feat: support other configured models in AI assistant

Author: devversion

report-app/report-server.ts

@@ -10,7 +10,7 @@ import {fileURLToPath} from 'node:url';
 import {chatWithReportAI} from '../runner/reporting/report-ai-chat';
 import {convertV2ReportToV3Report} from '../runner/reporting/migrations/v2_to_v3';
 import {FetchedLocalReports, fetchReportsFromDisk} from '../runner/reporting/report-local-disk';
-import {AiChatRequest, RunInfo} from '../runner/shared-interfaces';
+import {AiChatRequest, AIConfigState, RunInfo} from '../runner/shared-interfaces';
 
 // This will result in a lot of loading and would slow down the serving,
 // so it's loaded lazily below.
@@ -88,19 +88,42 @@ app.post('/api/reports/:id/chat', async (req, res) => {
     return;
   }
 
-  const {prompt, pastMessages, model} = req.body as AiChatRequest;
-  const assessments = reports.flatMap(run => run.results);
-  const abortController = new AbortController();
-  const summary = await chatWithReportAI(
-    await (llm ?? getOrCreateGenkitLlmRunner()),
-    prompt,
-    abortController.signal,
-    assessments,
-    pastMessages,
-    model,
-  );
-
-  res.json(summary);
+  try {
+    const {prompt, pastMessages, model} = req.body as AiChatRequest;
+    const assessments = reports.flatMap(run => run.results);
+    const abortController = new AbortController();
+    const summary = await chatWithReportAI(
+      await (llm ?? getOrCreateGenkitLlmRunner()),
+      prompt,
+      abortController.signal,
+      assessments,
+      pastMessages,
+      model,
+    );
+    res.json(summary);
+  } catch (e) {
+    console.error(e);
+    if (e instanceof Error) {
+      console.error(e.stack);
+    }
+    res.status(500);
+    res.end(`Unexpected error. See terminal logs.`);
+  }
+});
+
+app.get('/api/ai-config-state', async (req, res) => {
+  try {
+    const llm = await getOrCreateGenkitLlmRunner();
+    return res.json({
+      configuredModels: llm.getSupportedModelsWithAPIKey(),
+    } satisfies AIConfigState);
+  } catch (e) {
+    console.error('Could not instantiate LLM instance. Error:', e);
+    if (e instanceof Error) {
+      console.error(e.stack);
+    }
+    return res.json({configuredModels: []});
+  }
 });
 
 app.use(

report-app/src/app/shared/ai-assistant/ai-assistant.html

@@ -6,8 +6,8 @@ <h2>AI Assistant</h2>
       </div>
       <div class="model-selector-container">
         <select [(ngModel)]="selectedModel">
-          @for (model of models; track model) {
-            <option [value]="model.id">{{ model.name }}</option>
+          @for (model of models(); track model) {
+            <option [value]="model">{{ model }}</option>
           }
         </select>
       </div>
@@ -29,19 +29,34 @@ <h2>AI Assistant</h2>
   </header>
   <div class="ai-assistant-body">
     <div class="messages-container" #messagesContainer>
-      @for (message of messages; track $index) {
-        <div
-          class="message"
-          [class.user-message]="message.role === 'user'"
-          [class.model-message]="message.role === 'model'"
-        >
-          <div [innerHTML]="message.text"></div>
-        </div>
-      }
-      @if (isLoading()) {
-        <div class="message model-message">
-          <message-spinner message="Thinking..." />
-        </div>
+      @if (aiConfigState.isLoading()) {
+        <message-spinner message="Checking available models for chat..." />
+      } @else if (aiConfigState.error() !== undefined) {
+        Error fetching available models.
+      } @else if (models().length === 0) {
+        @if (models().length === 0) {
+          No models available. Make sure you set API keys as per
+          <a
+            href="https://github.com/angular/web-codegen-scorer?tab=readme-ov-file#setup"
+            target="_blank"
+            >Setup instructions.</a
+          >
+        }
+      } @else {
+        @for (message of messages; track $index) {
+          <div
+            class="message"
+            [class.user-message]="message.role === 'user'"
+            [class.model-message]="message.role === 'model'"
+          >
+            <div [innerHTML]="message.text"></div>
+          </div>
+        }
+        @if (isLoading()) {
+          <div class="message model-message">
+            <message-spinner message="Thinking..." />
+          </div>
+        }
       }
     </div>
     <div class="input-container">

report-app/src/app/shared/ai-assistant/ai-assistant.ts

@@ -1,19 +1,15 @@
-import {HttpClient} from '@angular/common/http';
-import {Component, inject, input, output, signal} from '@angular/core';
+import {HttpClient, httpResource} from '@angular/common/http';
+import {Component, computed, inject, input, linkedSignal, output, signal} from '@angular/core';
 import {FormsModule} from '@angular/forms';
 import {firstValueFrom} from 'rxjs';
 import {
   AiChatMessage,
   AiChatRequest,
   AiChatResponse,
+  AIConfigState,
 } from '../../../../../runner/shared-interfaces';
 import {MessageSpinner} from '../message-spinner';
 
-interface Model {
-  id: string;
-  name: string;
-}
-
 @Component({
   selector: 'app-ai-assistant',
   templateUrl: './ai-assistant.html',
@@ -34,12 +30,9 @@ export class AiAssistant {
 
   private readonly http = inject(HttpClient);
 
-  protected readonly models: Model[] = [
-    {id: 'gemini-2.5-flash', name: 'Gemini 2.5 Flash'},
-    {id: 'gemini-2.5-pro', name: 'Gemini 2.5 Pro'},
-    {id: 'gemini-2.5-flash-lite', name: 'Gemini 2.5 Flash Lite'},
-  ];
-  protected selectedModel = this.models[0].id;
+  protected readonly aiConfigState = httpResource<AIConfigState>(() => '/api/ai-config-state');
+  protected readonly models = computed(() => this.aiConfigState.value()?.configuredModels ?? []);
+  protected selectedModel = linkedSignal(() => this.models()[0]);
 
   protected toggleExpanded(): void {
     this.isExpanded.set(!this.isExpanded());
@@ -60,7 +53,7 @@ export class AiAssistant {
     const payload: AiChatRequest = {
       prompt,
       pastMessages,
-      model: this.selectedModel,
+      model: this.selectedModel(),
     };
 
     try {

runner/codegen/genkit/genkit-runner.ts

@@ -96,6 +96,10 @@ export class GenkitRunner implements LlmRunner {
     return MODEL_PROVIDERS.flatMap(p => p.getSupportedModels());
   }
 
+  getSupportedModelsWithAPIKey(): string[] {
+    return MODEL_PROVIDERS.filter(p => p.getApiKey() !== null).flatMap(p => p.getSupportedModels());
+  }
+
   private async _genkitRequest(
     provider: GenkitModelProvider,
     model: ModelReference<any>,

runner/shared-interfaces.ts

@@ -323,6 +323,11 @@ export interface AiChatMessage {
   text: string;
 }
 
+/** Interface describing the response of the AI config state report-server endpoint. */
+export interface AIConfigState {
+  configuredModels: string[];
+}
+
 /**
  * A summary of build outcomes and code quality scores for an entire assessment run.
  */