====== AI Chatbot with Sentiment and In Kind Responses ====== ===== Requirements ===== **✅ 1. Azure Resources Checklist** | **Resource Type** | **Name (per your setup)** | **Notes** | | **Function App** | dehamerfuncapp | Your C# Azure Function app | | **Storage Account** | Linked to Function App | Required for deployment—should auto-create if --functions-version specified | | **Azure Cognitive Services (Text Analytics)** | dehamersentimentai | For sentiment classification | | **Azure OpenAI** | don-openai-useast | For GPT-4.1-based reply generation | ===== Prerequisites ===== Install These brew install dotnet-sdk #This will be version 9 which will not work but gives you the rest of the stuff needed. brew install azure-cli Assuming you already have created a Resource Group named don-test-rg, an OpenAI deployment named don-openai-useast, and deployed a gpt model named gpt-4.1 inside openai. Those all require the portal. Install this from the webpage and follow directions. [[https://dotnet.microsoft.com/en-us/download/dotnet/8.0|dotnet 8.x]] Create a folder in your workspace and save the files at the end of this document. Open a terminal, set your folder to the one where the files are saved, then run these commands: These commands are only needed for Windows users: dotnet nuget add source https://api.nuget.org/v3/index.json -n nuget.org npm install -g azure-functions-core-tools@4 --unsafe-perm true dotnet nuget locals all --clear dotnet restore The rest of the instructions are for every OS: dotnet add package Microsoft.Azure.Functions.Worker.Extensions.OpenApi --version 1.4.0 dotnet --list-sdks dotnet add package Azure.AI.TextAnalytics --version 5.3.0 dotnet add package Azure.AI.OpenAI --version 2.0.0 Create Storage Account az storage account create \ --name dehamerfuncstorage \ --location eastus \ --resource-group don-test-rg \ --sku Standard_LRS Create Function Plan for Windows az functionapp plan create \ --resource-group don-test-rg \ --name dehamerfuncplan \ --location eastus \ --sku B1 \ --is-linux false Create Function App az functionapp create \ --resource-group don-test-rg \ --name dehamerfuncapp \ --plan dehamerfuncplan \ --storage-account dehamerfunctstorage \ --runtime dotnet-isolated \ --functions-version 4 \ --os-type Windows Create TexAnalytics az cognitiveservices account create \ --name dehamersentimentai \ --resource-group don-test-rg \ --location eastus \ --kind TextAnalytics \ --sku S \ --custom-domain dehamersentimentai az cognitiveservices account update \ --name dehamersentimentai \ --resource-group don-test-rg \ --set properties.publicNetworkAccess=Enabled Get keys and endpoint for export and app settings export TEXT_ANALYTICS_ENDPOINT=`az cognitiveservices account show \ --name dehamersentimentai \ --resource-group don-test-rg \ --query "properties.endpoint"|sed -e s:\"::g` export TEXT_ANALYTICS_KEY=`az cognitiveservices account keys list \ --name dehamersentamentai \ --resource-group don-test-rg \ --query "key1" -o tsv` az functionapp config appsettings set \ --name dehamerfuncapp \ --resource-group don-test-rg \ --settings \ TEXT_ANALYTICS_ENDPOINT=$TEXT_ANALYTICS_ENDPOINT \ TEXT_ANALYTICS_KEY=$TEXT_ANALYTICS_KEY export OPENAI_KEY=`az cognitiveservices account keys list \ --name don-openai-useast \ --resource-group don-test-rg \ --query "key1" -o tsv` export OPENAI_ENDPOINT=https://don-openai-useast.openai.azure.com/ export OPENAI_DEPLOYMENT=gpt-4.1 az functionapp config appsettings set \ --name dehamerfuncapp \ --resource-group don-test-rg \ --settings \ OPENAI_KEY=$OPENAI_KEY \ OPENAI_ENDPOINT=$OPENAI_ENDPOINT OPENAI_DEPLOYMENT=$OPENAI_DEPLOYMENT #Confirm they were set az functionapp config appsettings list \ --name dehamerfuncapp \ --resource-group don-test-rg \ --query "[?starts_with(name, 'TEXT_') || starts_with(name, 'OPENAI_')]" -o table Create a directory to store the functionapp files mkdir ~/FeedbackFunctionDotNet cd ~/FeedbackFunctionDotNet Save the FeedbackFunction.cs, FeedbackFunction.csproj, global.json, host.json, local.settings.json, and program.cs into the FeedBackFunctionDotNet directory. using System.Net.Http.Headers; using System.Text; using System.Text.Json; using Azure; using Azure.AI.TextAnalytics; using Microsoft.Azure.Functions.Worker; using Microsoft.Azure.Functions.Worker.Http; using Microsoft.Extensions.Logging; public class DeHamerFeedbackFunction { private readonly ILogger _logger; public DeHamerFeedbackFunction(ILoggerFactory loggerFactory) { _logger = loggerFactory.CreateLogger(); } [Function("DeHamerFeedbackFunction")] public async Task Run( [HttpTrigger(AuthorizationLevel.Anonymous, "post", Route = null)] HttpRequestData req) { _logger.LogInformation("DeHamerFeedbackFunction triggered."); var requestBody = await new StreamReader(req.Body).ReadToEndAsync(); var data = JsonSerializer.Deserialize>(requestBody); string feedback = data?