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) 
-                      }}

CONTRIBUTING.md

@@ -114,50 +114,52 @@ Flowise has 3 different modules in a single mono repository.
 
     to make sure everything works fine in production.
 
-11. Commit code and submit Pull Request from forked branch pointing to [Flowise master](https://github.com/FlowiseAI/Flowise/tree/master).
+11. Commit code and submit Pull Request from forked branch pointing to [Flowise main](https://github.com/FlowiseAI/Flowise/tree/main).
 
 ## 🌱 Env Variables
 
 Flowise support different environment variables to configure your instance. You can specify the following variables in the `.env` file inside `packages/server` folder. Read [more](https://docs.flowiseai.com/environment-variables)
 
-| Variable                           | Description                                                                      | Type                                             | Default                             |
-| ---------------------------------- | -------------------------------------------------------------------------------- | ------------------------------------------------ | ----------------------------------- |
-| PORT                               | The HTTP port Flowise runs on                                                    | Number                                           | 3000                                |
-| CORS_ORIGINS                       | The allowed origins for all cross-origin HTTP calls                              | String                                           |                                     |
-| IFRAME_ORIGINS                     | The allowed origins for iframe src embedding                                     | String                                           |                                     |
-| FLOWISE_FILE_SIZE_LIMIT            | Upload File Size Limit                                                           | String                                           | 50mb                                |
-| DEBUG                              | Print logs from components                                                       | Boolean                                          |                                     |
-| LOG_PATH                           | Location where log files are stored                                              | String                                           | `your-path/Flowise/logs`            |
-| LOG_LEVEL                          | Different levels of logs                                                         | Enum String: `error`, `info`, `verbose`, `debug` | `info`                              |
-| LOG_JSON_SPACES                    | Spaces to beautify JSON logs                                                     |                                                  | 2                                   |
-| TOOL_FUNCTION_BUILTIN_DEP          | NodeJS built-in modules to be used for Tool Function                             | String                                           |                                     |
-| TOOL_FUNCTION_EXTERNAL_DEP         | External modules to be used for Tool Function                                    | String                                           |                                     |
-| DATABASE_TYPE                      | Type of database to store the flowise data                                       | Enum String: `sqlite`, `mysql`, `postgres`       | `sqlite`                            |
-| DATABASE_PATH                      | Location where database is saved (When DATABASE_TYPE is sqlite)                  | String                                           | `your-home-dir/.flowise`            |
-| DATABASE_HOST                      | Host URL or IP address (When DATABASE_TYPE is not sqlite)                        | String                                           |                                     |
-| DATABASE_PORT                      | Database port (When DATABASE_TYPE is not sqlite)                                 | String                                           |                                     |
-| DATABASE_USER                      | Database username (When DATABASE_TYPE is not sqlite)                             | String                                           |                                     |
-| DATABASE_PASSWORD                  | Database password (When DATABASE_TYPE is not sqlite)                             | String                                           |                                     |
-| DATABASE_NAME                      | Database name (When DATABASE_TYPE is not sqlite)                                 | String                                           |                                     |
-| DATABASE_SSL_KEY_BASE64            | Database SSL client cert in base64 (takes priority over DATABASE_SSL)            | Boolean                                          | false                               |
-| DATABASE_SSL                       | Database connection overssl (When DATABASE_TYPE is postgre)                      | Boolean                                          | false                               |
-| SECRETKEY_PATH                     | Location where encryption key (used to encrypt/decrypt credentials) is saved     | String                                           | `your-path/Flowise/packages/server` |
-| FLOWISE_SECRETKEY_OVERWRITE        | Encryption key to be used instead of the key stored in SECRETKEY_PATH            | String                                           |                                     |
-| MODEL_LIST_CONFIG_JSON             | File path to load list of models from your local config file                     | String                                           | `/your_model_list_config_file_path` |
-| STORAGE_TYPE                       | Type of storage for uploaded files. default is `local`                           | Enum String: `s3`, `local`, `gcs`                | `local`                             |
-| BLOB_STORAGE_PATH                  | Local folder path where uploaded files are stored when `STORAGE_TYPE` is `local` | String                                           | `your-home-dir/.flowise/storage`    |
-| S3_STORAGE_BUCKET_NAME             | Bucket name to hold the uploaded files when `STORAGE_TYPE` is `s3`               | String                                           |                                     |
-| S3_STORAGE_ACCESS_KEY_ID           | AWS Access Key                                                                   | String                                           |                                     |
-| S3_STORAGE_SECRET_ACCESS_KEY       | AWS Secret Key                                                                   | String                                           |                                     |
-| S3_STORAGE_REGION                  | Region for S3 bucket                                                             | String                                           |                                     |
-| S3_ENDPOINT_URL                    | Custom Endpoint for S3                                                           | String                                           |                                     |
-| S3_FORCE_PATH_STYLE                | Set this to true to force the request to use path-style addressing               | Boolean                                          | false                               |
-| GOOGLE_CLOUD_STORAGE_PROJ_ID       | The GCP project id for cloud storage & logging when `STORAGE_TYPE` is `gcs`      | String                                           |                                     |
-| GOOGLE_CLOUD_STORAGE_CREDENTIAL    | The credential key file path when `STORAGE_TYPE` is `gcs`                        | String                                           |                                     |
-| GOOGLE_CLOUD_STORAGE_BUCKET_NAME   | Bucket name to hold the uploaded files when `STORAGE_TYPE` is `gcs`              | String                                           |                                     |
-| GOOGLE_CLOUD_UNIFORM_BUCKET_ACCESS | Enable uniform bucket level access when `STORAGE_TYPE` is `gcs`                  | Boolean                                          | true                                |
-| SHOW_COMMUNITY_NODES               | Show nodes created by community                                                  | Boolean                                          |                                     |
-| DISABLED_NODES                     | Hide nodes from UI (comma separated list of node names)                          | String                                           |                                     |
+| Variable                           | Description                                                                                                                                                                                                                                                                       | Type                                             | Default                             |
+| ---------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------ | ----------------------------------- |
+| PORT                               | The HTTP port Flowise runs on                                                                                                                                                                                                                                                     | Number                                           | 3000                                |
+| CORS_ORIGINS                       | The allowed origins for all cross-origin HTTP calls                                                                                                                                                                                                                               | String                                           |                                     |
+| IFRAME_ORIGINS                     | The allowed origins for iframe src embedding                                                                                                                                                                                                                                      | String                                           |                                     |
+| FLOWISE_FILE_SIZE_LIMIT            | Upload File Size Limit                                                                                                                                                                                                                                                            | String                                           | 50mb                                |
+| DEBUG                              | Print logs from components                                                                                                                                                                                                                                                        | Boolean                                          |                                     |
+| LOG_PATH                           | Location where log files are stored                                                                                                                                                                                                                                               | String                                           | `your-path/Flowise/logs`            |
+| LOG_LEVEL                          | Different levels of logs                                                                                                                                                                                                                                                          | Enum String: `error`, `info`, `verbose`, `debug` | `info`                              |
+| LOG_JSON_SPACES                    | Spaces to beautify JSON logs                                                                                                                                                                                                                                                      |                                                  | 2                                   |
+| TOOL_FUNCTION_BUILTIN_DEP          | NodeJS built-in modules to be used for Custom Tool or Function                                                                                                                                                                                                                    | String                                           |                                     |
+| TOOL_FUNCTION_EXTERNAL_DEP         | External modules to be used for Custom Tool or Function                                                                                                                                                                                                                           | String                                           |                                     |
+| ALLOW_BUILTIN_DEP                  | Allow project dependencies to be used for Custom Tool or Function                                                                                                                                                                                                                 | Boolean                                          | false                               |
+| DATABASE_TYPE                      | Type of database to store the flowise data                                                                                                                                                                                                                                        | Enum String: `sqlite`, `mysql`, `postgres`       | `sqlite`                            |
+| DATABASE_PATH                      | Location where database is saved (When DATABASE_TYPE is sqlite)                                                                                                                                                                                                                   | String                                           | `your-home-dir/.flowise`            |
+| DATABASE_HOST                      | Host URL or IP address (When DATABASE_TYPE is not sqlite)                                                                                                                                                                                                                         | String                                           |                                     |
+| DATABASE_PORT                      | Database port (When DATABASE_TYPE is not sqlite)                                                                                                                                                                                                                                  | String                                           |                                     |
+| DATABASE_USER                      | Database username (When DATABASE_TYPE is not sqlite)                                                                                                                                                                                                                              | String                                           |                                     |
+| DATABASE_PASSWORD                  | Database password (When DATABASE_TYPE is not sqlite)                                                                                                                                                                                                                              | String                                           |                                     |
+| DATABASE_NAME                      | Database name (When DATABASE_TYPE is not sqlite)                                                                                                                                                                                                                                  | String                                           |                                     |
+| DATABASE_SSL_KEY_BASE64            | Database SSL client cert in base64 (takes priority over DATABASE_SSL)                                                                                                                                                                                                             | Boolean                                          | false                               |
+| DATABASE_SSL                       | Database connection overssl (When DATABASE_TYPE is postgre)                                                                                                                                                                                                                       | Boolean                                          | false                               |
+| SECRETKEY_PATH                     | Location where encryption key (used to encrypt/decrypt credentials) is saved                                                                                                                                                                                                      | String                                           | `your-path/Flowise/packages/server` |
+| FLOWISE_SECRETKEY_OVERWRITE        | Encryption key to be used instead of the key stored in SECRETKEY_PATH                                                                                                                                                                                                             | String                                           |                                     |
+| MODEL_LIST_CONFIG_JSON             | File path to load list of models from your local config file                                                                                                                                                                                                                      | String                                           | `/your_model_list_config_file_path` |
+| STORAGE_TYPE                       | Type of storage for uploaded files. default is `local`                                                                                                                                                                                                                            | Enum String: `s3`, `local`, `gcs`                | `local`                             |
+| BLOB_STORAGE_PATH                  | Local folder path where uploaded files are stored when `STORAGE_TYPE` is `local`                                                                                                                                                                                                  | String                                           | `your-home-dir/.flowise/storage`    |
+| S3_STORAGE_BUCKET_NAME             | Bucket name to hold the uploaded files when `STORAGE_TYPE` is `s3`                                                                                                                                                                                                                | String                                           |                                     |
+| S3_STORAGE_ACCESS_KEY_ID           | AWS Access Key                                                                                                                                                                                                                                                                    | String                                           |                                     |
+| S3_STORAGE_SECRET_ACCESS_KEY       | AWS Secret Key                                                                                                                                                                                                                                                                    | String                                           |                                     |
+| S3_STORAGE_REGION                  | Region for S3 bucket                                                                                                                                                                                                                                                              | String                                           |                                     |
+| S3_ENDPOINT_URL                    | Custom Endpoint for S3                                                                                                                                                                                                                                                            | String                                           |                                     |
+| S3_FORCE_PATH_STYLE                | Set this to true to force the request to use path-style addressing                                                                                                                                                                                                                | Boolean                                          | false                               |
+| GOOGLE_CLOUD_STORAGE_PROJ_ID       | The GCP project id for cloud storage & logging when `STORAGE_TYPE` is `gcs`                                                                                                                                                                                                       | String                                           |                                     |
+| GOOGLE_CLOUD_STORAGE_CREDENTIAL    | The credential key file path when `STORAGE_TYPE` is `gcs`                                                                                                                                                                                                                         | String                                           |                                     |
+| GOOGLE_CLOUD_STORAGE_BUCKET_NAME   | Bucket name to hold the uploaded files when `STORAGE_TYPE` is `gcs`                                                                                                                                                                                                               | String                                           |                                     |
+| GOOGLE_CLOUD_UNIFORM_BUCKET_ACCESS | Enable uniform bucket level access when `STORAGE_TYPE` is `gcs`                                                                                                                                                                                                                   | Boolean                                          | true                                |
+| SHOW_COMMUNITY_NODES               | Show nodes created by community                                                                                                                                                                                                                                                   | Boolean                                          |                                     |
+| DISABLED_NODES                     | Hide nodes from UI (comma separated list of node names)                                                                                                                                                                                                                           | String                                           |                                     |
+| TRUST_PROXY                        | Configure proxy trust settings for proper IP detection. Values: 'true' (trust all), 'false' (disable), number (hop count), or Express proxy values (e.g., 'loopback', 'linklocal', 'uniquelocal', IP addresses). [Learn More](https://expressjs.com/en/guide/behind-proxies.html) | Boolean/String/Number                            | true                                |
 
 You can also specify the env variables when using `npx`. For example:
 

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

@@ -23,16 +23,16 @@ English | [繁體中文](./i18n/README-TW.md) | [简体中文](./i18n/README-ZH.
 
 ## 📚 Table of Contents
 
-- [⚡ Quick Start](#-quick-start)
-- [🐳 Docker](#-docker)
-- [👨‍💻 Developers](#-developers)
-- [🌱 Env Variables](#-env-variables)
-- [📖 Documentation](#-documentation)
-- [🌐 Self Host](#-self-host)
-- [☁️ Flowise Cloud](#️-flowise-cloud)
-- [🙋 Support](#-support)
-- [🙌 Contributing](#-contributing)
-- [📄 License](#-license)
+-   [⚡ Quick Start](#-quick-start)
+-   [🐳 Docker](#-docker)
+-   [👨‍💻 Developers](#-developers)
+-   [🌱 Env Variables](#-env-variables)
+-   [📖 Documentation](#-documentation)
+-   [🌐 Self Host](#-self-host)
+-   [☁️ Flowise Cloud](#️-flowise-cloud)
+-   [🙋 Support](#-support)
+-   [🙌 Contributing](#-contributing)
+-   [📄 License](#-license)
 
 ## ⚡Quick Start
 
@@ -64,18 +64,19 @@ Download and Install [NodeJS](https://nodejs.org/en/download) >= 18.15.0
 ### Docker Image
 
 1. Build the image locally:
-   
+
     ```bash
     docker build --no-cache -t flowise .
     ```
+
 2. Run image:
-   
+
     ```bash
     docker run -d --name flowise -p 3000:3000 flowise
     ```
 
