⚙️ chore: Resolve Build Warning, Package Cleanup, Robust Temp Chat Time (#9962)

* ⚙️ chore: Resolve Build Warning and `keyvMongo` types

* 🔄 chore: Update mongodb version to ^6.14.2 in package.json and package-lock.json

* chore: remove @langchain/openai dep

* 🔄 refactor: Change log level from warn to debug for missing endpoint config

* 🔄 refactor: Improve temp chat expiration date calculation in tests and implementation

api/app/clients/OpenAIClient.js

@@ -43,7 +43,6 @@ const { runTitleChain } = require('./chains');
 const { extractBaseURL } = require('~/utils');
 const { tokenSplit } = require('./document');
 const BaseClient = require('./BaseClient');
-const { createLLM } = require('./llm');
 
 class OpenAIClient extends BaseClient {
   constructor(apiKey, options = {}) {
@@ -614,65 +613,8 @@ class OpenAIClient extends BaseClient {
     return (reply ?? '').trim();
   }
 
-  initializeLLM({
-    model = openAISettings.model.default,
-    modelName,
-    temperature = 0.2,
-    max_tokens,
-    streaming,
-  }) {
-    const modelOptions = {
-      modelName: modelName ?? model,
-      temperature,
-      user: this.user,
-    };
-
-    if (max_tokens) {
-      modelOptions.max_tokens = max_tokens;
-    }
-
-    const configOptions = {};
-
-    if (this.langchainProxy) {
-      configOptions.basePath = this.langchainProxy;
-    }
-
-    if (this.useOpenRouter) {
-      configOptions.basePath = 'https://openrouter.ai/api/v1';
-      configOptions.baseOptions = {
-        headers: {
-          'HTTP-Referer': 'https://librechat.ai',
-          'X-Title': 'LibreChat',
-        },
-      };
-    }
-
-    const { headers } = this.options;
-    if (headers && typeof headers === 'object' && !Array.isArray(headers)) {
-      configOptions.baseOptions = {
-        headers: resolveHeaders({
-          headers: {
-            ...headers,
-            ...configOptions?.baseOptions?.headers,
-          },
-        }),
-      };
-    }
-
-    if (this.options.proxy) {
-      configOptions.httpAgent = new HttpsProxyAgent(this.options.proxy);
-      configOptions.httpsAgent = new HttpsProxyAgent(this.options.proxy);
-    }
-
-    const llm = createLLM({
-      modelOptions,
-      configOptions,
-      openAIApiKey: this.apiKey,
-      azure: this.azure,
-      streaming,
-    });
-
-    return llm;
+  initializeLLM() {
+    throw new Error('Deprecated');
   }
 
   /**

api/app/clients/llm/createLLM.js

@@ -1,81 +0,0 @@
-const { ChatOpenAI } = require('@langchain/openai');
-const { isEnabled, sanitizeModelName, constructAzureURL } = require('@librechat/api');
-
-/**
- * Creates a new instance of a language model (LLM) for chat interactions.
- *
- * @param {Object} options - The options for creating the LLM.
- * @param {ModelOptions} options.modelOptions - The options specific to the model, including modelName, temperature, presence_penalty, frequency_penalty, and other model-related settings.
- * @param {ConfigOptions} options.configOptions - Configuration options for the API requests, including proxy settings and custom headers.
- * @param {Callbacks} [options.callbacks] - Callback functions for managing the lifecycle of the LLM, including token buffers, context, and initial message count.
- * @param {boolean} [options.streaming=false] - Determines if the LLM should operate in streaming mode.
- * @param {string} options.openAIApiKey - The API key for OpenAI, used for authentication.
- * @param {AzureOptions} [options.azure={}] - Optional Azure-specific configurations. If provided, Azure configurations take precedence over OpenAI configurations.
- *
- * @returns {ChatOpenAI} An instance of the ChatOpenAI class, configured with the provided options.
- *
- * @example
- * const llm = createLLM({
- *   modelOptions: { modelName: 'gpt-4o-mini', temperature: 0.2 },
- *   configOptions: { basePath: 'https://example.api/path' },
- *   callbacks: { onMessage: handleMessage },
- *   openAIApiKey: 'your-api-key'
- * });
- */
-function createLLM({
-  modelOptions,
-  configOptions,
-  callbacks,
-  streaming = false,
-  openAIApiKey,
-  azure = {},
-}) {
-  let credentials = { openAIApiKey };
-  let configuration = {
-    apiKey: openAIApiKey,
-    ...(configOptions.basePath && { baseURL: configOptions.basePath }),
-  };
-
-  /**  @type {AzureOptions} */
-  let azureOptions = {};
-  if (azure) {
-    const useModelName = isEnabled(process.env.AZURE_USE_MODEL_AS_DEPLOYMENT_NAME);
-
-    credentials = {};
-    configuration = {};
-    azureOptions = azure;
-
-    azureOptions.azureOpenAIApiDeploymentName = useModelName
-      ? sanitizeModelName(modelOptions.modelName)
-      : azureOptions.azureOpenAIApiDeploymentName;
-  }
-
-  if (azure && process.env.AZURE_OPENAI_DEFAULT_MODEL) {
-    modelOptions.modelName = process.env.AZURE_OPENAI_DEFAULT_MODEL;
-  }
-
-  if (azure && configOptions.basePath) {
-    const azureURL = constructAzureURL({
-      baseURL: configOptions.basePath,
-      azureOptions,
-    });
-    azureOptions.azureOpenAIBasePath = azureURL.split(
-      `/${azureOptions.azureOpenAIApiDeploymentName}`,
-    )[0];
-  }
-
-  return new ChatOpenAI(
-    {
-      streaming,
-      credentials,
-      configuration,
-      ...azureOptions,
-      ...modelOptions,
-      ...credentials,
-      callbacks,
-    },
-    configOptions,
-  );
-}
-
-module.exports = createLLM;

