21 KiB
This tutorial assumes you already have an instance of Azure Search running. See the documentation here to get started with Azure Search https://docs.microsoft.com/en-us/azure/search/
If you're unfamiliar with Azure Search Cognitive Skills you can read more about them here: https://docs.microsoft.com/en-us/azure/search/cognitive-search-concept-intro
Prerequisites
Before running this sample, you must have the following:
-
Install the Azure CLI. This article requires the Azure CLI version 2.0 or later. Run
az --versionto find the version you have.
You can also use the Azure Cloud Shell. -
If you want to run the function locally install Azure Function Core Tools version 2.x
Running the Function App locally
If you just want to skip this and just deploy the prebuilt container to an Azure Function skip to Deploy Docker Container to Azure Functions using Azure CLI
Clone this repo
git clone https://github.com/Microsoft/SkillsExtractorCognitiveSearch
Start the Function
func host start
When the Functions host starts, it write something like the following output, which has been truncated for readability
%%%%%%
%%%%%%
@ %%%%%% @
@@ %%%%%% @@
@@@ %%%%%%%%%%% @@@
@@ %%%%%%%%%% @@
@@ %%%% @@
@@ %%% @@
@@ %% @@
%%
%
...
Content root path: C:\functions\MyFunctionProj
Now listening on: http://0.0.0.0:7071
Application started. Press Ctrl+C to shut down.
Http Functions:
extract_skills: [POST] http://localhost:7071/api/extract_skills
get_skill: [GET] http://localhost:7071/api/skills/{skill_id}
[8/27/2018 10:38:27 PM] Host started (29486ms)
[8/27/2018 10:38:27 PM] Job host started
Test the Function locally
Lets make sure we can process Azure Search Records as expected. Run the following POST request to test your function locally.
POST http://localhost:7071/api/extract_skills?skill_property=name
Content-Type: application/json
{
"values": [
{
"recordId": "a3",
"data": {
"text": "Azure Machine Learning team is a fast-paced product group within the Microsoft Artificial Intelligence & Research organization. We are building the Machine Learning development platform that will make it easy for all data scientists and AI Developers to create and deploy robust, scalable and highly available machine learning solutions on the cloud, using the best of the open source ecosystem and innovation from inside the company and the latest breakthroughs in research We are looking for a Principal Program Manager who is passionate about delivering a highly available and reliable cloud platform that will transform the data science and machine learning experience. Come to build out and lead the Artificial Intelligence/Machine/Deep Learning investments, define innovative experiences for data science, and extend the state of the art in deep learning performance and efficiency in the industry. We are looking for a creative and technically minded product visionary with expertise in building and shipping large scale user experiences. A strong performer that can lead our UX efforts and drive cross-team initiatives to address major customer needs. Responsibilities In this role you will be responsible for leading the development of our Azure Machine Learning Web UX and drive our journey to modernize the appearance combining the different AML properties into one portal UX. You’ll help define the roadmap and the vision for our next generation of data science web experiences. You will be working closely with design and research counterparts to invent great data science experiences and lead the development team to deliver these modern experiences to our highly engaged customers. You will work with teams across the org to make this experience simple, reliable, fast and coherent with the other Microsoft AI products. Qualifications Have experience in building and leading teams and driving large cross team efforts.Have a track record in building and shipping products with an emphasis on UX.Are equally comfortable articulating the big picture and refining the small details.Are customer and data obsessed, always learning and refining your features to deliver maximum business impact. Have a BS Degree in Engineering, Computer Science, or similar degree. 7+ years of Product or Program Management experience. #AIPLATFORM##AIPLATREF#",
"language": "en"
}
}
]
}
You should see a response that looks like this:
{
"values": [
{
"recordId": "a3",
"data": {
"skills": [
"Artificial intelligence",
"Azure Machine Learning",
"Business",
"Computer science",
"Data science",
"Deep learning",
"Design",
"Engineering",
"Machine learning"
]
},
"errors": null,
"warnings": null
}
]
}
It looks like we missed one potential skill: UX Let's add UX as a skill we want to extract.
Add a new Skill
The main data/skill_patterns.jsonl file is built programatically from data/skills.json
so we won't edit it directly. Instead we're going to add any new patterns to data/extra_skill_patterns.jsonl
Open the data/extra_skill_patterns.jsonl file and the following lines.
