Update README.md

Removes local installation instruction and includes it to local docs

README.md

@@ -42,126 +42,13 @@ Raw Data API consists of two elements:
 Raw Data API can be installed through `docker` or locally on your computer.
 
 - To install with docker see [docker installation](./docs/src/installation/docker.md).
-- To install locally, continue below.
-
-NOTE: The installation guide below is only tested to work on Ubuntu, we recommend using docker for other operating systems.
-
-### Local Installation Requirements.
-
-- Install [GDAL](https://gdal.org/index.html) on your computer using the command below:
-
-```
-sudo apt-get update && \
-sudo apt-get -y install gdal-bin python3-gdal && \
-sudo apt-get -y autoremove && \
-sudo apt-get clean
-
-```
-
-- Install [redis](https://redis.io/docs/getting-started/installation/) on your computer using the command below:
-
-```
-sudo apt-get -y install redis
-sudo apt-get -y install redis-tools # For client
-```
-
-- Confirm Redis Installation
-
-```
-redis-cli
-```
-
-Type `ping` it should return `pong`.
-
-If _redis_ is not running check out its [documentation](https://redis.io/docs/getting-started/)
-
-- Clone the Raw Data API repository on your computer
-
-```
-git clone https://github.com/hotosm/raw-data-api.git
-```
-
-- Navigate to the repository directory
-
-```
-cd raw-data-api
-```
-
-- Install the python dependencies
-
-```
-pip install -r requirements.txt
-```
+- To install locally, see [local installation](./docs/src/installation/local.md).
 
 ## Configurations
 
 Setup the necessary configurations for Raw Data API from [configurations](./docs/src/installation/configurations.md).
-
 Setup config.txt in project root or include your env variables in ```.env```
 
-### Optional : For Tiles Output
-If you opt for tiles output and have ```ENABLE_TILES : True``` in env variable . Make sure you install [Tippecanoe] (https://github.com/felt/tippecanoe)
-
-### Start the Server
-
-```
-uvicorn API.main:app --reload
-```
-
-### Queues 
-
-Currently there are two type of queue implemented : 
-- "raw_daemon" : Queue for recurring exports which will replace the previous exports if present on the system , can be enabled through uuid:false API Param 
-- "raw_ondemand" : Queue for default exports which will create each unique id for exports 
-
-### Start Celery Worker
-
-You should be able to start [celery](https://docs.celeryq.dev/en/stable/getting-started/first-steps-with-celery.html#running-the-celery-worker-server) worker by running following command on different shell
-
-- Start for default queue 
-  ```
-  celery --app API.api_worker worker --loglevel=INFO --queues="raw_ondemand" -n 'default_worker'
-  ```
-- Start for recurring queue 
-  ```
-  celery --app API.api_worker worker --loglevel=INFO --queues="raw_daemon" -n 'recurring_worker'
-  ```
-
-Set no of request that a worker can take at a time by using --concurrency 
-
-#### Note
-`If you are using postgres database as result_backend for celery you need to install sqlalchemy`
-```bash
-pip install SQLAlchemy==2.0.25
-```
-### Start flower for monitoring queue [OPTIONAL]
-
-Raw Data API uses flower for monitoring the Celery distributed queue. Run this command on a different shell , if you are running redis on same machine your broker could be `redis://localhost:6379//`.
-
-```
-celery --broker=redis://redis:6379// --app API.api_worker flower --port=5000 --queues="raw_daemon,raw_ondemand"
-```
-
-OR Simply use flower from application itself
-
-```bash
-celery --broker=redis://localhost:6379// flower
-```
-
-### Navigate to the docs to view Raw Data API endpoints
-
-After sucessfully starting the server, visit [http://127.0.0.1:8000/v1/docs](http://127.0.0.1:8000/v1/docs) on your browser to view the API docs.
-
-```
-http://127.0.0.1:8000/v1/docs
-```
-
-Flower dashboard should be available on port `5000` on your localhost.
-
-```
-http://127.0.0.1:5000/
-```
-
 ## Basic Usage
 
 - Confirm that Authetication works