 3. Stop image:
-   
+
     ```bash
     docker stop flowise
     ```
@@ -124,10 +125,24 @@ Flowise has 3 different modules in a single mono repository.
 
     <details>
     <summary>Exit code 134 (JavaScript heap out of memory)</summary>  
-      If you get this error when running the above `build` script, try increasing the Node.js heap size and run the script again:
+    If you get this error when running the above `build` script, try increasing the Node.js heap size and run the script again:
 
-        export NODE_OPTIONS="--max-old-space-size=4096"
-        pnpm build
+    ```bash
+    # macOS / Linux / Git Bash
+    export NODE_OPTIONS="--max-old-space-size=4096"
+
+    # Windows PowerShell
+    $env:NODE_OPTIONS="--max-old-space-size=4096"
+
+    # Windows CMD
+    set NODE_OPTIONS=--max-old-space-size=4096
+    ```
+
+    Then run:
+
+    ```bash
+    pnpm build
+    ```
 
     </details>
 
@@ -175,6 +190,10 @@ Deploy Flowise self-hosted in your existing infrastructure, we support various [
 
         [![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)
+
     -   [Render](https://docs.flowiseai.com/configuration/deployment/render)
 
         [![Deploy to Render](https://render.com/images/deploy-to-render-button.svg)](https://docs.flowiseai.com/configuration/deployment/render)

SECURITY.md

@@ -1,40 +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.
 
-### Vulnerabilities  
+### Out of scope vulnerabilities
 
-The following types of issues are some of the most common 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 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 appreciate your efforts in helping us maintain a secure platform and look forward to working together to resolve any issues responsibly.

docker/.env.example

@@ -14,6 +14,7 @@ DATABASE_PATH=/root/.flowise
 # DATABASE_USER=root
 # DATABASE_PASSWORD=mypassword
 # DATABASE_SSL=true
+# DATABASE_REJECT_UNAUTHORIZED=true
 # DATABASE_SSL_KEY_BASE64=<Self signed certificate in BASE64>
 
 
@@ -37,8 +38,11 @@ SECRETKEY_PATH=/root/.flowise
 # DEBUG=true
 LOG_PATH=/root/.flowise/logs
 # LOG_LEVEL=info #(error | warn | info | verbose | debug)
+# LOG_SANITIZE_BODY_FIELDS=password,pwd,pass,secret,token,apikey,api_key,accesstoken,access_token,refreshtoken,refresh_token,clientsecret,client_secret,privatekey,private_key,secretkey,secret_key,auth,authorization,credential,credentials
+# LOG_SANITIZE_HEADER_FIELDS=authorization,x-api-key,x-auth-token,cookie
 # TOOL_FUNCTION_BUILTIN_DEP=crypto,fs
 # TOOL_FUNCTION_EXTERNAL_DEP=moment,lodash
+# ALLOW_BUILTIN_DEP=false
 
 
 ############################################################################################################
@@ -97,6 +101,7 @@ JWT_TOKEN_EXPIRY_IN_MINUTES=360
 JWT_REFRESH_TOKEN_EXPIRY_IN_MINUTES=43200
 # EXPIRE_AUTH_TOKENS_ON_RESTART=true # (if you need to expire all tokens on app restart)
 # EXPRESS_SESSION_SECRET=flowise
+# SECURE_COOKIES=
 
 # INVITE_TOKEN_EXPIRY_IN_HOURS=24
 # PASSWORD_RESET_TOKEN_EXPIRY_IN_MINS=15
@@ -162,4 +167,14 @@ JWT_REFRESH_TOKEN_EXPIRY_IN_MINUTES=43200
 # REDIS_KEY=
 # REDIS_CA=
 # REDIS_KEEP_ALIVE=
-# ENABLE_BULLMQ_DASHBOARD=
+# ENABLE_BULLMQ_DASHBOARD=
+
+
+############################################################################################################
+############################################## SECURITY ####################################################
+############################################################################################################
+
+# HTTP_DENY_LIST=
+# CUSTOM_MCP_SECURITY_CHECK=true
+# CUSTOM_MCP_PROTOCOL=sse #(stdio | sse)
+# TRUST_PROXY=true #(true | false | 1 | loopback| linklocal | uniquelocal | IP addresses | loopback, IP addresses)

docker/README.md

@@ -18,7 +18,7 @@ If you like to persist your data (flows, logs, credentials, storage), set these
 -   SECRETKEY_PATH=/root/.flowise
 -   BLOB_STORAGE_PATH=/root/.flowise/storage
 
-Flowise also support different environment variables to configure your instance. Read [more](https://docs.flowiseai.com/environment-variables)
+Flowise also support different environment variables to configure your instance. Read [more](https://docs.flowiseai.com/configuration/environment-variables)
 
 ## Queue Mode:
 

docker/docker-compose-queue-prebuilt.yml

@@ -46,10 +46,13 @@ services:
             - DEBUG=${DEBUG}
             - LOG_PATH=${LOG_PATH}
             - LOG_LEVEL=${LOG_LEVEL}
+            - LOG_SANITIZE_BODY_FIELDS=${LOG_SANITIZE_BODY_FIELDS}
+            - LOG_SANITIZE_HEADER_FIELDS=${LOG_SANITIZE_HEADER_FIELDS}
 
-            # CUSTOM TOOL DEPENDENCIES
+            # CUSTOM TOOL/FUNCTION DEPENDENCIES
             - TOOL_FUNCTION_BUILTIN_DEP=${TOOL_FUNCTION_BUILTIN_DEP}
             - TOOL_FUNCTION_EXTERNAL_DEP=${TOOL_FUNCTION_EXTERNAL_DEP}
+            - ALLOW_BUILTIN_DEP=${ALLOW_BUILTIN_DEP}
 
             # STORAGE
             - STORAGE_TYPE=${STORAGE_TYPE}
@@ -88,6 +91,7 @@ services:
             - PASSWORD_RESET_TOKEN_EXPIRY_IN_MINS=${PASSWORD_RESET_TOKEN_EXPIRY_IN_MINS}
             - PASSWORD_SALT_HASH_ROUNDS=${PASSWORD_SALT_HASH_ROUNDS}
             - TOKEN_HASH_SECRET=${TOKEN_HASH_SECRET}
+            - SECURE_COOKIES=${SECURE_COOKIES}
 
             # EMAIL
             - SMTP_HOST=${SMTP_HOST}
@@ -138,6 +142,12 @@ services:
             - REDIS_CA=${REDIS_CA}
             - REDIS_KEEP_ALIVE=${REDIS_KEEP_ALIVE}
             - ENABLE_BULLMQ_DASHBOARD=${ENABLE_BULLMQ_DASHBOARD}
+
+            # SECURITY
+            - CUSTOM_MCP_SECURITY_CHECK=${CUSTOM_MCP_SECURITY_CHECK}
+            - CUSTOM_MCP_PROTOCOL=${CUSTOM_MCP_PROTOCOL}
+            - HTTP_DENY_LIST=${HTTP_DENY_LIST}
+            - TRUST_PROXY=${TRUST_PROXY}
         healthcheck:
             test: ['CMD', 'curl', '-f', 'http://localhost:${PORT:-3000}/api/v1/ping']
             interval: 10s
@@ -182,10 +192,13 @@ services:
             - DEBUG=${DEBUG}
             - LOG_PATH=${LOG_PATH}
             - LOG_LEVEL=${LOG_LEVEL}
+            - LOG_SANITIZE_BODY_FIELDS=${LOG_SANITIZE_BODY_FIELDS}
+            - LOG_SANITIZE_HEADER_FIELDS=${LOG_SANITIZE_HEADER_FIELDS}
 
-            # CUSTOM TOOL DEPENDENCIES
+            # CUSTOM TOOL/FUNCTION DEPENDENCIES
             - TOOL_FUNCTION_BUILTIN_DEP=${TOOL_FUNCTION_BUILTIN_DEP}
             - TOOL_FUNCTION_EXTERNAL_DEP=${TOOL_FUNCTION_EXTERNAL_DEP}
+            - ALLOW_BUILTIN_DEP=${ALLOW_BUILTIN_DEP}
 
             # STORAGE
             - STORAGE_TYPE=${STORAGE_TYPE}
@@ -224,6 +237,7 @@ services:
             - PASSWORD_RESET_TOKEN_EXPIRY_IN_MINS=${PASSWORD_RESET_TOKEN_EXPIRY_IN_MINS}
             - PASSWORD_SALT_HASH_ROUNDS=${PASSWORD_SALT_HASH_ROUNDS}
             - TOKEN_HASH_SECRET=${TOKEN_HASH_SECRET}
+            - SECURE_COOKIES=${SECURE_COOKIES}
 
             # EMAIL
             - SMTP_HOST=${SMTP_HOST}
@@ -274,6 +288,12 @@ services:
             - REDIS_CA=${REDIS_CA}
             - REDIS_KEEP_ALIVE=${REDIS_KEEP_ALIVE}
             - ENABLE_BULLMQ_DASHBOARD=${ENABLE_BULLMQ_DASHBOARD}
+
+            # SECURITY
+            - CUSTOM_MCP_SECURITY_CHECK=${CUSTOM_MCP_SECURITY_CHECK}
+            - CUSTOM_MCP_PROTOCOL=${CUSTOM_MCP_PROTOCOL}
+            - HTTP_DENY_LIST=${HTTP_DENY_LIST}
+            - TRUST_PROXY=${TRUST_PROXY}
         healthcheck:
             test: ['CMD', 'curl', '-f', 'http://localhost:${WORKER_PORT:-5566}/healthz']
             interval: 10s

docker/docker-compose.yml

@@ -31,10 +31,13 @@ services:
             - DEBUG=${DEBUG}
             - LOG_PATH=${LOG_PATH}
             - LOG_LEVEL=${LOG_LEVEL}
+            - LOG_SANITIZE_BODY_FIELDS=${LOG_SANITIZE_BODY_FIELDS}
+            - LOG_SANITIZE_HEADER_FIELDS=${LOG_SANITIZE_HEADER_FIELDS}
 
-            # CUSTOM TOOL DEPENDENCIES
+            # CUSTOM TOOL/FUNCTION DEPENDENCIES
             - TOOL_FUNCTION_BUILTIN_DEP=${TOOL_FUNCTION_BUILTIN_DEP}
             - TOOL_FUNCTION_EXTERNAL_DEP=${TOOL_FUNCTION_EXTERNAL_DEP}
+            - ALLOW_BUILTIN_DEP=${ALLOW_BUILTIN_DEP}
 
             # STORAGE
             - STORAGE_TYPE=${STORAGE_TYPE}
@@ -73,6 +76,7 @@ services:
             - PASSWORD_RESET_TOKEN_EXPIRY_IN_MINS=${PASSWORD_RESET_TOKEN_EXPIRY_IN_MINS}
             - PASSWORD_SALT_HASH_ROUNDS=${PASSWORD_SALT_HASH_ROUNDS}
             - TOKEN_HASH_SECRET=${TOKEN_HASH_SECRET}
+            - SECURE_COOKIES=${SECURE_COOKIES}
 
             # EMAIL
             - SMTP_HOST=${SMTP_HOST}
@@ -123,6 +127,12 @@ services:
             - REDIS_CA=${REDIS_CA}
             - REDIS_KEEP_ALIVE=${REDIS_KEEP_ALIVE}
             - ENABLE_BULLMQ_DASHBOARD=${ENABLE_BULLMQ_DASHBOARD}
+
+            # SECURITY
+            - CUSTOM_MCP_SECURITY_CHECK=${CUSTOM_MCP_SECURITY_CHECK}
+            - CUSTOM_MCP_PROTOCOL=${CUSTOM_MCP_PROTOCOL}
+            - HTTP_DENY_LIST=${HTTP_DENY_LIST}
+            - TRUST_PROXY=${TRUST_PROXY}
         ports:
             - '${PORT}:${PORT}'
         healthcheck:

docker/worker/.env.example

@@ -14,6 +14,7 @@ DATABASE_PATH=/root/.flowise
 # DATABASE_USER=root
 # DATABASE_PASSWORD=mypassword
 # DATABASE_SSL=true
+# DATABASE_REJECT_UNAUTHORIZED=true
 # DATABASE_SSL_KEY_BASE64=<Self signed certificate in BASE64>
 
 
@@ -37,8 +38,11 @@ SECRETKEY_PATH=/root/.flowise
 # DEBUG=true
 LOG_PATH=/root/.flowise/logs
 # LOG_LEVEL=info #(error | warn | info | verbose | debug)
+# LOG_SANITIZE_BODY_FIELDS=password,pwd,pass,secret,token,apikey,api_key,accesstoken,access_token,refreshtoken,refresh_token,clientsecret,client_secret,privatekey,private_key,secretkey,secret_key,auth,authorization,credential,credentials
+# LOG_SANITIZE_HEADER_FIELDS=authorization,x-api-key,x-auth-token,cookie
 # TOOL_FUNCTION_BUILTIN_DEP=crypto,fs
 # TOOL_FUNCTION_EXTERNAL_DEP=moment,lodash
+# ALLOW_BUILTIN_DEP=false
 
 
 ############################################################################################################
@@ -97,6 +101,7 @@ JWT_TOKEN_EXPIRY_IN_MINUTES=360
 JWT_REFRESH_TOKEN_EXPIRY_IN_MINUTES=43200
 # EXPIRE_AUTH_TOKENS_ON_RESTART=true # (if you need to expire all tokens on app restart)
 # EXPRESS_SESSION_SECRET=flowise
+# SECURE_COOKIES=
 
 # INVITE_TOKEN_EXPIRY_IN_HOURS=24
 # PASSWORD_RESET_TOKEN_EXPIRY_IN_MINS=15
@@ -162,4 +167,14 @@ JWT_REFRESH_TOKEN_EXPIRY_IN_MINUTES=43200
 # REDIS_KEY=
 # REDIS_CA=
 # REDIS_KEEP_ALIVE=
-# ENABLE_BULLMQ_DASHBOARD=
+# ENABLE_BULLMQ_DASHBOARD=
+
+
+############################################################################################################
+############################################## SECURITY ####################################################
+############################################################################################################
+
+# HTTP_DENY_LIST=
+# CUSTOM_MCP_SECURITY_CHECK=true
+# CUSTOM_MCP_PROTOCOL=sse #(stdio | sse)
+# TRUST_PROXY=true #(true | false | 1 | loopback| linklocal | uniquelocal | IP addresses | loopback, IP addresses)

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

docker/worker/docker-compose.yml

@@ -31,10 +31,13 @@ services:
             - DEBUG=${DEBUG}
             - LOG_PATH=${LOG_PATH}
             - LOG_LEVEL=${LOG_LEVEL}
+            - LOG_SANITIZE_BODY_FIELDS=${LOG_SANITIZE_BODY_FIELDS}
+            - LOG_SANITIZE_HEADER_FIELDS=${LOG_SANITIZE_HEADER_FIELDS}
 
-            # CUSTOM TOOL DEPENDENCIES
+            # CUSTOM TOOL/FUNCTION DEPENDENCIES
             - TOOL_FUNCTION_BUILTIN_DEP=${TOOL_FUNCTION_BUILTIN_DEP}
             - TOOL_FUNCTION_EXTERNAL_DEP=${TOOL_FUNCTION_EXTERNAL_DEP}
+            - ALLOW_BUILTIN_DEP=${ALLOW_BUILTIN_DEP}
 
             # STORAGE
             - STORAGE_TYPE=${STORAGE_TYPE}
@@ -73,6 +76,7 @@ services:
             - PASSWORD_RESET_TOKEN_EXPIRY_IN_MINS=${PASSWORD_RESET_TOKEN_EXPIRY_IN_MINS}
             - PASSWORD_SALT_HASH_ROUNDS=${PASSWORD_SALT_HASH_ROUNDS}
             - TOKEN_HASH_SECRET=${TOKEN_HASH_SECRET}
+            - SECURE_COOKIES=${SECURE_COOKIES}
 
             # EMAIL
             - SMTP_HOST=${SMTP_HOST}
@@ -123,6 +127,12 @@ services:
             - REDIS_CA=${REDIS_CA}
             - REDIS_KEEP_ALIVE=${REDIS_KEEP_ALIVE}
             - ENABLE_BULLMQ_DASHBOARD=${ENABLE_BULLMQ_DASHBOARD}
+
+            # SECURITY
+            - CUSTOM_MCP_SECURITY_CHECK=${CUSTOM_MCP_SECURITY_CHECK}
+            - CUSTOM_MCP_PROTOCOL=${CUSTOM_MCP_PROTOCOL}
+            - HTTP_DENY_LIST=${HTTP_DENY_LIST}
+            - TRUST_PROXY=${TRUST_PROXY}
         ports:
             - '${WORKER_PORT}:${WORKER_PORT}'
         healthcheck:

i18n/CONTRIBUTING-ZH.md

@@ -112,7 +112,7 @@ Flowise 在一个单一的单体存储库中有 3 个不同的模块。
     pnpm start
     ```
 
-11. 提交代码并从指向 [Flowise 主分支](https://github.com/FlowiseAI/Flowise/tree/master) 的分叉分支上提交 Pull Request。
+11. 提交代码并从指向 [Flowise 主分支](https://github.com/FlowiseAI/Flowise/tree/main) 的分叉分支上提交 Pull Request。
 
 ## 🌱 环境变量
 

i18n/README-TW.md

@@ -13,7 +13,7 @@
 
 [English](../README.md) | 繁體中文 | [简体中文](./README-ZH.md) | [日本語](./README-JA.md) | [한국어](./README-KR.md)
 
-<h3>可視化建構 AI/LLM 流程</h3>
+<h3>可視化建置 AI/LLM 流程</h3>
 <a href="https://github.com/FlowiseAI/Flowise">
 <img width="100%" src="https://github.com/FlowiseAI/Flowise/blob/main/images/flowise_agentflow.gif?raw=true"></a>
 
@@ -37,16 +37,16 @@
 
 ### Docker Compose
 
-1. 克隆 Flowise 項目
-2. 進入項目根目錄的 `docker` 文件夾
-3. 複製 `.env.example` 文件，粘貼到相同位置，並重命名為 `.env` 文件
+1. 複製 Flowise 專案
+2. 進入專案根目錄的 `docker` 資料夾
+3. 複製 `.env.example` 文件，貼到相同位置，並重新命名為 `.env` 文件
 4. `docker compose up -d`
 5. 打開 [http://localhost:3000](http://localhost:3000)
-6. 您可以通過 `docker compose stop` 停止容器
+6. 您可以透過 `docker compose stop` 停止容器
 
 ### Docker 映像
 
-1. 本地構建映像：
+1. 本地建置映像：
     ```bash
     docker build --no-cache -t flowise .
     ```
@@ -63,7 +63,7 @@
 
 ## 👨‍💻 開發者
 
-Flowise 在單個 mono 存儲庫中有 3 個不同的模塊。
+Flowise 在單個 mono 儲存庫中有 3 個不同的模組。
 
 -   `server`: 提供 API 邏輯的 Node 後端
 -   `ui`: React 前端
@@ -79,33 +79,33 @@ Flowise 在單個 mono 存儲庫中有 3 個不同的模塊。
 
 ### 設置
 
-1.  克隆存儲庫
+1.  複製儲存庫
 
     ```bash
     git clone https://github.com/FlowiseAI/Flowise.git
     ```
 
-2.  進入存儲庫文件夾
+2.  進入儲存庫文件夾
 
     ```bash
     cd Flowise
     ```
 
-3.  安裝所有模塊的所有依賴項：
+3.  安裝所有模組的所有依賴項：
 
     ```bash
     pnpm install
     ```
 
-4.  構建所有代碼：
+4.  建置所有程式碼：
 
     ```bash
     pnpm build
     ```
 
     <details>
-    <summary>退出代碼 134（JavaScript 堆內存不足）</summary>  
-      如果在運行上述 `build` 腳本時遇到此錯誤，請嘗試增加 Node.js 堆大小並重新運行腳本：
+    <summary>Exit code 134（JavaScript heap out of memory）</summary>  
+      如果在運行上述 `build` 腳本時遇到此錯誤，請嘗試增加 Node.js 中的 Heap 記憶體大小並重新運行腳本：
 
         export NODE_OPTIONS="--max-old-space-size=4096"
         pnpm build
@@ -118,9 +118,9 @@ Flowise 在單個 mono 存儲庫中有 3 個不同的模塊。
     pnpm start
     ```
 
-    您現在可以訪問 [http://localhost:3000](http://localhost:3000)
+    您現在可以開啟 [http://localhost:3000](http://localhost:3000)
 
-6.  對於開發構建：
+6.  對於開發建置：
 
     -   在 `packages/ui` 中創建 `.env` 文件並指定 `VITE_PORT`（參考 `.env.example`）
     -   在 `packages/server` 中創建 `.env` 文件並指定 `PORT`（參考 `.env.example`）
@@ -130,19 +130,19 @@ Flowise 在單個 mono 存儲庫中有 3 個不同的模塊。
         pnpm dev
         ```
 
-    任何代碼更改都會自動重新加載應用程序 [http://localhost:8080](http://localhost:8080)
+    任何程式碼更改都會自動重新加載應用程式 [http://localhost:8080](http://localhost:8080)
 
-## 🌱 環境變量
+## 🌱 環境變數
 
-Flowise 支持不同的環境變量來配置您的實例。您可以在 `packages/server` 文件夾中的 `.env` 文件中指定以下變量。閱讀 [更多](https://github.com/FlowiseAI/Flowise/blob/main/CONTRIBUTING.md#-env-variables)
+Flowise 支持不同的環境變數來配置您的實例。您可以在 `packages/server` 文件夾中的 `.env` 文件中指定以下變數。閱讀 [更多](https://github.com/FlowiseAI/Flowise/blob/main/CONTRIBUTING.md#-env-variables)
 
 ## 📖 文檔
 
 [Flowise 文檔](https://docs.flowiseai.com/)
 
-## 🌐 自我托管
+## 🌐 自行架設
 
-在您現有的基礎設施中部署 Flowise 自我托管，我們支持各種 [部署](https://docs.flowiseai.com/configuration/deployment)
+在您現有的基礎設施中部署 Flowise，我們支持各種自行架設選項 [部署](https://docs.flowiseai.com/configuration/deployment)
 
 -   [AWS](https://docs.flowiseai.com/configuration/deployment/aws)
 -   [Azure](https://docs.flowiseai.com/configuration/deployment/azure)
@@ -178,9 +178,9 @@ Flowise 支持不同的環境變量來配置您的實例。您可以在 `package
 
       </details>
 
-## ☁️ Flowise 雲
+## ☁️ Flowise 雲端平台
 
-[開始使用 Flowise 雲](https://flowiseai.com/)
+[開始使用 Flowise 雲端平台](https://flowiseai.com/)
 
 ## 🙋 支持
 
@@ -194,9 +194,9 @@ Flowise 支持不同的環境變量來配置您的實例。您可以在 `package
 <img src="https://contrib.rocks/image?repo=FlowiseAI/Flowise" />
 </a>
 
-請參閱 [貢獻指南](../CONTRIBUTING.md)。如果您有任何問題或問題，請通過 [Discord](https://discord.gg/jbaHfsRVBW) 與我們聯繫。
+請參閱 [貢獻指南](../CONTRIBUTING.md)。如果您有任何問題或問題，請透過 [Discord](https://discord.gg/jbaHfsRVBW) 與我們聯繫。
 [![Star History Chart](https://api.star-history.com/svg?repos=FlowiseAI/Flowise&type=Timeline)](https://star-history.com/#FlowiseAI/Flowise&Date)
 
 ## 📄 許可證
 
-此存儲庫中的源代碼根據 [Apache 許可證版本 2.0](../LICENSE.md) 提供。
+此儲存庫中的原始碼根據 [Apache 2.0 授權條款](../LICENSE.md) 授權使用。

metrics/otel/compose.yaml

@@ -1,6 +1,7 @@
 version: "2"
 services:
   otel-collector:
+    read_only: true
     image: otel/opentelemetry-collector-contrib
     command: ["--config=/etc/otelcol-contrib/config.yaml", "--feature-gates=-exporter.datadogexporter.DisableAPMStats", "${OTELCOL_ARGS}"]
     volumes:

package.json

@@ -1,6 +1,6 @@
 {
     "name": "flowise",
-    "version": "3.0.4",
+    "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",
@@ -66,10 +66,11 @@
             "sqlite3"
         ],
         "overrides": {
-            "axios": "1.10.0",
+            "axios": "1.12.0",
             "body-parser": "2.0.2",
             "braces": "3.0.3",
             "cross-spawn": "7.0.6",
+            "form-data": "4.0.4",
             "glob-parent": "6.0.2",
             "http-proxy-middleware": "3.0.3",
             "json5": "2.2.3",
@@ -79,6 +80,7 @@
             "rollup": "4.45.0",
             "semver": "7.7.1",
             "set-value": "4.1.0",
+            "solid-js": "1.9.7",
             "tar-fs": "3.1.0",
             "unset-value": "2.0.1",
             "webpack-dev-middleware": "7.4.2",

packages/components/credentials/CometApi.credential.ts

@@ -0,0 +1,23 @@
+import { INodeCredential, INodeParams } from '../src/Interface'
+
+class CometApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Comet API'
+        this.name = 'cometApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'Comet API Key',
+                name: 'cometApiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: CometApi }

packages/components/credentials/ElevenLabsApi.credential.ts

@@ -0,0 +1,26 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class ElevenLabsApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    description: string
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Eleven Labs API'
+        this.name = 'elevenLabsApi'
+        this.version = 1.0
+        this.description =
+            'Sign up for a Eleven Labs account and <a target="_blank" href="https://elevenlabs.io/app/settings/api-keys">create an API Key</a>.'
+        this.inputs = [
+            {
+                label: 'Eleven Labs API Key',
+                name: 'elevenLabsApiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: ElevenLabsApi }

packages/components/credentials/SambanovaApi.credential.ts

@@ -0,0 +1,23 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class SambanovaApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Sambanova API'
+        this.name = 'sambanovaApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'Sambanova Api Key',
+                name: 'sambanovaApiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: SambanovaApi }

packages/components/credentials/TeradataBearerToken.credential.ts

@@ -0,0 +1,26 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class TeradataBearerTokenCredential implements INodeCredential {
+    label: string
+    name: string
+    description: string
+    version: number
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Teradata Bearer Token'
+        this.name = 'teradataBearerToken'
+        this.version = 1.0
+        this.description =
+            'Refer to <a target="_blank" href="https://docs.teradata.com/r/Enterprise_IntelliFlex_VMware/Teradata-Vector-Store-User-Guide/Setting-up-Vector-Store/Importing-Modules-Required-for-Vector-Store">official guide</a> on how to get Teradata Bearer Token'
+        this.inputs = [
+            {
+                label: 'Token',
+                name: 'token',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: TeradataBearerTokenCredential }

packages/components/credentials/TeradataTD2.credential.ts

@@ -0,0 +1,28 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class TeradataTD2Credential implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Teradata TD2 Auth'
+        this.name = 'teradataTD2Auth'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'Teradata TD2 Auth Username',
+                name: 'tdUsername',
+                type: 'string'
+            },
+            {
+                label: 'Teradata TD2 Auth Password',
+                name: 'tdPassword',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: TeradataTD2Credential }

packages/components/credentials/TeradataVectorStoreApi.credential.ts

@@ -0,0 +1,47 @@
+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class TeradataVectorStoreApiCredentials implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Teradata Vector Store API Credentials'
+        this.name = 'teradataVectorStoreApiCredentials'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'Teradata Host IP',
+                name: 'tdHostIp',
+                type: 'string'
+            },
+            {
+                label: 'Username',
+                name: 'tdUsername',
+                type: 'string'
+            },
+            {
+                label: 'Password',
+                name: 'tdPassword',
+                type: 'password'
+            },
+            {
+                label: 'Vector_Store_Base_URL',
+                name: 'baseURL',
+                description: 'Teradata Vector Store Base URL',
+                placeholder: `Base_URL`,
+                type: 'string'
+            },
+            {
+                label: 'JWT Token',
