@ovotech/genesys-web-messaging-tester-cli/lib/commands/aiTest/chatCompletionClients/googleVertexAi/createChatCompletionClient.js

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.createChatCompletionClient = void 0;
const aiplatform_1 = require("@google-cloud/aiplatform");
const { PredictionServiceClient } = aiplatform_1.v1;
function createChatCompletionClient({ location, project, temperature, topK, topP, seed, modelVersion, examples, }) {
    const version = modelVersion ? `@${modelVersion}` : '';
    const endpoint = `projects/${project}/locations/${location}/publishers/google/models/chat-bison${version}`;
    const predictionServiceClient = new PredictionServiceClient({
        apiEndpoint: `${location}-aiplatform.googleapis.com`,
    });
    const parameters = aiplatform_1.helpers.toValue({
        ...(temperature ? { temperature } : {}),
        ...(topK ? { topK } : {}),
        ...(topP ? { topP } : {}),
        ...(seed ? { seed } : {}),
    });
    return {
        getProviderName() {
            return 'Google Vertex AI';
        },
        async preflightCheck() {
            const prompt = {
                context: 'You help people with math problems',
                messages: [{ author: 'student', content: 'What is 1+1?' }],
            };
            const instanceValue = aiplatform_1.helpers.toValue(prompt);
            const request = {
                endpoint,
                instances: [instanceValue],
                parameters,
            };
            try {
                await predictionServiceClient.predict(request);
                return { ok: true };
            }
            catch (error) {
                return {
                    ok: false,
                    reasonForError: error instanceof Error ? error.message : String(error),
                };
            }
        },
        async predict(context, conversationUtterances) {
            const prompt = {
                context,
                ...(examples
                    ? {
                        examples: examples.map(({ input, output }) => ({
                            input: { content: input },
                            output: { content: output },
                        })),
                    }
                    : {}),
                messages: [
                    // Google requires at least one message. This message is hopefully innocuous enough not to lead to an unexpected result.
                    { content: '...', author: 'bot' },
                    ...conversationUtterances.map((u) => ({
                        author: u.role,
                        content: u.content,
                    })),
                ],
            };
            const instanceValue = aiplatform_1.helpers.toValue(prompt);
            const request = {
                endpoint,
                instances: [instanceValue],
                parameters,
            };
            const [response] = await predictionServiceClient.predict(request);
            for (const prediction of response?.predictions || []) {
                const candidates = prediction.structValue?.fields?.candidates;
                for (const candidate of candidates?.listValue?.values || []) {
                    const content = candidate.structValue?.fields?.content?.stringValue;
                    // const author = candidate.structValue?.fields?.author?.stringValue;
                    if (content) {
                        return { content: content.trim(), role: 'customer' };
                    }
                }
            }
            return null;
        },
    };
}
exports.createChatCompletionClient = createChatCompletionClient;