Enable Gemini 1.5 Flash and Pro, and the Vertex AI in EMEA-based loca…

…tions

app/admin/system/integrations/Google.tsx

@@ -18,12 +18,11 @@ import { callApi } from '@lib/callApi';
 
 /**
  * Google endpoint locations that are available in the Volunteer Manager.
- *
- * @todo Update the locations once PaLM rolls out beyond us-central1.
+ * @see https://cloud.google.com/vertex-ai/docs/general/locations#europe
  */
 const kLocationOptions = [
-    //{ id: 'europe-west2', label: 'London (europe-west2)' },
-    //{ id: 'europe-west4', label: 'Amsterdam (europe-west4)' },
+    { id: 'europe-west2', label: 'London (europe-west2)' },
+    { id: 'europe-west4', label: 'Amsterdam (europe-west4)' },
     { id: 'us-central1', label: 'Iowa (us-central1)' },
     { id: 'us-west1', label: 'Oregon (us-west1)' },
 ];

app/api/admin/serviceHealth.ts

@@ -146,7 +146,9 @@ async function runGoogleHealthCheck(): Promise<Response> {
 async function runVertexAIHealthCheck(): Promise<Response> {
     try {
         const client = await createVertexAIClient();
-        const prediction = await client.predictText('Who is your favourite artist?');
+        const prediction = await client.predictText({
+            prompt: 'Who is your favourite artist?'
+        });
 
         if (typeof prediction === 'string') {
             return {

app/api/admin/vertexAi.ts

@@ -90,5 +90,7 @@ export async function vertexAi(request: Request, props: ActionProps): Promise<Re
         topP: settings?.topP ?? defaultSettings['integration-vertex-top-p']!,
     });
 
-    return { result: await client.predictText(request.prompt) };
+    return {
+        result: await client.predictText({ prompt: request.prompt })
+    };
 }

app/api/ai/generatePrompt.ts

@@ -215,7 +215,7 @@ export async function generatePrompt(request: Request, props: ActionProps): Prom
 
     const client = await createVertexAIClient();
 
-    const rawMessage = await client.predictText(prompt) ?? '[unable to generate message]';
+    const rawMessage = await client.predictText({ prompt }) ?? '[unable to generate message]';
     const message = rawMessage.replaceAll(/\n>[ ]*/g, '\n').replace(/^>\s*/, '');
 
     return { success: true, context, prompt, result: { subject, message } };

app/lib/integrations/vertexai/VertexAIClient.ts

@@ -6,11 +6,6 @@ import { VertexAI } from '@google-cloud/vertexai';
 import { GoogleClient, type GoogleClientSettings } from '../google/GoogleClient';
 import { VertexSupportedModels } from './VertexSupportedModels';
 
-/**
- * Publisher of the PaLM 2 model, as it makes no sense to train our own.
- */
-const kPublisher = 'google';
-
 /**
  * Settings required by the Vertex AI client.
  */
@@ -67,6 +62,24 @@ export interface VertexAISettings {
  */
 export type VertexAIClientSettings = VertexAISettings & GoogleClientSettings;
 
+/**
+ * Interface that describes an input prompt to use with the Vertex AI APIs, now that this can be
+ * richer than a simple string.
+ */
+export interface VertexPrompt {
+    /**
+     * The prompt that should be executed by the generative model.
+     */
+    prompt: string;
+
+    /**
+     * Instructions to share with the system before the LLM gets exposed to any instructions from
+     * the model. This can be used to define the persona, output formats, and so on.
+     * @see https://cloud.google.com/vertex-ai/generative-ai/docs/learn/prompts/system-instructions
+     */
+    systemInstruction?: string;
+}
+
 /**
  * The Vertex AI client allows convenient access to the Google Vertex AI. It builds on top of the
  * Google client for authentication purposes.
@@ -81,28 +94,11 @@ export class VertexAIClient {
     }
 
     /**
-     * Predicts responses to the given `prompt`, which is the full string that should be fed to the
-     * LLM, including instructions towards the answer that is expected from the model.
-     */
-    async predictText(prompt: string): Promise<string | undefined> {
-        switch (this.#settings.model) {
-            case 'text-bison':
-            case 'text-bison@001':
-            case 'text-bison@002':
-                throw new Error('The PaLM models are no longer supported.');
-
-            case 'gemini-pro':
-                return this.predictTextGemini(prompt);
-        }
-
-        throw new Error(`Unrecognised model specified for prediction: ${this.#settings.model}`);
-    }
-
-    /**
-     * Predicts responses to the given `prompt` using the Google Gemini model. The response will be
-     * returned as a string when successful; `undefined` will be returned in all other cases.
+     * Predicts responses to the given `prompt` using the configured Google Gemini model. The
+     * response will be returned as a string when successful; `undefined` will be returned in all
+     * other cases.
      */
-    private async predictTextGemini(prompt: string): Promise<string | undefined> {
+    async predictText(prompt: VertexPrompt): Promise<string | undefined> {
         const client = new VertexAI({
             project: this.#googleClient.projectId,
             location: this.#googleClient.location,
@@ -121,6 +117,7 @@ export class VertexAIClient {
                 topP: this.#settings.topP,
             },
             // TODO: `safetySettings`
+            systemInstruction: prompt.systemInstruction,
         });
 
         const result = await model.generateContent({
@@ -129,7 +126,7 @@ export class VertexAIClient {
                     role: 'USER',
                     parts: [
                         {
-                            text: prompt,
+                            text: prompt.prompt,
                         }
                     ]
                 }

app/lib/integrations/vertexai/VertexSupportedModels.ts

@@ -5,8 +5,7 @@
  * Enumeration of the models that are supported by the Vertex AI API.
  */
 export enum VertexSupportedModels {
-    'gemini-pro' = 'gemini-pro',
-    'text-bison' = 'text-bison',
-    'text-bison@001' = 'text-bison@001',
-    'text-bison@002' = 'text-bison@002',
+    'gemini-1.5-flash-001' = 'gemini-1.5-flash-001',
+    'gemini-1.5-pro-001' = 'gemini-1.5-pro-001',
+    'gemini-1.0-pro-002' = 'gemini-1.0-pro-002',
 }