api/app/clients/llm/index.js

@@ -1,7 +1,5 @@
-const createLLM = require('./createLLM');
 const createCoherePayload = require('./createCoherePayload');
 
 module.exports = {
-  createLLM,
   createCoherePayload,
 };

api/app/clients/memory/summaryBuffer.demo.js

@@ -1,31 +0,0 @@
-require('dotenv').config();
-const { ChatOpenAI } = require('@langchain/openai');
-const { getBufferString, ConversationSummaryBufferMemory } = require('langchain/memory');
-
-const chatPromptMemory = new ConversationSummaryBufferMemory({
-  llm: new ChatOpenAI({ modelName: 'gpt-4o-mini', temperature: 0 }),
-  maxTokenLimit: 10,
-  returnMessages: true,
-});
-
-(async () => {
-  await chatPromptMemory.saveContext({ input: 'hi my name\'s Danny' }, { output: 'whats up' });
-  await chatPromptMemory.saveContext({ input: 'not much you' }, { output: 'not much' });
-  await chatPromptMemory.saveContext(
-    { input: 'are you excited for the olympics?' },
-    { output: 'not really' },
-  );
-
-  // We can also utilize the predict_new_summary method directly.
-  const messages = await chatPromptMemory.chatHistory.getMessages();
-  console.log('MESSAGES\n\n');
-  console.log(JSON.stringify(messages));
-  const previous_summary = '';
-  const predictSummary = await chatPromptMemory.predictNewSummary(messages, previous_summary);
-  console.log('SUMMARY\n\n');
-  console.log(JSON.stringify(getBufferString([{ role: 'system', content: predictSummary }])));
-
-  // const { history } = await chatPromptMemory.loadMemoryVariables({});
-  // console.log('HISTORY\n\n');
-  // console.log(JSON.stringify(history));
-})();

api/app/clients/tools/util/handleTools.test.js

@@ -30,7 +30,6 @@ jest.mock('~/server/services/Config', () => ({
   }),
 }));
 
-const { BaseLLM } = require('@langchain/openai');
 const { Calculator } = require('@langchain/community/tools/calculator');
 
 const { User } = require('~/db/models');
@@ -172,7 +171,6 @@ describe('Tool Handlers', () => {
     beforeAll(async () => {
       const toolMap = await loadTools({
         user: fakeUser._id,
-        model: BaseLLM,
         tools: sampleTools,
         returnMap: true,
         useSpecs: true,
@@ -266,7 +264,6 @@ describe('Tool Handlers', () => {
     it('returns an empty object when no tools are requested', async () => {
       toolFunctions = await loadTools({
         user: fakeUser._id,
-        model: BaseLLM,
         returnMap: true,
         useSpecs: true,
       });
@@ -276,7 +273,6 @@ describe('Tool Handlers', () => {
       process.env.SD_WEBUI_URL = mockCredential;
       toolFunctions = await loadTools({
         user: fakeUser._id,
-        model: BaseLLM,
         tools: ['stable-diffusion'],
         functions: true,
         returnMap: true,