increment Agent node version

packages/components/models.json

@@ -647,6 +647,12 @@
                     "input_cost": 0.00002,
                     "output_cost": 0.00012
                 },
+                {
+                    "label": "gemini-3-pro-image-preview",
+                    "name": "gemini-3-pro-image-preview",
+                    "input_cost": 0.00002,
+                    "output_cost": 0.00012
+                },
                 {
                     "label": "gemini-2.5-pro",
                     "name": "gemini-2.5-pro",
@@ -659,6 +665,12 @@
                     "input_cost": 1.25e-6,
                     "output_cost": 0.00001
                 },
+                {
+                    "label": "gemini-2.5-flash-image",
+                    "name": "gemini-2.5-flash-image",
+                    "input_cost": 1.25e-6,
+                    "output_cost": 0.00001
+                },
                 {
                     "label": "gemini-2.5-flash-lite",
                     "name": "gemini-2.5-flash-lite",

packages/components/nodes/agentflow/Agent/Agent.ts

@@ -22,21 +22,16 @@ import zodToJsonSchema from 'zod-to-json-schema'
 import { getErrorMessage } from '../../../src/error'
 import { DataSource } from 'typeorm'
 import {
+    addImageArtifactsToMessages,
+    extractArtifactsFromResponse,
     getPastChatHistoryImageMessages,
     getUniqueImageMessages,
     processMessagesWithImages,
     replaceBase64ImagesWithFileReferences,
+    replaceInlineDataWithFileReferences,
     updateFlowState
 } from '../utils'
-import {
+import { convertMultiOptionsToStringArray, processTemplateVariables, configureStructuredOutput } from '../../../src/utils'
-    convertMultiOptionsToStringArray,
-    getCredentialData,
-    getCredentialParam,
-    processTemplateVariables,
-    configureStructuredOutput
-} from '../../../src/utils'
-import { addSingleFileToStorage } from '../../../src/storageUtils'
-import fetch from 'node-fetch'
 
 interface ITool {
     agentSelectedTool: string
@@ -87,7 +82,7 @@ class Agent_Agentflow implements INode {
     constructor() {
         this.label = 'Agent'
         this.name = 'agentAgentflow'
-        this.version = 2.2
+        this.version = 3.0
         this.type = 'Agent'
         this.category = 'Agent Flows'
         this.description = 'Dynamically choose and utilize tools during runtime, enabling multi-step reasoning'
@@ -1072,12 +1067,6 @@ class Agent_Agentflow implements INode {
                 llmIds = await analyticHandlers.onLLMStart(llmLabel, messages, options.parentTraceIds)
             }
 
-            // Track execution time
-            const startTime = Date.now()
-
-            // Get initial response from LLM
-            const sseStreamer: IServerSideEventStreamer | undefined = options.sseStreamer
-
             // Handle tool calls with support for recursion
             let usedTools: IUsedTool[] = []
             let sourceDocuments: Array<any> = []
@@ -1090,12 +1079,24 @@ class Agent_Agentflow implements INode {
             const messagesBeforeToolCalls = [...messages]
             let _toolCallMessages: BaseMessageLike[] = []
 
+            /**
+             * Add image artifacts from previous assistant responses as user messages
+             * Images are converted from FILE-STORAGE::<image_path> to base 64 image_url format
+             */
+            await addImageArtifactsToMessages(messages, options)
+
             // Check if this is hummanInput for tool calls
             const _humanInput = nodeData.inputs?.humanInput
             const humanInput: IHumanInput = typeof _humanInput === 'string' ? JSON.parse(_humanInput) : _humanInput
             const humanInputAction = options.humanInputAction
             const iterationContext = options.iterationContext
 
+            // Track execution time
+            const startTime = Date.now()
+
+            // Get initial response from LLM
+            const sseStreamer: IServerSideEventStreamer | undefined = options.sseStreamer
+
             if (humanInput) {
                 if (humanInput.type !== 'proceed' && humanInput.type !== 'reject') {
                     throw new Error(`Invalid human input type. Expected 'proceed' or 'reject', but got '${humanInput.type}'`)
@@ -1234,9 +1235,15 @@ class Agent_Agentflow implements INode {
             // Prepare final response and output object
             let finalResponse = ''
             if (response.content && Array.isArray(response.content)) {
-                finalResponse = response.content.map((item: any) => item.text).join('\n')
+                finalResponse = response.content
+                    .filter((item: any) => item.text)
+                    .map((item: any) => item.text)
+                    .join('\n')
             } else if (response.content && typeof response.content === 'string') {
                 finalResponse = response.content
+            } else if (response.content === '') {
+                // Empty response content, this could happen when there is only image data
+                finalResponse = ''
             } else {
                 finalResponse = JSON.stringify(response, null, 2)
             }
@@ -1252,10 +1259,13 @@ class Agent_Agentflow implements INode {
                 }
             }
 
-            // Extract artifacts from annotations in response metadata
+            // Extract artifacts from annotations in response metadata and replace inline data
             if (response.response_metadata) {
-                const { artifacts: extractedArtifacts, fileAnnotations: extractedFileAnnotations } =
+                const {
-                    await this.extractArtifactsFromResponse(response.response_metadata, newNodeData, options)
+                    artifacts: extractedArtifacts,
+                    fileAnnotations: extractedFileAnnotations,
+                    savedInlineImages
+                } = await extractArtifactsFromResponse(response.response_metadata, newNodeData, options)
                 if (extractedArtifacts.length > 0) {
                     artifacts = [...artifacts, ...extractedArtifacts]
 
