Bugfix/Remove postgres vector store data when deletion (#5536)

Remove postgres vector store data when deletion

- Introduced a new `doc_id` column in MySQL, Postgres, and SQLite record managers to support document identification.
- Updated the `update` method to handle both string and object formats for keys, allowing for better flexibility in document updates.
- Enhanced `listKeys` method to filter by `doc_id` when provided in options.
- Updated vector store integrations to utilize the new `doc_id` filtering capability

.github/workflows/docker-image-dockerhub.yml

@@ -0,0 +1,72 @@
+name: Docker Image CI - Docker Hub
+
+on:
+    workflow_dispatch:
+        inputs:
+            node_version:
+                description: 'Node.js version to build this image with.'
+                type: choice
+                required: true
+                default: '20'
+                options:
+                    - '20'
+            tag_version:
+                description: 'Tag version of the image to be pushed.'
+                type: string
+                required: true
+                default: 'latest'
+
+jobs:
+    docker:
+        runs-on: ubuntu-latest
+        steps:
+            - name: Set default values
+              id: defaults
+              run: |
+                  echo "node_version=${{ github.event.inputs.node_version || '20' }}" >> $GITHUB_OUTPUT
+                  echo "tag_version=${{ github.event.inputs.tag_version || 'latest' }}" >> $GITHUB_OUTPUT
+
+            - name: Checkout
+              uses: actions/checkout@v4.1.1
+
+            - name: Set up QEMU
+              uses: docker/setup-qemu-action@v3.0.0
+
+            - name: Set up Docker Buildx
+              uses: docker/setup-buildx-action@v3.0.0
+
+            - name: Login to Docker Hub
+              uses: docker/login-action@v3
+              with:
+                  username: ${{ secrets.DOCKERHUB_USERNAME }}
+                  password: ${{ secrets.DOCKERHUB_TOKEN }}
+
+            # -------------------------
+            # Build and push main image
+            # -------------------------
+            - name: Build and push main image
+              uses: docker/build-push-action@v5.3.0
+              with:
+                  context: .
+                  file: ./docker/Dockerfile
+                  build-args: |
+                      NODE_VERSION=${{ steps.defaults.outputs.node_version }}
+                  platforms: linux/amd64,linux/arm64
+                  push: true
+                  tags: |
+                      flowiseai/flowise:${{ steps.defaults.outputs.tag_version }}
+
+            # -------------------------
+            # Build and push worker image
+            # -------------------------
+            - name: Build and push worker image
+              uses: docker/build-push-action@v5.3.0
+              with:
+                  context: .
+                  file: docker/worker/Dockerfile
+                  build-args: |
+                      NODE_VERSION=${{ steps.defaults.outputs.node_version }}
+                  platforms: linux/amd64,linux/arm64
+                  push: true
+                  tags: |
+                      flowiseai/flowise-worker:${{ steps.defaults.outputs.tag_version }}

.github/workflows/docker-image-ecr.yml

@@ -0,0 +1,73 @@
+name: Docker Image CI - AWS ECR
+
+on:
+    workflow_dispatch:
+        inputs:
+            environment:
+                description: 'Environment to push the image to.'
+                required: true
+                default: 'dev'
+                type: choice
+                options:
+                    - dev
+                    - prod
+            node_version:
+                description: 'Node.js version to build this image with.'
+                type: choice
+                required: true
+                default: '20'
+                options:
+                    - '20'
+            tag_version:
+                description: 'Tag version of the image to be pushed.'
+                type: string
+                required: true
+                default: 'latest'
+
+jobs:
+    docker:
+        runs-on: ubuntu-latest
+        environment: ${{ github.event.inputs.environment }}
+        steps:
+            - name: Set default values
+              id: defaults
+              run: |
+                  echo "node_version=${{ github.event.inputs.node_version || '20' }}" >> $GITHUB_OUTPUT
+                  echo "tag_version=${{ github.event.inputs.tag_version || 'latest' }}" >> $GITHUB_OUTPUT
+
+            - name: Checkout
+              uses: actions/checkout@v4.1.1
+
+            - name: Set up QEMU
+              uses: docker/setup-qemu-action@v3.0.0
+
+            - name: Set up Docker Buildx
+              uses: docker/setup-buildx-action@v3.0.0
+
+            - name: Configure AWS Credentials
+              uses: aws-actions/configure-aws-credentials@v3
+              with:
+                  aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
+                  aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+                  aws-region: ${{ secrets.AWS_REGION }}
+
+            - name: Login to Amazon ECR
+              uses: aws-actions/amazon-ecr-login@v1
+
+            # -------------------------
+            # Build and push main image
+            # -------------------------
+            - name: Build and push main image
+              uses: docker/build-push-action@v5.3.0
+              with:
+                  context: .
+                  file: Dockerfile
+                  build-args: |
+                      NODE_VERSION=${{ steps.defaults.outputs.node_version }}
+                  platforms: linux/amd64,linux/arm64
+                  push: true
+                  tags: |
+                      ${{ format('{0}.dkr.ecr.{1}.amazonaws.com/flowise:{2}', 
+                          secrets.AWS_ACCOUNT_ID, 
+                          secrets.AWS_REGION, 
+                          steps.defaults.outputs.tag_version) }}

.github/workflows/docker-image.yml

@@ -1,114 +0,0 @@
-name: Docker Image CI
-
-on:
-    workflow_dispatch:
-        inputs:
-            registry:
-                description: 'Container Registry to push the image to.'
-                type: choice
-                required: true
-                default: 'aws_ecr'
-                options:
-                    - 'docker_hub'
-                    - 'aws_ecr'
-            environment:
-                description: 'Environment to push the image to.'
-                required: true
-                default: 'dev'
-                type: choice
-                options:
-                    - dev
-                    - prod
-            image_type:
-                description: 'Type of image to build and push.'
-                type: choice
-                required: true
-                default: 'main'
-                options:
-                    - 'main'
-                    - 'worker'
-            node_version:
-                description: 'Node.js version to build this image with.'
-                type: choice
-                required: true
-                default: '20'
-                options:
-                    - '20'
-            tag_version:
-                description: 'Tag version of the image to be pushed.'
-                type: string
-                required: true
-                default: 'latest'
-
-jobs:
-    docker:
-        runs-on: ubuntu-latest
-        environment: ${{ github.event.inputs.environment }}
-        steps:
-            - name: Set default values
-              id: defaults
-              run: |
-                  echo "registry=${{ github.event.inputs.registry || 'aws_ecr' }}" >> $GITHUB_OUTPUT
-                  echo "image_type=${{ github.event.inputs.image_type || 'main' }}" >> $GITHUB_OUTPUT
-                  echo "node_version=${{ github.event.inputs.node_version || '20' }}" >> $GITHUB_OUTPUT
-                  echo "tag_version=${{ github.event.inputs.tag_version || 'latest' }}" >> $GITHUB_OUTPUT
-
-            - name: Checkout
-              uses: actions/checkout@v4.1.1
-
-            - name: Set up QEMU
-              uses: docker/setup-qemu-action@v3.0.0
-
-            - name: Set up Docker Buildx
-              uses: docker/setup-buildx-action@v3.0.0
-
-            # ------------------------
-            # Login Steps (conditional)
-            # ------------------------
-            - name: Login to Docker Hub
-              if: steps.defaults.outputs.registry == 'docker_hub'
-              uses: docker/login-action@v3
-              with:
-                  username: ${{ secrets.DOCKERHUB_USERNAME }}
-                  password: ${{ secrets.DOCKERHUB_TOKEN }}
-
-            - name: Configure AWS Credentials
-              if: steps.defaults.outputs.registry == 'aws_ecr'
-              uses: aws-actions/configure-aws-credentials@v3
-              with:
-                  aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
-                  aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
-                  aws-region: ${{ secrets.AWS_REGION }}
-
-            - name: Login to Amazon ECR
-              if: steps.defaults.outputs.registry == 'aws_ecr'
-              uses: aws-actions/amazon-ecr-login@v1
-
-            # -------------------------
-            # Build and push (conditional tags)
-            # -------------------------
-            - name: Build and push
-              uses: docker/build-push-action@v5.3.0
-              with:
-                  context: .
-                  file: |
-                      ${{ 
-                        steps.defaults.outputs.image_type == 'worker' && 'docker/worker/Dockerfile' ||
-                        (steps.defaults.outputs.registry == 'docker_hub' && './docker/Dockerfile' || 'Dockerfile') 
-                      }}
-                  build-args: |
-                      NODE_VERSION=${{ steps.defaults.outputs.node_version }}
-                  platforms: linux/amd64,linux/arm64
-                  push: true
-                  tags: |
-                      ${{ 
-                          steps.defaults.outputs.registry == 'docker_hub' && 
-                          format('flowiseai/flowise{0}:{1}', 
-                              steps.defaults.outputs.image_type == 'worker' && '-worker' || '', 
-                              steps.defaults.outputs.tag_version) ||
-                          format('{0}.dkr.ecr.{1}.amazonaws.com/flowise{2}:{3}', 
-                              secrets.AWS_ACCOUNT_ID, 
-                              secrets.AWS_REGION, 
-                              steps.defaults.outputs.image_type == 'worker' && '-worker' || '',
-                              steps.defaults.outputs.tag_version) 
-                      }}

Dockerfile

@@ -5,34 +5,41 @@
 # docker run -d -p 3000:3000 flowise
 
 FROM node:20-alpine
-RUN apk add --update libc6-compat python3 make g++
-# needed for pdfjs-dist
-RUN apk add --no-cache build-base cairo-dev pango-dev
 
-# Install Chromium
-RUN apk add --no-cache chromium
-
-# Install curl for container-level health checks
-# Fixes: https://github.com/FlowiseAI/Flowise/issues/4126
-RUN apk add --no-cache curl
-
-#install PNPM globaly
-RUN npm install -g pnpm
+# Install system dependencies and build tools
+RUN apk update && \
+    apk add --no-cache \
+        libc6-compat \
+        python3 \
+        make \
+        g++ \
+        build-base \
+        cairo-dev \
+        pango-dev \
+        chromium \
+        curl && \
+    npm install -g pnpm
 
 ENV PUPPETEER_SKIP_DOWNLOAD=true
 ENV PUPPETEER_EXECUTABLE_PATH=/usr/bin/chromium-browser
 
 ENV NODE_OPTIONS=--max-old-space-size=8192
 
-WORKDIR /usr/src
+WORKDIR /usr/src/flowise
 
 # Copy app source
 COPY . .
 
-RUN pnpm install
+# Install dependencies and build
+RUN pnpm install && \
+    pnpm build
 
-RUN pnpm build
+# Give the node user ownership of the application files
+RUN chown -R node:node .
+
+# Switch to non-root user (node user already exists in node:20-alpine)
+USER node
 
 EXPOSE 3000
 
-CMD [ "pnpm", "start" ]
+CMD [ "pnpm", "start" ]

README.md

@@ -189,7 +189,7 @@ Deploy Flowise self-hosted in your existing infrastructure, we support various [
     -   [Railway](https://docs.flowiseai.com/configuration/deployment/railway)
 
         [![Deploy on Railway](https://railway.app/button.svg)](https://railway.app/template/pn4G8S?referralCode=WVNPD9)
-        
+
     -   [Northflank](https://northflank.com/stacks/deploy-flowiseai)
 
         [![Deploy to Northflank](https://assets.northflank.com/deploy_to_northflank_smm_36700fb050.svg)](https://northflank.com/stacks/deploy-flowiseai)

SECURITY.md

@@ -1,38 +1,38 @@
-### Responsible Disclosure Policy  
+### Responsible Disclosure Policy
 
-At Flowise, we prioritize security and continuously work to safeguard our systems. However, vulnerabilities can still exist. If you identify a security issue, please report it to us so we can address it promptly. Your cooperation helps us better protect our platform and users.  
+At Flowise, we prioritize security and continuously work to safeguard our systems. However, vulnerabilities can still exist. If you identify a security issue, please report it to us so we can address it promptly. Your cooperation helps us better protect our platform and users.
 
-### Out of scope vulnerabilities  
+### Out of scope vulnerabilities
 
-- Clickjacking on pages without sensitive actions  
-- CSRF on unauthenticated/logout/login pages  
-- Attacks requiring MITM (Man-in-the-Middle) or physical device access  
-- Social engineering attacks  
-- Activities that cause service disruption (DoS)  
-- Content spoofing and text injection without a valid attack vector  
-- Email spoofing  
-- Absence of DNSSEC, CAA, CSP headers  
-- Missing Secure or HTTP-only flag on non-sensitive cookies  
-- Deadlinks  
-- User enumeration  
+-   Clickjacking on pages without sensitive actions
+-   CSRF on unauthenticated/logout/login pages
+-   Attacks requiring MITM (Man-in-the-Middle) or physical device access
+-   Social engineering attacks
+-   Activities that cause service disruption (DoS)
+-   Content spoofing and text injection without a valid attack vector
+-   Email spoofing
+-   Absence of DNSSEC, CAA, CSP headers
+-   Missing Secure or HTTP-only flag on non-sensitive cookies
+-   Deadlinks
+-   User enumeration
 
-### Reporting Guidelines  
+### Reporting Guidelines
 
-- Submit your findings to https://github.com/FlowiseAI/Flowise/security
-- Provide clear details to help us reproduce and fix the issue quickly.  
+-   Submit your findings to https://github.com/FlowiseAI/Flowise/security
+-   Provide clear details to help us reproduce and fix the issue quickly.
 
-### Disclosure Guidelines  
+### Disclosure Guidelines
 
-- Do not publicly disclose vulnerabilities until we have assessed, resolved, and notified affected users.  
-- If you plan to present your research (e.g., at a conference or in a blog), share a draft with us at least **30 days in advance** for review.  
-- Avoid including:  
-  - Data from any Flowise customer projects  
-  - Flowise user/customer information  
-  - Details about Flowise employees, contractors, or partners  
+-   Do not publicly disclose vulnerabilities until we have assessed, resolved, and notified affected users.
+-   If you plan to present your research (e.g., at a conference or in a blog), share a draft with us at least **30 days in advance** for review.
+-   Avoid including:
+    -   Data from any Flowise customer projects
+    -   Flowise user/customer information
+    -   Details about Flowise employees, contractors, or partners
 
-### Response to Reports  
+### Response to Reports
 
-- We will acknowledge your report within **5 business days** and provide an estimated resolution timeline.  
-- Your report will be kept **confidential**, and your details will not be shared without your consent.
-  
-We appreciate your efforts in helping us maintain a secure platform and look forward to working together to resolve any issues responsibly.  
+-   We will acknowledge your report within **5 business days** and provide an estimated resolution timeline.
+-   Your report will be kept **confidential**, and your details will not be shared without your consent.
+
+We appreciate your efforts in helping us maintain a secure platform and look forward to working together to resolve any issues responsibly.

docker/worker/Dockerfile

@@ -7,7 +7,7 @@ RUN apk add --no-cache build-base cairo-dev pango-dev
 # Install Chromium and curl for container-level health checks
 RUN apk add --no-cache chromium curl
 
-#install PNPM globaly
+#install PNPM globally
 RUN npm install -g pnpm
 
 ENV PUPPETEER_SKIP_DOWNLOAD=true

package.json

@@ -1,6 +1,6 @@
 {
     "name": "flowise",
-    "version": "10",
+    "version": "3.0.11",
     "private": true,
     "homepage": "https://flowiseai.com",
     "workspaces": [
@@ -51,7 +51,7 @@
         "eslint-plugin-react-hooks": "^4.6.0",
         "eslint-plugin-unused-imports": "^2.0.0",
         "husky": "^8.0.1",
-        "kill-port": "^2.0.1",
+        "kill-port": "2.0.1",
         "lint-staged": "^13.0.3",
         "prettier": "^2.7.1",
         "pretty-quick": "^3.1.3",

packages/components/models.json

@@ -3,6 +3,13 @@
         {
             "name": "awsChatBedrock",
             "models": [
+                {
+                    "label": "anthropic.claude-opus-4-5-20251101-v1:0",
+                    "name": "anthropic.claude-opus-4-5-20251101-v1:0",
+                    "description": "Claude 4.5 Opus",
+                    "input_cost": 0.000005,
+                    "output_cost": 0.000025
+                },
                 {
                     "label": "anthropic.claude-sonnet-4-5-20250929-v1:0",
                     "name": "anthropic.claude-sonnet-4-5-20250929-v1:0",
@@ -315,6 +322,12 @@
         {
             "name": "azureChatOpenAI",
             "models": [
+                {
+                    "label": "gpt-5.1",
+                    "name": "gpt-5.1",
+                    "input_cost": 0.00000125,
+                    "output_cost": 0.00001
+                },
                 {
                     "label": "gpt-5",
                     "name": "gpt-5",
@@ -499,6 +512,13 @@
         {
             "name": "chatAnthropic",
             "models": [
+                {
+                    "label": "claude-opus-4-5",
+                    "name": "claude-opus-4-5",
+                    "description": "Claude 4.5 Opus",
+                    "input_cost": 0.000005,
+                    "output_cost": 0.000025
+                },
                 {
                     "label": "claude-sonnet-4-5",
                     "name": "claude-sonnet-4-5",
@@ -621,6 +641,18 @@
         {
             "name": "chatGoogleGenerativeAI",
             "models": [
+                {
+                    "label": "gemini-3-pro-preview",
+                    "name": "gemini-3-pro-preview",
+                    "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",
@@ -633,6 +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",
@@ -685,6 +723,12 @@
         {
             "name": "chatGoogleVertexAI",
             "models": [
+                {
+                    "label": "gemini-3-pro-preview",
+                    "name": "gemini-3-pro-preview",
+                    "input_cost": 0.00002,
+                    "output_cost": 0.00012
+                },
                 {
                     "label": "gemini-2.5-pro",
                     "name": "gemini-2.5-pro",
@@ -751,6 +795,13 @@
                     "input_cost": 1.25e-7,
                     "output_cost": 3.75e-7
                 },
+                {
+                    "label": "claude-opus-4-5@20251101",
+                    "name": "claude-opus-4-5@20251101",
+                    "description": "Claude 4.5 Opus",
+                    "input_cost": 0.000005,
+                    "output_cost": 0.000025
+                },
                 {
                     "label": "claude-sonnet-4-5@20250929",
                     "name": "claude-sonnet-4-5@20250929",
@@ -996,6 +1047,12 @@
         {
             "name": "chatOpenAI",
             "models": [
+                {
+                    "label": "gpt-5.1",
+                    "name": "gpt-5.1",
+                    "input_cost": 0.00000125,
+                    "output_cost": 0.00001
+                },
                 {
                     "label": "gpt-5",
                     "name": "gpt-5",

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

@@ -22,15 +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 { convertMultiOptionsToStringArray, getCredentialData, getCredentialParam, processTemplateVariables } from '../../../src/utils'
-import { addSingleFileToStorage } from '../../../src/storageUtils'
-import fetch from 'node-fetch'
+import { convertMultiOptionsToStringArray, processTemplateVariables, configureStructuredOutput } from '../../../src/utils'
 
 interface ITool {
     agentSelectedTool: string
@@ -81,7 +82,7 @@ class Agent_Agentflow implements INode {
     constructor() {
         this.label = 'Agent'
         this.name = 'agentAgentflow'
-        this.version = 2.2
+        this.version = 3.2
         this.type = 'Agent'
         this.category = 'Agent Flows'
         this.description = 'Dynamically choose and utilize tools during runtime, enabling multi-step reasoning'
@@ -176,6 +177,11 @@ class Agent_Agentflow implements INode {
                         label: 'Google Search',
                         name: 'googleSearch',
                         description: 'Search real-time web content'
+                    },
+                    {
+                        label: 'Code Execution',
+                        name: 'codeExecution',
+                        description: 'Write and run Python code in a sandboxed environment'
                     }
                 ],
                 show: {
@@ -394,6 +400,108 @@ class Agent_Agentflow implements INode {
                 ],
                 default: 'userMessage'
             },
+            {
+                label: 'JSON Structured Output',
+                name: 'agentStructuredOutput',
+                description: 'Instruct the Agent to give output in a JSON structured schema',
+                type: 'array',
+                optional: true,
+                acceptVariable: true,
+                array: [
+                    {
+                        label: 'Key',
+                        name: 'key',
+                        type: 'string'
+                    },
+                    {
+                        label: 'Type',
+                        name: 'type',
+                        type: 'options',
+                        options: [
+                            {
+                                label: 'String',
+                                name: 'string'
+                            },
+                            {
+                                label: 'String Array',
+                                name: 'stringArray'
+                            },
+                            {
+                                label: 'Number',
+                                name: 'number'
+                            },
+                            {
+                                label: 'Boolean',
+                                name: 'boolean'
+                            },
+                            {
+                                label: 'Enum',
+                                name: 'enum'
+                            },
+                            {
+                                label: 'JSON Array',
+                                name: 'jsonArray'
+                            }
+                        ]
+                    },
+                    {
+                        label: 'Enum Values',
+                        name: 'enumValues',
+                        type: 'string',
+                        placeholder: 'value1, value2, value3',
+                        description: 'Enum values. Separated by comma',
+                        optional: true,
+                        show: {
+                            'agentStructuredOutput[$index].type': 'enum'
+                        }
+                    },
+                    {
+                        label: 'JSON Schema',
+                        name: 'jsonSchema',
+                        type: 'code',
+                        placeholder: `{
+    "answer": {
+        "type": "string",
+        "description": "Value of the answer"
+    },
+    "reason": {
+        "type": "string",
+        "description": "Reason for the answer"
+    },
+    "optional": {
+        "type": "boolean"
+    },
+    "count": {
+        "type": "number"
+    },
+    "children": {
+        "type": "array",
+        "items": {
+            "type": "object",
+            "properties": {
+                "value": {
+                    "type": "string",
+                    "description": "Value of the children's answer"
+                }
+            }
+        }
+    }
+}`,
+                        description: 'JSON schema for the structured output',
+                        optional: true,
+                        hideCodeExecute: true,
+                        show: {
+                            'agentStructuredOutput[$index].type': 'jsonArray'
+                        }
+                    },
+                    {
+                        label: 'Description',
+                        name: 'description',
+                        type: 'string',
+                        placeholder: 'Description of the key'
+                    }
+                ]
+            },
             {
                 label: 'Update Flow State',
                 name: 'agentUpdateState',
@@ -406,8 +514,7 @@ class Agent_Agentflow implements INode {
                         label: 'Key',
                         name: 'key',
                         type: 'asyncOptions',
-                        loadMethod: 'listRuntimeStateKeys',
-                        freeSolo: true
+                        loadMethod: 'listRuntimeStateKeys'
                     },
                     {
                         label: 'Value',
@@ -770,6 +877,7 @@ class Agent_Agentflow implements INode {
             const memoryType = nodeData.inputs?.agentMemoryType as string
             const userMessage = nodeData.inputs?.agentUserMessage as string
             const _agentUpdateState = nodeData.inputs?.agentUpdateState
+            const _agentStructuredOutput = nodeData.inputs?.agentStructuredOutput
             const agentMessages = (nodeData.inputs?.agentMessages as unknown as ILLMMessage[]) ?? []
 
             // Extract runtime state and history
@@ -795,6 +903,8 @@ class Agent_Agentflow implements INode {
             const llmWithoutToolsBind = (await newLLMNodeInstance.init(newNodeData, '', options)) as BaseChatModel
             let llmNodeInstance = llmWithoutToolsBind
 
+            const isStructuredOutput = _agentStructuredOutput && Array.isArray(_agentStructuredOutput) && _agentStructuredOutput.length > 0
+
             const agentToolsBuiltInOpenAI = convertMultiOptionsToStringArray(nodeData.inputs?.agentToolsBuiltInOpenAI)
             if (agentToolsBuiltInOpenAI && agentToolsBuiltInOpenAI.length > 0) {
                 for (const tool of agentToolsBuiltInOpenAI) {
@@ -953,7 +1063,7 @@ class Agent_Agentflow implements INode {
             // Initialize response and determine if streaming is possible
             let response: AIMessageChunk = new AIMessageChunk('')
             const isLastNode = options.isLastNode as boolean
-            const isStreamable = isLastNode && options.sseStreamer !== undefined && modelConfig?.streaming !== false
+            const isStreamable = isLastNode && options.sseStreamer !== undefined && modelConfig?.streaming !== false && !isStructuredOutput
 
             // Start analytics
             if (analyticHandlers && options.parentTraceIds) {
@@ -961,12 +1071,6 @@ 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> = []
@@ -979,12 +1083,24 @@ 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}'`)
@@ -1002,7 +1118,8 @@ class Agent_Agentflow implements INode {
                     llmWithoutToolsBind,
                     isStreamable,
                     isLastNode,
-                    iterationContext
+                    iterationContext,
+                    isStructuredOutput
                 })
 
                 response = result.response
@@ -1031,7 +1148,14 @@ class Agent_Agentflow implements INode {
                 }
             } else {
                 if (isStreamable) {
-                    response = await this.handleStreamingResponse(sseStreamer, llmNodeInstance, messages, chatId, abortController)
+                    response = await this.handleStreamingResponse(
+                        sseStreamer,
+                        llmNodeInstance,
+                        messages,
+                        chatId,
+                        abortController,
+                        isStructuredOutput
+                    )
                 } else {
                     response = await llmNodeInstance.invoke(messages, { signal: abortController?.signal })
                 }
@@ -1053,7 +1177,8 @@ class Agent_Agentflow implements INode {
                     llmNodeInstance,
                     isStreamable,
                     isLastNode,
-                    iterationContext
+                    iterationContext,
+                    isStructuredOutput
                 })
 
                 response = result.response
@@ -1080,11 +1205,20 @@ class Agent_Agentflow implements INode {
                         sseStreamer.streamArtifactsEvent(chatId, flatten(artifacts))
                     }
                 }
-            } else if (!humanInput && !isStreamable && isLastNode && sseStreamer) {
+            } else if (!humanInput && !isStreamable && isLastNode && sseStreamer && !isStructuredOutput) {
                 // Stream whole response back to UI if not streaming and no tool calls
+                // Skip this if structured output is enabled - it will be streamed after conversion
                 let finalResponse = ''
                 if (response.content && Array.isArray(response.content)) {
-                    finalResponse = response.content.map((item: any) => item.text).join('\n')
+                    finalResponse = response.content
+                        .map((item: any) => {
+                            if ((item.text && !item.type) || (item.type === 'text' && item.text)) {
+                                return item.text
+                            }
+                            return ''
+                        })
+                        .filter((text: string) => text)
+                        .join('\n')
                 } else if (response.content && typeof response.content === 'string') {
                     finalResponse = response.content
                 } else {
@@ -1113,9 +1247,53 @@ 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')
+                // Process items and concatenate consecutive text items
+                const processedParts: string[] = []
+                let currentTextBuffer = ''
+
+                for (const item of response.content) {
+                    const itemAny = item as any
+                    const isTextItem = (itemAny.text && !itemAny.type) || (itemAny.type === 'text' && itemAny.text)
+
+                    if (isTextItem) {
+                        // Accumulate consecutive text items
+                        currentTextBuffer += itemAny.text
+                    } else {
+                        // Flush accumulated text before processing other types
+                        if (currentTextBuffer) {
+                            processedParts.push(currentTextBuffer)
+                            currentTextBuffer = ''
+                        }
+
+                        // Process non-text items
+                        if (itemAny.type === 'executableCode' && itemAny.executableCode) {
+                            // Format executable code as a code block
+                            const language = itemAny.executableCode.language?.toLowerCase() || 'python'
+                            processedParts.push(`\n\`\`\`${language}\n${itemAny.executableCode.code}\n\`\`\`\n`)
+                        } else if (itemAny.type === 'codeExecutionResult' && itemAny.codeExecutionResult) {
+                            // Format code execution result
+                            const outcome = itemAny.codeExecutionResult.outcome || 'OUTCOME_OK'
+                            const output = itemAny.codeExecutionResult.output || ''
+                            if (outcome === 'OUTCOME_OK' && output) {
+                                processedParts.push(`**Code Output:**\n\`\`\`\n${output}\n\`\`\`\n`)
+                            } else if (outcome !== 'OUTCOME_OK') {
+                                processedParts.push(`**Code Execution Error:**\n\`\`\`\n${output}\n\`\`\`\n`)
+                            }
+                        }
+                    }
+                }
+
+                // Flush any remaining text
+                if (currentTextBuffer) {
+                    processedParts.push(currentTextBuffer)
+                }
+
+                finalResponse = processedParts.filter((text) => 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)
             }
@@ -1131,10 +1309,13 @@ 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 } =
-                    await this.extractArtifactsFromResponse(response.response_metadata, newNodeData, options)
+                const {
+                    artifacts: extractedArtifacts,
+                    fileAnnotations: extractedFileAnnotations,
+                    savedInlineImages
+                } = await extractArtifactsFromResponse(response.response_metadata, newNodeData, options)
                 if (extractedArtifacts.length > 0) {
                     artifacts = [...artifacts, ...extractedArtifacts]
 
@@ -1152,6 +1333,11 @@ 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)
@@ -1159,6 +1345,23 @@ class Agent_Agentflow implements INode {
                 finalResponse = await this.processSandboxLinks(finalResponse, options.baseURL, options.chatflowid, chatId)
             }
 
+            // If is structured output, then invoke LLM again with structured output at the very end after all tool calls
+            if (isStructuredOutput) {
+                llmNodeInstance = configureStructuredOutput(llmNodeInstance, _agentStructuredOutput)
+                const prompt = 'Convert the following response to the structured output format: ' + finalResponse
+                response = await llmNodeInstance.invoke(prompt, { signal: abortController?.signal })
+
+                if (typeof response === 'object') {
+                    finalResponse = '```json\n' + JSON.stringify(response, null, 2) + '\n```'
+                } else {
+                    finalResponse = response
+                }
+
+                if (isLastNode && sseStreamer) {
+                    sseStreamer.streamTokenEvent(chatId, finalResponse)
+                }
+            }
+
             const output = this.prepareOutputObject(
                 response,
                 availableTools,
@@ -1171,7 +1374,8 @@ class Agent_Agentflow implements INode {
                 artifacts,
                 additionalTokens,
                 isWaitingForHumanInput,
-                fileAnnotations
+                fileAnnotations,
+                isStructuredOutput
             )
 
