Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Cookiecutter Spacy Fastapi | 370 | 6 months ago | 4 | mit | Python | |||||
Cookiecutter API for creating Custom Skills for Azure Search using Python and Docker | ||||||||||
Azuresearch_jfk_files | 329 | 10 months ago | 10 | mit | TypeScript | |||||
This repo contains the sample code of the Azure Search and Cognitive Services used to provide insights and analysis around the JFK Files. | ||||||||||
Azure Search Knowledge Mining | 265 | 3 months ago | 5 | mit | CSS | |||||
Azure Search Knowledge Mining Accelerator | ||||||||||
Azure Search Power Skills | 136 | 8 days ago | 12 | mit | C# | |||||
A collection of useful functions to be deployed as custom skills for Azure Cognitive Search | ||||||||||
Cognitive Services Python Sdk Samples | 106 | 2 years ago | 5 | mit | Python | |||||
Learn how to use the Cognitive Services Python SDK with these samples | ||||||||||
Azure Search Dotnet Samples | 101 | 13 days ago | 2 | mit | C# | |||||
Azure Search .NET sample code | ||||||||||
Search Dotnet Getting Started | 99 | 8 months ago | mit | C# | ||||||
Getting Started with Azure Search using .NET | ||||||||||
Ecommerce Chatbot | 84 | 5 years ago | mit | JavaScript | ||||||
An example of a chatbot built with Microsoft Bot Framework and featuring e-commerce capabilities via Moltin, Azure Search, Recommendations API, and LUIS | ||||||||||
Search Dotnet Asp Net Mvc Jobs | 72 | 2 years ago | 1 | mit | JavaScript | |||||
Azure Search Jobs Website Sample using ASP.NET MVC | ||||||||||
Log4j S3 Search | 57 | 4 months ago | 3 | mit | Java | |||||
Log4j appender with S3, Azure, Google Cloud, and search publishing |
Note: the bot is still using the original State API that was deprecated. It works, but the recommendation from Microsoft is to implement a custom state data.
An example of a chatbot built with Microsoft Bot Framework and featuring e-commerce capabilities via:
I presented this bot on API Strat in Boston as an example of a smart app built with cognitive APIs. This bot is also going to SATURN and SYNTAX.
If you would like to run it, you would need:
categories
, products
, and variants
. You can find the index definitions and the script that can set up everything you need here
Deploy your bot (I used Azure App Service) and register it with the dev.botframework.com.
Set the following environment variables:
MICROSOFT_APP_ID
- you will get it from the dev.botframework.com during registrationMICROSFT_APP_PASSWORD
- you will get it from the dev.botframework.com during registrationRECOMMENDATION_API_KEY
- your API key to the Recommendations API service from the Microsoft Cognitive ServicesRECOMMENDATION_MODEL
- you can create multiple recommendation models and this way you can choose which one the bot will use for suggestionsRECOMMENDATION_BUILD
- a given model (your product catalog, historical transactions, and business rules) can have multiple recommendation builds and this is how you tell which one the bot will useSEARCH_APP_NAME
- the name of your Azure Search service. The code assumes that you have all three indexes in the same Azure Search resourceSEARCH_API_KEY
- your API key to the Azure Search serviceLUIS_ENDPOINT
- the URL of your published LUIS model. Please keep the Add verbose flag
on and remove &q=
from the URL. THe bot framework will add it.SENTIMENT_API_KEY
- your API key to the Text Analytics service.SENTIMENT_ENDPOINT
- the enpoint of yout Text Analytics service. Defaults to https://westus.api.cognitive.microsoft.com/text/analytics/v2.0/sentiment
If you would like to connect the Bing Spell Check service, you would do so in LUIS when publishing your endpoint. This integration is transparent to the app and all you do is provision your Azure subscription key to the service and connect it to your LUIS app.
session.privateConversationData.cart
) and does not sync back to MoltinMIT