+                name: 'jwtToken',
+                type: 'password',
+                description: 'Bearer token for JWT authentication',
+                optional: true
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: TeradataVectorStoreApiCredentials }

packages/components/jest.config.js

@@ -0,0 +1,15 @@
+module.exports = {
+    preset: 'ts-jest',
+    testEnvironment: 'node',
+    roots: ['<rootDir>/nodes'],
+    transform: {
+        '^.+\\.tsx?$': 'ts-jest'
+    },
+    testRegex: '(/__tests__/.*|(\\.|/)(test|spec))\\.tsx?$',
+    moduleFileExtensions: ['ts', 'tsx', 'js', 'jsx', 'json', 'node'],
+    verbose: true,
+    testPathIgnorePatterns: ['/node_modules/', '/dist/'],
+    moduleNameMapper: {
+        '^../../../src/(.*)$': '<rootDir>/src/$1'
+    }
+}

packages/components/models.json

@@ -3,6 +3,48 @@
         {
             "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",
+                    "description": "Claude 4.5 Sonnet",
+                    "input_cost": 0.000003,
+                    "output_cost": 0.000015
+                },
+                {
+                    "label": "anthropic.claude-haiku-4-5-20251001-v1:0",
+                    "name": "anthropic.claude-haiku-4-5-20251001-v1:0",
+                    "description": "Claude 4.5 Haiku",
+                    "input_cost": 0.000001,
+                    "output_cost": 0.000005
+                },
+                {
+                    "label": "openai.gpt-oss-20b-1:0",
+                    "name": "openai.gpt-oss-20b-1:0",
+                    "description": "21B parameters model optimized for lower latency, local, and specialized use cases",
+                    "input_cost": 0.00007,
+                    "output_cost": 0.0003
+                },
+                {
+                    "label": "openai.gpt-oss-120b-1:0",
+                    "name": "openai.gpt-oss-120b-1:0",
+                    "description": "120B parameters model optimized for production, general purpose, and high-reasoning use cases",
+                    "input_cost": 0.00015,
+                    "output_cost": 0.0006
+                },
+                {
+                    "label": "anthropic.claude-opus-4-1-20250805-v1:0",
+                    "name": "anthropic.claude-opus-4-1-20250805-v1:0",
+                    "description": "Claude 4.1 Opus",
+                    "input_cost": 0.000015,
+                    "output_cost": 0.000075
+                },
                 {
                     "label": "anthropic.claude-sonnet-4-20250514-v1:0",
                     "name": "anthropic.claude-sonnet-4-20250514-v1:0",
@@ -280,6 +322,30 @@
         {
             "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",
+                    "input_cost": 0.00000125,
+                    "output_cost": 0.00001
+                },
+                {
+                    "label": "gpt-5-mini",
+                    "name": "gpt-5-mini",
+                    "input_cost": 0.00000025,
+                    "output_cost": 0.000002
+                },
+                {
+                    "label": "gpt-5-nano",
+                    "name": "gpt-5-nano",
+                    "input_cost": 0.00000005,
+                    "output_cost": 0.0000004
+                },
                 {
                     "label": "gpt-4.1",
                     "name": "gpt-4.1",
@@ -357,6 +423,18 @@
                     "name": "gpt-4.5-preview",
                     "input_cost": 0.000075,
                     "output_cost": 0.00015
+                },
+                {
+                    "label": "gpt-4.1-mini",
+                    "name": "gpt-4.1-mini",
+                    "input_cost": 0.0000004,
+                    "output_cost": 0.0000016
+                },
+                {
+                    "label": "gpt-5-chat-latest",
+                    "name": "gpt-5-chat-latest",
+                    "input_cost": 0.00000125,
+                    "output_cost": 0.00001
                 }
             ]
         },
@@ -416,12 +494,45 @@
                     "name": "gpt-4-1106-preview",
                     "input_cost": 0.00001,
                     "output_cost": 0.00003
+                },
+                {
+                    "label": "gpt-4.1-mini",
+                    "name": "gpt-4.1-mini",
+                    "input_cost": 0.0000004,
+                    "output_cost": 0.0000016
+                },
+                {
+                    "label": "gpt-5-chat-latest",
+                    "name": "gpt-5-chat-latest",
+                    "input_cost": 0.00000125,
+                    "output_cost": 0.00001
                 }
             ]
         },
         {
             "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",
+                    "description": "Claude 4.5 Sonnet",
+                    "input_cost": 0.000003,
+                    "output_cost": 0.000015
+                },
+                {
+                    "label": "claude-haiku-4-5",
+                    "name": "claude-haiku-4-5",
+                    "description": "Claude 4.5 Haiku",
+                    "input_cost": 0.000001,
+                    "output_cost": 0.000005
+                },
                 {
                     "label": "claude-sonnet-4-0",
                     "name": "claude-sonnet-4-0",
@@ -429,6 +540,13 @@
                     "input_cost": 0.000003,
                     "output_cost": 0.000015
                 },
+                {
+                    "label": "claude-opus-4-1",
+                    "name": "claude-opus-4-1",
+                    "description": "Claude 4.1 Opus",
+                    "input_cost": 0.000015,
+                    "output_cost": 0.000075
+                },
                 {
                     "label": "claude-opus-4-0",
                     "name": "claude-opus-4-0",
@@ -524,17 +642,41 @@
             "name": "chatGoogleGenerativeAI",
             "models": [
                 {
-                    "label": "gemini-2.5-flash-preview-05-20",
-                    "name": "gemini-2.5-flash-preview-05-20",
-                    "input_cost": 0.15e-6,
-                    "output_cost": 6e-7
+                    "label": "gemini-3-pro-preview",
+                    "name": "gemini-3-pro-preview",
+                    "input_cost": 0.00002,
+                    "output_cost": 0.00012
                 },
                 {
-                    "label": "gemini-2.5-pro-preview-03-25",
-                    "name": "gemini-2.5-pro-preview-03-25",
+                    "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",
+                    "input_cost": 0.3e-6,
+                    "output_cost": 0.000025
+                },
+                {
+                    "label": "gemini-2.5-flash",
+                    "name": "gemini-2.5-flash",
                     "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",
+                    "input_cost": 1e-7,
+                    "output_cost": 4e-7
+                },
                 {
                     "label": "gemini-2.0-flash",
                     "name": "gemini-2.0-flash",
@@ -582,17 +724,29 @@
             "name": "chatGoogleVertexAI",
             "models": [
                 {
-                    "label": "gemini-2.5-flash",
-                    "name": "gemini-2.5-flash",
-                    "input_cost": 0.15e-6,
-                    "output_cost": 6e-7
+                    "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",
+                    "input_cost": 0.3e-6,
+                    "output_cost": 0.000025
+                },
+                {
+                    "label": "gemini-2.5-flash",
+                    "name": "gemini-2.5-flash",
                     "input_cost": 1.25e-6,
                     "output_cost": 0.00001
                 },
+                {
+                    "label": "gemini-2.5-flash-lite",
+                    "name": "gemini-2.5-flash-lite",
+                    "input_cost": 1e-7,
+                    "output_cost": 4e-7
+                },
                 {
                     "label": "gemini-2.0-flash",
                     "name": "gemini-2.0-flash-001",
@@ -641,6 +795,34 @@
                     "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",
+                    "description": "Claude 4.5 Sonnet",
+                    "input_cost": 0.000003,
+                    "output_cost": 0.000015
+                },
+                {
+                    "label": "claude-haiku-4-5@20251001",
+                    "name": "claude-haiku-4-5@20251001",
+                    "description": "Claude 4.5 Haiku",
+                    "input_cost": 0.000001,
+                    "output_cost": 0.000005
+                },
+                {
+                    "label": "claude-opus-4-1@20250805",
+                    "name": "claude-opus-4-1@20250805",
+                    "description": "Claude 4.1 Opus",
+                    "input_cost": 0.000015,
+                    "output_cost": 0.000075
+                },
                 {
                     "label": "claude-sonnet-4@20250514",
                     "name": "claude-sonnet-4@20250514",
@@ -746,6 +928,14 @@
         {
             "name": "groqChat",
             "models": [
+                {
+                    "label": "openai/gpt-oss-20b",
+                    "name": "openai/gpt-oss-20b"
+                },
+                {
+                    "label": "openai/gpt-oss-120b",
+                    "name": "openai/gpt-oss-120b"
+                },
                 {
                     "label": "meta-llama/llama-4-maverick-17b-128e-instruct",
                     "name": "meta-llama/llama-4-maverick-17b-128e-instruct"
@@ -857,6 +1047,30 @@
         {
             "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",
+                    "input_cost": 0.00000125,
+                    "output_cost": 0.00001
+                },
+                {
+                    "label": "gpt-5-mini",
+                    "name": "gpt-5-mini",
+                    "input_cost": 0.00000025,
+                    "output_cost": 0.000002
+                },
+                {
+                    "label": "gpt-5-nano",
+                    "name": "gpt-5-nano",
+                    "input_cost": 0.00000005,
+                    "output_cost": 0.0000004
+                },
                 {
                     "label": "gpt-4.1",
                     "name": "gpt-4.1",
@@ -1591,6 +1805,18 @@
                     "name": "gpt-4-32k",
                     "input_cost": 0.00006,
                     "output_cost": 0.00012
+                },
+                {
+                    "label": "gpt-4.1-mini",
+                    "name": "gpt-4.1-mini",
+                    "input_cost": 0.0000004,
+                    "output_cost": 0.0000016
+                },
+                {
+                    "label": "gpt-5-chat-latest",
+                    "name": "gpt-5-chat-latest",
+                    "input_cost": 0.00000125,
+                    "output_cost": 0.00001
                 }
             ]
         },

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

@@ -8,7 +8,7 @@ import {
     INodeParams,
     IServerSideEventStreamer
 } from '../../../src/Interface'
-import { getVars, executeJavaScriptCode, createCodeExecutionSandbox } from '../../../src/utils'
+import { getVars, executeJavaScriptCode, createCodeExecutionSandbox, processTemplateVariables } from '../../../src/utils'
 import { updateFlowState } from '../utils'
 
 interface ICustomFunctionInputVariables {
@@ -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
@@ -145,19 +144,19 @@ class CustomFunction_Agentflow implements INode {
         const appDataSource = options.appDataSource as DataSource
         const databaseEntities = options.databaseEntities as IDatabaseEntity
 
-        // Update flow state if needed
-        let newState = { ...state }
-        if (_customFunctionUpdateState && Array.isArray(_customFunctionUpdateState) && _customFunctionUpdateState.length > 0) {
-            newState = updateFlowState(state, _customFunctionUpdateState)
-        }
-
         const variables = await getVars(appDataSource, databaseEntities, nodeData, options)
         const flow = {
+            input,
+            state,
             chatflowId: options.chatflowid,
             sessionId: options.sessionId,
             chatId: options.chatId,
-            input,
-            state: newState
+            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
@@ -181,8 +180,7 @@ class CustomFunction_Agentflow implements INode {
         try {
             const response = await executeJavaScriptCode(javascriptFunction, sandbox, {
                 libraries: ['axios'],
-                streamOutput,
-                timeout: 10000
+                streamOutput
             })
 
             let finalOutput = response
@@ -190,15 +188,14 @@ class CustomFunction_Agentflow implements INode {
                 finalOutput = JSON.stringify(response, null, 2)
             }
 
-            // Process template variables in state
-            if (newState && Object.keys(newState).length > 0) {
-                for (const key in newState) {
-                    if (newState[key].toString().includes('{{ output }}')) {
-                        newState[key] = finalOutput
-                    }
-                }
+            // Update flow state if needed
+            let newState = { ...state }
+            if (_customFunctionUpdateState && Array.isArray(_customFunctionUpdateState) && _customFunctionUpdateState.length > 0) {
+                newState = updateFlowState(state, _customFunctionUpdateState)
             }
 
+            newState = processTemplateVariables(newState, finalOutput)
+
             const returnOutput = {
                 id: nodeData.id,
                 name: this.name,

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

@@ -8,7 +8,7 @@ import {
     IServerSideEventStreamer
 } from '../../../src/Interface'
 import axios, { AxiosRequestConfig } from 'axios'
-import { getCredentialData, getCredentialParam } from '../../../src/utils'
+import { getCredentialData, getCredentialParam, processTemplateVariables, parseJsonBody } from '../../../src/utils'
 import { DataSource } from 'typeorm'
 import { BaseMessageLike } from '@langchain/core/messages'
 import { updateFlowState } from '../utils'
@@ -30,7 +30,7 @@ class ExecuteFlow_Agentflow implements INode {
     constructor() {
         this.label = 'Execute Flow'
         this.name = 'executeFlowAgentflow'
-        this.version = 1.0
+        this.version = 1.2
         this.type = 'ExecuteFlow'
         this.category = 'Agent Flows'
         this.description = 'Execute another flow'
@@ -62,7 +62,8 @@ class ExecuteFlow_Agentflow implements INode {
                 name: 'executeFlowOverrideConfig',
                 description: 'Override the config passed to the flow',
                 type: 'json',
-                optional: true
+                optional: true,
+                acceptVariable: true
             },
             {
                 label: 'Base URL',
@@ -101,8 +102,7 @@ class ExecuteFlow_Agentflow implements INode {
                         label: 'Key',
                         name: 'key',
                         type: 'asyncOptions',
-                        loadMethod: 'listRuntimeStateKeys',
-                        freeSolo: true
+                        loadMethod: 'listRuntimeStateKeys'
                     },
                     {
                         label: 'Value',
@@ -162,12 +162,15 @@ class ExecuteFlow_Agentflow implements INode {
         const flowInput = nodeData.inputs?.executeFlowInput as string
         const returnResponseAs = nodeData.inputs?.executeFlowReturnResponseAs as string
         const _executeFlowUpdateState = nodeData.inputs?.executeFlowUpdateState
-        const overrideConfig =
-            typeof nodeData.inputs?.executeFlowOverrideConfig === 'string' &&
-            nodeData.inputs.executeFlowOverrideConfig.startsWith('{') &&
-            nodeData.inputs.executeFlowOverrideConfig.endsWith('}')
-                ? JSON.parse(nodeData.inputs.executeFlowOverrideConfig)
-                : nodeData.inputs?.executeFlowOverrideConfig
+
+        let overrideConfig = nodeData.inputs?.executeFlowOverrideConfig
+        if (typeof overrideConfig === 'string' && overrideConfig.startsWith('{') && overrideConfig.endsWith('}')) {
+            try {
+                overrideConfig = parseJsonBody(overrideConfig)
+            } catch (parseError) {
+                throw new Error(`Invalid JSON in executeFlowOverrideConfig: ${parseError.message}`)
+            }
+        }
 
         const state = options.agentflowRuntime?.state as ICommonObject
         const runtimeChatHistory = (options.agentflowRuntime?.chatHistory as BaseMessageLike[]) ?? []
@@ -216,13 +219,7 @@ class ExecuteFlow_Agentflow implements INode {
             }
 
             // Process template variables in state
-            if (newState && Object.keys(newState).length > 0) {
-                for (const key in newState) {
-                    if (newState[key].toString().includes('{{ output }}')) {
-                        newState[key] = resultText
-                    }
-                }
-            }
+            newState = processTemplateVariables(newState, resultText)
 
             // Only add to runtime chat history if this is the first node
             const inputMessages = []

packages/components/nodes/agentflow/HTTP/HTTP.ts

@@ -1,8 +1,9 @@
 import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
-import axios, { AxiosRequestConfig, Method, ResponseType } from 'axios'
+import { AxiosRequestConfig, Method, ResponseType } from 'axios'
 import FormData from 'form-data'
 import * as querystring from 'querystring'
-import { getCredentialData, getCredentialParam } from '../../../src/utils'
+import { getCredentialData, getCredentialParam, parseJsonBody } from '../../../src/utils'
+import { secureAxiosRequest } from '../../../src/httpSecurity'
 
 class HTTP_Agentflow implements INode {
     label: string
@@ -18,37 +19,6 @@ class HTTP_Agentflow implements INode {
     credential: INodeParams
     inputs: INodeParams[]
 
-    private sanitizeJsonString(jsonString: string): string {
-        // Remove common problematic escape sequences that are not valid JSON
-        let sanitized = jsonString
-            // Remove escaped square brackets (not valid JSON)
-            .replace(/\\(\[|\])/g, '$1')
-            // Fix unquoted string values in JSON (simple case)
-            .replace(/:\s*([a-zA-Z][a-zA-Z0-9]*)\s*([,}])/g, ': "$1"$2')
-            // Fix trailing commas
-            .replace(/,(\s*[}\]])/g, '$1')
-
-        return sanitized
-    }
-
-    private parseJsonBody(body: string): any {
-        try {
-            // First try to parse as-is
-            return JSON.parse(body)
-        } catch (error) {
-            try {
-                // If that fails, try to sanitize and parse
-                const sanitized = this.sanitizeJsonString(body)
-                return JSON.parse(sanitized)
-            } catch (sanitizeError) {
-                // If sanitization also fails, throw the original error with helpful message
-                throw new Error(
-                    `Invalid JSON format in body. Original error: ${error.message}. Please ensure your JSON is properly formatted with quoted strings and valid escape sequences.`
-                )
-            }
-        }
-    }
-
     constructor() {
         this.label = 'HTTP'
         this.name = 'httpAgentflow'
@@ -97,7 +67,8 @@ class HTTP_Agentflow implements INode {
             {
                 label: 'URL',
                 name: 'url',
-                type: 'string'
+                type: 'string',
+                acceptVariable: true
             },
             {
                 label: 'Headers',
@@ -304,7 +275,7 @@ class HTTP_Agentflow implements INode {
             if (method !== 'GET' && body) {
                 switch (bodyType) {
                     case 'json': {
-                        requestConfig.data = typeof body === 'string' ? this.parseJsonBody(body) : body
+                        requestConfig.data = typeof body === 'string' ? parseJsonBody(body) : body
                         requestHeaders['Content-Type'] = 'application/json'
                         break
                     }
@@ -322,14 +293,14 @@ class HTTP_Agentflow implements INode {
                         break
                     }
                     case 'xWwwFormUrlencoded':
-                        requestConfig.data = querystring.stringify(typeof body === 'string' ? this.parseJsonBody(body) : body)
+                        requestConfig.data = querystring.stringify(typeof body === 'string' ? parseJsonBody(body) : body)
                         requestHeaders['Content-Type'] = 'application/x-www-form-urlencoded'
                         break
                 }
             }
 
-            // Make the HTTP request
-            const response = await axios(requestConfig)
+            // Make the secure HTTP request that validates all URLs in redirect chains
+            const response = await secureAxiosRequest(requestConfig)
 
             // Process response based on response type
             let responseData

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

@@ -208,7 +208,7 @@ class HumanInput_Agentflow implements INode {
                 humanInputDescription = (nodeData.inputs?.humanInputDescription as string) || 'Do you want to proceed?'
                 const messages = [...pastChatHistory, ...runtimeChatHistory]
                 // Find the last message in the messages array
-                const lastMessage = (messages[messages.length - 1] as any).content || ''
