Merge branch 'dev'

This commit is contained in:
Daniele Viti 2023-12-31 11:20:20 +01:00
commit 7354e8ebae
24 changed files with 880 additions and 18 deletions

291
.gitignore vendored
View File

@ -8,3 +8,294 @@ node_modules
!.env.example
vite.config.js.timestamp-*
vite.config.ts.timestamp-*
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
.pybuilder/
target/
# Jupyter Notebook
.ipynb_checkpoints
# IPython
profile_default/
ipython_config.py
# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
# .python-version
# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock
# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock
# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
# in version control.
# https://pdm.fming.dev/#use-with-ide
.pdm.toml
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/
# Celery stuff
celerybeat-schedule
celerybeat.pid
# SageMath parsed files
*.sage.py
# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject
.spyproject
# Rope project settings
.ropeproject
# mkdocs documentation
/site
# mypy
.mypy_cache/
.dmypy.json
dmypy.json
# Pyre type checker
.pyre/
# pytype static type analyzer
.pytype/
# Cython debug symbols
cython_debug/
# PyCharm
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/
# Logs
logs
*.log
npm-debug.log*
yarn-debug.log*
yarn-error.log*
lerna-debug.log*
.pnpm-debug.log*
# Diagnostic reports (https://nodejs.org/api/report.html)
report.[0-9]*.[0-9]*.[0-9]*.[0-9]*.json
# Runtime data
pids
*.pid
*.seed
*.pid.lock
# Directory for instrumented libs generated by jscoverage/JSCover
lib-cov
# Coverage directory used by tools like istanbul
coverage
*.lcov
# nyc test coverage
.nyc_output
# Grunt intermediate storage (https://gruntjs.com/creating-plugins#storing-task-files)
.grunt
# Bower dependency directory (https://bower.io/)
bower_components
# node-waf configuration
.lock-wscript
# Compiled binary addons (https://nodejs.org/api/addons.html)
build/Release
# Dependency directories
node_modules/
jspm_packages/
# Snowpack dependency directory (https://snowpack.dev/)
web_modules/
# TypeScript cache
*.tsbuildinfo
# Optional npm cache directory
.npm
# Optional eslint cache
.eslintcache
# Optional stylelint cache
.stylelintcache
# Microbundle cache
.rpt2_cache/
.rts2_cache_cjs/
.rts2_cache_es/
.rts2_cache_umd/
# Optional REPL history
.node_repl_history
# Output of 'npm pack'
*.tgz
# Yarn Integrity file
.yarn-integrity
# dotenv environment variable files
.env
.env.development.local
.env.test.local
.env.production.local
.env.local
# parcel-bundler cache (https://parceljs.org/)
.cache
.parcel-cache
# Next.js build output
.next
out
# Nuxt.js build / generate output
.nuxt
dist
# Gatsby files
.cache/
# Comment in the public line in if your project uses Gatsby and not Next.js
# https://nextjs.org/blog/next-9-1#public-directory-support
# public
# vuepress build output
.vuepress/dist
# vuepress v2.x temp and cache directory
.temp
.cache
# Docusaurus cache and generated files
.docusaurus
# Serverless directories
.serverless/
# FuseBox cache
.fusebox/
# DynamoDB Local files
.dynamodb/
# TernJS port file
.tern-port
# Stores VSCode versions used for testing VSCode extensions
.vscode-test
# yarn v2
.yarn/cache
.yarn/unplugged
.yarn/build-state.yml
.yarn/install-state.gz
.pnp.*