@@ -1273,6 +1283,11 @@ class Agent_Agentflow implements INode {
                         sseStreamer.streamFileAnnotationsEvent(chatId, fileAnnotations)
                     }
                 }
+
+                // Replace inlineData base64 with file references in the response
+                if (savedInlineImages && savedInlineImages.length > 0) {
+                    replaceInlineDataWithFileReferences(response, savedInlineImages)
+                }
             }
 
             // Replace sandbox links with proper download URLs. Example: [Download the script](sandbox:/mnt/data/dummy_bar_graph.py)
@@ -1331,9 +1346,15 @@ class Agent_Agentflow implements INode {
             // Process template variables in state
             newState = processTemplateVariables(newState, finalResponse)
 
+            /**
+             * Remove the temporarily added image artifact messages before storing
+             * This is to avoid storing the actual base64 data into database
+             */
+            const messagesToStore = messages.filter((msg: any) => !msg._isTemporaryImageMessage)
+
             // Replace the actual messages array with one that includes the file references for images instead of base64 data
             const messagesWithFileReferences = replaceBase64ImagesWithFileReferences(
-                messages,
+                messagesToStore,
                 runtimeImageMessagesWithFileRef,
                 pastImageMessagesWithFileRef
             )
@@ -1500,44 +1521,6 @@ class Agent_Agentflow implements INode {
         return builtInUsedTools
     }
 
-    /**
-     * Saves base64 image data to storage and returns file information
-     */
-    private async saveBase64Image(
-        outputItem: any,
-        options: ICommonObject
-    ): Promise<{ filePath: string; fileName: string; totalSize: number } | null> {
-        try {
-            if (!outputItem.result) {
-                return null
-            }
-
-            // Extract base64 data and create buffer
-            const base64Data = outputItem.result
-            const imageBuffer = Buffer.from(base64Data, 'base64')
-
-            // Determine file extension and MIME type
-            const outputFormat = outputItem.output_format || 'png'
-            const fileName = `generated_image_${outputItem.id || Date.now()}.${outputFormat}`
-            const mimeType = outputFormat === 'png' ? 'image/png' : 'image/jpeg'
-
-            // Save the image using the existing storage utility
-            const { path, totalSize } = await addSingleFileToStorage(
-                mimeType,
-                imageBuffer,
-                fileName,
-                options.orgId,
-                options.chatflowid,
-                options.chatId
-            )
-
-            return { filePath: path, fileName, totalSize }
-        } catch (error) {
-            console.error('Error saving base64 image:', error)
-            return null
-        }
-    }
-
     /**
      * Handles memory management based on the specified memory type
      */
@@ -2484,190 +2467,6 @@ class Agent_Agentflow implements INode {
         return { response: newResponse, usedTools, sourceDocuments, artifacts, totalTokens, isWaitingForHumanInput }
     }
 
