Fix 127, 128, 177 (#190)

## Purpose
<!-- Describe the intention of the changes being proposed. What problem
does it solve or functionality does it add? -->
* ...

Fix
#127 
#128 
#177 

## Application Insights
<img width="1488" alt="image"
src="https://github.com/Azure-Samples/azure-search-openai-demo-csharp/assets/16876986/923a2b35-7a67-4f78-b59d-ed65ca8c8599">


## Does this introduce a breaking change?
<!-- Mark one with an "x". -->
```
[ ] Yes
[ ] No
```

## Pull Request Type
What kind of change does this Pull Request introduce?

<!-- Please check the one that applies to this PR using "x". -->
```
[ ] Bugfix
[ ] Feature
[ ] Code style update (formatting, local variables)
[ ] Refactoring (no functional changes, no api changes)
[ ] Documentation content changes
[ ] Other... Please describe:
```

## How to Test
*  Get the code

```
git clone [repo-address]
cd [repo-name]
git checkout [branch-name]
npm install
```

* Test the code
<!-- Add steps to run the tests suite and/or manually test -->
```
```

## What to Check
Verify that the following are valid
* ...

## Other Information
<!-- Add any other helpful information that may be needed here. -->

---------

Co-authored-by: Luis Quintanilla <[email protected]>

Author: LittleLittleCloud

README.md

@@ -200,4 +200,4 @@ Once in the web app:
 
 **_Question_**: Why do we need to break up the PDFs into chunks when Azure Cognitive Search supports searching large documents?
 
-**_Answer_**: Chunking allows us to limit the amount of information we send to OpenAI due to token limits. By breaking up the content, it allows us to easily find potential chunks of text that we can inject into OpenAI. The method of chunking we use leverages a sliding window of text such that sentences that end one chunk will start the next. This allows us to reduce the chance of losing the context of the text.
+**_Answer_**: Chunking allows us to limit the amount of information we send to OpenAI due to token limits. By breaking up the content, it allows us to easily find potential chunks of text that we can inject into OpenAI. The method of chunking we use leverages a sliding window of text such that sentences that end one chunk will start the next. This allows us to reduce the chance of losing the context of the text.

app/backend/MinimalApi.csproj

@@ -17,6 +17,7 @@
     <PackageReference Include="Azure.Storage.Blobs" Version="$(AzureStorageBlobsVersion)" />
     <PackageReference Include="Azure.AI.OpenAI" Version="$(AzureOpenAIVersion)" />
     <PackageReference Include="Azure.Extensions.AspNetCore.Configuration.Secrets" Version="1.2.2" />
+    <PackageReference Include="Microsoft.ApplicationInsights.AspNetCore" Version="2.22.0-beta3" />
     <PackageReference Include="Microsoft.Extensions.Caching.StackExchangeRedis" Version="7.0.10" />
     <PackageReference Include="Microsoft.VisualStudio.Azure.Containers.Tools.Targets" Version="1.19.5" />
     <PackageReference Include="PdfSharpCore" Version="1.3.60" />

app/backend/Program.cs

@@ -19,14 +19,15 @@
 }
 else
 {
+    static string? GetEnvVar(string key) => Environment.GetEnvironmentVariable(key);
+
     builder.Services.AddStackExchangeRedisCache(options =>
     {
         var name = builder.Configuration["AzureRedisCacheName"] +
             ".redis.cache.windows.net";
         var key = builder.Configuration["AzureRedisCachePrimaryKey"];
         var ssl = "true";
 
-        static string? GetEnvVar(string key) => Environment.GetEnvironmentVariable(key);
 
         if (GetEnvVar("REDIS_HOST") is string redisHost)
         {
@@ -46,7 +47,18 @@
             {name},abortConnect=false,ssl={ssl},allowAdmin=true,password={key}
             """;
         options.InstanceName = "content";
+
+        
     });
+
+    // set application telemetry
+    if (GetEnvVar("APPLICATIONINSIGHTS_CONNECTION_STRING") is string appInsightsConnectionString)
+    {
+        builder.Services.AddApplicationInsightsTelemetry((option) =>
+        {
+            option.ConnectionString = appInsightsConnectionString;
+        });
+    }
 }
 
 var app = builder.Build();

infra/main.bicep

@@ -10,6 +10,19 @@ param environmentName string
 param location string
 param tags string = ''
 
+@description('Location for the OpenAI resource group')
+@allowed(['canadaeast', 'eastus', 'eastus2', 'francecentral', 'switzerlandnorth', 'uksouth', 'japaneast', 'northcentralus'])
+@metadata({
+  azd: {
+    type: 'location'
+  }
+})
+param openAiResourceGroupLocation string
+
+@description('Name of the chat GPT model. Default: gpt-35-turbo')
+@allowed(['gpt-35-turbo', 'gpt-4', 'gpt-35-turbo-16k', 'gpt-4-16k'])
+param chatGptModelName string = 'gpt-35-turbo'
+
 @description('Name of the Azure Application Insights dashboard')
 param applicationInsightsDashboardName string = ''
 
@@ -22,9 +35,6 @@ param chatGptDeploymentCapacity int = 30
 @description('Name of the chat GPT deployment')
 param chatGptDeploymentName string = 'chat'
 
-@description('Name of the chat GPT model. Default: gpt-35-turbo')
-param chatGptModelName string = 'gpt-35-turbo'
-
 @description('Name of the embedding deployment. Default: embedding')
 param embeddingDeploymentName string = 'embedding'
 
@@ -67,9 +77,6 @@ param keyVaultResourceGroupName string = ''
 @description('Name of the Azure Log Analytics workspace')
 param logAnalyticsName string = ''
 
-@description('Location of the resource group for the OpenAI resources')
-param openAiResourceGroupLocation string = location
-
 @description('Name of the resource group for the OpenAI resources')
 param openAiResourceGroupName string = ''
 
@@ -493,6 +500,7 @@ output AZURE_KEY_VAULT_ENDPOINT string = keyVault.outputs.endpoint
 output AZURE_KEY_VAULT_NAME string = keyVault.outputs.name
 output AZURE_KEY_VAULT_RESOURCE_GROUP string = keyVaultResourceGroup.name
 output AZURE_LOCATION string = location
+output AZURE_OPENAI_RESOURCE_LOCATION string = openAiResourceGroupLocation
 output AZURE_OPENAI_CHATGPT_DEPLOYMENT string = chatGptDeploymentName
 output AZURE_OPENAI_EMBEDDING_DEPLOYMENT string = embeddingDeploymentName
 output AZURE_OPENAI_ENDPOINT string = openAi.outputs.endpoint

infra/main.parameters.json

@@ -29,6 +29,15 @@
     "openAiResourceGroupName": {
       "value": "${AZURE_OPENAI_RESOURCE_GROUP}"
     },
+    "openAiResourceGroupLocation":{
+      "value": "${AZURE_OPENAI_RESOURCE_LOCATION=${AZURE_LOCATION}}"
+    },    
+    "chatGptDeploymentName":{
+      "value": "${AZURE_OPENAI_CHATGPT_DEPLOYMENT=chat}"
+    },
+    "embeddingDeploymentName":{
+      "value": "${AZURE_OPENAI_EMBEDDING_DEPLOYMENT=embedding}"
+    },
     "openAiServiceName": {
       "value": "${AZURE_OPENAI_SERVICE}"
     },