View File

@ -27,7 +27,7 @@ Also check our sibling project, [OllamaHub](https://ollamahub.com/), where you c
- ⚡ **Swift Responsiveness**: Enjoy fast and responsive performance.
- 🚀 **Effortless Setup**: Install seamlessly using Docker for a hassle-free experience.
- 🚀 **Effortless Setup**: Install seamlessly using Docker or Kubernetes (kubectl, kustomize or helm) for a hassle-free experience.
- 💻 **Code Syntax Highlighting**: Enjoy enhanced code readability with our syntax highlighting feature.
@ -81,30 +81,50 @@ Don't forget to explore our sibling project, [OllamaHub](https://ollamahub.com/)
### Installing Both Ollama and Ollama Web UI Using Docker Compose
If you don't have Ollama installed yet, you can use the provided Docker Compose file for a hassle-free installation. Simply run the following command:
If you don't have Ollama installed yet, you can use the provided bash script for a hassle-free installation. Simply run the following command:
For cpu-only container
```bash
docker compose up -d --build
chmod +x run-compose.sh && ./run-compose.sh
```
This command will install both Ollama and Ollama Web UI on your system.
#### Enable GPU
Use the additional Docker Compose file designed to enable GPU support by running the following command:
For gpu-enabled container (to enable this you must have your gpu driver for docker, it mostly works with nvidia so this is the official install guide: [nvidia-container-toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html))
```bash
docker compose -f docker-compose.yml -f docker-compose.gpu.yml up -d --build
chmod +x run-compose.sh && ./run-compose.sh --enable-gpu[count=1]
```
#### Expose Ollama API outside the container stack
Deploy the service with an additional Docker Compose file designed for API exposure:
Note that both the above commands will use the latest production docker image in repository, to be able to build the latest local version you'll need to append the `--build` parameter, for example:
```bash
docker compose -f docker-compose.yml -f docker-compose.api.yml up -d --build
./run-compose.sh --build --enable-gpu[count=1]
```
### Installing Both Ollama and Ollama Web UI Using Kustomize
For cpu-only pod
```bash
kubectl apply -f ./kubernetes/manifest/base
```
For gpu-enabled pod
```bash
kubectl apply -k ./kubernetes/manifest
```
### Installing Both Ollama and Ollama Web UI Using Helm
Package Helm file first
```bash
helm package ./kubernetes/helm/
```
For cpu-only pod
```bash
helm install ollama-webui ./ollama-webui-*.tgz
```
For gpu-enabled pod
```bash
helm install ollama-webui ./ollama-webui-*.tgz --set ollama.resources.limits.nvidia.com/gpu="1"
```
Check the `kubernetes/helm/values.yaml` file to know which parameters are available for customization
### Installing Ollama Web UI Only
#### Prerequisites

6
docker-compose.api.yaml Normal file
View File

@ -0,0 +1,6 @@
version: '3.8'
services:
ollama:
ports:
- ${OLLAMA_WEBAPI_PORT-11434}:11434

6
docker-compose.data.yaml Normal file
View File

@ -0,0 +1,6 @@
version: '3.8'
services:
ollama:
volumes:
- ${OLLAMA_DATA_DIR-./ollama-data}:/root/.ollama

12
docker-compose.gpu.yaml Normal file
View File

@ -0,0 +1,12 @@
version: '3.8'
services:
ollama:
deploy:
resources:
reservations:
devices:
- driver: ${OLLAMA_GPU_DRIVER-nvidia}
count: ${OLLAMA_GPU_COUNT-1}
capabilities:
- gpu

View File

@ -1,4 +1,4 @@
version: '3.6'
version: '3.8'
services:
ollama:
@ -16,14 +16,14 @@ services:
args:
OLLAMA_API_BASE_URL: '/ollama/api'
dockerfile: Dockerfile
image: ollama-webui:latest
image: ghcr.io/ollama-webui/ollama-webui:main
container_name: ollama-webui
volumes:
- ollama-webui:/app/backend/data
depends_on:
- ollama
ports:
- 3000:8080
- ${OLLAMA_WEBUI_PORT-3000}:8080
environment:
- "OLLAMA_API_BASE_URL=http://ollama:11434/api"
extra_hosts:

View File

View File

@ -0,0 +1,5 @@
apiVersion: v2
name: ollama-webui
description: "Ollama Web UI: A User-Friendly Web Interface for Chat Interactions 👋"
version: 1.0.0
icon: https://raw.githubusercontent.com/ollama-webui/ollama-webui/main/static/favicon.png

View File

@ -0,0 +1,4 @@
apiVersion: v1
kind: Namespace
metadata:
name: {{ .Values.namespace }}

View File

@ -0,0 +1,12 @@
apiVersion: v1
kind: Service
metadata:
name: ollama-service
namespace: {{ .Values.namespace }}
spec:
selector:
app: ollama
ports:
- protocol: TCP
port: {{ .Values.ollama.servicePort }}
targetPort: {{ .Values.ollama.servicePort }}

View File

@ -0,0 +1,38 @@
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: ollama
namespace: {{ .Values.namespace }}
spec:
serviceName: "ollama"
replicas: {{ .Values.ollama.replicaCount }}
selector:
matchLabels:
app: ollama
template:
metadata:
labels:
app: ollama
spec:
containers:
- name: ollama
image: {{ .Values.ollama.image }}
ports:
- containerPort: {{ .Values.ollama.servicePort }}
resources:
limits:
cpu: {{ .Values.ollama.resources.limits.cpu }}
memory: {{ .Values.ollama.resources.limits.memory }}
nvidia.com/gpu: {{ .Values.ollama.resources.limits.gpu }}
volumeMounts:
- name: ollama-volume
mountPath: /root/.ollama
tty: true
volumeClaimTemplates:
- metadata:
name: ollama-volume
spec:
accessModes: [ "ReadWriteOnce" ]
resources:
requests:
storage: 1Gi