-    /**
-     * Extracts artifacts from response metadata (both annotations and built-in tools)
-     */
-    private async extractArtifactsFromResponse(
-        responseMetadata: any,
-        modelNodeData: INodeData,
-        options: ICommonObject
-    ): Promise<{ artifacts: any[]; fileAnnotations: any[] }> {
-        const artifacts: any[] = []
-        const fileAnnotations: any[] = []
-
-        if (!responseMetadata?.output || !Array.isArray(responseMetadata.output)) {
-            return { artifacts, fileAnnotations }
-        }
-
-        for (const outputItem of responseMetadata.output) {
-            // Handle container file citations from annotations
-            if (outputItem.type === 'message' && outputItem.content && Array.isArray(outputItem.content)) {
-                for (const contentItem of outputItem.content) {
-                    if (contentItem.annotations && Array.isArray(contentItem.annotations)) {
-                        for (const annotation of contentItem.annotations) {
-                            if (annotation.type === 'container_file_citation' && annotation.file_id && annotation.filename) {
-                                try {
-                                    // Download and store the file content
-                                    const downloadResult = await this.downloadContainerFile(
-                                        annotation.container_id,
-                                        annotation.file_id,
-                                        annotation.filename,
-                                        modelNodeData,
-                                        options
-                                    )
-
-                                    if (downloadResult) {
-                                        const fileType = this.getArtifactTypeFromFilename(annotation.filename)
-
-                                        if (fileType === 'png' || fileType === 'jpeg' || fileType === 'jpg') {
-                                            const artifact = {
-                                                type: fileType,
-                                                data: downloadResult.filePath
-                                            }
-
-                                            artifacts.push(artifact)
-                                        } else {
-                                            fileAnnotations.push({
-                                                filePath: downloadResult.filePath,
-                                                fileName: annotation.filename
-                                            })
-                                        }
-                                    }
-                                } catch (error) {
-                                    console.error('Error processing annotation:', error)
-                                }
-                            }
-                        }
-                    }
-                }
-            }
-
-            // Handle built-in tool artifacts (like image generation)
-            if (outputItem.type === 'image_generation_call' && outputItem.result) {
-                try {
-                    const savedImageResult = await this.saveBase64Image(outputItem, options)
-                    if (savedImageResult) {
-                        // Replace the base64 result with the file path in the response metadata
-                        outputItem.result = savedImageResult.filePath
-
-                        // Create artifact in the same format as other image artifacts
-                        const fileType = this.getArtifactTypeFromFilename(savedImageResult.fileName)
-                        artifacts.push({
-                            type: fileType,
-                            data: savedImageResult.filePath
-                        })
-                    }
-                } catch (error) {
-                    console.error('Error processing image generation artifact:', error)
-                }
-            }
-        }
-
-        return { artifacts, fileAnnotations }
-    }
-
-    /**
-     * Downloads file content from container file citation
-     */
-    private async downloadContainerFile(
-        containerId: string,
-        fileId: string,
-        filename: string,
-        modelNodeData: INodeData,
-        options: ICommonObject
-    ): Promise<{ filePath: string; totalSize: number } | null> {
-        try {
-            const credentialData = await getCredentialData(modelNodeData.credential ?? '', options)
-            const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, modelNodeData)
-
-            if (!openAIApiKey) {
-                console.warn('No OpenAI API key available for downloading container file')
-                return null
-            }
-
-            // Download the file using OpenAI Container API
-            const response = await fetch(`https://api.openai.com/v1/containers/${containerId}/files/${fileId}/content`, {
-                method: 'GET',
-                headers: {
-                    Accept: '*/*',
-                    Authorization: `Bearer ${openAIApiKey}`
-                }
-            })
-
-            if (!response.ok) {
-                console.warn(
-                    `Failed to download container file ${fileId} from container ${containerId}: ${response.status} ${response.statusText}`
-                )
-                return null
-            }
-
-            // Extract the binary data from the Response object
-            const data = await response.arrayBuffer()
-            const dataBuffer = Buffer.from(data)
-            const mimeType = this.getMimeTypeFromFilename(filename)
-
-            // Store the file using the same storage utility as OpenAIAssistant
-            const { path, totalSize } = await addSingleFileToStorage(
-                mimeType,
-                dataBuffer,
-                filename,
-                options.orgId,
-                options.chatflowid,
-                options.chatId
-            )
-
-            return { filePath: path, totalSize }
-        } catch (error) {
-            console.error('Error downloading container file:', error)
-            return null
-        }
-    }
-
-    /**
-     * Gets MIME type from filename extension
-     */
-    private getMimeTypeFromFilename(filename: string): string {
-        const extension = filename.toLowerCase().split('.').pop()
-        const mimeTypes: { [key: string]: string } = {
-            png: 'image/png',
-            jpg: 'image/jpeg',
-            jpeg: 'image/jpeg',
-            gif: 'image/gif',
-            pdf: 'application/pdf',
-            txt: 'text/plain',
-            csv: 'text/csv',
-            json: 'application/json',
-            html: 'text/html',
-            xml: 'application/xml'
-        }
-        return mimeTypes[extension || ''] || 'application/octet-stream'
-    }
-
-    /**
-     * Gets artifact type from filename extension for UI rendering
-     */
-    private getArtifactTypeFromFilename(filename: string): string {
-        const extension = filename.toLowerCase().split('.').pop()
-        const artifactTypes: { [key: string]: string } = {
-            png: 'png',
-            jpg: 'jpeg',
-            jpeg: 'jpeg',
-            html: 'html',
-            htm: 'html',
-            md: 'markdown',
-            markdown: 'markdown',
-            json: 'json',
-            js: 'javascript',
-            javascript: 'javascript',
-            tex: 'latex',
-            latex: 'latex',
-            txt: 'text',
-            csv: 'text',
-            pdf: 'text'
-        }
-        return artifactTypes[extension || ''] || 'text'
-    }
-
     /**
      * Processes sandbox links in the response text and converts them to file annotations
      */

packages/components/nodes/agentflow/LLM/LLM.ts

@@ -5,10 +5,13 @@ import { DEFAULT_SUMMARIZER_TEMPLATE } from '../prompt'
 import { AnalyticHandler } from '../../../src/handler'
 import { ILLMMessage } from '../Interface.Agentflow'
 import {
+    addImageArtifactsToMessages,
+    extractArtifactsFromResponse,
     getPastChatHistoryImageMessages,
     getUniqueImageMessages,
     processMessagesWithImages,
     replaceBase64ImagesWithFileReferences,
+    replaceInlineDataWithFileReferences,
     updateFlowState
 } from '../utils'
 import { processTemplateVariables, configureStructuredOutput } from '../../../src/utils'
@@ -448,6 +451,12 @@ class LLM_Agentflow implements INode {
             }
             delete nodeData.inputs?.llmMessages
 
+            /**
+             * Add image artifacts from previous assistant responses as user messages
+             * Images are converted from FILE-STORAGE::<image_path> to base 64 image_url format
+             */
+            await addImageArtifactsToMessages(messages, options)
+
             // Configure structured output if specified
             const isStructuredOutput = _llmStructuredOutput && Array.isArray(_llmStructuredOutput) && _llmStructuredOutput.length > 0
             if (isStructuredOutput) {
@@ -467,9 +476,11 @@ class LLM_Agentflow implements INode {
 
             // Track execution time
             const startTime = Date.now()
-
             const sseStreamer: IServerSideEventStreamer | undefined = options.sseStreamer
 
+            /*
+             * Invoke LLM
+             */
             if (isStreamable) {
                 response = await this.handleStreamingResponse(sseStreamer, llmNodeInstance, messages, chatId, abortController)
             } else {
@@ -494,6 +505,40 @@ class LLM_Agentflow implements INode {
             const endTime = Date.now()
             const timeDelta = endTime - startTime
 