+                const lastMessage = messages.length > 0 ? (messages[messages.length - 1] as any).content || '' : ''
                 humanInputDescription = `${lastMessage}\n\n${humanInputDescription}`
                 if (isStreamable) {
                     const sseStreamer: IServerSideEventStreamer = options.sseStreamer as IServerSideEventStreamer
@@ -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/Iteration/Iteration.ts

@@ -1,4 +1,5 @@
 import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { parseJsonBody } from '../../../src/utils'
 
 class Iteration_Agentflow implements INode {
     label: string
@@ -39,12 +40,17 @@ class Iteration_Agentflow implements INode {
         const iterationInput = nodeData.inputs?.iterationInput
 
         // Helper function to clean JSON strings with redundant backslashes
-        const cleanJsonString = (str: string): string => {
-            return str.replace(/\\(["'[\]{}])/g, '$1')
+        const safeParseJson = (str: string): string => {
+            try {
+                return parseJsonBody(str)
+            } catch {
+                // Try parsing after cleaning
+                return parseJsonBody(str.replace(/\\(["'[\]{}])/g, '$1'))
+            }
         }
 
         const iterationInputArray =
-            typeof iterationInput === 'string' && iterationInput !== '' ? JSON.parse(cleanJsonString(iterationInput)) : iterationInput
+            typeof iterationInput === 'string' && iterationInput !== '' ? safeParseJson(iterationInput) : iterationInput
 
         if (!iterationInputArray || !Array.isArray(iterationInputArray)) {
             throw new Error('Invalid input array')

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

@@ -2,17 +2,20 @@ 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 { get } from 'lodash'
+import { processTemplateVariables, configureStructuredOutput } from '../../../src/utils'
+import { flatten } from 'lodash'
 
 class LLM_Agentflow implements INode {
     label: string
@@ -31,7 +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'
@@ -287,8 +290,7 @@ class LLM_Agentflow implements INode {
                         label: 'Key',
                         name: 'key',
                         type: 'asyncOptions',
-                        loadMethod: 'listRuntimeStateKeys',
-                        freeSolo: true
+                        loadMethod: 'listRuntimeStateKeys'
                     },
                     {
                         label: 'Value',
@@ -399,7 +401,11 @@ class LLM_Agentflow implements INode {
                 const role = msg.role
                 const content = msg.content
                 if (role && content) {
-                    messages.push({ role, content })
+                    if (role === 'system') {
+                        messages.unshift({ role, content })
+                    } else {
+                        messages.push({ role, content })
+                    }
                 }
             }
 
@@ -444,10 +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
@@ -463,9 +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 {
@@ -474,11 +488,15 @@ class LLM_Agentflow implements INode {
                 // Stream whole response back to UI if this is the last node
                 if (isLastNode && options.sseStreamer) {
                     const sseStreamer: IServerSideEventStreamer = options.sseStreamer as IServerSideEventStreamer
-                    let responseContent = JSON.stringify(response, null, 2)
-                    if (typeof response.content === 'string') {
-                        responseContent = response.content
+                    let finalResponse = ''
+                    if (response.content && Array.isArray(response.content)) {
+                        finalResponse = response.content.map((item: any) => item.text).join('\n')
+                    } else if (response.content && typeof response.content === 'string') {
+                        finalResponse = response.content
+                    } else {
+                        finalResponse = JSON.stringify(response, null, 2)
                     }
-                    sseStreamer.streamTokenEvent(chatId, responseContent)
+                    sseStreamer.streamTokenEvent(chatId, finalResponse)
                 }
             }
 
@@ -486,6 +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) {
@@ -505,10 +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) {
@@ -520,41 +584,23 @@ class LLM_Agentflow implements INode {
                 this.sendStreamingEvents(options, chatId, response)
             }
 
-            // Process template variables in state
-            if (newState && Object.keys(newState).length > 0) {
-                for (const key in newState) {
-                    const stateValue = newState[key].toString()
-                    if (stateValue.includes('{{ output')) {
-                        // Handle simple output replacement
-                        if (stateValue === '{{ output }}') {
-                            newState[key] = finalResponse
-                            continue
-                        }
-
-                        // Handle JSON path expressions like {{ output.item1 }}
-                        // eslint-disable-next-line
-                        const match = stateValue.match(/{{[\s]*output\.([\w\.]+)[\s]*}}/)
-                        if (match) {
-                            try {
-                                // Parse the response if it's JSON
-                                const jsonResponse = typeof finalResponse === 'string' ? JSON.parse(finalResponse) : finalResponse
-                                // Get the value using lodash get
-                                const path = match[1]
-                                const value = get(jsonResponse, path)
-                                newState[key] = value ?? stateValue // Fall back to original if path not found
-                            } catch (e) {
-                                // If JSON parsing fails, keep original template
-                                console.warn(`Failed to parse JSON or find path in output: ${e}`)
-                                newState[key] = stateValue
-                            }
-                        }
-                    }
-                }
+            // 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
             )
@@ -605,7 +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 })
+                            }
+                        })
                     }
                 ]
             }
@@ -775,59 +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
      */
@@ -844,16 +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)
@@ -875,7 +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,
@@ -894,15 +899,27 @@ 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) {
-                if (structuredOutput[key]) {
+                if (structuredOutput[key] !== undefined && structuredOutput[key] !== null) {
                     output[key] = structuredOutput[key]
                 }
             }
         }
 
+        if (artifacts && artifacts.length > 0) {
+            output.artifacts = flatten(artifacts)
+        }
+
+        if (fileAnnotations && fileAnnotations.length > 0) {
+            output.fileAnnotations = fileAnnotations
+        }
+
         return output
     }
 
@@ -913,7 +930,12 @@ class LLM_Agentflow implements INode {
         const sseStreamer: IServerSideEventStreamer = options.sseStreamer as IServerSideEventStreamer
 
         if (response.tool_calls) {
-            sseStreamer.streamCalledToolsEvent(chatId, response.tool_calls)
+            const formattedToolCalls = response.tool_calls.map((toolCall: any) => ({
+                tool: toolCall.name || 'tool',
+                toolInput: toolCall.args,
+                toolOutput: ''
+            }))
+            sseStreamer.streamCalledToolsEvent(chatId, flatten(formattedToolCalls))
         }
 
         if (response.usage_metadata) {
@@ -922,107 +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

@@ -1,4 +1,5 @@
 import { ICommonObject, INode, INodeData, INodeOptionsValue, INodeParams } from '../../../src/Interface'
+import { updateFlowState } from '../utils'
 
 class Loop_Agentflow implements INode {
     label: string
@@ -19,7 +20,7 @@ class Loop_Agentflow implements INode {
     constructor() {
         this.label = 'Loop'
         this.name = 'loopAgentflow'
-        this.version = 1.0
+        this.version = 1.2
         this.type = 'Loop'
         this.category = 'Agent Flows'
         this.description = 'Loop back to a previous node'
@@ -40,6 +41,39 @@ class Loop_Agentflow implements INode {
                 name: 'maxLoopCount',
                 type: 'number',
                 default: 5
+            },
+            {
+                label: 'Fallback Message',
+                name: 'fallbackMessage',
+                type: 'string',
+                description: 'Message to display if the loop count is exceeded',
+                placeholder: 'Enter your fallback message here',
+                rows: 4,
+                acceptVariable: true,
+                optional: true
+            },
+            {
+                label: 'Update Flow State',
+                name: 'loopUpdateState',
+                description: 'Update runtime state during the execution of the workflow',
+                type: 'array',
+                optional: true,
+                acceptVariable: true,
+                array: [
+                    {
+                        label: 'Key',
+                        name: 'key',
+                        type: 'asyncOptions',
+                        loadMethod: 'listRuntimeStateKeys'
+                    },
+                    {
+                        label: 'Value',
+                        name: 'value',
+                        type: 'string',
+                        acceptVariable: true,
+                        acceptNodeOutputAsVariable: true
+                    }
+                ]
             }
         ]
     }
@@ -58,12 +92,20 @@ class Loop_Agentflow implements INode {
                 })
             }
             return returnOptions
+        },
+        async listRuntimeStateKeys(_: INodeData, options: ICommonObject): Promise<INodeOptionsValue[]> {
+            const previousNodes = options.previousNodes as ICommonObject[]
+            const startAgentflowNode = previousNodes.find((node) => node.name === 'startAgentflow')
+            const state = startAgentflowNode?.inputs?.startState as ICommonObject[]
+            return state.map((item) => ({ label: item.key, name: item.key }))
         }
     }
 
     async run(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
         const loopBackToNode = nodeData.inputs?.loopBackToNode as string
         const _maxLoopCount = nodeData.inputs?.maxLoopCount as string
+        const fallbackMessage = nodeData.inputs?.fallbackMessage as string
+        const _loopUpdateState = nodeData.inputs?.loopUpdateState
 
         const state = options.agentflowRuntime?.state as ICommonObject
 
@@ -75,16 +117,34 @@ class Loop_Agentflow implements INode {
             maxLoopCount: _maxLoopCount ? parseInt(_maxLoopCount) : 5
         }
 
+        const finalOutput = 'Loop back to ' + `${loopBackToNodeLabel} (${loopBackToNodeId})`
+
+        // Update flow state if needed
+        let newState = { ...state }
+        if (_loopUpdateState && Array.isArray(_loopUpdateState) && _loopUpdateState.length > 0) {
+            newState = updateFlowState(state, _loopUpdateState)
+        }
+
+        // Process template variables in state
+        if (newState && Object.keys(newState).length > 0) {
+            for (const key in newState) {
+                if (newState[key].toString().includes('{{ output }}')) {
+                    newState[key] = finalOutput
+                }
+            }
+        }
+
         const returnOutput = {
             id: nodeData.id,
             name: this.name,
             input: data,
             output: {
-                content: 'Loop back to ' + `${loopBackToNodeLabel} (${loopBackToNodeId})`,
+                content: finalOutput,
                 nodeID: loopBackToNodeId,
-                maxLoopCount: _maxLoopCount ? parseInt(_maxLoopCount) : 5
+                maxLoopCount: _maxLoopCount ? parseInt(_maxLoopCount) : 5,
+                fallbackMessage
             },
-            state
+            state: newState
         }
 
         return returnOutput

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

@@ -8,6 +8,7 @@ import {
     IServerSideEventStreamer
 } from '../../../src/Interface'
 import { updateFlowState } from '../utils'
+import { processTemplateVariables } from '../../../src/utils'
 import { DataSource } from 'typeorm'
 import { BaseRetriever } from '@langchain/core/retrievers'
 import { Document } from '@langchain/core/documents'
@@ -35,7 +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'
@@ -86,8 +87,7 @@ class Retriever_Agentflow implements INode {
                         label: 'Key',
                         name: 'key',
                         type: 'asyncOptions',
-                        loadMethod: 'listRuntimeStateKeys',
-                        freeSolo: true
+                        loadMethod: 'listRuntimeStateKeys'
                     },
                     {
                         label: 'Value',
@@ -197,14 +197,7 @@ class Retriever_Agentflow implements INode {
                 sseStreamer.streamTokenEvent(chatId, finalOutput)
             }
 
-            // Process template variables in state
-            if (newState && Object.keys(newState).length > 0) {
-                for (const key in newState) {
-                    if (newState[key].toString().includes('{{ output }}')) {
-                        newState[key] = finalOutput
-                    }
-                }
-            }
+            newState = processTemplateVariables(newState, finalOutput)
 
             const returnOutput = {
                 id: nodeData.id,

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

@@ -1,5 +1,6 @@
 import { ICommonObject, INode, INodeData, INodeOptionsValue, INodeParams, IServerSideEventStreamer } from '../../../src/Interface'
 import { updateFlowState } from '../utils'
+import { processTemplateVariables } from '../../../src/utils'
 import { Tool } from '@langchain/core/tools'
 import { ARTIFACTS_PREFIX, TOOL_ARGS_PREFIX } from '../../../src/agents'
 import zodToJsonSchema from 'zod-to-json-schema'
@@ -28,7 +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'
@@ -79,8 +80,7 @@ class Tool_Agentflow implements INode {
                         label: 'Key',
                         name: 'key',
                         type: 'asyncOptions',
-                        loadMethod: 'listRuntimeStateKeys',
-                        freeSolo: true
+                        loadMethod: 'listRuntimeStateKeys'
                     },
                     {
                         label: 'Value',
@@ -274,6 +274,7 @@ class Tool_Agentflow implements INode {
         }
 
         const flowConfig = {
+            chatflowId: options.chatflowid,
             sessionId: options.sessionId,
             chatId: options.chatId,
             input: input,
@@ -329,14 +330,7 @@ class Tool_Agentflow implements INode {
                 sseStreamer.streamTokenEvent(chatId, toolOutput)
             }
 
-            // Process template variables in state
-            if (newState && Object.keys(newState).length > 0) {
-                for (const key in newState) {
-                    if (newState[key].toString().includes('{{ output }}')) {
-                        newState[key] = toolOutput
-                    }
-                }
-            }
+            newState = processTemplateVariables(newState, toolOutput)
 
             const returnOutput = {
                 id: nodeData.id,

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')
@@ -313,13 +316,17 @@ export const getPastChatHistoryImageMessages = async (
         if (message.additional_kwargs && message.additional_kwargs.fileUploads) {
             // example: [{"type":"stored-file","name":"0_DiXc4ZklSTo3M8J4.jpg","mime":"image/jpeg"}]
             const fileUploads = message.additional_kwargs.fileUploads
+            const artifacts = message.additional_kwargs.artifacts
+            const fileAnnotations = message.additional_kwargs.fileAnnotations
+            const usedTools = message.additional_kwargs.usedTools
             try {
                 let messageWithFileUploads = ''
                 const uploads: IFileUpload[] = typeof fileUploads === 'string' ? JSON.parse(fileUploads) : fileUploads
                 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')
 
@@ -358,22 +365,83 @@ export const getPastChatHistoryImageMessages = async (
                     }
                 }
                 const messageContent = messageWithFileUploads ? `${messageWithFileUploads}\n\n${message.content}` : message.content
+                const hasArtifacts = artifacts && Array.isArray(artifacts) && artifacts.length > 0
+                const hasFileAnnotations = fileAnnotations && Array.isArray(fileAnnotations) && fileAnnotations.length > 0
+                const hasUsedTools = usedTools && Array.isArray(usedTools) && usedTools.length > 0
+
                 if (imageContents.length > 0) {
-                    chatHistory.push({
+                    const imageMessage: any = {
                         role: messageRole,
                         content: imageContents
-                    })
+                    }
+                    if (hasArtifacts || hasFileAnnotations || hasUsedTools) {
+                        imageMessage.additional_kwargs = {}
+                        if (hasArtifacts) imageMessage.additional_kwargs.artifacts = artifacts
+                        if (hasFileAnnotations) imageMessage.additional_kwargs.fileAnnotations = fileAnnotations
+                        if (hasUsedTools) imageMessage.additional_kwargs.usedTools = usedTools
+                    }
+                    chatHistory.push(imageMessage)
                     transformedPastMessages.push({
                         role: messageRole,
                         content: [...JSON.parse((pastChatHistory[i] as any).additional_kwargs.fileUploads)]
                     })
                 }
-                chatHistory.push({
+
+                const contentMessage: any = {
                     role: messageRole,
                     content: messageContent
-                })
+                }
+                if (hasArtifacts || hasFileAnnotations || hasUsedTools) {
+                    contentMessage.additional_kwargs = {}
+                    if (hasArtifacts) contentMessage.additional_kwargs.artifacts = artifacts
+                    if (hasFileAnnotations) contentMessage.additional_kwargs.fileAnnotations = fileAnnotations
+                    if (hasUsedTools) contentMessage.additional_kwargs.usedTools = usedTools
+                }
+                chatHistory.push(contentMessage)
             } catch (e) {
                 // failed to parse fileUploads, continue with text only
+                const hasArtifacts = artifacts && Array.isArray(artifacts) && artifacts.length > 0
+                const hasFileAnnotations = fileAnnotations && Array.isArray(fileAnnotations) && fileAnnotations.length > 0
+                const hasUsedTools = usedTools && Array.isArray(usedTools) && usedTools.length > 0
+
+                const errorMessage: any = {
+                    role: messageRole,
+                    content: message.content
+                }
+                if (hasArtifacts || hasFileAnnotations || hasUsedTools) {
+                    errorMessage.additional_kwargs = {}
+                    if (hasArtifacts) errorMessage.additional_kwargs.artifacts = artifacts
+                    if (hasFileAnnotations) errorMessage.additional_kwargs.fileAnnotations = fileAnnotations
+                    if (hasUsedTools) errorMessage.additional_kwargs.usedTools = usedTools
+                }
+                chatHistory.push(errorMessage)
+            }
+        } else if (message.additional_kwargs) {
+            const hasArtifacts =
+                message.additional_kwargs.artifacts &&
+                Array.isArray(message.additional_kwargs.artifacts) &&
+                message.additional_kwargs.artifacts.length > 0
+            const hasFileAnnotations =
+                message.additional_kwargs.fileAnnotations &&
+                Array.isArray(message.additional_kwargs.fileAnnotations) &&
+                message.additional_kwargs.fileAnnotations.length > 0
+            const hasUsedTools =
+                message.additional_kwargs.usedTools &&
+                Array.isArray(message.additional_kwargs.usedTools) &&
+                message.additional_kwargs.usedTools.length > 0
+
+            if (hasArtifacts || hasFileAnnotations || hasUsedTools) {
+                const messageAdditionalKwargs: any = {}
+                if (hasArtifacts) messageAdditionalKwargs.artifacts = message.additional_kwargs.artifacts
+                if (hasFileAnnotations) messageAdditionalKwargs.fileAnnotations = message.additional_kwargs.fileAnnotations
+                if (hasUsedTools) messageAdditionalKwargs.usedTools = message.additional_kwargs.usedTools
+
+                chatHistory.push({
+                    role: messageRole,
+                    content: message.content,
+                    additional_kwargs: messageAdditionalKwargs
+                })
+            } else {
                 chatHistory.push({
                     role: messageRole,
                     content: message.content
@@ -392,12 +460,443 @@ 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
  */
