Semantic Kernel - Code Interpreter Plugin with Azure Container Apps
This example demonstrates how to do AI Code Interpretetion using a Plugin with Azure Container Apps to execute python code in a container.
Create and Configure Azure Container App Session Pool
- Create a new Container App Session Pool using the Azure CLI or Azure Portal.
- Specify "Python code interpreter" as the pool type.
- Add the following roles to the user that will be used to access the session pool:
- The
Azure ContainerApps Session Executorrole to be able to create and manage sessions. - The
Container Apps SessionPools Contributorrole to be able to work with files.
- The
Configuring Secrets
The example require credentials to access OpenAI and Azure Container Apps (ACA)
If you have set up those credentials as secrets within Secret Manager or through environment variables for other samples from the solution in which this project is found, they will be re-used.
To set your secrets with Secret Manager:
dotnet user-secrets init
dotnet user-secrets set "OpenAI:ApiKey" "..."
dotnet user-secrets set "OpenAI:ChatModelId" "gpt-3.5-turbo" # or any other function callable model.
dotnet user-secrets set "AzureContainerAppSessionPool:Endpoint" " .. endpoint .. "
To set your secrets with environment variables
Use these names:
# OpenAI
OpenAI__ApiKey
OpenAI__ChatModelId
# Azure Container Apps
AzureContainerAppSessionPool__Endpoint
Usage Example
User: Upload the file c:\temp\code-interpreter\test-file.txt
Assistant: The file test-file.txt has been successfully uploaded.
User: How many files I have uploaded ?
Assistant: You have uploaded 1 file.
User: Show me the contents of this file
Assistant: The contents of the file "test-file.txt" are as follows:
the contents of the file