LibreChat/api/server/services/ModelService.spec.js
Danny Avila d59b62174f
🪨 feat: AWS Bedrock support (#3935)
* feat: Add BedrockIcon component to SVG library

* feat: EModelEndpoint.bedrock

* feat: first pass, bedrock chat. note: AgentClient is returning `agents` as conversation.endpoint

* fix: declare endpoint in initialization step

* chore: Update @librechat/agents dependency to version 1.4.5

* feat: backend content aggregation for agents/bedrock

* feat: abort agent requests

* feat: AWS Bedrock icons

* WIP: agent provider schema parsing

* chore: Update EditIcon props type

* refactor(useGenerationsByLatest): make agents and bedrock editable

* refactor: non-assistant message content, parts

* fix: Bedrock response `sender`

* fix: use endpointOption.model_parameters not endpointOption.modelOptions

* fix: types for step handler

* refactor: Update Agents.ToolCallDelta type

* refactor: Remove unnecessary assignment of parentMessageId in AskController

* refactor: remove unnecessary assignment of parentMessageId (agent request handler)

* fix(bedrock/agents): message regeneration

* refactor: dynamic form elements using react-hook-form Controllers

* fix: agent icons/labels for messages

* fix: agent actions

* fix: use of new dynamic tags causing application crash

* refactor: dynamic settings touch-ups

* refactor: update Slider component to allow custom track class name

* refactor: update DynamicSlider component styles

* refactor: use Constants value for GLOBAL_PROJECT_NAME (enum)

* feat: agent share global methods/controllers

* fix: agents query

* fix: `getResponseModel`

* fix: share prompt a11y issue

* refactor: update SharePrompt dialog theme styles

* refactor: explicit typing for SharePrompt

* feat: add agent roles/permissions

* chore: update @librechat/agents dependency to version 1.4.7 for tool_call_ids edge case

* fix(Anthropic): messages.X.content.Y.tool_use.input: Input should be a valid dictionary

* fix: handle text parts with tool_call_ids and empty text

* fix: role initialization

* refactor: don't make instructions required

* refactor: improve typing of Text part

* fix: setShowStopButton for agents route

* chore: remove params for now

* fix: add streamBuffer and streamRate to help prevent 'Overloaded' errors from Anthropic API

* refactor: remove console.log statement in ContentRender component

* chore: typing, rename Context to Delete Button

* chore(DeleteButton): logging

* refactor(Action): make accessible

* style(Action): improve a11y again

* refactor: remove use/mention of mongoose sessions

* feat: first pass, sharing agents

* feat: visual indicator for global agent, remove author when serving to non-author

* wip: params

* chore: fix typing issues

* fix(schemas): typing

* refactor: improve accessibility of ListCard component and fix console React warning

* wip: reset templates for non-legacy new convos

* Revert "wip: params"

This reverts commit f8067e91d4.

* Revert "refactor: dynamic form elements using react-hook-form Controllers"

This reverts commit 2150c4815d.

* fix(Parameters): types and parameter effect update to only update local state to parameters

* refactor: optimize useDebouncedInput hook for better performance

* feat: first pass, anthropic bedrock params

* chore: paramEndpoints check for endpointType too

* fix: maxTokens to use coerceNumber.optional(),

* feat: extra chat model params

* chore: reduce code repetition

* refactor: improve preset title handling in SaveAsPresetDialog component

* refactor: improve preset handling in HeaderOptions component

* chore: improve typing, replace legacy dialog for SaveAsPresetDialog

* feat: save as preset from parameters panel

* fix: multi-search in select dropdown when using Option type

* refactor: update default showDefault value to false in Dynamic components

* feat: Bedrock presets settings

* chore: config, fix agents schema, update config version

* refactor: update AWS region variable name in bedrock options endpoint to BEDROCK_AWS_DEFAULT_REGION

* refactor: update baseEndpointSchema in config.ts to include baseURL property

* refactor: update createRun function to include req parameter and set streamRate based on provider

* feat: availableRegions via config

* refactor: remove unused demo agent controller file

* WIP: title

* Update @librechat/agents to version 1.5.0

* chore: addTitle.js to handle empty responseText

* feat: support images and titles

* feat: context token updates

* Refactor BaseClient test to use expect.objectContaining

* refactor: add model select, remove header options params, move side panel params below prompts

