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Copy file name to clipboardExpand all lines: README.md
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|[analyzer_training.ipynb](notebooks/analyzer_training.ipynb)| Provide training data to improve the quality of your analyzer |
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## Getting started with GitHub Codespaces
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## Getting started
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### GitHub Codespaces
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You can run this repo virtually by using GitHub Codespaces, which will open a web-based VS Code in your browser.
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[](https://github.com/codespaces/new?skip_quickstart=true&machine=basicLinux32gb&repo=899687170&ref=main&geo=UsEast&devcontainer_path=.devcontainer%2Fdevcontainer.json)
2. Make a new directory called `azure-ai-content-understanding-python` and clone this template into it using the `azd` CLI:
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```shell
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azd init -t azure-ai-content-understanding-python
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```
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You can also use git to clone the repository if you prefer.
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## Configure Azure AI service resource
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### (Option 1) Use `azd` commands to auto create temporal resources to run sample
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1. Login Azure
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```shell
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1. Copy `notebooks/.env.sample` to `notebooks/.env`
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1. Fill **AZURE_AI_ENDPOINT** with the endpoint from your Azure portal Azure AI Services instance.
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### Open a Jupyter notebook and follow the step-by-step guidance
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## Open a Jupyter notebook and follow the step-by-step guidance
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Navigate to the `notebooks` directory and selectthe sample notebook you are interested in. Since Codespaces is pre-configured with the necessary environment, you can directly execute each step in the notebook.
Copy file name to clipboardExpand all lines: notebooks/field_extraction.ipynb
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"metadata": {},
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"source": [
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"## Prerequisites\n",
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"1. Follow the steps in the [README](../README.md#Configure-Azure-AI-Service-resource) to create a `.env` file and configure your Azure AI Service.\n",
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"1. Ensure Azure AI service is configured following [steps](../README.md#configure-azure-ai-service-resource)\n",
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"2. Install the required packages to run the sample."
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