["feedback"] ?? string.Empty; // Get Text Analytics config var textEndpoint = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_ENDPOINT"); var textKey = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_KEY"); _logger.LogInformation("Using Text Analytics endpoint: {endpoint}", textEndpoint); var credentials = new AzureKeyCredential(textKey); var client = new TextAnalyticsClient(new Uri(textEndpoint), credentials); var documentSentiment = await client.AnalyzeSentimentAsync(feedback); var sentiment = documentSentiment.Value.Sentiment.ToString().ToLower(); _logger.LogInformation("Sentiment detected: {sentiment}", sentiment); // Compose prompt string prompt = sentiment switch { "positive" => $"Respond in a cheerful and thankful tone to the following positive customer feedback:\n\"{feedback}\"", "negative" => $"Respond in a harsh, sarcastic, and annoyed tone to the following negative customer feedback:\n\"{feedback}\"", _ => $"Respond neutrally and professionally to the following feedback:\n\"{feedback}\"" }; // OpenAI Setup var openaiEndpoint = Environment.GetEnvironmentVariable("OPENAI_ENDPOINT")?.TrimEnd('/'); var openaiKey = Environment.GetEnvironmentVariable("OPENAI_KEY"); var deployment = Environment.GetEnvironmentVariable("OPENAI_DEPLOYMENT"); _logger.LogInformation("Calling OpenAI at: {url}", $"{openaiEndpoint}/openai/deployments/{deployment}/chat/completions"); using var httpClient = new HttpClient(); httpClient.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", openaiKey); var payload = JsonSerializer.Serialize(new { messages = new[] { new { role = "system", content = "You are a customer support agent who mirrors the customer's sentiment tone." }, new { role = "user", content = prompt } } }); _logger.LogInformation("Payload sent to OpenAI: {payload}", payload); var response = await httpClient.PostAsync( $"{openaiEndpoint}/openai/deployments/{deployment}/chat/completions?api-version=2024-02-15-preview", new StringContent(payload, Encoding.UTF8, "application/json")); if (!response.IsSuccessStatusCode) { var errorDetails = await response.Content.ReadAsStringAsync(); _logger.LogError("OpenAI API call failed: {status} - {details}", response.StatusCode, errorDetails); var errorResponse = req.CreateResponse(System.Net.HttpStatusCode.InternalServerError); await errorResponse.WriteAsJsonAsync(new { error = "Failed to get OpenAI response", status = response.StatusCode, details = errorDetails }); return errorResponse; } var json = JsonDocument.Parse(await response.Content.ReadAsStringAsync()); _logger.LogInformation("Raw OpenAI response: {json}", json); var message = json.RootElement.GetProperty("choices")[0].GetProperty("message").GetProperty("content").GetString(); var result = new { sentiment = sentiment, message = message }; var responseData = req.CreateResponse(System.Net.HttpStatusCode.OK); await responseData.WriteAsJsonAsync(result); return responseData; } } net8.0 v4 Exe enable enable PreserveNewest PreserveNewest Never Make sure this matches the version of dotnet 8.x you install. { "sdk": { "version": "8.0.411" } } { "version": "2.0" } { "IsEncrypted": false, "Values": { "AzureWebJobsStorage": "UseDevelopmentStorage=true", "FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated" } } using Microsoft.Extensions.Hosting; using Microsoft.Extensions.DependencyInjection; var host = new HostBuilder() .ConfigureFunctionsWorkerDefaults() .Build(); host.Run(); From the FeedbackFunctionDonnet directory: dotnet clean dotnet publish -c Release -o publish cd publish zip -r ../publish.zip . cd .. az functionapp deployment source config-zip --resource-group don-test-rg --name dehamerfuncapp --src publish.zip After running you will see additional files in the FeedbackFunctionDotnet directory. This is normal. ls bin FeedbackFunction.csproj host.json obj publish FeedbackFunction.cs global.json local.settings.json Program.cs publish.zip To test if it is working export FUNCTION_KEY=`az functionapp function keys list \ --name dehamerfuncapp \ --resource-group don-test-rg \ --function-name dehamerfeedbackfunction --query "default" | sed -e s:\"::` curl -X POST https://dehamerfuncapp.azurewebsites.net/api/dehamerfeedbackfunction \ -H "x-functions-key: $FUNCTION_KEY" \ -H "Content-Type: application/json" \ -d '{"feedback": "This service was trash. I want my time back."}' You should see something like: {"sentiment":"negative","message":"Oh, absolutely\u2014because we totally specialize in time travel, right? Sorry our \u0022trash\u0022 service didn\u2019t meet your sky-high expectations. Your valuable time is obviously worth so much, so thanks for investing it with us just to let us know how you feel."}% Confirmation tests az functionapp function list --name dehamerfuncapp --resource-group don-test-rg --query "[].