View File

@ -0,0 +1,28 @@
apiVersion: apps/v1
kind: Deployment
metadata:
name: ollama-webui-deployment
namespace: {{ .Values.namespace }}
spec:
replicas: 1
selector:
matchLabels:
app: ollama-webui
template:
metadata:
labels:
app: ollama-webui
spec:
containers:
- name: ollama-webui
image: ghcr.io/ollama-webui/ollama-webui:main
ports:
- containerPort: 8080
resources:
limits:
cpu: "500m"
memory: "500Mi"
env:
- name: OLLAMA_API_BASE_URL
value: "http://ollama-service.{{ .Values.namespace }}.svc.cluster.local:{{ .Values.ollama.servicePort }}/api"
tty: true

View File

@ -0,0 +1,20 @@
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: ollama-webui-ingress
namespace: {{ .Values.namespace }}
#annotations:
# Use appropriate annotations for your Ingress controller, e.g., for NGINX:
# nginx.ingress.kubernetes.io/rewrite-target: /
spec:
rules:
- host: {{ .Values.webui.ingress.host }}
http:
paths:
- path: /
pathType: Prefix
backend:
service:
name: ollama-webui-service
port:
number: {{ .Values.webui.servicePort }}

View File

@ -0,0 +1,15 @@
apiVersion: v1
kind: Service
metadata:
name: ollama-webui-service
namespace: {{ .Values.namespace }}
spec:
type: NodePort # Use LoadBalancer if you're on a cloud that supports it
selector:
app: ollama-webui
ports:
- protocol: TCP
port: {{ .Values.webui.servicePort }}
targetPort: {{ .Values.webui.servicePort }}
# If using NodePort, you can optionally specify the nodePort:
# nodePort: 30000

View File

@ -0,0 +1,23 @@
namespace: ollama-namespace
ollama:
replicaCount: 1
image: ollama/ollama:latest
servicePort: 11434
resources:
limits:
cpu: "2000m"
memory: "2Gi"
nvidia.com/gpu: "0"
volumeSize: 1Gi
webui:
replicaCount: 1
image: ghcr.io/ollama-webui/ollama-webui:main
servicePort: 8080
resources:
limits:
cpu: "500m"
memory: "500Mi"
ingress:
host: ollama.minikube.local

View File

@ -0,0 +1,4 @@
apiVersion: v1
kind: Namespace
metadata:
name: ollama-namespace

View File

@ -0,0 +1,12 @@
apiVersion: v1
kind: Service
metadata:
name: ollama-service
namespace: ollama-namespace
spec:
selector:
app: ollama
ports:
- protocol: TCP
port: 11434
targetPort: 11434

View File

@ -0,0 +1,37 @@
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: ollama
namespace: ollama-namespace
spec:
serviceName: "ollama"
replicas: 1
selector:
matchLabels:
app: ollama
template:
metadata:
labels:
app: ollama
spec:
containers:
- name: ollama
image: ollama/ollama:latest
ports:
- containerPort: 11434
resources:
limits:
cpu: "2000m"
memory: "2Gi"
volumeMounts:
- name: ollama-volume
mountPath: /root/.ollama
tty: true
volumeClaimTemplates:
- metadata:
name: ollama-volume
spec:
accessModes: [ "ReadWriteOnce" ]
resources:
requests:
storage: 1Gi

View File

@ -0,0 +1,28 @@
apiVersion: apps/v1
kind: Deployment
metadata:
name: ollama-webui-deployment
namespace: ollama-namespace
spec:
replicas: 1
selector:
matchLabels:
app: ollama-webui
template:
metadata:
labels:
app: ollama-webui
spec:
containers:
- name: ollama-webui
image: ghcr.io/ollama-webui/ollama-webui:main
ports:
- containerPort: 8080
resources:
limits:
cpu: "500m"
memory: "500Mi"
env:
- name: OLLAMA_API_BASE_URL
value: "http://ollama-service.ollama-namespace.svc.cluster.local:11434/api"
tty: true