             // End analytics tracking
@@ -1192,9 +1396,15 @@ 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
             )
@@ -1333,7 +1543,12 @@ class Agent_Agentflow implements INode {
         // Handle Gemini googleSearch tool
         if (groundingMetadata && groundingMetadata.webSearchQueries && Array.isArray(groundingMetadata.webSearchQueries)) {
             // Check for duplicates
-            if (!builtInUsedTools.find((tool) => tool.tool === 'googleSearch')) {
+            const isDuplicate = builtInUsedTools.find(
+                (tool) =>
+                    tool.tool === 'googleSearch' &&
+                    JSON.stringify((tool.toolInput as any)?.queries) === JSON.stringify(groundingMetadata.webSearchQueries)
+            )
+            if (!isDuplicate) {
                 builtInUsedTools.push({
                     tool: 'googleSearch',
                     toolInput: {
@@ -1347,7 +1562,12 @@ class Agent_Agentflow implements INode {
         // Handle Gemini urlContext tool
         if (urlContextMetadata && urlContextMetadata.urlMetadata && Array.isArray(urlContextMetadata.urlMetadata)) {
             // Check for duplicates
-            if (!builtInUsedTools.find((tool) => tool.tool === 'urlContext')) {
+            const isDuplicate = builtInUsedTools.find(
+                (tool) =>
+                    tool.tool === 'urlContext' &&
+                    JSON.stringify((tool.toolInput as any)?.urlMetadata) === JSON.stringify(urlContextMetadata.urlMetadata)
+            )
+            if (!isDuplicate) {
                 builtInUsedTools.push({
                     tool: 'urlContext',
                     toolInput: {
@@ -1358,45 +1578,53 @@ class Agent_Agentflow implements INode {
             }
         }
 
-        return builtInUsedTools
-    }
+        // Handle Gemini codeExecution tool
+        if (response.content && Array.isArray(response.content)) {
+            for (let i = 0; i < response.content.length; i++) {
+                const item = response.content[i]
 
-    /**
-     * 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
+                if (item.type === 'executableCode' && item.executableCode) {
+                    const language = item.executableCode.language || 'PYTHON'
+                    const code = item.executableCode.code || ''
+                    let toolOutput = ''
+
+                    // Check for duplicates
+                    const isDuplicate = builtInUsedTools.find(
+                        (tool) =>
+                            tool.tool === 'codeExecution' &&
+                            (tool.toolInput as any)?.language === language &&
+                            (tool.toolInput as any)?.code === code
+                    )
+                    if (isDuplicate) {
+                        continue
+                    }
+
+                    // Check the next item for the output
+                    const nextItem = i + 1 < response.content.length ? response.content[i + 1] : null
+
+                    if (nextItem) {
+                        if (nextItem.type === 'codeExecutionResult' && nextItem.codeExecutionResult) {
+                            const outcome = nextItem.codeExecutionResult.outcome
+                            const output = nextItem.codeExecutionResult.output || ''
+                            toolOutput = outcome === 'OUTCOME_OK' ? output : `Error: ${output}`
+                        } else if (nextItem.type === 'inlineData') {
+                            toolOutput = 'Generated image data'
+                        }
+                    }
+
+                    builtInUsedTools.push({
+                        tool: 'codeExecution',
+                        toolInput: {
+                            language,
+                            code
+                        },
+                        toolOutput
+                    })
+                }
             }
-
-            // Extract base64 data and create buffer
-            const base64Data = outputItem.result
-            const imageBuffer = Buffer.from(base64Data, 'base64')
-
-            // Determine file extension and MIME type
-            const outputFormat = outputItem.output_format || 'png'
-            const fileName = `generated_image_${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
         }
+
+        return builtInUsedTools
     }
 
     /**
@@ -1561,32 +1789,62 @@ class Agent_Agentflow implements INode {
         llmNodeInstance: BaseChatModel,
         messages: BaseMessageLike[],
         chatId: string,
-        abortController: AbortController
+        abortController: AbortController,
+        isStructuredOutput: boolean = false
     ): Promise<AIMessageChunk> {
         let response = new AIMessageChunk('')
 
         try {
             for await (const chunk of await llmNodeInstance.stream(messages, { signal: abortController?.signal })) {
-                if (sseStreamer) {
+                if (sseStreamer && !isStructuredOutput) {
                     let content = ''
-                    if (Array.isArray(chunk.content) && chunk.content.length > 0) {
-                        const contents = chunk.content as MessageContentText[]
-                        content = contents.map((item) => item.text).join('')
-                    } else {
+
+                    if (typeof chunk === 'string') {
+                        content = chunk
+                    } else if (Array.isArray(chunk.content) && chunk.content.length > 0) {
+                        content = chunk.content
+                            .map((item: any) => {
+                                if ((item.text && !item.type) || (item.type === 'text' && item.text)) {
+                                    return item.text
+                                } else if (item.type === 'executableCode' && item.executableCode) {
+                                    const language = item.executableCode.language?.toLowerCase() || 'python'
+                                    return `\n\`\`\`${language}\n${item.executableCode.code}\n\`\`\`\n`
+                                } else if (item.type === 'codeExecutionResult' && item.codeExecutionResult) {
+                                    const outcome = item.codeExecutionResult.outcome || 'OUTCOME_OK'
+                                    const output = item.codeExecutionResult.output || ''
+                                    if (outcome === 'OUTCOME_OK' && output) {
+                                        return `**Code Output:**\n\`\`\`\n${output}\n\`\`\`\n`
+                                    } else if (outcome !== 'OUTCOME_OK') {
+                                        return `**Code Execution Error:**\n\`\`\`\n${output}\n\`\`\`\n`
+                                    }
+                                }
+                                return ''
+                            })
+                            .filter((text: string) => text)
+                            .join('')
+                    } else if (chunk.content) {
                         content = chunk.content.toString()
                     }
                     sseStreamer.streamTokenEvent(chatId, content)
                 }
 
-                response = response.concat(chunk)
+                const messageChunk = typeof chunk === 'string' ? new AIMessageChunk(chunk) : chunk
+                response = response.concat(messageChunk)
             }
         } catch (error) {
             console.error('Error during streaming:', error)
             throw error
         }
+
+        // Only convert to string if all content items are text (no inlineData or other special types)
         if (Array.isArray(response.content) && response.content.length > 0) {
-            const responseContents = response.content as MessageContentText[]
-            response.content = responseContents.map((item) => item.text).join('')
+            const hasNonTextContent = response.content.some(
+                (item: any) => item.type === 'inlineData' || item.type === 'executableCode' || item.type === 'codeExecutionResult'
+            )
+            if (!hasNonTextContent) {
+                const responseContents = response.content as MessageContentText[]
+                response.content = responseContents.map((item) => item.text).join('')
+            }
         }
         return response
     }
@@ -1606,7 +1864,8 @@ class Agent_Agentflow implements INode {
         artifacts: any[],
         additionalTokens: number = 0,
         isWaitingForHumanInput: boolean = false,
-        fileAnnotations: any[] = []
+        fileAnnotations: any[] = [],
+        isStructuredOutput: boolean = false
     ): any {
         const output: any = {
             content: finalResponse,
@@ -1641,6 +1900,15 @@ class Agent_Agentflow implements INode {
             output.responseMetadata = response.response_metadata
         }
 
+        if (isStructuredOutput && typeof response === 'object') {
+            const structuredOutput = response as Record<string, any>
+            for (const key in structuredOutput) {
+                if (structuredOutput[key] !== undefined && structuredOutput[key] !== null) {
+                    output[key] = structuredOutput[key]
+                }
+            }
+        }
+
         // Add used tools, source documents and artifacts to output
         if (usedTools && usedTools.length > 0) {
             output.usedTools = flatten(usedTools)
@@ -1706,7 +1974,8 @@ class Agent_Agentflow implements INode {
         llmNodeInstance,
         isStreamable,
         isLastNode,
-        iterationContext
+        iterationContext,
+        isStructuredOutput = false
     }: {
         response: AIMessageChunk
         messages: BaseMessageLike[]
@@ -1720,6 +1989,7 @@ class Agent_Agentflow implements INode {
         isStreamable: boolean
         isLastNode: boolean
         iterationContext: ICommonObject
+        isStructuredOutput?: boolean
     }): Promise<{
         response: AIMessageChunk
         usedTools: IUsedTool[]
@@ -1799,7 +2069,9 @@ class Agent_Agentflow implements INode {
                     const toolCallDetails = '```json\n' + JSON.stringify(toolCall, null, 2) + '\n```'
                     const responseContent = response.content + `\nAttempting to use tool:\n${toolCallDetails}`
                     response.content = responseContent
-                    sseStreamer?.streamTokenEvent(chatId, responseContent)
+                    if (!isStructuredOutput) {
+                        sseStreamer?.streamTokenEvent(chatId, responseContent)
+                    }
                     return { response, usedTools, sourceDocuments, artifacts, totalTokens, isWaitingForHumanInput: true }
                 }
 
@@ -1905,7 +2177,7 @@ class Agent_Agentflow implements INode {
                 const lastToolOutput = usedTools[0]?.toolOutput || ''
                 const lastToolOutputString = typeof lastToolOutput === 'string' ? lastToolOutput : JSON.stringify(lastToolOutput, null, 2)
 
-                if (sseStreamer) {
+                if (sseStreamer && !isStructuredOutput) {
                     sseStreamer.streamTokenEvent(chatId, lastToolOutputString)
                 }
 
@@ -1934,12 +2206,19 @@ class Agent_Agentflow implements INode {
         let newResponse: AIMessageChunk
 
         if (isStreamable) {
-            newResponse = await this.handleStreamingResponse(sseStreamer, llmNodeInstance, messages, chatId, abortController)
+            newResponse = await this.handleStreamingResponse(
+                sseStreamer,
+                llmNodeInstance,
+                messages,
+                chatId,
+                abortController,
+                isStructuredOutput
+            )
         } else {
             newResponse = await llmNodeInstance.invoke(messages, { signal: abortController?.signal })
 
             // Stream non-streaming response if this is the last node
-            if (isLastNode && sseStreamer) {
+            if (isLastNode && sseStreamer && !isStructuredOutput) {
                 let responseContent = JSON.stringify(newResponse, null, 2)
                 if (typeof newResponse.content === 'string') {
                     responseContent = newResponse.content
@@ -1974,7 +2253,8 @@ class Agent_Agentflow implements INode {
                 llmNodeInstance,
                 isStreamable,
                 isLastNode,
-                iterationContext
+                iterationContext,
+                isStructuredOutput
             })
 
             // Merge results from recursive tool calls
@@ -2005,7 +2285,8 @@ class Agent_Agentflow implements INode {
         llmWithoutToolsBind,
         isStreamable,
         isLastNode,
-        iterationContext
+        iterationContext,
+        isStructuredOutput = false
     }: {
         humanInput: IHumanInput
         humanInputAction: Record<string, any> | undefined
@@ -2020,6 +2301,7 @@ class Agent_Agentflow implements INode {
         isStreamable: boolean
         isLastNode: boolean
         iterationContext: ICommonObject
+        isStructuredOutput?: boolean
     }): Promise<{
         response: AIMessageChunk
         usedTools: IUsedTool[]
@@ -2222,7 +2504,7 @@ class Agent_Agentflow implements INode {
                 const lastToolOutput = usedTools[0]?.toolOutput || ''
                 const lastToolOutputString = typeof lastToolOutput === 'string' ? lastToolOutput : JSON.stringify(lastToolOutput, null, 2)
 
-                if (sseStreamer) {
+                if (sseStreamer && !isStructuredOutput) {
                     sseStreamer.streamTokenEvent(chatId, lastToolOutputString)
                 }
 
@@ -2253,12 +2535,19 @@ class Agent_Agentflow implements INode {
         }
 
         if (isStreamable) {
-            newResponse = await this.handleStreamingResponse(sseStreamer, llmNodeInstance, messages, chatId, abortController)
+            newResponse = await this.handleStreamingResponse(
+                sseStreamer,
+                llmNodeInstance,
+                messages,
+                chatId,
+                abortController,
+                isStructuredOutput
+            )
         } else {
             newResponse = await llmNodeInstance.invoke(messages, { signal: abortController?.signal })
 
             // Stream non-streaming response if this is the last node
-            if (isLastNode && sseStreamer) {
+            if (isLastNode && sseStreamer && !isStructuredOutput) {
                 let responseContent = JSON.stringify(newResponse, null, 2)
                 if (typeof newResponse.content === 'string') {
                     responseContent = newResponse.content
@@ -2293,7 +2582,8 @@ class Agent_Agentflow implements INode {
                 llmNodeInstance,
                 isStreamable,
                 isLastNode,
-                iterationContext
+                iterationContext,
+                isStructuredOutput
             })
 
             // Merge results from recursive tool calls
@@ -2308,190 +2598,6 @@ 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/Condition/Condition.ts

@@ -317,7 +317,7 @@ class Condition_Agentflow implements INode {
             }
         }
 
-        // If no condition is fullfilled, add isFulfilled to the ELSE condition
+        // If no condition is fulfilled, add isFulfilled to the ELSE condition
         const dummyElseConditionData = {
             type: 'string',
             value1: '',

packages/components/nodes/agentflow/CustomFunction/CustomFunction.ts

@@ -60,7 +60,7 @@ class CustomFunction_Agentflow implements INode {
     constructor() {
         this.label = 'Custom Function'
         this.name = 'customFunctionAgentflow'
-        this.version = 1.0
+        this.version = 1.1
         this.type = 'CustomFunction'
         this.category = 'Agent Flows'
         this.description = 'Execute custom function'
@@ -107,8 +107,7 @@ class CustomFunction_Agentflow implements INode {
                         label: 'Key',
                         name: 'key',
                         type: 'asyncOptions',
-                        loadMethod: 'listRuntimeStateKeys',
-                        freeSolo: true
+                        loadMethod: 'listRuntimeStateKeys'
                     },
                     {
                         label: 'Value',
@@ -134,7 +133,7 @@ class CustomFunction_Agentflow implements INode {
 
     async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<any> {
         const javascriptFunction = nodeData.inputs?.customFunctionJavascriptFunction as string
-        const functionInputVariables = nodeData.inputs?.customFunctionInputVariables as ICustomFunctionInputVariables[]
+        const functionInputVariables = (nodeData.inputs?.customFunctionInputVariables as ICustomFunctionInputVariables[]) ?? []
         const _customFunctionUpdateState = nodeData.inputs?.customFunctionUpdateState
 
         const state = options.agentflowRuntime?.state as ICommonObject
@@ -147,11 +146,17 @@ class CustomFunction_Agentflow implements INode {
 
         const variables = await getVars(appDataSource, databaseEntities, nodeData, options)
         const flow = {
+            input,
+            state,
             chatflowId: options.chatflowid,
             sessionId: options.sessionId,
             chatId: options.chatId,
-            input,
-            state
+            rawOutput: options.postProcessing?.rawOutput || '',
+            chatHistory: options.postProcessing?.chatHistory || [],
+            sourceDocuments: options.postProcessing?.sourceDocuments,
+            usedTools: options.postProcessing?.usedTools,
+            artifacts: options.postProcessing?.artifacts,
+            fileAnnotations: options.postProcessing?.fileAnnotations
         }
 
         // Create additional sandbox variables for custom function inputs

packages/components/nodes/agentflow/ExecuteFlow/ExecuteFlow.ts

@@ -30,7 +30,7 @@ class ExecuteFlow_Agentflow implements INode {
     constructor() {
         this.label = 'Execute Flow'
         this.name = 'executeFlowAgentflow'
-        this.version = 1.1
+        this.version = 1.2
         this.type = 'ExecuteFlow'
         this.category = 'Agent Flows'
         this.description = 'Execute another flow'
@@ -102,8 +102,7 @@ class ExecuteFlow_Agentflow implements INode {
                         label: 'Key',
                         name: 'key',
                         type: 'asyncOptions',
-                        loadMethod: 'listRuntimeStateKeys',
-                        freeSolo: true
+                        loadMethod: 'listRuntimeStateKeys'
                     },
                     {
                         label: 'Value',

packages/components/nodes/agentflow/HumanInput/HumanInput.ts

@@ -241,8 +241,11 @@ class HumanInput_Agentflow implements INode {
                     if (isStreamable) {
                         const sseStreamer: IServerSideEventStreamer = options.sseStreamer as IServerSideEventStreamer
                         for await (const chunk of await llmNodeInstance.stream(messages)) {
-                            sseStreamer.streamTokenEvent(chatId, chunk.content.toString())
-                            response = response.concat(chunk)
+                            const content = typeof chunk === 'string' ? chunk : chunk.content.toString()
+                            sseStreamer.streamTokenEvent(chatId, content)
+
+                            const messageChunk = typeof chunk === 'string' ? new AIMessageChunk(chunk) : chunk
+                            response = response.concat(messageChunk)
                         }
                         humanInputDescription = response.content as string
                     } else {

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

@@ -2,17 +2,19 @@ import { BaseChatModel } from '@langchain/core/language_models/chat_models'
 import { ICommonObject, IMessage, INode, INodeData, INodeOptionsValue, INodeParams, IServerSideEventStreamer } from '../../../src/Interface'
 import { AIMessageChunk, BaseMessageLike, MessageContentText } from '@langchain/core/messages'
 import { DEFAULT_SUMMARIZER_TEMPLATE } from '../prompt'
-import { z } from 'zod'
 import { AnalyticHandler } from '../../../src/handler'
-import { ILLMMessage, IStructuredOutput } from '../Interface.Agentflow'
+import { ILLMMessage } from '../Interface.Agentflow'
 import {
+    addImageArtifactsToMessages,
+    extractArtifactsFromResponse,
     getPastChatHistoryImageMessages,
     getUniqueImageMessages,
     processMessagesWithImages,
     replaceBase64ImagesWithFileReferences,
+    replaceInlineDataWithFileReferences,
     updateFlowState
 } from '../utils'
-import { processTemplateVariables } from '../../../src/utils'
+import { processTemplateVariables, configureStructuredOutput } from '../../../src/utils'
 import { flatten } from 'lodash'
 
 class LLM_Agentflow implements INode {
@@ -32,7 +34,7 @@ class LLM_Agentflow implements INode {
     constructor() {
         this.label = 'LLM'
         this.name = 'llmAgentflow'
-        this.version = 1.0
+        this.version = 1.1
         this.type = 'LLM'
         this.category = 'Agent Flows'
         this.description = 'Large language models to analyze user-provided inputs and generate responses'
@@ -288,8 +290,7 @@ class LLM_Agentflow implements INode {
                         label: 'Key',
                         name: 'key',
                         type: 'asyncOptions',
-                        loadMethod: 'listRuntimeStateKeys',
-                        freeSolo: true
+                        loadMethod: 'listRuntimeStateKeys'
                     },
                     {
                         label: 'Value',
@@ -449,10 +450,16 @@ 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) {
-                llmNodeInstance = this.configureStructuredOutput(llmNodeInstance, _llmStructuredOutput)
+                llmNodeInstance = configureStructuredOutput(llmNodeInstance, _llmStructuredOutput)
             }
 
             // Initialize response and determine if streaming is possible
@@ -468,9 +475,11 @@ 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 {
@@ -495,6 +504,40 @@ 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) {
@@ -514,10 +557,22 @@ 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) {
@@ -529,12 +584,23 @@ 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
             )
@@ -585,7 +651,13 @@ 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 })
+                            }
+                        })
                     }
                 ]
             }
@@ -755,59 +827,6 @@ class LLM_Agentflow implements INode {
         }
     }
 
-    /**
-     * Configures structured output for the LLM
-     */
-    private configureStructuredOutput(llmNodeInstance: BaseChatModel, llmStructuredOutput: IStructuredOutput[]): BaseChatModel {
-        try {
-            const zodObj: ICommonObject = {}
-            for (const sch of llmStructuredOutput) {
-                if (sch.type === 'string') {
-                    zodObj[sch.key] = z.string().describe(sch.description || '')
-                } else if (sch.type === 'stringArray') {
-                    zodObj[sch.key] = z.array(z.string()).describe(sch.description || '')
-                } else if (sch.type === 'number') {
-                    zodObj[sch.key] = z.number().describe(sch.description || '')
-                } else if (sch.type === 'boolean') {
-                    zodObj[sch.key] = z.boolean().describe(sch.description || '')
-                } else if (sch.type === 'enum') {
-                    const enumValues = sch.enumValues?.split(',').map((item: string) => item.trim()) || []
-                    zodObj[sch.key] = z
-                        .enum(enumValues.length ? (enumValues as [string, ...string[]]) : ['default'])
-                        .describe(sch.description || '')
-                } else if (sch.type === 'jsonArray') {
-                    const jsonSchema = sch.jsonSchema
-                    if (jsonSchema) {
-                        try {
-                            // Parse the JSON schema
-                            const schemaObj = JSON.parse(jsonSchema)
-
-                            // Create a Zod schema from the JSON schema
-                            const itemSchema = this.createZodSchemaFromJSON(schemaObj)
-
-                            // Create an array schema of the item schema
-                            zodObj[sch.key] = z.array(itemSchema).describe(sch.description || '')
-                        } catch (err) {
-                            console.error(`Error parsing JSON schema for ${sch.key}:`, err)
-                            // Fallback to generic array of records
-                            zodObj[sch.key] = z.array(z.record(z.any())).describe(sch.description || '')
-                        }
-                    } else {
-                        // If no schema provided, use generic array of records
-                        zodObj[sch.key] = z.array(z.record(z.any())).describe(sch.description || '')
-                    }
-                }
-            }
-            const structuredOutput = z.object(zodObj)
-
-            // @ts-ignore
-            return llmNodeInstance.withStructuredOutput(structuredOutput)
-        } catch (exception) {
-            console.error(exception)
-            return llmNodeInstance
-        }
-    }
-
     /**
      * Handles streaming response from the LLM
      */
@@ -824,16 +843,20 @@ class LLM_Agentflow implements INode {
             for await (const chunk of await llmNodeInstance.stream(messages, { signal: abortController?.signal })) {
                 if (sseStreamer) {
                     let content = ''
-                    if (Array.isArray(chunk.content) && chunk.content.length > 0) {
+
+                    if (typeof chunk === 'string') {
+                        content = chunk
+                    } else if (Array.isArray(chunk.content) && chunk.content.length > 0) {
                         const contents = chunk.content as MessageContentText[]
                         content = contents.map((item) => item.text).join('')
-                    } else {
+                    } else if (chunk.content) {
                         content = chunk.content.toString()
                     }
                     sseStreamer.streamTokenEvent(chatId, content)
                 }
 
-                response = response.concat(chunk)
+                const messageChunk = typeof chunk === 'string' ? new AIMessageChunk(chunk) : chunk
+                response = response.concat(messageChunk)
             }
         } catch (error) {
             console.error('Error during streaming:', error)
@@ -855,7 +878,9 @@ 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,
@@ -874,6 +899,10 @@ 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) {
@@ -883,6 +912,14 @@ class LLM_Agentflow implements INode {
             }
         }
 
+        if (artifacts && artifacts.length > 0) {
+            output.artifacts = flatten(artifacts)
+        }
+
+        if (fileAnnotations && fileAnnotations.length > 0) {
+            output.fileAnnotations = fileAnnotations
+        }
+
         return output
     }
 
@@ -907,107 +944,6 @@ class LLM_Agentflow implements INode {
 
         sseStreamer.streamEndEvent(chatId)
     }
-
-    /**
-     * Creates a Zod schema from a JSON schema object
-     * @param jsonSchema The JSON schema object
-     * @returns A Zod schema
-     */
-    private createZodSchemaFromJSON(jsonSchema: any): z.ZodTypeAny {
-        // If the schema is an object with properties, create an object schema
-        if (typeof jsonSchema === 'object' && jsonSchema !== null) {
-            const schemaObj: Record<string, z.ZodTypeAny> = {}
-
-            // Process each property in the schema
-            for (const [key, value] of Object.entries(jsonSchema)) {
-                if (value === null) {
-                    // Handle null values
-                    schemaObj[key] = z.null()
-                } else if (typeof value === 'object' && !Array.isArray(value)) {
-                    // Check if the property has a type definition
-                    if ('type' in value) {
-                        const type = value.type as string
-                        const description = ('description' in value ? (value.description as string) : '') || ''
-
-                        // Create the appropriate Zod type based on the type property
-                        if (type === 'string') {
-                            schemaObj[key] = z.string().describe(description)
-                        } else if (type === 'number') {
-                            schemaObj[key] = z.number().describe(description)
-                        } else if (type === 'boolean') {
-                            schemaObj[key] = z.boolean().describe(description)
-                        } else if (type === 'array') {
-                            // If it's an array type, check if items is defined
-                            if ('items' in value && value.items) {
-                                const itemSchema = this.createZodSchemaFromJSON(value.items)
-                                schemaObj[key] = z.array(itemSchema).describe(description)
-                            } else {
-                                // Default to array of any if items not specified
-                                schemaObj[key] = z.array(z.any()).describe(description)
-                            }
-                        } else if (type === 'object') {
-                            // If it's an object type, check if properties is defined
-                            if ('properties' in value && value.properties) {
-                                const nestedSchema = this.createZodSchemaFromJSON(value.properties)
-                                schemaObj[key] = nestedSchema.describe(description)
-                            } else {
-                                // Default to record of any if properties not specified
-                                schemaObj[key] = z.record(z.any()).describe(description)
-                            }
-                        } else {
-                            // Default to any for unknown types
-                            schemaObj[key] = z.any().describe(description)
-                        }
-
-                        // Check if the property is optional
-                        if ('optional' in value && value.optional === true) {
-                            schemaObj[key] = schemaObj[key].optional()
-                        }
-                    } else if (Array.isArray(value)) {
-                        // Array values without a type property
-                        if (value.length > 0) {
-                            // If the array has items, recursively create a schema for the first item
-                            const itemSchema = this.createZodSchemaFromJSON(value[0])
-                            schemaObj[key] = z.array(itemSchema)
-                        } else {
-                            // Empty array, allow any array
-                            schemaObj[key] = z.array(z.any())
-                        }
-                    } else {
-                        // It's a nested object without a type property, recursively create schema
-                        schemaObj[key] = this.createZodSchemaFromJSON(value)
-                    }
-                } else if (Array.isArray(value)) {
-                    // Array values
-                    if (value.length > 0) {
-                        // If the array has items, recursively create a schema for the first item
-                        const itemSchema = this.createZodSchemaFromJSON(value[0])
-                        schemaObj[key] = z.array(itemSchema)
-                    } else {
-                        // Empty array, allow any array
-                        schemaObj[key] = z.array(z.any())
-                    }
-                } else {
-                    // For primitive values (which shouldn't be in the schema directly)
-                    // Use the corresponding Zod type
-                    if (typeof value === 'string') {
-                        schemaObj[key] = z.string()
-                    } else if (typeof value === 'number') {
-                        schemaObj[key] = z.number()
-                    } else if (typeof value === 'boolean') {
-                        schemaObj[key] = z.boolean()
-                    } else {
-                        schemaObj[key] = z.any()
-                    }
-                }
-            }
-
-            return z.object(schemaObj)
-        }
-
-        // Fallback to any for unknown types
-        return z.any()
-    }
 }
 
 module.exports = { nodeClass: LLM_Agentflow }

packages/components/nodes/agentflow/Loop/Loop.ts

@@ -20,7 +20,7 @@ class Loop_Agentflow implements INode {
     constructor() {
         this.label = 'Loop'
         this.name = 'loopAgentflow'
-        this.version = 1.1
+        this.version = 1.2
         this.type = 'Loop'
         this.category = 'Agent Flows'
         this.description = 'Loop back to a previous node'
@@ -64,8 +64,7 @@ class Loop_Agentflow implements INode {
                         label: 'Key',
                         name: 'key',
                         type: 'asyncOptions',
-                        loadMethod: 'listRuntimeStateKeys',
-                        freeSolo: true
+                        loadMethod: 'listRuntimeStateKeys'
                     },
                     {
                         label: 'Value',

packages/components/nodes/agentflow/Retriever/Retriever.ts

@@ -36,7 +36,7 @@ class Retriever_Agentflow implements INode {
     constructor() {
         this.label = 'Retriever'
         this.name = 'retrieverAgentflow'
-        this.version = 1.0
+        this.version = 1.1
         this.type = 'Retriever'
         this.category = 'Agent Flows'
         this.description = 'Retrieve information from vector database'
@@ -87,8 +87,7 @@ class Retriever_Agentflow implements INode {
                         label: 'Key',
                         name: 'key',
                         type: 'asyncOptions',
-                        loadMethod: 'listRuntimeStateKeys',
-                        freeSolo: true
+                        loadMethod: 'listRuntimeStateKeys'
                     },
                     {
                         label: 'Value',

packages/components/nodes/agentflow/Tool/Tool.ts

@@ -29,7 +29,7 @@ class Tool_Agentflow implements INode {
     constructor() {
         this.label = 'Tool'
         this.name = 'toolAgentflow'
-        this.version = 1.1
+        this.version = 1.2
         this.type = 'Tool'
         this.category = 'Agent Flows'
         this.description = 'Tools allow LLM to interact with external systems'
@@ -80,8 +80,7 @@ class Tool_Agentflow implements INode {
                         label: 'Key',
                         name: 'key',
                         type: 'asyncOptions',
-                        loadMethod: 'listRuntimeStateKeys',
-                        freeSolo: true
+                        loadMethod: 'listRuntimeStateKeys'
                     },
                     {
                         label: 'Value',

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 { ICommonObject, IFileUpload } from '../../src/Interface'
+import { addSingleFileToStorage, getFileFromStorage } from '../../src/storageUtils'
+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/agents/ConversationalRetrievalToolAgent/ConversationalRetrievalToolAgent.ts

@@ -5,7 +5,7 @@ import { RunnableSequence } from '@langchain/core/runnables'
 import { BaseChatModel } from '@langchain/core/language_models/chat_models'
 import { ChatPromptTemplate, MessagesPlaceholder, HumanMessagePromptTemplate, PromptTemplate } from '@langchain/core/prompts'
 import { formatToOpenAIToolMessages } from 'langchain/agents/format_scratchpad/openai_tools'
-import { getBaseClasses, transformBracesWithColon } from '../../../src/utils'
+import { getBaseClasses, transformBracesWithColon, convertChatHistoryToText, convertBaseMessagetoIMessage } from '../../../src/utils'
 import { type ToolsAgentStep } from 'langchain/agents/openai/output_parser'
 import {
     FlowiseMemory,
@@ -23,8 +23,10 @@ import { Moderation, checkInputs, streamResponse } from '../../moderation/Modera
 import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 import type { Document } from '@langchain/core/documents'
 import { BaseRetriever } from '@langchain/core/retrievers'
-import { RESPONSE_TEMPLATE } from '../../chains/ConversationalRetrievalQAChain/prompts'
+import { RESPONSE_TEMPLATE, REPHRASE_TEMPLATE } from '../../chains/ConversationalRetrievalQAChain/prompts'
 import { addImagesToMessages, llmSupportsVision } from '../../../src/multiModalUtils'
+import { StringOutputParser } from '@langchain/core/output_parsers'
+import { Tool } from '@langchain/core/tools'
 
 class ConversationalRetrievalToolAgent_Agents implements INode {
     label: string
@@ -42,7 +44,7 @@ class ConversationalRetrievalToolAgent_Agents implements INode {
     constructor(fields?: { sessionId?: string }) {
         this.label = 'Conversational Retrieval Tool Agent'
         this.name = 'conversationalRetrievalToolAgent'
-        this.author = 'niztal(falkor)'
+        this.author = 'niztal(falkor) and nikitas-novatix'
         this.version = 1.0
         this.type = 'AgentExecutor'
         this.category = 'Agents'
@@ -79,6 +81,26 @@ class ConversationalRetrievalToolAgent_Agents implements INode {
                 optional: true,
                 default: RESPONSE_TEMPLATE
             },
+            {
+                label: 'Rephrase Prompt',
+                name: 'rephrasePrompt',
+                type: 'string',
+                description: 'Using previous chat history, rephrase question into a standalone question',
+                warning: 'Prompt must include input variables: {chat_history} and {question}',
+                rows: 4,
+                additionalParams: true,
+                optional: true,
+                default: REPHRASE_TEMPLATE
+            },
+            {
+                label: 'Rephrase Model',
+                name: 'rephraseModel',
+                type: 'BaseChatModel',
+                description:
+                    'Optional: Use a different (faster/cheaper) model for rephrasing. If not specified, uses the main Tool Calling Chat Model.',
+                optional: true,
+                additionalParams: true
+            },
             {
                 label: 'Input Moderation',
                 description: 'Detect text that could generate harmful output and prevent it from being sent to the language model',
@@ -103,8 +125,9 @@ class ConversationalRetrievalToolAgent_Agents implements INode {
         this.sessionId = fields?.sessionId
     }
 