+            // Extract artifacts and file annotations from response metadata
+            let artifacts: any[] = []
+            let fileAnnotations: any[] = []
+            if (response.response_metadata) {
+                const {
+                    artifacts: extractedArtifacts,
+                    fileAnnotations: extractedFileAnnotations,
+                    savedInlineImages
+                } = await extractArtifactsFromResponse(response.response_metadata, newNodeData, options)
+
+                if (extractedArtifacts.length > 0) {
+                    artifacts = extractedArtifacts
+
+                    // Stream artifacts if this is the last node
+                    if (isLastNode && sseStreamer) {
+                        sseStreamer.streamArtifactsEvent(chatId, artifacts)
+                    }
+                }
+
+                if (extractedFileAnnotations.length > 0) {
+                    fileAnnotations = extractedFileAnnotations
+
+                    // Stream file annotations if this is the last node
+                    if (isLastNode && sseStreamer) {
+                        sseStreamer.streamFileAnnotationsEvent(chatId, fileAnnotations)
+                    }
+                }
+
+                // Replace inlineData base64 with file references in the response
+                if (savedInlineImages && savedInlineImages.length > 0) {
+                    replaceInlineDataWithFileReferences(response, savedInlineImages)
+                }
+            }
+
             // Update flow state if needed
             let newState = { ...state }
             if (_llmUpdateState && Array.isArray(_llmUpdateState) && _llmUpdateState.length > 0) {
@@ -513,10 +558,22 @@ class LLM_Agentflow implements INode {
                 finalResponse = response.content.map((item: any) => item.text).join('\n')
             } else if (response.content && typeof response.content === 'string') {
                 finalResponse = response.content
+            } else if (response.content === '') {
+                // Empty response content, this could happen when there is only image data
+                finalResponse = ''
             } else {
                 finalResponse = JSON.stringify(response, null, 2)
             }
-            const output = this.prepareOutputObject(response, finalResponse, startTime, endTime, timeDelta, isStructuredOutput)
+            const output = this.prepareOutputObject(
+                response,
+                finalResponse,
+                startTime,
+                endTime,
+                timeDelta,
+                isStructuredOutput,
+                artifacts,
+                fileAnnotations
+            )
 
             // End analytics tracking
             if (analyticHandlers && llmIds) {
@@ -528,12 +585,23 @@ class LLM_Agentflow implements INode {
                 this.sendStreamingEvents(options, chatId, response)
             }
 
+            // Stream file annotations if any were extracted
+            if (fileAnnotations.length > 0 && isLastNode && sseStreamer) {
+                sseStreamer.streamFileAnnotationsEvent(chatId, fileAnnotations)
+            }
+
             // Process template variables in state
             newState = processTemplateVariables(newState, finalResponse)
 
+            /**
+             * Remove the temporarily added image artifact messages before storing
+             * This is to avoid storing the actual base64 data into database
+             */
+            const messagesToStore = messages.filter((msg: any) => !msg._isTemporaryImageMessage)
+
             // Replace the actual messages array with one that includes the file references for images instead of base64 data
             const messagesWithFileReferences = replaceBase64ImagesWithFileReferences(
-                messages,
+                messagesToStore,
                 runtimeImageMessagesWithFileRef,
                 pastImageMessagesWithFileRef
             )
@@ -584,7 +652,13 @@ class LLM_Agentflow implements INode {
                     {
                         role: returnRole,
                         content: finalResponse,
-                        name: nodeData?.label ? nodeData?.label.toLowerCase().replace(/\s/g, '_').trim() : nodeData?.id
+                        name: nodeData?.label ? nodeData?.label.toLowerCase().replace(/\s/g, '_').trim() : nodeData?.id,
+                        ...(((artifacts && artifacts.length > 0) || (fileAnnotations && fileAnnotations.length > 0)) && {
+                            additional_kwargs: {
+                                ...(artifacts && artifacts.length > 0 && { artifacts }),
+                                ...(fileAnnotations && fileAnnotations.length > 0 && { fileAnnotations })
+                            }
+                        })
                     }
                 ]
             }
@@ -805,7 +879,9 @@ class LLM_Agentflow implements INode {
         startTime: number,
         endTime: number,
         timeDelta: number,
-        isStructuredOutput: boolean
+        isStructuredOutput: boolean,
+        artifacts: any[] = [],
+        fileAnnotations: any[] = []
     ): any {
         const output: any = {
             content: finalResponse,
@@ -824,6 +900,10 @@ class LLM_Agentflow implements INode {
             output.usageMetadata = response.usage_metadata
         }
 
+        if (response.response_metadata) {
+            output.responseMetadata = response.response_metadata
+        }
+
         if (isStructuredOutput && typeof response === 'object') {
             const structuredOutput = response as Record<string, any>
             for (const key in structuredOutput) {
@@ -833,6 +913,14 @@ class LLM_Agentflow implements INode {
             }
         }
 
