Merge branch 'danny-avila:main' into main

.env.example

@@ -352,6 +352,7 @@ ILLEGAL_MODEL_REQ_SCORE=5
 #========================#
 
 CHECK_BALANCE=false
+# START_BALANCE=20000 # note: the number of tokens that will be credited after registration.
 
 #========================#
 # Registration and Login #

api/app/clients/GoogleClient.js

@@ -1,11 +1,11 @@
 const { google } = require('googleapis');
 const { Agent, ProxyAgent } = require('undici');
 const { ChatVertexAI } = require('@langchain/google-vertexai');
+const { GoogleVertexAI } = require('@langchain/google-vertexai');
+const { ChatGoogleVertexAI } = require('@langchain/google-vertexai');
 const { ChatGoogleGenerativeAI } = require('@langchain/google-genai');
 const { GoogleGenerativeAI: GenAI } = require('@google/generative-ai');
-const { GoogleVertexAI } = require('@langchain/community/llms/googlevertexai');
-const { ChatGoogleVertexAI } = require('langchain/chat_models/googlevertexai');
-const { AIMessage, HumanMessage, SystemMessage } = require('langchain/schema');
+const { AIMessage, HumanMessage, SystemMessage } = require('@langchain/core/messages');
 const { encoding_for_model: encodingForModel, get_encoding: getEncoding } = require('tiktoken');
 const {
   validateVisionModel,

api/app/clients/PluginsClient.js

@@ -1,14 +1,13 @@
 const OpenAIClient = require('./OpenAIClient');
-const { CallbackManager } = require('langchain/callbacks');
 const { CacheKeys, Time } = require('librechat-data-provider');
+const { CallbackManager } = require('@langchain/core/callbacks/manager');
 const { BufferMemory, ChatMessageHistory } = require('langchain/memory');
-const { initializeCustomAgent, initializeFunctionsAgent } = require('./agents');
 const { addImages, buildErrorInput, buildPromptPrefix } = require('./output_parsers');
+const { initializeCustomAgent, initializeFunctionsAgent } = require('./agents');
 const { processFileURL } = require('~/server/services/Files/process');
 const { EModelEndpoint } = require('librechat-data-provider');
 const { formatLangChainMessages } = require('./prompts');
 const checkBalance = require('~/models/checkBalance');
-const { SelfReflectionTool } = require('./tools');
 const { isEnabled } = require('~/server/utils');
 const { extractBaseURL } = require('~/utils');
 const { loadTools } = require('./tools/util');
@@ -122,9 +121,7 @@ class PluginsClient extends OpenAIClient {
       },
     });
 
-    if (this.tools.length > 0 && !this.functionsAgent) {
-      this.tools.push(new SelfReflectionTool({ message, isGpt3: false }));
-    } else if (this.tools.length === 0) {
+    if (this.tools.length === 0) {
       return;
     }
 

api/app/clients/agents/CustomAgent/CustomAgent.js

@@ -1,5 +1,5 @@
 const { ZeroShotAgent } = require('langchain/agents');
-const { PromptTemplate, renderTemplate } = require('langchain/prompts');
+const { PromptTemplate, renderTemplate } = require('@langchain/core/prompts');
 const { gpt3, gpt4 } = require('./instructions');
 
 class CustomAgent extends ZeroShotAgent {

api/app/clients/agents/CustomAgent/initializeCustomAgent.js

@@ -7,7 +7,7 @@ const {
   ChatPromptTemplate,
   SystemMessagePromptTemplate,
   HumanMessagePromptTemplate,
-} = require('langchain/prompts');
+} = require('@langchain/core/prompts');
 
 const initializeCustomAgent = async ({
   tools,

api/app/clients/document/tokenSplit.js

@@ -1,4 +1,4 @@
-const { TokenTextSplitter } = require('langchain/text_splitter');
+const { TokenTextSplitter } = require('@langchain/textsplitters');
 
 /**
  * Splits a given text by token chunks, based on the provided parameters for the TokenTextSplitter.

api/app/clients/document/tokenSplit.spec.js

@@ -12,7 +12,7 @@ describe('tokenSplit', () => {
       returnSize: 5,
     });
 
