🧬 chore: Align LibreChat With Agents LangChain Upgrade (#12922)

* 🔧 chore: Update dependencies in package-lock.json and package.json

- Bump version of @librechat/agents to 3.1.75-dev.0 in multiple package.json files.
- Upgrade various AWS SDK and Smithy dependencies to their latest versions in package-lock.json for improved stability and performance.

* 🔧 chore: Update AWS SDK and Smithy dependencies in package-lock.json

- Bump version of @aws-sdk/client-bedrock-runtime to 3.1041.0 and update related dependencies for improved performance and stability.
- Upgrade various AWS SDK and Smithy packages to their latest versions, ensuring compatibility and enhanced functionality.

* chore: Align LibreChat with agents LangChain upgrade

- Route LangChain imports through @librechat/agents facade exports
- Update @librechat/agents to 3.1.75-dev.1 and remove direct LangChain deps
- Normalize nullable agent model params and API key override typing
- Update Google thinking config typing for newer LangChain packages
- Refresh targeted audit-related dependency overrides

* chore: Add Jest types for API specs

* test: Fix LangChain upgrade CI specs

* test: Exercise agents env facade

* fix: Clean up TS preview diagnostics

* fix: Address Codex review feedback

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

@@ -1,6 +1,10 @@
-const { ToolMessage } = require('@langchain/core/messages');
 const { ContentTypes } = require('librechat-data-provider');
-const { HumanMessage, AIMessage, SystemMessage } = require('@langchain/core/messages');
+const {
+  AIMessage,
+  ToolMessage,
+  HumanMessage,
+  SystemMessage,
+} = require('@librechat/agents/langchain/messages');
 const { formatAgentMessages } = require('./formatMessages');
 
 describe('formatAgentMessages', () => {

api/app/clients/prompts/formatMessages.js

@@ -1,6 +1,10 @@
-const { ToolMessage } = require('@langchain/core/messages');
 const { EModelEndpoint, ContentTypes } = require('librechat-data-provider');
-const { HumanMessage, AIMessage, SystemMessage } = require('@langchain/core/messages');
+const {
+  AIMessage,
+  ToolMessage,
+  HumanMessage,
+  SystemMessage,
+} = require('@librechat/agents/langchain/messages');
 
 /**
  * Formats a message to OpenAI Vision API payload format.
@@ -191,7 +195,7 @@ const formatAgentMessages = (payload) => {
         let args = _args;
         try {
           args = JSON.parse(_args);
-        } catch (e) {
+        } catch (_e) {
           if (typeof _args === 'string') {
             args = { input: _args };
           }

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

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

api/app/clients/prompts/summaryPrompts.js

@@ -1,4 +1,4 @@
-const { PromptTemplate } = require('@langchain/core/prompts');
+const { PromptTemplate } = require('@librechat/agents/langchain/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/tools/structured/AzureAISearch.js

@@ -1,5 +1,5 @@
-const { Tool } = require('@langchain/core/tools');
 const { logger } = require('@librechat/data-schemas');
+const { Tool } = require('@librechat/agents/langchain/tools');
 const { SearchClient, AzureKeyCredential } = require('@azure/search-documents');
 
 const azureAISearchJsonSchema = {

api/app/clients/tools/structured/DALLE3.js

@@ -2,8 +2,8 @@ const path = require('path');
 const OpenAI = require('openai');
 const { v4: uuidv4 } = require('uuid');
 const { ProxyAgent, fetch } = require('undici');
-const { Tool } = require('@langchain/core/tools');
 const { logger } = require('@librechat/data-schemas');
+const { Tool } = require('@librechat/agents/langchain/tools');
 const { getImageBasename, extractBaseURL } = require('@librechat/api');
 const { FileContext, ContentTypes } = require('librechat-data-provider');
 

api/app/clients/tools/structured/FluxAPI.js

@@ -1,9 +1,9 @@
 const axios = require('axios');
 const fetch = require('node-fetch');
 const { v4: uuidv4 } = require('uuid');
-const { Tool } = require('@langchain/core/tools');
 const { logger } = require('@librechat/data-schemas');
 const { HttpsProxyAgent } = require('https-proxy-agent');
+const { Tool } = require('@librechat/agents/langchain/tools');
 const { FileContext, ContentTypes } = require('librechat-data-provider');
 
 const fluxApiJsonSchema = {

api/app/clients/tools/structured/GeminiImageGen.js

@@ -3,8 +3,8 @@ const sharp = require('sharp');
 const { v4 } = require('uuid');
 const { ProxyAgent } = require('undici');
 const { GoogleGenAI } = require('@google/genai');
-const { tool } = require('@langchain/core/tools');
 const { logger } = require('@librechat/data-schemas');
+const { tool } = require('@librechat/agents/langchain/tools');
 const { ContentTypes, EImageOutputType } = require('librechat-data-provider');
 const {
   geminiToolkit,

api/app/clients/tools/structured/GoogleSearch.js

@@ -1,5 +1,5 @@
-const { Tool } = require('@langchain/core/tools');
-const { getEnvironmentVariable } = require('@langchain/core/utils/env');
+const { Tool } = require('@librechat/agents/langchain/tools');
+const { getEnvironmentVariable } = require('@librechat/agents/langchain/utils/env');
 