{"label":"SKILL|ux","pattern":[{"LOWER":"ux"}]}
{"label":"SKILL|ux","pattern":[{"LOWER":"user"}, {"LOWER":"experience"}]}
This pattern syntax is specific to SpaCy's rule based matching. If you want learn more about the pattern syntax the SpaCy Docs have a great User Guide here:
https://spacy.io/usage/rule-based-matching#entityruler
JSONL (files like *.jsonl) is an extension of JSON where each new line is a separate JSON object
Restart the Function and test your new patterns
End the running host process and start the Functions host again with
func host start
Run the same POST request as before to http://localhost:7071/api/extract_skills?skill_property=name
Your response should now have UX included in the list of skills like below:
{
"values": [
{
"recordId": "a3",
"data": {
"skills": [
"Artificial intelligence",
"Azure Machine Learning",
"Business",
"Computer science",
"Data science",
"Deep learning",
"Design",
"Engineering",
"Machine learning",
"UX"
]
},
"errors": null,
"warnings": null
}
]
}
Build a Docker Image from the Dockerfile
In the root folder run the docker build command providing your Docker Hub user id, image name and tag name
For instance
docker build . -t <docker_id>/skills-extractor-cognitive-search:v1.0.0
Push the built image to Docker Hub
You need to be logged in to push this image to Docker Hub
Docker Login
docker login -u <docker_id> -p <dockerhub_password>
Push your image to Docker Hub
For instance
docker push <docker_id>/skills-extractor-cognitive-search:v1.0.0
Next we'll deploy this container to Azure Functions using the Azure CLI
Deploy Docker Container to Azure Functions using Azure CLI
The first step is deploy your own instance of the Skills Extractor Azure Function.
You can build and host the container yourself from this repo or use the prebuilt container on Docker Hub: mcr.microsoft.com/wwllab/skills/skills-extractor-cognitive-search
For a more complete walktrhough of deploying Azure Functions, Follow instructions here: https://docs.microsoft.com/en-us/azure/azure-functions/functions-create-function-linux-custom-image#create-a-resource-group
Login with Azure CLI
az login
Set an active subscription
az account set --subscription mySubscriptionIdOrName
Create a resource group
az group create --name myResourceGroup --location westus
Create an Azure Storage account
az storage account create --name <storage_name> --location westus --resource-group myResourceGroup --sku Standard_LRS
Create an App Service Plan for Linux
az appservice plan create --name myAppServicePlan --resource-group myResourceGroup --sku B1 --is-linux
Create and deploy the custom image
The function app hosts the execution of your functions. Create a function app from a Docker Hub image by using the az functionapp create command.
az functionapp create --name <app_name> --storage-account <storage_name> --resource-group myResourceGroup \
--plan myAppServicePlan --deployment-container-image-name mcr.microsoft.com/wwllab/skills/skills-extractor-cognitive-search
Configure the function app
The function needs the connection string to connect to the default storage account. The following command will add the necessary AzureWebJobsStorage setting to your function application settings
storageConnectionString=$(az storage account show-connection-string --resource-group myResourceGroup --name <storage_name> --query connectionString --output tsv)
az functionapp config appsettings set --name <app_name> \
--resource-group myResourceGroup \
--settings AzureWebJobsDashboard=$storageConnectionString \
AzureWebJobsStorage=$storageConnectionString
It can take up to 20 minutes (usually around 5) for your function app to deploy this Docker Image.
Test your Azure Function.
Get the Function Url from the Azure Portal
Open the Azure Portal and navigate to the function app you created to in the previous step.
Click Get Function URL
And copy the Function URL
Run the following HTTP Request
POST {YOUR_FUNCTION_URL_WITH_CODE}
Content-Type: application/json
{
"values": [
{
"recordId": "a3",
"data": {
"text": "Azure Machine Learning team is a fast-paced product group within the Microsoft Artificial Intelligence & Research organization. We are building the Machine Learning development platform that will make it easy for all data scientists and AI Developers to create and deploy robust, scalable and highly available machine learning solutions on the cloud, using the best of the open source ecosystem and innovation from inside the company and the latest breakthroughs in research We are looking for a Principal Program Manager who is passionate about delivering a highly available and reliable cloud platform that will transform the data science and machine learning experience. Come to build out and lead the Artificial Intelligence/Machine/Deep Learning investments, define innovative experiences for data science, and extend the state of the art in deep learning performance and efficiency in the industry. We are looking for a creative and technically minded product visionary with expertise in building and shipping large scale user experiences. A strong performer that can lead our UX efforts and drive cross-team initiatives to address major customer needs. Responsibilities In this role you will be responsible for leading the development of our Azure Machine Learning Web UX and drive our journey to modernize the appearance combining the different AML properties into one portal UX. You’ll help define the roadmap and the vision for our next generation of data science web experiences. You will be working closely with design and research counterparts to invent great data science experiences and lead the development team to deliver these modern experiences to our highly engaged customers. You will work with teams across the org to make this experience simple, reliable, fast and coherent with the other Microsoft AI products. Qualifications Have experience in building and leading teams and driving large cross team efforts.Have a track record in building and shipping products with an emphasis on UX.Are equally comfortable articulating the big picture and refining the small details.Are customer and data obsessed, always learning and refining your features to deliver maximum business impact. Have a BS Degree in Engineering, Computer Science, or similar degree. 7+ years of Product or Program Management experience. #AIPLATFORM##AIPLATREF#",
"language": "en"
}
}
]
}
You should see a response that looks like this:
{
"values": [
{
"recordId": "a3",
"data": {
"skills": [
"Artificial intelligence",
"Azure Machine Learning",
"Business",
"Computer science",
"Data science",
"Deep learning",
"Design",
"Engineering",
"Machine learning"
]
},
"errors": null,
"warnings": null
}
]
}
Now let's setup an indexer to add these extracted skills to your search index
Create a new Cognitive Skill in Azure Search
For the full documentation on integrating custom cognitive skills see: https://docs.microsoft.com/en-us/azure/search/cognitive-search-custom-skill-interface
Add a skills field to your search index
Open your search index in the Azure Portal and add a new field with the name skills.