-    async init(nodeData: INodeData, input: string, options: ICommonObject): Promise<any> {
-        return prepareAgent(nodeData, options, { sessionId: this.sessionId, chatId: options.chatId, input })
+    // The agent will be prepared in run() with the correct user message - it needs the actual runtime input for rephrasing
+    async init(_nodeData: INodeData, _input: string, _options: ICommonObject): Promise<any> {
+        return null
     }
 
     async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | ICommonObject> {
@@ -148,6 +171,23 @@ class ConversationalRetrievalToolAgent_Agents implements INode {
                 sseStreamer.streamUsedToolsEvent(chatId, res.usedTools)
                 usedTools = res.usedTools
             }
+
+            // If the tool is set to returnDirect, stream the output to the client
+            if (res.usedTools && res.usedTools.length) {
+                let inputTools = nodeData.inputs?.tools
+                inputTools = flatten(inputTools)
+                for (const tool of res.usedTools) {
+                    const inputTool = inputTools.find((inputTool: Tool) => inputTool.name === tool.tool)
+                    if (inputTool && (inputTool as any).returnDirect && shouldStreamResponse) {
+                        sseStreamer.streamTokenEvent(chatId, tool.toolOutput)
+                        // Prevent CustomChainHandler from streaming the same output again
+                        if (res.output === tool.toolOutput) {
+                            res.output = ''
+                        }
+                    }
+                }
+            }
+            // The CustomChainHandler will send the stream end event
         } else {
             res = await executor.invoke({ input }, { callbacks: [loggerHandler, ...callbacks] })
             if (res.sourceDocuments) {
@@ -210,9 +250,11 @@ const prepareAgent = async (
     flowObj: { sessionId?: string; chatId?: string; input?: string }
 ) => {
     const model = nodeData.inputs?.model as BaseChatModel
+    const rephraseModel = (nodeData.inputs?.rephraseModel as BaseChatModel) || model // Use main model if not specified
     const maxIterations = nodeData.inputs?.maxIterations as string
     const memory = nodeData.inputs?.memory as FlowiseMemory
     let systemMessage = nodeData.inputs?.systemMessage as string
+    let rephrasePrompt = nodeData.inputs?.rephrasePrompt as string
     let tools = nodeData.inputs?.tools
     tools = flatten(tools)
     const memoryKey = memory.memoryKey ? memory.memoryKey : 'chat_history'
@@ -220,6 +262,9 @@ const prepareAgent = async (
     const vectorStoreRetriever = nodeData.inputs?.vectorStoreRetriever as BaseRetriever
 
     systemMessage = transformBracesWithColon(systemMessage)
+    if (rephrasePrompt) {
+        rephrasePrompt = transformBracesWithColon(rephrasePrompt)
+    }
 
     const prompt = ChatPromptTemplate.fromMessages([
         ['system', systemMessage ? systemMessage : `You are a helpful AI assistant.`],
@@ -263,6 +308,37 @@ const prepareAgent = async (
 
     const modelWithTools = model.bindTools(tools)
 
+    // Function to get standalone question (either rephrased or original)
+    const getStandaloneQuestion = async (input: string): Promise<string> => {
+        // If no rephrase prompt, return the original input
+        if (!rephrasePrompt) {
+            return input
+        }
+
+        // Get chat history (use empty string if none)
+        const messages = (await memory.getChatMessages(flowObj?.sessionId, true)) as BaseMessage[]
+        const iMessages = convertBaseMessagetoIMessage(messages)
+        const chatHistoryString = convertChatHistoryToText(iMessages)
+
+        // Always rephrase to normalize/expand user queries for better retrieval
+        try {
+            const CONDENSE_QUESTION_PROMPT = PromptTemplate.fromTemplate(rephrasePrompt)
+            const condenseQuestionChain = RunnableSequence.from([CONDENSE_QUESTION_PROMPT, rephraseModel, new StringOutputParser()])
+            const res = await condenseQuestionChain.invoke({
+                question: input,
+                chat_history: chatHistoryString
+            })
+            return res
+        } catch (error) {
+            console.error('Error rephrasing question:', error)
+            // On error, fall back to original input
+            return input
+        }
+    }
+
+    // Get standalone question before creating runnable
+    const standaloneQuestion = await getStandaloneQuestion(flowObj?.input || '')
+
     const runnableAgent = RunnableSequence.from([
         {
             [inputKey]: (i: { input: string; steps: ToolsAgentStep[] }) => i.input,
@@ -272,7 +348,9 @@ const prepareAgent = async (
                 return messages ?? []
             },
             context: async (i: { input: string; chatHistory?: string }) => {
-                const relevantDocs = await vectorStoreRetriever.invoke(i.input)
+                // Use the standalone question (rephrased or original) for retrieval
+                const retrievalQuery = standaloneQuestion || i.input
+                const relevantDocs = await vectorStoreRetriever.invoke(retrievalQuery)
                 const formattedDocs = formatDocs(relevantDocs)
                 return formattedDocs
             }
@@ -295,4 +373,6 @@ const prepareAgent = async (
     return executor
 }
 
-module.exports = { nodeClass: ConversationalRetrievalToolAgent_Agents }
+module.exports = {
+    nodeClass: ConversationalRetrievalToolAgent_Agents
+}

packages/components/nodes/agents/OpenAIAssistant/OpenAIAssistant.ts

@@ -578,7 +578,7 @@ class OpenAIAssistant_Agents implements INode {
                                         toolOutput
                                     })
                                 } catch (e) {
-                                    await analyticHandlers.onToolEnd(toolIds, e)
+                                    await analyticHandlers.onToolError(toolIds, e)
                                     console.error('Error executing tool', e)
                                     throw new Error(
                                         `Error executing tool. Tool: ${tool.name}. Thread ID: ${threadId}. Run ID: ${runThreadId}`
@@ -703,7 +703,7 @@ class OpenAIAssistant_Agents implements INode {
                                                 toolOutput
                                             })
                                         } catch (e) {
-                                            await analyticHandlers.onToolEnd(toolIds, e)
+                                            await analyticHandlers.onToolError(toolIds, e)
                                             console.error('Error executing tool', e)
                                             clearInterval(timeout)
                                             reject(
@@ -1096,7 +1096,7 @@ async function handleToolSubmission(params: ToolSubmissionParams): Promise<ToolS
                                 toolOutput
                             })
                         } catch (e) {
-                            await analyticHandlers.onToolEnd(toolIds, e)
+                            await analyticHandlers.onToolError(toolIds, e)
                             console.error('Error executing tool', e)
                             throw new Error(`Error executing tool. Tool: ${tool.name}. Thread ID: ${threadId}. Run ID: ${runThreadId}`)
                         }

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
     })

packages/components/nodes/chatmodels/ChatHuggingFace/ChatHuggingFace.ts

@@ -41,15 +41,17 @@ class ChatHuggingFace_ChatModels implements INode {
                 label: 'Model',
                 name: 'model',
                 type: 'string',
-                description: 'If using own inference endpoint, leave this blank',
-                placeholder: 'gpt2'
+                description:
+                    'Model name (e.g., deepseek-ai/DeepSeek-V3.2-Exp:novita). If model includes provider (:) or using router endpoint, leave Endpoint blank.',
+                placeholder: 'deepseek-ai/DeepSeek-V3.2-Exp:novita'
             },
             {
                 label: 'Endpoint',
                 name: 'endpoint',
                 type: 'string',
                 placeholder: 'https://xyz.eu-west-1.aws.endpoints.huggingface.cloud/gpt2',
-                description: 'Using your own inference endpoint',
+                description:
+                    'Custom inference endpoint (optional). Not needed for models with providers (:) or router endpoints. Leave blank to use Inference Providers.',
                 optional: true
             },
             {
@@ -103,7 +105,7 @@ class ChatHuggingFace_ChatModels implements INode {
                 type: 'string',
                 rows: 4,
                 placeholder: 'AI assistant:',
-                description: 'Sets the stop sequences to use. Use comma to seperate different sequences.',
+                description: 'Sets the stop sequences to use. Use comma to separate different sequences.',
                 optional: true,
                 additionalParams: true
             }
@@ -124,6 +126,15 @@ class ChatHuggingFace_ChatModels implements INode {
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const huggingFaceApiKey = getCredentialParam('huggingFaceApiKey', credentialData, nodeData)
 
+        if (!huggingFaceApiKey) {
+            console.error('[ChatHuggingFace] API key validation failed: No API key found')
+            throw new Error('HuggingFace API key is required. Please configure it in the credential settings.')
+        }
+
+        if (!huggingFaceApiKey.startsWith('hf_')) {
+            console.warn('[ChatHuggingFace] API key format warning: Key does not start with "hf_"')
+        }
+
         const obj: Partial<HFInput> = {
             model,
             apiKey: huggingFaceApiKey

packages/components/nodes/chatmodels/ChatHuggingFace/core.ts

@@ -56,9 +56,9 @@ export class HuggingFaceInference extends LLM implements HFInput {
         this.apiKey = fields?.apiKey ?? getEnvironmentVariable('HUGGINGFACEHUB_API_KEY')
         this.endpointUrl = fields?.endpointUrl
         this.includeCredentials = fields?.includeCredentials
-        if (!this.apiKey) {
+        if (!this.apiKey || this.apiKey.trim() === '') {
             throw new Error(
-                'Please set an API key for HuggingFace Hub in the environment variable HUGGINGFACEHUB_API_KEY or in the apiKey field of the HuggingFaceInference constructor.'
+                'Please set an API key for HuggingFace Hub. Either configure it in the credential settings in the UI, or set the environment variable HUGGINGFACEHUB_API_KEY.'
             )
         }
     }
@@ -68,19 +68,21 @@ export class HuggingFaceInference extends LLM implements HFInput {
     }
 
     invocationParams(options?: this['ParsedCallOptions']) {
-        return {
-            model: this.model,
-            parameters: {
-                // make it behave similar to openai, returning only the generated text
-                return_full_text: false,
-                temperature: this.temperature,
-                max_new_tokens: this.maxTokens,
-                stop: options?.stop ?? this.stopSequences,
-                top_p: this.topP,
-                top_k: this.topK,
-                repetition_penalty: this.frequencyPenalty
-            }
+        // Return parameters compatible with chatCompletion API (OpenAI-compatible format)
+        const params: any = {
+            temperature: this.temperature,
+            max_tokens: this.maxTokens,
+            stop: options?.stop ?? this.stopSequences,
+            top_p: this.topP
         }
+        // Include optional parameters if they are defined
+        if (this.topK !== undefined) {
+            params.top_k = this.topK
+        }
+        if (this.frequencyPenalty !== undefined) {
+            params.frequency_penalty = this.frequencyPenalty
+        }
+        return params
     }
 
     async *_streamResponseChunks(
@@ -88,51 +90,109 @@ export class HuggingFaceInference extends LLM implements HFInput {
         options: this['ParsedCallOptions'],
         runManager?: CallbackManagerForLLMRun
     ): AsyncGenerator<GenerationChunk> {
-        const hfi = await this._prepareHFInference()
-        const stream = await this.caller.call(async () =>
-            hfi.textGenerationStream({
-                ...this.invocationParams(options),
-                inputs: prompt
-            })
-        )
-        for await (const chunk of stream) {
-            const token = chunk.token.text
-            yield new GenerationChunk({ text: token, generationInfo: chunk })
-            await runManager?.handleLLMNewToken(token ?? '')
-
-            // stream is done
-            if (chunk.generated_text)
-                yield new GenerationChunk({
-                    text: '',
-                    generationInfo: { finished: true }
+        try {
+            const client = await this._prepareHFInference()
+            const stream = await this.caller.call(async () =>
+                client.chatCompletionStream({
+                    model: this.model,
+                    messages: [{ role: 'user', content: prompt }],
+                    ...this.invocationParams(options)
                 })
+            )
+            for await (const chunk of stream) {
+                const token = chunk.choices[0]?.delta?.content || ''
+                if (token) {
+                    yield new GenerationChunk({ text: token, generationInfo: chunk })
+                    await runManager?.handleLLMNewToken(token)
+                }
+                // stream is done when finish_reason is set
+                if (chunk.choices[0]?.finish_reason) {
+                    yield new GenerationChunk({
+                        text: '',
+                        generationInfo: { finished: true }
+                    })
+                    break
+                }
+            }
+        } catch (error: any) {
+            console.error('[ChatHuggingFace] Error in _streamResponseChunks:', error)
+            // Provide more helpful error messages
+            if (error?.message?.includes('endpointUrl') || error?.message?.includes('third-party provider')) {
+                throw new Error(
+                    `Cannot use custom endpoint with model "${this.model}" that includes a provider. Please leave the Endpoint field blank in the UI. Original error: ${error.message}`
+                )
+            }
+            throw error
         }
     }
 
     /** @ignore */
     async _call(prompt: string, options: this['ParsedCallOptions']): Promise<string> {
-        const hfi = await this._prepareHFInference()
-        const args = { ...this.invocationParams(options), inputs: prompt }
-        const res = await this.caller.callWithOptions({ signal: options.signal }, hfi.textGeneration.bind(hfi), args)
-        return res.generated_text
+        try {
+            const client = await this._prepareHFInference()
+            // Use chatCompletion for chat models (v4 supports conversational models via Inference Providers)
+            const args = {
+                model: this.model,
+                messages: [{ role: 'user', content: prompt }],
+                ...this.invocationParams(options)
+            }
+            const res = await this.caller.callWithOptions({ signal: options.signal }, client.chatCompletion.bind(client), args)
+            const content = res.choices[0]?.message?.content || ''
+            if (!content) {
+                console.error('[ChatHuggingFace] No content in response:', JSON.stringify(res))
+                throw new Error(`No content received from HuggingFace API. Response: ${JSON.stringify(res)}`)
+            }
+            return content
+        } catch (error: any) {
+            console.error('[ChatHuggingFace] Error in _call:', error.message)
+            // Provide more helpful error messages
+            if (error?.message?.includes('endpointUrl') || error?.message?.includes('third-party provider')) {
+                throw new Error(
+                    `Cannot use custom endpoint with model "${this.model}" that includes a provider. Please leave the Endpoint field blank in the UI. Original error: ${error.message}`
+                )
+            }
+            if (error?.message?.includes('Invalid username or password') || error?.message?.includes('authentication')) {
+                throw new Error(
+                    `HuggingFace API authentication failed. Please verify your API key is correct and starts with "hf_". Original error: ${error.message}`
+                )
+            }
+            throw error
+        }
     }
 
     /** @ignore */
     private async _prepareHFInference() {
-        const { HfInference } = await HuggingFaceInference.imports()
-        const hfi = new HfInference(this.apiKey, {
-            includeCredentials: this.includeCredentials
-        })
-        return this.endpointUrl ? hfi.endpoint(this.endpointUrl) : hfi
+        if (!this.apiKey || this.apiKey.trim() === '') {
+            console.error('[ChatHuggingFace] API key validation failed: Empty or undefined')
+            throw new Error('HuggingFace API key is required. Please configure it in the credential settings.')
+        }
+
+        const { InferenceClient } = await HuggingFaceInference.imports()
+        // Use InferenceClient for chat models (works better with Inference Providers)
+        const client = new InferenceClient(this.apiKey)
+
+        // Don't override endpoint if model uses a provider (contains ':') or if endpoint is router-based
+        // When using Inference Providers, endpoint should be left blank - InferenceClient handles routing automatically
+        if (
+            this.endpointUrl &&
+            !this.model.includes(':') &&
+            !this.endpointUrl.includes('/v1/chat/completions') &&
+            !this.endpointUrl.includes('router.huggingface.co')
+        ) {
+            return client.endpoint(this.endpointUrl)
+        }
+
+        // Return client without endpoint override - InferenceClient will use Inference Providers automatically
+        return client
     }
 
     /** @ignore */
     static async imports(): Promise<{
-        HfInference: typeof import('@huggingface/inference').HfInference
+        InferenceClient: typeof import('@huggingface/inference').InferenceClient
     }> {
         try {
-            const { HfInference } = await import('@huggingface/inference')
-            return { HfInference }
+            const { InferenceClient } = await import('@huggingface/inference')
+            return { InferenceClient }
         } catch (e) {
             throw new Error('Please install huggingface as a dependency with, e.g. `pnpm install @huggingface/inference`')
         }

packages/components/nodes/chatmodels/ChatOpenRouter/ChatOpenRouter.ts

@@ -1,7 +1,8 @@
-import { ChatOpenAI, ChatOpenAIFields } from '@langchain/openai'
+import { ChatOpenAI as LangchainChatOpenAI, ChatOpenAIFields } from '@langchain/openai'
 import { BaseCache } from '@langchain/core/caches'
-import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { ICommonObject, IMultiModalOption, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+import { ChatOpenRouter } from './FlowiseChatOpenRouter'
 
 class ChatOpenRouter_ChatModels implements INode {
     label: string
@@ -23,7 +24,7 @@ class ChatOpenRouter_ChatModels implements INode {
         this.icon = 'openRouter.svg'
         this.category = 'Chat Models'
         this.description = 'Wrapper around Open Router Inference API'
-        this.baseClasses = [this.type, ...getBaseClasses(ChatOpenAI)]
+        this.baseClasses = [this.type, ...getBaseClasses(LangchainChatOpenAI)]
         this.credential = {
             label: 'Connect Credential',
             name: 'credential',
@@ -114,6 +115,40 @@ class ChatOpenRouter_ChatModels implements INode {
                 type: 'json',
                 optional: true,
                 additionalParams: true
+            },
+            {
+                label: 'Allow Image Uploads',
+                name: 'allowImageUploads',
+                type: 'boolean',
+                description:
+                    'Allow image input. Refer to the <a href="https://docs.flowiseai.com/using-flowise/uploads#image" target="_blank">docs</a> for more details.',
+                default: false,
+                optional: true
+            },
+            {
+                label: 'Image Resolution',
+                description: 'This parameter controls the resolution in which the model views the image.',
+                name: 'imageResolution',
+                type: 'options',
+                options: [
+                    {
+                        label: 'Low',
+                        name: 'low'
+                    },
+                    {
+                        label: 'High',
+                        name: 'high'
+                    },
+                    {
+                        label: 'Auto',
+                        name: 'auto'
+                    }
+                ],
+                default: 'low',
+                optional: false,
+                show: {
+                    allowImageUploads: true
+                }
             }
         ]
     }
@@ -130,6 +165,8 @@ class ChatOpenRouter_ChatModels implements INode {
         const basePath = (nodeData.inputs?.basepath as string) || 'https://openrouter.ai/api/v1'
         const baseOptions = nodeData.inputs?.baseOptions
         const cache = nodeData.inputs?.cache as BaseCache
+        const allowImageUploads = nodeData.inputs?.allowImageUploads as boolean
+        const imageResolution = nodeData.inputs?.imageResolution as string
 
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const openRouterApiKey = getCredentialParam('openRouterApiKey', credentialData, nodeData)
@@ -155,7 +192,7 @@ class ChatOpenRouter_ChatModels implements INode {
             try {
                 parsedBaseOptions = typeof baseOptions === 'object' ? baseOptions : JSON.parse(baseOptions)
             } catch (exception) {
-                throw new Error("Invalid JSON in the ChatCerebras's BaseOptions: " + exception)
+                throw new Error("Invalid JSON in the ChatOpenRouter's BaseOptions: " + exception)
             }
         }
 
@@ -166,7 +203,15 @@ class ChatOpenRouter_ChatModels implements INode {
             }
         }
 
-        const model = new ChatOpenAI(obj)
+        const multiModalOption: IMultiModalOption = {
+            image: {
+                allowImageUploads: allowImageUploads ?? false,
+                imageResolution
+            }
+        }
+
+        const model = new ChatOpenRouter(nodeData.id, obj)
+        model.setMultiModalOption(multiModalOption)
         return model
     }
 }

packages/components/nodes/chatmodels/ChatOpenRouter/FlowiseChatOpenRouter.ts

@@ -0,0 +1,29 @@
+import { ChatOpenAI as LangchainChatOpenAI, ChatOpenAIFields } from '@langchain/openai'
+import { IMultiModalOption, IVisionChatModal } from '../../../src'
+
+export class ChatOpenRouter extends LangchainChatOpenAI implements IVisionChatModal {
+    configuredModel: string
+    configuredMaxToken?: number
+    multiModalOption: IMultiModalOption
+    id: string
+
+    constructor(id: string, fields?: ChatOpenAIFields) {
+        super(fields)
+        this.id = id
+        this.configuredModel = fields?.modelName ?? ''
+        this.configuredMaxToken = fields?.maxTokens
+    }
+
+    revertToOriginalModel(): void {
+        this.model = this.configuredModel
+        this.maxTokens = this.configuredMaxToken
+    }
+
+    setMultiModalOption(multiModalOption: IMultiModalOption): void {
+        this.multiModalOption = multiModalOption
+    }
+
+    setVisionModel(): void {
+        // pass - OpenRouter models don't need model switching
+    }
+}

packages/components/nodes/documentloaders/Json/Json.ts

@@ -47,7 +47,7 @@ class Json_DocumentLoaders implements INode {
     constructor() {
         this.label = 'Json File'
         this.name = 'jsonFile'
-        this.version = 3.0
+        this.version = 3.1
         this.type = 'Document'
         this.icon = 'json.svg'
         this.category = 'Document Loaders'
@@ -66,6 +66,14 @@ class Json_DocumentLoaders implements INode {
                 type: 'TextSplitter',
                 optional: true
             },
+            {
+                label: 'Separate by JSON Object (JSON Array)',
+                name: 'separateByObject',
+                type: 'boolean',
+                description: 'If enabled and the file is a JSON Array, each JSON object will be extracted as a chunk',
+                optional: true,
+                additionalParams: true
+            },
             {
                 label: 'Pointers Extraction (separated by commas)',
                 name: 'pointersName',
@@ -73,7 +81,10 @@ class Json_DocumentLoaders implements INode {
                 description:
                     'Ex: { "key": "value" }, Pointer Extraction = "key", "value" will be extracted as pageContent of the chunk. Use comma to separate multiple pointers',
                 placeholder: 'key1, key2',
-                optional: true
+                optional: true,
+                hide: {
+                    separateByObject: true
+                }
             },
             {
                 label: 'Additional Metadata',
@@ -122,6 +133,7 @@ class Json_DocumentLoaders implements INode {
         const pointersName = nodeData.inputs?.pointersName as string
         const metadata = nodeData.inputs?.metadata
         const _omitMetadataKeys = nodeData.inputs?.omitMetadataKeys as string
+        const separateByObject = nodeData.inputs?.separateByObject as boolean
         const output = nodeData.outputs?.output as string
 
         let omitMetadataKeys: string[] = []
@@ -153,7 +165,7 @@ class Json_DocumentLoaders implements INode {
                 if (!file) continue
                 const fileData = await getFileFromStorage(file, orgId, chatflowid)
                 const blob = new Blob([fileData])
-                const loader = new JSONLoader(blob, pointers.length != 0 ? pointers : undefined, metadata)
+                const loader = new JSONLoader(blob, pointers.length != 0 ? pointers : undefined, metadata, separateByObject)
 
                 if (textSplitter) {
                     let splittedDocs = await loader.load()
@@ -176,7 +188,7 @@ class Json_DocumentLoaders implements INode {
                 splitDataURI.pop()
                 const bf = Buffer.from(splitDataURI.pop() || '', 'base64')
                 const blob = new Blob([bf])
-                const loader = new JSONLoader(blob, pointers.length != 0 ? pointers : undefined, metadata)
+                const loader = new JSONLoader(blob, pointers.length != 0 ? pointers : undefined, metadata, separateByObject)
 
                 if (textSplitter) {
                     let splittedDocs = await loader.load()
@@ -306,13 +318,20 @@ class TextLoader extends BaseDocumentLoader {
 class JSONLoader extends TextLoader {
     public pointers: string[]
     private metadataMapping: Record<string, string>
+    private separateByObject: boolean
 
-    constructor(filePathOrBlob: string | Blob, pointers: string | string[] = [], metadataMapping: Record<string, string> = {}) {
+    constructor(
+        filePathOrBlob: string | Blob,
+        pointers: string | string[] = [],
+        metadataMapping: Record<string, string> = {},
+        separateByObject: boolean = false
+    ) {
         super(filePathOrBlob)
         this.pointers = Array.isArray(pointers) ? pointers : [pointers]
         if (metadataMapping) {
             this.metadataMapping = typeof metadataMapping === 'object' ? metadataMapping : JSON.parse(metadataMapping)
         }
+        this.separateByObject = separateByObject
     }
 
     protected async parse(raw: string): Promise<Document[]> {
@@ -323,14 +342,24 @@ class JSONLoader extends TextLoader {
         const jsonArray = Array.isArray(json) ? json : [json]
 
         for (const item of jsonArray) {
-            const content = this.extractContent(item)
-            const metadata = this.extractMetadata(item)
-
-            for (const pageContent of content) {
-                documents.push({
-                    pageContent,
-                    metadata
-                })
+            if (this.separateByObject) {
+                if (typeof item === 'object' && item !== null && !Array.isArray(item)) {
+                    const metadata = this.extractMetadata(item)
+                    const pageContent = this.formatObjectAsKeyValue(item)
+                    documents.push({
+                        pageContent,
+                        metadata
+                    })
+                }
+            } else {
+                const content = this.extractContent(item)
+                const metadata = this.extractMetadata(item)
+                for (const pageContent of content) {
+                    documents.push({
+                        pageContent,
+                        metadata
+                    })
+                }
             }
         }
 
@@ -370,6 +399,30 @@ class JSONLoader extends TextLoader {
         return metadata
     }
 
+    /**
+     * Formats a JSON object as readable key-value pairs
+     */
+    private formatObjectAsKeyValue(obj: any, prefix: string = ''): string {
+        const lines: string[] = []
+
+        for (const [key, value] of Object.entries(obj)) {
+            const fullKey = prefix ? `${prefix}.${key}` : key
+
+            if (value === null || value === undefined) {
+                lines.push(`${fullKey}: ${value}`)
+            } else if (Array.isArray(value)) {
+                lines.push(`${fullKey}: ${JSON.stringify(value)}`)
+            } else if (typeof value === 'object') {
+                // Recursively format nested objects
+                lines.push(this.formatObjectAsKeyValue(value, fullKey))
+            } else {
+                lines.push(`${fullKey}: ${value}`)
+            }
+        }
+
+        return lines.join('\n')
+    }
+
     /**
      * If JSON pointers are specified, return all strings below any of them
      * and exclude all other nodes expect if they match a JSON pointer.