 const googleSearchJsonSchema = {
   type: 'object',

api/app/clients/tools/structured/OpenAIImageTools.js

@@ -3,9 +3,9 @@ const { v4 } = require('uuid');
 const OpenAI = require('openai');
 const FormData = require('form-data');
 const { ProxyAgent } = require('undici');
-const { tool } = require('@langchain/core/tools');
 const { logger } = require('@librechat/data-schemas');
 const { HttpsProxyAgent } = require('https-proxy-agent');
+const { tool } = require('@librechat/agents/langchain/tools');
 const { ContentTypes, EImageOutputType } = require('librechat-data-provider');
 const { logAxiosError, oaiToolkit, extractBaseURL } = require('@librechat/api');
 const { getStrategyFunctions } = require('~/server/services/Files/strategies');

api/app/clients/tools/structured/OpenWeather.js

@@ -1,6 +1,6 @@
-const { Tool } = require('@langchain/core/tools');
-const { getEnvironmentVariable } = require('@langchain/core/utils/env');
 const fetch = require('node-fetch');
+const { Tool } = require('@librechat/agents/langchain/tools');
+const { getEnvironmentVariable } = require('@librechat/agents/langchain/utils/env');
 
 const openWeatherJsonSchema = {
   type: 'object',

api/app/clients/tools/structured/StableDiffusion.js

@@ -4,8 +4,8 @@ const path = require('path');
 const axios = require('axios');
 const sharp = require('sharp');
 const { v4: uuidv4 } = require('uuid');
-const { Tool } = require('@langchain/core/tools');
 const { logger } = require('@librechat/data-schemas');
+const { Tool } = require('@librechat/agents/langchain/tools');
 const { FileContext, ContentTypes } = require('librechat-data-provider');
 const { getBasePath } = require('@librechat/api');
 const paths = require('~/config/paths');

api/app/clients/tools/structured/TavilySearch.js

@@ -1,6 +1,6 @@
 const { z } = require('zod');
 const { ProxyAgent, fetch } = require('undici');
-const { tool } = require('@langchain/core/tools');
+const { tool } = require('@librechat/agents/langchain/tools');
 const { getApiKey } = require('./credentials');
 
 function createTavilySearchTool(fields = {}) {

api/app/clients/tools/structured/TavilySearchResults.js

@@ -1,6 +1,6 @@
 const { ProxyAgent, fetch } = require('undici');
-const { Tool } = require('@langchain/core/tools');
-const { getEnvironmentVariable } = require('@langchain/core/utils/env');
+const { Tool } = require('@librechat/agents/langchain/tools');
+const { getEnvironmentVariable } = require('@librechat/agents/langchain/utils/env');
 
 const tavilySearchJsonSchema = {
   type: 'object',

api/app/clients/tools/structured/TraversaalSearch.js

@@ -1,6 +1,6 @@
-const { Tool } = require('@langchain/core/tools');
 const { logger } = require('@librechat/data-schemas');
-const { getEnvironmentVariable } = require('@langchain/core/utils/env');
+const { Tool } = require('@librechat/agents/langchain/tools');
+const { getEnvironmentVariable } = require('@librechat/agents/langchain/utils/env');
 
 const traversaalSearchJsonSchema = {
   type: 'object',

api/app/clients/tools/structured/Wolfram.js

@@ -1,7 +1,7 @@
 /* eslint-disable no-useless-escape */
 const axios = require('axios');
-const { Tool } = require('@langchain/core/tools');
 const { logger } = require('@librechat/data-schemas');
+const { Tool } = require('@librechat/agents/langchain/tools');
 
 const wolframJsonSchema = {
   type: 'object',

api/app/clients/tools/structured/credentials.js

@@ -1,4 +1,4 @@
-const { getEnvironmentVariable } = require('@langchain/core/utils/env');
+const { getEnvironmentVariable } = require('@librechat/agents/langchain/utils/env');
 
 function getApiKey(envVar, override) {
   const key = getEnvironmentVariable(envVar);

api/app/clients/tools/structured/specs/GoogleSearch.spec.js

@@ -1,7 +1,6 @@
 const GoogleSearch = require('../GoogleSearch');
 
 jest.mock('node-fetch');
-jest.mock('@langchain/core/utils/env');
 
 describe('GoogleSearch', () => {
   let originalEnv;

api/app/clients/tools/structured/specs/TavilySearchResults.spec.js

@@ -2,7 +2,6 @@ const { fetch, ProxyAgent } = require('undici');
 const TavilySearchResults = require('../TavilySearchResults');
 
 jest.mock('undici');
-jest.mock('@langchain/core/utils/env');
 
 describe('TavilySearchResults', () => {
   let originalEnv;

api/app/clients/tools/structured/specs/imageTools-agent.spec.js

@@ -12,8 +12,8 @@ const axios = require('axios');
 const OpenAI = require('openai');
 const undici = require('undici');
 const fetch = require('node-fetch');
-const { ToolMessage } = require('@langchain/core/messages');
 const { ContentTypes } = require('librechat-data-provider');
+const { ToolMessage } = require('@librechat/agents/langchain/messages');
 const StableDiffusionAPI = require('../StableDiffusion');
 const FluxAPI = require('../FluxAPI');
 const DALLE3 = require('../DALLE3');

api/app/clients/tools/util/fileSearch.js

@@ -1,6 +1,6 @@
 const axios = require('axios');
-const { tool } = require('@langchain/core/tools');
 const { logger } = require('@librechat/data-schemas');
+const { tool } = require('@librechat/agents/langchain/tools');
 const { generateShortLivedToken } = require('@librechat/api');
 const { Tools, EToolResources } = require('librechat-data-provider');
 const { filterFilesByAgentAccess } = require('~/server/services/Files/permissions');

