postgresql

•  ubuntu 24.04 install postgresql

• sudo apt install postgresql postgresql-contrib > Y
• sudo systemctl enable postgresql.service
• sudo systemctl start postgresql.service

• test
• sudo -i -u postgres
• psql
• \q
• exit

• create user
• sudo -i -u postgres
• createuser --interactive
• >myuser
• >n,n,n
• createdb mydb
• psql
• sudo -u postgres psql
• ALTER USER myuser WITH PASSWORD 'pass';
• GRANT ALL PRIVILEGES ON DATABASE mydb TO myuser;
• \q

• connect config
• sudo nano /etc/postgresql/XX/main/postgresql.conf
• listen_addresses = '*'
• sudo nano /etc/postgresql/16/main/pg_hba.conf
• IPV4
• host    db       user       ip           mode:md5(trust)

• firewall config
• sudo ufw enable
• sudo ufw start
• sudo ufw allow ssh
• sudo ufw allow 5432/tcp
• sudo ufw status numbered
• sudo ufw logging on

• debug can not connect
• sudo lsof -i :5432
• test connect
• psql -h out_host -U user -d database  

• Note
• $ sudo -u postgres psql
• postgres=# CREATE DATABASE yourdbname;
• postgres=# CREATE USER youruser WITH ENCRYPTED PASSWORD 'yourpass';
• postgres=# GRANT ALL PRIVILEGES ON DATABASE yourdbname TO youruser;

iTOP

•  https://www.combodo.com/itop-193
• docker run -d -p 8080:80 --name=my-itop -v my-itop-conf-volume:/var/www/html/conf -v my-itop-db-volume:/var/lib/mysql vbkunin/itop

• docker exec my-itop chown www-data:www-data /var/www/html/conf
• get mysql pass to install:
• win>
• docker logs my-itop | Select-String -Pattern "Your MySQL user 'admin' has password:" -Context 1,7
• linux>
• docker logs my-itop | grep -A7 -B1 "Your MySQL user 'admin' has password:"
• http://localhost:8080/ install and use itil

Wazuh

•  git clone https://github.com/wazuh/wazuh-docker.git -b v4.9.2

• cd wazuh-docker/single-node/
• modify docker-compose.yml
• #change 443 to your port
• #modify memory or  CPU limit
• docker-compose -f generate-indexer-certs.yml run --rm generator
• docker-compose up -d

• open https://ip:your_port or space(443) to check is running
• admin:SecretPassword
• modify default password

• Agent
• https://wazuh.com/install/
• docker ps
• docker exec -it single-node-wazuh.manager-1 or com-id /bin/bash
• bash-5.2# /var/ossec/bin/manage_agents
• ****************************************
• * Wazuh v4.9.2 Agent manager.          *
• * The following options are available: *
• ****************************************
•    (A)dd an agent (A).
•    (E)xtract key for an agent (E).
•    (L)ist already added agents (L).
•    (R)emove an agent (R).
•    (Q)uit.
• Choose your action: A,E,L,R or Q:
• 1.Press (A) to set a new agent with name (Computer's name), IP (any)
• 2.Press (L) to find ID 00x
• 3.Press (E) to create auth key
• get the auth key to keyin agent on win or linux
• check wazuh run on services.msc

install ubuntu

• install ubunto 24.04.1 

• sudo apt-get install openssh-server
• sudo systemctl start ssh
• sudo systemctl enable ssh

• sudo ufw enable
• sudo ufw allow ssh

• sudo reboot

• sudo apt upgrade -y && sudo apt update -y
• sudo apt upgrade -y && sudo apt update -y

clamav for linux

• sudo apt update && sudo apt upgrade
• sudo apt install clamav clamav-daemon -y 
• sudo systemctl stop clamav-freshclam.service
• sudo freshclam
• sudo systemctl start clamav-freshclam.service
• #sudo clamscan -r /path/to/folder
• sudo systemctl enable clamav-daemon
• sudo systemctl enable clamav-freshclam.service

create ocs on docker

•  git clone https://github.com/OCSInventory-NG/OCSInventory-Docker-Image
• cd OCSInventory-Docker-Image
• cd new_version
• modify docker-compose.yml config ports
• PS>docker-compose up -d

F5-TTS

Env

• conda create -n f5tts python=3.10
• conda activate f5tts

(apt install -y ffmpeg)

Python

• pip uninstall torch torchvision torchaudio transformers
• pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
• pip install transformers

Git

• git clone https://github.com/SWivid/F5-TTS.git

Run

• cd F5-TTS
• pip install -e .
• f5-tts_infer-gradio --port 7865 --host 0.0.0.0 --share