packages/components/nodes/documentloaders/Playwright/Playwright.ts

@@ -190,11 +190,14 @@ class Playwright_DocumentLoaders implements INode {
         async function playwrightLoader(url: string): Promise<Document[] | undefined> {
             try {
                 let docs = []
+
+                const executablePath = process.env.PLAYWRIGHT_EXECUTABLE_PATH
+
                 const config: PlaywrightWebBaseLoaderOptions = {
                     launchOptions: {
                         args: ['--no-sandbox'],
                         headless: true,
-                        executablePath: process.env.PLAYWRIGHT_EXECUTABLE_FILE_PATH
+                        executablePath: executablePath
                     }
                 }
                 if (waitUntilGoToOption) {

packages/components/nodes/documentloaders/Puppeteer/Puppeteer.ts

@@ -181,11 +181,14 @@ class Puppeteer_DocumentLoaders implements INode {
         async function puppeteerLoader(url: string): Promise<Document[] | undefined> {
             try {
                 let docs: Document[] = []
+
+                const executablePath = process.env.PUPPETEER_EXECUTABLE_PATH
+
                 const config: PuppeteerWebBaseLoaderOptions = {
                     launchOptions: {
                         args: ['--no-sandbox'],
                         headless: 'new',
-                        executablePath: process.env.PUPPETEER_EXECUTABLE_FILE_PATH
+                        executablePath: executablePath
                     }
                 }
                 if (waitUntilGoToOption) {

packages/components/nodes/documentloaders/Unstructured/Unstructured.ts

@@ -27,8 +27,6 @@ type Element = {
 }
 
 export class UnstructuredLoader extends BaseDocumentLoader {
-    public filePath: string
-
     private apiUrl = process.env.UNSTRUCTURED_API_URL || 'https://api.unstructuredapp.io/general/v0/general'
 
     private apiKey: string | undefined = process.env.UNSTRUCTURED_API_KEY
@@ -138,7 +136,7 @@ export class UnstructuredLoader extends BaseDocumentLoader {
         })
 
         if (!response.ok) {
-            throw new Error(`Failed to partition file ${this.filePath} with error ${response.status} and message ${await response.text()}`)
+            throw new Error(`Failed to partition file with error ${response.status} and message ${await response.text()}`)
         }
 
         const elements = await response.json()

packages/components/nodes/documentloaders/Unstructured/UnstructuredFile.ts

@@ -4,15 +4,11 @@ import {
     UnstructuredLoaderOptions,
     UnstructuredLoaderStrategy,
     SkipInferTableTypes,
-    HiResModelName,
-    UnstructuredLoader as LCUnstructuredLoader
+    HiResModelName
 } from '@langchain/community/document_loaders/fs/unstructured'
 import { getCredentialData, getCredentialParam, handleEscapeCharacters } from '../../../src/utils'
 import { getFileFromStorage, INodeOutputsValue } from '../../../src'
 import { UnstructuredLoader } from './Unstructured'
-import { isPathTraversal } from '../../../src/validator'
-import sanitize from 'sanitize-filename'
-import path from 'path'
 
 class UnstructuredFile_DocumentLoaders implements INode {
     label: string
@@ -44,17 +40,6 @@ class UnstructuredFile_DocumentLoaders implements INode {
             optional: true
         }
         this.inputs = [
-            /** Deprecated
-            {
-                label: 'File Path',
-                name: 'filePath',
-                type: 'string',
-                placeholder: '',
-                optional: true,
-                warning:
-                    'Use the File Upload instead of File path. If file is uploaded, this path is ignored. Path will be deprecated in future releases.'
-            },
-             */
             {
                 label: 'Files Upload',
                 name: 'fileObject',
@@ -455,7 +440,6 @@ class UnstructuredFile_DocumentLoaders implements INode {
     }
 
     async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
-        const filePath = nodeData.inputs?.filePath as string
         const unstructuredAPIUrl = nodeData.inputs?.unstructuredAPIUrl as string
         const strategy = nodeData.inputs?.strategy as UnstructuredLoaderStrategy
         const encoding = nodeData.inputs?.encoding as string
@@ -560,37 +544,8 @@ class UnstructuredFile_DocumentLoaders implements INode {
                     docs.push(...loaderDocs)
                 }
             }
-        } else if (filePath) {
-            if (!filePath || typeof filePath !== 'string') {
-                throw new Error('Invalid file path format')
-            }
-
-            if (isPathTraversal(filePath)) {
-                throw new Error('Invalid path characters detected in filePath - path traversal not allowed')
-            }
-
-            const parsedPath = path.parse(filePath)
-            const sanitizedFilename = sanitize(parsedPath.base)
-
-            if (!sanitizedFilename || sanitizedFilename.trim() === '') {
-                throw new Error('Invalid filename after sanitization')
-            }
-
-            const sanitizedFilePath = path.join(parsedPath.dir, sanitizedFilename)
-
-            if (!path.isAbsolute(sanitizedFilePath)) {
-                throw new Error('File path must be absolute')
-            }
-
-            if (sanitizedFilePath.includes('..')) {
-                throw new Error('Invalid file path - directory traversal not allowed')
-            }
-
-            const loader = new LCUnstructuredLoader(sanitizedFilePath, obj)
-            const loaderDocs = await loader.load()
-            docs.push(...loaderDocs)
         } else {
-            throw new Error('File path or File upload is required')
+            throw new Error('File upload is required')
         }
 
         if (metadata) {

packages/components/nodes/documentloaders/Unstructured/UnstructuredFolder.ts

@@ -1,3 +1,6 @@
+/*
+* Uncomment this if you want to use the UnstructuredFolder to load a folder from the file system
+
 import { omit } from 'lodash'
 import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
 import {
@@ -516,3 +519,4 @@ class UnstructuredFolder_DocumentLoaders implements INode {
 }
 
 module.exports = { nodeClass: UnstructuredFolder_DocumentLoaders }
+*/

packages/components/nodes/embeddings/AWSBedrockEmbedding/AWSBedrockEmbedding.ts

@@ -96,7 +96,7 @@ class AWSBedrockEmbedding_Embeddings implements INode {
             {
                 label: 'Max AWS API retries',
                 name: 'maxRetries',
-                description: 'This will limit the nubmer of AWS API for Titan model embeddings call retries. Used to avoid throttling.',
+                description: 'This will limit the number of AWS API for Titan model embeddings call retries. Used to avoid throttling.',
                 type: 'number',
                 optional: true,
                 default: 5,

packages/components/nodes/embeddings/HuggingFaceInferenceEmbedding/core.ts

@@ -23,24 +23,22 @@ export class HuggingFaceInferenceEmbeddings extends Embeddings implements Huggin
         this.model = fields?.model ?? 'sentence-transformers/distilbert-base-nli-mean-tokens'
         this.apiKey = fields?.apiKey ?? getEnvironmentVariable('HUGGINGFACEHUB_API_KEY')
         this.endpoint = fields?.endpoint ?? ''
-        this.client = new HfInference(this.apiKey)
-        if (this.endpoint) this.client.endpoint(this.endpoint)
+        const hf = new HfInference(this.apiKey)
+        // v4 uses Inference Providers by default; only override if custom endpoint provided
+        this.client = this.endpoint ? hf.endpoint(this.endpoint) : hf
     }
 
     async _embed(texts: string[]): Promise<number[][]> {
         // replace newlines, which can negatively affect performance.
         const clean = texts.map((text) => text.replace(/\n/g, ' '))
-        const hf = new HfInference(this.apiKey)
         const obj: any = {
             inputs: clean
         }
-        if (this.endpoint) {
-            hf.endpoint(this.endpoint)
-        } else {
+        if (!this.endpoint) {
             obj.model = this.model
         }
 
-        const res = await this.caller.callWithOptions({}, hf.featureExtraction.bind(hf), obj)
+        const res = await this.caller.callWithOptions({}, this.client.featureExtraction.bind(this.client), obj)
         return res as number[][]
     }
 

packages/components/nodes/engine/SubQuestionQueryEngine/SubQuestionQueryEngine.ts

@@ -39,7 +39,7 @@ class SubQuestionQueryEngine_LlamaIndex implements INode {
         this.icon = 'subQueryEngine.svg'
         this.category = 'Engine'
         this.description =
-            'Breaks complex query into sub questions for each relevant data source, then gather all the intermediate reponses and synthesizes a final response'
+            'Breaks complex query into sub questions for each relevant data source, then gather all the intermediate responses and synthesizes a final response'
         this.baseClasses = [this.type, 'BaseQueryEngine']
         this.tags = ['LlamaIndex']
         this.inputs = [

packages/components/nodes/llms/HuggingFaceInference/core.ts

@@ -78,6 +78,8 @@ export class HuggingFaceInference extends LLM implements HFInput {
     async _call(prompt: string, options: this['ParsedCallOptions']): Promise<string> {
         const { HfInference } = await HuggingFaceInference.imports()
         const hf = new HfInference(this.apiKey)
+        // v4 uses Inference Providers by default; only override if custom endpoint provided
+        const hfClient = this.endpoint ? hf.endpoint(this.endpoint) : hf
         const obj: any = {
             parameters: {
                 // make it behave similar to openai, returning only the generated text
@@ -90,12 +92,10 @@ export class HuggingFaceInference extends LLM implements HFInput {
             },
             inputs: prompt
         }
-        if (this.endpoint) {
-            hf.endpoint(this.endpoint)
-        } else {
+        if (!this.endpoint) {
             obj.model = this.model
         }
-        const res = await this.caller.callWithOptions({ signal: options.signal }, hf.textGeneration.bind(hf), obj)
+        const res = await this.caller.callWithOptions({ signal: options.signal }, hfClient.textGeneration.bind(hfClient), obj)
         return res.generated_text
     }
 

packages/components/nodes/multiagents/Supervisor/Supervisor.ts

@@ -21,6 +21,7 @@ import { ChatOpenAI } from '../../chatmodels/ChatOpenAI/FlowiseChatOpenAI'
 import { ChatAnthropic } from '../../chatmodels/ChatAnthropic/FlowiseChatAnthropic'
 import { addImagesToMessages, llmSupportsVision } from '../../../src/multiModalUtils'
 import { ChatGoogleGenerativeAI } from '../../chatmodels/ChatGoogleGenerativeAI/FlowiseChatGoogleGenerativeAI'
+import { AzureChatOpenAI } from '../../chatmodels/AzureChatOpenAI/FlowiseAzureChatOpenAI'
 
 const sysPrompt = `You are a supervisor tasked with managing a conversation between the following workers: {team_members}.
 Given the following user request, respond with the worker to act next.
@@ -242,7 +243,7 @@ class Supervisor_MultiAgents implements INode {
                             }
                         }
                     })
-            } else if (llm instanceof ChatOpenAI) {
+            } else if (llm instanceof ChatOpenAI || llm instanceof AzureChatOpenAI) {
                 let prompt = ChatPromptTemplate.fromMessages([
                     ['system', systemPrompt],
                     new MessagesPlaceholder('messages'),

packages/components/nodes/prompts/ChatPromptTemplate/ChatPromptTemplate.ts

@@ -11,7 +11,7 @@ return [
         tool_calls: [
         {
             id: "12345",
-            name: "calulator",
+            name: "calculator",
             args: {
                 number1: 333382,
                 number2: 1932,

packages/components/nodes/recordmanager/MySQLRecordManager/MySQLrecordManager.ts

@@ -62,7 +62,6 @@ class MySQLRecordManager_RecordManager implements INode {
                 label: 'Namespace',
                 name: 'namespace',
                 type: 'string',
-                description: 'If not specified, chatflowid will be used',
                 additionalParams: true,
                 optional: true
             },
@@ -219,7 +218,16 @@ class MySQLRecordManager implements RecordManagerInterface {
                 unique key \`unique_key_namespace\` (\`key\`,
 \`namespace\`));`)
 
-            const columns = [`updated_at`, `key`, `namespace`, `group_id`]
+            // Add doc_id column if it doesn't exist (migration for existing tables)
+            const checkColumn = await queryRunner.manager.query(
+                `SELECT COUNT(1) ColumnExists FROM INFORMATION_SCHEMA.COLUMNS 
+                    WHERE table_schema=DATABASE() AND table_name='${tableName}' AND column_name='doc_id';`
+            )
+            if (checkColumn[0].ColumnExists === 0) {
+                await queryRunner.manager.query(`ALTER TABLE \`${tableName}\` ADD COLUMN \`doc_id\` longtext;`)
+            }
+
+            const columns = [`updated_at`, `key`, `namespace`, `group_id`, `doc_id`]
             for (const column of columns) {
                 // MySQL does not support 'IF NOT EXISTS' function for Index
                 const Check = await queryRunner.manager.query(
@@ -261,7 +269,7 @@ class MySQLRecordManager implements RecordManagerInterface {
         }
     }
 
-    async update(keys: string[], updateOptions?: UpdateOptions): Promise<void> {
+    async update(keys: Array<{ uid: string; docId: string }> | string[], updateOptions?: UpdateOptions): Promise<void> {
         if (keys.length === 0) {
             return
         }
@@ -277,23 +285,23 @@ class MySQLRecordManager implements RecordManagerInterface {
             throw new Error(`Time sync issue with database ${updatedAt} < ${timeAtLeast}`)
         }
 
-        const groupIds = _groupIds ?? keys.map(() => null)
+        // Handle both new format (objects with uid and docId) and old format (strings)
+        const isNewFormat = keys.length > 0 && typeof keys[0] === 'object' && 'uid' in keys[0]
+        const keyStrings = isNewFormat ? (keys as Array<{ uid: string; docId: string }>).map((k) => k.uid) : (keys as string[])
+        const docIds = isNewFormat ? (keys as Array<{ uid: string; docId: string }>).map((k) => k.docId) : keys.map(() => null)
 
-        if (groupIds.length !== keys.length) {
-            throw new Error(`Number of keys (${keys.length}) does not match number of group_ids (${groupIds.length})`)
+        const groupIds = _groupIds ?? keyStrings.map(() => null)
+
+        if (groupIds.length !== keyStrings.length) {
+            throw new Error(`Number of keys (${keyStrings.length}) does not match number of group_ids (${groupIds.length})`)
         }
 
-        const recordsToUpsert = keys.map((key, i) => [
-            key,
-            this.namespace,
-            updatedAt,
-            groupIds[i] ?? null // Ensure groupIds[i] is null if undefined
-        ])
+        const recordsToUpsert = keyStrings.map((key, i) => [key, this.namespace, updatedAt, groupIds[i] ?? null, docIds[i] ?? null])
 
         const query = `
-            INSERT INTO \`${tableName}\` (\`key\`, \`namespace\`, \`updated_at\`, \`group_id\`)
-            VALUES (?, ?, ?, ?)
-            ON DUPLICATE KEY UPDATE \`updated_at\` = VALUES(\`updated_at\`)`
+            INSERT INTO \`${tableName}\` (\`key\`, \`namespace\`, \`updated_at\`, \`group_id\`, \`doc_id\`)
+            VALUES (?, ?, ?, ?, ?)
+            ON DUPLICATE KEY UPDATE \`updated_at\` = VALUES(\`updated_at\`), \`doc_id\` = VALUES(\`doc_id\`)`
 
         // To handle multiple files upsert
         try {
@@ -349,13 +357,13 @@ class MySQLRecordManager implements RecordManagerInterface {
         }
     }
 
-    async listKeys(options?: ListKeyOptions): Promise<string[]> {
+    async listKeys(options?: ListKeyOptions & { docId?: string }): Promise<string[]> {
         const dataSource = await this.getDataSource()
         const queryRunner = dataSource.createQueryRunner()
         const tableName = this.sanitizeTableName(this.tableName)
 
         try {
-            const { before, after, limit, groupIds } = options ?? {}
+            const { before, after, limit, groupIds, docId } = options ?? {}
             let query = `SELECT \`key\` FROM \`${tableName}\` WHERE \`namespace\` = ?`
             const values: (string | number | string[])[] = [this.namespace]
 
@@ -382,6 +390,11 @@ class MySQLRecordManager implements RecordManagerInterface {
                 values.push(...groupIds.filter((gid): gid is string => gid !== null))
             }
 
+            if (docId) {
+                query += ` AND \`doc_id\` = ?`
+                values.push(docId)
+            }
+
             query += ';'
 
             // Directly using try/catch with async/await for cleaner flow

packages/components/nodes/recordmanager/PostgresRecordManager/PostgresRecordManager.ts

@@ -78,7 +78,6 @@ class PostgresRecordManager_RecordManager implements INode {
                 label: 'Namespace',
                 name: 'namespace',
                 type: 'string',
-                description: 'If not specified, chatflowid will be used',
                 additionalParams: true,
                 optional: true
             },
@@ -241,6 +240,19 @@ class PostgresRecordManager implements RecordManagerInterface {
   CREATE INDEX IF NOT EXISTS namespace_index ON "${tableName}" (namespace);
   CREATE INDEX IF NOT EXISTS group_id_index ON "${tableName}" (group_id);`)
 
+            // Add doc_id column if it doesn't exist (migration for existing tables)
+            await queryRunner.manager.query(`
+  DO $$
+  BEGIN
+    IF NOT EXISTS (
+      SELECT 1 FROM information_schema.columns 
+      WHERE table_name = '${tableName}' AND column_name = 'doc_id'
+    ) THEN
+      ALTER TABLE "${tableName}" ADD COLUMN doc_id TEXT;
+      CREATE INDEX IF NOT EXISTS doc_id_index ON "${tableName}" (doc_id);
+    END IF;
+  END $$;`)
+
             await queryRunner.release()
         } catch (e: any) {
             // This error indicates that the table already exists
@@ -286,7 +298,7 @@ class PostgresRecordManager implements RecordManagerInterface {
         return `(${placeholders.join(', ')})`
     }
 
-    async update(keys: string[], updateOptions?: UpdateOptions): Promise<void> {
+    async update(keys: Array<{ uid: string; docId: string }> | string[], updateOptions?: UpdateOptions): Promise<void> {
         if (keys.length === 0) {
             return
         }
@@ -302,17 +314,22 @@ class PostgresRecordManager implements RecordManagerInterface {
             throw new Error(`Time sync issue with database ${updatedAt} < ${timeAtLeast}`)
         }
 
-        const groupIds = _groupIds ?? keys.map(() => null)
+        // Handle both new format (objects with uid and docId) and old format (strings)
+        const isNewFormat = keys.length > 0 && typeof keys[0] === 'object' && 'uid' in keys[0]
+        const keyStrings = isNewFormat ? (keys as Array<{ uid: string; docId: string }>).map((k) => k.uid) : (keys as string[])
+        const docIds = isNewFormat ? (keys as Array<{ uid: string; docId: string }>).map((k) => k.docId) : keys.map(() => null)
 
-        if (groupIds.length !== keys.length) {
-            throw new Error(`Number of keys (${keys.length}) does not match number of group_ids ${groupIds.length})`)
+        const groupIds = _groupIds ?? keyStrings.map(() => null)
+
+        if (groupIds.length !== keyStrings.length) {
+            throw new Error(`Number of keys (${keyStrings.length}) does not match number of group_ids ${groupIds.length})`)
         }
 
-        const recordsToUpsert = keys.map((key, i) => [key, this.namespace, updatedAt, groupIds[i]])
+        const recordsToUpsert = keyStrings.map((key, i) => [key, this.namespace, updatedAt, groupIds[i], docIds[i]])
 
         const valuesPlaceholders = recordsToUpsert.map((_, j) => this.generatePlaceholderForRowAt(j, recordsToUpsert[0].length)).join(', ')
 
-        const query = `INSERT INTO "${tableName}" (key, namespace, updated_at, group_id) VALUES ${valuesPlaceholders} ON CONFLICT (key, namespace) DO UPDATE SET updated_at = EXCLUDED.updated_at;`
+        const query = `INSERT INTO "${tableName}" (key, namespace, updated_at, group_id, doc_id) VALUES ${valuesPlaceholders} ON CONFLICT (key, namespace) DO UPDATE SET updated_at = EXCLUDED.updated_at, doc_id = EXCLUDED.doc_id;`
         try {
             await queryRunner.manager.query(query, recordsToUpsert.flat())
             await queryRunner.release()
@@ -351,8 +368,8 @@ class PostgresRecordManager implements RecordManagerInterface {
         }
     }
 
-    async listKeys(options?: ListKeyOptions): Promise<string[]> {
-        const { before, after, limit, groupIds } = options ?? {}
+    async listKeys(options?: ListKeyOptions & { docId?: string }): Promise<string[]> {
+        const { before, after, limit, groupIds, docId } = options ?? {}
         const tableName = this.sanitizeTableName(this.tableName)
 
         let query = `SELECT key FROM "${tableName}" WHERE namespace = $1`
@@ -383,6 +400,12 @@ class PostgresRecordManager implements RecordManagerInterface {
             index += 1
         }
 
+        if (docId) {
+            values.push(docId)
+            query += ` AND doc_id = $${index}`
+            index += 1
+        }
+
         query += ';'
 
         const dataSource = await this.getDataSource()

packages/components/nodes/recordmanager/SQLiteRecordManager/SQLiteRecordManager.ts

@@ -51,7 +51,6 @@ class SQLiteRecordManager_RecordManager implements INode {
                 label: 'Namespace',
                 name: 'namespace',
                 type: 'string',
-                description: 'If not specified, chatflowid will be used',
                 additionalParams: true,
                 optional: true
             },
@@ -198,6 +197,15 @@ CREATE INDEX IF NOT EXISTS key_index ON "${tableName}" (key);
 CREATE INDEX IF NOT EXISTS namespace_index ON "${tableName}" (namespace);
 CREATE INDEX IF NOT EXISTS group_id_index ON "${tableName}" (group_id);`)
 
+            // Add doc_id column if it doesn't exist (migration for existing tables)
+            const checkColumn = await queryRunner.manager.query(
+                `SELECT COUNT(*) as count FROM pragma_table_info('${tableName}') WHERE name='doc_id';`
+            )
+            if (checkColumn[0].count === 0) {
+                await queryRunner.manager.query(`ALTER TABLE "${tableName}" ADD COLUMN doc_id TEXT;`)
+                await queryRunner.manager.query(`CREATE INDEX IF NOT EXISTS doc_id_index ON "${tableName}" (doc_id);`)
+            }
+
             await queryRunner.release()
         } catch (e: any) {
             // This error indicates that the table already exists
@@ -228,7 +236,7 @@ CREATE INDEX IF NOT EXISTS group_id_index ON "${tableName}" (group_id);`)
         }
     }
 
-    async update(keys: string[], updateOptions?: UpdateOptions): Promise<void> {
+    async update(keys: Array<{ uid: string; docId: string }> | string[], updateOptions?: UpdateOptions): Promise<void> {
         if (keys.length === 0) {
             return
         }
@@ -243,23 +251,23 @@ CREATE INDEX IF NOT EXISTS group_id_index ON "${tableName}" (group_id);`)
             throw new Error(`Time sync issue with database ${updatedAt} < ${timeAtLeast}`)
         }
 
-        const groupIds = _groupIds ?? keys.map(() => null)
+        // Handle both new format (objects with uid and docId) and old format (strings)
+        const isNewFormat = keys.length > 0 && typeof keys[0] === 'object' && 'uid' in keys[0]
+        const keyStrings = isNewFormat ? (keys as Array<{ uid: string; docId: string }>).map((k) => k.uid) : (keys as string[])
+        const docIds = isNewFormat ? (keys as Array<{ uid: string; docId: string }>).map((k) => k.docId) : keys.map(() => null)
 
-        if (groupIds.length !== keys.length) {
-            throw new Error(`Number of keys (${keys.length}) does not match number of group_ids (${groupIds.length})`)
+        const groupIds = _groupIds ?? keyStrings.map(() => null)
+
+        if (groupIds.length !== keyStrings.length) {
+            throw new Error(`Number of keys (${keyStrings.length}) does not match number of group_ids (${groupIds.length})`)
         }
 
-        const recordsToUpsert = keys.map((key, i) => [
-            key,
-            this.namespace,
-            updatedAt,
-            groupIds[i] ?? null // Ensure groupIds[i] is null if undefined
-        ])
+        const recordsToUpsert = keyStrings.map((key, i) => [key, this.namespace, updatedAt, groupIds[i] ?? null, docIds[i] ?? null])
 
         const query = `
-        INSERT INTO "${tableName}" (key, namespace, updated_at, group_id)
-        VALUES (?, ?, ?, ?)
-        ON CONFLICT (key, namespace) DO UPDATE SET updated_at = excluded.updated_at`
+        INSERT INTO "${tableName}" (key, namespace, updated_at, group_id, doc_id)
+        VALUES (?, ?, ?, ?, ?)
+        ON CONFLICT (key, namespace) DO UPDATE SET updated_at = excluded.updated_at, doc_id = excluded.doc_id`
 
         try {
             // To handle multiple files upsert
@@ -314,8 +322,8 @@ CREATE INDEX IF NOT EXISTS group_id_index ON "${tableName}" (group_id);`)
         }
     }
 
-    async listKeys(options?: ListKeyOptions): Promise<string[]> {
-        const { before, after, limit, groupIds } = options ?? {}
+    async listKeys(options?: ListKeyOptions & { docId?: string }): Promise<string[]> {
+        const { before, after, limit, groupIds, docId } = options ?? {}
         const tableName = this.sanitizeTableName(this.tableName)
 
         let query = `SELECT key FROM "${tableName}" WHERE namespace = ?`
@@ -344,6 +352,11 @@ CREATE INDEX IF NOT EXISTS group_id_index ON "${tableName}" (group_id);`)
             values.push(...groupIds.filter((gid): gid is string => gid !== null))
         }
 
+        if (docId) {
+            query += ` AND doc_id = ?`
+            values.push(docId)
+        }
+
         query += ';'
 
         const dataSource = await this.getDataSource()

packages/components/nodes/tools/MCP/CustomMCP/CustomMCP.ts

@@ -136,17 +136,17 @@ class Custom_MCP implements INode {
         }
 
         let sandbox: ICommonObject = {}
+        const workspaceId = options?.searchOptions?.workspaceId?._value || options?.workspaceId
 
         if (mcpServerConfig.includes('$vars')) {
             const appDataSource = options.appDataSource as DataSource
             const databaseEntities = options.databaseEntities as IDatabaseEntity
-
-            const variables = await getVars(appDataSource, databaseEntities, nodeData, options)
+            // If options.workspaceId is not set, create a new options object with the workspaceId for getVars.
+            const optionsWithWorkspaceId = options.workspaceId ? options : { ...options, workspaceId }
+            const variables = await getVars(appDataSource, databaseEntities, nodeData, optionsWithWorkspaceId)
             sandbox['$vars'] = prepareSandboxVars(variables)
         }
 
-        const workspaceId = options?.searchOptions?.workspaceId?._value || options?.workspaceId
-
         let canonicalConfig
         try {
             canonicalConfig = JSON.parse(mcpServerConfig)

packages/components/nodes/tools/ReadFile/ReadFile.ts

@@ -1,147 +0,0 @@
-import { z } from 'zod'
-import path from 'path'
-import { StructuredTool, ToolParams } from '@langchain/core/tools'
-import { Serializable } from '@langchain/core/load/serializable'
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { getBaseClasses, getUserHome } from '../../../src/utils'
-import { SecureFileStore, FileSecurityConfig } from '../../../src/SecureFileStore'
-
-abstract class BaseFileStore extends Serializable {
-    abstract readFile(path: string): Promise<string>
-    abstract writeFile(path: string, contents: string): Promise<void>
-}
-
-class ReadFile_Tools implements INode {
-    label: string
-    name: string
-    version: number
-    description: string
-    type: string
-    icon: string
-    category: string
-    baseClasses: string[]
-    inputs: INodeParams[]
-    warning: string
-
-    constructor() {
-        this.label = 'Read File'
-        this.name = 'readFile'
-        this.version = 2.0
-        this.type = 'ReadFile'
-        this.icon = 'readfile.svg'
-        this.category = 'Tools'
-        this.warning = 'This tool can be used to read files from the disk. It is recommended to use this tool with caution.'
-        this.description = 'Read file from disk'
-        this.baseClasses = [this.type, 'Tool', ...getBaseClasses(ReadFileTool)]
-        this.inputs = [
-            {
-                label: 'Workspace Path',
-                name: 'workspacePath',
-                placeholder: `C:\\Users\\User\\MyProject`,
-                type: 'string',
-                description: 'Base workspace directory for file operations. All file paths will be relative to this directory.',
-                optional: true
-            },
-            {
-                label: 'Enforce Workspace Boundaries',
-                name: 'enforceWorkspaceBoundaries',
-                type: 'boolean',
-                description: 'When enabled, restricts file access to the workspace directory for security. Recommended: true',
-                default: true,
-                optional: true
-            },
-            {
-                label: 'Max File Size (MB)',
-                name: 'maxFileSize',
-                type: 'number',
-                description: 'Maximum file size in megabytes that can be read',
-                default: 10,
-                optional: true
-            },
-            {
-                label: 'Allowed Extensions',
-                name: 'allowedExtensions',
-                type: 'string',
-                description: 'Comma-separated list of allowed file extensions (e.g., .txt,.json,.md). Leave empty to allow all.',
-                placeholder: '.txt,.json,.md,.py,.js',
-                optional: true
-            }
-        ]
-    }
-
-    async init(nodeData: INodeData): Promise<any> {
-        const workspacePath = nodeData.inputs?.workspacePath as string
-        const enforceWorkspaceBoundaries = nodeData.inputs?.enforceWorkspaceBoundaries !== false // Default to true
-        const maxFileSize = nodeData.inputs?.maxFileSize as number
-        const allowedExtensions = nodeData.inputs?.allowedExtensions as string
-
-        // Parse allowed extensions
-        const allowedExtensionsList = allowedExtensions ? allowedExtensions.split(',').map((ext) => ext.trim().toLowerCase()) : []
-
-        let store: BaseFileStore
-
-        if (workspacePath) {
-            // Create secure file store with workspace boundaries
-            const config: FileSecurityConfig = {
-                workspacePath,
-                enforceWorkspaceBoundaries,
-                maxFileSize: maxFileSize ? maxFileSize * 1024 * 1024 : undefined, // Convert MB to bytes
-                allowedExtensions: allowedExtensionsList.length > 0 ? allowedExtensionsList : undefined
-            }
-            store = new SecureFileStore(config)
-        } else {
-            // Fallback to current working directory with security warnings
-            if (enforceWorkspaceBoundaries) {
-                const fallbackWorkspacePath = path.join(getUserHome(), '.flowise')
-                console.warn(`[ReadFile] No workspace path specified, using ${fallbackWorkspacePath} with security restrictions`)
-                store = new SecureFileStore({
-                    workspacePath: fallbackWorkspacePath,
-                    enforceWorkspaceBoundaries: true,
-                    maxFileSize: maxFileSize ? maxFileSize * 1024 * 1024 : undefined,
-                    allowedExtensions: allowedExtensionsList.length > 0 ? allowedExtensionsList : undefined
-                })
-            } else {
-                console.warn('[ReadFile] SECURITY WARNING: Workspace boundaries disabled - unrestricted file access enabled')
-                store = SecureFileStore.createUnsecure()
-            }
-        }
-
-        return new ReadFileTool({ store })
-    }
-}
-
-interface ReadFileParams extends ToolParams {
-    store: BaseFileStore
-}
-
-/**
- * Class for reading files from the disk. Extends the StructuredTool
- * class.
- */
-export class ReadFileTool extends StructuredTool {
-    static lc_name() {
-        return 'ReadFileTool'
-    }
-
-    schema = z.object({
-        file_path: z.string().describe('name of file')
-    }) as any
-
-    name = 'read_file'
-
-    description = 'Read file from disk'
-
-    store: BaseFileStore
-
-    constructor({ store }: ReadFileParams) {
-        super(...arguments)
-
-        this.store = store
-    }
-
-    async _call({ file_path }: z.infer<typeof this.schema>) {
-        return await this.store.readFile(file_path)
-    }
-}
-
-module.exports = { nodeClass: ReadFile_Tools }

packages/components/nodes/tools/ReadFile/readfile.svg

@@ -1,4 +0,0 @@
-<svg width="32" height="32" viewBox="0 0 32 32" fill="none" xmlns="http://www.w3.org/2000/svg">
-<path d="M18 5H9C7.89543 5 7 5.89543 7 7V25C7 26.1046 7.89543 27 9 27H12M18 5L25 12M18 5V12H25M25 12V25C25 26.1046 24.1046 27 23 27H20" stroke="black" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"/>
-<path d="M16 17V29M16 17L13 20.1361M16 17L19 20.1361" stroke="black" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"/>
-</svg>