-    expect(result).toEqual(['. Null', ' Nullam', 'am id', ' id.', '.']);
+    expect(result).toEqual(['it.', '. Null', ' Nullam', 'am id', ' id.']);
   });
 
   it('returns correct text chunks with default parameters', async () => {

api/app/clients/llm/createLLM.js

@@ -1,4 +1,4 @@
-const { ChatOpenAI } = require('langchain/chat_models/openai');
+const { ChatOpenAI } = require('@langchain/openai');
 const { sanitizeModelName, constructAzureURL } = require('~/utils');
 const { isEnabled } = require('~/server/utils');
 

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

@@ -1,5 +1,5 @@
 require('dotenv').config();
-const { ChatOpenAI } = require('langchain/chat_models/openai');
+const { ChatOpenAI } = require('@langchain/openai');
 const { getBufferString, ConversationSummaryBufferMemory } = require('langchain/memory');
 
 const chatPromptMemory = new ConversationSummaryBufferMemory({

api/app/clients/prompts/formatAgentMessages.spec.js

@@ -1,6 +1,6 @@
 const { ToolMessage } = require('@langchain/core/messages');
 const { ContentTypes } = require('librechat-data-provider');
-const { HumanMessage, AIMessage, SystemMessage } = require('langchain/schema');
+const { HumanMessage, AIMessage, SystemMessage } = require('@langchain/core/messages');
 const { formatAgentMessages } = require('./formatMessages');
 
 describe('formatAgentMessages', () => {
@@ -120,7 +120,7 @@ describe('formatAgentMessages', () => {
     ];
     const result = formatAgentMessages(payload);
     expect(result).toHaveLength(2);
-    expect(result[0].tool_calls[0].args).toBe('non-json-string');
+    expect(result[0].tool_calls[0].args).toStrictEqual({ input: 'non-json-string' });
   });
 
   it('should handle complex tool calls with multiple steps', () => {

api/app/clients/prompts/formatMessages.js

@@ -1,6 +1,6 @@
 const { ToolMessage } = require('@langchain/core/messages');
 const { EModelEndpoint, ContentTypes } = require('librechat-data-provider');
-const { HumanMessage, AIMessage, SystemMessage } = require('langchain/schema');
+const { HumanMessage, AIMessage, SystemMessage } = require('@langchain/core/messages');
 
 /**
  * Formats a message to OpenAI Vision API payload format.
@@ -189,10 +189,13 @@ const formatAgentMessages = (payload) => {
         // TODO: investigate; args as dictionary may need to be provider-or-tool-specific
         let args = _args;
         try {
-          args = JSON.parse(args);
+          args = JSON.parse(_args);
         } catch (e) {
-          // failed to parse, leave as is
+          if (typeof _args === 'string') {
+            args = { input: _args };
+          }
         }
+
         tool_call.args = args;
         lastAIMessage.tool_calls.push(tool_call);
 

api/app/clients/prompts/formatMessages.spec.js

@@ -1,5 +1,5 @@
 const { Constants } = require('librechat-data-provider');
-const { HumanMessage, AIMessage, SystemMessage } = require('langchain/schema');
+const { HumanMessage, AIMessage, SystemMessage } = require('@langchain/core/messages');
 const { formatMessage, formatLangChainMessages, formatFromLangChain } = require('./formatMessages');
 
 describe('formatMessage', () => {

api/app/clients/prompts/summaryPrompts.js

@@ -1,4 +1,4 @@
-const { PromptTemplate } = require('langchain/prompts');
+const { PromptTemplate } = require('@langchain/core/prompts');
 /*
  * Without `{summary}` and `{new_lines}`, token count is 98
  * We are counting this towards the max context tokens for summaries, +3 for the assistant label (101)

api/app/clients/prompts/titlePrompts.js

@@ -2,7 +2,7 @@ const {
   ChatPromptTemplate,
   SystemMessagePromptTemplate,
   HumanMessagePromptTemplate,
-} = require('langchain/prompts');
+} = require('@langchain/core/prompts');
 
 const langPrompt = new ChatPromptTemplate({
   promptMessages: [
@@ -99,10 +99,24 @@ ONLY include the generated translation without quotations, nor its related key</
  * @returns {string} The parsed parameter's value or a default value if not found.
  */
 function parseParamFromPrompt(prompt, paramName) {
-  const paramRegex = new RegExp(`<${paramName}>([\\s\\S]+?)</${paramName}>`);
+  // Handle null/undefined prompt
+  if (!prompt) {
+    return `No ${paramName} provided`;
+  }
+
+  // Try original format first: <title>value</title>
+  const simpleRegex = new RegExp(`<${paramName}>(.*?)</${paramName}>`, 's');
+  const simpleMatch = prompt.match(simpleRegex);
+
+  if (simpleMatch) {
+    return simpleMatch[1].trim();
+  }
+
+  // Try parameter format: <parameter name="title">value</parameter>
+  const paramRegex = new RegExp(`<parameter name="${paramName}">(.*?)</parameter>`, 's');
   const paramMatch = prompt.match(paramRegex);
 