+        if (artifacts && artifacts.length > 0) {
+            output.artifacts = flatten(artifacts)
+        }
+
+        if (fileAnnotations && fileAnnotations.length > 0) {
+            output.fileAnnotations = fileAnnotations
+        }
+
         return output
     }
 

packages/components/nodes/agentflow/utils.ts

@@ -1,10 +1,11 @@
-import { BaseMessage, MessageContentImageUrl } from '@langchain/core/messages'
+import { BaseMessage, MessageContentImageUrl, AIMessageChunk } from '@langchain/core/messages'
 import { getImageUploads } from '../../src/multiModalUtils'
-import { getFileFromStorage } from '../../src/storageUtils'
+import { addSingleFileToStorage, getFileFromStorage } from '../../src/storageUtils'
-import { ICommonObject, IFileUpload } from '../../src/Interface'
+import { ICommonObject, IFileUpload, INodeData } from '../../src/Interface'
 import { BaseMessageLike } from '@langchain/core/messages'
 import { IFlowState } from './Interface.Agentflow'
-import { handleEscapeCharacters, mapMimeTypeToInputField } from '../../src/utils'
+import { getCredentialData, getCredentialParam, handleEscapeCharacters, mapMimeTypeToInputField } from '../../src/utils'
+import fetch from 'node-fetch'
 
 export const addImagesToMessages = async (
     options: ICommonObject,
@@ -18,7 +19,8 @@ export const addImagesToMessages = async (
         for (const upload of imageUploads) {
             let bf = upload.data
             if (upload.type == 'stored-file') {
-                const contents = await getFileFromStorage(upload.name, options.orgId, options.chatflowid, options.chatId)
+                const fileName = upload.name.replace(/^FILE-STORAGE::/, '')
+                const contents = await getFileFromStorage(fileName, options.orgId, options.chatflowid, options.chatId)
                 // as the image is stored in the server, read the file and convert it to base64
                 bf = 'data:' + upload.mime + ';base64,' + contents.toString('base64')
 
@@ -89,8 +91,9 @@ export const processMessagesWithImages = async (
                 if (item.type === 'stored-file' && item.name && item.mime.startsWith('image/')) {
                     hasImageReferences = true
                     try {
+                        const fileName = item.name.replace(/^FILE-STORAGE::/, '')
                         // Get file contents from storage
-                        const contents = await getFileFromStorage(item.name, options.orgId, options.chatflowid, options.chatId)
+                        const contents = await getFileFromStorage(fileName, options.orgId, options.chatflowid, options.chatId)
 
                         // Create base64 data URL
                         const base64Data = 'data:' + item.mime + ';base64,' + contents.toString('base64')
@@ -322,7 +325,8 @@ export const getPastChatHistoryImageMessages = async (
                 const imageContents: MessageContentImageUrl[] = []
                 for (const upload of uploads) {
                     if (upload.type === 'stored-file' && upload.mime.startsWith('image/')) {
-                        const fileData = await getFileFromStorage(upload.name, options.orgId, options.chatflowid, options.chatId)
+                        const fileName = upload.name.replace(/^FILE-STORAGE::/, '')
+                        const fileData = await getFileFromStorage(fileName, options.orgId, options.chatflowid, options.chatId)
                         // as the image is stored in the server, read the file and convert it to base64
                         const bf = 'data:' + upload.mime + ';base64,' + fileData.toString('base64')
 
@@ -456,6 +460,437 @@ export const getPastChatHistoryImageMessages = async (
     }
 }
 