packages/components/nodes/tools/WriteFile/WriteFile.ts

@@ -1,149 +0,0 @@
-import { z } from 'zod'
-import path from 'path'
-import { StructuredTool, ToolParams } from '@langchain/core/tools'
-import { Serializable } from '@langchain/core/load/serializable'
-import { INode, INodeData, INodeParams } from '../../../src/Interface'
-import { getBaseClasses, getUserHome } from '../../../src/utils'
-import { SecureFileStore, FileSecurityConfig } from '../../../src/SecureFileStore'
-
-abstract class BaseFileStore extends Serializable {
-    abstract readFile(path: string): Promise<string>
-    abstract writeFile(path: string, contents: string): Promise<void>
-}
-
-class WriteFile_Tools implements INode {
-    label: string
-    name: string
-    version: number
-    description: string
-    type: string
-    icon: string
-    category: string
-    baseClasses: string[]
-    inputs: INodeParams[]
-    warning: string
-
-    constructor() {
-        this.label = 'Write File'
-        this.name = 'writeFile'
-        this.version = 2.0
-        this.type = 'WriteFile'
-        this.icon = 'writefile.svg'
-        this.category = 'Tools'
-        this.warning = 'This tool can be used to write files to the disk. It is recommended to use this tool with caution.'
-        this.description = 'Write file to disk'
-        this.baseClasses = [this.type, 'Tool', ...getBaseClasses(WriteFileTool)]
-        this.inputs = [
-            {
-                label: 'Workspace Path',
-                name: 'workspacePath',
-                placeholder: `C:\\Users\\User\\MyProject`,
-                type: 'string',
-                description: 'Base workspace directory for file operations. All file paths will be relative to this directory.',
-                optional: true
-            },
-            {
-                label: 'Enforce Workspace Boundaries',
-                name: 'enforceWorkspaceBoundaries',
-                type: 'boolean',
-                description: 'When enabled, restricts file access to the workspace directory for security. Recommended: true',
-                default: true,
-                optional: true
-            },
-            {
-                label: 'Max File Size (MB)',
-                name: 'maxFileSize',
-                type: 'number',
-                description: 'Maximum file size in megabytes that can be written',
-                default: 10,
-                optional: true
-            },
-            {
-                label: 'Allowed Extensions',
-                name: 'allowedExtensions',
-                type: 'string',
-                description: 'Comma-separated list of allowed file extensions (e.g., .txt,.json,.md). Leave empty to allow all.',
-                placeholder: '.txt,.json,.md,.py,.js',
-                optional: true
-            }
-        ]
-    }
-
-    async init(nodeData: INodeData): Promise<any> {
-        const workspacePath = nodeData.inputs?.workspacePath as string
-        const enforceWorkspaceBoundaries = nodeData.inputs?.enforceWorkspaceBoundaries !== false // Default to true
-        const maxFileSize = nodeData.inputs?.maxFileSize as number
-        const allowedExtensions = nodeData.inputs?.allowedExtensions as string
-
-        // Parse allowed extensions
-        const allowedExtensionsList = allowedExtensions ? allowedExtensions.split(',').map((ext) => ext.trim().toLowerCase()) : []
-
-        let store: BaseFileStore
-
-        if (workspacePath) {
-            // Create secure file store with workspace boundaries
-            const config: FileSecurityConfig = {
-                workspacePath,
-                enforceWorkspaceBoundaries,
-                maxFileSize: maxFileSize ? maxFileSize * 1024 * 1024 : undefined, // Convert MB to bytes
-                allowedExtensions: allowedExtensionsList.length > 0 ? allowedExtensionsList : undefined
-            }
-            store = new SecureFileStore(config)
-        } else {
-            // Fallback to current working directory with security warnings
-            if (enforceWorkspaceBoundaries) {
-                const fallbackWorkspacePath = path.join(getUserHome(), '.flowise')
-                console.warn(`[WriteFile] No workspace path specified, using ${fallbackWorkspacePath} with security restrictions`)
-                store = new SecureFileStore({
-                    workspacePath: fallbackWorkspacePath,
-                    enforceWorkspaceBoundaries: true,
-                    maxFileSize: maxFileSize ? maxFileSize * 1024 * 1024 : undefined,
-                    allowedExtensions: allowedExtensionsList.length > 0 ? allowedExtensionsList : undefined
-                })
-            } else {
-                console.warn('[WriteFile] SECURITY WARNING: Workspace boundaries disabled - unrestricted file access enabled')
-                store = SecureFileStore.createUnsecure()
-            }
-        }
-
-        return new WriteFileTool({ store })
-    }
-}
-
-interface WriteFileParams extends ToolParams {
-    store: BaseFileStore
-}
-
-/**
- * Class for writing data to files on the disk. Extends the StructuredTool
- * class.
- */
-export class WriteFileTool extends StructuredTool {
-    static lc_name() {
-        return 'WriteFileTool'
-    }
-
-    schema = z.object({
-        file_path: z.string().describe('name of file'),
-        text: z.string().describe('text to write to file')
-    }) as any
-
-    name = 'write_file'
-
-    description = 'Write file to disk'
-
-    store: BaseFileStore
-
-    constructor({ store, ...rest }: WriteFileParams) {
-        super(rest)
-
-        this.store = store
-    }
-
-    async _call({ file_path, text }: z.infer<typeof this.schema>) {
-        await this.store.writeFile(file_path, text)
-        return `File written to ${file_path} successfully.`
-    }
-}
-
-module.exports = { nodeClass: WriteFile_Tools }

packages/components/nodes/tools/WriteFile/writefile.svg

@@ -1,4 +0,0 @@
-<svg width="32" height="32" viewBox="0 0 32 32" fill="none" xmlns="http://www.w3.org/2000/svg">
-<path d="M25 18V25C25 26.1046 24.1046 27 23 27H9C7.89543 27 7 26.1046 7 25V7C7 5.89543 7.89543 5 9 5H18L19 6" stroke="black" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"/>
-<path d="M12 19.3284V22H14.6716C15.202 22 15.7107 21.7893 16.0858 21.4142L24.5858 12.9142C25.3668 12.1332 25.3668 10.8668 24.5858 10.0858L23.9142 9.41421C23.1332 8.63316 21.8668 8.63317 21.0858 9.41421L12.5858 17.9142C12.2107 18.2893 12 18.798 12 19.3284Z" stroke="black" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"/>
-</svg>

packages/components/nodes/utilities/CustomFunction/CustomFunction.ts

@@ -84,11 +84,16 @@ class CustomFunction_Utilities implements INode {
 
         const variables = await getVars(appDataSource, databaseEntities, nodeData, options)
         const flow = {
+            input,
             chatflowId: options.chatflowid,
             sessionId: options.sessionId,
             chatId: options.chatId,
-            rawOutput: options.rawOutput || '',
-            input
+            rawOutput: options.postProcessing?.rawOutput || '',
+            chatHistory: options.postProcessing?.chatHistory || [],
+            sourceDocuments: options.postProcessing?.sourceDocuments,
+            usedTools: options.postProcessing?.usedTools,
+            artifacts: options.postProcessing?.artifacts,
+            fileAnnotations: options.postProcessing?.fileAnnotations
         }
 
         let inputVars: ICommonObject = {}

packages/components/nodes/vectorstores/Chroma/Chroma.ts

@@ -186,7 +186,11 @@ class Chroma_VectorStores implements INode {
                     const vectorStoreName = collectionName
                     await recordManager.createSchema()
                     ;(recordManager as any).namespace = (recordManager as any).namespace + '_' + vectorStoreName
-                    const keys: string[] = await recordManager.listKeys({})
+                    const filterKeys: ICommonObject = {}
+                    if (options.docId) {
+                        filterKeys.docId = options.docId
+                    }
+                    const keys: string[] = await recordManager.listKeys(filterKeys)
 
                     const chromaStore = new ChromaExtended(embeddings, obj)
 

packages/components/nodes/vectorstores/Elasticsearch/Elasticsearch.ts

@@ -198,7 +198,11 @@ class Elasticsearch_VectorStores implements INode {
                     const vectorStoreName = indexName
                     await recordManager.createSchema()
                     ;(recordManager as any).namespace = (recordManager as any).namespace + '_' + vectorStoreName
-                    const keys: string[] = await recordManager.listKeys({})
+                    const filterKeys: ICommonObject = {}
+                    if (options.docId) {
+                        filterKeys.docId = options.docId
+                    }
+                    const keys: string[] = await recordManager.listKeys(filterKeys)
 
                     await vectorStore.delete({ ids: keys })
                     await recordManager.deleteKeys(keys)

packages/components/nodes/vectorstores/Pinecone/Pinecone.ts

@@ -212,7 +212,11 @@ class Pinecone_VectorStores implements INode {
                     const vectorStoreName = pineconeNamespace
                     await recordManager.createSchema()
                     ;(recordManager as any).namespace = (recordManager as any).namespace + '_' + vectorStoreName
-                    const keys: string[] = await recordManager.listKeys({})
+                    const filterKeys: ICommonObject = {}
+                    if (options.docId) {
+                        filterKeys.docId = options.docId
+                    }
+                    const keys: string[] = await recordManager.listKeys(filterKeys)
 
                     await pineconeStore.delete({ ids: keys })
                     await recordManager.deleteKeys(keys)

packages/components/nodes/vectorstores/Postgres/Postgres.ts

@@ -49,7 +49,7 @@ class Postgres_VectorStores implements INode {
     constructor() {
         this.label = 'Postgres'
         this.name = 'postgres'
-        this.version = 7.0
+        this.version = 7.1
         this.type = 'Postgres'
         this.icon = 'postgres.svg'
         this.category = 'Vector Stores'
@@ -173,6 +173,15 @@ class Postgres_VectorStores implements INode {
                 additionalParams: true,
                 optional: true
             },
+            {
+                label: 'Upsert Batch Size',
+                name: 'batchSize',
+                type: 'number',
+                step: 1,
+                description: 'Upsert in batches of size N',
+                additionalParams: true,
+                optional: true
+            },
             {
                 label: 'Additional Configuration',
                 name: 'additionalConfig',
@@ -232,6 +241,7 @@ class Postgres_VectorStores implements INode {
             const docs = nodeData.inputs?.document as Document[]
             const recordManager = nodeData.inputs?.recordManager
             const isFileUploadEnabled = nodeData.inputs?.fileUpload as boolean
+            const _batchSize = nodeData.inputs?.batchSize
             const vectorStoreDriver: VectorStoreDriver = Postgres_VectorStores.getDriverFromConfig(nodeData, options)
 
             const flattenDocs = docs && docs.length ? flatten(docs) : []
@@ -265,7 +275,15 @@ class Postgres_VectorStores implements INode {
 
                     return res
                 } else {
-                    await vectorStoreDriver.fromDocuments(finalDocs)
+                    if (_batchSize) {
+                        const batchSize = parseInt(_batchSize, 10)
+                        for (let i = 0; i < finalDocs.length; i += batchSize) {
+                            const batch = finalDocs.slice(i, i + batchSize)
+                            await vectorStoreDriver.fromDocuments(batch)
+                        }
+                    } else {
+                        await vectorStoreDriver.fromDocuments(finalDocs)
+                    }
 
                     return { numAdded: finalDocs.length, addedDocs: finalDocs }
                 }
@@ -285,7 +303,11 @@ class Postgres_VectorStores implements INode {
                     const vectorStoreName = tableName
                     await recordManager.createSchema()
                     ;(recordManager as any).namespace = (recordManager as any).namespace + '_' + vectorStoreName
-                    const keys: string[] = await recordManager.listKeys({})
+                    const filterKeys: ICommonObject = {}
+                    if (options.docId) {
+                        filterKeys.docId = options.docId
+                    }
+                    const keys: string[] = await recordManager.listKeys(filterKeys)
 
                     await vectorStore.delete({ ids: keys })
                     await recordManager.deleteKeys(keys)

packages/components/nodes/vectorstores/Postgres/driver/TypeORM.ts

@@ -5,6 +5,11 @@ import { TypeORMVectorStore, TypeORMVectorStoreArgs, TypeORMVectorStoreDocument
 import { VectorStore } from '@langchain/core/vectorstores'
 import { Document } from '@langchain/core/documents'
 import { Pool } from 'pg'
+import { v4 as uuid } from 'uuid'
+
+type TypeORMAddDocumentOptions = {
+    ids?: string[]
+}
 
 export class TypeORMDriver extends VectorStoreDriver {
     protected _postgresConnectionOptions: DataSourceOptions
@@ -95,15 +100,45 @@ export class TypeORMDriver extends VectorStoreDriver {
                 try {
                     instance.appDataSource.getRepository(instance.documentEntity).delete(ids)
                 } catch (e) {
-                    console.error('Failed to delete')
+                    console.error('Failed to delete', e)
                 }
             }
         }
 
-        const baseAddVectorsFn = instance.addVectors.bind(instance)
+        instance.addVectors = async (
+            vectors: number[][],
+            documents: Document[],
+            documentOptions?: TypeORMAddDocumentOptions
+        ): Promise<void> => {
+            const rows = vectors.map((embedding, idx) => {
+                const embeddingString = `[${embedding.join(',')}]`
+                const documentRow = {
+                    id: documentOptions?.ids?.length ? documentOptions.ids[idx] : uuid(),
+                    pageContent: documents[idx].pageContent,
+                    embedding: embeddingString,
+                    metadata: documents[idx].metadata
+                }
+                return documentRow
+            })
 
-        instance.addVectors = async (vectors, documents) => {
-            return baseAddVectorsFn(vectors, this.sanitizeDocuments(documents))
+            const documentRepository = instance.appDataSource.getRepository(instance.documentEntity)
+            const _batchSize = this.nodeData.inputs?.batchSize
+            const chunkSize = _batchSize ? parseInt(_batchSize, 10) : 500
+
+            for (let i = 0; i < rows.length; i += chunkSize) {
+                const chunk = rows.slice(i, i + chunkSize)
+                try {
+                    await documentRepository.save(chunk)
+                } catch (e) {
+                    console.error(e)
+                    throw new Error(`Error inserting: ${chunk[0].pageContent}`)
+                }
+            }
+        }
+
+        instance.addDocuments = async (documents: Document[], options?: { ids?: string[] }): Promise<void> => {
+            const texts = documents.map(({ pageContent }) => pageContent)
+            return (instance.addVectors as any)(await this.getEmbeddings().embedDocuments(texts), documents, options)
         }
 
         return instance

packages/components/nodes/vectorstores/Qdrant/Qdrant.ts

@@ -385,7 +385,11 @@ class Qdrant_VectorStores implements INode {
                     const vectorStoreName = collectionName
                     await recordManager.createSchema()
                     ;(recordManager as any).namespace = (recordManager as any).namespace + '_' + vectorStoreName
-                    const keys: string[] = await recordManager.listKeys({})
+                    const filterKeys: ICommonObject = {}
+                    if (options.docId) {
+                        filterKeys.docId = options.docId
+                    }
+                    const keys: string[] = await recordManager.listKeys(filterKeys)
 
                     await vectorStore.delete({ ids: keys })
                     await recordManager.deleteKeys(keys)

packages/components/nodes/vectorstores/Supabase/Supabase.ts

@@ -197,7 +197,11 @@ class Supabase_VectorStores implements INode {
                     const vectorStoreName = tableName + '_' + queryName
                     await recordManager.createSchema()
                     ;(recordManager as any).namespace = (recordManager as any).namespace + '_' + vectorStoreName
-                    const keys: string[] = await recordManager.listKeys({})
+                    const filterKeys: ICommonObject = {}
+                    if (options.docId) {
+                        filterKeys.docId = options.docId
+                    }
+                    const keys: string[] = await recordManager.listKeys(filterKeys)
 
                     await supabaseStore.delete({ ids: keys })
                     await recordManager.deleteKeys(keys)

packages/components/nodes/vectorstores/Upstash/Upstash.ts

@@ -187,7 +187,11 @@ class Upstash_VectorStores implements INode {
                     const vectorStoreName = UPSTASH_VECTOR_REST_URL
                     await recordManager.createSchema()
                     ;(recordManager as any).namespace = (recordManager as any).namespace + '_' + vectorStoreName
-                    const keys: string[] = await recordManager.listKeys({})
+                    const filterKeys: ICommonObject = {}
+                    if (options.docId) {
+                        filterKeys.docId = options.docId
+                    }
+                    const keys: string[] = await recordManager.listKeys(filterKeys)
 
                     await upstashStore.delete({ ids: keys })
                     await recordManager.deleteKeys(keys)

packages/components/nodes/vectorstores/Weaviate/Weaviate.ts

@@ -252,7 +252,11 @@ class Weaviate_VectorStores implements INode {
                     const vectorStoreName = weaviateTextKey ? weaviateIndex + '_' + weaviateTextKey : weaviateIndex
                     await recordManager.createSchema()
                     ;(recordManager as any).namespace = (recordManager as any).namespace + '_' + vectorStoreName
-                    const keys: string[] = await recordManager.listKeys({})
+                    const filterKeys: ICommonObject = {}
+                    if (options.docId) {
+                        filterKeys.docId = options.docId
+                    }
+                    const keys: string[] = await recordManager.listKeys(filterKeys)
 
                     await weaviateStore.delete({ ids: keys })
                     await recordManager.deleteKeys(keys)

packages/components/package.json

@@ -1,6 +1,6 @@
 {
     "name": "flowise-components",
-    "version": "3.0.10",
+    "version": "3.0.11",
     "description": "Flowiseai Components",
     "main": "dist/src/index",
     "types": "dist/src/index.d.ts",
@@ -42,7 +42,8 @@
         "@google-ai/generativelanguage": "^2.5.0",
         "@google-cloud/storage": "^7.15.2",
         "@google/generative-ai": "^0.24.0",
-        "@huggingface/inference": "^2.6.1",
+        "@grpc/grpc-js": "^1.10.10",
+        "@huggingface/inference": "^4.13.2",
         "@langchain/anthropic": "0.3.33",
         "@langchain/aws": "^0.1.11",
         "@langchain/baidu-qianfan": "^0.1.0",
@@ -73,6 +74,20 @@
         "@modelcontextprotocol/server-slack": "^2025.1.17",
         "@notionhq/client": "^2.2.8",
         "@opensearch-project/opensearch": "^1.2.0",
+        "@opentelemetry/api": "1.9.0",
+        "@opentelemetry/auto-instrumentations-node": "^0.52.0",
+        "@opentelemetry/core": "1.27.0",
+        "@opentelemetry/exporter-metrics-otlp-grpc": "0.54.0",
+        "@opentelemetry/exporter-metrics-otlp-http": "0.54.0",
+        "@opentelemetry/exporter-metrics-otlp-proto": "0.54.0",
+        "@opentelemetry/exporter-trace-otlp-grpc": "0.54.0",
+        "@opentelemetry/exporter-trace-otlp-http": "0.54.0",
+        "@opentelemetry/exporter-trace-otlp-proto": "0.54.0",
+        "@opentelemetry/resources": "1.27.0",
+        "@opentelemetry/sdk-metrics": "1.27.0",
+        "@opentelemetry/sdk-node": "^0.54.0",
+        "@opentelemetry/sdk-trace-base": "1.27.0",
+        "@opentelemetry/semantic-conventions": "1.27.0",
         "@pinecone-database/pinecone": "4.0.0",
         "@qdrant/js-client-rest": "^1.9.0",
         "@stripe/agent-toolkit": "^0.1.20",

packages/components/src/SecureFileStore.ts

@@ -1,167 +0,0 @@
-import { Serializable } from '@langchain/core/load/serializable'
-import { NodeFileStore } from 'langchain/stores/file/node'
-import { isUnsafeFilePath, isWithinWorkspace } from './validator'
-import * as path from 'path'
-import * as fs from 'fs'
-
-/**
- * Security configuration for file operations
- */
-export interface FileSecurityConfig {
-    /** Base workspace path - all file operations are restricted to this directory */
-    workspacePath: string
-    /** Whether to enforce workspace boundaries (default: true) */
-    enforceWorkspaceBoundaries?: boolean
-    /** Maximum file size in bytes (default: 10MB) */
-    maxFileSize?: number
-    /** Allowed file extensions (if empty, all extensions allowed) */
-    allowedExtensions?: string[]
-    /** Blocked file extensions */
-    blockedExtensions?: string[]
-}
-
-/**
- * Secure file store that enforces workspace boundaries and validates file operations
- */
-export class SecureFileStore extends Serializable {
-    lc_namespace = ['flowise', 'components', 'stores', 'file']
-
-    private config: Required<FileSecurityConfig>
-    private nodeFileStore: NodeFileStore
-
-    constructor(config: FileSecurityConfig) {
-        super()
-
-        // Set default configuration
-        this.config = {
-            workspacePath: config.workspacePath,
-            enforceWorkspaceBoundaries: config.enforceWorkspaceBoundaries ?? true,
-            maxFileSize: config.maxFileSize ?? 10 * 1024 * 1024, // 10MB default
-            allowedExtensions: config.allowedExtensions ?? [],
-            blockedExtensions: config.blockedExtensions ?? [
-                '.exe',
-                '.bat',
-                '.cmd',
-                '.sh',
-                '.ps1',
-                '.vbs',
-                '.scr',
-                '.com',
-                '.pif',
-                '.dll',
-                '.sys',
-                '.msi',
-                '.jar'
-            ]
-        }
-
-        // Validate workspace path
-        if (!this.config.workspacePath || !path.isAbsolute(this.config.workspacePath)) {
-            throw new Error('Workspace path must be an absolute path')
-        }
-
-        // Ensure workspace directory exists
-        if (!fs.existsSync(this.config.workspacePath)) {
-            throw new Error(`Workspace directory does not exist: ${this.config.workspacePath}`)
-        }
-
-        // Initialize the underlying NodeFileStore with workspace path
-        this.nodeFileStore = new NodeFileStore(this.config.workspacePath)
-    }
-
-    /**
-     * Validates a file path against security policies
-     */
-    private validateFilePath(filePath: string): void {
-        // Check for unsafe path patterns
-        if (isUnsafeFilePath(filePath)) {
-            throw new Error(`Unsafe file path detected: ${filePath}`)
-        }
-
-        // Enforce workspace boundaries if enabled
-        if (this.config.enforceWorkspaceBoundaries) {
-            if (!isWithinWorkspace(filePath, this.config.workspacePath)) {
-                throw new Error(`File path outside workspace boundaries: ${filePath}`)
-            }
-        }
-
-        // Check file extension
-        const ext = path.extname(filePath).toLowerCase()
-
-        // Check blocked extensions
-        if (this.config.blockedExtensions.includes(ext)) {
-            throw new Error(`File extension not allowed: ${ext}`)
-        }
-
-        // Check allowed extensions (if specified)
-        if (this.config.allowedExtensions.length > 0 && !this.config.allowedExtensions.includes(ext)) {
-            throw new Error(`File extension not in allowed list: ${ext}`)
-        }
-    }
-
-    /**
-     * Validates file size
-     */
-    private validateFileSize(content: string): void {
-        const sizeInBytes = Buffer.byteLength(content, 'utf8')
-        if (sizeInBytes > this.config.maxFileSize) {
-            throw new Error(`File size exceeds maximum allowed size: ${sizeInBytes} > ${this.config.maxFileSize}`)
-        }
-    }
-
-    /**
-     * Reads a file with security validation
-     */
-    async readFile(filePath: string): Promise<string> {
-        this.validateFilePath(filePath)
-
-        try {
-            return await this.nodeFileStore.readFile(filePath)
-        } catch (error) {
-            // Provide generic error message to avoid information leakage
-            throw new Error(`Failed to read file: ${path.basename(filePath)}`)
-        }
-    }
-
-    /**
-     * Writes a file with security validation
-     */
-    async writeFile(filePath: string, contents: string): Promise<void> {
-        this.validateFilePath(filePath)
-        this.validateFileSize(contents)
-
-        try {
-            // Ensure the directory exists
-            const dir = path.dirname(path.resolve(this.config.workspacePath, filePath))
-            if (!fs.existsSync(dir)) {
-                fs.mkdirSync(dir, { recursive: true })
-            }
-
-            await this.nodeFileStore.writeFile(filePath, contents)
-        } catch (error) {
-            // Provide generic error message to avoid information leakage
-            throw new Error(`Failed to write file: ${path.basename(filePath)}`)
-        }
-    }
-
-    /**
-     * Gets the workspace configuration
-     */
-    getConfig(): Readonly<Required<FileSecurityConfig>> {
-        return { ...this.config }
-    }
-
-    /**
-     * Creates a secure file store with workspace enforcement disabled (for backward compatibility)
-     * WARNING: This should only be used when absolutely necessary and with proper user consent
-     */
-    static createUnsecure(basePath?: string): SecureFileStore {
-        const workspacePath = basePath || process.cwd()
-        return new SecureFileStore({
-            workspacePath,
-            enforceWorkspaceBoundaries: false,
-            maxFileSize: 50 * 1024 * 1024, // 50MB for insecure mode
-            blockedExtensions: [] // No extension restrictions in insecure mode
-        })
-    }
-}

packages/components/src/handler.ts

@@ -1774,7 +1774,7 @@ export class AnalyticHandler {
         }
 
         if (Object.prototype.hasOwnProperty.call(this.handlers, 'lunary')) {
-            const toolEventId: string = this.handlers['lunary'].llmEvent[returnIds['lunary'].toolEvent]
+            const toolEventId: string = this.handlers['lunary'].toolEvent[returnIds['lunary'].toolEvent]
             const monitor = this.handlers['lunary'].client
 
             if (monitor && toolEventId) {

packages/components/src/indexing.ts

@@ -8,6 +8,10 @@ import { IndexingResult } from './Interface'
 
 type Metadata = Record<string, unknown>
 
+export interface ExtendedRecordManagerInterface extends RecordManagerInterface {
+    update(keys: Array<{ uid: string; docId: string }> | string[], updateOptions?: Record<string, any>): Promise<void>
+}
+
 type StringOrDocFunc = string | ((doc: DocumentInterface) => string)
 
 export interface HashedDocumentInterface extends DocumentInterface {
@@ -207,7 +211,7 @@ export const _isBaseDocumentLoader = (arg: any): arg is BaseDocumentLoader => {
 
 interface IndexArgs {
     docsSource: BaseDocumentLoader | DocumentInterface[]
-    recordManager: RecordManagerInterface
+    recordManager: ExtendedRecordManagerInterface
     vectorStore: VectorStore
     options?: IndexOptions
 }
@@ -275,7 +279,7 @@ export async function index(args: IndexArgs): Promise<IndexingResult> {
 
         const uids: string[] = []
         const docsToIndex: DocumentInterface[] = []
-        const docsToUpdate: string[] = []
+        const docsToUpdate: Array<{ uid: string; docId: string }> = []
         const seenDocs = new Set<string>()
         hashedDocs.forEach((hashedDoc, i) => {
             const docExists = batchExists[i]
@@ -283,7 +287,7 @@ export async function index(args: IndexArgs): Promise<IndexingResult> {
                 if (forceUpdate) {
                     seenDocs.add(hashedDoc.uid)
                 } else {
-                    docsToUpdate.push(hashedDoc.uid)
+                    docsToUpdate.push({ uid: hashedDoc.uid, docId: hashedDoc.metadata.docId as string })
                     return
                 }
             }
@@ -308,7 +312,7 @@ export async function index(args: IndexArgs): Promise<IndexingResult> {
         }
 
         await recordManager.update(
-            hashedDocs.map((doc) => doc.uid),
+            hashedDocs.map((doc) => ({ uid: doc.uid, docId: doc.metadata.docId as string })),
             { timeAtLeast: indexStartDt, groupIds: sourceIds }
         )
 

packages/components/src/utils.ts

@@ -8,6 +8,7 @@ import { cloneDeep, omit, get } from 'lodash'
 import TurndownService from 'turndown'
 import { DataSource, Equal } from 'typeorm'
 import { ICommonObject, IDatabaseEntity, IFileUpload, IMessage, INodeData, IVariable, MessageContentImageUrl } from './Interface'
+import { BaseChatModel } from '@langchain/core/language_models/chat_models'
 import { AES, enc } from 'crypto-js'
 import { AIMessage, HumanMessage, BaseMessage } from '@langchain/core/messages'
 import { Document } from '@langchain/core/documents'
@@ -1500,9 +1501,29 @@ export const executeJavaScriptCode = async (
 
             const sbx = await Sandbox.create({ apiKey: process.env.E2B_APIKEY, timeoutMs })
 
+            // Determine which libraries to install
+            const librariesToInstall = new Set<string>(libraries)
+
+            // Auto-detect required libraries from code
+            // Extract required modules from import/require statements
+            const importRegex = /(?:import\s+.*?\s+from\s+['"]([^'"]+)['"]|require\s*\(\s*['"]([^'"]+)['"]\s*\))/g
+            let match
+            while ((match = importRegex.exec(code)) !== null) {
+                const moduleName = match[1] || match[2]
+                // Extract base module name (e.g., 'typeorm' from 'typeorm/something')
+                const baseModuleName = moduleName.split('/')[0]
+                librariesToInstall.add(baseModuleName)
+            }
+
             // Install libraries
-            for (const library of libraries) {
-                await sbx.commands.run(`npm install ${library}`)
+            for (const library of librariesToInstall) {
+                // Validate library name to prevent command injection.
+                const validPackageNameRegex = /^(@[a-z0-9-~][a-z0-9-._~]*\/)?[a-z0-9-~][a-z0-9-._~]*$/
+                if (validPackageNameRegex.test(library)) {
+                    await sbx.commands.run(`npm install ${library}`)
+                } else {
+                    console.warn(`[Sandbox] Skipping installation of invalid module: ${library}`)
+                }
             }
 