View File

@ -0,0 +1,20 @@
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: ollama-webui-ingress
namespace: ollama-namespace
#annotations:
# Use appropriate annotations for your Ingress controller, e.g., for NGINX:
# nginx.ingress.kubernetes.io/rewrite-target: /
spec:
rules:
- host: ollama.minikube.local
http:
paths:
- path: /
pathType: Prefix
backend:
service:
name: ollama-webui-service
port:
number: 8080

View File

@ -0,0 +1,15 @@
apiVersion: v1
kind: Service
metadata:
name: ollama-webui-service
namespace: ollama-namespace
spec:
type: NodePort # Use LoadBalancer if you're on a cloud that supports it
selector:
app: ollama-webui
ports:
- protocol: TCP
port: 8080
targetPort: 8080
# If using NodePort, you can optionally specify the nodePort:
# nodePort: 30000

View File

@ -0,0 +1,12 @@
resources:
- base/ollama-namespace.yaml
- base/ollama-service.yaml
- base/ollama-statefulset.yaml
- base/webui-deployment.yaml
- base/webui-service.yaml
- base/webui-ingress.yaml
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
patches:
- path: patches/ollama-statefulset-gpu.yaml

View File

@ -0,0 +1,17 @@
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: ollama
namespace: ollama-namespace
spec:
selector:
matchLabels:
app: ollama
serviceName: "ollama"
template:
spec:
containers:
- name: ollama
resources:
limits:
nvidia.com/gpu: "1"