Kotaemon AI/RAG

Install on docker

• docker run -e GRADIO_SERVER_NAME=0.0.0.0 -e GRADIO_SERVER_PORT=7860 -p 7860:7860 --name kotaemon -d ghcr.io/cinnamon/kotaemon:main-full 
• no --it --rm

iRedMail Old to New

Ubuntu 24.04

Install iRedMail : https://docs.iredmail.org/install.iredmail.on.debian.ubuntu.html

Check : Important things you MUST know after installation

Conf : https://docs.iredmail.org/file.locations.html

Addtion: https://spiderd.io/ 

• Roundcube webmail: https://your_server/mail/
• SOGo Groupware: https://your_server/SOGo
• Web admin panel (iRedAdmin): https://your_server/iredadmin/

Ubuntu: 

• sudo systemctl enable ufw 
• sudo ufw allow smtps pop3s
• sudo reboot

Use old dkim : https://docs.iredmail.org/sign.dkim.signature.for.new.domain.html#use-existing-dkim-key-for-new-mail-domain

• copy pem from oldsvr, path /var/lib/dkim/domain.pem to newsvr(use:sudo su)
• modify newsvr /etc/amavis/conf.d/50-user before # Disclaimer settings(see oldsvr /etc/amavisd/amavisd.conf)
  dkim_key('domain.com', 'dkim', '/var/lib/dkim/domain.com.pem');
  @dkim_signature_options_bysender_maps = ({
      # 'd' defaults to a domain of an author/sender address,
      # 's' defaults to whatever selector is offered by a matching key
      # Per-domain dkim key
      #"domain.com"  => { d => "domain.com", a => 'rsa-sha256', ttl => 10*24*3600 },
      # catch-all (one dkim key for all domains)
      '.' => {d => 'domain.com',
                 a => 'rsa-sha256',
                 c => 'relaxed/simple',
                 ttl => 30*24*3600 },
      });
• sudo reboot
• sudo amavisd testkeys (=>pass)

Fail2Ban

• modify /etc/fail2ban/jail.local
• modify /etc/postfix/helo_access.pcre
• sudo su, cd /opt/iredapd/tools
  python wblist_admin.py --list --whitelist for oldsvr to list....
  sudo python3 wblist_admin.py --list --whitelist for newsvr ....
  >> sudo python3 wblist_admin.py --add --whitelist ip or domain from oldsvr

Create Cert

Let's Encrypt offers FREE SSL certificate.

https://docs.iredmail.org/letsencrypt.html

• sudo apt install -y certbot
• sudo certbot certonly --webroot --dry-run -w /var/www/html -d mail.domain.com
• sudo certbot certonly --webroot -w /var/www/html -d mail.domain.com

Backup Cert

• mv /etc/ssl/certs/iRedMail.crt /etc/ssl/certs/iRedMail.crt.bak
• mv /etc/ssl/private/iRedMail.key /etc/ssl/private/iRedMail.key.bak

Use New Cert

• ln -s /etc/letsencrypt/live/mail.domain.com/fullchain.pem /etc/ssl/certs/iRedMail.crt
• ln -s /etc/letsencrypt/live/mail.domain.com/privkey.pem /etc/ssl/private/iRedMail.key

Restart Service

• sudo systemctl restart postfix dovecot nginx

use axolotl for trainning

Env

• no internet
• qlora_root c:\qlora
• gguf_root c:\gguf

Dataset 

• c:/qlora/output_dataset/instruction_dataset.parquet

PS:Axolotl

• docker run --gpus '"all"' --rm -it winglian/axolotl:main-latest

PS:Dataset

• docker cp C:\qlora\output_dataset\instruction_dataset.parquet container_name:/workspace/axolotl/examples/instruction_dataset.parquet

PS:LLM

• docker cp C:\Meta-Llama-3.1-8B container_name:/workspace/axolotl/examples/Meta-Llama-3.1-8B/

Axolotl:Qlora

• open ./examples/llama-3/qlora.yml find and modify path of llm and parquet

Axolotl:Trainning

• CUDA_VISIBLE_DEVICES="" python -m axolotl.cli.preprocess examples/llama-3/qlora.yml
• accelerate launch -m axolotl.cli.train examples/llama-3/qlora.yml

Axolotl:Test(need internet)

• accelerate launch -m axolotl.cli.inference examples/llama-3/qlora.yml --lora_model_dir="./outputs/qlora-out" --gradio

Axolotl:Merged

• python3 -m axolotl.cli.merge_lora examples/llama-3/qlora.yml --lora_model_dir="./outputs/qlora-out"

