fix: improve performance in AI request logging (#14769)

Instead of appending AI requests line by line to the output channel, we
now append them in a single step. Since appending to a channel is a
relatively expensive operation, this change significantly improves
performance for large requests.

This is particularly noticeable when AI inline code completions are
enabled for large files, as many requests may be sent during typing.

Also requests text responses by the LLM instead of streamed responses
in the autocomplete case.

packages/ai-code-completion/src/browser/code-completion-agent.ts

@@ -114,6 +114,9 @@ export class CodeCompletionAgentImpl implements CodeCompletionAgent {
             const requestId = generateUuid();
             const request: LanguageModelRequest = {
                 messages: [{ type: 'text', actor: 'user', query: prompt }],
+                settings: {
+                    stream: false
+                }
             };
             if (token.isCancellationRequested) {
                 return undefined;

packages/ai-core/src/browser/frontend-language-model-registry.ts

@@ -366,7 +366,7 @@ const languageModelOutputHandler = (
                     'Sending request:'
                 );
                 const formattedRequest = formatJsonWithIndentation(args[0]);
-                formattedRequest.forEach(line => outputChannel.appendLine(line));
+                outputChannel.append(formattedRequest.join('\n'));
                 if (args[1]) {
                     args[1] = new Proxy(args[1], {
                         get<CK extends keyof CancellationToken>(

packages/ai-openai/src/node/openai-language-model.ts

@@ -66,7 +66,7 @@ export class OpenAiModel implements LanguageModel {
         const settings = this.getSettings(request);
         const openai = this.initializeOpenAi();
 
-        if (this.isNonStreamingModel(this.model)) {
+        if (this.isNonStreamingModel(this.model) || (typeof settings.stream === 'boolean' && !settings.stream)) {
             return this.handleNonStreamingRequest(openai, request);
         }