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Add extraction samples (#2)
* extraction * env * env * env * env * clean
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‎.devcontainer/devcontainer.json

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{
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"name": "Azure Content Understanding Demo",
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"image": "mcr.microsoft.com/devcontainers/python:3.11",
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"customizations": {
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"vscode": {
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"extensions": [
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"ms-azuretools.azure-dev",
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"ms-azuretools.vscode-bicep",
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"ms-python.python",
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"ms-toolsai.jupyter",
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"esbenp.prettier-vscode"
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]
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}
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}
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}

‎.gitattributes

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* text=auto
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*.sh text eol=lf
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run text eol=lf
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# lfs tracked extensions
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*.dll filter=lfs diff=lfs merge=lfs -text
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*.lzma filter=lfs diff=lfs merge=lfs -text
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*.ogv filter=lfs diff=lfs merge=lfs -text
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‎CHANGELOG.md

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‎CODE_OF_CONDUCT.md

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‎LICENSE.md

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‎README.md

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- The contents of this repository default to the latest preview version: **(2024-12-01-preview)**.
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[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://github.com/codespaces/new?skip_quickstart=true&machine=basicLinux32gb&repo=879881662&ref=main&geo=UsEast)
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## Features
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Azure AI Content Understanding is a new Generative AI based [Azure AI service](https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/overview), designed to process/ingest content of any types (document, image, audio, and video) into an user-defined output format. Content Understanding offers a streamlined process to reason over large amounts of unstructured data, accelerating time-to-value by generating an output that can be integrated into automation and analytical workflows.
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## Sample List
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| File | Description |
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| --- | --- |
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| [field_extraction.ipynb](notebooks/field_extraction.ipynb) | Extract customized fields defined in analyzer templates |
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| [content_extraction.ipynb](notebooks/content_extraction.ipynb) | Extract structrued content understanding result from your input files |
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| [analyzer_training.ipynb](notebooks/analyzer_training.ipynb) | Provide training data to improve quality of your analyzer |
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## Prerequisites
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1. To get started, you need an active [Azure account](https://azure.microsoft.com/free/cognitive-services/). If you don't have one, you can [create a free subscription](https://azure.microsoft.com/free/).
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1. Once you have Azure subscription, create an [Content Understanding Service and Get endpoint and keys](Create_Content_Understanding_Service.md).
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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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[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://github.com/codespaces/new?skip_quickstart=true&machine=basicLinux32gb&repo=899687170&ref=main&geo=UsEast&devcontainer_path=.devcontainer%2Fdevcontainer.json)
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### Note
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>Trademarks This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow [Microsoft’s Trademark & Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general). Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party’s policies.

‎analyzer_templates/sample_call_transcript_analyzer.json

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{
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"analyzerId": "sample_chart_analyzer",
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"description": "Sample call transcript analyzer",
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"scenario": "callCenter",
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"config": {
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"returnDetails": true,
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"locales": ["en-US"]
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},
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"fieldSchema": {
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"fields": {
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"Summary": {
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"type": "string",
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"method": "generate"
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},
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"Sentiment": {
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"type": "string",
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"method": "classify",
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"enum": [ "Positive", "Neutral", "Negative" ]
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},
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"People": {
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"type": "array",
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"description": "List of people mentioned",
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"items": {
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"type": "object",
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"properties": {
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"Name": { "type": "string" },
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"Role": { "type": "string" }
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}
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}
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}
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}
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}
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}

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