-  if (paramMatch && paramMatch[1]) {
+  if (paramMatch) {
     return paramMatch[1].trim();
   }
 

api/app/clients/prompts/titlePrompts.spec.js

@@ -0,0 +1,73 @@
+const { parseParamFromPrompt } = require('./titlePrompts');
+describe('parseParamFromPrompt', () => {
+  // Original simple format tests
+  test('extracts parameter from simple format', () => {
+    const prompt = '<title>Simple Title</title>';
+    expect(parseParamFromPrompt(prompt, 'title')).toBe('Simple Title');
+  });
+
+  // Parameter format tests
+  test('extracts parameter from parameter format', () => {
+    const prompt =
+      '<function_calls> <invoke name="submit_title"> <parameter name="title">Complex Title</parameter> </invoke>';
+    expect(parseParamFromPrompt(prompt, 'title')).toBe('Complex Title');
+  });
+
+  // Edge cases and error handling
+  test('returns NO TOOL INVOCATION message for non-matching content', () => {
+    const prompt = 'Some random text without parameters';
+    expect(parseParamFromPrompt(prompt, 'title')).toBe(
+      'NO TOOL INVOCATION: Some random text without parameters',
+    );
+  });
+
+  test('returns default message for empty prompt', () => {
+    expect(parseParamFromPrompt('', 'title')).toBe('No title provided');
+  });
+
+  test('returns default message for null prompt', () => {
+    expect(parseParamFromPrompt(null, 'title')).toBe('No title provided');
+  });
+
+  // Multiple parameter tests
+  test('works with different parameter names', () => {
+    const prompt = '<name>John Doe</name>';
+    expect(parseParamFromPrompt(prompt, 'name')).toBe('John Doe');
+  });
+
+  test('handles multiline content', () => {
+    const prompt = `<parameter name="description">This is a
+    multiline
+    description</parameter>`;
+    expect(parseParamFromPrompt(prompt, 'description')).toBe(
+      'This is a\n    multiline\n    description',
+    );
+  });
+
+  // Whitespace handling
+  test('trims whitespace from extracted content', () => {
+    const prompt = '<title>  Padded Title  </title>';
+    expect(parseParamFromPrompt(prompt, 'title')).toBe('Padded Title');
+  });
+
+  test('handles whitespace in parameter format', () => {
+    const prompt = '<parameter name="title">  Padded Parameter Title  </parameter>';
+    expect(parseParamFromPrompt(prompt, 'title')).toBe('Padded Parameter Title');
+  });
+
+  // Invalid format tests
+  test('handles malformed tags', () => {
+    const prompt = '<title>Incomplete Tag';
+    expect(parseParamFromPrompt(prompt, 'title')).toBe('NO TOOL INVOCATION: <title>Incomplete Tag');
+  });
+
+  test('handles empty tags', () => {
+    const prompt = '<title></title>';
+    expect(parseParamFromPrompt(prompt, 'title')).toBe('');
+  });
+
+  test('handles empty parameter tags', () => {
+    const prompt = '<parameter name="title"></parameter>';
+    expect(parseParamFromPrompt(prompt, 'title')).toBe('');
+  });
+});

api/app/clients/specs/BaseClient.test.js

@@ -30,7 +30,7 @@ jest.mock('~/models', () => ({
   updateFileUsage: jest.fn(),
 }));
 
-jest.mock('langchain/chat_models/openai', () => {
+jest.mock('@langchain/openai', () => {
   return {
     ChatOpenAI: jest.fn().mockImplementation(() => {
       return {};

api/app/clients/specs/OpenAIClient.test.js

@@ -34,7 +34,7 @@ jest.mock('~/models', () => ({
   updateFileUsage: jest.fn(),
 }));
 
-jest.mock('langchain/chat_models/openai', () => {
+jest.mock('@langchain/openai', () => {
   return {
     ChatOpenAI: jest.fn().mockImplementation(() => {
       return {};