This uses OpenAI API Whisper(whisper-1), DALL-E, GPT(gpt-3.5-turbo), also Azure OpenAI and Google PaLM (https://developers.generativeai.google)
export required environment variables
export AZURE_REGISTRY_NAME = "Set Azure Container registry name here"
export P_MONGODB_DATABASE = "Mongo database"
export P_MONGODB_URI = "Mongo connection string"
build a docker image locally or use GitHub Workflow action
docker build --rm --pull \
--file "Dockerfile" \
--label "com.$AZURE_REGISTRY_NAME.ask-picturize-it" \
--tag "ask-picturize-it:latest" \
.
Run and test
docker run -e P_MONGODB_DATABASE -e P_MONGODB_URI -it --publish 80:80 --publish 27017:27017 ask-picturize-it:latest
Login to Azure Container registry
az login --use-device-code
az acr login --name $AZURE_REGISTRY_NAME.azurecr.io
Tag and Push the docker image to the Azure Container registry
docker tag ask-picturize-it $AZURE_REGISTRY_NAME.azurecr.io/ask-picturize-it
docker push $AZURE_REGISTRY_NAME.azurecr.io/ask-picturize-it
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Use https://jupyter.org (locally, or on the Cloud or in GitHub Codespaces) or Login to https://ml.azure.com and use Notebooks
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Clone repo and rename env.example to .env and set values to variables
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uncomment following lines
#from dotenv import load_dotenv #load_dotenv()
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Install
pip install python-dotenv
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Run to install dependencies
pip install -r requirements.txt
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Install pip install p2j
pip install p2j
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Run to convert py to ipynb
p2j app.py