Clean up OTel instrumentation

Author: reakaleek

src/api/Elastic.Documentation.Api.Core/AskAi/AskAiUsecase.cs

@@ -16,41 +16,26 @@ public class AskAiUsecase(
 
 	public async Task<Stream> AskAi(AskAiRequest askAiRequest, Cancel ctx)
 	{
-		// Start activity for the chat request - DO NOT use 'using' because the stream is consumed later
-		// The activity will be passed to the transformer which will dispose it when the stream completes
-		var activity = AskAiActivitySource.StartActivity("chat", ActivityKind.Client);
-
-		// Generate a correlation ID for tracking if this is a new conversation
-		// For first messages (no ThreadId), generate a temporary ID that will be updated when the provider responds
-		var correlationId = askAiRequest.ThreadId ?? $"temp-{Guid.NewGuid()}";
-
-		// Set GenAI semantic convention attributes
-		_ = (activity?.SetTag("gen_ai.operation.name", "chat"));
-		_ = (activity?.SetTag("gen_ai.conversation.id", correlationId)); // Will be updated when we receive ConversationStart with actual ID
-		_ = (activity?.SetTag("gen_ai.usage.input_tokens", askAiRequest.Message.Length)); // Approximate token count
-
-		// Custom attributes for tracking our abstraction layer
-		// We use custom attributes because we don't know the actual GenAI provider (OpenAI, Anthropic, etc.)
-		// or model (gpt-4, claude, etc.) - those are abstracted by AgentBuilder/LlmGateway
-		_ = (activity?.SetTag("docs.ai.gateway", streamTransformer.AgentProvider)); // agent-builder or llm-gateway
-		_ = (activity?.SetTag("docs.ai.agent_name", streamTransformer.AgentId)); // docs-agent or docs_assistant
-
-		// Add GenAI prompt event
-		_ = (activity?.AddEvent(new ActivityEvent("gen_ai.content.prompt",
-			timestamp: DateTimeOffset.UtcNow,
-			tags:
-			[
-				new KeyValuePair<string, object?>("gen_ai.prompt", askAiRequest.Message),
-				new KeyValuePair<string, object?>("gen_ai.system_instructions", AskAiRequest.SystemPrompt)
-			])));
-
-		logger.LogDebug("Processing AskAiRequest: {Request}", askAiRequest);
-
+		var activity = AskAiActivitySource.StartActivity($"chat", ActivityKind.Client);
+		_ = activity?.SetTag("gen_ai.operation.name", "chat");
+		_ = activity?.SetTag("gen_ai.provider.name", streamTransformer.AgentProvider); // agent-builder or llm-gateway
+		_ = activity?.SetTag("gen_ai.agent.id", streamTransformer.AgentId); // docs-agent or docs_assistant
+		var inputMessages = new object[]
+		{
+			new
+			{
+				role = "user",
+				parts = new object[]
+				{
+					new { type = "text", content = askAiRequest.Message }
+				}
+			}
+		};
+		var inputMessagesJson = System.Text.Json.JsonSerializer.Serialize(inputMessages);
+		_ = activity?.SetTag("gen_ai.input.messages", inputMessagesJson);
 		var rawStream = await askAiGateway.AskAi(askAiRequest, ctx);
-
 		// The stream transformer will handle disposing the activity when streaming completes
 		var transformedStream = await streamTransformer.TransformAsync(rawStream, activity, ctx);
-
 		return transformedStream;
 	}
 }

src/api/Elastic.Documentation.Api.Infrastructure/Adapters/AskAi/LlmGatewayStreamTransformer.cs

@@ -56,6 +56,8 @@ public class LlmGatewayStreamTransformer(ILogger<LlmGatewayStreamTransformer> lo
 			"agent_end" =>
 				new AskAiEvent.ConversationEnd(id, timestamp),
 
+			"error" => ParseErrorEvent(id, timestamp, messageData),
+
 			"chat_model_start" or "chat_model_end" =>
 				null, // Skip model lifecycle events
 
@@ -110,4 +112,18 @@ public class LlmGatewayStreamTransformer(ILogger<LlmGatewayStreamTransformer> lo
 		Logger.LogWarning("Unknown LLM Gateway event type: {Type}", type);
 		return null;
 	}
+
+	private AskAiEvent.ErrorEvent ParseErrorEvent(string id, long timestamp, JsonElement messageData)
+	{
+		// LLM Gateway error format: {error: "...", message: "..."}
+		var errorMessage = messageData.TryGetProperty("message", out var msgProp)
+			? msgProp.GetString()
+			: messageData.TryGetProperty("error", out var errProp)
+				? errProp.GetString()
+				: null;
+
+		Logger.LogError("Error event received from LLM Gateway: {ErrorMessage}", errorMessage ?? "Unknown error");
+
+		return new AskAiEvent.ErrorEvent(id, timestamp, errorMessage ?? "Unknown error occurred");
+	}
 }