You can also update your search index using the Azure Search REST API docs here:
https://docs.microsoft.com/en-us/azure/search/search-what-is-an-index
Get the Function Url from the Azure Portal
Open the Azure Portal and navigate to the function app you created to in the previous step.
Click Get Function URL
And copy the Function URL
Create a new skillset in Azure Search that points to your function url
Change content "source": "document/content" to the attribute that has the most text in for each document in your search index.
For Example: "source": "document/description" if you have a description attribute for each document in your search index.
PUT https://[servicename].search.windows.net/skillsets/extractskills?api-version=2017-11-11-Preview
api-key: [admin key]
Content-Type: application/json
{
"skills": [
...,
{
"@odata.type": "#Microsoft.Skills.Custom.WebApiSkill",
"description": "Extract skills from each document",
"uri": "[Your function url here]",
"batchSize": 100,
"context": "/document",
"inputs": [
{
"name": "text",
"source": "/document/content"
}
],
"outputs": [
{
"name": "skills",
"targetName": "skills"
}
]
}
]
}
Create a new indexer to map the skills output field to a search index
PUT https://[servicename].search.windows.net/indexers/[indexer name]?api-version=2017-11-11-Preview
api-key: [admin key]
Content-Type: application/json
{
"name": "myIndexer",
"dataSourceName": "myDataSource",
"targetIndexName": "myIndex",
"skillsetName": "extractskills",
"outputFieldMappings": [
{
"sourceFieldName": "/document/skills",
"targetFieldName": "skills"
}
]
}
Check your search index and you should see a new skills array
PUT https://[servicename].search.windows.net/indexes/[indexer name]/docs?api-version=2017-11-11-Preview&search=machine learning
api-key: [admin key]
Content-Type: application/json
Real World Example Response for skills extracted from a job description from the Microsoft Careers Page
{
"@odata.context": "https://microsoft-careers.search.windows.net/indexes('[indexer name]')/$metadata#docs(*)",
"value": [
{
"@search.score": 1.5600916,
"job_id": 588309,
"title": "Applied Machine Learning Developer",
"description": "The Xbox Advanced Technology Group (ATG) provides deep technical consultation and integration services to game developers world-wide as they create cutting-edge experiences for Microsoft game platforms and services. Our team also does advanced research and incubation and we are seeking an Applied Machine Learning Developer to help us bring Machine Learning techniques to gaming. If you have a strong ML/graphics background and can roll up your sleeves to do the engineering work required to ship high quality ML models in production, this is a unique opportunity to tackle challenging problems in the gaming and graphics space! Responsibilities Develop high-performance machine learning systems for gaming ML scenarios and graphics techniques.Develop optimized GPU kernels for deep learning inference via DirectX and DirectML and other graphics technologies.Do analysis on performance on internal and 3PP machine learning models and propose improvements and optimizations.Develop infrastructure as required to enable high performance ML in gaming.Act as an expert in applied machine learning to serve the needs of Game Developers Qualifications Required Qualifications: Masters or PhD or equivalent experience in relevant discipline (Machine Learning, Computer Science, Engineering)3+ years of relevant work experienceExperience in GPU programming (DirectX, Vulkan, OpenCL, etc) and performance modelling, profiling and optimization. Preferred Qualifications:Game Development experience - one or more shipped titles.Experience with Azure cloud services.Experience with Mobile/Tablet machine learning developmentMicrosoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form. Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work. XGAXGCATG#gamingjobs",
"category": "Engineering",
"subCategory": "Software Engineering",
"country": "United States",
"state": "Washington",
"id": "513c8222-8004-d30b-8993-4c759fb05c9b",
"skills": [
"machine-learning",
"engineering",
"deep-learning",
"inference",
"computer-science",
"game-development",
"azure",
"mobile"
]
}
...
]
}
Troubleshooting
-
If you get timeout errors while running the indexer in Azure Search, change
batchSizein the skillset definition to a lower number (e.g. 50)
For Example:
PUT https://[servicename].search.windows.net/skillsets/extractSkills?api-version=2017-11-11-Preview
api-key: [admin key]
Content-Type: application/json
{
"skills": [
...,
{
"@odata.type": "#Microsoft.Skills.Custom.WebApiSkill",
"description": "Extract skills from each document",
"uri": "[Your function url here]",
"batchSize": 50,
"context": "/document",
"inputs": [
{
"name": "text",
"source": "/document/content"
}
],
"outputs": [
{
"name": "skills",
"targetName": "skills"
}
]
}
]
}