Skip to main content

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

Project description

🤖 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 
    #uvicorn main:app --app-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


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

dockerize app (from src)

  • cpu
docker build -f Dockerfile -t ws-bom-robot-app:cpu --build-arg DEVICE=cpu .
docker run --rm -d --name ws-bom-robot-app --env-file .env -p 6001:6001 ws-bom-robot-app:cpu
  • gpu
docker build -f Dockerfile -t ws-bom-robot-app:gpu --build-arg DEVICE=gpu .
docker run --rm -d --name ws-bom-robot-app --gpus all --env-file .env -p 6001:6001 ws-bom-robot-app:gpu

dockerize app (from latest)

  • cpu
docker build -f Dockerfile-pkg -t ws-bom-robot-app-pkg:cpu --build-arg DEVICE=cpu .
docker run --rm -d --name ws-bom-robot-app-pkg --env-file .env -p 6001:6001 ws-bom-robot-app-pkg:cpu
  • gpu
docker build -f Dockerfile-pkg -t ws-bom-robot-app-pkg:gpu --build-arg DEVICE=gpu .
docker run --rm -d --name ws-bom-robot-app-pkg --gpus all --env-file .env -p 6001:6001 ws-bom-robot-app-pkg:gpu
<# test gpu: nvidia-smi #>

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

  • install uv venv package management
py -m pip install --upgrade uv
# create venv
uv venv
# activate venv
#win: .venv/Scripts/activate
#linux: source .venv/bin/activate
  • project requirements update
uv pip install --upgrade -r requirements.txt
  • build tools
uv pip install --upgrade setuptools build twine streamlit 

🪛 build

  • clean dist and build package
if (Test-Path ./dist) {rm ./dist -r -force}; `
py -m build && twine check dist/*
  • linux/mac
[ -d ./dist ] && rm -rf ./dist
python -m build && twine check dist/*

📦 test / 🧪 debugger

Install the package in editable project location

uv pip install -U -e .
uv pip show ws-bom-robot-app

code quality tools

# .\src\robot
uv 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

uv 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.llm.vector_store --log-cli-level=info ./tests/app/llm/vector_store

🐞 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/* 
    

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ws_bom_robot_app-0.0.121.tar.gz (96.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ws_bom_robot_app-0.0.121-py3-none-any.whl (125.4 kB view details)

Uploaded Python 3

File details

Details for the file ws_bom_robot_app-0.0.121.tar.gz.

File metadata

  • Download URL: ws_bom_robot_app-0.0.121.tar.gz
  • Upload date:
  • Size: 96.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.7

File hashes

Hashes for ws_bom_robot_app-0.0.121.tar.gz
Algorithm Hash digest
SHA256 10fd35eda91314444f2400517cbd58e8a490f317d873aa84dcbd1132281bf4d6
MD5 e5e700bbc4001de3ff6573bcb8366381
BLAKE2b-256 25522495b939c2cc802899cf235de86b1cdacd84c0ccdc2aa1363db40c897608

See more details on using hashes here.

File details

Details for the file ws_bom_robot_app-0.0.121-py3-none-any.whl.

File metadata

File hashes

Hashes for ws_bom_robot_app-0.0.121-py3-none-any.whl
Algorithm Hash digest
SHA256 bef8afe9c6bda79f0f6099fb820ce842215e5bafb85665474616656d56ab5018
MD5 013337bfd1fcdcb4fed6979057cc83b7
BLAKE2b-256 74e0fe28fc2cc633aafac47be4fa2f96f503e1f8a93017a41b46568e059793c3

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page