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

@@ -106,8 +106,8 @@ const validateTools = async (user, tools = []) => {
   }
 };
 
-/** @typedef {typeof import('@langchain/core/tools').Tool} ToolConstructor */
-/** @typedef {import('@langchain/core/tools').Tool} Tool */
+/** @typedef {typeof import('@librechat/agents/langchain/tools').Tool} ToolConstructor */
+/** @typedef {import('@librechat/agents/langchain/tools').Tool} Tool */
 
 /**
  * Initializes a tool with authentication values for the given user, supporting alternate authentication fields.

api/package.json

@@ -38,13 +38,12 @@
     "@aws-sdk/client-bedrock-runtime": "^3.1013.0",
     "@aws-sdk/client-s3": "^3.980.0",
     "@aws-sdk/s3-request-presigner": "^3.758.0",
-    "@azure/identity": "^4.7.0",
+    "@azure/identity": "^4.13.1",
     "@azure/search-documents": "^12.0.0",
     "@azure/storage-blob": "^12.30.0",
     "@google/genai": "^1.19.0",
     "@keyv/redis": "^4.3.3",
-    "@langchain/core": "^0.3.80",
-    "@librechat/agents": "^3.1.75",
+    "@librechat/agents": "^3.1.75-dev.1",
     "@librechat/api": "*",
     "@librechat/data-schemas": "*",
     "@microsoft/microsoft-graph-client": "^3.0.7",

api/server/controllers/agents/client.js

@@ -1,6 +1,6 @@
 require('events').EventEmitter.defaultMaxListeners = 100;
 const { logger } = require('@librechat/data-schemas');
-const { getBufferString, HumanMessage } = require('@langchain/core/messages');
+const { getBufferString, HumanMessage } = require('@librechat/agents/langchain/messages');
 const {
   createRun,
   isEnabled,

api/server/controllers/agents/client.test.js

@@ -1250,7 +1250,7 @@ describe('AgentClient - titleConvo', () => {
         '# MCP Server Instructions\n\nTest MCP instructions here',
       );
 
-      const { DynamicStructuredTool } = require('@langchain/core/tools');
+      const { DynamicStructuredTool } = require('@librechat/agents/langchain/tools');
 
       // Create mock MCP tools with the delimiter pattern
       const mockMCPTool1 = new DynamicStructuredTool({
@@ -1482,7 +1482,7 @@ describe('AgentClient - titleConvo', () => {
     });
 
     it('should filter out image URLs from message content', async () => {
-      const { HumanMessage, AIMessage } = require('@langchain/core/messages');
+      const { HumanMessage, AIMessage } = require('@librechat/agents/langchain/messages');
       const messages = [
         new HumanMessage({
           content: [
@@ -1538,7 +1538,7 @@ describe('AgentClient - titleConvo', () => {
     });
 
     it('should handle messages with only text content', async () => {
-      const { HumanMessage, AIMessage } = require('@langchain/core/messages');
+      const { HumanMessage, AIMessage } = require('@librechat/agents/langchain/messages');
       const messages = [
         new HumanMessage('Hello, how are you?'),
         new AIMessage('I am doing well, thank you!'),
@@ -1556,7 +1556,7 @@ describe('AgentClient - titleConvo', () => {
     });
 
     it('should handle mixed content types correctly', async () => {
-      const { HumanMessage } = require('@langchain/core/messages');
+      const { HumanMessage } = require('@librechat/agents/langchain/messages');
       const { ContentTypes } = require('librechat-data-provider');
 
       const messages = [
@@ -1593,7 +1593,7 @@ describe('AgentClient - titleConvo', () => {
     });
 
     it('should preserve original messages without mutation', async () => {
-      const { HumanMessage } = require('@langchain/core/messages');
+      const { HumanMessage } = require('@librechat/agents/langchain/messages');
       const originalContent = [
         {
           type: 'text',
@@ -1622,7 +1622,7 @@ describe('AgentClient - titleConvo', () => {
     });
 
     it('should handle message window size correctly', async () => {
-      const { HumanMessage, AIMessage } = require('@langchain/core/messages');
+      const { HumanMessage, AIMessage } = require('@librechat/agents/langchain/messages');
       const messages = [
         new HumanMessage('Message 1'),
         new AIMessage('Response 1'),
@@ -1646,7 +1646,7 @@ describe('AgentClient - titleConvo', () => {
     });
 
     it('should return early if processMemory is not set', async () => {
-      const { HumanMessage } = require('@langchain/core/messages');
+      const { HumanMessage } = require('@librechat/agents/langchain/messages');
       client.processMemory = null;
 
       const result = await client.runMemory([new HumanMessage('Test')]);

api/server/services/ActionService.js

@@ -1,7 +1,7 @@
 const jwt = require('jsonwebtoken');
 const { nanoid } = require('nanoid');
-const { tool } = require('@langchain/core/tools');
 const { GraphEvents, sleep } = require('@librechat/agents');
+const { tool } = require('@librechat/agents/langchain/tools');
 const { logger, encryptV2, decryptV2 } = require('@librechat/data-schemas');
 const {
   sendEvent,