-export const updateFlowState = (state: ICommonObject, llmUpdateState: IFlowState[]): ICommonObject => {
+export const updateFlowState = (state: ICommonObject, updateState: IFlowState[]): ICommonObject => {
     let newFlowState: Record<string, any> = {}
-    for (const state of llmUpdateState) {
+    for (const state of updateState) {
         newFlowState[state.key] = state.value
     }
 

packages/components/nodes/agents/AirtableAgent/AirtableAgent.ts

@@ -183,7 +183,7 @@ json.dumps(my_dict)`
                 // TODO: get print console output
                 finalResult = await pyodide.runPythonAsync(code)
             } catch (error) {
-                throw new Error(`Sorry, I'm unable to find answer for question: "${input}" using follwoing code: "${pythonCode}"`)
+                throw new Error(`Sorry, I'm unable to find answer for question: "${input}" using following code: "${pythonCode}"`)
             }
         }
 

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/AzureChatOpenAI/AzureChatOpenAI.ts

@@ -1,9 +1,10 @@
-import { AzureOpenAIInput, AzureChatOpenAI as LangchainAzureChatOpenAI, ChatOpenAIFields, OpenAIClient } from '@langchain/openai'
+import { AzureOpenAIInput, AzureChatOpenAI as LangchainAzureChatOpenAI, ChatOpenAIFields } from '@langchain/openai'
 import { BaseCache } from '@langchain/core/caches'
 import { ICommonObject, IMultiModalOption, INode, INodeData, INodeOptionsValue, INodeParams } from '../../../src/Interface'
 import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
 import { getModels, MODEL_TYPE } from '../../../src/modelLoader'
 import { AzureChatOpenAI } from './FlowiseAzureChatOpenAI'
+import { OpenAI as OpenAIClient } from 'openai'
 
 const serverCredentialsExists =
     !!process.env.AZURE_OPENAI_API_KEY &&
@@ -26,7 +27,7 @@ class AzureChatOpenAI_ChatModels implements INode {
     constructor() {
         this.label = 'Azure ChatOpenAI'
         this.name = 'azureChatOpenAI'
-        this.version = 7.0
+        this.version = 7.1
         this.type = 'AzureChatOpenAI'
         this.icon = 'Azure.svg'
         this.category = 'Chat Models'
@@ -154,6 +155,15 @@ class AzureChatOpenAI_ChatModels implements INode {
                 optional: false,
                 additionalParams: true
             },
+            {
+                label: 'Reasoning',
+                description: 'Whether the model supports reasoning. Only applicable for reasoning models.',
+                name: 'reasoning',
+                type: 'boolean',
+                default: false,
+                optional: true,
+                additionalParams: true
+            },
             {
                 label: 'Reasoning Effort',
                 description: 'Constrains effort on reasoning for reasoning models. Only applicable for o1 and o3 models.',
@@ -173,9 +183,34 @@ class AzureChatOpenAI_ChatModels implements INode {
                         name: 'high'
                     }
                 ],
-                default: 'medium',
-                optional: false,
-                additionalParams: true
+                additionalParams: true,
+                show: {
+                    reasoning: true
+                }
+            },
+            {
+                label: 'Reasoning Summary',
+                description: `A summary of the reasoning performed by the model. This can be useful for debugging and understanding the model's reasoning process`,
+                name: 'reasoningSummary',
+                type: 'options',
+                options: [
+                    {
+                        label: 'Auto',
+                        name: 'auto'
+                    },
+                    {
+                        label: 'Concise',
+                        name: 'concise'
+                    },
+                    {
+                        label: 'Detailed',
+                        name: 'detailed'
+                    }
+                ],
+                additionalParams: true,
+                show: {
+                    reasoning: true
+                }
             }
         ]
     }
@@ -199,7 +234,8 @@ class AzureChatOpenAI_ChatModels implements INode {
         const topP = nodeData.inputs?.topP as string
         const basePath = nodeData.inputs?.basepath as string
         const baseOptions = nodeData.inputs?.baseOptions
-        const reasoningEffort = nodeData.inputs?.reasoningEffort as OpenAIClient.Chat.ChatCompletionReasoningEffort
+        const reasoningEffort = nodeData.inputs?.reasoningEffort as OpenAIClient.Chat.ChatCompletionReasoningEffort | null
+        const reasoningSummary = nodeData.inputs?.reasoningSummary as 'auto' | 'concise' | 'detailed' | null
 
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const azureOpenAIApiKey = getCredentialParam('azureOpenAIApiKey', credentialData, nodeData)
@@ -237,11 +273,22 @@ class AzureChatOpenAI_ChatModels implements INode {
                 console.error('Error parsing base options', exception)
             }
         }
-        if (modelName === 'o3-mini' || modelName.includes('o1')) {
+        if (modelName.includes('o1') || modelName.includes('o3') || modelName.includes('gpt-5')) {
             delete obj.temperature
-        }
-        if ((modelName.includes('o1') || modelName.includes('o3')) && reasoningEffort) {
-            obj.reasoningEffort = reasoningEffort
+            delete obj.stop
+            const reasoning: OpenAIClient.Reasoning = {}
+            if (reasoningEffort) {
+                reasoning.effort = reasoningEffort
+            }
+            if (reasoningSummary) {
+                reasoning.summary = reasoningSummary
+            }
+            obj.reasoning = reasoning
+
+            if (maxTokens) {
+                delete obj.maxTokens
+                obj.maxCompletionTokens = parseInt(maxTokens, 10)
+            }
         }
 
         const multiModalOption: IMultiModalOption = {

packages/components/nodes/chatmodels/AzureChatOpenAI/FlowiseAzureChatOpenAI.ts

@@ -6,6 +6,7 @@ export class AzureChatOpenAI extends LangchainAzureChatOpenAI implements IVision
     configuredModel: string
     configuredMaxToken?: number
     multiModalOption: IMultiModalOption
+    builtInTools: Record<string, any>[] = []
     id: string
 
     constructor(
@@ -27,7 +28,7 @@ export class AzureChatOpenAI extends LangchainAzureChatOpenAI implements IVision
     }
 
     revertToOriginalModel(): void {
-        this.modelName = this.configuredModel
+        this.model = this.configuredModel
         this.maxTokens = this.configuredMaxToken
     }
 
@@ -38,4 +39,8 @@ export class AzureChatOpenAI extends LangchainAzureChatOpenAI implements IVision
     setVisionModel(): void {
         // pass
     }
+
+    addBuiltInTools(builtInTool: Record<string, any>): void {
+        this.builtInTools.push(builtInTool)
+    }
 }

packages/components/nodes/chatmodels/ChatAnthropic/ChatAnthropic.ts

@@ -91,7 +91,7 @@ class ChatAnthropic_ChatModels implements INode {
                 label: 'Extended Thinking',
                 name: 'extendedThinking',
                 type: 'boolean',
-                description: 'Enable extended thinking for reasoning model such as Claude Sonnet 3.7',
+                description: 'Enable extended thinking for reasoning model such as Claude Sonnet 3.7 and Claude 4',
                 optional: true,
                 additionalParams: true
             },

packages/components/nodes/chatmodels/ChatCerebras/ChatCerebras.ts

@@ -136,7 +136,8 @@ class ChatCerebras_ChatModels implements INode {
 
         const obj: ChatOpenAIFields = {
             temperature: parseFloat(temperature),
-            modelName,
+            model: modelName,
+            apiKey: cerebrasAIApiKey,
             openAIApiKey: cerebrasAIApiKey,
             streaming: streaming ?? true
         }

packages/components/nodes/chatmodels/ChatCometAPI/ChatCometAPI.ts

@@ -0,0 +1,176 @@
+import { BaseCache } from '@langchain/core/caches'
+import { ChatOpenAI, ChatOpenAIFields } from '@langchain/openai'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+
+class ChatCometAPI_ChatModels implements INode {
+    readonly baseURL: string = 'https://api.cometapi.com/v1'
+    label: string
+    name: string
+    version: number
+    type: string
+    icon: string
+    category: string
+    description: string
+    baseClasses: string[]
+    credential: INodeParams
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'ChatCometAPI'
+        this.name = 'chatCometAPI'
+        this.version = 1.0
+        this.type = 'ChatCometAPI'
+        this.icon = 'cometapi.svg'
+        this.category = 'Chat Models'
+        this.description = 'Wrapper around CometAPI large language models that use the Chat endpoint'
+        this.baseClasses = [this.type, ...getBaseClasses(ChatOpenAI)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['cometApi']
+        }
+        this.inputs = [
+            {
+                label: 'Cache',
+                name: 'cache',
+                type: 'BaseCache',
+                optional: true
+            },
+            {
+                label: 'Model Name',
+                name: 'modelName',
+                type: 'string',
+                default: 'gpt-5-mini',
+                description: 'Enter the model name (e.g., gpt-5-mini, claude-sonnet-4-20250514, gemini-2.0-flash)'
+            },
+            {
+                label: 'Temperature',
+                name: 'temperature',
+                type: 'number',
+                step: 0.1,
+                default: 0.7,
+                optional: true
+            },
+            {
+                label: 'Streaming',
+                name: 'streaming',
+                type: 'boolean',
+                default: true,
+                optional: true,
+                additionalParams: true
+            },
+            {
+                label: 'Max Tokens',
+                name: 'maxTokens',
+                type: 'number',
+                step: 1,
+                optional: true,
+                additionalParams: true
+            },
+            {
+                label: 'Top Probability',
+                name: 'topP',
+                type: 'number',
+                step: 0.1,
+                optional: true,
+                additionalParams: true
+            },
+            {
+                label: 'Frequency Penalty',
+                name: 'frequencyPenalty',
+                type: 'number',
+                step: 0.1,
+                optional: true,
+                additionalParams: true
+            },
+            {
+                label: 'Presence Penalty',
+                name: 'presencePenalty',
+                type: 'number',
+                step: 0.1,
+                optional: true,
+                additionalParams: true
+            },
+            {
+                label: 'Base Options',
+                name: 'baseOptions',
+                type: 'json',
+                optional: true,
+                additionalParams: true,
+                description: 'Additional options to pass to the CometAPI client. This should be a JSON object.'
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
+        const temperature = nodeData.inputs?.temperature as string
+        const modelName = nodeData.inputs?.modelName as string
+        const maxTokens = nodeData.inputs?.maxTokens as string
+        const topP = nodeData.inputs?.topP as string
+        const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
+        const presencePenalty = nodeData.inputs?.presencePenalty as string
+        const streaming = nodeData.inputs?.streaming as boolean
+        const baseOptions = nodeData.inputs?.baseOptions
+
+        if (nodeData.inputs?.credentialId) {
+            nodeData.credential = nodeData.inputs?.credentialId
+        }
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const openAIApiKey = getCredentialParam('cometApiKey', credentialData, nodeData)
+
+        // Custom error handling for missing API key
+        if (!openAIApiKey || openAIApiKey.trim() === '') {
+            throw new Error(
+                'CometAPI API Key is missing or empty. Please provide a valid CometAPI API key in the credential configuration.'
+            )
+        }
+
+        // Custom error handling for missing model name
+        if (!modelName || modelName.trim() === '') {
+            throw new Error('Model Name is required. Please enter a valid model name (e.g., gpt-5-mini, claude-sonnet-4-20250514).')
+        }
+
+        const cache = nodeData.inputs?.cache as BaseCache
+
+        const obj: ChatOpenAIFields = {
+            temperature: parseFloat(temperature),
+            modelName,
+            openAIApiKey,
+            apiKey: openAIApiKey,
+            streaming: streaming ?? true
+        }
+
+        if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
+        if (topP) obj.topP = parseFloat(topP)
+        if (frequencyPenalty) obj.frequencyPenalty = parseFloat(frequencyPenalty)
+        if (presencePenalty) obj.presencePenalty = parseFloat(presencePenalty)
+        if (cache) obj.cache = cache
+
+        let parsedBaseOptions: any | undefined = undefined
+
+        if (baseOptions) {
+            try {
+                parsedBaseOptions = typeof baseOptions === 'object' ? baseOptions : JSON.parse(baseOptions)
+                if (parsedBaseOptions.baseURL) {
+                    console.warn("The 'baseURL' parameter is not allowed when using the ChatCometAPI node.")
+                    parsedBaseOptions.baseURL = undefined
+                }
+            } catch (exception) {
+                throw new Error('Invalid JSON in the BaseOptions: ' + exception)
+            }
+        }
+
+        const model = new ChatOpenAI({
+            ...obj,
+            configuration: {
+                baseURL: this.baseURL,
+                ...parsedBaseOptions
+            }
+        })
+        return model
+    }
+}
+
+module.exports = { nodeClass: ChatCometAPI_ChatModels }

packages/components/nodes/chatmodels/ChatCometAPI/cometapi.svg

@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<svg version="1.1" xmlns="http://www.w3.org/2000/svg" width="207" height="232">
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+<path d="M0 0 C3.59370889 2.76840946 6.81090677 5.77847531 10 9 C10.69867188 9.66515625 11.39734375 10.3303125 12.1171875 11.015625 C16.54012757 15.52461449 19.531169 20.41283818 22.375 26 C22.70902832 26.65234619 23.04305664 27.30469238 23.38720703 27.97680664 C29.78966214 41.20843735 30.40448825 59.20573624 26.08984375 73.18359375 C18.48979965 92.82385108 6.27019435 105.41854323 -13 114 C-29.20527458 120.38314632 -45.91187826 119.08787574 -61.9140625 112.8671875 C-78.47633521 105.1244532 -90.6818902 90.79579279 -97.20117188 73.89526367 C-101.70761398 60.18076397 -101.08909063 42.12663774 -95 29 C-94.57589844 28.06671875 -94.15179688 27.1334375 -93.71484375 26.171875 C-85.2846631 9.3584785 -71.84223513 -1.671465 -54.3125 -7.96484375 C-35.99378812 -13.48589997 -16.09003976 -10.05627485 0 0 Z " fill="#0274C3" transform="translate(163,25)"/>
+<path d="M0 0 C3.59370889 2.76840946 6.81090677 5.77847531 10 9 C10.69867188 9.66515625 11.39734375 10.3303125 12.1171875 11.015625 C16.54012757 15.52461449 19.531169 20.41283818 22.375 26 C22.70902832 26.65234619 23.04305664 27.30469238 23.38720703 27.97680664 C29.78966214 41.20843735 30.40448825 59.20573624 26.08984375 73.18359375 C18.48979965 92.82385108 6.27019435 105.41854323 -13 114 C-29.20527458 120.38314632 -45.91187826 119.08787574 -61.9140625 112.8671875 C-78.47633521 105.1244532 -90.6818902 90.79579279 -97.20117188 73.89526367 C-101.70761398 60.18076397 -101.08909063 42.12663774 -95 29 C-94.57589844 28.06671875 -94.15179688 27.1334375 -93.71484375 26.171875 C-85.2846631 9.3584785 -71.84223513 -1.671465 -54.3125 -7.96484375 C-35.99378812 -13.48589997 -16.09003976 -10.05627485 0 0 Z M-72.85546875 22.3046875 C-81.52384195 33.1993642 -85.32925872 46.19509438 -84 60 C-81.19770636 74.79342134 -74.05177982 85.87095721 -62 95 C-50.07317504 102.49999729 -36.59178226 103.84984433 -22.875 100.9375 C-9.58998661 97.14684284 0.96143129 88.7625654 7.6796875 76.7578125 C13.61298631 64.36459073 14.80612594 52.14069452 11.02734375 38.90625 C6.83721139 27.05279572 -1.00703398 17.2712335 -11.984375 10.95703125 C-15.54241409 9.26765223 -19.22605928 8.10166317 -23 7 C-23.99 6.67 -24.98 6.34 -26 6 C-44.99521417 4.32054509 -59.38243396 8.38333807 -72.85546875 22.3046875 Z " fill="#FAFDFE" transform="translate(163,25)"/>
+<path d="M0 0 C6.24302767 5.06772084 11.11257121 12.4655725 12.15625 20.50390625 C12.39769334 29.34676869 10.95006126 36.08814626 5.75 43.375 C1.38925675 47.21456516 -1.15219336 48.71018589 -7.05664062 48.625 C-10.77603931 48.20106141 -13.73923312 46.63634037 -17 44.875 C-17.68956787 44.5147876 -18.37913574 44.1545752 -19.08959961 43.78344727 C-41.85230667 31.66318165 -41.85230667 31.66318165 -46.25 21.375 C-47.21511912 15.34300547 -45.21326136 11.66919243 -42.0234375 6.7421875 C-37.16499414 0.25712874 -31.52400844 -3.17464768 -23.75 -5.3125 C-15.10762666 -6.39279667 -7.23796009 -4.98215226 0 0 Z " fill="#FCFDFE" transform="translate(149.25,47.625)"/>
+</svg>

packages/components/nodes/chatmodels/ChatFireworks/ChatFireworks.ts

@@ -1,7 +1,7 @@
 import { BaseCache } from '@langchain/core/caches'
-import { ChatFireworks } from '@langchain/community/chat_models/fireworks'
 import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+import { ChatFireworks, ChatFireworksParams } from './core'
 
 class ChatFireworks_ChatModels implements INode {
     label: string
@@ -41,8 +41,8 @@ class ChatFireworks_ChatModels implements INode {
                 label: 'Model',
                 name: 'modelName',
                 type: 'string',
-                default: 'accounts/fireworks/models/llama-v2-13b-chat',
-                placeholder: 'accounts/fireworks/models/llama-v2-13b-chat'
+                default: 'accounts/fireworks/models/llama-v3p1-8b-instruct',
+                placeholder: 'accounts/fireworks/models/llama-v3p1-8b-instruct'
             },
             {
                 label: 'Temperature',
@@ -71,9 +71,8 @@ class ChatFireworks_ChatModels implements INode {
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const fireworksApiKey = getCredentialParam('fireworksApiKey', credentialData, nodeData)
 
-        const obj: Partial<ChatFireworks> = {
+        const obj: ChatFireworksParams = {
             fireworksApiKey,
-            model: modelName,
             modelName,
             temperature: temperature ? parseFloat(temperature) : undefined,
             streaming: streaming ?? true

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

@@ -0,0 +1,126 @@
+import type { BaseChatModelParams, LangSmithParams } from '@langchain/core/language_models/chat_models'
+import {
+    type OpenAIClient,
+    type ChatOpenAICallOptions,
+    type OpenAIChatInput,
+    type OpenAICoreRequestOptions,
+    ChatOpenAICompletions
+} from '@langchain/openai'
+
+import { getEnvironmentVariable } from '@langchain/core/utils/env'
+
+type FireworksUnsupportedArgs = 'frequencyPenalty' | 'presencePenalty' | 'logitBias' | 'functions'
+
+type FireworksUnsupportedCallOptions = 'functions' | 'function_call'
+
+export type ChatFireworksCallOptions = Partial<Omit<ChatOpenAICallOptions, FireworksUnsupportedCallOptions>>
+
+export type ChatFireworksParams = Partial<Omit<OpenAIChatInput, 'openAIApiKey' | FireworksUnsupportedArgs>> &
+    BaseChatModelParams & {
+        /**
+         * Prefer `apiKey`
+         */
+        fireworksApiKey?: string
+        /**
+         * The Fireworks API key to use.
+         */
+        apiKey?: string
+    }
+
+export class ChatFireworks extends ChatOpenAICompletions<ChatFireworksCallOptions> {
+    static lc_name() {
+        return 'ChatFireworks'
+    }
+
+    _llmType() {
+        return 'fireworks'
+    }
+
+    get lc_secrets(): { [key: string]: string } | undefined {
+        return {
+            fireworksApiKey: 'FIREWORKS_API_KEY',
+            apiKey: 'FIREWORKS_API_KEY'
+        }
+    }
+
+    lc_serializable = true
+
+    fireworksApiKey?: string
+
+    apiKey?: string
+
+    constructor(fields?: ChatFireworksParams) {
+        const fireworksApiKey = fields?.apiKey || fields?.fireworksApiKey || getEnvironmentVariable('FIREWORKS_API_KEY')
+
+        if (!fireworksApiKey) {
+            throw new Error(
+                `Fireworks API key not found. Please set the FIREWORKS_API_KEY environment variable or provide the key into "fireworksApiKey"`
+            )
+        }
+
+        super({
+            ...fields,
+            model: fields?.model || fields?.modelName || 'accounts/fireworks/models/llama-v3p1-8b-instruct',
+            apiKey: fireworksApiKey,
+            configuration: {
+                baseURL: 'https://api.fireworks.ai/inference/v1'
+            },
+            streamUsage: false
+        })
+
+        this.fireworksApiKey = fireworksApiKey
+        this.apiKey = fireworksApiKey
+    }
+
+    getLsParams(options: any): LangSmithParams {
+        const params = super.getLsParams(options)
+        params.ls_provider = 'fireworks'
+        return params
+    }
+
+    toJSON() {
+        const result = super.toJSON()
+
+        if ('kwargs' in result && typeof result.kwargs === 'object' && result.kwargs != null) {
+            delete result.kwargs.openai_api_key
+            delete result.kwargs.configuration
+        }
+
+        return result
+    }
+
+    // eslint-disable-next-line
+    async completionWithRetry(
+        request: OpenAIClient.Chat.ChatCompletionCreateParamsStreaming,
+        options?: OpenAICoreRequestOptions
+    ): Promise<AsyncIterable<OpenAIClient.Chat.Completions.ChatCompletionChunk>>
+
+    // eslint-disable-next-line
+    async completionWithRetry(
+        request: OpenAIClient.Chat.ChatCompletionCreateParamsNonStreaming,
+        options?: OpenAICoreRequestOptions