* chore: update models list, catch title error

* feat: model service for bedrock models (env)

* chore: Remove verbose debug log in AgentClient class following stream

* feat(bedrock): track token spend; fix: token rates, value key mapping for AWS models

* refactor: handle streamRate in `handleLLMNewToken` callback

* chore: AWS Bedrock example config in `.env.example`

* refactor: Rename bedrockMeta to bedrockGeneral in settings.ts and use for AI21 and Amazon Bedrock providers

* refactor: Update `.env.example` with AWS Bedrock model IDs URL and additional notes

* feat: titleModel support for bedrock

* refactor: Update `.env.example` with additional notes for AWS Bedrock model IDs
2024-09-09 12:06:59 -04:00

408 lines
12 KiB
JavaScript

const axios = require('axios');
const { EModelEndpoint, defaultModels } = require('librechat-data-provider');
const { logger } = require('~/config');
const {
fetchModels,
splitAndTrim,
getOpenAIModels,
getGoogleModels,
getBedrockModels,
getAnthropicModels,
} = require('./ModelService');
jest.mock('~/utils', () => {
const originalUtils = jest.requireActual('~/utils');
return {
...originalUtils,
processModelData: jest.fn((...args) => {
return originalUtils.processModelData(...args);
}),
};
});
jest.mock('axios');
jest.mock('~/cache/getLogStores', () =>
jest.fn().mockImplementation(() => ({
get: jest.fn().mockResolvedValue(undefined),
set: jest.fn().mockResolvedValue(true),
})),
);
jest.mock('~/config', () => ({
logger: {
error: jest.fn(),
},
}));
jest.mock('./Config/EndpointService', () => ({
config: {
openAIApiKey: 'mockedApiKey',
userProvidedOpenAI: false,
},
}));
axios.get.mockResolvedValue({
data: {
data: [{ id: 'model-1' }, { id: 'model-2' }],
},
});
describe('fetchModels', () => {
it('fetches models successfully from the API', async () => {
const models = await fetchModels({
user: 'user123',
apiKey: 'testApiKey',
baseURL: 'https://api.test.com',
name: 'TestAPI',
});
expect(models).toEqual(['model-1', 'model-2']);
expect(axios.get).toHaveBeenCalledWith(
expect.stringContaining('https://api.test.com/models'),
expect.any(Object),
);
});
it('adds the user ID to the models query when option and ID are passed', async () => {
const models = await fetchModels({
user: 'user123',
apiKey: 'testApiKey',
baseURL: 'https://api.test.com',
userIdQuery: true,
name: 'TestAPI',
});
expect(models).toEqual(['model-1', 'model-2']);
expect(axios.get).toHaveBeenCalledWith(
expect.stringContaining('https://api.test.com/models?user=user123'),
expect.any(Object),
);
});
afterEach(() => {
jest.clearAllMocks();
});
});
describe('fetchModels with createTokenConfig true', () => {
const data = {
data: [
{
id: 'model-1',
pricing: {
prompt: '0.002',
completion: '0.001',
},
context_length: 1024,
},
{
id: 'model-2',
pricing: {
prompt: '0.003',
completion: '0.0015',
},
context_length: 2048,
},
],
};
beforeEach(() => {
// Clears the mock's history before each test
const _utils = require('~/utils');
axios.get.mockResolvedValue({ data });
});
it('creates and stores token configuration if createTokenConfig is true', async () => {
await fetchModels({
user: 'user123',
apiKey: 'testApiKey',
baseURL: 'https://api.test.com',
createTokenConfig: true,
});
const { processModelData } = require('~/utils');
expect(processModelData).toHaveBeenCalled();
expect(processModelData).toHaveBeenCalledWith(data);
});
});
describe('getOpenAIModels', () => {
let originalEnv;
beforeEach(() => {
originalEnv = { ...process.env };
axios.get.mockRejectedValue(new Error('Network error'));
});
afterEach(() => {
process.env = originalEnv;
axios.get.mockReset();
});
it('returns default models when no environment configurations are provided (and fetch fails)', async () => {
const models = await getOpenAIModels({ user: 'user456' });
