-ner-pdf.hf.space/docs>
## Development
Run tests:
```sh
uv pip install -e .[dev]
uv run pytest
```
|