+    ): Promise<OpenAIClient.Chat.Completions.ChatCompletion>
+
+    /**
+     * Calls the Fireworks API with retry logic in case of failures.
+     * @param request The request to send to the Fireworks API.
+     * @param options Optional configuration for the API call.
+     * @returns The response from the Fireworks API.
+     */
+    // eslint-disable-next-line
+    async completionWithRetry(
+        request: OpenAIClient.Chat.ChatCompletionCreateParamsStreaming | OpenAIClient.Chat.ChatCompletionCreateParamsNonStreaming,
+        options?: OpenAICoreRequestOptions
+    ): Promise<AsyncIterable<OpenAIClient.Chat.Completions.ChatCompletionChunk> | OpenAIClient.Chat.Completions.ChatCompletion> {
+        delete request.frequency_penalty
+        delete request.presence_penalty
+        delete request.logit_bias
+        delete request.functions
+
+        if (request.stream === true) {
+            return super.completionWithRetry(request, options)
+        }
+
+        return super.completionWithRetry(request, options)
+    }
+}

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

@@ -174,6 +174,18 @@ class GoogleGenerativeAI_ChatModels implements INode {
                 optional: true,
                 additionalParams: true
             },
+            {
+                label: 'Thinking Budget',
+                name: 'thinkingBudget',
+                type: 'number',
+                description: 'Guides the number of thinking tokens. -1 for dynamic, 0 to disable, or positive integer (Gemini 2.5 models).',
+                step: 1,
+                optional: true,
+                additionalParams: true,
+                show: {
+                    modelName: ['gemini-2.5-pro', 'gemini-2.5-flash', 'gemini-2.5-flash-lite']
+                }
+            },
             {
                 label: 'Base URL',
                 name: 'baseUrl',
@@ -216,6 +228,7 @@ class GoogleGenerativeAI_ChatModels implements INode {
         const cache = nodeData.inputs?.cache as BaseCache
         const streaming = nodeData.inputs?.streaming as boolean
         const baseUrl = nodeData.inputs?.baseUrl as string | undefined
+        const thinkingBudget = nodeData.inputs?.thinkingBudget as string
 
         const allowImageUploads = nodeData.inputs?.allowImageUploads as boolean
 
@@ -235,6 +248,7 @@ class GoogleGenerativeAI_ChatModels implements INode {
         if (cache) obj.cache = cache
         if (temperature) obj.temperature = parseFloat(temperature)
         if (baseUrl) obj.baseUrl = baseUrl
+        if (thinkingBudget) obj.thinkingBudget = parseInt(thinkingBudget, 10)
 
         let safetySettings: SafetySetting[] = []
         if (_safetySettings) {

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

@@ -174,6 +174,9 @@ export interface GoogleGenerativeAIChatInput extends BaseChatModelParams, Pick<G
      * - Gemini 1.0 Pro version gemini-1.0-pro-002
      */
     convertSystemMessageToHumanContent?: boolean | undefined
+
+    /** Thinking budget for Gemini 2.5 thinking models. Supports -1 (dynamic), 0 (off), or positive integers. */
+    thinkingBudget?: number
 }
 
 /**
@@ -599,10 +602,17 @@ export class LangchainChatGoogleGenerativeAI
 
     convertSystemMessageToHumanContent: boolean | undefined
 
+    thinkingBudget?: number
+
     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) {
@@ -657,6 +667,7 @@ export class LangchainChatGoogleGenerativeAI
 
         this.streaming = fields.streaming ?? this.streaming
         this.json = fields.json
+        this.thinkingBudget = fields.thinkingBudget
 
         this.client = new GenerativeAI(this.apiKey).getGenerativeModel(
             {
@@ -676,12 +687,22 @@ export class LangchainChatGoogleGenerativeAI
                 baseUrl: fields.baseUrl
             }
         )
+        if (this.thinkingBudget !== undefined) {
+            ;(this.client.generationConfig as any).thinkingConfig = {
+                ...(this.thinkingBudget !== undefined ? { thinkingBudget: this.thinkingBudget } : {})
+            }
+        }
         this.streamUsage = fields.streamUsage ?? this.streamUsage
     }
 
     useCachedContent(cachedContent: CachedContent, modelParams?: ModelParams, requestOptions?: RequestOptions): void {
         if (!this.apiKey) return
         this.client = new GenerativeAI(this.apiKey).getGenerativeModelFromCachedContent(cachedContent, modelParams, requestOptions)
+        if (this.thinkingBudget !== undefined) {
+            ;(this.client.generationConfig as any).thinkingConfig = {
+                ...(this.thinkingBudget !== undefined ? { thinkingBudget: this.thinkingBudget } : {})
+            }
+        }
     }
 
     get useSystemInstruction(): boolean {
@@ -770,6 +791,12 @@ export class LangchainChatGoogleGenerativeAI
             this.client.systemInstruction = systemInstruction
             actualPrompt = prompt.slice(1)
         }
+
+        // Ensure actualPrompt is never empty
+        if (actualPrompt.length === 0) {
+            actualPrompt = [{ role: 'user', parts: [{ text: '...' }] }]
+        }
+
         const parameters = this.invocationParams(options)
 
         // Handle streaming
@@ -834,6 +861,12 @@ export class LangchainChatGoogleGenerativeAI
             this.client.systemInstruction = systemInstruction
             actualPrompt = prompt.slice(1)
         }
+
+        // Ensure actualPrompt is never empty
+        if (actualPrompt.length === 0) {
+            actualPrompt = [{ role: 'user', parts: [{ text: '...' }] }]
+        }
+
         const parameters = this.invocationParams(options)
         const request = {
             ...parameters,

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

@@ -48,6 +48,8 @@ export function getMessageAuthor(message: BaseMessage) {
 }
 
 /**
+ * !!! IMPORTANT: Must return 'user' as default instead of throwing error
+ * https://github.com/FlowiseAI/Flowise/issues/4743
  * Maps a message type to a Google Generative AI chat author.
  * @param message The message to map.
  * @param model The model to use for mapping.
@@ -450,6 +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
@@ -470,6 +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
         })
@@ -486,6 +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({
@@ -500,7 +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
     }
@@ -531,6 +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('')
@@ -551,6 +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
         })
@@ -580,6 +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({
@@ -589,7 +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/ChatGoogleVertexAI/ChatGoogleVertexAI.ts

@@ -1,5 +1,6 @@
 import { BaseCache } from '@langchain/core/caches'
 import { ChatVertexAIInput, ChatVertexAI as LcChatVertexAI } from '@langchain/google-vertexai'
+import { buildGoogleCredentials } from '../../../src/google-utils'
 import {
     ICommonObject,
     IMultiModalOption,
@@ -10,7 +11,7 @@ import {
     IVisionChatModal
 } from '../../../src/Interface'
 import { getModels, getRegions, MODEL_TYPE } from '../../../src/modelLoader'
-import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+import { getBaseClasses } from '../../../src/utils'
 
 const DEFAULT_IMAGE_MAX_TOKEN = 8192
 const DEFAULT_IMAGE_MODEL = 'gemini-1.5-flash-latest'
@@ -184,27 +185,6 @@ class GoogleVertexAI_ChatModels implements INode {
     }
 
     async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
-        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
-        const googleApplicationCredentialFilePath = getCredentialParam('googleApplicationCredentialFilePath', credentialData, nodeData)
-        const googleApplicationCredential = getCredentialParam('googleApplicationCredential', credentialData, nodeData)
-        const projectID = getCredentialParam('projectID', credentialData, nodeData)
-
-        const authOptions: ICommonObject = {}
-        if (Object.keys(credentialData).length !== 0) {
-            if (!googleApplicationCredentialFilePath && !googleApplicationCredential)
-                throw new Error('Please specify your Google Application Credential')
-            if (!googleApplicationCredentialFilePath && !googleApplicationCredential)
-                throw new Error(
-                    'Error: More than one component has been inputted. Please use only one of the following: Google Application Credential File Path or Google Credential JSON Object'
-                )
-            if (googleApplicationCredentialFilePath && !googleApplicationCredential)
-                authOptions.keyFile = googleApplicationCredentialFilePath
-            else if (!googleApplicationCredentialFilePath && googleApplicationCredential)
-                authOptions.credentials = JSON.parse(googleApplicationCredential)
-
-            if (projectID) authOptions.projectId = projectID
-        }
-
         const temperature = nodeData.inputs?.temperature as string
         const modelName = nodeData.inputs?.modelName as string
         const customModelName = nodeData.inputs?.customModelName as string
@@ -229,7 +209,10 @@ class GoogleVertexAI_ChatModels implements INode {
             modelName: customModelName || modelName,
             streaming: streaming ?? true
         }
-        if (Object.keys(authOptions).length !== 0) obj.authOptions = authOptions
+
+        const authOptions = await buildGoogleCredentials(nodeData, options)
+        if (authOptions && Object.keys(authOptions).length !== 0) obj.authOptions = authOptions
+
         if (maxOutputTokens) obj.maxOutputTokens = parseInt(maxOutputTokens, 10)
         if (topP) obj.topP = parseFloat(topP)
         if (cache) obj.cache = cache

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/ChatLitellm/ChatLitellm.ts

@@ -124,7 +124,10 @@ class ChatLitellm_ChatModels implements INode {
         if (topP) obj.topP = parseFloat(topP)
         if (timeout) obj.timeout = parseInt(timeout, 10)
         if (cache) obj.cache = cache
-        if (apiKey) obj.openAIApiKey = apiKey
+        if (apiKey) {
+            obj.openAIApiKey = apiKey
+            obj.apiKey = apiKey
+        }
 
         const model = new ChatOpenAI(obj)
 

packages/components/nodes/chatmodels/ChatLocalAI/ChatLocalAI.ts

@@ -111,6 +111,7 @@ class ChatLocalAI_ChatModels implements INode {
             temperature: parseFloat(temperature),
             modelName,
             openAIApiKey: 'sk-',
+            apiKey: 'sk-',
             streaming: streaming ?? true
         }
 
@@ -118,7 +119,10 @@ class ChatLocalAI_ChatModels implements INode {
         if (topP) obj.topP = parseFloat(topP)
         if (timeout) obj.timeout = parseInt(timeout, 10)
         if (cache) obj.cache = cache
-        if (localAIApiKey) obj.openAIApiKey = localAIApiKey
+        if (localAIApiKey) {
+            obj.openAIApiKey = localAIApiKey
+            obj.apiKey = localAIApiKey
+        }
         if (basePath) obj.configuration = { baseURL: basePath }
 
         const model = new ChatOpenAI(obj)

packages/components/nodes/chatmodels/ChatNvdiaNIM/ChatNvdiaNIM.ts

@@ -17,9 +17,9 @@ class ChatNvdiaNIM_ChatModels implements INode {
 
     constructor() {
         this.label = 'Chat NVIDIA NIM'
-        this.name = 'Chat NVIDIA NIM'
+        this.name = 'chatNvidiaNIM'
         this.version = 1.1
-        this.type = 'Chat NVIDIA NIM'
+        this.type = 'ChatNvidiaNIM'
         this.icon = 'nvdia.svg'
         this.category = 'Chat Models'
         this.description = 'Wrapper around NVIDIA NIM Inference API'
@@ -137,6 +137,7 @@ class ChatNvdiaNIM_ChatModels implements INode {
             temperature: parseFloat(temperature),
             modelName,
             openAIApiKey: nvidiaNIMApiKey ?? 'sk-',
+            apiKey: nvidiaNIMApiKey ?? 'sk-',
             streaming: streaming ?? true
         }
 

packages/components/nodes/chatmodels/ChatOpenAI/ChatOpenAI.ts

@@ -1,10 +1,11 @@
-import { ChatOpenAI as LangchainChatOpenAI, ChatOpenAIFields, OpenAIClient } from '@langchain/openai'
+import { ChatOpenAI as LangchainChatOpenAI, ChatOpenAIFields } from '@langchain/openai'
 import { BaseCache } from '@langchain/core/caches'
 import { ICommonObject, IMultiModalOption, INode, INodeData, INodeOptionsValue, INodeParams } from '../../../src/Interface'
 import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
 import { ChatOpenAI } from './FlowiseChatOpenAI'
 import { getModels, MODEL_TYPE } from '../../../src/modelLoader'
 import { HttpsProxyAgent } from 'https-proxy-agent'
+import { OpenAI as OpenAIClient } from 'openai'
 
 class ChatOpenAI_ChatModels implements INode {
     label: string
@@ -21,7 +22,7 @@ class ChatOpenAI_ChatModels implements INode {
     constructor() {
         this.label = 'ChatOpenAI'
         this.name = 'chatOpenAI'
-        this.version = 8.2
+        this.version = 8.3
         this.type = 'ChatOpenAI'
         this.icon = 'openai.svg'
         this.category = 'Chat Models'
@@ -176,9 +177,18 @@ class ChatOpenAI_ChatModels implements INode {
                     allowImageUploads: true
                 }
             },
+            {
+                label: 'Reasoning',
+                description: 'Whether the model supports reasoning. Only applicable for reasoning models.',
+                name: 'reasoning',
+                type: 'boolean',
+                default: false,
+                optional: true,
+                additionalParams: true
+            },
             {
                 label: 'Reasoning Effort',
-                description: 'Constrains effort on reasoning for reasoning models. Only applicable for o1 and o3 models.',
+                description: 'Constrains effort on reasoning for reasoning models',
                 name: 'reasoningEffort',
                 type: 'options',
                 options: [
@@ -195,9 +205,34 @@ class ChatOpenAI_ChatModels implements INode {
                         name: 'high'
                     }
                 ],
-                default: 'medium',
-                optional: false,
-                additionalParams: true
+                additionalParams: true,
+                show: {
+                    reasoning: true
+                }
+            },
+            {
+                label: 'Reasoning Summary',
+                description: `A summary of the reasoning performed by the model. This can be useful for debugging and understanding the model's reasoning process`,
+                name: 'reasoningSummary',
+                type: 'options',
+                options: [
+                    {
+                        label: 'Auto',
+                        name: 'auto'
+                    },
+                    {
+                        label: 'Concise',
+                        name: 'concise'
+                    },
+                    {
+                        label: 'Detailed',
+                        name: 'detailed'
+                    }
+                ],
+                additionalParams: true,
+                show: {
+                    reasoning: true
+                }
             }
         ]
     }
@@ -223,7 +258,8 @@ class ChatOpenAI_ChatModels implements INode {
         const basePath = nodeData.inputs?.basepath as string
         const proxyUrl = nodeData.inputs?.proxyUrl as string
         const baseOptions = nodeData.inputs?.baseOptions
-        const reasoningEffort = nodeData.inputs?.reasoningEffort as OpenAIClient.Chat.ChatCompletionReasoningEffort
+        const reasoningEffort = nodeData.inputs?.reasoningEffort as OpenAIClient.ReasoningEffort | null
+        const reasoningSummary = nodeData.inputs?.reasoningSummary as 'auto' | 'concise' | 'detailed' | null
 
         const allowImageUploads = nodeData.inputs?.allowImageUploads as boolean
         const imageResolution = nodeData.inputs?.imageResolution as string
@@ -240,15 +276,10 @@ class ChatOpenAI_ChatModels implements INode {
             temperature: parseFloat(temperature),
             modelName,
             openAIApiKey,
+            apiKey: openAIApiKey,
             streaming: streaming ?? true
         }
 
-        if (modelName.includes('o3') || modelName.includes('o1')) {
-            delete obj.temperature
-        }
-        if ((modelName.includes('o1') || modelName.includes('o3')) && reasoningEffort) {
-            obj.reasoningEffort = reasoningEffort
-        }
         if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
         if (topP) obj.topP = parseFloat(topP)
         if (frequencyPenalty) obj.frequencyPenalty = parseFloat(frequencyPenalty)
@@ -261,6 +292,19 @@ class ChatOpenAI_ChatModels implements INode {
         }
         if (strictToolCalling) obj.supportsStrictToolCalling = strictToolCalling
 
+        if (modelName.includes('o1') || modelName.includes('o3') || modelName.includes('gpt-5')) {
+            delete obj.temperature
+            delete obj.stop
+            const reasoning: OpenAIClient.Reasoning = {}
+            if (reasoningEffort) {
+                reasoning.effort = reasoningEffort
+            }
+            if (reasoningSummary) {
+                reasoning.summary = reasoningSummary
+            }
+            obj.reasoning = reasoning
+        }
+
         let parsedBaseOptions: any | undefined = undefined
 
         if (baseOptions) {

packages/components/nodes/chatmodels/ChatOpenAI/FlowiseChatOpenAI.ts

@@ -5,6 +5,7 @@ export class ChatOpenAI extends LangchainChatOpenAI implements IVisionChatModal
     configuredModel: string
     configuredMaxToken?: number
     multiModalOption: IMultiModalOption
+    builtInTools: Record<string, any>[] = []
     id: string
 
     constructor(id: string, fields?: ChatOpenAIFields) {
@@ -15,7 +16,7 @@ export class ChatOpenAI extends LangchainChatOpenAI implements IVisionChatModal
     }
 
     revertToOriginalModel(): void {
-        this.modelName = this.configuredModel
+        this.model = this.configuredModel
         this.maxTokens = this.configuredMaxToken
     }
 
@@ -26,4 +27,8 @@ export class ChatOpenAI extends LangchainChatOpenAI implements IVisionChatModal
     setVisionModel(): void {
         // pass
     }
+
+    addBuiltInTools(builtInTool: Record<string, any>): void {
+        this.builtInTools.push(builtInTool)
+    }
 }

packages/components/nodes/chatmodels/ChatOpenAICustom/ChatOpenAICustom.ts

@@ -137,6 +137,7 @@ class ChatOpenAICustom_ChatModels implements INode {
             temperature: parseFloat(temperature),
             modelName,
             openAIApiKey,
+            apiKey: openAIApiKey,
             streaming: streaming ?? true
         }
 

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)
@@ -138,6 +175,7 @@ class ChatOpenRouter_ChatModels implements INode {
             temperature: parseFloat(temperature),
             modelName,
             openAIApiKey: openRouterApiKey,
+            apiKey: openRouterApiKey,
             streaming: streaming ?? true
         }
 
@@ -154,7 +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)
             }
         }
 
@@ -165,7 +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/chatmodels/ChatSambanova/ChatSambanova.ts

@@ -0,0 +1,123 @@
+import { BaseCache } from '@langchain/core/caches'
+import { ChatOpenAI, ChatOpenAIFields } from '@langchain/openai'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+
+class ChatSambanova_ChatModels implements INode {
+    label: string
+    name: string
+    version: number
+    type: string
+    icon: string
+    category: string
+    description: string
+    baseClasses: string[]
+    credential: INodeParams
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'ChatSambanova'
+        this.name = 'chatSambanova'
+        this.version = 1.0
+        this.type = 'ChatSambanova'
+        this.icon = 'sambanova.png'
+        this.category = 'Chat Models'
+        this.description = 'Wrapper around Sambanova Chat Endpoints'
+        this.baseClasses = [this.type, ...getBaseClasses(ChatOpenAI)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['sambanovaApi']
+        }
+        this.inputs = [
+            {
+                label: 'Cache',
+                name: 'cache',
+                type: 'BaseCache',
+                optional: true
+            },
+            {
+                label: 'Model',
+                name: 'modelName',
+                type: 'string',
+                default: 'Meta-Llama-3.3-70B-Instruct',
+                placeholder: 'Meta-Llama-3.3-70B-Instruct'
+            },
+            {
+                label: 'Temperature',
+                name: 'temperature',
+                type: 'number',
+                step: 0.1,
+                default: 0.9,
+                optional: true
+            },
+            {
+                label: 'Streaming',
+                name: 'streaming',
+                type: 'boolean',
+                default: true,
+                optional: true
+            },
+            {
+                label: 'BasePath',
+                name: 'basepath',
+                type: 'string',
+                optional: true,
+                default: 'htps://api.sambanova.ai/v1',
+                additionalParams: true
+            },
+            {
+                label: 'BaseOptions',
+                name: 'baseOptions',
+                type: 'json',
+                optional: true,
+                additionalParams: true
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
+        const cache = nodeData.inputs?.cache as BaseCache
+        const temperature = nodeData.inputs?.temperature as string
+        const modelName = nodeData.inputs?.modelName as string
+        const streaming = nodeData.inputs?.streaming as boolean
+        const basePath = nodeData.inputs?.basepath as string
+        const baseOptions = nodeData.inputs?.baseOptions
+
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const sambanovaApiKey = getCredentialParam('sambanovaApiKey', credentialData, nodeData)
