https://github.com/deckerego/docmag

The web UI for Facile Search. Together with DocIndex, this UI can help you search the myriad of scanned documents you have been accumulating over the years. Using the power of Docker & Elasticsearch you can run a powerful search engine that lets you convert scanned (image-based) PDFs to searchable text, group documents by letterhead, run fuzzy searches by date and view document metadata.
https://github.com/deckerego/docmag

docker elasticsearch full-text-search kubernetes pdf scanned-documents

Last synced: 2 months ago
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The web UI for Facile Search. Together with DocIndex, this UI can help you search the myriad of scanned documents you have been accumulating over the years. Using the power of Docker & Elasticsearch you can run a powerful search engine that lets you convert scanned (image-based) PDFs to searchable text, group documents by letterhead, run fuzzy searches by date and view document metadata.

• Host: GitHub
• URL: https://github.com/deckerego/docmag
• Owner: deckerego
• License: mpl-2.0
• Created: 2017-10-17T01:20:04.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2024-10-04T23:18:16.000Z (3 months ago)
• Last Synced: 2024-10-10T22:44:41.485Z (3 months ago)
• Topics: docker, elasticsearch, full-text-search, kubernetes, pdf, scanned-documents
• Language: Groovy
• Homepage: https://github.com/deckerego/docmag/wiki
• Size: 2.46 MB
• Stars: 4
• Watchers: 2
• Forks: 0
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Facile Search

Facile Search bundles together Elasticsearch and DocIndex

to make searching across documents simple and efficient.

## Requirements

Usually you won't want to build and run docmag locally, instead it is best to

run the docker container published at: https://hub.docker.com/r/deckerego/docmagui/

To run the containers needed for Facile Search you have three recommended options:

1. [Running on a single server with Docker Compose](docs/docker_compose.md)

1. [Installing within a cluster using Kubernetes and Helm](docs/kubernetes.md)

1. [Installing on a Synology NAS device](docs/synology.md)

See the [docs/](docs/) directory for instructions on installation and setup on these platforms.

## Using DocIndex to Index Files

The docidx daemon indexes files within Elasticsearch and prepares them for display - this is the

process that feeds docmag. More info is available at https://github.com/deckerego/docidx

## Building and Testing Locally

Building the app and its necessary infrastructure locally is performed with

Maven and `docker-compose`.

To compose the necessary containers and configure Elasticsearch indexes:

    mvn install

    export DOCUMENT_HOST_DIR=/mnt/documents && docker-compose -f docker-compose.yml -f docker-compose-devel.yml up -d

    cd es/

    ./configure.sh

The development instance of the composition config will expose Elasticsearch,

Spring Boot, and Kibana to local ports - so don't use this in a

production setting.

This should build & run the necessary containers, then begin indexing documents

from the directory specified as `DOCUMENT_HOST_DIR`. To shut down and delete the

Elasticsearch metadata generated from these containers, execute:

    export DOCUMENT_HOST_DIR=/mnt/documents && docker-compose -f docker-compose.yml -f docker-compose-devel.yml down -v

## Searching and Querying Documents

To search within your documents, view thumbnails and open the full document

navigate to `http://localhost:1080`. This should take you to the main search

interface, which will perform a full text search on your indexed documents.