             // Separate imports from the rest of the code for proper ES6 module structure
@@ -1921,3 +1942,160 @@ export async function parseWithTypeConversion<T extends z.ZodTypeAny>(schema: T,
         throw e
     }
 }
+
+/**
+ * Configures structured output for the LLM using Zod schema
+ * @param {BaseChatModel} llmNodeInstance - The LLM instance to configure
+ * @param {any[]} structuredOutput - Array of structured output schema definitions
+ * @returns {BaseChatModel} - The configured LLM instance
+ */
+export const configureStructuredOutput = (llmNodeInstance: BaseChatModel, structuredOutput: any[]): BaseChatModel => {
+    try {
+        const zodObj: ICommonObject = {}
+        for (const sch of structuredOutput) {
+            if (sch.type === 'string') {
+                zodObj[sch.key] = z.string().describe(sch.description || '')
+            } else if (sch.type === 'stringArray') {
+                zodObj[sch.key] = z.array(z.string()).describe(sch.description || '')
+            } else if (sch.type === 'number') {
+                zodObj[sch.key] = z.number().describe(sch.description || '')
+            } else if (sch.type === 'boolean') {
+                zodObj[sch.key] = z.boolean().describe(sch.description || '')
+            } else if (sch.type === 'enum') {
+                const enumValues = sch.enumValues?.split(',').map((item: string) => item.trim()) || []
+                zodObj[sch.key] = z
+                    .enum(enumValues.length ? (enumValues as [string, ...string[]]) : ['default'])
+                    .describe(sch.description || '')
+            } else if (sch.type === 'jsonArray') {
+                const jsonSchema = sch.jsonSchema
+                if (jsonSchema) {
+                    try {
+                        // Parse the JSON schema
+                        const schemaObj = JSON.parse(jsonSchema)
+
+                        // Create a Zod schema from the JSON schema
+                        const itemSchema = createZodSchemaFromJSON(schemaObj)
+
+                        // Create an array schema of the item schema
+                        zodObj[sch.key] = z.array(itemSchema).describe(sch.description || '')
+                    } catch (err) {
+                        console.error(`Error parsing JSON schema for ${sch.key}:`, err)
+                        // Fallback to generic array of records
+                        zodObj[sch.key] = z.array(z.record(z.any())).describe(sch.description || '')
+                    }
+                } else {
+                    // If no schema provided, use generic array of records
+                    zodObj[sch.key] = z.array(z.record(z.any())).describe(sch.description || '')
+                }
+            }
+        }
+        const structuredOutputSchema = z.object(zodObj)
+
+        // @ts-ignore
+        return llmNodeInstance.withStructuredOutput(structuredOutputSchema)
+    } catch (exception) {
+        console.error(exception)
+        return llmNodeInstance
+    }
+}
+
+/**
+ * Creates a Zod schema from a JSON schema object
+ * @param {any} jsonSchema - The JSON schema object
+ * @returns {z.ZodTypeAny} - A Zod schema
+ */
+export const createZodSchemaFromJSON = (jsonSchema: any): z.ZodTypeAny => {
+    // If the schema is an object with properties, create an object schema
+    if (typeof jsonSchema === 'object' && jsonSchema !== null) {
+        const schemaObj: Record<string, z.ZodTypeAny> = {}
+
+        // Process each property in the schema
+        for (const [key, value] of Object.entries(jsonSchema)) {
+            if (value === null) {
+                // Handle null values
+                schemaObj[key] = z.null()
+            } else if (typeof value === 'object' && !Array.isArray(value)) {
+                // Check if the property has a type definition
+                if ('type' in value) {
+                    const type = value.type as string
+                    const description = ('description' in value ? (value.description as string) : '') || ''
+
+                    // Create the appropriate Zod type based on the type property
+                    if (type === 'string') {
+                        schemaObj[key] = z.string().describe(description)
+                    } else if (type === 'number') {
+                        schemaObj[key] = z.number().describe(description)
+                    } else if (type === 'boolean') {
+                        schemaObj[key] = z.boolean().describe(description)
+                    } else if (type === 'array') {
+                        // If it's an array type, check if items is defined
+                        if ('items' in value && value.items) {
+                            const itemSchema = createZodSchemaFromJSON(value.items)
+                            schemaObj[key] = z.array(itemSchema).describe(description)
+                        } else {
+                            // Default to array of any if items not specified
+                            schemaObj[key] = z.array(z.any()).describe(description)
+                        }
+                    } else if (type === 'object') {
+                        // If it's an object type, check if properties is defined
+                        if ('properties' in value && value.properties) {
+                            const nestedSchema = createZodSchemaFromJSON(value.properties)
+                            schemaObj[key] = nestedSchema.describe(description)
+                        } else {
+                            // Default to record of any if properties not specified
+                            schemaObj[key] = z.record(z.any()).describe(description)
+                        }
+                    } else {
+                        // Default to any for unknown types
+                        schemaObj[key] = z.any().describe(description)
+                    }
+
+                    // Check if the property is optional
+                    if ('optional' in value && value.optional === true) {
+                        schemaObj[key] = schemaObj[key].optional()
+                    }
+                } else if (Array.isArray(value)) {
+                    // Array values without a type property
+                    if (value.length > 0) {
+                        // If the array has items, recursively create a schema for the first item
+                        const itemSchema = createZodSchemaFromJSON(value[0])
+                        schemaObj[key] = z.array(itemSchema)
+                    } else {
+                        // Empty array, allow any array
+                        schemaObj[key] = z.array(z.any())
+                    }
+                } else {
+                    // It's a nested object without a type property, recursively create schema
+                    schemaObj[key] = createZodSchemaFromJSON(value)
+                }
+            } else if (Array.isArray(value)) {
+                // Array values
+                if (value.length > 0) {
+                    // If the array has items, recursively create a schema for the first item
+                    const itemSchema = createZodSchemaFromJSON(value[0])
+                    schemaObj[key] = z.array(itemSchema)
+                } else {
+                    // Empty array, allow any array
+                    schemaObj[key] = z.array(z.any())
+                }
+            } else {
+                // For primitive values (which shouldn't be in the schema directly)
+                // Use the corresponding Zod type
+                if (typeof value === 'string') {
+                    schemaObj[key] = z.string()
+                } else if (typeof value === 'number') {
+                    schemaObj[key] = z.number()
+                } else if (typeof value === 'boolean') {
+                    schemaObj[key] = z.boolean()
+                } else {
+                    schemaObj[key] = z.any()
+                }
+            }
+        }
+
+        return z.object(schemaObj)
+    }
+
+    // Fallback to any for unknown types
+    return z.any()
+}

packages/components/src/validator.ts

@@ -69,36 +69,3 @@ export const isUnsafeFilePath = (filePath: string): boolean => {
 
     return dangerousPatterns.some((pattern) => pattern.test(filePath))
 }
-
-/**
- * Validates if a file path is within the allowed workspace boundaries
- * @param {string} filePath The file path to validate
- * @param {string} workspacePath The workspace base path
- * @returns {boolean} True if path is within workspace, false otherwise
- */
-export const isWithinWorkspace = (filePath: string, workspacePath: string): boolean => {
-    if (!filePath || !workspacePath) {
-        return false
-    }
-
-    try {
-        const path = require('path')
-
-        // Resolve both paths to absolute paths
-        const resolvedFilePath = path.resolve(workspacePath, filePath)
-        const resolvedWorkspacePath = path.resolve(workspacePath)
-
-        // Normalize paths to handle different separators
-        const normalizedFilePath = path.normalize(resolvedFilePath)
-        const normalizedWorkspacePath = path.normalize(resolvedWorkspacePath)
-
-        // Check if the file path starts with the workspace path
-        const relativePath = path.relative(normalizedWorkspacePath, normalizedFilePath)
-
-        // If relative path starts with '..' or is absolute, it's outside workspace
-        return !relativePath.startsWith('..') && !path.isAbsolute(relativePath)
-    } catch (error) {
-        // If any error occurs during path resolution, deny access
-        return false
-    }
-}