+
+        const obj: ChatOpenAIFields = {
+            temperature: temperature ? parseFloat(temperature) : undefined,
+            model: modelName,
+            apiKey: sambanovaApiKey,
+            openAIApiKey: sambanovaApiKey,
+            streaming: streaming ?? true
+        }
+
+        if (cache) obj.cache = cache
+
+        let parsedBaseOptions: any | undefined = undefined
+
+        if (baseOptions) {
+            try {
+                parsedBaseOptions = typeof baseOptions === 'object' ? baseOptions : JSON.parse(baseOptions)
+            } catch (exception) {
+                throw new Error("Invalid JSON in the ChatSambanova's BaseOptions: " + exception)
+            }
+        }
+
+        if (basePath || parsedBaseOptions) {
+            obj.configuration = {
+                baseURL: basePath,
+                defaultHeaders: parsedBaseOptions
+            }
+        }
+
+        const model = new ChatOpenAI(obj)
+        return model
+    }
+}
+
+module.exports = { nodeClass: ChatSambanova_ChatModels }

packages/components/nodes/chatmodels/Deepseek/Deepseek.ts

@@ -153,6 +153,7 @@ class Deepseek_ChatModels implements INode {
             temperature: parseFloat(temperature),
             modelName,
             openAIApiKey,
+            apiKey: openAIApiKey,
             streaming: streaming ?? true
         }
 

packages/components/nodes/documentloaders/API/APILoader.ts

@@ -95,7 +95,7 @@ class API_DocumentLoaders implements INode {
                 type: 'string',
                 rows: 4,
                 description:
-                    'Each document loader comes with a default set of metadata keys that are extracted from the document. You can use this field to omit some of the default metadata keys. The value should be a list of keys, seperated by comma. Use * to omit all metadata keys execept the ones you specify in the Additional Metadata field',
+                    'Each document loader comes with a default set of metadata keys that are extracted from the document. You can use this field to omit some of the default metadata keys. The value should be a list of keys, separated by comma. Use * to omit all metadata keys except the ones you specify in the Additional Metadata field',
                 placeholder: 'key1, key2, key3.nestedKey1',
                 optional: true,
                 additionalParams: true

packages/components/nodes/documentloaders/ApifyWebsiteContentCrawler/apify-symbol-transparent.svg

@@ -1,5 +1,12 @@
-<svg width="32" height="32" viewBox="0 0 32 32" fill="none" xmlns="http://www.w3.org/2000/svg">
-<path d="M4.72492 9.35559L6.5 24L15 5.5L6.33616 7.15025C5.30261 7.34712 4.59832 8.3111 4.72492 9.35559Z" fill="#97D700" stroke="#97D700" stroke-width="2" stroke-linejoin="round"/>
-<path d="M26.6204 20.5943L26.5699 20.6161L19.5 4.5L24.0986 4.14626C25.163 4.06438 26.1041 4.83296 26.2365 5.8923L27.8137 18.5094C27.9241 19.3925 27.4377 20.2422 26.6204 20.5943Z" fill="#71C5E8" stroke="#71C5E8" stroke-width="2" stroke-linejoin="round"/>
-<path d="M17.5 10L9.5 28L23 22L17.5 10Z" fill="#FF9114" stroke="#FF9114" stroke-width="2" stroke-linejoin="round"/>
+<svg width="200" height="200" viewBox="0 0 200 200" fill="none" xmlns="http://www.w3.org/2000/svg">
+<g clip-path="url(#clip0_267_4154)">
+<path d="M114.695 0H196.97C198.643 0 200 1.35671 200 3.03031V128.766C200 131.778 196.083 132.945 194.434 130.425L112.159 4.68953C110.841 2.67412 112.287 0 114.695 0Z" fill="#246DFF"/>
+<path d="M85.3048 0H3.0303C1.35671 0 0 1.35671 0 3.03031V128.766C0 131.778 3.91698 132.945 5.566 130.425L87.8405 4.68953C89.1593 2.67412 87.7134 0 85.3048 0Z" fill="#20A34E"/>
+<path d="M98.5909 100.668L5.12683 194.835C3.22886 196.747 4.58334 200 7.27759 200H192.8C195.483 200 196.842 196.77 194.967 194.852L102.908 100.685C101.726 99.4749 99.7824 99.4676 98.5909 100.668Z" fill="#F86606"/>
+</g>
+<defs>
+<clipPath id="clip0_267_4154">
+<rect width="200" height="200" fill="white"/>
+</clipPath>
+</defs>
 </svg>

packages/components/nodes/documentloaders/Csv/CsvLoader.ts

@@ -2,7 +2,7 @@ import { TextLoader } from 'langchain/document_loaders/fs/text'
 import Papa from 'papaparse'
 
 type CSVLoaderOptions = {
-    // Return specifific column from key (string) or index (integer)
+    // Return specific column from key (string) or index (integer)
     column?: string | number
     // Force separator (default: auto detect)
     separator?: string

packages/components/nodes/documentloaders/CustomDocumentLoader/CustomDocumentLoader.ts

@@ -119,8 +119,7 @@ class CustomDocumentLoader_DocumentLoaders implements INode {
 
         try {
             const response = await executeJavaScriptCode(javascriptFunction, sandbox, {
-                libraries: ['axios'],
-                timeout: 10000
+                libraries: ['axios']
             })
 
             if (output === 'document' && Array.isArray(response)) {

packages/components/nodes/documentloaders/File/File.ts

@@ -136,9 +136,10 @@ class File_DocumentLoaders implements INode {
 
         let files: string[] = []
         const fileBlobs: { blob: Blob; ext: string }[] = []
+        const processRaw = options.processRaw
 
         //FILE-STORAGE::["CONTRIBUTING.md","LICENSE.md","README.md"]
-        const totalFiles = getOverrideFileInputs(nodeData) || fileBase64
+        const totalFiles = getOverrideFileInputs(nodeData, processRaw) || fileBase64
         if (totalFiles.startsWith('FILE-STORAGE::')) {
             const fileName = totalFiles.replace('FILE-STORAGE::', '')
             if (fileName.startsWith('[') && fileName.endsWith(']')) {
@@ -298,7 +299,7 @@ class File_DocumentLoaders implements INode {
     }
 }
 
-const getOverrideFileInputs = (nodeData: INodeData) => {
+const getOverrideFileInputs = (nodeData: INodeData, processRaw: boolean) => {
     const txtFileBase64 = nodeData.inputs?.txtFile as string
     const pdfFileBase64 = nodeData.inputs?.pdfFile as string
     const jsonFileBase64 = nodeData.inputs?.jsonFile as string
@@ -347,6 +348,10 @@ const getOverrideFileInputs = (nodeData: INodeData) => {
         files.push(...removePrefix(powerpointFileBase64))
     }
 
+    if (processRaw) {
+        return files.length ? JSON.stringify(files) : ''
+    }
+
     return files.length ? `FILE-STORAGE::${JSON.stringify(files)}` : ''
 }
 

packages/components/nodes/documentloaders/Folder/Folder.ts

@@ -10,6 +10,7 @@ import { DocxLoader } from '@langchain/community/document_loaders/fs/docx'
 import { LoadOfSheet } from '../MicrosoftExcel/ExcelLoader'
 import { PowerpointLoader } from '../MicrosoftPowerpoint/PowerpointLoader'
 import { handleEscapeCharacters } from '../../../src/utils'
+import { isPathTraversal } from '../../../src/validator'
 
 class Folder_DocumentLoaders implements INode {
     label: string
@@ -125,6 +126,14 @@ class Folder_DocumentLoaders implements INode {
         const _omitMetadataKeys = nodeData.inputs?.omitMetadataKeys as string
         const output = nodeData.outputs?.output as string
 
+        if (!folderPath) {
+            throw new Error('Folder path is required')
+        }
+
+        if (isPathTraversal(folderPath)) {
+            throw new Error('Invalid folder path: Path traversal detected. Please provide a safe folder path.')
+        }
+
         let omitMetadataKeys: string[] = []
         if (_omitMetadataKeys) {
             omitMetadataKeys = _omitMetadataKeys.split(',').map((key) => key.trim())

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/Oxylabs/Oxylabs.ts

@@ -95,20 +95,29 @@ export class OxylabsLoader extends BaseDocumentLoader {
     }
 
     public async load(): Promise<DocumentInterface[]> {
-        const response = await this.sendAPIRequest<OxylabsResponse>({
-            url: this.params.query,
+        let isUrlSource = this.params.source == 'universal'
+
+        const params = {
             source: this.params.source,
             geo_location: this.params.geo_location,
-            render: this.params.render,
+            render: this.params.render ? 'html' : null,
             parse: this.params.parse,
-            user_agent_type: this.params.user_agent_type
-        })
+            user_agent_type: this.params.user_agent_type,
+            markdown: !this.params.parse,
+            url: isUrlSource ? this.params.query : null,
+            query: !isUrlSource ? this.params.query : null
+        }
 
-        const docs: OxylabsDocument[] = response.data.results.map((result, index) => ({
-            id: `${response.data.job.id.toString()}-${index}`,
-            pageContent: result.content,
-            metadata: {}
-        }))
+        const response = await this.sendAPIRequest<OxylabsResponse>(params)
+
+        const docs: OxylabsDocument[] = response.data.results.map((result, index) => {
+            const content = typeof result.content === 'string' ? result.content : JSON.stringify(result.content)
+            return {
+                id: `${response.data.job.id.toString()}-${index}`,
+                pageContent: content,
+                metadata: {}
+            }
+        })
 
         return docs
     }

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

@@ -1,14 +1,15 @@
-import { omit } from 'lodash'
-import { ICommonObject, IDocument, INode, INodeData, INodeParams } from '../../../src/Interface'
-import { TextSplitter } from 'langchain/text_splitter'
 import {
     Browser,
     Page,
     PlaywrightWebBaseLoader,
     PlaywrightWebBaseLoaderOptions
 } from '@langchain/community/document_loaders/web/playwright'
+import { Document } from '@langchain/core/documents'
+import { TextSplitter } from 'langchain/text_splitter'
 import { test } from 'linkifyjs'
+import { omit } from 'lodash'
 import { handleEscapeCharacters, INodeOutputsValue, webCrawl, xmlScrape } from '../../../src'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 
 class Playwright_DocumentLoaders implements INode {
     label: string
@@ -113,6 +114,14 @@ class Playwright_DocumentLoaders implements INode {
                 additionalParams: true,
                 description: 'CSS selectors like .div or #div'
             },
+            {
+                label: 'CSS Selector (Optional)',
+                name: 'cssSelector',
+                type: 'string',
+                description: 'Only content inside this selector will be extracted. Leave empty to use the entire page body.',
+                optional: true,
+                additionalParams: true
+            },
             {
                 label: 'Additional Metadata',
                 name: 'metadata',
@@ -155,8 +164,14 @@ class Playwright_DocumentLoaders implements INode {
         const relativeLinksMethod = nodeData.inputs?.relativeLinksMethod as string
         const selectedLinks = nodeData.inputs?.selectedLinks as string[]
         let limit = parseInt(nodeData.inputs?.limit as string)
-        let waitUntilGoToOption = nodeData.inputs?.waitUntilGoToOption as 'load' | 'domcontentloaded' | 'networkidle' | 'commit' | undefined
-        let waitForSelector = nodeData.inputs?.waitForSelector as string
+        const waitUntilGoToOption = nodeData.inputs?.waitUntilGoToOption as
+            | 'load'
+            | 'domcontentloaded'
+            | 'networkidle'
+            | 'commit'
+            | undefined
+        const waitForSelector = nodeData.inputs?.waitForSelector as string
+        const cssSelector = nodeData.inputs?.cssSelector as string
         const _omitMetadataKeys = nodeData.inputs?.omitMetadataKeys as string
         const output = nodeData.outputs?.output as string
         const orgId = options.orgId
@@ -172,13 +187,17 @@ class Playwright_DocumentLoaders implements INode {
             throw new Error('Invalid URL')
         }
 
-        async function playwrightLoader(url: string): Promise<any> {
+        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
+                        headless: true,
+                        executablePath: executablePath
                     }
                 }
                 if (waitUntilGoToOption) {
@@ -186,12 +205,22 @@ class Playwright_DocumentLoaders implements INode {
                         waitUntil: waitUntilGoToOption
                     }
                 }
-                if (waitForSelector) {
+                if (cssSelector || waitForSelector) {
                     config['evaluate'] = async (page: Page, _: Browser): Promise<string> => {
-                        await page.waitForSelector(waitForSelector)
+                        if (waitForSelector) {
+                            await page.waitForSelector(waitForSelector)
+                        }
 
-                        const result = await page.evaluate(() => document.body.innerHTML)
-                        return result
+                        if (cssSelector) {
+                            const selectorHandle = await page.$(cssSelector)
+                            const result = await page.evaluate(
+                                (htmlSelection) => htmlSelection?.innerHTML ?? document.body.innerHTML,
+                                selectorHandle
+                            )
+                            return result
+                        } else {
+                            return await page.evaluate(() => document.body.innerHTML)
+                        }
                     }
                 }
                 const loader = new PlaywrightWebBaseLoader(url, config)
@@ -208,7 +237,7 @@ class Playwright_DocumentLoaders implements INode {
             }
         }
 
-        let docs: IDocument[] = []
+        let docs: Document[] = []
         if (relativeLinksMethod) {
             if (process.env.DEBUG === 'true') options.logger.info(`[${orgId}]: Start PlaywrightWebBaseLoader ${relativeLinksMethod}`)
             // if limit is 0 we don't want it to default to 10 so we check explicitly for null or undefined
@@ -225,7 +254,10 @@ class Playwright_DocumentLoaders implements INode {
                 options.logger.info(`[${orgId}]: PlaywrightWebBaseLoader pages: ${JSON.stringify(pages)}, length: ${pages.length}`)
             if (!pages || pages.length === 0) throw new Error('No relative links found')
             for (const page of pages) {
-                docs.push(...(await playwrightLoader(page)))
+                const result = await playwrightLoader(page)
+                if (result) {
+                    docs.push(...result)
+                }
             }
             if (process.env.DEBUG === 'true') options.logger.info(`[${orgId}]: Finish PlaywrightWebBaseLoader ${relativeLinksMethod}`)
         } else if (selectedLinks && selectedLinks.length > 0) {
@@ -234,10 +266,16 @@ class Playwright_DocumentLoaders implements INode {
                     `[${orgId}]: PlaywrightWebBaseLoader pages: ${JSON.stringify(selectedLinks)}, length: ${selectedLinks.length}`
                 )
             for (const page of selectedLinks.slice(0, limit)) {
-                docs.push(...(await playwrightLoader(page)))
+                const result = await playwrightLoader(page)
+                if (result) {
+                    docs.push(...result)
+                }
             }
         } else {
-            docs = await playwrightLoader(url)
+            const result = await playwrightLoader(url)
+            if (result) {
+                docs.push(...result)
+            }
         }
 
         if (metadata) {

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

@@ -1,10 +1,11 @@
-import { omit } from 'lodash'
-import { ICommonObject, IDocument, INode, INodeData, INodeParams } from '../../../src/Interface'
-import { TextSplitter } from 'langchain/text_splitter'
 import { Browser, Page, PuppeteerWebBaseLoader, PuppeteerWebBaseLoaderOptions } from '@langchain/community/document_loaders/web/puppeteer'
+import { Document } from '@langchain/core/documents'
+import { TextSplitter } from 'langchain/text_splitter'
 import { test } from 'linkifyjs'
-import { handleEscapeCharacters, INodeOutputsValue, webCrawl, xmlScrape } from '../../../src'
+import { omit } from 'lodash'
 import { PuppeteerLifeCycleEvent } from 'puppeteer'
+import { handleEscapeCharacters, INodeOutputsValue, webCrawl, xmlScrape } from '../../../src'
+import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 
 class Puppeteer_DocumentLoaders implements INode {
     label: string
@@ -109,6 +110,14 @@ class Puppeteer_DocumentLoaders implements INode {
                 additionalParams: true,
                 description: 'CSS selectors like .div or #div'
             },
+            {
+                label: 'CSS Selector (Optional)',
+                name: 'cssSelector',
+                type: 'string',
+                description: 'Only content inside this selector will be extracted. Leave empty to use the entire page body.',
+                optional: true,
+                additionalParams: true
+            },
             {
                 label: 'Additional Metadata',
                 name: 'metadata',
@@ -151,8 +160,9 @@ class Puppeteer_DocumentLoaders implements INode {
         const relativeLinksMethod = nodeData.inputs?.relativeLinksMethod as string
         const selectedLinks = nodeData.inputs?.selectedLinks as string[]
         let limit = parseInt(nodeData.inputs?.limit as string)
-        let waitUntilGoToOption = nodeData.inputs?.waitUntilGoToOption as PuppeteerLifeCycleEvent
-        let waitForSelector = nodeData.inputs?.waitForSelector as string
+        const waitUntilGoToOption = nodeData.inputs?.waitUntilGoToOption as PuppeteerLifeCycleEvent
+        const waitForSelector = nodeData.inputs?.waitForSelector as string
+        const cssSelector = nodeData.inputs?.cssSelector as string
         const _omitMetadataKeys = nodeData.inputs?.omitMetadataKeys as string
         const output = nodeData.outputs?.output as string
         const orgId = options.orgId
@@ -168,13 +178,17 @@ class Puppeteer_DocumentLoaders implements INode {
             throw new Error('Invalid URL')
         }
 
-        async function puppeteerLoader(url: string): Promise<any> {
+        async function puppeteerLoader(url: string): Promise<Document[] | undefined> {
             try {
-                let docs = []
+                let docs: Document[] = []
+
+                const executablePath = process.env.PUPPETEER_EXECUTABLE_PATH
+
                 const config: PuppeteerWebBaseLoaderOptions = {
                     launchOptions: {
                         args: ['--no-sandbox'],
-                        headless: 'new'
+                        headless: 'new',
+                        executablePath: executablePath
                     }
                 }
                 if (waitUntilGoToOption) {
@@ -182,12 +196,22 @@ class Puppeteer_DocumentLoaders implements INode {
                         waitUntil: waitUntilGoToOption
                     }
                 }
-                if (waitForSelector) {
+                if (cssSelector || waitForSelector) {
                     config['evaluate'] = async (page: Page, _: Browser): Promise<string> => {
-                        await page.waitForSelector(waitForSelector)
+                        if (waitForSelector) {
+                            await page.waitForSelector(waitForSelector)
+                        }
 
-                        const result = await page.evaluate(() => document.body.innerHTML)
-                        return result
+                        if (cssSelector) {
+                            const selectorHandle = await page.$(cssSelector)
+                            const result = await page.evaluate(
+                                (htmlSelection) => htmlSelection?.innerHTML ?? document.body.innerHTML,
+                                selectorHandle
+                            )
+                            return result
+                        } else {
+                            return await page.evaluate(() => document.body.innerHTML)
+                        }
                     }
                 }
                 const loader = new PuppeteerWebBaseLoader(url, config)
@@ -204,7 +228,7 @@ class Puppeteer_DocumentLoaders implements INode {
             }
         }
 
-        let docs: IDocument[] = []
+        let docs: Document[] = []
         if (relativeLinksMethod) {
             if (process.env.DEBUG === 'true') options.logger.info(`[${orgId}]: Start PuppeteerWebBaseLoader ${relativeLinksMethod}`)
             // if limit is 0 we don't want it to default to 10 so we check explicitly for null or undefined
@@ -221,7 +245,10 @@ class Puppeteer_DocumentLoaders implements INode {
                 options.logger.info(`[${orgId}]: PuppeteerWebBaseLoader pages: ${JSON.stringify(pages)}, length: ${pages.length}`)
             if (!pages || pages.length === 0) throw new Error('No relative links found')
             for (const page of pages) {
-                docs.push(...(await puppeteerLoader(page)))
+                const result = await puppeteerLoader(page)
+                if (result) {
+                    docs.push(...result)
+                }
             }
             if (process.env.DEBUG === 'true') options.logger.info(`[${orgId}]: Finish PuppeteerWebBaseLoader ${relativeLinksMethod}`)
         } else if (selectedLinks && selectedLinks.length > 0) {
@@ -230,10 +257,16 @@ class Puppeteer_DocumentLoaders implements INode {
                     `[${orgId}]: PuppeteerWebBaseLoader pages: ${JSON.stringify(selectedLinks)}, length: ${selectedLinks.length}`
                 )
             for (const page of selectedLinks.slice(0, limit)) {
-                docs.push(...(await puppeteerLoader(page)))
+                const result = await puppeteerLoader(page)
+                if (result) {
+                    docs.push(...result)
+                }
             }
         } else {
-            docs = await puppeteerLoader(url)
