ws-bom-robot-app 0.0.82

A FastAPI application serving ws bom/robot/llm platform ai.

🤖 ws-bom-robot-app

A FastAPI application serving ws bom/robot/llm platform ai

🌵 Minimal app structure

app/
|-- .env
|-- main.py

Fill main.py with the following code:

from ws_bom_robot_app import main
app = main.app

Create a .env file in the root directory with the following configuration:

# robot configuration
robot_env=development
robot_user=your_username
USER_AGENT=ws-bom-robot-app

# cms (bowl) configuration
robot_cms_host='http://localhost:4000'
robot_cms_auth='users API-Key your-api-key-here'

# llm providers: fill one or more of these with your API keys
DEEPSEEK_API_KEY="your-deepseek-api-key"
OPENAI_API_KEY="your-openai-api-key"
GOOGLE_API_KEY="your-google-api-key"
ANTHROPIC_API_KEY="your-anthropic-api-key"
GROQ_API_KEY="your-groq-api-key"
# ibm
WATSONX_URL="https://eu-gb.ml.cloud.ibm.com"
WATSONX_APIKEY="your-watsonx-api-key"
WATSONX_PROJECTID="your-watsonx-project-id"
# gvertex: ensure to mount the file in docker
GOOGLE_APPLICATION_CREDENTIALS="./.data/secrets/google-credentials.json" 

🚀 Run the app

• development

  fastapi dev --port 6001
  #uvicorn main:app --app-dir ./ws_bom_robot_app --reload --reload-dir ws_bom_robot_app --host 0.0.0.0 --port 6001 
  

• production

  uvicorn main:app --host 0.0.0.0 --port 6001  
  

• production with multipler workers

  fastapi run --port 6001 --workers 4
  #uvicorn main:app --host 0.0.0.0 --port 6001 --workers 4
  #gunicorn -w 4 -k uvicorn.workers.UvicornWorker main:app --bind
  

📖 API documentation

• swagger
• redoc

---

🐳 Docker

dockerize base image

<# cpu #>
#docker build -f Dockerfile-robot-base-cpu -t ws-bom-robot-base:cpu .
#docker tag ws-bom-robot-base:cpu ghcr.io/websolutespa/ws-bom-robot-base:cpu
docker build -f Dockerfile-robot-base-cpu -t ghcr.io/websolutespa/ws-bom-robot-base:cpu .
docker push ghcr.io/websolutespa/ws-bom-robot-base:cpu
<# gpu #>
docker build -f Dockerfile-robot-base-gpu -t ghcr.io/websolutespa/ws-bom-robot-base:gpu .
docker push ghcr.io/websolutespa/ws-bom-robot-base:gpu

dockerize app (from src)

docker build -f Dockerfile -t ws-bom-robot-app .
docker run --rm -d --env-file .env -p 6001:6001 ws-bom-robot-app

dockerize app (from latest)

docker build -f Dockerfile-pkg -t ws-bom-robot-app-pkg .
docker run --rm -d --env-file .env -p 6001:6001 ws-bom-robot-app-pkg

docker run mounted to src (dev mode)

docker run --rm  -d --env-file .env -v "$(pwd)/.data:/app/.data" -p 6001:6001 ws-bom-robot-app fastapi dev ./ws_bom_robot_app/main.py --host 0.0.0.0 --port 6001
docker run --rm  -d --env-file .env -v "$(pwd)/.data:/app/.data" -p 6001:6001 ws-bom-robot-app uvicorn ws_bom_robot_app.main:app --reload --host 0.0.0.0 --port 6001

---

🔖 Windows requirements (for RAG functionality only)

⚠️ While it's strongly recommended to use a docker container for development, you can run the app on Windows with the following requirements

libmagic (mandatory)

py -m pip install --upgrade python-magic-bin

tesseract-ocr (mandatory)

Install tesseract Last win-64 release

Add tesseract executable (C:\Program Files\Tesseract-OCR) to system PATH

$pathToAdd = "C:\Program Files\Tesseract-OCR"; `
$currentPath = [System.Environment]::GetEnvironmentVariable("Path", [System.EnvironmentVariableTarget]::Machine); `
if ($currentPath -split ';' -notcontains $pathToAdd) { `
  [System.Environment]::SetEnvironmentVariable("Path", "$currentPath;$pathToAdd", [System.EnvironmentVariableTarget]::Machine) `
}

docling

Set the following environment variables

KMP_DUPLICATE_LIB_OK=TRUE

libreoffice (optional: for robot_env set to development/production)

Install libreoffice Last win-64 release

Add libreoffice executable (C:\Program Files\LibreOffice\program) to system PATH

$pathToAdd = "C:\Program Files\LibreOffice\program"; `
$currentPath = [System.Environment]::GetEnvironmentVariable("Path", [System.EnvironmentVariableTarget]::Machine); `
if ($currentPath -split ';' -notcontains $pathToAdd) { `
  [System.Environment]::SetEnvironmentVariable("Path", "$currentPath;$pathToAdd", [System.EnvironmentVariableTarget]::Machine) `
}

poppler (optional: for robot_env set to development/production)

Download win poppler release Extract the zip, copy the nested folder "poppler-x.x.x." to a program folder (e.g. C:\Program Files\poppler-24.08.0) Add poppler executable (C:\Program Files\poppler-24.08.0\Library\bin) to system PATH

$pathToAdd = "C:\Program Files\poppler-24.08.0\Library\bin"; `
$currentPath = [System.Environment]::GetEnvironmentVariable("Path", [System.EnvironmentVariableTarget]::Machine); `
if ($currentPath -split ';' -notcontains $pathToAdd) { `
  [System.Environment]::SetEnvironmentVariable("Path", "$currentPath;$pathToAdd", [System.EnvironmentVariableTarget]::Machine) `
}

---

👷 Contributors

Build/distribute pkg from websolutespa bom [Github]

dir in robot project folder

  cd ./src/robot

🔖 requirements

py -m pip install --upgrade setuptools build twine streamlit 

🪛 build

if (Test-Path ./dist) {rm ./dist -r -force}; `
py -m build && twine check dist/*

📦 test / 🧪 debugger

Install the package in editable project location

py -m pip install -U -e .
py -m pip show ws-bom-robot-app

code quality tools

# .\src\robot
!py -m pip install -U scanreq prospector[with_everything]
## unused requirements
scanreq -r requirements.txt -p ./ws_bom_robot_app
## style/linting
prospector ./ws_bom_robot_app -t pylint -t pydocstyle
## code quality/complexity
prospector ./ws_bom_robot_app -t vulture -t mccabe -t mypy 
## security
prospector ./ws_bom_robot_app -t dodgy -t bandit
## package
prospector ./ws_bom_robot_app -t pyroma

🧪 run tests

!py -m pip install -U pytest pytest-asyncio pytest-mock pytest-cov pyclean
# clean cache if needed
# pyclean --verbose .
pytest --cov=ws_bom_robot_app --log-cli-level=info
# directory
# pytest --cov=ws_bom_robot_app --log-cli-level=info ./tests/app/llm/vector_store/db

🐞 start debugger

streamlit run debugger.py --server.port 8051

✈️ publish

• testpypi

  twine upload --verbose -r testpypi dist/*
  #pip install -i https://test.pypi.org/simple/ -U ws-bom-robot-app 
  

• pypi

  twine upload --verbose dist/*