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Updated docs after Dockerhub build changes
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.circleci/config.yml

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version: 2.1
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commands:
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abort_for_docs:
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steps:
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- run:
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name: Avoid tests for docs
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command: |
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if [[ $CIRCLE_BRANCH == *_docs ]]; then
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echo "Identifies as documents PR, no testing required"
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circleci step halt
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fi
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early_return_for_forked_pull_requests:
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description: >-
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If this build is from a fork, stop executing the current job and return success.
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This is useful to avoid steps that will fail due to missing credentials.
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steps:
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- run:
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name: Early return if this build is from a forked PR
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command: |
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if [[ -n "$CIRCLE_PR_NUMBER" ]]; then
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echo "Nothing to do for forked PRs, so marking this step successful"
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circleci step halt
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fi
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setup-executor:
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steps:
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- run:
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platform:
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type: string
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steps:
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- abort_for_docs
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- checkout
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- run:
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name: Submodule checkout
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platforms-build-steps:
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steps:
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- abort_for_docs
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- checkout
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- run:
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name: Relocate docker overlay2 dir
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from:
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type: string
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steps:
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- abort_for_docs
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- early_return_for_forked_pull_requests
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- run:
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name: Deploy to S3
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command: |
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docker:
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- image: redisfab/rmbuilder:6.0.9-x64-buster
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steps:
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- abort_for_docs
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- checkout
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name: Submodule checkout
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docker:
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- image: redisfab/rmbuilder:6.0.9-x64-buster
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steps:
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- abort_for_docs
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- checkout
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name: Submodule checkout
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macos:
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xcode: 11.3.0
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steps:
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- abort_for_docs
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name: Fix macOS Python installation
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command: |
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brew reinstall -f python2
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- build-steps:
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platform: macosx
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platform: macos
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build-multiarch-docker:
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machine:
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enabled: true
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image: cimg/base:2020.01
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steps:
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- abort_for_docs
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- checkout
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name: Submodule checkout
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resource_class: gpu.nvidia.small
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image: ubuntu-1604-cuda-11.1:202012-01
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steps:
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- abort_for_docs
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- checkout
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name: Submodule checkout
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- image: redisfab/rmbuilder:6.0.9-x64-buster
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steps:
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- abort_for_docs
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- early_return_for_forked_pull_requests
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- attach_workspace:
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at: workspace
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- run:
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- image: redisfab/rmbuilder:6.0.9-x64-buster
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steps:
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- abort_for_docs
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- early_return_for_forked_pull_requests
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- attach_workspace:
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at: workspace
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- run:
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- image: redisfab/rmbuilder:6.0.9-x64-buster
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steps:
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- abort_for_docs
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- early_return_for_forked_pull_requests
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- attach_workspace:
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at: workspace
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- run:

README.md

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[![GitHub issues](https://img.shields.io/github/release/RedisAI/RedisAI.svg?sort=semver)](https://github.com/RedisAI/RedisAI/releases/latest)
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[![CircleCI](https://circleci.com/gh/RedisAI/RedisAI/tree/master.svg?style=svg)](https://circleci.com/gh/RedisAI/RedisAI/tree/master)
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[![Docker Cloud Build Status](https://img.shields.io/docker/cloud/build/redisai/redisai.svg)](https://hub.docker.com/r/redisai/redisai/builds/)
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[![Dockerhub](https://img.shields.io/badge/dockerhub-redislabs%2Fredisai-blue)](https://hub.docker.com/r/redislabs/redisai/tags/)
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[![codecov](https://codecov.io/gh/RedisAI/RedisAI/branch/master/graph/badge.svg)](https://codecov.io/gh/RedisAI/RedisAI)
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[![Total alerts](https://img.shields.io/lgtm/alerts/g/RedisAI/RedisAI.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/RedisAI/RedisAI/alerts/)
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To quickly tryout RedisAI, launch an instance using docker:
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```sh
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docker run -p 6379:6379 -it --rm redisai/redisai
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docker run -p 6379:6379 -it --rm redislabs/redisai
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```
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For docker instance with GPU support, you can launch it from `tensorwerk/redisai-gpu`
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```sh
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docker run -p 6379:6379 --gpus all -it --rm redisai/redisai:latest-gpu
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docker run -p 6379:6379 --gpus all -it --rm redislabs/redisai:latest-gpu
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```
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But if you'd like to build the docker image, you need a machine that has Nvidia driver (CUDA 10.0), nvidia-container-toolkit and Docker 19.03+ installed. For detailed information, checkout [nvidia-docker documentation](https://github.com/NVIDIA/nvidia-docker)

docs/index.md

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## Quick Links
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* [Source code repository](https://github.com/RedisAI/RedisAI)
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* [Releases](https://github.com/RedisAI/RedisAI/releases)
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* [Docker image](https://hub.docker.com/r/redisai/redisai/)
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* [Docker image](https://hub.docker.com/r/redislabs/redisai/)
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## Contact Us
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If you have questions, want to provide feedback or perhaps report an issue or [contribute some code](contrib.md), here's where we're listening to you:

docs/intro.md

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The easiest way to get a standalone Redis server with RedisAI bootstrapped locally is to use the official RedisAI Docker container image:
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```
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docker run -d --name redisai -p 6379:6379 redisai/redisai:latest
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docker run -d --name redisai -p 6379:6379 redislabs/redisai:latest
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```
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??? info "Further reference"

docs/quickstart.md

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### On a CPU only machine
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```
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docker run -p 6379:6379 redisai/redisai:latest
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docker run -p 6379:6379 redislabs/redisai:latest
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```
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### On a GPU machine
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```
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docker run -p 6379:6379 --gpus all -it --rm redisai/redisai:latest-gpu
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docker run -p 6379:6379 --gpus all -it --rm redislabs/redisai:latest-gpu
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```
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## Download

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