{name:name, status:invokeUrlTemplate}" -o table Name Status -------------------------------------- -------------------------------------------------------------------- dehamerfuncapp/DeHamerFeedbackFunction https://dehamerfuncapp.azurewebsites.net/api/dehamerfeedbackfunction az functionapp show --name dehamerfuncapp --resource-group don-test-rg --query "enabledHostNames" [ "dehamerfuncapp.azurewebsites.net", "dehamerfuncapp.scm.azurewebsites.net" ] az functionapp function list \ --name dehamerfuncapp \ --resource-group don-test-rg \ --query "[].invokeUrlTemplate" \ --output tsv https://dehamerfuncapp.azurewebsites.net/api/dehamerfeedbackfunction az functionapp function show \ --name dehamerfuncapp \ --resource-group don-test-rg \ --function-name dehamerfeedbackfunction \ --query "isDisabled" false If true az functionapp function update \ --name dehamerfuncapp \ --resource-group don-test-rg \ --function-name dehamerfeedbackfunction \ --set isDisabled=false Tailing logs if enabled. Notice it says webapp, not functionapp. This is because after deployment the functionapp is in a similar deployment mode to webapps and this command tails logs for both types. You would run this in one terminal logged in with az login and then run the curl from another terminal, also logged in unless you already have the key in your curl statement. az webapp log tail \ --name dehamerfuncapp \ --resource-group don-test-rg If you want it to autostart after issues. #Optional az webapp config set \ --name dehamerfuncapp \ --resource-group don-test-rg \ --always-on true Get a list of your functionapps az functionapp function list \ --name dehamerfuncapp \ --resource-group don-test-rg \ --output table Href InvokeUrlTemplate IsDisabled Language Location Name ResourceGroup ScriptHref TestData TestDataHref -------------------------------------------------------------------------------- -------------------------------------------------------------------- ------------ --------------- ---------- -------------------------------------- --------------- ------------------------------------------------------------------------------------ ---------- -------------------------------------------------------------------------------------------------------- https://dehamerfuncapp.azurewebsites.net/admin/functions/DeHamerFeedbackFunction https://dehamerfuncapp.azurewebsites.net/api/dehamerfeedbackfunction False dotnet-isolated East US dehamerfuncapp/DeHamerFeedbackFunction don-test-rg https://dehamerfuncapp.azurewebsites.net/admin/vfs/site/wwwroot/FeedbackFunction.dll https://dehamerfuncapp.azurewebsites.net/admin/vfs/data/Functions/sampledata/DeHamerFeedbackFunction.dat Only do this for testing. It's not secure in the real world unless you don't want to have domain restrictions on access to the functionapp. I had to do it so I could test from my home webserver. az functionapp cors add \ --name dehamerfuncapp \ --resource-group don-test-rg \ --allowed-origins "*" If you have a webserver that you trust, you can create this webpage and test it: Dennis Feedback Page
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Dennis Feedback Page



===== Dennis Additions ===== ==== Azure CLI vs Azure Portal Instructions ==== | Task | Azure CLI Command | Azure Portal Steps | | Create Resource Group | az group create --name don-test-rg --location eastus | Go to Azure Portal > Resource Groups > Create | | Create Storage Account | az storage account create --name dehamerfuncstorage --location eastus --resource-group don-test-rg --sku Standard_LRS | Go to Storage Accounts > Create | | Create Function App | az functionapp create --resource-group don-test-rg --consumption-plan-location eastus --runtime dotnet-isolated --functions-version 4 --name dehamerfuncapp --storage-account dehamerfuncstorage | Go to Function Apps > Create > Choose .NET Isolated | | Deploy Code via Zip | az functionapp deployment source config-zip --src publish.zip --name dehamerfuncapp --resource-group don-test-rg | Go to Function App > Deployment Center > Zip Deploy | | Create Cognitive Services Resource | az cognitiveservices account create --name dehamersentimentai --resource-group don-test-rg --kind TextAnalytics --sku S --location eastus --yes | Search 'Cognitive Services' > Create > Choose Text Analytics | | Set App Settings | az functionapp config appsettings set --name dehamerfuncapp --resource-group don-test-rg --settings KEY=value | Go to Configuration > Application Settings > Add New | ==== Successful Deployment Steps ==== After resolving early build issues and switching from Linux to a Windows-hosted function plan due to SDK compatibility, the deployment succeeded with the following workflow: - Rewrote the function class to eliminate naming conflicts\\ - Set AuthorizationLevel to Anonymous to permit open feedback submission\\ - Used curl to verify responses from the deployed function\\ - Created an HTML frontend to POST feedback to the function endpoint ==== Architectural Diagram ==== {{:wiki:ai:chatgpt_image_jun_24_2025_05_00_18_pm.png}}\\ \\ [[ai_knowledge|AI Knowledge]]