api/server/services/MCP.js

@@ -1,4 +1,4 @@
-const { tool } = require('@langchain/core/tools');
+const { tool } = require('@librechat/agents/langchain/tools');
 const { logger, getTenantId } = require('@librechat/data-schemas');
 const {
   Providers,

api/server/services/ToolService.js

@@ -1,12 +1,12 @@
 const { logger } = require('@librechat/data-schemas');
-const { tool: toolFn, DynamicStructuredTool } = require('@langchain/core/tools');
+const { tool: toolFn, DynamicStructuredTool } = require('@librechat/agents/langchain/tools');
 const {
   sleep,
   StepTypes,
   GraphEvents,
   createToolSearch,
-  Constants: AgentConstants,
   createBashExecutionTool,
+  Constants: AgentConstants,
   createProgrammaticToolCallingTool,
 } = require('@librechat/agents');
 const {
@@ -17,10 +17,10 @@ const {
   GenerationJobManager,
   isActionDomainAllowed,
   buildWebSearchContext,
-  buildWebSearchDynamicContext,
   buildImageToolContext,
-  buildToolClassification,
   buildOAuthToolCallName,
+  buildToolClassification,
+  buildWebSearchDynamicContext,
 } = require('@librechat/api');
 const {
   Time,

api/server/services/start/tools.js

@@ -1,9 +1,9 @@
 const fs = require('fs');
 const path = require('path');
-const { Tool } = require('@langchain/core/tools');
 const { Calculator } = require('@librechat/agents');
 const { logger } = require('@librechat/data-schemas');
 const { zodToJsonSchema } = require('zod-to-json-schema');
+const { Tool } = require('@librechat/agents/langchain/tools');
 const { Tools, ImageVisionTool } = require('librechat-data-provider');
 const { getToolkitKey, oaiToolkit, geminiToolkit } = require('@librechat/api');
 const { toolkits } = require('~/app/clients/tools/manifest');

api/typedefs.js

@@ -162,25 +162,25 @@
 
 /**
  * @exports BaseMessage
- * @typedef {import('@langchain/core/messages').BaseMessage} BaseMessage
+ * @typedef {import('@librechat/agents/langchain/messages').BaseMessage} BaseMessage
  * @memberof typedefs
  */
 
 /**
  * @exports UsageMetadata
- * @typedef {import('@langchain/core/messages').UsageMetadata} UsageMetadata
+ * @typedef {import('@librechat/agents/langchain/messages').UsageMetadata} UsageMetadata
  * @memberof typedefs
  */
 
 /**
  * @exports LangChainToolCall
- * @typedef {import('@langchain/core/messages/tool').ToolCall} LangChainToolCall
+ * @typedef {import('@librechat/agents/langchain/messages/tool').ToolCall} LangChainToolCall
  * @memberof typedefs
  */
 
 /**
  * @exports GraphRunnableConfig
- * @typedef {import('@langchain/core/runnables').RunnableConfig<{
+ * @typedef {import('@librechat/agents/langchain/runnables').RunnableConfig<{
  *  req: ServerRequest;
  * thread_id: string;
  * run_id: string;

package.json

@@ -139,20 +139,15 @@
     "typescript-eslint": "^8.24.0"
   },
   "overrides": {
-    "@anthropic-ai/sdk": "0.73.0",
     "@xmldom/xmldom": "^0.8.13",
-    "@librechat/agents": {
-      "@langchain/anthropic": {
-        "@anthropic-ai/sdk": "0.73.0",
-        "fast-xml-parser": "5.6.0"
-      },
-      "@anthropic-ai/sdk": "0.73.0",
-      "fast-xml-parser": "5.6.0"
-    },
     "elliptic": "^6.6.1",
-    "fast-xml-parser": "5.6.0",
     "form-data": "^4.0.4",
+    "langsmith": "^0.6.0",
+    "postcss": "^8.5.13",
     "tslib": "^2.8.1",
+    "@anthropic-ai/sdk": "^0.92.0",
+    "fast-xml-parser": "5.7.2",
+    "serialize-javascript": "7.0.5",
     "mdast-util-gfm-autolink-literal": "2.0.0",
     "remark-gfm": {
       "mdast-util-gfm-autolink-literal": "2.0.0"
@@ -169,7 +164,6 @@
         "katex": "^0.16.21"
       }
     },
-    "langsmith": "0.4.12",
     "eslint": {
       "ajv": "6.14.0"
     },

packages/api/package.json

@@ -89,13 +89,12 @@
     "@anthropic-ai/vertex-sdk": "^0.14.3",
     "@aws-sdk/client-bedrock-runtime": "^3.1013.0",
     "@aws-sdk/client-s3": "^3.980.0",
-    "@azure/identity": "^4.7.0",
+    "@azure/identity": "^4.13.1",
     "@azure/search-documents": "^12.0.0",
     "@azure/storage-blob": "^12.30.0",
     "@google/genai": "^1.19.0",
     "@keyv/redis": "^4.3.3",
-    "@langchain/core": "^0.3.80",
-    "@librechat/agents": "^3.1.75",
+    "@librechat/agents": "^3.1.75-dev.1",
     "@librechat/data-schemas": "*",
     "@modelcontextprotocol/sdk": "^1.29.0",
     "@smithy/node-http-handler": "^4.4.5",

packages/api/src/agents/__tests__/skills.test.ts

@@ -33,7 +33,7 @@ jest.mock('@librechat/agents', () => ({
 }));
 