packages/server/README.md

@@ -41,7 +41,7 @@ cd Flowise/packages/server
 pnpm install
 ./node_modules/.bin/cypress install
 pnpm build
-#Only for writting new tests on local dev -> pnpm run cypress:open
+#Only for writing new tests on local dev -> pnpm run cypress:open
 pnpm run e2e
 ```
 

packages/server/marketplaces/agentflowsv2/SQL Agent.json

@@ -284,7 +284,7 @@
                 "inputAnchors": [],
                 "inputs": {
                     "customFunctionInputVariables": "",
-                    "customFunctionJavascriptFunction": "const { DataSource } = require('typeorm');\n\nconst HOST = 'localhost';\nconst USER = 'testuser';\nconst PASSWORD = 'testpwd';\nconst DATABASE = 'abudhabi';\nconst PORT = 5555;\n\nlet sqlSchemaPrompt = '';\n\nconst AppDataSource = new DataSource({\n  type: 'postgres',\n  host: HOST,\n  port: PORT,\n  username: USER,\n  password: PASSWORD,\n  database: DATABASE,\n  synchronize: false,\n  logging: false,\n});\n\nasync function getSQLPrompt() {\n  try {\n    await AppDataSource.initialize();\n    const queryRunner = AppDataSource.createQueryRunner();\n\n    // Get all user-defined tables (excluding system tables)\n    const tablesResult = await queryRunner.query(`\n      SELECT table_name\n      FROM information_schema.tables\n      WHERE table_schema = 'public' AND table_type = 'BASE TABLE'\n    `);\n\n    for (const tableRow of tablesResult) {\n      const tableName = tableRow.table_name;\n\n      const schemaInfo = await queryRunner.query(`\n        SELECT column_name, data_type, is_nullable\n        FROM information_schema.columns\n        WHERE table_name = '${tableName}'\n      `);\n\n      const createColumns = [];\n      const columnNames = [];\n\n      for (const column of schemaInfo) {\n        const name = column.column_name;\n        const type = column.data_type.toUpperCase();\n        const notNull = column.is_nullable === 'NO' ? 'NOT NULL' : '';\n        columnNames.push(name);\n        createColumns.push(`${name} ${type} ${notNull}`);\n      }\n\n      const sqlCreateTableQuery = `CREATE TABLE ${tableName} (${createColumns.join(', ')})`;\n      const sqlSelectTableQuery = `SELECT * FROM ${tableName} LIMIT 3`;\n\n      let allValues = [];\n      try {\n        const rows = await queryRunner.query(sqlSelectTableQuery);\n\n        allValues = rows.map(row =>\n          columnNames.map(col => row[col]).join(' ')\n        );\n      } catch (err) {\n        allValues.push('[ERROR FETCHING ROWS]');\n      }\n\n      sqlSchemaPrompt +=\n        sqlCreateTableQuery +\n        '\\n' +\n        sqlSelectTableQuery +\n        '\\n' +\n        columnNames.join(' ') +\n        '\\n' +\n        allValues.join('\\n') +\n        '\\n\\n';\n    }\n\n    await queryRunner.release();\n  } catch (err) {\n    console.error(err);\n    throw err;\n  }\n}\n\nasync function main() {\n  await getSQLPrompt();\n}\n\nawait main();\n\nreturn sqlSchemaPrompt;\n",
+                    "customFunctionJavascriptFunction": "const { DataSource } = require('typeorm');\nconst { Pool } = require('pg');\n\nconst HOST = 'localhost';\nconst USER = 'testuser';\nconst PASSWORD = 'testpwd';\nconst DATABASE = 'abudhabi';\nconst PORT = 5555;\n\nlet sqlSchemaPrompt = '';\n\nconst AppDataSource = new DataSource({\n  type: 'postgres',\n  host: HOST,\n  port: PORT,\n  username: USER,\n  password: PASSWORD,\n  database: DATABASE,\n  synchronize: false,\n  logging: false,\n});\n\nasync function getSQLPrompt() {\n  try {\n    await AppDataSource.initialize();\n    const queryRunner = AppDataSource.createQueryRunner();\n\n    // Get all user-defined tables (excluding system tables)\n    const tablesResult = await queryRunner.query(`\n      SELECT table_name\n      FROM information_schema.tables\n      WHERE table_schema = 'public' AND table_type = 'BASE TABLE'\n    `);\n\n    for (const tableRow of tablesResult) {\n      const tableName = tableRow.table_name;\n\n      const schemaInfo = await queryRunner.query(`\n        SELECT column_name, data_type, is_nullable\n        FROM information_schema.columns\n        WHERE table_name = '${tableName}'\n      `);\n\n      const createColumns = [];\n      const columnNames = [];\n\n      for (const column of schemaInfo) {\n        const name = column.column_name;\n        const type = column.data_type.toUpperCase();\n        const notNull = column.is_nullable === 'NO' ? 'NOT NULL' : '';\n        columnNames.push(name);\n        createColumns.push(`${name} ${type} ${notNull}`);\n      }\n\n      const sqlCreateTableQuery = `CREATE TABLE ${tableName} (${createColumns.join(', ')})`;\n      const sqlSelectTableQuery = `SELECT * FROM ${tableName} LIMIT 3`;\n\n      let allValues = [];\n      try {\n        const rows = await queryRunner.query(sqlSelectTableQuery);\n\n        allValues = rows.map(row =>\n          columnNames.map(col => row[col]).join(' ')\n        );\n      } catch (err) {\n        allValues.push('[ERROR FETCHING ROWS]');\n      }\n\n      sqlSchemaPrompt +=\n        sqlCreateTableQuery +\n        '\\n' +\n        sqlSelectTableQuery +\n        '\\n' +\n        columnNames.join(' ') +\n        '\\n' +\n        allValues.join('\\n') +\n        '\\n\\n';\n    }\n\n    await queryRunner.release();\n  } catch (err) {\n    console.error(err);\n    throw err;\n  }\n}\n\nasync function main() {\n  await getSQLPrompt();\n}\n\nawait main();\n\nreturn sqlSchemaPrompt;\n",
                     "customFunctionUpdateState": ""
                 },
                 "outputAnchors": [
@@ -913,7 +913,7 @@
                             "variableValue": "<p><span class=\"variable\" data-type=\"mention\" data-id=\"$flow.state.sqlQuery\" data-label=\"$flow.state.sqlQuery\">{{ $flow.state.sqlQuery }}</span> </p>"
                         }
                     ],
-                    "customFunctionJavascriptFunction": "const { DataSource } = require('typeorm');\n\n// Configuration\nconst HOST = 'localhost';\nconst USER = 'testuser';\nconst PASSWORD = 'testpwd';\nconst DATABASE = 'abudhabi';\nconst PORT = 5555;\n\nconst sqlQuery = $sqlQuery;\n\nconst AppDataSource = new DataSource({\n  type: 'postgres',\n  host: HOST,\n  port: PORT,\n  username: USER,\n  password: PASSWORD,\n  database: DATABASE,\n  synchronize: false,\n  logging: false,\n});\n\nlet formattedResult = '';\n\nasync function runSQLQuery(query) {\n  try {\n    await AppDataSource.initialize();\n    const queryRunner = AppDataSource.createQueryRunner();\n\n    const rows = await queryRunner.query(query);\n    console.log('rows =', rows);\n\n    if (rows.length === 0) {\n      formattedResult = '[No results returned]';\n    } else {\n      const columnNames = Object.keys(rows[0]);\n      const header = columnNames.join(' ');\n      const values = rows.map(row =>\n        columnNames.map(col => row[col]).join(' ')\n      );\n\n      formattedResult = query + '\\n' + header + '\\n' + values.join('\\n');\n    }\n\n    await queryRunner.release();\n  } catch (err) {\n    console.error('[ERROR]', err);\n    formattedResult = `[Error executing query]: ${err}`;\n  }\n\n  return formattedResult;\n}\n\nasync function main() {\n  formattedResult = await runSQLQuery(sqlQuery);\n}\n\nawait main();\n\nreturn formattedResult;\n",
+                    "customFunctionJavascriptFunction": "const { DataSource } = require('typeorm');\nconst { Pool } = require('pg');\n\n// Configuration\nconst HOST = 'localhost';\nconst USER = 'testuser';\nconst PASSWORD = 'testpwd';\nconst DATABASE = 'abudhabi';\nconst PORT = 5555;\n\nconst sqlQuery = $sqlQuery;\n\nconst AppDataSource = new DataSource({\n  type: 'postgres',\n  host: HOST,\n  port: PORT,\n  username: USER,\n  password: PASSWORD,\n  database: DATABASE,\n  synchronize: false,\n  logging: false,\n});\n\nlet formattedResult = '';\n\nasync function runSQLQuery(query) {\n  try {\n    await AppDataSource.initialize();\n    const queryRunner = AppDataSource.createQueryRunner();\n\n    const rows = await queryRunner.query(query);\n    console.log('rows =', rows);\n\n    if (rows.length === 0) {\n      formattedResult = '[No results returned]';\n    } else {\n      const columnNames = Object.keys(rows[0]);\n      const header = columnNames.join(' ');\n      const values = rows.map(row =>\n        columnNames.map(col => row[col]).join(' ')\n      );\n\n      formattedResult = query + '\\n' + header + '\\n' + values.join('\\n');\n    }\n\n    await queryRunner.release();\n  } catch (err) {\n    console.error('[ERROR]', err);\n    formattedResult = `[Error executing query]: ${err}`;\n  }\n\n  return formattedResult;\n}\n\nasync function main() {\n  formattedResult = await runSQLQuery(sqlQuery);\n}\n\nawait main();\n\nreturn formattedResult;\n",
                     "customFunctionUpdateState": ""
                 },
                 "outputAnchors": [

packages/server/package.json

@@ -1,6 +1,6 @@
 {
     "name": "flowise",
-    "version": "3.0.10",
+    "version": "3.0.11",
     "description": "Flowiseai Server",
     "main": "dist/index",
     "types": "dist/index.d.ts",
@@ -66,7 +66,7 @@
         "@google-cloud/logging-winston": "^6.0.0",
         "@keyv/redis": "^4.2.0",
         "@oclif/core": "4.0.7",
-        "@opentelemetry/api": "^1.3.0",
+        "@opentelemetry/api": "1.9.0",
         "@opentelemetry/auto-instrumentations-node": "^0.52.0",
         "@opentelemetry/core": "1.27.0",
         "@opentelemetry/exporter-metrics-otlp-grpc": "0.54.0",
@@ -119,12 +119,12 @@
         "lodash": "^4.17.21",
         "moment": "^2.29.3",
         "moment-timezone": "^0.5.34",
-        "multer": "^1.4.5-lts.1",
+        "multer": "^2.0.2",
         "multer-cloud-storage": "^4.0.0",
         "multer-s3": "^3.0.1",
         "mysql2": "^3.11.3",
         "nanoid": "3",
-        "nodemailer": "^6.9.14",
+        "nodemailer": "^7.0.7",
         "openai": "^4.96.0",
         "passport": "^0.7.0",
         "passport-auth0": "^1.4.4",

packages/server/src/UsageCacheManager.ts

@@ -37,7 +37,19 @@ export class UsageCacheManager {
         if (process.env.MODE === MODE.QUEUE) {
             let redisConfig: string | Record<string, any>
             if (process.env.REDIS_URL) {
-                redisConfig = process.env.REDIS_URL
+                redisConfig = {
+                    url: process.env.REDIS_URL,
+                    socket: {
+                        keepAlive:
+                            process.env.REDIS_KEEP_ALIVE && !isNaN(parseInt(process.env.REDIS_KEEP_ALIVE, 10))
+                                ? parseInt(process.env.REDIS_KEEP_ALIVE, 10)
+                                : undefined
+                    },
+                    pingInterval:
+                        process.env.REDIS_KEEP_ALIVE && !isNaN(parseInt(process.env.REDIS_KEEP_ALIVE, 10))
+                            ? parseInt(process.env.REDIS_KEEP_ALIVE, 10)
+                            : undefined
+                }
             } else {
                 redisConfig = {
                     username: process.env.REDIS_USERNAME || undefined,
@@ -48,8 +60,16 @@ export class UsageCacheManager {
                         tls: process.env.REDIS_TLS === 'true',
                         cert: process.env.REDIS_CERT ? Buffer.from(process.env.REDIS_CERT, 'base64') : undefined,
                         key: process.env.REDIS_KEY ? Buffer.from(process.env.REDIS_KEY, 'base64') : undefined,
-                        ca: process.env.REDIS_CA ? Buffer.from(process.env.REDIS_CA, 'base64') : undefined
-                    }
+                        ca: process.env.REDIS_CA ? Buffer.from(process.env.REDIS_CA, 'base64') : undefined,
+                        keepAlive:
+                            process.env.REDIS_KEEP_ALIVE && !isNaN(parseInt(process.env.REDIS_KEEP_ALIVE, 10))
+                                ? parseInt(process.env.REDIS_KEEP_ALIVE, 10)
+                                : undefined
+                    },
+                    pingInterval:
+                        process.env.REDIS_KEEP_ALIVE && !isNaN(parseInt(process.env.REDIS_KEEP_ALIVE, 10))
+                            ? parseInt(process.env.REDIS_KEEP_ALIVE, 10)
+                            : undefined
                 }
             }
             this.cache = createCache({

packages/server/src/controllers/documentstore/index.ts

@@ -465,9 +465,10 @@ const insertIntoVectorStore = async (req: Request, res: Response, next: NextFunc
         }
         const subscriptionId = req.user?.activeOrganizationSubscriptionId || ''
         const body = req.body
+        const isStrictSave = body.isStrictSave ?? false
         const apiResponse = await documentStoreService.insertIntoVectorStoreMiddleware(
             body,
-            false,
+            isStrictSave,
             orgId,
             workspaceId,
             subscriptionId,
@@ -513,7 +514,11 @@ const deleteVectorStoreFromStore = async (req: Request, res: Response, next: Nex
                 `Error: documentStoreController.deleteVectorStoreFromStore - workspaceId not provided!`
             )
         }
-        const apiResponse = await documentStoreService.deleteVectorStoreFromStore(req.params.storeId, workspaceId)
+        const apiResponse = await documentStoreService.deleteVectorStoreFromStore(
+            req.params.storeId,
+            workspaceId,
+            (req.query.docId as string) || undefined
+        )
         return res.json(apiResponse)
     } catch (error) {
         next(error)

packages/server/src/database/migrations/mariadb/1765000000000-FixDocumentStoreFileChunkLongText.ts

@@ -0,0 +1,14 @@
+import { MigrationInterface, QueryRunner } from 'typeorm'
+
+export class FixDocumentStoreFileChunkLongText1765000000000 implements MigrationInterface {
+    public async up(queryRunner: QueryRunner): Promise<void> {
+        await queryRunner.query(`ALTER TABLE \`document_store_file_chunk\` MODIFY \`pageContent\` LONGTEXT NOT NULL;`)
+        await queryRunner.query(`ALTER TABLE \`document_store_file_chunk\` MODIFY \`metadata\` LONGTEXT NULL;`)
+    }
+
+    public async down(queryRunner: QueryRunner): Promise<void> {
+        // WARNING: Reverting to TEXT may cause data loss if content exceeds the 64KB limit.
+        await queryRunner.query(`ALTER TABLE \`document_store_file_chunk\` MODIFY \`pageContent\` TEXT NOT NULL;`)
+        await queryRunner.query(`ALTER TABLE \`document_store_file_chunk\` MODIFY \`metadata\` TEXT NULL;`)
+    }
+}

packages/server/src/database/migrations/mariadb/index.ts

@@ -40,6 +40,7 @@ import { AddTextToSpeechToChatFlow1754986457485 } from './1754986457485-AddTextT
 import { ModifyChatflowType1755066758601 } from './1755066758601-ModifyChatflowType'
 import { AddTextToSpeechToChatFlow1759419231100 } from './1759419231100-AddTextToSpeechToChatFlow'
 import { AddChatFlowNameIndex1759424809984 } from './1759424809984-AddChatFlowNameIndex'
+import { FixDocumentStoreFileChunkLongText1765000000000 } from './1765000000000-FixDocumentStoreFileChunkLongText'
 
 import { AddAuthTables1720230151482 } from '../../../enterprise/database/migrations/mariadb/1720230151482-AddAuthTables'
 import { AddWorkspace1725437498242 } from '../../../enterprise/database/migrations/mariadb/1725437498242-AddWorkspace'
@@ -106,5 +107,6 @@ export const mariadbMigrations = [
     AddTextToSpeechToChatFlow1754986457485,
     ModifyChatflowType1755066758601,
     AddTextToSpeechToChatFlow1759419231100,
-    AddChatFlowNameIndex1759424809984
+    AddChatFlowNameIndex1759424809984,
+    FixDocumentStoreFileChunkLongText1765000000000
 ]

packages/server/src/database/migrations/mysql/1765000000000-FixDocumentStoreFileChunkLongText.ts

@@ -0,0 +1,14 @@
+import { MigrationInterface, QueryRunner } from 'typeorm'
+
+export class FixDocumentStoreFileChunkLongText1765000000000 implements MigrationInterface {
+    public async up(queryRunner: QueryRunner): Promise<void> {
+        await queryRunner.query(`ALTER TABLE \`document_store_file_chunk\` MODIFY \`pageContent\` LONGTEXT NOT NULL;`)
+        await queryRunner.query(`ALTER TABLE \`document_store_file_chunk\` MODIFY \`metadata\` LONGTEXT NULL;`)
+    }
+
+    public async down(queryRunner: QueryRunner): Promise<void> {
+        // WARNING: Reverting to TEXT may cause data loss if content exceeds the 64KB limit.
+        await queryRunner.query(`ALTER TABLE \`document_store_file_chunk\` MODIFY \`pageContent\` TEXT NOT NULL;`)
+        await queryRunner.query(`ALTER TABLE \`document_store_file_chunk\` MODIFY \`metadata\` TEXT NULL;`)
+    }
+}

packages/server/src/database/migrations/mysql/index.ts

@@ -41,6 +41,7 @@ import { AddTextToSpeechToChatFlow1754986468397 } from './1754986468397-AddTextT
 import { ModifyChatflowType1755066758601 } from './1755066758601-ModifyChatflowType'
 import { AddTextToSpeechToChatFlow1759419216034 } from './1759419216034-AddTextToSpeechToChatFlow'
 import { AddChatFlowNameIndex1759424828558 } from './1759424828558-AddChatFlowNameIndex'
+import { FixDocumentStoreFileChunkLongText1765000000000 } from './1765000000000-FixDocumentStoreFileChunkLongText'
 
 import { AddAuthTables1720230151482 } from '../../../enterprise/database/migrations/mysql/1720230151482-AddAuthTables'
 import { AddWorkspace1720230151484 } from '../../../enterprise/database/migrations/mysql/1720230151484-AddWorkspace'
@@ -108,5 +109,6 @@ export const mysqlMigrations = [
     AddTextToSpeechToChatFlow1754986468397,
     ModifyChatflowType1755066758601,
     AddTextToSpeechToChatFlow1759419216034,
-    AddChatFlowNameIndex1759424828558
+    AddChatFlowNameIndex1759424828558,
+    FixDocumentStoreFileChunkLongText1765000000000
 ]

packages/server/src/services/documentstore/index.ts

@@ -391,7 +391,7 @@ const deleteDocumentStoreFileChunk = async (storeId: string, docId: string, chun
     }
 }
 
-const deleteVectorStoreFromStore = async (storeId: string, workspaceId: string) => {
+const deleteVectorStoreFromStore = async (storeId: string, workspaceId: string, docId?: string) => {
     try {
         const appServer = getRunningExpressApp()
         const componentNodes = appServer.nodesPool.componentNodes
@@ -461,7 +461,7 @@ const deleteVectorStoreFromStore = async (storeId: string, workspaceId: string)
 
         // Call the delete method of the vector store
         if (vectorStoreObj.vectorStoreMethods.delete) {
-            await vectorStoreObj.vectorStoreMethods.delete(vStoreNodeData, idsToDelete, options)
+            await vectorStoreObj.vectorStoreMethods.delete(vStoreNodeData, idsToDelete, { ...options, docId })
         }
     } catch (error) {
         throw new InternalFlowiseError(
@@ -1157,6 +1157,18 @@ const updateVectorStoreConfigOnly = async (data: ICommonObject, workspaceId: str
         )
     }
 }
+/**
+ * Saves vector store configuration to the document store entity.
+ * Handles embedding, vector store, and record manager configurations.
+ *
+ * @example
+ * // Strict mode: Only save what's provided, clear the rest
+ * await saveVectorStoreConfig(ds, { storeId, embeddingName, embeddingConfig }, true, wsId)
+ *
+ * @example
+ * // Lenient mode: Reuse existing configs if not provided
+ * await saveVectorStoreConfig(ds, { storeId, vectorStoreName, vectorStoreConfig }, false, wsId)
+ */
 const saveVectorStoreConfig = async (appDataSource: DataSource, data: ICommonObject, isStrictSave = true, workspaceId: string) => {
     try {
         const entity = await appDataSource.getRepository(DocumentStore).findOneBy({
@@ -1221,6 +1233,15 @@ const saveVectorStoreConfig = async (appDataSource: DataSource, data: ICommonObj
     }
 }
 
+/**
+ * Inserts documents from document store into the configured vector store.
+ *
+ * Process:
+ * 1. Saves vector store configuration (embedding, vector store, record manager)
+ * 2. Sets document store status to UPSERTING
+ * 3. Performs the actual vector store upsert operation
+ * 4. Updates status to UPSERTED upon completion
+ */
 export const insertIntoVectorStore = async ({
     appDataSource,
     componentNodes,
@@ -1231,19 +1252,16 @@ export const insertIntoVectorStore = async ({
     workspaceId
 }: IExecuteVectorStoreInsert) => {
     try {
+        // Step 1: Save configuration based on isStrictSave mode
         const entity = await saveVectorStoreConfig(appDataSource, data, isStrictSave, workspaceId)
+
+        // Step 2: Mark as UPSERTING before starting the operation
         entity.status = DocumentStoreStatus.UPSERTING
         await appDataSource.getRepository(DocumentStore).save(entity)
 
-        const indexResult = await _insertIntoVectorStoreWorkerThread(
-            appDataSource,
-            componentNodes,
-            telemetry,
-            data,
-            isStrictSave,
-            orgId,
-            workspaceId
-        )
+        // Step 3: Perform the actual vector store upsert
+        // Note: Configuration already saved above, worker thread just retrieves and uses it
+        const indexResult = await _insertIntoVectorStoreWorkerThread(appDataSource, componentNodes, telemetry, data, orgId, workspaceId)
         return indexResult
     } catch (error) {
         throw new InternalFlowiseError(
@@ -1308,12 +1326,18 @@ const _insertIntoVectorStoreWorkerThread = async (
     componentNodes: IComponentNodes,
     telemetry: Telemetry,
     data: ICommonObject,
-    isStrictSave = true,
     orgId: string,
     workspaceId: string
 ) => {
     try {
-        const entity = await saveVectorStoreConfig(appDataSource, data, isStrictSave, workspaceId)
+        // Configuration already saved by insertIntoVectorStore, just retrieve the entity
+        const entity = await appDataSource.getRepository(DocumentStore).findOneBy({
+            id: data.storeId,
+            workspaceId: workspaceId
+        })
+        if (!entity) {
+            throw new InternalFlowiseError(StatusCodes.NOT_FOUND, `Document store ${data.storeId} not found`)
+        }
         let upsertHistory: Record<string, any> = {}
         const chatflowid = data.storeId // fake chatflowid because this is not tied to any chatflow
 
@@ -1350,7 +1374,10 @@ const _insertIntoVectorStoreWorkerThread = async (
         const docs: Document[] = chunks.map((chunk: DocumentStoreFileChunk) => {
             return new Document({
                 pageContent: chunk.pageContent,
-                metadata: JSON.parse(chunk.metadata)
+                metadata: {
+                    ...JSON.parse(chunk.metadata),
+                    docId: chunk.docId
+                }
             })
         })
         vStoreNodeData.inputs.document = docs
@@ -1911,6 +1938,8 @@ const upsertDocStore = async (
             recordManagerConfig
         }
 
+        // Use isStrictSave: false to preserve existing configurations during upsert
+        // This allows the operation to reuse existing embedding/vector store/record manager configs
         const res = await insertIntoVectorStore({
             appDataSource,
             componentNodes,

packages/server/src/utils/buildAgentflow.ts

@@ -2122,7 +2122,62 @@ export const executeAgentFlow = async ({
 
     // check if last agentFlowExecutedData.data.output contains the key "content"
     const lastNodeOutput = agentFlowExecutedData[agentFlowExecutedData.length - 1].data?.output as ICommonObject | undefined
-    const content = (lastNodeOutput?.content as string) ?? ' '
+    let content = (lastNodeOutput?.content as string) ?? ' '
+
+    /* Check for post-processing settings */
+    let chatflowConfig: ICommonObject = {}
+    try {
+        if (chatflow.chatbotConfig) {
+            chatflowConfig = typeof chatflow.chatbotConfig === 'string' ? JSON.parse(chatflow.chatbotConfig) : chatflow.chatbotConfig
+        }
+    } catch (e) {
+        logger.error('[server]: Error parsing chatflow config:', e)
+    }
+
+    if (chatflowConfig?.postProcessing?.enabled === true && content) {
+        try {
+            const postProcessingFunction = JSON.parse(chatflowConfig?.postProcessing?.customFunction)
+            const nodeInstanceFilePath = componentNodes['customFunctionAgentflow'].filePath as string
+            const nodeModule = await import(nodeInstanceFilePath)
+            //set the outputs.output to EndingNode to prevent json escaping of content...
+            const nodeData = {
+                inputs: { customFunctionJavascriptFunction: postProcessingFunction }
+            }
+            const runtimeChatHistory = agentflowRuntime.chatHistory || []
+            const chatHistory = [...pastChatHistory, ...runtimeChatHistory]
+            const options: ICommonObject = {
+                chatflowid: chatflow.id,
+                sessionId,
+                chatId,
+                input: question || form,
+                postProcessing: {
+                    rawOutput: content,
+                    chatHistory: cloneDeep(chatHistory),
+                    sourceDocuments: lastNodeOutput?.sourceDocuments ? cloneDeep(lastNodeOutput.sourceDocuments) : undefined,
+                    usedTools: lastNodeOutput?.usedTools ? cloneDeep(lastNodeOutput.usedTools) : undefined,
+                    artifacts: lastNodeOutput?.artifacts ? cloneDeep(lastNodeOutput.artifacts) : undefined,
+                    fileAnnotations: lastNodeOutput?.fileAnnotations ? cloneDeep(lastNodeOutput.fileAnnotations) : undefined
+                },
+                appDataSource,
+                databaseEntities,
+                workspaceId,
+                orgId,
+                logger
+            }
+            const customFuncNodeInstance = new nodeModule.nodeClass()
+            const customFunctionResponse = await customFuncNodeInstance.run(nodeData, question || form, options)
+            const moderatedResponse = customFunctionResponse.output.content
+            if (typeof moderatedResponse === 'string') {
+                content = moderatedResponse
+            } else if (typeof moderatedResponse === 'object') {
+                content = '```json\n' + JSON.stringify(moderatedResponse, null, 2) + '\n```'
+            } else {
+                content = moderatedResponse
+            }
+        } catch (e) {
+            logger.error('[server]: Post Processing Error:', e)
+        }
+    }
 
     // remove credentialId from agentFlowExecutedData
     agentFlowExecutedData = agentFlowExecutedData.map((data) => _removeCredentialId(data))

packages/server/src/utils/buildChatflow.ts

@@ -2,7 +2,7 @@ import { Request } from 'express'
 import * as path from 'path'
 import { DataSource } from 'typeorm'
 import { v4 as uuidv4 } from 'uuid'
-import { omit } from 'lodash'
+import { omit, cloneDeep } from 'lodash'
 import {
     IFileUpload,
     convertSpeechToText,
@@ -817,7 +817,14 @@ export const executeFlow = async ({
                         sessionId,
                         chatId,
                         input: question,
-                        rawOutput: resultText,
+                        postProcessing: {
+                            rawOutput: resultText,
+                            chatHistory: cloneDeep(chatHistory),
+                            sourceDocuments: result?.sourceDocuments ? cloneDeep(result.sourceDocuments) : undefined,
+                            usedTools: result?.usedTools ? cloneDeep(result.usedTools) : undefined,
+                            artifacts: result?.artifacts ? cloneDeep(result.artifacts) : undefined,
+                            fileAnnotations: result?.fileAnnotations ? cloneDeep(result.fileAnnotations) : undefined
+                        },
                         appDataSource,
                         databaseEntities,
                         workspaceId,

packages/server/src/utils/quotaUsage.ts

@@ -70,7 +70,7 @@ export const checkUsageLimit = async (
     if (limit === -1) return
 
     if (currentUsage > limit) {
-        throw new InternalFlowiseError(StatusCodes.TOO_MANY_REQUESTS, `Limit exceeded: ${type}`)
+        throw new InternalFlowiseError(StatusCodes.PAYMENT_REQUIRED, `Limit exceeded: ${type}`)
     }
 }
 
@@ -135,7 +135,7 @@ export const checkPredictions = async (orgId: string, subscriptionId: string, us
     if (predictionsLimit === -1) return
 
     if (currentPredictions >= predictionsLimit) {
-        throw new InternalFlowiseError(StatusCodes.TOO_MANY_REQUESTS, 'Predictions limit exceeded')
+        throw new InternalFlowiseError(StatusCodes.PAYMENT_REQUIRED, 'Predictions limit exceeded')
     }
 
     return {
@@ -161,7 +161,7 @@ export const checkStorage = async (orgId: string, subscriptionId: string, usageC
     if (storageLimit === -1) return
 
     if (currentStorageUsage >= storageLimit) {
-        throw new InternalFlowiseError(StatusCodes.TOO_MANY_REQUESTS, 'Storage limit exceeded')
+        throw new InternalFlowiseError(StatusCodes.PAYMENT_REQUIRED, 'Storage limit exceeded')
     }
 
     return {

packages/ui/package.json

@@ -1,6 +1,6 @@
 {
     "name": "flowise-ui",
-    "version": "3.0.10",
+    "version": "3.0.11",
     "license": "SEE LICENSE IN LICENSE.md",
     "homepage": "https://flowiseai.com",
     "author": {

packages/ui/src/api/documentstore.js

@@ -22,7 +22,10 @@ const refreshLoader = (storeId) => client.post(`/document-store/refresh/${storeI
 const insertIntoVectorStore = (body) => client.post(`/document-store/vectorstore/insert`, body)
 const saveVectorStoreConfig = (body) => client.post(`/document-store/vectorstore/save`, body)
 const updateVectorStoreConfig = (body) => client.post(`/document-store/vectorstore/update`, body)
-const deleteVectorStoreDataFromStore = (storeId) => client.delete(`/document-store/vectorstore/${storeId}`)
+const deleteVectorStoreDataFromStore = (storeId, docId) => {
+    const url = docId ? `/document-store/vectorstore/${storeId}?docId=${docId}` : `/document-store/vectorstore/${storeId}`
+    return client.delete(url)
+}
 const queryVectorStore = (body) => client.post(`/document-store/vectorstore/query`, body)
 const getVectorStoreProviders = () => client.get('/document-store/components/vectorstore')
 const getEmbeddingProviders = () => client.get('/document-store/components/embeddings')

packages/ui/src/layout/MainLayout/Sidebar/MenuList/NavGroup/index.jsx

@@ -58,7 +58,7 @@ const NavGroup = ({ item }) => {
 
     const renderNonPrimaryGroups = () => {
         let nonprimaryGroups = item.children.filter((child) => child.id !== 'primary')
-        // Display chilren based on permission and display
+        // Display children based on permission and display
         nonprimaryGroups = nonprimaryGroups.map((group) => {
             const children = group.children.filter((menu) => shouldDisplayMenu(menu))
             return { ...group, children }

packages/ui/src/routes/AuthRoutes.jsx

@@ -10,6 +10,7 @@ const VerifyEmailPage = Loadable(lazy(() => import('@/views/auth/verify-email'))
 const ForgotPasswordPage = Loadable(lazy(() => import('@/views/auth/forgotPassword')))
 const ResetPasswordPage = Loadable(lazy(() => import('@/views/auth/resetPassword')))
 const UnauthorizedPage = Loadable(lazy(() => import('@/views/auth/unauthorized')))
+const RateLimitedPage = Loadable(lazy(() => import('@/views/auth/rateLimited')))
 const OrganizationSetupPage = Loadable(lazy(() => import('@/views/organization/index')))
 const LicenseExpiredPage = Loadable(lazy(() => import('@/views/auth/expired')))
 
@@ -45,6 +46,10 @@ const AuthRoutes = {
             path: '/unauthorized',
             element: <UnauthorizedPage />
         },
+        {
+            path: '/rate-limited',
+            element: <RateLimitedPage />
+        },
         {
             path: '/organization-setup',
             element: <OrganizationSetupPage />

packages/ui/src/store/context/ErrorContext.jsx

@@ -10,11 +10,29 @@ const ErrorContext = createContext()
 
 export const ErrorProvider = ({ children }) => {
     const [error, setError] = useState(null)
+    const [authRateLimitError, setAuthRateLimitError] = useState(null)
     const navigate = useNavigate()
 
     const handleError = async (err) => {
         console.error(err)
-        if (err?.response?.status === 403) {
+        if (err?.response?.status === 429 && err?.response?.data?.type === 'authentication_rate_limit') {
+            setAuthRateLimitError("You're making a lot of requests. Please wait and try again later.")
+        } else if (err?.response?.status === 429 && err?.response?.data?.type !== 'authentication_rate_limit') {
+            const retryAfterHeader = err?.response?.headers?.['retry-after']
+            let retryAfter = 60 // Default in seconds
+            if (retryAfterHeader) {
+                const parsedSeconds = parseInt(retryAfterHeader, 10)
+                if (Number.isNaN(parsedSeconds)) {
+                    const retryDate = new Date(retryAfterHeader)
+                    if (!Number.isNaN(retryDate.getTime())) {
+                        retryAfter = Math.max(0, Math.ceil((retryDate.getTime() - Date.now()) / 1000))
+                    }
+                } else {
+                    retryAfter = parsedSeconds
+                }
+            }
+            navigate('/rate-limited', { state: { retryAfter } })
+        } else if (err?.response?.status === 403) {
             navigate('/unauthorized')
         } else if (err?.response?.status === 401) {
             if (ErrorMessage.INVALID_MISSING_TOKEN === err?.response?.data?.message) {
@@ -44,7 +62,9 @@ export const ErrorProvider = ({ children }) => {
             value={{
                 error,
                 setError,
-                handleError
+                handleError,
+                authRateLimitError,
+                setAuthRateLimitError
             }}
         >
             {children}

packages/ui/src/ui-component/button/FlowListMenu.jsx

@@ -74,7 +74,7 @@ const StyledMenu = styled((props) => (
     }
 }))
 
-export default function FlowListMenu({ chatflow, isAgentCanvas, isAgentflowV2, setError, updateFlowsApi }) {
+export default function FlowListMenu({ chatflow, isAgentCanvas, isAgentflowV2, setError, updateFlowsApi, currentPage, pageLimit }) {
     const { confirm } = useConfirm()
     const dispatch = useDispatch()
     const updateChatflowApi = useApi(chatflowsApi.updateChatflow)
@@ -166,10 +166,16 @@ export default function FlowListMenu({ chatflow, isAgentCanvas, isAgentflowV2, s
         }
         try {
             await updateChatflowApi.request(chatflow.id, updateBody)
+            const params = {
+                page: currentPage,
+                limit: pageLimit
+            }
             if (isAgentCanvas && isAgentflowV2) {
-                await updateFlowsApi.request('AGENTFLOW')
+                await updateFlowsApi.request('AGENTFLOW', params)
+            } else if (isAgentCanvas) {
+                await updateFlowsApi.request('MULTIAGENT', params)
             } else {
-                await updateFlowsApi.request(isAgentCanvas ? 'MULTIAGENT' : undefined)
+                await updateFlowsApi.request(params)
             }
         } catch (error) {
             if (setError) setError(error)
@@ -209,7 +215,15 @@ export default function FlowListMenu({ chatflow, isAgentCanvas, isAgentflowV2, s
         }
         try {
             await updateChatflowApi.request(chatflow.id, updateBody)
-            await updateFlowsApi.request(isAgentCanvas ? 'AGENTFLOW' : undefined)
+            const params = {
+                page: currentPage,
+                limit: pageLimit
+            }
+            if (isAgentCanvas) {
+                await updateFlowsApi.request('AGENTFLOW', params)
+            } else {
+                await updateFlowsApi.request(params)
+            }
         } catch (error) {
             if (setError) setError(error)
             enqueueSnackbar({
@@ -241,10 +255,16 @@ export default function FlowListMenu({ chatflow, isAgentCanvas, isAgentflowV2, s
         if (isConfirmed) {
             try {
                 await chatflowsApi.deleteChatflow(chatflow.id)
+                const params = {
+                    page: currentPage,
+                    limit: pageLimit
+                }
                 if (isAgentCanvas && isAgentflowV2) {
-                    await updateFlowsApi.request('AGENTFLOW')
+                    await updateFlowsApi.request('AGENTFLOW', params)
+                } else if (isAgentCanvas) {
+                    await updateFlowsApi.request('MULTIAGENT', params)
                 } else {
-                    await updateFlowsApi.request(isAgentCanvas ? 'MULTIAGENT' : undefined)
+                    await updateFlowsApi.request(params)
                 }
             } catch (error) {
                 if (setError) setError(error)
@@ -454,5 +474,7 @@ FlowListMenu.propTypes = {
     isAgentCanvas: PropTypes.bool,
     isAgentflowV2: PropTypes.bool,
     setError: PropTypes.func,
-    updateFlowsApi: PropTypes.object
+    updateFlowsApi: PropTypes.object,
+    currentPage: PropTypes.number,
+    pageLimit: PropTypes.number
 }

packages/ui/src/ui-component/dialog/ChatflowConfigurationDialog.jsx

@@ -53,8 +53,7 @@ const CHATFLOW_CONFIGURATION_TABS = [
     },
     {
         label: 'Post Processing',
-        id: 'postProcessing',
-        hideInAgentFlow: true
+        id: 'postProcessing'
     }
 ]
 

packages/ui/src/ui-component/dialog/ExpandRichInputDialog.jsx

@@ -16,11 +16,11 @@ import { useEditor, EditorContent } from '@tiptap/react'
 import Placeholder from '@tiptap/extension-placeholder'
 import { mergeAttributes } from '@tiptap/core'
 import StarterKit from '@tiptap/starter-kit'
-import Mention from '@tiptap/extension-mention'
 import CodeBlockLowlight from '@tiptap/extension-code-block-lowlight'
 import { common, createLowlight } from 'lowlight'
 import { suggestionOptions } from '@/ui-component/input/suggestionOption'
 import { getAvailableNodesForVariable } from '@/utils/genericHelper'
+import { CustomMention } from '@/utils/customMention'
 
 const lowlight = createLowlight(common)
 
@@ -78,7 +78,7 @@ const extensions = (availableNodesForVariable, availableState, acceptNodeOutputA
     StarterKit.configure({
         codeBlock: false
     }),
-    Mention.configure({
+    CustomMention.configure({
         HTMLAttributes: {
             class: 'variable'
         },

packages/ui/src/ui-component/extended/PostProcessing.jsx

@@ -4,8 +4,25 @@ import PropTypes from 'prop-types'
 import { useSelector } from 'react-redux'
 
 // material-ui
-import { IconButton, Button, Box, Typography } from '@mui/material'
-import { IconArrowsMaximize, IconBulb, IconX } from '@tabler/icons-react'
+import {
+    IconButton,
+    Button,
+    Box,
+    Typography,
+    TableContainer,
+    Table,
+    TableHead,
+    TableBody,
+    TableRow,
+    TableCell,
+    Paper,
+    Accordion,
+    AccordionSummary,
+    AccordionDetails,
+    Card
+} from '@mui/material'
+import { IconArrowsMaximize, IconX } from '@tabler/icons-react'
+import ExpandMoreIcon from '@mui/icons-material/ExpandMore'
 import { useTheme } from '@mui/material/styles'
 
 // Project import
@@ -21,7 +38,11 @@ import useNotifier from '@/utils/useNotifier'
 // API
 import chatflowsApi from '@/api/chatflows'
 
-const sampleFunction = `return $flow.rawOutput + " This is a post processed response!";`
+const sampleFunction = `// Access chat history as a string
+const chatHistory = JSON.stringify($flow.chatHistory, null, 2); 
+
+// Return a modified response
+return $flow.rawOutput + " This is a post processed response!";`
 
 const PostProcessing = ({ dialogProps }) => {
     const dispatch = useDispatch()
@@ -175,31 +196,105 @@ const PostProcessing = ({ dialogProps }) => {
                     />
                 </div>
             </Box>
-            <div
-                style={{
-                    display: 'flex',
-                    flexDirection: 'column',
-                    borderRadius: 10,
-                    background: '#d8f3dc',
-                    padding: 10,
-                    marginTop: 10
-                }}
-            >
-                <div
-                    style={{
-                        display: 'flex',
-                        flexDirection: 'row',
-                        alignItems: 'center',
-                        paddingTop: 10
+            <Card sx={{ borderColor: theme.palette.primary[200] + 75, mt: 2, mb: 2 }} variant='outlined'>
+                <Accordion
+                    disableGutters
+                    sx={{
+                        '&:before': {
+                            display: 'none'
+                        }
                     }}
                 >
-                    <IconBulb size={30} color='#2d6a4f' />
-                    <span style={{ color: '#2d6a4f', marginLeft: 10, fontWeight: 500 }}>
-                        The following variables are available to use in the custom function:{' '}
-                        <pre>$flow.rawOutput, $flow.input, $flow.chatflowId, $flow.sessionId, $flow.chatId</pre>
-                    </span>
-                </div>
-            </div>
+                    <AccordionSummary expandIcon={<ExpandMoreIcon />}>
+                        <Typography>Available Variables</Typography>
+                    </AccordionSummary>
+                    <AccordionDetails sx={{ p: 0 }}>
+                        <TableContainer component={Paper}>
+                            <Table aria-label='available variables table'>
+                                <TableHead>
+                                    <TableRow>
+                                        <TableCell sx={{ width: '30%' }}>Variable</TableCell>
+                                        <TableCell sx={{ width: '15%' }}>Type</TableCell>
+                                        <TableCell sx={{ width: '55%' }}>Description</TableCell>
+                                    </TableRow>
+                                </TableHead>
+                                <TableBody>
+                                    <TableRow>
+                                        <TableCell>
+                                            <code>$flow.rawOutput</code>
+                                        </TableCell>
+                                        <TableCell>string</TableCell>
+                                        <TableCell>The raw output response from the flow</TableCell>
+                                    </TableRow>
+                                    <TableRow>
+                                        <TableCell>
+                                            <code>$flow.input</code>
+                                        </TableCell>
+                                        <TableCell>string</TableCell>
+                                        <TableCell>The user input message</TableCell>
+                                    </TableRow>
+                                    <TableRow>
+                                        <TableCell>
+                                            <code>$flow.chatHistory</code>
+                                        </TableCell>
+                                        <TableCell>array</TableCell>
+                                        <TableCell>Array of previous messages in the conversation</TableCell>
+                                    </TableRow>
+                                    <TableRow>
+                                        <TableCell>
+                                            <code>$flow.chatflowId</code>
+                                        </TableCell>
+                                        <TableCell>string</TableCell>
+                                        <TableCell>Unique identifier for the chatflow</TableCell>
+                                    </TableRow>
+                                    <TableRow>
+                                        <TableCell>
+                                            <code>$flow.sessionId</code>
+                                        </TableCell>
+                                        <TableCell>string</TableCell>
+                                        <TableCell>Current session identifier</TableCell>
+                                    </TableRow>
+                                    <TableRow>
+                                        <TableCell>
+                                            <code>$flow.chatId</code>
+                                        </TableCell>
+                                        <TableCell>string</TableCell>
+                                        <TableCell>Current chat identifier</TableCell>
+                                    </TableRow>
+                                    <TableRow>
+                                        <TableCell>
+                                            <code>$flow.sourceDocuments</code>
+                                        </TableCell>
+                                        <TableCell>array</TableCell>
+                                        <TableCell>Source documents used in retrieval (if applicable)</TableCell>
+                                    </TableRow>
+                                    <TableRow>
+                                        <TableCell>
+                                            <code>$flow.usedTools</code>
+                                        </TableCell>
+                                        <TableCell>array</TableCell>
+                                        <TableCell>List of tools used during execution</TableCell>
+                                    </TableRow>
+                                    <TableRow>
+                                        <TableCell>
+                                            <code>$flow.artifacts</code>
+                                        </TableCell>
+                                        <TableCell>array</TableCell>
+                                        <TableCell>List of artifacts generated during execution</TableCell>
+                                    </TableRow>
+                                    <TableRow>
+                                        <TableCell sx={{ borderBottom: 'none' }}>
+                                            <code>$flow.fileAnnotations</code>
+                                        </TableCell>
+                                        <TableCell sx={{ borderBottom: 'none' }}>array</TableCell>
+                                        <TableCell sx={{ borderBottom: 'none' }}>File annotations associated with the response</TableCell>
+                                    </TableRow>
+                                </TableBody>
+                            </Table>
+                        </TableContainer>
+                    </AccordionDetails>
+                </Accordion>
+            </Card>
             <StyledButton
                 style={{ marginBottom: 10, marginTop: 10 }}
                 variant='contained'

packages/ui/src/ui-component/input/RichInput.jsx

@@ -7,11 +7,11 @@ import { mergeAttributes } from '@tiptap/core'
 import StarterKit from '@tiptap/starter-kit'
 import { styled } from '@mui/material/styles'
 import { Box } from '@mui/material'
-import Mention from '@tiptap/extension-mention'
 import CodeBlockLowlight from '@tiptap/extension-code-block-lowlight'
 import { common, createLowlight } from 'lowlight'
 import { suggestionOptions } from './suggestionOption'
 import { getAvailableNodesForVariable } from '@/utils/genericHelper'
+import { CustomMention } from '@/utils/customMention'
 
 const lowlight = createLowlight(common)
 
@@ -20,7 +20,7 @@ const extensions = (availableNodesForVariable, availableState, acceptNodeOutputA
     StarterKit.configure({
         codeBlock: false
     }),
-    Mention.configure({
+    CustomMention.configure({
         HTMLAttributes: {
             class: 'variable'
         },

packages/ui/src/ui-component/input/suggestionOption.js

@@ -112,7 +112,7 @@ export const suggestionOptions = (
                 category: 'Node Outputs'
             })
 
-            const structuredOutputs = nodeData?.inputs?.llmStructuredOutput ?? []
+            const structuredOutputs = nodeData?.inputs?.llmStructuredOutput ?? nodeData?.inputs?.agentStructuredOutput ?? []
             if (structuredOutputs && structuredOutputs.length > 0) {
                 structuredOutputs.forEach((item) => {
                     defaultItems.unshift({

packages/ui/src/ui-component/table/FlowListTable.jsx

@@ -59,7 +59,9 @@ export const FlowListTable = ({
     updateFlowsApi,
     setError,
     isAgentCanvas,
-    isAgentflowV2
+    isAgentflowV2,
+    currentPage,
+    pageLimit
 }) => {
     const { hasPermission } = useAuth()
     const isActionsAvailable = isAgentCanvas
@@ -331,6 +333,8 @@ export const FlowListTable = ({
                                                         chatflow={row}
                                                         setError={setError}
                                                         updateFlowsApi={updateFlowsApi}
+                                                        currentPage={currentPage}
+                                                        pageLimit={pageLimit}
                                                     />
                                                 </Stack>
                                             </StyledTableCell>
@@ -355,5 +359,7 @@ FlowListTable.propTypes = {
     updateFlowsApi: PropTypes.object,
     setError: PropTypes.func,
     isAgentCanvas: PropTypes.bool,
-    isAgentflowV2: PropTypes.bool
+    isAgentflowV2: PropTypes.bool,
+    currentPage: PropTypes.number,
+    pageLimit: PropTypes.number
 }

packages/ui/src/utils/customMention.js

@@ -0,0 +1,26 @@
+import Mention from '@tiptap/extension-mention'