PS:Export

• docker cp container_name:/workspace/axolotl/outputs/qlora-out/merged C:\merged

GGUF

• convert to merged_f16.gguf

Ollama

• ollama run merged

unsloth

Conda

• conda install -c conda-forge xformers
• pip install xformers
• conda config --add channels conda-forge
• conda update conda

Env

• conda create --name unsloth python=3.11 pytorch-cuda=12.1 pytorch cudatoolkit -c pytorch -c nvidia -y
• conda activate unsloth
• pip install xformers

Install

• pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
• pip install --no-deps trl peft accelerate bitsandbytes

Huggingface model convert gguf

config env

• mkdir model and cd model
• conda create -n gguf
• conda activate gguf
• pip install huggingface_hub

dl model from hf:get model_id,local_dir

• create file:download.py and save
  from huggingface_hub import snapshot_download
  model_id="Qwen/Qwen2-1.5B-Instruct"
  snapshot_download(repo_id=model_id, local_dir="Qwen2-1.5B-Instruct",local_dir_use_symlinks=False, revision="main")
• python download.py

config llama.cpp

• cd ..
• git clone https://github.com/ggerganov/llama.cpp.git
• cd llama.cpp
• pip install -r requirements.txt

run python llama.cpp/convert_hf_to_gguf.py -h

convert

• cd ..
  check path for directory of model
• #full f16 or f32
  python ./llama.cpp/convert_hf_to_gguf.py ./model/qwen2_1.5b_instruct  --outtype f32 --verbose --outfile ./Qwen2-1.5B-Instruct_f32.gguf
• #q2_k,q3_k_l/q3_k_m/q3_k_s,q4_0/q4_1/q4_k_m/q4_k_s,q5_0/q5_1/q5_k_m/q5_k_s,q6_k,q8_0,fp16/f32
  python ./llama.cpp/convert_hf_to_gguf.py ./model/qwen2_1.5b_instruct  --outtype q8_0 --verbose --outfile ./Qwen2-1.5B-Instruct_q8_0.gguf

perplexica update

Check

• docker volume ls | perplexica_backend-dbstore
• docker run -it --rm -v perplexica_backend-dbstore:/data busybox ls -l /data

Backup

• docker run --rm -v perplexica_backend-dbstore:/data -v C:/backup:/backup busybox tar cvf /backup/perplexica_backend-dbstore.tar /data

Remove

• docker remove old container

Update

• goto perplexica of directory and run git pull origin master
• check config.toml and docker-compose.yaml

ReBuild

• goto perplexica of directory and docker compose up -d --build

Recovery

• docker run --rm -v perplexica_backend-dbstore:/data -v C:/backup:/backup busybox tar xvf /backup/perplexica_backend-dbstore.tar -C /data

Check

• docker run -it --rm -v perplexica_backend-dbstore:/data busybox ls -l /data

anythingllm update(update 2024.09.23)

Get-New

• docker pull mintplexlabs/anythingllm

Remove

• docker remove old container

Run

• docker run -d -p 3001:3001 --cap-add SYS_ADMIN -v C:/anythingllm/storage:/app/server/storage -v C:/anythingllm/env.txt:/app/server/.env -e STORAGE_DIR="/app/server/storage" --add-host=host.docker.internal:host-gateway --name anythingllm mintplexlabs/anythingllm

---------------------------------------

use github to pull to docker and update

• git clone https://github.com/Mintplex-Labs/anything-llm
• copy ./docker to ./anythingllm
• into ./anything-llm/anythingllm and rename .env.example to .env
• PS>docker compose up -d (--build)

change port number

• .env
  SERVER_PORT=3001
• docker-compose.yml
  ports:
  - "3001:3001"

change name

• docker-compose.yml
  name: anythingllm
  container_name: anythingllm

Chroma update

 

Backup

• docker volume ls
• docker run --rm -v chroma_chroma-data:/data -v C:/backup:/backup busybox tar cvf /backup/chroma_chroma-data.tar /data

Remove

• docker remove old container

Get-New

• get new version from https://github.com/chroma-core/chroma/releases
• docker pull ghcr.io/chroma-core/chroma:0.5.4
• docker run -p 8000:8000 ghcr.io/chroma-core/chroma:0.5.4

Recovery

• docker run --rm -v chroma_chroma-data:/data -v C:/backup:/backup busybox tar xvf /backup/chroma_chroma-data.tar -C /data
• docker run -it --rm -v chroma_chroma-data:/data busybox ls -l /data