 import { Types } from 'mongoose';
-import { HumanMessage, AIMessage } from '@langchain/core/messages';
+import { HumanMessage, AIMessage } from '@librechat/agents/langchain/messages';
 import {
   scopeSkillIds,
   resolveSkillActive,

packages/api/src/agents/chain.ts

@@ -1,5 +1,5 @@
-import { PromptTemplate } from '@langchain/core/prompts';
-import { BaseMessage, getBufferString } from '@langchain/core/messages';
+import { PromptTemplate } from '@librechat/agents/langchain/prompts';
+import { BaseMessage, getBufferString } from '@librechat/agents/langchain/messages';
 import type { GraphEdge } from '@librechat/agents';
 
 const DEFAULT_PROMPT_TEMPLATE = `Based on the following conversation and analysis from previous agents, please provide your insights:\n\n{convo}\n\nPlease add your specific expertise and perspective to this discussion.`;

packages/api/src/agents/client.ts

@@ -7,9 +7,9 @@ import {
   estimateOpenAIImageTokens,
   estimateAnthropicImageTokens,
 } from '@librechat/agents';
+import type { BaseMessage } from '@librechat/agents/langchain/messages';
 import type { MessageContentComplex } from '@librechat/agents';
 import type { Agent, TMessage } from 'librechat-data-provider';
-import type { BaseMessage } from '@langchain/core/messages';
 import type { ServerRequest } from '~/types';
 import Tokenizer from '~/utils/tokenizer';
 import { logAxiosError } from '~/utils';

packages/api/src/agents/context.spec.ts

@@ -1,6 +1,6 @@
 import { z } from 'zod';
 import { Constants } from 'librechat-data-provider';
-import { DynamicStructuredTool } from '@langchain/core/tools';
+import { DynamicStructuredTool } from '@librechat/agents/langchain/tools';
 import type { Logger } from 'winston';
 import type { MCPManager } from '~/mcp/MCPManager';
 import type { AgentWithTools } from './context';

packages/api/src/agents/context.ts

@@ -1,5 +1,5 @@
 import { Constants } from 'librechat-data-provider';
-import { DynamicStructuredTool } from '@langchain/core/tools';
+import { DynamicStructuredTool } from '@librechat/agents/langchain/tools';
 import type { Agent, TEphemeralAgent } from 'librechat-data-provider';
 import type { LCTool } from '@librechat/agents';
 import type { Logger } from 'winston';

packages/api/src/agents/handlers.ts

@@ -10,12 +10,12 @@ import type {
   ToolExecuteBatchRequest,
 } from '@librechat/agents';
 import { Types } from 'mongoose';
-import type { StructuredToolInterface } from '@langchain/core/tools';
+import type { StructuredToolInterface } from '@librechat/agents/langchain/tools';
+import type { SkillFileRecord } from './skillFiles';
 import type { ServerRequest } from '~/types';
+import { buildSkillPrimeMessage } from './skills';
 import { cleanCodeToolOutput } from './cleanup';
 import { primeSkillFiles } from './skillFiles';
-import type { SkillFileRecord } from './skillFiles';
-import { buildSkillPrimeMessage } from './skills';
 import { runOutsideTracing } from '~/utils';
 
 export interface ToolEndCallbackData {
@@ -694,13 +694,13 @@ async function handleReadFileCall(
     }
 
     const stream = await strategy.getDownloadStream(req, file.filepath);
-    const chunks: Buffer[] = [];
+    const chunks: Uint8Array[] = [];
     // Use the larger binary limit as streaming cap; cheaper type-specific
     // checks happen after binary detection on the assembled buffer.
     const streamLimit = MAX_BINARY_BYTES;
     let streamedBytes = 0;
-    for await (const chunk of stream as AsyncIterable<Buffer>) {
-      streamedBytes += chunk.length;
+    for await (const chunk of stream as AsyncIterable<Uint8Array>) {
+      streamedBytes += chunk.byteLength;
       if (streamedBytes > streamLimit) {
         // Destroy the stream if possible to free resources
         if (

packages/api/src/agents/memory.spec.ts

@@ -326,7 +326,7 @@ describe('Memory Agent Header Resolution', () => {
       model: 'us.anthropic.claude-haiku-4-5-20251001-v1:0',
     };
 
-    const { HumanMessage } = await import('@langchain/core/messages');
+    const { HumanMessage } = await import('@librechat/agents/langchain/messages');
     const testMessage = new HumanMessage('test chat content');
 
     await processMemory({

packages/api/src/agents/memory.ts

@@ -1,22 +1,22 @@
 /** Memories */
 import { z } from 'zod';
-import { tool } from '@langchain/core/tools';
 import { Tools } from 'librechat-data-provider';
 import { logger } from '@librechat/data-schemas';
-import { HumanMessage } from '@langchain/core/messages';
+import { tool } from '@librechat/agents/langchain/tools';
 import { Run, Providers, GraphEvents } from '@librechat/agents';
+import { HumanMessage } from '@librechat/agents/langchain/messages';
 import type {
   OpenAIClientOptions,
   StreamEventData,
   ToolEndCallback,
-  ClientOptions,
   EventHandler,
   ToolEndData,
   LLMConfig,
 } from '@librechat/agents';
+import type { BaseMessage, ToolMessage } from '@librechat/agents/langchain/messages';
+import type { DynamicStructuredTool } from '@librechat/agents/langchain/tools';
 import type { ObjectId, MemoryMethods, IUser } from '@librechat/data-schemas';
 import type { TAttachment, MemoryArtifact } from 'librechat-data-provider';
-import type { BaseMessage, ToolMessage } from '@langchain/core/messages';
 import type { Response as ServerResponse } from 'express';
 import { GenerationJobManager } from '~/stream/GenerationJobManager';
 import { resolveHeaders, createSafeUser } from '~/utils';
@@ -32,6 +32,8 @@ type ToolEndMetadata = Record<string, unknown> & {
   thread_id?: string;
 };
 