expect(models).toContain('gpt-4');
});
it('returns `AZURE_OPENAI_MODELS` with `azure` flag (and fetch fails)', async () => {
process.env.AZURE_OPENAI_MODELS = 'azure-model,azure-model-2';
const models = await getOpenAIModels({ azure: true });
expect(models).toEqual(expect.arrayContaining(['azure-model', 'azure-model-2']));
});
it('returns `PLUGIN_MODELS` with `plugins` flag (and fetch fails)', async () => {
process.env.PLUGIN_MODELS = 'plugins-model,plugins-model-2';
const models = await getOpenAIModels({ plugins: true });
expect(models).toEqual(expect.arrayContaining(['plugins-model', 'plugins-model-2']));
});
it('returns `OPENAI_MODELS` with no flags (and fetch fails)', async () => {
process.env.OPENAI_MODELS = 'openai-model,openai-model-2';
const models = await getOpenAIModels({});
expect(models).toEqual(expect.arrayContaining(['openai-model', 'openai-model-2']));
});
it('attempts to use OPENROUTER_API_KEY if set', async () => {
process.env.OPENROUTER_API_KEY = 'test-router-key';
const expectedModels = ['model-router-1', 'model-router-2'];
axios.get.mockResolvedValue({
data: {
data: expectedModels.map((id) => ({ id })),
},
});
const models = await getOpenAIModels({ user: 'user456' });
expect(models).toEqual(expect.arrayContaining(expectedModels));
expect(axios.get).toHaveBeenCalled();
});
it('utilizes proxy configuration when PROXY is set', async () => {
axios.get.mockResolvedValue({
data: {
data: [],
},
});
process.env.PROXY = 'http://localhost:8888';
await getOpenAIModels({ user: 'user456' });
expect(axios.get).toHaveBeenCalledWith(
expect.any(String),
expect.objectContaining({
httpsAgent: expect.anything(),
}),
);
});
});
describe('getOpenAIModels with mocked config', () => {
it('uses alternative behavior when userProvidedOpenAI is true', async () => {
jest.mock('./Config/EndpointService', () => ({
config: {
openAIApiKey: 'mockedApiKey',
userProvidedOpenAI: true,
},
}));
jest.mock('librechat-data-provider', () => {
const original = jest.requireActual('librechat-data-provider');
return {
...original,
defaultModels: {
[original.EModelEndpoint.openAI]: ['some-default-model'],
},
};
});
jest.resetModules();
const { getOpenAIModels } = require('./ModelService');
const models = await getOpenAIModels({ user: 'user456' });
expect(models).toContain('some-default-model');
});
});
describe('getOpenAIModels sorting behavior', () => {
beforeEach(() => {
axios.get.mockResolvedValue({
data: {
data: [
{ id: 'gpt-3.5-turbo-instruct-0914' },
{ id: 'gpt-3.5-turbo-instruct' },
{ id: 'gpt-3.5-turbo' },
{ id: 'gpt-4-0314' },
{ id: 'gpt-4-turbo-preview' },
],
},
});
});
it('ensures instruct models are listed last', async () => {
const models = await getOpenAIModels({ user: 'user456' });
// Check if the last model is an "instruct" model
expect(models[models.length - 1]).toMatch(/instruct/);
// Check if the "instruct" models are placed at the end
const instructIndexes = models
.map((model, index) => (model.includes('instruct') ? index : -1))
.filter((index) => index !== -1);
const nonInstructIndexes = models
.map((model, index) => (!model.includes('instruct') ? index : -1))
.filter((index) => index !== -1);
expect(Math.max(...nonInstructIndexes)).toBeLessThan(Math.min(...instructIndexes));
const expectedOrder = [
'gpt-3.5-turbo',
'gpt-4-0314',
'gpt-4-turbo-preview',
'gpt-3.5-turbo-instruct-0914',
'gpt-3.5-turbo-instruct',
];
expect(models).toEqual(expectedOrder);
});
afterEach(() => {
jest.clearAllMocks();
});
});
describe('fetchModels with Ollama specific logic', () => {
const mockOllamaData = {
data: {
models: [{ name: 'Ollama-Base' }, { name: 'Ollama-Advanced' }],
},
};
beforeEach(() => {
axios.get.mockResolvedValue(mockOllamaData);
});
afterEach(() => {
jest.clearAllMocks();
});