+/**
+ * Gets MIME type from filename extension
+ */
+export const getMimeTypeFromFilename = (filename: string): string => {
+    const extension = filename.toLowerCase().split('.').pop()
+    const mimeTypes: { [key: string]: string } = {
+        png: 'image/png',
+        jpg: 'image/jpeg',
+        jpeg: 'image/jpeg',
+        gif: 'image/gif',
+        pdf: 'application/pdf',
+        txt: 'text/plain',
+        csv: 'text/csv',
+        json: 'application/json',
+        html: 'text/html',
+        xml: 'application/xml'
+    }
+    return mimeTypes[extension || ''] || 'application/octet-stream'
+}
+
+/**
+ * Gets artifact type from filename extension for UI rendering
+ */
+export const getArtifactTypeFromFilename = (filename: string): string => {
+    const extension = filename.toLowerCase().split('.').pop()
+    const artifactTypes: { [key: string]: string } = {
+        png: 'png',
+        jpg: 'jpeg',
+        jpeg: 'jpeg',
+        html: 'html',
+        htm: 'html',
+        md: 'markdown',
+        markdown: 'markdown',
+        json: 'json',
+        js: 'javascript',
+        javascript: 'javascript',
+        tex: 'latex',
+        latex: 'latex',
+        txt: 'text',
+        csv: 'text',
+        pdf: 'text'
+    }
+    return artifactTypes[extension || ''] || 'text'
+}
+
+/**
+ * Saves base64 image data to storage and returns file information
+ */
+export const saveBase64Image = async (
+    outputItem: any,
+    options: ICommonObject
+): Promise<{ filePath: string; fileName: string; totalSize: number } | null> => {
+    try {
+        if (!outputItem.result) {
+            return null
+        }
+
+        // Extract base64 data and create buffer
+        const base64Data = outputItem.result
+        const imageBuffer = Buffer.from(base64Data, 'base64')
+
+        // Determine file extension and MIME type
+        const outputFormat = outputItem.output_format || 'png'
+        const fileName = `generated_image_${outputItem.id || Date.now()}.${outputFormat}`
+        const mimeType = outputFormat === 'png' ? 'image/png' : 'image/jpeg'
+
+        // Save the image using the existing storage utility
+        const { path, totalSize } = await addSingleFileToStorage(
+            mimeType,
+            imageBuffer,
+            fileName,
+            options.orgId,
+            options.chatflowid,
+            options.chatId
+        )
+
+        return { filePath: path, fileName, totalSize }
+    } catch (error) {
+        console.error('Error saving base64 image:', error)
+        return null
+    }
+}
+
+/**
+ * Saves Gemini inline image data to storage and returns file information
+ */
+export const saveGeminiInlineImage = async (
+    inlineItem: any,
+    options: ICommonObject
+): Promise<{ filePath: string; fileName: string; totalSize: number } | null> => {
+    try {
+        if (!inlineItem.data || !inlineItem.mimeType) {
+            return null
+        }
+
+        // Extract base64 data and create buffer
+        const base64Data = inlineItem.data
+        const imageBuffer = Buffer.from(base64Data, 'base64')
+
+        // Determine file extension from MIME type
+        const mimeType = inlineItem.mimeType
+        let extension = 'png'
+        if (mimeType.includes('jpeg') || mimeType.includes('jpg')) {
+            extension = 'jpg'
+        } else if (mimeType.includes('png')) {
+            extension = 'png'
+        } else if (mimeType.includes('gif')) {
+            extension = 'gif'
+        } else if (mimeType.includes('webp')) {
+            extension = 'webp'
+        }
+
+        const fileName = `gemini_generated_image_${Date.now()}.${extension}`
+
+        // Save the image using the existing storage utility
+        const { path, totalSize } = await addSingleFileToStorage(
+            mimeType,
+            imageBuffer,
+            fileName,
+            options.orgId,
+            options.chatflowid,
+            options.chatId
+        )
+
+        return { filePath: path, fileName, totalSize }
+    } catch (error) {
+        console.error('Error saving Gemini inline image:', error)
+        return null
+    }
+}
+
+/**
+ * Downloads file content from container file citation
+ */
+export const downloadContainerFile = async (
+    containerId: string,
+    fileId: string,
+    filename: string,
+    modelNodeData: INodeData,
+    options: ICommonObject
+): Promise<{ filePath: string; totalSize: number } | null> => {
+    try {
+        const credentialData = await getCredentialData(modelNodeData.credential ?? '', options)
+        const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, modelNodeData)
+
+        if (!openAIApiKey) {
+            console.warn('No OpenAI API key available for downloading container file')
+            return null
+        }
+
+        // Download the file using OpenAI Container API
+        const response = await fetch(`https://api.openai.com/v1/containers/${containerId}/files/${fileId}/content`, {
+            method: 'GET',
+            headers: {
+                Accept: '*/*',
+                Authorization: `Bearer ${openAIApiKey}`
+            }
+        })
+
+        if (!response.ok) {
+            console.warn(
+                `Failed to download container file ${fileId} from container ${containerId}: ${response.status} ${response.statusText}`
+            )
+            return null
+        }
+
+        // Extract the binary data from the Response object
+        const data = await response.arrayBuffer()
+        const dataBuffer = Buffer.from(data)
+        const mimeType = getMimeTypeFromFilename(filename)
+
+        // Store the file using the same storage utility as OpenAIAssistant
+        const { path, totalSize } = await addSingleFileToStorage(
+            mimeType,
+            dataBuffer,
+            filename,
+            options.orgId,
+            options.chatflowid,
+            options.chatId
+        )
+
+        return { filePath: path, totalSize }
+    } catch (error) {
+        console.error('Error downloading container file:', error)
+        return null
+    }
+}
+
+/**
+ * Replace inlineData base64 with file references in the response content
+ */
+export const replaceInlineDataWithFileReferences = (
+    response: AIMessageChunk,
+    savedInlineImages: Array<{ filePath: string; fileName: string; mimeType: string }>
+): void => {
+    // Check if content is an array
+    if (!Array.isArray(response.content)) {
+        return
+    }
+
+    // Replace base64 data with file references in response content
+    let savedImageIndex = 0
+    for (let i = 0; i < response.content.length; i++) {
+        const contentItem = response.content[i]
+        if (
+            typeof contentItem === 'object' &&
+            contentItem.type === 'inlineData' &&
+            contentItem.inlineData &&
+            savedImageIndex < savedInlineImages.length
+        ) {
+            const savedImage = savedInlineImages[savedImageIndex]
+            // Replace with file reference
+            response.content[i] = {
+                type: 'stored-file',
+                name: savedImage.fileName,
+                mime: savedImage.mimeType,
+                path: savedImage.filePath
+            }
+            savedImageIndex++
+        }
+    }
+
+    // Clear the inlineData from response_metadata to avoid duplication
+    if (response.response_metadata?.inlineData) {
+        delete response.response_metadata.inlineData
+    }
+}
+
+/**
+ * Extracts artifacts from response metadata (both annotations and built-in tools)
+ */
+export const extractArtifactsFromResponse = async (
+    responseMetadata: any,
+    modelNodeData: INodeData,
+    options: ICommonObject
+): Promise<{
+    artifacts: any[]
+    fileAnnotations: any[]
+    savedInlineImages?: Array<{ filePath: string; fileName: string; mimeType: string }>
+}> => {
+    const artifacts: any[] = []
+    const fileAnnotations: any[] = []
+    const savedInlineImages: Array<{ filePath: string; fileName: string; mimeType: string }> = []
+
+    // Handle Gemini inline data (image generation)
+    if (responseMetadata?.inlineData && Array.isArray(responseMetadata.inlineData)) {
+        for (const inlineItem of responseMetadata.inlineData) {
+            if (inlineItem.type === 'gemini_inline_data' && inlineItem.data && inlineItem.mimeType) {
+                try {
+                    const savedImageResult = await saveGeminiInlineImage(inlineItem, options)
+                    if (savedImageResult) {
+                        // Create artifact in the same format as other image artifacts