+type SanitizedMemoryLLMConfig = Omit<Partial<LLMConfig>, 'apiKey'> & { apiKey?: string };
+
 export interface MemoryConfig {
   validKeys?: string[];
   instructions?: string;
@@ -39,6 +41,14 @@ export interface MemoryConfig {
   tokenLimit?: number;
 }
 
+function normalizeMemoryLLMConfig(llmConfig?: Partial<LLMConfig>): SanitizedMemoryLLMConfig {
+  const config = { ...(llmConfig ?? {}) } as Record<string, unknown>;
+  if (typeof config.apiKey !== 'string') {
+    delete config.apiKey;
+  }
+  return config as SanitizedMemoryLLMConfig;
+}
+
 export const memoryInstructions =
   'The system automatically stores important user information and can update or delete memories based on user requests, enabling dynamic memory management.';
 
@@ -88,7 +98,7 @@ export const createMemoryTool = ({
   validKeys?: string[];
   tokenLimit?: number;
   totalTokens?: number;
-}) => {
+}): DynamicStructuredTool => {
   const remainingTokens = tokenLimit ? tokenLimit - totalTokens : Infinity;
   const isOverflowing = tokenLimit ? remainingTokens <= 0 : false;
 
@@ -342,15 +352,15 @@ ${memory ?? 'No existing memories'}`;
       disableStreaming: true,
     };
 
-    const finalLLMConfig: ClientOptions = {
+    const finalLLMConfig = {
       ...defaultLLMConfig,
-      ...llmConfig,
+      ...normalizeMemoryLLMConfig(llmConfig),
       /**
        * Ensure streaming is always disabled for memory processing
        */
       streaming: false,
       disableStreaming: true,
-    };
+    } as LLMConfig;
 
     // Handle GPT-5+ models
     if ('model' in finalLLMConfig && /\bgpt-[5-9](?:\.\d+)?\b/i.test(finalLLMConfig.model ?? '')) {

packages/api/src/agents/run.spec.ts

@@ -1,4 +1,4 @@
-import { ToolMessage, AIMessage, HumanMessage } from '@langchain/core/messages';
+import { ToolMessage, AIMessage, HumanMessage } from '@librechat/agents/langchain/messages';
 import { extractDiscoveredToolsFromHistory } from './run';
 
 describe('extractDiscoveredToolsFromHistory', () => {

packages/api/src/agents/run.ts

@@ -20,13 +20,18 @@ import type {
   IState,
   LCTool,
 } from '@librechat/agents';
-import type { Agent, AgentSubagentsConfig, SummarizationConfig } from 'librechat-data-provider';
-import type { BaseMessage } from '@langchain/core/messages';
+import type {
+  Agent,
+  AgentModelParameters,
+  AgentSubagentsConfig,
+  SummarizationConfig,
+} from 'librechat-data-provider';
+import type { BaseMessage } from '@librechat/agents/langchain/messages';
 import type { AppConfig, IUser } from '@librechat/data-schemas';
 import type * as t from '~/types';
 import { getProviderConfig } from '~/endpoints/config/providers';
-import { getOpenAIConfig } from '~/endpoints/openai/config';
 import { resolveHeaders, createSafeUser } from '~/utils/env';
+import { getOpenAIConfig } from '~/endpoints/openai/config';
 import { isUserProvided } from '~/utils/common';
 
 /** Expected shape of JSON tool search results */
@@ -275,6 +280,31 @@ function isPlainObject(value: unknown): value is Record<string, unknown> {
   return value != null && typeof value === 'object' && !Array.isArray(value);
 }
 
+const nullableAgentModelParameterKeys = [
+  'temperature',
+  'maxContextTokens',
+  'max_context_tokens',
+  'max_output_tokens',
+  'top_p',
+  'frequency_penalty',
+  'presence_penalty',
+] satisfies Array<keyof AgentModelParameters>;
+
+function normalizeAgentModelParameters(
+  modelParameters: AgentModelParameters | undefined,
+): Partial<AgentModelParameters> | undefined {
+  if (!modelParameters) {
+    return undefined;
+  }
+  const normalized: Partial<AgentModelParameters> = { ...modelParameters };
+  for (const key of nullableAgentModelParameterKeys) {
+    if (normalized[key] === null) {
+      delete normalized[key];
+    }
+  }
+  return normalized;
+}
+
 /**
  * Merges user-supplied summarization parameters on top of endpoint-resolved
  * overrides. User params win for top-level keys; `configuration` is
@@ -398,9 +428,11 @@ function resolveSummarizationProvider(
       },
       rawProvider,
     );
-    const clientOverrides: SummarizationClientOverrides = {
-      ...llmConfig,
-    };
+    const { apiKey: resolvedApiKey, ...llmConfigOverrides } = llmConfig;
+    const clientOverrides: SummarizationClientOverrides = { ...llmConfigOverrides };
+    if (typeof resolvedApiKey === 'string') {
+      clientOverrides.apiKey = resolvedApiKey;
+    }
     if (configOptions) {
       clientOverrides.configuration = configOptions;
     }
@@ -718,14 +750,15 @@ export async function createRun({
       { user, requestBody },
     );
 