it('should fetch Ollama models when name starts with "ollama"', async () => {
const models = await fetchModels({
user: 'user789',
apiKey: 'testApiKey',
baseURL: 'https://api.ollama.test.com',
name: 'OllamaAPI',
});
expect(models).toEqual(['Ollama-Base', 'Ollama-Advanced']);
expect(axios.get).toHaveBeenCalledWith('https://api.ollama.test.com/api/tags'); // Adjusted to expect only one argument if no options are passed
});
it('should handle errors gracefully when fetching Ollama models fails', async () => {
axios.get.mockRejectedValue(new Error('Network error'));
const models = await fetchModels({
user: 'user789',
apiKey: 'testApiKey',
baseURL: 'https://api.ollama.test.com',
name: 'OllamaAPI',
});
expect(models).toEqual([]);
expect(logger.error).toHaveBeenCalled();
});
it('should return an empty array if no baseURL is provided', async () => {
const models = await fetchModels({
user: 'user789',
apiKey: 'testApiKey',
name: 'OllamaAPI',
});
expect(models).toEqual([]);
});
it('should not fetch Ollama models if the name does not start with "ollama"', async () => {
// Mock axios to return a different set of models for non-Ollama API calls
axios.get.mockResolvedValue({
data: {
data: [{ id: 'model-1' }, { id: 'model-2' }],
},
});
const models = await fetchModels({
user: 'user789',
apiKey: 'testApiKey',
baseURL: 'https://api.test.com',
name: 'TestAPI',
});
expect(models).toEqual(['model-1', 'model-2']);
expect(axios.get).toHaveBeenCalledWith(
'https://api.test.com/models', // Ensure the correct API endpoint is called
expect.any(Object), // Ensuring some object (headers, etc.) is passed
);
});
});
describe('splitAndTrim', () => {
it('should split a string by commas and trim each value', () => {
const input = ' model1, model2 , model3,model4 ';
const expected = ['model1', 'model2', 'model3', 'model4'];
expect(splitAndTrim(input)).toEqual(expected);
});
it('should return an empty array for empty input', () => {
expect(splitAndTrim('')).toEqual([]);
});
it('should return an empty array for null input', () => {
expect(splitAndTrim(null)).toEqual([]);
});
it('should return an empty array for undefined input', () => {
expect(splitAndTrim(undefined)).toEqual([]);
});
it('should filter out empty values after trimming', () => {
const input = 'model1,, ,model2,';
const expected = ['model1', 'model2'];
expect(splitAndTrim(input)).toEqual(expected);
});
});
describe('getAnthropicModels', () => {
it('returns default models when ANTHROPIC_MODELS is not set', () => {
delete process.env.ANTHROPIC_MODELS;
const models = getAnthropicModels();
expect(models).toEqual(defaultModels[EModelEndpoint.anthropic]);
});
it('returns models from ANTHROPIC_MODELS when set', () => {
process.env.ANTHROPIC_MODELS = 'claude-1, claude-2 ';
const models = getAnthropicModels();
expect(models).toEqual(['claude-1', 'claude-2']);
});
});
describe('getGoogleModels', () => {
it('returns default models when GOOGLE_MODELS is not set', () => {
delete process.env.GOOGLE_MODELS;
const models = getGoogleModels();
expect(models).toEqual(defaultModels[EModelEndpoint.google]);
});
it('returns models from GOOGLE_MODELS when set', () => {
process.env.GOOGLE_MODELS = 'gemini-pro, bard ';
const models = getGoogleModels();
expect(models).toEqual(['gemini-pro', 'bard']);
});
});
describe('getBedrockModels', () => {
it('returns default models when BEDROCK_AWS_MODELS is not set', () => {
delete process.env.BEDROCK_AWS_MODELS;
const models = getBedrockModels();
expect(models).toEqual(defaultModels[EModelEndpoint.bedrock]);
});
it('returns models from BEDROCK_AWS_MODELS when set', () => {
process.env.BEDROCK_AWS_MODELS = 'anthropic.claude-v2, ai21.j2-ultra ';
const models = getBedrockModels();
expect(models).toEqual(['anthropic.claude-v2', 'ai21.j2-ultra']);
});
});