🚀 fix: Resolve Google Client Issues, CDN Screenshots, Update Models (#5703)

* 🤖 refactor: streamline model selection logic for title model in GoogleClient

* refactor: add options for empty object schemas in convertJsonSchemaToZod

* refactor: add utility function to check for empty object schemas in convertJsonSchemaToZod

* fix: Google MCP Tool errors, and remove Object Unescaping as Google fixed this

* fix: google safetySettings

* feat: add safety settings exclusion via GOOGLE_EXCLUDE_SAFETY_SETTINGS environment variable

* fix: rename environment variable for console JSON string length

* fix: disable portal for dropdown in ExportModal component

* fix: screenshot functionality to use image placeholder for remote images

* feat: add visionMode property to BaseClient and initialize in GoogleClient to fix resendFiles issue

* fix: enhance formatMessages to include image URLs in message content for Vertex AI

* fix: safety settings for titleChatCompletion

* fix: remove deprecated model assignment in GoogleClient and streamline title model retrieval

* fix: remove unused image preloading logic in ScreenshotContext

* chore: update default google models to latest models shared by vertex ai and gen ai

* refactor: enhance Google error messaging

* fix: update token values and model limits for Gemini models

* ci: fix model matching

* chore: bump version of librechat-data-provider to 0.7.699

api/server/services/Endpoints/google/llm.js

@@ -1,18 +1,42 @@
 const { Providers } = require('@librechat/agents');
 const { AuthKeys } = require('librechat-data-provider');
+const { isEnabled } = require('~/server/utils');
+
+function getThresholdMapping(model) {
+  const gemini1Pattern = /gemini-(1\.0|1\.5|pro$|1\.0-pro|1\.5-pro|1\.5-flash-001)/;
+  const restrictedPattern = /(gemini-(1\.5-flash-8b|2\.0|exp)|learnlm)/;
+
+  if (gemini1Pattern.test(model)) {
+    return (value) => {
+      if (value === 'OFF') {
+        return 'BLOCK_NONE';
+      }
+      return value;
+    };
+  }
+
+  if (restrictedPattern.test(model)) {
+    return (value) => {
+      if (value === 'OFF' || value === 'HARM_BLOCK_THRESHOLD_UNSPECIFIED') {
+        return 'BLOCK_NONE';
+      }
+      return value;
+    };
+  }
+
+  return (value) => value;
+}
 
 /**
  *
- * @param {boolean} isGemini2
- * @returns {Array<{category: string, threshold: string}>}
+ * @param {string} model
+ * @returns {Array<{category: string, threshold: string}> | undefined}
  */
-function getSafetySettings(isGemini2) {
-  const mapThreshold = (value) => {
-    if (isGemini2 && value === 'BLOCK_NONE') {
-      return 'OFF';
-    }
-    return value;
-  };
+function getSafetySettings(model) {
+  if (isEnabled(process.env.GOOGLE_EXCLUDE_SAFETY_SETTINGS)) {
+    return undefined;
+  }
+  const mapThreshold = getThresholdMapping(model);
 
   return [
     {
@@ -85,8 +109,7 @@ function getLLMConfig(credentials, options = {}) {
   };
 
   /** Used only for Safety Settings */
-  const isGemini2 = llmConfig.model.includes('gemini-2.0') && !llmConfig.model.includes('thinking');
-  llmConfig.safetySettings = getSafetySettings(isGemini2);
+  llmConfig.safetySettings = getSafetySettings(llmConfig.model);
 
   let provider;
 
@@ -153,4 +176,5 @@ function getLLMConfig(credentials, options = {}) {
 
 module.exports = {
   getLLMConfig,
+  getSafetySettings,
 };

api/server/services/Endpoints/google/title.js

@@ -1,9 +1,8 @@
-const { CacheKeys, Constants } = require('librechat-data-provider');
+const { EModelEndpoint, CacheKeys, Constants, googleSettings } = require('librechat-data-provider');
 const getLogStores = require('~/cache/getLogStores');
+const initializeClient = require('./initialize');
 const { isEnabled } = require('~/server/utils');
 const { saveConvo } = require('~/models');
-const { logger } = require('~/config');
-const initializeClient = require('./initialize');
 
 const addTitle = async (req, { text, response, client }) => {
   const { TITLE_CONVO = 'true' } = process.env ?? {};
@@ -14,22 +13,16 @@ const addTitle = async (req, { text, response, client }) => {
   if (client.options.titleConvo === false) {
     return;
   }
-
-  const DEFAULT_TITLE_MODEL = 'gemini-pro';
   const { GOOGLE_TITLE_MODEL } = process.env ?? {};
-
-  let model = GOOGLE_TITLE_MODEL ?? DEFAULT_TITLE_MODEL;
+  const providerConfig = req.app.locals[EModelEndpoint.google];
+  let model =
+    providerConfig?.titleModel ??
+    GOOGLE_TITLE_MODEL ??
+    client.options?.modelOptions.model ??
+    googleSettings.model.default;
 
   if (GOOGLE_TITLE_MODEL === Constants.CURRENT_MODEL) {
     model = client.options?.modelOptions.model;
-
-    if (client.isVisionModel) {
-      logger.warn(
-        `current_model was specified for Google title request, but the model ${model} cannot process a text-only conversation. Falling back to ${DEFAULT_TITLE_MODEL}`,
-      );
-
-      model = DEFAULT_TITLE_MODEL;
-    }
   }
 
   const titleEndpointOptions = {

api/server/services/MCP.js

@@ -1,9 +1,11 @@
+const { z } = require('zod');
 const { tool } = require('@langchain/core/tools');
-const { Constants: AgentConstants } = require('@librechat/agents');
+const { Constants: AgentConstants, Providers } = require('@librechat/agents');
 const {
   Constants,
-  convertJsonSchemaToZod,
+  ContentTypes,
   isAssistantsEndpoint,
+  convertJsonSchemaToZod,
 } = require('librechat-data-provider');
 const { logger, getMCPManager } = require('~/config');
 
@@ -25,7 +27,15 @@ async function createMCPTool({ req, toolKey, provider }) {
   }
   /** @type {LCTool} */
   const { description, parameters } = toolDefinition;
-  const schema = convertJsonSchemaToZod(parameters);
+  const isGoogle = provider === Providers.VERTEXAI || provider === Providers.GOOGLE;
+  let schema = convertJsonSchemaToZod(parameters, {
+    allowEmptyObject: !isGoogle,
+  });
+
+  if (!schema) {
+    schema = z.object({ input: z.string().optional() });
+  }
+
   const [toolName, serverName] = toolKey.split(Constants.mcp_delimiter);
   /** @type {(toolInput: Object | string) => Promise<unknown>} */
   const _call = async (toolInput) => {
@@ -35,6 +45,9 @@ async function createMCPTool({ req, toolKey, provider }) {
       if (isAssistantsEndpoint(provider) && Array.isArray(result)) {
         return result[0];
       }
+      if (isGoogle && Array.isArray(result[0]) && result[0][0]?.type === ContentTypes.TEXT) {
+        return [result[0][0].text, result[1]];
+      }
       return result;
     } catch (error) {
       logger.error(`${toolName} MCP server tool call failed`, error);