-    const llmConfig: t.RunLLMConfig = Object.assign(
+    const modelParameters = normalizeAgentModelParameters(agent.model_parameters);
+    const llmConfig = Object.assign(
       {
         provider,
         streaming,
         streamUsage,
       },
-      agent.model_parameters,
-    );
+      modelParameters,
+    ) as t.RunLLMConfig;
 
     const joinInstructionMap = (map?: Record<string, unknown>) =>
       Object.values(map ?? {})

packages/api/src/agents/skills.ts

@@ -1,9 +1,9 @@
 import { logger } from '@librechat/data-schemas';
-import { HumanMessage } from '@langchain/core/messages';
 import { isEphemeralAgentId } from 'librechat-data-provider';
+import { HumanMessage } from '@librechat/agents/langchain/messages';
 import { formatSkillCatalog, SkillToolDefinition } from '@librechat/agents';
 import type { LCToolRegistry, LCTool, InjectedMessage } from '@librechat/agents';
-import type { BaseMessage } from '@langchain/core/messages';
+import type { BaseMessage } from '@librechat/agents/langchain/messages';
 import type { Agent } from 'librechat-data-provider';
 import type { Types } from 'mongoose';
 import type { InitializeAgentDbMethods } from './initialize';

packages/api/src/endpoints/anthropic/llm.ts

@@ -138,7 +138,7 @@ function getLLMConfig(
   let requestOptions: AnthropicClientOptions & { stream?: boolean } = {
     model: mergedOptions.model,
     stream: mergedOptions.stream,
-    temperature: mergedOptions.temperature,
+    temperature: mergedOptions.temperature ?? undefined,
     stopSequences: mergedOptions.stop,
     maxTokens:
       mergedOptions.maxOutputTokens || anthropicSettings.maxOutputTokens.reset(mergedOptions.model),

packages/api/src/endpoints/google/llm.spec.ts

@@ -384,7 +384,7 @@ describe('getGoogleConfig', () => {
       expect(result.llmConfig).toHaveProperty('thinkingConfig');
       expect((result.llmConfig as Record<string, unknown>).thinkingConfig).toMatchObject({
         includeThoughts: true,
-        thinkingLevel: ThinkingLevel.high,
+        thinkingLevel: 'HIGH',
       });
       expect((result.llmConfig as Record<string, unknown>).thinkingConfig).not.toHaveProperty(
         'thinkingBudget',
@@ -406,7 +406,26 @@ describe('getGoogleConfig', () => {
 
       expect((result.llmConfig as Record<string, unknown>).thinkingConfig).toMatchObject({
         includeThoughts: true,
-        thinkingLevel: ThinkingLevel.medium,
+        thinkingLevel: 'MEDIUM',
+      });
+    });
+
+    it('should preserve minimal thinkingLevel for Gemini 3 Flash models', () => {
+      const credentials = {
+        [AuthKeys.GOOGLE_API_KEY]: 'test-api-key',
+      };
+
+      const result = getGoogleConfig(credentials, {
+        modelOptions: {
+          model: 'gemini-3-flash-preview',
+          thinking: true,
+          thinkingLevel: ThinkingLevel.minimal,
+        },
+      });
+
+      expect((result.llmConfig as Record<string, unknown>).thinkingConfig).toMatchObject({
+        includeThoughts: true,
+        thinkingLevel: 'MINIMAL',
       });
     });
 
@@ -466,7 +485,7 @@ describe('getGoogleConfig', () => {
       expect(result.provider).toBe(Providers.VERTEXAI);
       expect((result.llmConfig as Record<string, unknown>).thinkingConfig).toMatchObject({
         includeThoughts: true,
-        thinkingLevel: ThinkingLevel.low,
+        thinkingLevel: 'LOW',
       });
       expect(result.llmConfig).toHaveProperty('includeThoughts', true);
     });

packages/api/src/endpoints/google/llm.ts

@@ -1,10 +1,24 @@
 import { Providers } from '@librechat/agents';
 import { googleSettings, AuthKeys, removeNullishValues } from 'librechat-data-provider';
 import type { GoogleClientOptions, VertexAIClientOptions } from '@librechat/agents';
-import type { GoogleAIToolType } from '@langchain/google-common';
+import type { GoogleAIToolType } from '@librechat/agents/langchain/google-common';
 import type * as t from '~/types';
 import { isEnabled } from '~/utils';
 
+type GoogleThinkingLevel = 'THINKING_LEVEL_UNSPECIFIED' | 'MINIMAL' | 'LOW' | 'MEDIUM' | 'HIGH';
+type GoogleThinkingConfig = {
+  includeThoughts: boolean;
+  thinkingLevel?: GoogleThinkingLevel;
+};
+
+const googleThinkingLevels = new Set<GoogleThinkingLevel>([
+  'THINKING_LEVEL_UNSPECIFIED',
+  'MINIMAL',
+  'LOW',
+  'MEDIUM',
+  'HIGH',
+]);
+
 /** Known Google/Vertex AI parameters that map directly to the client config */
 export const knownGoogleParams = new Set([
   'model',
@@ -70,6 +84,17 @@ function getThresholdMapping(model: string) {
   return (value: string) => value;
 }
 
