LibreChat/api/app/clients/prompts/formatGoogleInputs.spec.js

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feat(Google): Support all Text/Chat Models, Response streaming, `PaLM` -> `Google` 🤖 (#1316) * feat: update PaLM icons * feat: add additional google models * POC: formatting inputs for Vertex AI streaming * refactor: move endpoints services outside of /routes dir to /services/Endpoints * refactor: shorten schemas import * refactor: rename PALM to GOOGLE * feat: make Google editable endpoint * feat: reusable Ask and Edit controllers based off Anthropic * chore: organize imports/logic * fix(parseConvo): include examples in googleSchema * fix: google only allows odd number of messages to be sent * fix: pass proxy to AnthropicClient * refactor: change `google` altName to `Google` * refactor: update getModelMaxTokens and related functions to handle maxTokensMap with nested endpoint model key/values * refactor: google Icon and response sender changes (Codey and Google logo instead of PaLM in all cases) * feat: google support for maxTokensMap * feat: google updated endpoints with Ask/Edit controllers, buildOptions, and initializeClient * feat(GoogleClient): now builds prompt for text models and supports real streaming from Vertex AI through langchain * chore(GoogleClient): remove comments, left before for reference in git history * docs: update google instructions (WIP) * docs(apis_and_tokens.md): add images to google instructions * docs: remove typo apis_and_tokens.md * Update apis_and_tokens.md * feat(Google): use default settings map, fully support context for both text and chat models, fully support examples for chat models * chore: update more PaLM references to Google * chore: move playwright out of workflows to avoid failing tests
2023-12-10 14:54:13 -05:00
const formatGoogleInputs = require('./formatGoogleInputs');
describe('formatGoogleInputs', () => {
it('formats message correctly', () => {
const input = {
messages: [
{
content: 'hi',
author: 'user',
},
],
context: 'context',
examples: [
{
input: {
author: 'user',
content: 'user input',
},
output: {
author: 'bot',
content: 'bot output',
},
},
],
parameters: {
temperature: 0.2,
topP: 0.8,
topK: 40,
maxOutputTokens: 1024,
},
};
const expectedOutput = {
struct_val: {
messages: {
list_val: [
{
struct_val: {
content: {
string_val: ['hi'],
},
author: {
string_val: ['user'],
},
},
},
],
},
context: {
string_val: ['context'],
},
examples: {
list_val: [
{
struct_val: {
input: {
struct_val: {
author: {
string_val: ['user'],
},
content: {
string_val: ['user input'],
},
},
},
output: {
struct_val: {
author: {
string_val: ['bot'],
},
content: {
string_val: ['bot output'],
},
},
},
},
},
],
},
parameters: {
struct_val: {
temperature: {
float_val: 0.2,
},
topP: {
float_val: 0.8,
},
topK: {
int_val: 40,
},
maxOutputTokens: {
int_val: 1024,
},
},
},
},
};
const result = formatGoogleInputs(input);
expect(JSON.stringify(result)).toEqual(JSON.stringify(expectedOutput));
});
it('formats real payload parts', () => {
const input = {
instances: [
{
context: 'context',
examples: [
{
input: {
author: 'user',
content: 'user input',
},
output: {
author: 'bot',
content: 'user output',
},
},
],
messages: [
{
author: 'user',
content: 'hi',
},
],
},
],
parameters: {
candidateCount: 1,
maxOutputTokens: 1024,
temperature: 0.2,
topP: 0.8,
topK: 40,
},
};
const expectedOutput = {
struct_val: {
instances: {
list_val: [
{
struct_val: {
context: { string_val: ['context'] },
examples: {
list_val: [
{
struct_val: {
input: {
struct_val: {
author: { string_val: ['user'] },
content: { string_val: ['user input'] },
},
},
output: {
struct_val: {
author: { string_val: ['bot'] },
content: { string_val: ['user output'] },
},
},
},
},
],
},
messages: {
list_val: [
{
struct_val: {
author: { string_val: ['user'] },
content: { string_val: ['hi'] },
},
},
],
},
},
},
],
},
parameters: {
struct_val: {
candidateCount: { int_val: 1 },
maxOutputTokens: { int_val: 1024 },
temperature: { float_val: 0.2 },
topP: { float_val: 0.8 },
topK: { int_val: 40 },
},
},
},
};
const result = formatGoogleInputs(input);
expect(JSON.stringify(result)).toEqual(JSON.stringify(expectedOutput));
});
it('helps create valid payload parts', () => {
const instances = {
context: 'context',
examples: [
{
input: {
author: 'user',
content: 'user input',
},
output: {
author: 'bot',
content: 'user output',
},
},
],
messages: [
{
author: 'user',
content: 'hi',
},
],
};
const expectedInstances = {
struct_val: {
context: { string_val: ['context'] },
examples: {
list_val: [
{
struct_val: {
input: {
struct_val: {
author: { string_val: ['user'] },
content: { string_val: ['user input'] },
},
},
output: {
struct_val: {
author: { string_val: ['bot'] },
content: { string_val: ['user output'] },
},
},
},
},
],
},
messages: {
list_val: [
{
struct_val: {
author: { string_val: ['user'] },
content: { string_val: ['hi'] },
},
},
],
},
},
};
const parameters = {
candidateCount: 1,
maxOutputTokens: 1024,
temperature: 0.2,
topP: 0.8,
topK: 40,
};
const expectedParameters = {
struct_val: {
candidateCount: { int_val: 1 },
maxOutputTokens: { int_val: 1024 },
temperature: { float_val: 0.2 },
topP: { float_val: 0.8 },
topK: { int_val: 40 },
},
};
const instancesResult = formatGoogleInputs(instances);
const parametersResult = formatGoogleInputs(parameters);
expect(JSON.stringify(instancesResult)).toEqual(JSON.stringify(expectedInstances));
expect(JSON.stringify(parametersResult)).toEqual(JSON.stringify(expectedParameters));
});
});