237
run-compose.sh Executable file
View File

@ -0,0 +1,237 @@
#!/bin/bash
# Define color and formatting codes
BOLD='\033[1m'
GREEN='\033[1;32m'
WHITE='\033[1;37m'
RED='\033[0;31m'
NC='\033[0m' # No Color
# Unicode character for tick mark
TICK='\u2713'
# Detect GPU driver
get_gpu_driver() {
# Detect NVIDIA GPUs
if lspci | grep -i nvidia >/dev/null; then
echo "nvidia"
return
fi
# Detect AMD GPUs (including GCN architecture check for amdgpu vs radeon)
if lspci | grep -i amd >/dev/null; then
# List of known GCN and later architecture cards
# This is a simplified list, and in a real-world scenario, you'd want a more comprehensive one
local gcn_and_later=("Radeon HD 7000" "Radeon HD 8000" "Radeon R5" "Radeon R7" "Radeon R9" "Radeon RX")
# Get GPU information
local gpu_info=$(lspci | grep -i 'vga.*amd')
for model in "${gcn_and_later[@]}"; do
if echo "$gpu_info" | grep -iq "$model"; then
echo "amdgpu"
return
fi
done
# Default to radeon if no GCN or later architecture is detected
echo "radeon"
return
fi
# Detect Intel GPUs
if lspci | grep -i intel >/dev/null; then
echo "i915"
return
fi
# If no known GPU is detected
echo "Unknown or unsupported GPU driver"
exit 1
}
# Function for rolling animation
show_loading() {
local spin='-\|/'
local i=0
printf " "
while kill -0 $1 2>/dev/null; do
i=$(( (i+1) %4 ))
printf "\b${spin:$i:1}"
sleep .1
done
# Replace the spinner with a tick
printf "\b${GREEN}${TICK}${NC}"
}
# Usage information
usage() {
echo "Usage: $0 [OPTIONS]"
echo "Options:"
echo " --enable-gpu[count=COUNT] Enable GPU support with the specified count."
echo " --enable-api[port=PORT] Enable API and expose it on the specified port."
echo " --webui[port=PORT] Set the port for the web user interface."
echo " --data[folder=PATH] Bind mount for ollama data folder (by default will create the 'ollama' volume)."
echo " --build Build the docker image before running the compose project."
echo " --drop Drop the compose project."
echo " -q, --quiet Run script in headless mode."
echo " -h, --help Show this help message."
echo ""
echo "Examples:"
echo " ./$0 --drop"
echo " ./$0 --enable-gpu[count=1]"
echo " ./$0 --enable-api[port=11435]"
echo " ./$0 --enable-gpu[count=1] --enable-api[port=12345] --webui[port=3000]"
echo " ./$0 --enable-gpu[count=1] --enable-api[port=12345] --webui[port=3000] --data[folder=./ollama-data]"
echo " ./$0 --enable-gpu[count=1] --enable-api[port=12345] --webui[port=3000] --data[folder=./ollama-data] --build"
echo ""
echo "This script configures and runs a docker-compose setup with optional GPU support, API exposure, and web UI configuration."
echo "About the gpu to use, the script automatically detects it using the "lspci" command."
echo "In this case the gpu detected is: $(get_gpu_driver)"
}
# Default values
gpu_count=1
api_port=11435
webui_port=3000
headless=false
build_image=false
kill_compose=false
# Function to extract value from the parameter
extract_value() {
echo "$1" | sed -E 's/.*\[.*=(.*)\].*/\1/; t; s/.*//'
}
# Parse arguments
while [[ $# -gt 0 ]]; do
key="$1"
case $key in
--enable-gpu*)
enable_gpu=true
value=$(extract_value "$key")
gpu_count=${value:-1}
;;
--enable-api*)
enable_api=true
value=$(extract_value "$key")
api_port=${value:-11435}
;;
--webui*)
value=$(extract_value "$key")
webui_port=${value:-3000}
;;
--data*)
value=$(extract_value "$key")
data_dir=${value:-"./ollama-data"}
;;
--drop)
kill_compose=true
;;
--build)
build_image=true
;;
-q|--quiet)
headless=true
;;
-h|--help)
usage
exit
;;
*)
# Unknown option
echo "Unknown option: $key"
usage
exit 1
;;
esac
shift # past argument or value
done
if [[ $kill_compose == true ]]; then
docker compose down --remove-orphans
echo -e "${GREEN}${BOLD}Compose project dropped successfully.${NC}"
exit
else
DEFAULT_COMPOSE_COMMAND="docker compose -f docker-compose.yaml"
if [[ $enable_gpu == true ]]; then
# Validate and process command-line arguments
if [[ -n $gpu_count ]]; then
if ! [[ $gpu_count =~ ^[0-9]+$ ]]; then
echo "Invalid GPU count: $gpu_count"
exit 1
fi
echo "Enabling GPU with $gpu_count GPUs"
# Add your GPU allocation logic here
export OLLAMA_GPU_DRIVER=$(get_gpu_driver)
export OLLAMA_GPU_COUNT=$gpu_count # Set OLLAMA_GPU_COUNT environment variable
fi
DEFAULT_COMPOSE_COMMAND+=" -f docker-compose.gpu.yaml"
fi
if [[ $enable_api == true ]]; then
DEFAULT_COMPOSE_COMMAND+=" -f docker-compose.api.yaml"
if [[ -n $api_port ]]; then
export OLLAMA_WEBAPI_PORT=$api_port # Set OLLAMA_WEBAPI_PORT environment variable
fi
fi
if [[ -n $data_dir ]]; then
DEFAULT_COMPOSE_COMMAND+=" -f docker-compose.data.yaml"
export OLLAMA_DATA_DIR=$data_dir # Set OLLAMA_DATA_DIR environment variable
fi
DEFAULT_COMPOSE_COMMAND+=" up -d"
DEFAULT_COMPOSE_COMMAND+=" --remove-orphans"
DEFAULT_COMPOSE_COMMAND+=" --force-recreate"
if [[ $build_image == true ]]; then
DEFAULT_COMPOSE_COMMAND+=" --build"
fi
fi
# Recap of environment variables
echo
echo -e "${WHITE}${BOLD}Current Setup:${NC}"
echo -e " ${GREEN}${BOLD}GPU Driver:${NC} ${OLLAMA_GPU_DRIVER:-Not Enabled}"
echo -e " ${GREEN}${BOLD}GPU Count:${NC} ${OLLAMA_GPU_COUNT:-Not Enabled}"
echo -e " ${GREEN}${BOLD}WebAPI Port:${NC} ${OLLAMA_WEBAPI_PORT:-Not Enabled}"
echo -e " ${GREEN}${BOLD}Data Folder:${NC} ${data_dir:-Using ollama volume}"
echo -e " ${GREEN}${BOLD}WebUI Port:${NC} $webui_port"
echo
if [[ $headless == true ]]; then
echo -ne "${WHITE}${BOLD}Running in headless mode... ${NC}"
choice="y"
else
# Ask for user acceptance
echo -ne "${WHITE}${BOLD}Do you want to proceed with current setup? (Y/n): ${NC}"
read -n1 -s choice
fi
echo
if [[ $choice == "" || $choice == "y" ]]; then
# Execute the command with the current user
eval "$DEFAULT_COMPOSE_COMMAND" &
# Capture the background process PID
PID=$!
# Display the loading animation
#show_loading $PID
# Wait for the command to finish
wait $PID
echo
# Check exit status
if [ $? -eq 0 ]; then
echo -e "${GREEN}${BOLD}Compose project started successfully.${NC}"
else
echo -e "${RED}${BOLD}There was an error starting the compose project.${NC}"
fi
else
echo "Aborted."
fi
echo