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When using `DownloadPipelineArtifact` as opposed to `download`, the artifacts are flattened into $(Pipeline.Workspace) (rather than being placed into a sub-folder named after the artifact). This updates the baseline path to point to the correct location for downloaded NLU results. |
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| .azdo | ||
| .config | ||
| docs | ||
| extensions | ||
| models | ||
| src | ||
| .gitignore | ||
| LICENSE | ||
| README.md | ||
| SECURITY.md | ||
| _config.yml | ||
README.md
NLU.DevOps · 
Continuous integration and deployment of NLU models.
Getting Started
Getting Started with the NLU.DevOps Azure DevOps extension
We have published an Azure DevOps extension that wraps the steps below into three pipeline tasks for training, testing and deleting your NLU model. To get started, install the NLU.DevOps extension to your Azure DevOps organization.
See the Azure DevOps extension overview for more details.
Detailed information for each Azure Pipelines task can be found in the docs folder:
Getting Started with the NLU.DevOps CLI
To install the NLU.DevOps CLI tool, run:
dotnet tool install -g dotnet-nlu
This will install the CLI tool to your default .NET Core tools path. See the documentation on the dotnet tool install command for more information on how to customize the installation directory or package source.
The CLI tool by default supports training and testing NLU models against LUIS and Lex.
Detailed information on the CLI tool sub-commands and arguments can be found in the docs folder:
- Training an NLU model
- Testing an NLU model
- Tearing down an NLU model
- Analyzing NLU model results
- Generic utterances model
- Extending the generic utterance model
- LUIS model configuration
- LUIS endpoint configuration
- Lex bot configuration
- Lex endpoint configuration
- Dialogflow endpoint configuration
- Configuring LUIS CI/CD with Azure Pipelines
- Extending the CLI to new NLU providers
Contributing
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.
When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
For more information on reporting potential security vulnerabilities, see the Security overview.