+                        const fileType = getArtifactTypeFromFilename(savedImageResult.fileName)
+                        artifacts.push({
+                            type: fileType,
+                            data: savedImageResult.filePath
+                        })
+
+                        // Track saved image for replacing base64 data in content
+                        savedInlineImages.push({
+                            filePath: savedImageResult.filePath,
+                            fileName: savedImageResult.fileName,
+                            mimeType: inlineItem.mimeType
+                        })
+                    }
+                } catch (error) {
+                    console.error('Error processing Gemini inline image artifact:', error)
+                }
+            }
+        }
+    }
+
+    if (!responseMetadata?.output || !Array.isArray(responseMetadata.output)) {
+        return { artifacts, fileAnnotations, savedInlineImages: savedInlineImages.length > 0 ? savedInlineImages : undefined }
+    }
+
+    for (const outputItem of responseMetadata.output) {
+        // Handle container file citations from annotations
+        if (outputItem.type === 'message' && outputItem.content && Array.isArray(outputItem.content)) {
+            for (const contentItem of outputItem.content) {
+                if (contentItem.annotations && Array.isArray(contentItem.annotations)) {
+                    for (const annotation of contentItem.annotations) {
+                        if (annotation.type === 'container_file_citation' && annotation.file_id && annotation.filename) {
+                            try {
+                                // Download and store the file content
+                                const downloadResult = await downloadContainerFile(
+                                    annotation.container_id,
+                                    annotation.file_id,
+                                    annotation.filename,
+                                    modelNodeData,
+                                    options
+                                )
+
+                                if (downloadResult) {
+                                    const fileType = getArtifactTypeFromFilename(annotation.filename)
+
+                                    if (fileType === 'png' || fileType === 'jpeg' || fileType === 'jpg') {
+                                        const artifact = {
+                                            type: fileType,
+                                            data: downloadResult.filePath
+                                        }
+
+                                        artifacts.push(artifact)
+                                    } else {
+                                        fileAnnotations.push({
+                                            filePath: downloadResult.filePath,
+                                            fileName: annotation.filename
+                                        })
+                                    }
+                                }
+                            } catch (error) {
+                                console.error('Error processing annotation:', error)
+                            }
+                        }
+                    }
+                }
+            }
+        }
+
+        // Handle built-in tool artifacts (like image generation)
+        if (outputItem.type === 'image_generation_call' && outputItem.result) {
+            try {
+                const savedImageResult = await saveBase64Image(outputItem, options)
+                if (savedImageResult) {
+                    // Replace the base64 result with the file path in the response metadata
+                    outputItem.result = savedImageResult.filePath
+
+                    // Create artifact in the same format as other image artifacts
+                    const fileType = getArtifactTypeFromFilename(savedImageResult.fileName)
+                    artifacts.push({
+                        type: fileType,
+                        data: savedImageResult.filePath
+                    })
+                }
+            } catch (error) {
+                console.error('Error processing image generation artifact:', error)
+            }
+        }
+    }
+
+    return { artifacts, fileAnnotations, savedInlineImages: savedInlineImages.length > 0 ? savedInlineImages : undefined }
+}
+
+/**
+ * Add image artifacts from previous assistant messages as user messages
+ * This allows the LLM to see and reference the generated images in the conversation
+ * Messages are marked with a special flag for later removal
+ */
+export const addImageArtifactsToMessages = async (messages: BaseMessageLike[], options: ICommonObject): Promise<void> => {
+    const imageExtensions = ['png', 'jpg', 'jpeg', 'gif', 'webp']
+    const messagesToInsert: Array<{ index: number; message: any }> = []
+
+    // Iterate through messages to find assistant messages with image artifacts
+    for (let i = 0; i < messages.length; i++) {
+        const message = messages[i] as any
+
+        // Check if this is an assistant message with artifacts
+        if (
+            (message.role === 'assistant' || message.role === 'ai') &&
+            message.additional_kwargs?.artifacts &&
+            Array.isArray(message.additional_kwargs.artifacts)
+        ) {
+            const artifacts = message.additional_kwargs.artifacts
+            const imageArtifacts: Array<{ type: string; name: string; mime: string }> = []
+
+            // Extract image artifacts
+            for (const artifact of artifacts) {
+                if (artifact.type && artifact.data) {
+                    // Check if this is an image artifact by file type
+                    if (imageExtensions.includes(artifact.type.toLowerCase())) {
+                        // Extract filename from the file path
+                        const fileName = artifact.data.split('/').pop() || artifact.data
+                        const mimeType = `image/${artifact.type.toLowerCase()}`
+
+                        imageArtifacts.push({
+                            type: 'stored-file',
+                            name: fileName,
+                            mime: mimeType
+                        })
+                    }
+                }
+            }
+
+            // If we found image artifacts, prepare to insert a user message after this assistant message
+            if (imageArtifacts.length > 0) {
+                // Check if the next message already contains these image artifacts to avoid duplicates
+                const nextMessage = messages[i + 1] as any
+                const shouldInsert =
+                    !nextMessage ||
+                    nextMessage.role !== 'user' ||
+                    !Array.isArray(nextMessage.content) ||
+                    !nextMessage.content.some(
+                        (item: any) =>
+                            (item.type === 'stored-file' || item.type === 'image_url') &&
+                            imageArtifacts.some((artifact) => {
+                                // Compare with and without FILE-STORAGE:: prefix
+                                const artifactName = artifact.name.replace('FILE-STORAGE::', '')
+                                const itemName = item.name?.replace('FILE-STORAGE::', '') || ''
+                                return artifactName === itemName
+                            })
+                    )
+
+                if (shouldInsert) {
+                    messagesToInsert.push({
+                        index: i + 1,
+                        message: {
+                            role: 'user',
+                            content: imageArtifacts,
+                            _isTemporaryImageMessage: true // Mark for later removal
+                        }
+                    })
+                }
+            }
+        }
+    }
+
+    // Insert messages in reverse order to maintain correct indices
+    for (let i = messagesToInsert.length - 1; i >= 0; i--) {
+        const { index, message } = messagesToInsert[i]
+        messages.splice(index, 0, message)
+    }
+
+    // Convert stored-file references to base64 image_url format
+    if (messagesToInsert.length > 0) {
+        const { updatedMessages } = await processMessagesWithImages(messages, options)
+        // Replace the messages array content with the updated messages
+        messages.length = 0
+        messages.push(...updatedMessages)
+    }
+}
+
 /**
  * Updates the flow state with new values
  */