+            const result = await puppeteerLoader(url)
+            if (result) {
+                docs.push(...result)
+            }
         }
 
         if (metadata) {

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

@@ -4,8 +4,7 @@ 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'
@@ -41,17 +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',
@@ -452,7 +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
@@ -557,12 +544,8 @@ class UnstructuredFile_DocumentLoaders implements INode {
                     docs.push(...loaderDocs)
                 }
             }
-        } else if (filePath) {
-            const loader = new LCUnstructuredLoader(filePath, 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/GoogleGenerativeAIEmbedding/GoogleGenerativeAIEmbedding.ts

@@ -4,6 +4,25 @@ import { GoogleGenerativeAIEmbeddings, GoogleGenerativeAIEmbeddingsParams } from
 import { TaskType } from '@google/generative-ai'
 import { MODEL_TYPE, getModels } from '../../../src/modelLoader'
 
+class GoogleGenerativeAIEmbeddingsWithStripNewLines extends GoogleGenerativeAIEmbeddings {
+    stripNewLines: boolean
+
+    constructor(params: GoogleGenerativeAIEmbeddingsParams & { stripNewLines?: boolean }) {
+        super(params)
+        this.stripNewLines = params.stripNewLines ?? false
+    }
+
+    async embedDocuments(texts: string[]): Promise<number[][]> {
+        const processedTexts = this.stripNewLines ? texts.map((text) => text.replace(/\n/g, ' ')) : texts
+        return super.embedDocuments(processedTexts)
+    }
+
+    async embedQuery(text: string): Promise<number[]> {
+        const processedText = this.stripNewLines ? text.replace(/\n/g, ' ') : text
+        return super.embedQuery(processedText)
+    }
+}
+
 class GoogleGenerativeAIEmbedding_Embeddings implements INode {
     label: string
     name: string
@@ -24,7 +43,7 @@ class GoogleGenerativeAIEmbedding_Embeddings implements INode {
         this.icon = 'GoogleGemini.svg'
         this.category = 'Embeddings'
         this.description = 'Google Generative API to generate embeddings for a given text'
-        this.baseClasses = [this.type, ...getBaseClasses(GoogleGenerativeAIEmbeddings)]
+        this.baseClasses = [this.type, ...getBaseClasses(GoogleGenerativeAIEmbeddingsWithStripNewLines)]
         this.credential = {
             label: 'Connect Credential',
             name: 'credential',
@@ -55,6 +74,14 @@ class GoogleGenerativeAIEmbedding_Embeddings implements INode {
                     { label: 'CLUSTERING', name: 'CLUSTERING' }
                 ],
                 default: 'TASK_TYPE_UNSPECIFIED'
+            },
+            {
+                label: 'Strip New Lines',
+                name: 'stripNewLines',
+                type: 'boolean',
+                optional: true,
+                additionalParams: true,
+                description: 'Remove new lines from input text before embedding to reduce token count'
             }
         ]
     }
@@ -71,6 +98,7 @@ class GoogleGenerativeAIEmbedding_Embeddings implements INode {
         const modelName = nodeData.inputs?.modelName as string
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const apiKey = getCredentialParam('googleGenerativeAPIKey', credentialData, nodeData)
+        const stripNewLines = nodeData.inputs?.stripNewLines as boolean
 
         let taskType: TaskType
         switch (nodeData.inputs?.tasktype as string) {
@@ -93,13 +121,14 @@ class GoogleGenerativeAIEmbedding_Embeddings implements INode {
                 taskType = TaskType.TASK_TYPE_UNSPECIFIED
                 break
         }
-        const obj: GoogleGenerativeAIEmbeddingsParams = {
+        const obj: GoogleGenerativeAIEmbeddingsParams & { stripNewLines?: boolean } = {
             apiKey: apiKey,
             modelName: modelName,
-            taskType: taskType
+            taskType: taskType,
+            stripNewLines
         }
 
-        const model = new GoogleGenerativeAIEmbeddings(obj)
+        const model = new GoogleGenerativeAIEmbeddingsWithStripNewLines(obj)
         return model
     }
 }

packages/components/nodes/embeddings/GoogleVertexAIEmbedding/GoogleVertexAIEmbedding.ts

@@ -1,7 +1,27 @@
 import { GoogleVertexAIEmbeddingsInput, VertexAIEmbeddings } from '@langchain/google-vertexai'
+import { buildGoogleCredentials } from '../../../src/google-utils'
 import { ICommonObject, INode, INodeData, INodeOptionsValue, INodeParams } from '../../../src/Interface'
 import { MODEL_TYPE, getModels, getRegions } from '../../../src/modelLoader'
-import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+import { getBaseClasses } from '../../../src/utils'
+
+class VertexAIEmbeddingsWithStripNewLines extends VertexAIEmbeddings {
+    stripNewLines: boolean
+
+    constructor(params: GoogleVertexAIEmbeddingsInput & { stripNewLines?: boolean }) {
+        super(params)
+        this.stripNewLines = params.stripNewLines ?? false
+    }
+
+    async embedDocuments(texts: string[]): Promise<number[][]> {
+        const processedTexts = this.stripNewLines ? texts.map((text) => text.replace(/\n/g, ' ')) : texts
+        return super.embedDocuments(processedTexts)
+    }
+
+    async embedQuery(text: string): Promise<number[]> {
+        const processedText = this.stripNewLines ? text.replace(/\n/g, ' ') : text
+        return super.embedQuery(processedText)
+    }
+}
 
 class GoogleVertexAIEmbedding_Embeddings implements INode {
     label: string
@@ -23,7 +43,7 @@ class GoogleVertexAIEmbedding_Embeddings implements INode {
         this.icon = 'GoogleVertex.svg'
         this.category = 'Embeddings'
         this.description = 'Google vertexAI API to generate embeddings for a given text'
-        this.baseClasses = [this.type, ...getBaseClasses(VertexAIEmbeddings)]
+        this.baseClasses = [this.type, ...getBaseClasses(VertexAIEmbeddingsWithStripNewLines)]
         this.credential = {
             label: 'Connect Credential',
             name: 'credential',
@@ -48,6 +68,14 @@ class GoogleVertexAIEmbedding_Embeddings implements INode {
                 type: 'asyncOptions',
                 loadMethod: 'listRegions',
                 optional: true
+            },
+            {
+                label: 'Strip New Lines',
+                name: 'stripNewLines',
+                type: 'boolean',
+                optional: true,
+                additionalParams: true,
+                description: 'Remove new lines from input text before embedding to reduce token count'
             }
         ]
     }
@@ -63,36 +91,21 @@ class GoogleVertexAIEmbedding_Embeddings implements INode {
     }
 
     async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
-        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const modelName = nodeData.inputs?.modelName as string
         const region = nodeData.inputs?.region as string
-        const googleApplicationCredentialFilePath = getCredentialParam('googleApplicationCredentialFilePath', credentialData, nodeData)
-        const googleApplicationCredential = getCredentialParam('googleApplicationCredential', credentialData, nodeData)
-        const projectID = getCredentialParam('projectID', credentialData, nodeData)
+        const stripNewLines = nodeData.inputs?.stripNewLines as boolean
 
-        const authOptions: any = {}
-        if (Object.keys(credentialData).length !== 0) {
-            if (!googleApplicationCredentialFilePath && !googleApplicationCredential)
-                throw new Error('Please specify your Google Application Credential')
-            if (!googleApplicationCredentialFilePath && !googleApplicationCredential)
-                throw new Error(
-                    'Error: More than one component has been inputted. Please use only one of the following: Google Application Credential File Path or Google Credential JSON Object'
-                )
-
-            if (googleApplicationCredentialFilePath && !googleApplicationCredential)
-                authOptions.keyFile = googleApplicationCredentialFilePath
-            else if (!googleApplicationCredentialFilePath && googleApplicationCredential)
-                authOptions.credentials = JSON.parse(googleApplicationCredential)
-
-            if (projectID) authOptions.projectId = projectID
+        const obj: GoogleVertexAIEmbeddingsInput & { stripNewLines?: boolean } = {
+            model: modelName,
+            stripNewLines
         }
-        const obj: GoogleVertexAIEmbeddingsInput = {
-            model: modelName
-        }
-        if (Object.keys(authOptions).length !== 0) obj.authOptions = authOptions
+
+        const authOptions = await buildGoogleCredentials(nodeData, options)
+        if (authOptions && Object.keys(authOptions).length !== 0) obj.authOptions = authOptions
+
         if (region) obj.location = region
 
-        const model = new VertexAIEmbeddings(obj)
+        const model = new VertexAIEmbeddingsWithStripNewLines(obj)
         return model
     }
 }

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/GoogleVertexAI/GoogleVertexAI.ts

@@ -1,8 +1,9 @@
 import { BaseCache } from '@langchain/core/caches'
 import { VertexAI, VertexAIInput } from '@langchain/google-vertexai'
 import { ICommonObject, INode, INodeData, INodeOptionsValue, INodeParams } from '../../../src/Interface'
-import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+import { getBaseClasses } from '../../../src/utils'
 import { getModels, MODEL_TYPE } from '../../../src/modelLoader'
+import { buildGoogleCredentials } from '../../../src/google-utils'
 
 class GoogleVertexAI_LLMs implements INode {
     label: string
@@ -83,28 +84,6 @@ class GoogleVertexAI_LLMs implements INode {
     }
 
     async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
-        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
-        const googleApplicationCredentialFilePath = getCredentialParam('googleApplicationCredentialFilePath', credentialData, nodeData)
-        const googleApplicationCredential = getCredentialParam('googleApplicationCredential', credentialData, nodeData)
-        const projectID = getCredentialParam('projectID', credentialData, nodeData)
-
-        const authOptions: any = {}
-        if (Object.keys(credentialData).length !== 0) {
-            if (!googleApplicationCredentialFilePath && !googleApplicationCredential)
-                throw new Error('Please specify your Google Application Credential')
-            if (!googleApplicationCredentialFilePath && !googleApplicationCredential)
-                throw new Error(
-                    'Error: More than one component has been inputted. Please use only one of the following: Google Application Credential File Path or Google Credential JSON Object'
-                )
-
-            if (googleApplicationCredentialFilePath && !googleApplicationCredential)
-                authOptions.keyFile = googleApplicationCredentialFilePath
-            else if (!googleApplicationCredentialFilePath && googleApplicationCredential)
-                authOptions.credentials = JSON.parse(googleApplicationCredential)
-
-            if (projectID) authOptions.projectId = projectID
-        }
-
         const temperature = nodeData.inputs?.temperature as string
         const modelName = nodeData.inputs?.modelName as string
         const maxOutputTokens = nodeData.inputs?.maxOutputTokens as string
@@ -115,7 +94,9 @@ class GoogleVertexAI_LLMs implements INode {
             temperature: parseFloat(temperature),
             model: modelName
         }
-        if (Object.keys(authOptions).length !== 0) obj.authOptions = authOptions
+
+        const authOptions = await buildGoogleCredentials(nodeData, options)
+        if (authOptions && Object.keys(authOptions).length !== 0) obj.authOptions = authOptions
 
         if (maxOutputTokens) obj.maxOutputTokens = parseInt(maxOutputTokens, 10)
         if (topP) obj.topP = parseFloat(topP)

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/llms/SambaNova/Sambanova.ts

@@ -0,0 +1,71 @@
+import { getBaseClasses, getCredentialData, getCredentialParam, ICommonObject, INode, INodeData, INodeParams } from '../../../src'
+import { OpenAI } from '@langchain/openai'
+import { BaseCache } from '@langchain/core/caches'
+
+class Sambanova_LLMs implements INode {
+    label: string
+    name: string
+    version: number
+    type: string
+    icon: string
+    category: string
+    description: string
+    baseClasses: string[]
+    credential: INodeParams
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Sambanova'
+        this.name = 'sambanova'
+        this.version = 1.0
+        this.type = 'Sambanova'
+        this.icon = 'sambanova.png'
+        this.category = 'LLMs'
+        this.description = 'Wrapper around Sambanova API for large language models'
+        this.baseClasses = [this.type, ...getBaseClasses(OpenAI)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['sambanovaApi']
+        }
+        this.inputs = [
+            {
+                label: 'Cache',
+                name: 'cache',
+                type: 'BaseCache',
+                optional: true
+            },
+            {
+                label: 'Model Name',
+                name: 'modelName',
+                type: 'string',
+                default: 'Meta-Llama-3.3-70B-Instruct',
+                description: 'For more details see https://docs.sambanova.ai/cloud/docs/get-started/supported-models',
+                optional: true
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
+        const cache = nodeData.inputs?.cache as BaseCache
+        const modelName = nodeData.inputs?.modelName as string
+
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const sambanovaKey = getCredentialParam('sambanovaApiKey', credentialData, nodeData)
+
+        const obj: any = {
+            model: modelName,
+            configuration: {
+                baseURL: 'https://api.sambanova.ai/v1',
+                apiKey: sambanovaKey
+            }
+        }
+        if (cache) obj.cache = cache
+
+        const sambanova = new OpenAI(obj)
+        return sambanova
+    }
+}
+
+module.exports = { nodeClass: Sambanova_LLMs }

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,
@@ -130,8 +130,7 @@ class ChatPromptTemplate_Prompts implements INode {
 
             try {
                 const response = await executeJavaScriptCode(messageHistoryCode, sandbox, {
-                    libraries: ['axios', '@langchain/core'],
-                    timeout: 10000
+                    libraries: ['axios', '@langchain/core']
                 })
 
                 const parsedResponse = JSON.parse(response)

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
             },
@@ -205,8 +204,8 @@ class MySQLRecordManager implements RecordManagerInterface {
     }
 
     async createSchema(): Promise<void> {
+        const dataSource = await this.getDataSource()
         try {
-            const dataSource = await this.getDataSource()
             const queryRunner = dataSource.createQueryRunner()
             const tableName = this.sanitizeTableName(this.tableName)
 
@@ -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(
@@ -241,6 +249,8 @@ class MySQLRecordManager implements RecordManagerInterface {
                 return
             }
             throw e
+        } finally {
+            await dataSource.destroy()
         }
     }
 
@@ -259,7 +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
         }
@@ -275,23 +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 {
@@ -347,13 +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]
 
@@ -380,6 +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
             },
@@ -222,8 +221,8 @@ class PostgresRecordManager implements RecordManagerInterface {
     }
 
     async createSchema(): Promise<void> {
+        const dataSource = await this.getDataSource()
         try {
-            const dataSource = await this.getDataSource()
             const queryRunner = dataSource.createQueryRunner()
             const tableName = this.sanitizeTableName(this.tableName)
 
@@ -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
@@ -251,6 +263,8 @@ class PostgresRecordManager implements RecordManagerInterface {
                 return
             }
             throw e
+        } finally {
+            await dataSource.destroy()
         }
     }
 
@@ -284,7 +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
         }
@@ -300,17 +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()
@@ -349,8 +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`
@@ -381,6 +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
             },
@@ -179,8 +178,8 @@ class SQLiteRecordManager implements RecordManagerInterface {
     }
 
     async createSchema(): Promise<void> {
+        const dataSource = await this.getDataSource()
         try {
-            const dataSource = await this.getDataSource()
             const queryRunner = dataSource.createQueryRunner()
             const tableName = this.sanitizeTableName(this.tableName)
 
@@ -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 "${tableName}" (doc_id);`)
+            }
+
             await queryRunner.release()
         } catch (e: any) {
             // This error indicates that the table already exists
@@ -208,6 +216,8 @@ CREATE INDEX IF NOT EXISTS group_id_index ON "${tableName}" (group_id);`)
                 return
             }
             throw e
+        } finally {
+            await dataSource.destroy()
         }
     }
 
@@ -226,7 +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
         }
@@ -241,23 +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
@@ -312,8 +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 "${tableName}" WHERE namespace = ?`
@@ -342,6 +352,11 @@ CREATE INDEX IF NOT EXISTS group_id_index ON "${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/sequentialagents/Agent/Agent.ts

@@ -940,9 +940,7 @@ const getReturnOutput = async (nodeData: INodeData, input: string, options: ICom
         const sandbox = createCodeExecutionSandbox(input, variables, flow)
 
         try {
-            const response = await executeJavaScriptCode(updateStateMemoryCode, sandbox, {
-                timeout: 10000
-            })
+            const response = await executeJavaScriptCode(updateStateMemoryCode, sandbox)
 
             if (typeof response !== 'object') throw new Error('Return output must be an object')
             return response

packages/components/nodes/sequentialagents/Condition/Condition.ts

@@ -282,9 +282,7 @@ const runCondition = async (nodeData: INodeData, input: string, options: ICommon
         const sandbox = createCodeExecutionSandbox(input, variables, flow)
 
         try {
-            const response = await executeJavaScriptCode(conditionFunction, sandbox, {
-                timeout: 10000
-            })
+            const response = await executeJavaScriptCode(conditionFunction, sandbox)
 
             if (typeof response !== 'string') throw new Error('Condition function must return a string')
             return response

packages/components/nodes/sequentialagents/ConditionAgent/ConditionAgent.ts

@@ -549,9 +549,7 @@ const runCondition = async (
         const sandbox = createCodeExecutionSandbox(input, variables, flow)
 
         try {
-            const response = await executeJavaScriptCode(conditionFunction, sandbox, {
-                timeout: 10000
-            })
+            const response = await executeJavaScriptCode(conditionFunction, sandbox)
 
             if (typeof response !== 'string') throw new Error('Condition function must return a string')
             return response

packages/components/nodes/sequentialagents/CustomFunction/CustomFunction.ts

@@ -166,9 +166,7 @@ class CustomFunction_SeqAgents implements INode {
             const sandbox = createCodeExecutionSandbox(input, variables, flow, additionalSandbox)
 
             try {
-                const response = await executeJavaScriptCode(javascriptFunction, sandbox, {
-                    timeout: 10000
-                })
+                const response = await executeJavaScriptCode(javascriptFunction, sandbox)
 
                 if (returnValueAs === 'stateObj') {
                     if (typeof response !== 'object') {

packages/components/nodes/sequentialagents/ExecuteFlow/ExecuteFlow.ts

@@ -264,8 +264,7 @@ class ExecuteFlow_SeqAgents implements INode {
 
             try {
                 let response = await executeJavaScriptCode(code, sandbox, {
-                    useSandbox: false,
-                    timeout: 10000
+                    useSandbox: false
                 })
 
                 if (typeof response === 'object') {

packages/components/nodes/sequentialagents/LLMNode/LLMNode.ts

@@ -712,9 +712,7 @@ const getReturnOutput = async (nodeData: INodeData, input: string, options: ICom
         const sandbox = createCodeExecutionSandbox(input, variables, flow)
 
         try {
-            const response = await executeJavaScriptCode(updateStateMemoryCode, sandbox, {
-                timeout: 10000
-            })
+            const response = await executeJavaScriptCode(updateStateMemoryCode, sandbox)
 
             if (typeof response !== 'object') throw new Error('Return output must be an object')
             return response

packages/components/nodes/sequentialagents/State/State.ts

@@ -204,9 +204,7 @@ class State_SeqAgents implements INode {
             const sandbox = createCodeExecutionSandbox('', variables, flow)
 
             try {
-                const response = await executeJavaScriptCode(`return ${stateMemoryCode}`, sandbox, {
-                    timeout: 10000
-                })
+                const response = await executeJavaScriptCode(`return ${stateMemoryCode}`, sandbox)
 
                 if (typeof response !== 'object') throw new Error('State must be an object')
                 const returnOutput: ISeqAgentNode = {