AI-powered enterprise search engine 🔎

June 23, 2023 · View on GitHub

⚡🔎 Live online demo!

AI-powered enterprise search engine 🔎

Join Discord for early access code!

Discord Follow DockerHub Pulls

Join here!

Search engine for your organization!

first image Find any conversation, doc, or internal page in seconds ⏲️⚡️
Join 100+ devs by hosting your own gerev instance, become a hero within your org! 💪

Made for help desk techies 👨‍💻

Troubleshoot Issues 🐛

fourth image

Or find internal issues fast ⚡️

second image

Integrations

  • Slack
  • Confluence
  • Jira
  • Google Drive (Docs, .docx, .pptx) - by @bary12 :pray:
  • Confluence Cloud - by @bryan-pakulski :pray:
  • Bookstack - by @flifloo :pray:
  • Mattermost - by @itaykal :pray:
  • RocketChat - by @flifloo :pray:
  • Gitlab Issues - by @eran1232 :pray:
  • Zendesk (In PR :pray:)
  • Stackoverflow Teams (In PR :pray:)
  • Azure DevOps (In PR :pray:)
  • Phabricator (In PR :pray:)
  • Trello (In PR... :pray:)
  • Notion (In Progress... :pray:)
  • Asana
  • Sharepoint
  • Box
  • Dropbox
  • Github Enterprise
  • Microsoft Teams

:pray: - by the community

Add your own data source NOW 🚀

See the full guide at ADDING-A-DATA-SOURCE.md.

Natural Language

Enables searching using natural language. such as "How to do X", "how to connect to Y", "Do we support Z"

Getting Started

Managed Cloud (Pro)

Sign up Free

  • Authentication
  • Multiple Users
  • GPU machine
  • 24/7 Support
  • Self hosted version (with multi-user also supported)

Self-hosted (Community)

  1. Install Nvidia for docker (on host that runs the docker runtime)
  2. Run docker

Nvidia for docker

Install nvidia container toolkit on the host machine.

distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
   && curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \
   && curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
   
sudo apt-get update

sudo apt-get install -y nvidia-docker2

sudo systemctl restart docker

Run docker

Then run the docker container like so:

Nvidia hardware

docker run --gpus all --name=gerev -p 80:80 -v ~/.gerev/storage:/opt/storage gerev/gerev

CPU only (no GPU)

docker run --name=gerev -p 80:80 -v ~/.gerev/storage:/opt/storage gerev/gerev

add -d if you want to detach the container.

Run from source

See ADDING-A-DATA-SOURCE.md in the Setup development environment section.

  • gerev is also popular with some big names. 😉

first image

Built by the community 💜

Made with contributors-img.