SenseVoice

Get 

• git clone https://github.com/FunAudioLLM/SenseVoice.git

Env

• conda create -n sensevoice python=3.8
• conda activate sensevoice

Install

• cd sensevoice
• pip install -r requirements.txt

Run

• python webui.py

Change port

• demo.launch(server_port=your_portnumber,share=True,server_name='your_ip')

Chroma for AI(update 2024.09.23)

Get1

•  docker pull ghcr.io/chroma-core/chroma:0.5.4

Get2

• git clone https://github.com/chroma-core/chroma.git
• docker compose up -d

Update1

• watch version on https://github.com/chroma-core/chroma
• docker pull ghcr.io/chroma-core/chroma:version

Update2

•  goto chroma of directory
• PS>docker compose up -d --build

-----------------------------------------------

you can use github to pull to docker

• git clone https://github.com/chroma-core/chroma
• cd ./chroma and copy compose-env.windows .env
• rename docker-compose.yml to docker-compose-any.yml
• copy docker-compose.server.example.yml to docker-compose.yml
• PS>docker compose up -d (--build)

LangFlow

Github

• git clone https://github.com/langflow-ai/langflow.git

Docker

• cd langflow
• copy ./docker_example ./langflow (or your_name_for_docker)
• open and config(ChangePort) langflow/langflow  (or your_name_for_docker)/docker-compose.yml
• PowerShell>
  cd langflow/langflow  (or your_name_for_docker)
  docker compose up -d (--build)

Run

• Open http://localhost:7860/store and Click API_Key
• Login https://www.langflow.store/ and get API-Key

ChatTTS

It good than Bark

Github

• git clone https://github.com/2noise/ChatTTS.git
• cd ChatTTS

Env

• conda create -n chattts python=3.8
• conda activate chattts

Install

• pip install --upgrade -r requirements.txt
• pip install -r requirements.txt

Run

• python examples/web/webui.py

Change port, public link

• open ChatTTS\examples\web\webui.py
• find
  demo.launch()
• and add args
  server_name='0.0.0.0'
  server_port=7860
  share=True

LivePortrait

• ffmpeg (https://www.ffmpeg.org/)
  download > win > Windows builds from gyan.dev > release builds > ffmpeg-release-full.7z
  move bin/*.exe to windows/system32/
• conda create -n liveportrait python=3.9 and activate it
• d1: git clone https://github.com/KwaiVGI/LivePortrait
• d2: git clone from hugiingface https://huggingface.co/KwaiVGI/LivePortrait
  move both directory insightface and liveportrait to d1 ./pretrained_weights/ 
• run for cmd
  first: python  inference.py to create sample in d1 ./animations
  custom: python  inference.py -s d1 .\LivePortrait\assets\examples\source\?.jpg d1 .\LivePortrait\assets\examples\driving\?.mp4 and see outpurt in d1 ./animations
• run for webgui
  python app.py and open 127.0.0.1:8890
  public: modify d1 .\LivePortrait\src\config\argument_config.py server_ip, server_port, and share for true

Moodle

Get

• git clone -b MOODLE_404_STABLE git://git.moodle.org/moodle.git on /pathto/moodle/
• chown -R root /pathto/moodle/
• chmod -R 0755 /pathto/moodle/
• find /pathto/moodle/ -type f -exec chmod 0644 {} \;

MoodleData

• mkdir /pathto/moodledata
• chmod 0777 /pathto/moodledata
• setfacl -R -m u:$(whoami):rwX /pathto/moodledata
• setfacl -R -d -m u:$(whoami):rwX /pathto/moodledata

Security

• goto /home/moodle/moodledata and create file of .htaccess
  order deny,allow
  deny from all

Install

• open localhost/moodle to install
• create moodle/config.php
  chmod -R 0644 moodle/config.php

mysql upgrade 5 to 8

Backup

• mkdir mysqlbk
• mysqldump ---all-databases --routines --events > ~/mysqlbk/mysql_backup.sql
• cp /etc/my.cnf ~/mysqlbk/my.cnf
• cp -R /etc/my.cnf.d/ ~/mysqlbk/etc_my.cnf.d/
• cp -R /var/lib/mysql/ ~/mysqlbk/var_lib_mysql/
• mysql -u -p
  mysql> open mysql
  mysql> SELECT User, Host FROM mysql.user;  # list user and backup

Upgrade

• rpm -e --nodeps mysql57-community-release
• yum update -y
• rpm --import https://repo.mysql.com/RPM-GPG-KEY-mysql-2023
• yum install -y https://repo.mysql.com/mysql84-community-release-el7-1.noarch.rpm
• yum makecache
• systemctl stop mysqld.service
• yum remove -y mysql-community-client-5.7* mysql-community-common-5.7* mysql-community-libs-5.7* mysql-community-server-5.7* 
• yum install mysql-community-server
• systemctl start mysqld.service

ERROR:Data Dictionary initialization failed.

