LEARN . MICROSOFT . COM {}

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Monthly Traffic Estimate
How Does Learn.microsoft.com Make Money
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We are analyzing https://learn.microsoft.com/en-us/dotnet/ai/tutorials/tutorial-ai-vector-search.

Title:
Tutorial - Integrate OpenAI with the RAG pattern and vector search using Azure Cosmos DB for MongoDB - .NET | Microsoft Learn
Description:
Create a simple recipe app using the RAG pattern and vector search using Azure Cosmos DB for MongoDB.
Website Age:
34 years and 2 months (reg. 1991-05-02).

Matching Content Categories {📚}

Mobile Technology & AI
Telecommunications
Graphic Design

Content Management System {📝}

What CMS is learn.microsoft.com built with?

Custom-built

No common CMS systems were detected on Learn.microsoft.com, and no known web development framework was identified.

Traffic Estimate {📈}

What is the average monthly size of learn.microsoft.com audience?

🌠 Phenomenal Traffic: 5M - 10M visitors per month

Based on our best estimate, this website will receive around 5,000,019 visitors per month in the current month.
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How Does Learn.microsoft.com Make Money? {💸}

We see no obvious way the site makes money.

Earning money isn't the goal of every website; some are designed to offer support or promote social causes. People have different reasons for creating websites. This might be one such reason. Learn.microsoft.com might have a hidden revenue stream, but it's not something we can detect.

Keywords {🔍}

vector, azure, search, cosmos, app, recipe, recipes, embedding, mongodb, user, response, open, data, embeddings, net, model, file, public, var, options, openai, sample, find, return, throw, string, catch, exmessage, rag, searches, service, perform, select, json, method, documents, async, bsondocument, document, await, exception, chatmessage, content, application, explore, vcore, chat, completions, guide, prompt,

Topics {✒️}

open ai service open ai models ai driven searches generative ai models tutorial explores integration meaningful answers based local json files cs file performs azure cosmos db public void createvectorindexifnotexists cs class parses contextually similar embeddings provide helpful answers upload sample data uploaded sample data recommend users search mongodb vcore service search results data json items uploaded cs file creates vector search capabilities cosmos db account custom data stored sections ahead guide vector index exists answer questions related open source project azure openai ada-deployment cs file uploads command line console embedding model await _recipecollection find related recipes select upload recipe mongodb vcore collection getchatcompletionasync method generates ai assistant step cooking instructions cooking instructions provided git clone https provide feedback sample application vector searches choices[0] azure account azure cosmosdb cosmos db perform vector _systempromptrecipeassistant + documents

Questions {❓}

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Schema {🗺️}

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      context:https://schema.org
      itemListElement:
            name:Learn
            position:1
            type:ListItem
            item:https://learn.microsoft.com/en-us/
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      item:https://learn.microsoft.com/en-us/