packages/components/nodes/chatmodels/ChatGoogleGenerativeAI/FlowiseChatGoogleGenerativeAI.ts

@@ -607,7 +607,12 @@ export class LangchainChatGoogleGenerativeAI
     private client: GenerativeModel
 
     get _isMultimodalModel() {
-        return this.model.includes('vision') || this.model.startsWith('gemini-1.5') || this.model.startsWith('gemini-2')
+        return (
+            this.model.includes('vision') ||
+            this.model.startsWith('gemini-1.5') ||
+            this.model.startsWith('gemini-2') ||
+            this.model.startsWith('gemini-3')
+        )
     }
 
     constructor(fields: GoogleGenerativeAIChatInput) {

packages/components/nodes/chatmodels/ChatGoogleGenerativeAI/utils/common.ts

@@ -452,6 +452,7 @@ export function mapGenerateContentResultToChatResult(
     const [candidate] = response.candidates
     const { content: candidateContent, ...generationInfo } = candidate
     let content: MessageContent | undefined
+    const inlineDataItems: any[] = []
 
     if (Array.isArray(candidateContent?.parts) && candidateContent.parts.length === 1 && candidateContent.parts[0].text) {
         content = candidateContent.parts[0].text
@@ -472,6 +473,18 @@ export function mapGenerateContentResultToChatResult(
                     type: 'codeExecutionResult',
                     codeExecutionResult: p.codeExecutionResult
                 }
+            } else if ('inlineData' in p && p.inlineData) {
+                // Extract inline image data for processing by Agent
+                inlineDataItems.push({
+                    type: 'gemini_inline_data',
+                    mimeType: p.inlineData.mimeType,
+                    data: p.inlineData.data
+                })
+                // Return the inline data as part of the content structure
+                return {
+                    type: 'inlineData',
+                    inlineData: p.inlineData
+                }
             }
             return p
         })
@@ -488,6 +501,12 @@ export function mapGenerateContentResultToChatResult(
         text = block?.text ?? text
     }
 
+    // Build response_metadata with inline data if present
+    const response_metadata: any = {}
+    if (inlineDataItems.length > 0) {
+        response_metadata.inlineData = inlineDataItems
+    }
+
     const generation: ChatGeneration = {
         text,
         message: new AIMessage({
@@ -502,7 +521,8 @@ export function mapGenerateContentResultToChatResult(
             additional_kwargs: {
                 ...generationInfo
             },
-            usage_metadata: extra?.usageMetadata
+            usage_metadata: extra?.usageMetadata,
+            response_metadata: Object.keys(response_metadata).length > 0 ? response_metadata : undefined
         }),
         generationInfo
     }
@@ -533,6 +553,8 @@ export function convertResponseContentToChatGenerationChunk(
     const [candidate] = response.candidates
     const { content: candidateContent, ...generationInfo } = candidate
     let content: MessageContent | undefined
+    const inlineDataItems: any[] = []
+
     // Checks if some parts do not have text. If false, it means that the content is a string.
     if (Array.isArray(candidateContent?.parts) && candidateContent.parts.every((p) => 'text' in p)) {
         content = candidateContent.parts.map((p) => p.text).join('')
@@ -553,6 +575,18 @@ export function convertResponseContentToChatGenerationChunk(
                     type: 'codeExecutionResult',
                     codeExecutionResult: p.codeExecutionResult
                 }
+            } else if ('inlineData' in p && p.inlineData) {
+                // Extract inline image data for processing by Agent
+                inlineDataItems.push({
+                    type: 'gemini_inline_data',
+                    mimeType: p.inlineData.mimeType,
+                    data: p.inlineData.data
+                })
+                // Return the inline data as part of the content structure
+                return {
+                    type: 'inlineData',
+                    inlineData: p.inlineData
+                }
             }
             return p
         })
@@ -582,6 +616,12 @@ export function convertResponseContentToChatGenerationChunk(
         )
     }
 
+    // Build response_metadata with inline data if present
+    const response_metadata: any = {}
+    if (inlineDataItems.length > 0) {
+        response_metadata.inlineData = inlineDataItems
+    }
+
     return new ChatGenerationChunk({
         text,
         message: new AIMessageChunk({
@@ -591,7 +631,8 @@ export function convertResponseContentToChatGenerationChunk(
             // Each chunk can have unique "generationInfo", and merging strategy is unclear,
             // so leave blank for now.
             additional_kwargs: {},
-            usage_metadata: extra.usageMetadata
+            usage_metadata: extra.usageMetadata,
+            response_metadata: Object.keys(response_metadata).length > 0 ? response_metadata : undefined
         }),
         generationInfo
     })