• rm -rf /var/lib/mysql
• mysqld --initialize --console
• chown -R mysql:mysql /var/lib/mysql
• systemctl start mysqld

Config

• grep 'temporary password' /var/log/mysqld.log
• mysql_secure_installation

Perplexica - AI Search

Before

• install git & lfs
• install docker
• install ollama and llm

Install

• git clone https://github.com/ItzCrazyKns/Perplexica
• goto directory of perplexica
• rename .\Perplexica\sample.config.toml .\Perplexica\config.toml
• powershell> docker compose up -d (--build)
• open localhost:3000

Default Port Change [3001]

• open config.toml
• find [GENERAL] PORT = 3001 # Port to run the server on
• change 3001 to your_port
• open docker-compose.yaml
• find ports: - 3001:3001
• change 3001 to your_port both
• find 2line like NEXT_PUBLIC
• change 3001 to your_port

Run on public IP

• open config.toml
• find [API_ENDPOINTS] SEARXNG = and OLLAMA =
• change to your_ip
• open docker-compose.yaml
• find 2line like NEXT_PUBLIC_
• change to your_public_ip
• config your win's env 
• OLLAMA_HOST=0.0.0.0

UPDATE

• stop perplexica on docker
• goto directory of perplexica
• git pull origin master
• check config.toml and docker-compose.yaml
• powershell> docker compose up -d --build

Bark

 Bark

• Git
  git clone https://github.com/C0untFloyd/bark-gui
• Anaconda
• Install
  pip install .
  pip install -r requirements.txt
• Run
  python webui.py
• WEB
  Open http://127.0.0.1:7860
• ERROR:bark Audio.__init__() got an unexpected keyword argument 'source'
  pip uninstall gradio
  pip install gradio==3.50.2

AnythingLLM with Ollama

1.Install Ollama First

2.chroma install use docker

• PS>> docker pull ghcr.io/chroma-core/chroma:0.4.24
• PS>> docker run -p 8000:8000 ghcr.io/chroma-core/chroma:0.4.24

3.anythingllm install use docker

• create directory C:/anythingllm/storage and file C:/anythingllm/env.txt
• PS>> docker run -d -p 3001:3001 --cap-add SYS_ADMIN -v C:/anythingllm/storage:/app/server/storage -v C:/anythingllm/env.txt:/app/server/.env -e STORAGE_DIR="/app/server/storage" --add-host=host.docker.internal:host-gateway --name anythingllm mintplexlabs/anythingllm
• Open localhost:3001, and config llm setting to use http://host.docker.internal:11434

2024/8/4

UPDATE

• Stop anythingllm on docker
• PS> docker pull mintplexlabs/anythingllm
• Start anythingllm on docker

LLama-Factory

 For Windows

• Download and Unzip file from https://github.com/hiyouga/LLaMA-Factory and Unzip
• Install rustup‑init.exe from https://rustup.rs/
• Use Anconda create a env and activate
• Install Anconda ( https://www.anaconda.com/download )
• Install Python ( https://www.python.org/downloads/ )
• Install Pytorch ( https://pytorch.org/get-started/locally/ , just use conda to install 12.x )
• # Test CUDA with GPU
• python
• >> import torch
• >> torch.cuda.is_available()
• true
• cd llama-factory directory
• pip install -r requirements.txt
• pip install https://github.com/jllllll/bitsandbytes-windows-webui/releases/download/wheels/bitsandbytes-0.39.1-py3-none-win_amd64.whl
• python .\src\train_web.py
• Open localhost:7860 and Train your LLM

Use Ollama with Chatbot-Ollama to use local LLM files.

Just go

• Download and Install ollama from ollama.com or ollama.ai
• Open http://127.0.0.1:11434/ to show [ollama is running]
• Use PowerShell to use ollama
  command: ollama list , to list all model
  command: ollama rm modelname , to del model
• Install docker manager and use it to install chatbox-ollama
• Open http://127.0.0.1:3000/
• Use already download model files
• Create a Modelfile as your_modelname, and config LLM path like below
  FROM c:\path\your_modelname.gguf
  SYSTEM ""
• Open powershell and goto your_modelname file of directory, run command like below
  ollama create your_modelname -f ./your_modelname
  ollama run your_modelname(>> /bye to exit)
• Open http://127.0.0.1:3000/zh , chat with llm