+function normalizeGoogleThinkingLevel(value: unknown): GoogleThinkingLevel | undefined {
+  if (typeof value !== 'string') {
+    return undefined;
+  }
+  const normalized = value.toUpperCase() as GoogleThinkingLevel;
+  if (!googleThinkingLevels.has(normalized)) {
+    return undefined;
+  }
+  return normalized;
+}
+
 export function getSafetySettings(
   model?: string,
 ): Array<{ category: string; threshold: string }> | undefined {
@@ -206,22 +231,23 @@ export function getGoogleConfig(
    * with `includeThoughts: true`. The `thinkingBudget` param is ignored for Gemini 3+.
    *
    * For Vertex AI, top-level `includeThoughts` is still required because
-   * `@langchain/google-common`'s `formatGenerationConfig` reads it separately
+   * `@librechat/agents/langchain/google-common`'s `formatGenerationConfig` reads it separately
    * from `thinkingConfig` — they serve different purposes in the request pipeline.
    */
   const isGemini3Plus = /gemini-([3-9]|\d{2,})/i.test(modelName);
 
   if (isGemini3Plus && thinking) {
-    const thinkingConfig: { includeThoughts: boolean; thinkingLevel?: string } = {
+    const thinkingConfig: GoogleThinkingConfig = {
       includeThoughts: true,
     };
-    if (thinkingLevel) {
-      thinkingConfig.thinkingLevel = thinkingLevel as string;
+    const normalizedThinkingLevel = normalizeGoogleThinkingLevel(thinkingLevel);
+    if (normalizedThinkingLevel) {
+      thinkingConfig.thinkingLevel = normalizedThinkingLevel;
     }
     if (provider === Providers.GOOGLE) {
-      (llmConfig as GoogleClientOptions).thinkingConfig = thinkingConfig;
+      (llmConfig as { thinkingConfig?: GoogleThinkingConfig }).thinkingConfig = thinkingConfig;
     } else if (provider === Providers.VERTEXAI) {
-      (llmConfig as Record<string, unknown>).thinkingConfig = thinkingConfig;
+      (llmConfig as { thinkingConfig?: GoogleThinkingConfig }).thinkingConfig = thinkingConfig;
       (llmConfig as VertexAIClientOptions).includeThoughts = true;
     }
   } else if (!isGemini3Plus) {

packages/api/src/endpoints/openai/llm.ts

@@ -1,7 +1,7 @@
 import { EModelEndpoint, removeNullishValues } from 'librechat-data-provider';
-import type { BindToolsInput } from '@langchain/core/language_models/chat_models';
+import type { BindToolsInput } from '@librechat/agents/langchain/language_models/chat_models';
+import type { AzureOpenAIInput } from '@librechat/agents/langchain/openai';
 import type { SettingDefinition } from 'librechat-data-provider';
-import type { AzureOpenAIInput } from '@langchain/openai';
 import type { OpenAI } from 'openai';
 import type * as t from '~/types';
 import { sanitizeModelName, constructAzureURL } from '~/utils/azure';

packages/api/src/endpoints/openai/transform.ts

@@ -1,5 +1,5 @@
 import { EModelEndpoint } from 'librechat-data-provider';
-import type { GoogleAIToolType } from '@langchain/google-common';
+import type { GoogleAIToolType } from '@librechat/agents/langchain/google-common';
 import type { ClientOptions } from '@librechat/agents';
 import type * as t from '~/types';
 import { knownOpenAIParams } from './llm';

packages/api/src/types/es2024-string.d.ts

@@ -1,3 +1,5 @@
+/// <reference types="jest" />
+
 /** String.prototype.isWellFormed — ES2024 API, available in Node 20+ but absent from TS 5.3 lib */
 interface String {
   isWellFormed(): boolean;

packages/api/src/types/openai.ts

@@ -1,8 +1,8 @@
 import { z } from 'zod';
 import { openAISchema } from 'librechat-data-provider';
-import type { TConfig } from 'librechat-data-provider';
+import type { BindToolsInput } from '@librechat/agents/langchain/language_models/chat_models';
 import type { OpenAIClientOptions, Providers } from '@librechat/agents';
-import type { BindToolsInput } from '@langchain/core/language_models/chat_models';
+import type { TConfig } from 'librechat-data-provider';
 import type { AzureOptions } from './azure';
 
 export type OpenAIParameters = z.infer<typeof openAISchema>;

packages/api/src/utils/content.spec.ts

@@ -1,6 +1,6 @@
 import { ContentTypes, ToolCallTypes } from 'librechat-data-provider';
 import type { Agents, PartMetadata, TMessageContentParts } from 'librechat-data-provider';
-import type { ToolCall } from '@langchain/core/messages/tool';
+import type { ToolCall } from '@librechat/agents/langchain/messages/tool';
 import { filterMalformedContentParts } from './content';
 
 describe('filterMalformedContentParts', () => {

packages/api/src/utils/tokenMap.ts

@@ -1,4 +1,4 @@
-import type { BaseMessage } from '@langchain/core/messages';
+import type { BaseMessage } from '@librechat/agents/langchain/messages';
 
 /** Signature for a function that counts tokens in a LangChain message. */
 export type TokenCounter = (message: BaseMessage) => number;