+import { PasteRule } from '@tiptap/core'
+
+export const CustomMention = Mention.extend({
+    renderText({ node }) {
+        return `{{${node.attrs.label ?? node.attrs.id}}}`
+    },
+    addPasteRules() {
+        return [
+            new PasteRule({
+                find: /\{\{([^{}]+)\}\}/g,
+                handler: ({ match, chain, range }) => {
+                    const label = match[1].trim()
+                    if (label) {
+                        chain()
+                            .deleteRange(range)
+                            .insertContentAt(range.from, {
+                                type: this.name,
+                                attrs: { id: label, label: label }
+                            })
+                    }
+                }
+            })
+        ]
+    }
+})

packages/ui/src/views/agentflows/index.jsx

@@ -325,6 +325,8 @@ const Agentflows = () => {
                                     filterFunction={filterFlows}
                                     updateFlowsApi={getAllAgentflows}
                                     setError={setError}
+                                    currentPage={currentPage}
+                                    pageLimit={pageLimit}
                                 />
                             )}
                             {/* Pagination and Page Size Controls */}

packages/ui/src/views/agentflowsv2/AgentFlowNode.jsx

@@ -150,6 +150,8 @@ const AgentFlowNode = ({ data }) => {
                 return <IconWorldWww size={14} color={'white'} />
             case 'googleSearch':
                 return <IconBrandGoogle size={14} color={'white'} />
+            case 'codeExecution':
+                return <IconCode size={14} color={'white'} />
             default:
                 return null
         }

packages/ui/src/views/auth/forgotPassword.jsx

@@ -16,6 +16,7 @@ import accountApi from '@/api/account.api'
 // Hooks
 import useApi from '@/hooks/useApi'
 import { useConfig } from '@/store/context/ConfigContext'
+import { useError } from '@/store/context/ErrorContext'
 
 // utils
 import useNotifier from '@/utils/useNotifier'
@@ -41,10 +42,13 @@ const ForgotPasswordPage = () => {
     const [isLoading, setLoading] = useState(false)
     const [responseMsg, setResponseMsg] = useState(undefined)
 
+    const { authRateLimitError, setAuthRateLimitError } = useError()
+
     const forgotPasswordApi = useApi(accountApi.forgotPassword)
 
     const sendResetRequest = async (event) => {
         event.preventDefault()
+        setAuthRateLimitError(null)
         const body = {
             user: {
                 email: usernameVal
@@ -54,6 +58,11 @@ const ForgotPasswordPage = () => {
         await forgotPasswordApi.request(body)
     }
 
+    useEffect(() => {
+        setAuthRateLimitError(null)
+        // eslint-disable-next-line react-hooks/exhaustive-deps
+    }, [setAuthRateLimitError])
+
     useEffect(() => {
         if (forgotPasswordApi.error) {
             const errMessage =
@@ -89,6 +98,11 @@ const ForgotPasswordPage = () => {
                             {responseMsg.msg}
                         </Alert>
                     )}
+                    {authRateLimitError && (
+                        <Alert icon={<IconExclamationCircle />} variant='filled' severity='error'>
+                            {authRateLimitError}
+                        </Alert>
+                    )}
                     {responseMsg && responseMsg?.type !== 'error' && (
                         <Alert icon={<IconCircleCheck />} variant='filled' severity='success'>
                             {responseMsg.msg}

packages/ui/src/views/auth/rateLimited.jsx

@@ -0,0 +1,51 @@
+import { Box, Button, Stack, Typography } from '@mui/material'
+import { Link, useLocation } from 'react-router-dom'
+import unauthorizedSVG from '@/assets/images/unauthorized.svg'
+import MainCard from '@/ui-component/cards/MainCard'
+
+// ==============================|| RateLimitedPage ||============================== //
+
+const RateLimitedPage = () => {
+    const location = useLocation()
+
+    const retryAfter = location.state?.retryAfter || 60
+
+    return (
+        <MainCard>
+            <Box
+                sx={{
+                    display: 'flex',
+                    justifyContent: 'center',
+                    alignItems: 'center',
+                    height: 'calc(100vh - 210px)'
+                }}
+            >
+                <Stack
+                    sx={{
+                        alignItems: 'center',
+                        justifyContent: 'center',
+                        maxWidth: '500px'
+                    }}
+                    flexDirection='column'
+                >
+                    <Box sx={{ p: 2, height: 'auto' }}>
+                        <img style={{ objectFit: 'cover', height: '20vh', width: 'auto' }} src={unauthorizedSVG} alt='rateLimitedSVG' />
+                    </Box>
+                    <Typography sx={{ mb: 2 }} variant='h4' component='div' fontWeight='bold'>
+                        429 Too Many Requests
+                    </Typography>
+                    <Typography variant='body1' component='div' sx={{ mb: 2, textAlign: 'center' }}>
+                        {`You have made too many requests in a short period of time. Please wait ${retryAfter}s before trying again.`}
+                    </Typography>
+                    <Link to='/'>
+                        <Button variant='contained' color='primary'>
+                            Back to Home
+                        </Button>
+                    </Link>
+                </Stack>
+            </Box>
+        </MainCard>
+    )
+}
+
+export default RateLimitedPage

packages/ui/src/views/auth/register.jsx

@@ -18,6 +18,7 @@ import ssoApi from '@/api/sso'
 // Hooks
 import useApi from '@/hooks/useApi'
 import { useConfig } from '@/store/context/ConfigContext'
+import { useError } from '@/store/context/ErrorContext'
 
 // utils
 import useNotifier from '@/utils/useNotifier'
@@ -111,7 +112,9 @@ const RegisterPage = () => {
 
     const [loading, setLoading] = useState(false)
     const [authError, setAuthError] = useState('')
-    const [successMsg, setSuccessMsg] = useState(undefined)
+    const [successMsg, setSuccessMsg] = useState('')
+
+    const { authRateLimitError, setAuthRateLimitError } = useError()
 
     const registerApi = useApi(accountApi.registerAccount)
     const ssoLoginApi = useApi(ssoApi.ssoLogin)
@@ -120,6 +123,7 @@ const RegisterPage = () => {
 
     const register = async (event) => {
         event.preventDefault()
+        setAuthRateLimitError(null)
         if (isEnterpriseLicensed) {
             const result = RegisterEnterpriseUserSchema.safeParse({
                 username,
@@ -192,6 +196,7 @@ const RegisterPage = () => {
     }, [registerApi.error])
 
     useEffect(() => {
+        setAuthRateLimitError(null)
         if (!isOpenSource) {
             getDefaultProvidersApi.request()
         }
@@ -274,6 +279,11 @@ const RegisterPage = () => {
                             )}
                         </Alert>
                     )}
+                    {authRateLimitError && (
+                        <Alert icon={<IconExclamationCircle />} variant='filled' severity='error'>
+                            {authRateLimitError}
+                        </Alert>
+                    )}
                     {successMsg && (
                         <Alert icon={<IconCircleCheck />} variant='filled' severity='success'>
                             {successMsg}

packages/ui/src/views/auth/resetPassword.jsx

@@ -1,4 +1,4 @@
-import { useState } from 'react'
+import { useEffect, useState } from 'react'
 import { useDispatch } from 'react-redux'
 import { Link, useNavigate, useSearchParams } from 'react-router-dom'
 
@@ -19,6 +19,9 @@ import accountApi from '@/api/account.api'
 import useNotifier from '@/utils/useNotifier'
 import { validatePassword } from '@/utils/validation'
 
+// Hooks
+import { useError } from '@/store/context/ErrorContext'
+
 // Icons
 import { IconExclamationCircle, IconX } from '@tabler/icons-react'
 
@@ -70,6 +73,8 @@ const ResetPasswordPage = () => {
     const [loading, setLoading] = useState(false)
     const [authErrors, setAuthErrors] = useState([])
 
+    const { authRateLimitError, setAuthRateLimitError } = useError()
+
     const goLogin = () => {
         navigate('/signin', { replace: true })
     }
@@ -78,6 +83,7 @@ const ResetPasswordPage = () => {
         event.preventDefault()
         const validationErrors = []
         setAuthErrors([])
+        setAuthRateLimitError(null)
         if (!tokenVal) {
             validationErrors.push('Token cannot be left blank!')
         }
@@ -142,6 +148,11 @@ const ResetPasswordPage = () => {
         }
     }
 
+    useEffect(() => {
+        setAuthRateLimitError(null)
+        // eslint-disable-next-line react-hooks/exhaustive-deps
+    }, [])
+
     return (
         <>
             <MainCard>
@@ -155,6 +166,11 @@ const ResetPasswordPage = () => {
                             </ul>
                         </Alert>
                     )}
+                    {authRateLimitError && (
+                        <Alert icon={<IconExclamationCircle />} variant='filled' severity='error'>
+                            {authRateLimitError}
+                        </Alert>
+                    )}
                     <Stack sx={{ gap: 1 }}>
                         <Typography variant='h1'>Reset Password</Typography>
                         <Typography variant='body2' sx={{ color: theme.palette.grey[600] }}>

packages/ui/src/views/auth/signIn.jsx

@@ -14,6 +14,7 @@ import { Input } from '@/ui-component/input/Input'
 // Hooks
 import useApi from '@/hooks/useApi'
 import { useConfig } from '@/store/context/ConfigContext'
+import { useError } from '@/store/context/ErrorContext'
 
 // API
 import authApi from '@/api/auth'
@@ -62,6 +63,8 @@ const SignInPage = () => {
     const [showResendButton, setShowResendButton] = useState(false)
     const [successMessage, setSuccessMessage] = useState('')
 
+    const { authRateLimitError, setAuthRateLimitError } = useError()
+
     const loginApi = useApi(authApi.login)
     const ssoLoginApi = useApi(ssoApi.ssoLogin)
     const getDefaultProvidersApi = useApi(loginMethodApi.getDefaultLoginMethods)
@@ -71,6 +74,7 @@ const SignInPage = () => {
 
     const doLogin = (event) => {
         event.preventDefault()
+        setAuthRateLimitError(null)
         setLoading(true)
         const body = {
             email: usernameVal,
@@ -92,11 +96,12 @@ const SignInPage = () => {
 
     useEffect(() => {
         store.dispatch(logoutSuccess())
+        setAuthRateLimitError(null)
         if (!isOpenSource) {
             getDefaultProvidersApi.request()
         }
         // eslint-disable-next-line react-hooks/exhaustive-deps
-    }, [])
+    }, [setAuthRateLimitError, isOpenSource])
 
     useEffect(() => {
         // Parse the "user" query parameter from the URL
@@ -179,6 +184,11 @@ const SignInPage = () => {
                             {successMessage}
                         </Alert>
                     )}
+                    {authRateLimitError && (
+                        <Alert icon={<IconExclamationCircle />} variant='filled' severity='error'>
+                            {authRateLimitError}
+                        </Alert>
+                    )}
                     {authError && (
                         <Alert icon={<IconExclamationCircle />} variant='filled' severity='error'>
                             {authError}

packages/ui/src/views/chatflows/index.jsx

@@ -208,6 +208,8 @@ const Chatflows = () => {
                                     filterFunction={filterFlows}
                                     updateFlowsApi={getAllChatflowsApi}
                                     setError={setError}
+                                    currentPage={currentPage}
+                                    pageLimit={pageLimit}
                                 />
                             )}
                             {/* Pagination and Page Size Controls */}

packages/ui/src/views/docstore/DeleteDocStoreDialog.jsx

@@ -18,11 +18,15 @@ import {
     TableContainer,
     TableRow,
     TableCell,
-    Checkbox,
-    FormControlLabel,
-    DialogActions
+    DialogActions,
+    Card,
+    Stack,
+    Link
 } from '@mui/material'
+import { useTheme } from '@mui/material/styles'
 import ExpandMoreIcon from '@mui/icons-material/ExpandMore'
+import SettingsIcon from '@mui/icons-material/Settings'
+import { IconAlertTriangle } from '@tabler/icons-react'
 import { TableViewOnly } from '@/ui-component/table/Table'
 import { v4 as uuidv4 } from 'uuid'
 
@@ -36,12 +40,13 @@ import { initNode } from '@/utils/genericHelper'
 
 const DeleteDocStoreDialog = ({ show, dialogProps, onCancel, onDelete }) => {
     const portalElement = document.getElementById('portal')
+    const theme = useTheme()
     const [nodeConfigExpanded, setNodeConfigExpanded] = useState({})
-    const [removeFromVS, setRemoveFromVS] = useState(false)
     const [vsFlowData, setVSFlowData] = useState([])
     const [rmFlowData, setRMFlowData] = useState([])
 
-    const getSpecificNodeApi = useApi(nodesApi.getSpecificNode)
+    const getVectorStoreNodeApi = useApi(nodesApi.getSpecificNode)
+    const getRecordManagerNodeApi = useApi(nodesApi.getSpecificNode)
 
     const handleAccordionChange = (nodeName) => (event, isExpanded) => {
         const accordianNodes = { ...nodeConfigExpanded }
@@ -52,42 +57,37 @@ const DeleteDocStoreDialog = ({ show, dialogProps, onCancel, onDelete }) => {
     useEffect(() => {
         if (dialogProps.recordManagerConfig) {
             const nodeName = dialogProps.recordManagerConfig.name
-            if (nodeName) getSpecificNodeApi.request(nodeName)
+            if (nodeName) getRecordManagerNodeApi.request(nodeName)
+        }
 
-            if (dialogProps.vectorStoreConfig) {
-                const nodeName = dialogProps.vectorStoreConfig.name
-                if (nodeName) getSpecificNodeApi.request(nodeName)
-            }
+        if (dialogProps.vectorStoreConfig) {
+            const nodeName = dialogProps.vectorStoreConfig.name
+            if (nodeName) getVectorStoreNodeApi.request(nodeName)
         }
 
         return () => {
             setNodeConfigExpanded({})
-            setRemoveFromVS(false)
             setVSFlowData([])
             setRMFlowData([])
         }
         // eslint-disable-next-line react-hooks/exhaustive-deps
     }, [dialogProps])
 
+    // Process Vector Store node data
     useEffect(() => {
-        if (getSpecificNodeApi.data) {
-            const nodeData = cloneDeep(initNode(getSpecificNodeApi.data, uuidv4()))
-
-            let config = 'vectorStoreConfig'
-            if (nodeData.category === 'Record Manager') config = 'recordManagerConfig'
+        if (getVectorStoreNodeApi.data && dialogProps.vectorStoreConfig) {
+            const nodeData = cloneDeep(initNode(getVectorStoreNodeApi.data, uuidv4()))
 
             const paramValues = []
 
-            for (const inputName in dialogProps[config].config) {
+            for (const inputName in dialogProps.vectorStoreConfig.config) {
                 const inputParam = nodeData.inputParams.find((inp) => inp.name === inputName)
 
                 if (!inputParam) continue
 
                 if (inputParam.type === 'credential') continue
 
-                let paramValue = {}
-
-                const inputValue = dialogProps[config].config[inputName]
+                const inputValue = dialogProps.vectorStoreConfig.config[inputName]
 
                 if (!inputValue) continue
 
@@ -95,40 +95,71 @@ const DeleteDocStoreDialog = ({ show, dialogProps, onCancel, onDelete }) => {
                     continue
                 }
 
-                paramValue = {
+                paramValues.push({
                     label: inputParam?.label,
                     name: inputParam?.name,
                     type: inputParam?.type,
                     value: inputValue
-                }
-                paramValues.push(paramValue)
+                })
             }
 
-            if (config === 'vectorStoreConfig') {
-                setVSFlowData([
-                    {
-                        label: nodeData.label,
-                        name: nodeData.name,
-                        category: nodeData.category,
-                        id: nodeData.id,
-                        paramValues
-                    }
-                ])
-            } else if (config === 'recordManagerConfig') {
-                setRMFlowData([
-                    {
-                        label: nodeData.label,
-                        name: nodeData.name,
-                        category: nodeData.category,
-                        id: nodeData.id,
-                        paramValues
-                    }
-                ])
-            }
+            setVSFlowData([
+                {
+                    label: nodeData.label,
+                    name: nodeData.name,
+                    category: nodeData.category,
+                    id: nodeData.id,
+                    paramValues
+                }
+            ])
         }
 
         // eslint-disable-next-line react-hooks/exhaustive-deps
-    }, [getSpecificNodeApi.data])
+    }, [getVectorStoreNodeApi.data])
+
+    // Process Record Manager node data
+    useEffect(() => {
+        if (getRecordManagerNodeApi.data && dialogProps.recordManagerConfig) {
+            const nodeData = cloneDeep(initNode(getRecordManagerNodeApi.data, uuidv4()))
+
+            const paramValues = []
+
+            for (const inputName in dialogProps.recordManagerConfig.config) {
+                const inputParam = nodeData.inputParams.find((inp) => inp.name === inputName)
+
+                if (!inputParam) continue
+
+                if (inputParam.type === 'credential') continue
+
+                const inputValue = dialogProps.recordManagerConfig.config[inputName]
+
+                if (!inputValue) continue
+
+                if (typeof inputValue === 'string' && inputValue.startsWith('{{') && inputValue.endsWith('}}')) {
+                    continue
+                }
+
+                paramValues.push({
+                    label: inputParam?.label,
+                    name: inputParam?.name,
+                    type: inputParam?.type,
+                    value: inputValue
+                })
+            }
+
+            setRMFlowData([
+                {
+                    label: nodeData.label,
+                    name: nodeData.name,
+                    category: nodeData.category,
+                    id: nodeData.id,
+                    paramValues
+                }
+            ])
+        }
+
+        // eslint-disable-next-line react-hooks/exhaustive-deps
+    }, [getRecordManagerNodeApi.data])
 
     const component = show ? (
         <Dialog
@@ -142,91 +173,130 @@ const DeleteDocStoreDialog = ({ show, dialogProps, onCancel, onDelete }) => {
             <DialogTitle sx={{ fontSize: '1rem', p: 3, pb: 0 }} id='alert-dialog-title'>
                 {dialogProps.title}
             </DialogTitle>
-            <DialogContent sx={{ display: 'flex', flexDirection: 'column', gap: 2, maxHeight: '75vh', position: 'relative', px: 3, pb: 3 }}>
+            <DialogContent
+                sx={{
+                    display: 'flex',
+                    flexDirection: 'column',
+                    gap: 2,
+                    maxHeight: '75vh',
+                    position: 'relative',
+                    px: 3,
+                    pb: 3,
+                    overflow: 'auto'
+                }}
+            >
                 <span style={{ marginTop: '20px' }}>{dialogProps.description}</span>
-                {dialogProps.type === 'STORE' && dialogProps.recordManagerConfig && (
-                    <FormControlLabel
-                        control={<Checkbox checked={removeFromVS} onChange={(event) => setRemoveFromVS(event.target.checked)} />}
-                        label='Remove data from vector store and record manager'
-                    />
+                {dialogProps.vectorStoreConfig && !dialogProps.recordManagerConfig && (
+                    <div
+                        style={{
+                            display: 'flex',
+                            flexDirection: 'row',
+                            alignItems: 'center',
+                            borderRadius: 10,
+                            background: 'rgb(254,252,191)',
+                            padding: 10
+                        }}
+                    >
+                        <IconAlertTriangle size={70} color='orange' />
+                        <span style={{ color: 'rgb(116,66,16)', marginLeft: 10 }}>
+                            <strong>Note:</strong> Without a Record Manager configured, only the document chunks will be removed from the
+                            document store. The actual vector embeddings in your vector store database will remain unchanged. To enable
+                            automatic cleanup of vector store data, please configure a Record Manager.{' '}
+                            <Link
+                                href='https://docs.flowiseai.com/integrations/langchain/record-managers'
+                                target='_blank'
+                                rel='noopener noreferrer'
+                                sx={{ fontWeight: 500, color: 'rgb(116,66,16)', textDecoration: 'underline' }}
+                            >
+                                Learn more
+                            </Link>
+                        </span>
+                    </div>
                 )}
-                {removeFromVS && (
-                    <div>
-                        <TableContainer component={Paper}>
-                            <Table sx={{ minWidth: 650 }} aria-label='simple table'>
-                                <TableBody>
-                                    <TableRow sx={{ '& td': { border: 0 } }}>
-                                        <TableCell sx={{ pb: 0, pt: 0 }} colSpan={6}>
-                                            <Box>
-                                                {([...vsFlowData, ...rmFlowData] || []).map((node, index) => {
-                                                    return (
-                                                        <Accordion
-                                                            expanded={nodeConfigExpanded[node.name] || true}
-                                                            onChange={handleAccordionChange(node.name)}
-                                                            key={index}
-                                                            disableGutters
-                                                        >
-                                                            <AccordionSummary
-                                                                expandIcon={<ExpandMoreIcon />}
-                                                                aria-controls={`nodes-accordian-${node.name}`}
-                                                                id={`nodes-accordian-header-${node.name}`}
+                {vsFlowData && vsFlowData.length > 0 && rmFlowData && rmFlowData.length > 0 && (
+                    <Card sx={{ borderColor: theme.palette.primary[200] + 75, p: 2 }} variant='outlined'>
+                        <Stack sx={{ mt: 1, mb: 2, ml: 1, alignItems: 'center' }} direction='row' spacing={2}>
+                            <SettingsIcon />
+                            <Typography variant='h4'>Configuration</Typography>
+                        </Stack>
+                        <Stack direction='column'>
+                            <TableContainer component={Paper} sx={{ maxHeight: '400px', overflow: 'auto' }}>
+                                <Table sx={{ minWidth: 650 }} aria-label='simple table'>
+                                    <TableBody>
+                                        <TableRow sx={{ '& td': { border: 0 } }}>
+                                            <TableCell sx={{ pb: 0, pt: 0 }} colSpan={6}>
+                                                <Box>
+                                                    {([...vsFlowData, ...rmFlowData] || []).map((node, index) => {
+                                                        return (
+                                                            <Accordion
+                                                                expanded={nodeConfigExpanded[node.name] || false}
+                                                                onChange={handleAccordionChange(node.name)}
+                                                                key={index}
+                                                                disableGutters
                                                             >
-                                                                <div
-                                                                    style={{ display: 'flex', flexDirection: 'row', alignItems: 'center' }}
+                                                                <AccordionSummary
+                                                                    expandIcon={<ExpandMoreIcon />}
+                                                                    aria-controls={`nodes-accordian-${node.name}`}
+                                                                    id={`nodes-accordian-header-${node.name}`}
                                                                 >
                                                                     <div
                                                                         style={{
-                                                                            width: 40,
-                                                                            height: 40,
-                                                                            marginRight: 10,
-                                                                            borderRadius: '50%',
-                                                                            backgroundColor: 'white'
+                                                                            display: 'flex',
+                                                                            flexDirection: 'row',
+                                                                            alignItems: 'center'
                                                                         }}
                                                                     >
-                                                                        <img
+                                                                        <div
                                                                             style={{
-                                                                                width: '100%',
-                                                                                height: '100%',
-                                                                                padding: 7,
+                                                                                width: 40,
+                                                                                height: 40,
+                                                                                marginRight: 10,
                                                                                 borderRadius: '50%',
-                                                                                objectFit: 'contain'
+                                                                                backgroundColor: 'white'
                                                                             }}
-                                                                            alt={node.name}
-                                                                            src={`${baseURL}/api/v1/node-icon/${node.name}`}
-                                                                        />
+                                                                        >
+                                                                            <img
+                                                                                style={{
+                                                                                    width: '100%',
+                                                                                    height: '100%',
+                                                                                    padding: 7,
+                                                                                    borderRadius: '50%',
+                                                                                    objectFit: 'contain'
+                                                                                }}
+                                                                                alt={node.name}
+                                                                                src={`${baseURL}/api/v1/node-icon/${node.name}`}
+                                                                            />
+                                                                        </div>
+                                                                        <Typography variant='h5'>{node.label}</Typography>
                                                                     </div>
-                                                                    <Typography variant='h5'>{node.label}</Typography>
-                                                                </div>
-                                                            </AccordionSummary>
-                                                            <AccordionDetails>
-                                                                {node.paramValues[0] && (
-                                                                    <TableViewOnly
-                                                                        sx={{ minWidth: 150 }}
-                                                                        rows={node.paramValues}
-                                                                        columns={Object.keys(node.paramValues[0])}
-                                                                    />
-                                                                )}
-                                                            </AccordionDetails>
-                                                        </Accordion>
-                                                    )
-                                                })}
-                                            </Box>
-                                        </TableCell>
-                                    </TableRow>
-                                </TableBody>
-                            </Table>
-                        </TableContainer>
-                        <span style={{ marginTop: '30px', fontStyle: 'italic', color: '#b35702' }}>
-                            * Only data that were upserted with Record Manager will be deleted from vector store
-                        </span>
-                    </div>
+                                                                </AccordionSummary>
+                                                                <AccordionDetails sx={{ p: 0 }}>
+                                                                    {node.paramValues[0] && (
+                                                                        <TableViewOnly
+                                                                            sx={{ minWidth: 150 }}
+                                                                            rows={node.paramValues}
+                                                                            columns={Object.keys(node.paramValues[0])}
+                                                                        />
+                                                                    )}
+                                                                </AccordionDetails>
+                                                            </Accordion>
+                                                        )
+                                                    })}
+                                                </Box>
+                                            </TableCell>
+                                        </TableRow>
+                                    </TableBody>
+                                </Table>
+                            </TableContainer>
+                        </Stack>
+                    </Card>
                 )}
             </DialogContent>
             <DialogActions sx={{ pr: 3, pb: 3 }}>
                 <Button onClick={onCancel} color='primary'>
                     Cancel
                 </Button>
-                <Button variant='contained' onClick={() => onDelete(dialogProps.type, dialogProps.file, removeFromVS)} color='error'>
+                <Button variant='contained' onClick={() => onDelete(dialogProps.type, dialogProps.file)} color='error'>
                     Delete
                 </Button>
             </DialogActions>

packages/ui/src/views/docstore/DocumentStoreDetail.jsx

@@ -186,19 +186,19 @@ const DocumentStoreDetails = () => {
         setShowDocumentLoaderListDialog(true)
     }
 
-    const deleteVectorStoreDataFromStore = async (storeId) => {
+    const deleteVectorStoreDataFromStore = async (storeId, docId) => {
         try {
-            await documentsApi.deleteVectorStoreDataFromStore(storeId)
+            await documentsApi.deleteVectorStoreDataFromStore(storeId, docId)
         } catch (error) {
             console.error(error)
         }
     }
 
-    const onDocStoreDelete = async (type, file, removeFromVectorStore) => {
+    const onDocStoreDelete = async (type, file) => {
         setBackdropLoading(true)
         setShowDeleteDocStoreDialog(false)
         if (type === 'STORE') {
-            if (removeFromVectorStore) {
+            if (documentStore.recordManagerConfig) {
                 await deleteVectorStoreDataFromStore(storeId)
             }
             try {
@@ -239,6 +239,9 @@ const DocumentStoreDetails = () => {
                 })
             }
         } else if (type === 'LOADER') {
+            if (documentStore.recordManagerConfig) {
+                await deleteVectorStoreDataFromStore(storeId, file.id)
+            }
             try {
                 const deleteResp = await documentsApi.deleteLoaderFromStore(storeId, file.id)
                 setBackdropLoading(false)
@@ -280,9 +283,40 @@ const DocumentStoreDetails = () => {
     }
 
     const onLoaderDelete = (file, vectorStoreConfig, recordManagerConfig) => {
+        // Get the display name in the format "LoaderName (sourceName)"
+        const loaderName = file.loaderName || 'Unknown'
+        let sourceName = ''
+
+        // Prefer files.name when files array exists and has items
+        if (file.files && Array.isArray(file.files) && file.files.length > 0) {
+            sourceName = file.files.map((f) => f.name).join(', ')
+        } else if (file.source) {
+            // Fallback to source logic
+            if (typeof file.source === 'string' && file.source.includes('base64')) {
+                sourceName = getFileName(file.source)
+            } else if (typeof file.source === 'string' && file.source.startsWith('[') && file.source.endsWith(']')) {
+                sourceName = JSON.parse(file.source).join(', ')
+            } else if (typeof file.source === 'string') {
+                sourceName = file.source
+            }
+        }
+
+        const displayName = sourceName ? `${loaderName} (${sourceName})` : loaderName
+
+        let description = `Delete "${displayName}"? This will delete all the associated document chunks from the document store.`
+
+        if (
+            recordManagerConfig &&
+            vectorStoreConfig &&
+            Object.keys(recordManagerConfig).length > 0 &&
+            Object.keys(vectorStoreConfig).length > 0
+        ) {
+            description = `Delete "${displayName}"? This will delete all the associated document chunks from the document store and remove the actual data from the vector store database.`
+        }
+
         const props = {
             title: `Delete`,
-            description: `Delete Loader ${file.loaderName} ? This will delete all the associated document chunks.`,
+            description,
             vectorStoreConfig,
             recordManagerConfig,
             type: 'LOADER',
@@ -294,9 +328,20 @@ const DocumentStoreDetails = () => {
     }
 
     const onStoreDelete = (vectorStoreConfig, recordManagerConfig) => {
+        let description = `Delete Store ${getSpecificDocumentStore.data?.name}? This will delete all the associated loaders and document chunks from the document store.`
+
+        if (
+            recordManagerConfig &&
+            vectorStoreConfig &&
+            Object.keys(recordManagerConfig).length > 0 &&
+            Object.keys(vectorStoreConfig).length > 0
+        ) {
+            description = `Delete Store ${getSpecificDocumentStore.data?.name}? This will delete all the associated loaders and document chunks from the document store, and remove the actual data from the vector store database.`
+        }
+
         const props = {
             title: `Delete`,
-            description: `Delete Store ${getSpecificDocumentStore.data?.name} ? This will delete all the associated loaders and document chunks.`,
+            description,
             vectorStoreConfig,
             recordManagerConfig,
             type: 'STORE'
@@ -481,7 +526,10 @@ const DocumentStoreDetails = () => {
                             >
                                 <MenuItem
                                     disabled={documentStore?.totalChunks <= 0 || documentStore?.status === 'UPSERTING'}
-                                    onClick={() => showStoredChunks('all')}
+                                    onClick={() => {
+                                        handleClose()
+                                        showStoredChunks('all')
+                                    }}
                                     disableRipple
                                 >
                                     <FileChunksIcon />
@@ -490,7 +538,10 @@ const DocumentStoreDetails = () => {
                                 <Available permission={'documentStores:upsert-config'}>
                                     <MenuItem
                                         disabled={documentStore?.totalChunks <= 0 || documentStore?.status === 'UPSERTING'}
-                                        onClick={() => showVectorStore(documentStore.id)}
+                                        onClick={() => {
+                                            handleClose()
+                                            showVectorStore(documentStore.id)
+                                        }}
                                         disableRipple
                                     >
                                         <NoteAddIcon />
@@ -499,7 +550,10 @@ const DocumentStoreDetails = () => {
                                 </Available>
                                 <MenuItem
                                     disabled={documentStore?.totalChunks <= 0 || documentStore?.status !== 'UPSERTED'}
-                                    onClick={() => showVectorStoreQuery(documentStore.id)}
+                                    onClick={() => {
+                                        handleClose()
+                                        showVectorStoreQuery(documentStore.id)
+                                    }}
                                     disableRipple
                                 >
                                     <SearchIcon />
@@ -518,7 +572,10 @@ const DocumentStoreDetails = () => {
                                 </Available>
                                 <Divider sx={{ my: 0.5 }} />
                                 <MenuItem
-                                    onClick={() => onStoreDelete(documentStore.vectorStoreConfig, documentStore.recordManagerConfig)}
+                                    onClick={() => {
+                                        handleClose()
+                                        onStoreDelete(documentStore.vectorStoreConfig, documentStore.recordManagerConfig)
+                                    }}
                                     disableRipple
                                 >
                                     <FileDeleteIcon />
@@ -756,20 +813,26 @@ function LoaderRow(props) {
         setAnchorEl(null)
     }
 
-    const formatSources = (files, source) => {
+    const formatSources = (files, source, loaderName) => {
+        let sourceName = ''
+
         // Prefer files.name when files array exists and has items
         if (files && Array.isArray(files) && files.length > 0) {
-            return files.map((file) => file.name).join(', ')
+            sourceName = files.map((file) => file.name).join(', ')
+        } else if (source && typeof source === 'string' && source.includes('base64')) {
+            // Fallback to original source logic
+            sourceName = getFileName(source)
+        } else if (source && typeof source === 'string' && source.startsWith('[') && source.endsWith(']')) {
+            sourceName = JSON.parse(source).join(', ')
+        } else if (source) {
+            sourceName = source
         }
 
-        // Fallback to original source logic
-        if (source && typeof source === 'string' && source.includes('base64')) {
-            return getFileName(source)
+        // Return format: "LoaderName (sourceName)" or just "LoaderName" if no source
+        if (!sourceName) {
+            return loaderName || 'No source'
         }
-        if (source && typeof source === 'string' && source.startsWith('[') && source.endsWith(']')) {
-            return JSON.parse(source).join(', ')
-        }
-        return source || 'No source'
+        return loaderName ? `${loaderName} (${sourceName})` : sourceName
     }
 
     return (
@@ -823,32 +886,62 @@ function LoaderRow(props) {
                                 onClose={handleClose}
                             >
                                 <Available permission={'documentStores:preview-process'}>
-                                    <MenuItem onClick={props.onEditClick} disableRipple>
+                                    <MenuItem
+                                        onClick={() => {
+                                            handleClose()
+                                            props.onEditClick()
+                                        }}
+                                        disableRipple
+                                    >
                                         <FileEditIcon />
                                         Preview & Process
                                     </MenuItem>
                                 </Available>
                                 <Available permission={'documentStores:preview-process'}>
-                                    <MenuItem onClick={props.onViewChunksClick} disableRipple>
+                                    <MenuItem
+                                        onClick={() => {
+                                            handleClose()
+                                            props.onViewChunksClick()
+                                        }}
+                                        disableRipple
+                                    >
                                         <FileChunksIcon />
                                         View & Edit Chunks
                                     </MenuItem>
                                 </Available>
                                 <Available permission={'documentStores:preview-process'}>
-                                    <MenuItem onClick={props.onChunkUpsert} disableRipple>
+                                    <MenuItem
+                                        onClick={() => {
+                                            handleClose()
+                                            props.onChunkUpsert()
+                                        }}
+                                        disableRipple
+                                    >
                                         <NoteAddIcon />
                                         Upsert Chunks
                                     </MenuItem>
                                 </Available>
                                 <Available permission={'documentStores:preview-process'}>
-                                    <MenuItem onClick={props.onViewUpsertAPI} disableRipple>
+                                    <MenuItem
+                                        onClick={() => {
+                                            handleClose()
+                                            props.onViewUpsertAPI()
+                                        }}
+                                        disableRipple
+                                    >
                                         <CodeIcon />
                                         View API
                                     </MenuItem>
                                 </Available>
                                 <Divider sx={{ my: 0.5 }} />
                                 <Available permission={'documentStores:delete-loader'}>
-                                    <MenuItem onClick={props.onDeleteClick} disableRipple>
+                                    <MenuItem
+                                        onClick={() => {
+                                            handleClose()
+                                            props.onDeleteClick()
+                                        }}
+                                        disableRipple
+                                    >
                                         <FileDeleteIcon />
                                         Delete
                                     </MenuItem>

packages/ui/src/views/docstore/ShowStoredChunks.jsx

@@ -26,6 +26,7 @@ import useApi from '@/hooks/useApi'
 import useConfirm from '@/hooks/useConfirm'
 import useNotifier from '@/utils/useNotifier'
 import { useAuth } from '@/hooks/useAuth'
+import { getFileName } from '@/utils/genericHelper'
 
 // store
 import { closeSnackbar as closeSnackbarAction, enqueueSnackbar as enqueueSnackbarAction } from '@/store/actions'
@@ -76,6 +77,7 @@ const ShowStoredChunks = () => {
     const [showExpandedChunkDialog, setShowExpandedChunkDialog] = useState(false)
     const [expandedChunkDialogProps, setExpandedChunkDialogProps] = useState({})
     const [fileNames, setFileNames] = useState([])
+    const [loaderDisplayName, setLoaderDisplayName] = useState('')
 
     const chunkSelected = (chunkId) => {
         const selectedChunk = documentChunks.find((chunk) => chunk.id === chunkId)
@@ -212,13 +214,32 @@ const ShowStoredChunks = () => {
             setCurrentPage(data.currentPage)
             setStart(data.currentPage * 50 - 49)
             setEnd(data.currentPage * 50 > data.count ? data.count : data.currentPage * 50)
+
+            // Build the loader display name in format "LoaderName (sourceName)"
+            const loaderName = data.file?.loaderName || data.storeName || ''
+            let sourceName = ''
+
             if (data.file?.files && data.file.files.length > 0) {
                 const fileNames = []
                 for (const attachedFile of data.file.files) {
                     fileNames.push(attachedFile.name)
                 }
                 setFileNames(fileNames)
+                sourceName = fileNames.join(', ')
+            } else if (data.file?.source) {
+                const source = data.file.source
+                if (typeof source === 'string' && source.includes('base64')) {
+                    sourceName = getFileName(source)
+                } else if (typeof source === 'string' && source.startsWith('[') && source.endsWith(']')) {
+                    sourceName = JSON.parse(source).join(', ')
+                } else if (typeof source === 'string') {
+                    sourceName = source
+                }
             }
+
+            // Set display name in format "LoaderName (sourceName)" or just "LoaderName"
+            const displayName = sourceName ? `${loaderName} (${sourceName})` : loaderName
+            setLoaderDisplayName(displayName)
         }
 
         // eslint-disable-next-line react-hooks/exhaustive-deps
@@ -234,7 +255,7 @@ const ShowStoredChunks = () => {
                         <ViewHeader
                             isBackButton={true}
                             search={false}
-                            title={getChunksApi.data?.file?.loaderName || getChunksApi.data?.storeName}
+                            title={loaderDisplayName}
                             description={getChunksApi.data?.file?.splitterName || getChunksApi.data?.description}
                             onBack={() => navigate(-1)}
                         ></ViewHeader>