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Merge branch 'main' into chore/Models-Update 

# Conflicts:
#	packages/components/models.json
This commit is contained in:
Henry 2025-11-26 15:37:45 +00:00
parent 0c8b6d586a 3ad2b3a559
commit 9b9798b451
909 changed files with 109690 additions and 20524 deletions
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37
.github/ISSUE_TEMPLATE/bug_report.md vendored
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@ -1,37 +0,0 @@
---
name: Bug report
about: Create a report to help us improve
title: '[BUG]'
labels: ''
assignees: ''
---
**Describe the bug**
A clear and concise description of what the bug is.
**To Reproduce**
Steps to reproduce the behavior:
1. Go to '...'
2. Click on '....'
3. Scroll down to '....'
4. See error
**Expected behavior**
A clear and concise description of what you expected to happen.
**Screenshots**
If applicable, add screenshots to help explain your problem.
**Flow**
If applicable, add exported flow in order to help replicating the problem.
**Setup**
- Installation [e.g. docker, `npx flowise start`, `pnpm start`]
- Flowise Version [e.g. 1.2.11]
- OS: [e.g. macOS, Windows, Linux]
- Browser [e.g. chrome, safari]
**Additional context**
Add any other context about the problem here.

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.github/ISSUE_TEMPLATE/bug_report.yml vendored Normal file
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@ -0,0 +1,101 @@
name: Bug Report
description: File a bug report to help us improve
labels: ['bug']
assignees: []
body:
- type: markdown
attributes:
value: |
Make sure to have a proper title and description.
- type: textarea
id: bug-description
attributes:
label: Describe the bug
description: A clear and concise description of what the bug is.
placeholder: Tell us what you see!
validations:
required: true
- type: textarea
id: reproduce
attributes:
label: To Reproduce
description: Steps to reproduce the behavior
placeholder: |
1. Go to '...'
2. Click on '....'
3. Scroll down to '....'
4. See error
validations:
required: true
- type: textarea
id: expected
attributes:
label: Expected behavior
description: A clear and concise description of what you expected to happen.
validations:
required: true
- type: textarea
id: screenshots
attributes:
label: Screenshots
description: If applicable, add screenshots to help explain your problem.
placeholder: Drag and drop or paste screenshots here
- type: textarea
id: flow
attributes:
label: Flow
description: If applicable, add exported flow in order to help replicating the problem.
placeholder: Paste your exported flow here
- type: dropdown
id: method
attributes:
label: Use Method
description: How did you use Flowise?
options:
- Flowise Cloud
- Docker
- npx flowise start
- pnpm start
- type: input
id: version
attributes:
label: Flowise Version
description: What version of Flowise are you running?
placeholder: e.g., 1.2.11
- type: dropdown
id: os
attributes:
label: Operating System
description: What operating system are you using?
options:
- Windows
- macOS
- Linux
- Other
- type: dropdown
id: browser
attributes:
label: Browser
description: What browser are you using?
options:
- Chrome
- Firefox
- Safari
- Edge
- Other
- type: textarea
id: context
attributes:
label: Additional context
description: Add any other context about the problem here.
placeholder: Any additional information that might be helpful

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.github/ISSUE_TEMPLATE/feature_request.md vendored
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@ -1,13 +0,0 @@
---
name: Feature request
about: Suggest an idea for this project
title: '[FEATURE]'
labels: ''
assignees: ''
---
**Describe the feature you'd like**
A clear and concise description of what you would like Flowise to have.
**Additional context**
Add any other context or screenshots about the feature request here.

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name: Feature Request
description: Suggest a new feature or enhancement for Flowise
labels: ['enhancement']
assignees: []
body:
- type: markdown
attributes:
value: |
Thanks for suggesting a new feature! Please provide as much detail as possible to help us understand your request.
- type: textarea
id: feature-description
attributes:
label: Feature Description
description: A clear and concise description of the feature you'd like to see in Flowise.
placeholder: Describe what you want to be added or improved...
validations:
required: true
- type: dropdown
id: feature-category
attributes:
label: Feature Category
description: What category does this feature belong to?
options:
- UI/UX Improvement
- New Node/Component
- Integration
- Performance
- Security
- Documentation
- API Enhancement
- Workflow/Flow Management
- Authentication/Authorization
- Database/Storage
- Deployment/DevOps
- Other
validations:
required: true
- type: textarea
id: problem-statement
attributes:
label: Problem Statement
description: What problem does this feature solve? What's the current pain point?
placeholder: Describe the problem or limitation you're facing...
- type: textarea
id: proposed-solution
attributes:
label: Proposed Solution
description: How would you like this feature to work? Be as specific as possible.
placeholder: Describe your ideal solution in detail...
- type: textarea
id: mockups-references
attributes:
label: Mockups or References
description: Any mockups, screenshots, or references to similar features in other tools?
placeholder: Upload images or provide links to examples...
- type: textarea
id: additional-context
attributes:
label: Additional Context
description: Any other information, context, or examples that would help us understand this request.
placeholder: Add any other relevant information...

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.github/workflows/autoSyncMergedPullRequest.yml vendored
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@ -1,33 +0,0 @@
name: autoSyncMergedPullRequest
on:
pull_request_target:
types:
- closed
branches: ['main']
jobs:
autoSyncMergedPullRequest:
if: github.event.pull_request.merged == true
runs-on: ubuntu-latest
permissions:
contents: write
steps:
- uses: actions/checkout@v4
- name: Show PR info
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
echo The PR #${{ github.event.pull_request.number }} was merged on main branch!
- name: Repository Dispatch
uses: peter-evans/repository-dispatch@v3
with:
token: ${{ secrets.AUTOSYNC_TOKEN }}
repository: ${{ secrets.AUTOSYNC_CH_URL }}
event-type: ${{ secrets.AUTOSYNC_PR_EVENT_TYPE }}
client-payload: >-
{
"ref": "${{ github.ref }}",
"prNumber": "${{ github.event.pull_request.number }}",
"prTitle": "${{ github.event.pull_request.title }}",
"prDescription": "",
"sha": "${{ github.sha }}"
}

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@ -1,36 +0,0 @@
name: autoSyncSingleCommit
on:
push:
branches:
- main
jobs:
doNotAutoSyncSingleCommit:
if: github.event.commits[1] != null
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: IGNORE autoSyncSingleCommit
run: |
echo This single commit has came from a merged commit. We will ignore it. This case is handled in autoSyncMergedPullRequest workflow for merge commits comming from merged pull requests only! Beware, the regular merge commits are not handled by any workflow for the moment.
autoSyncSingleCommit:
if: github.event.commits[1] == null
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: autoSyncSingleCommit
env:
GITHUB_CONTEXT: ${{ toJSON(github) }}
run: |
echo Autosync a single commit with id: ${{ github.sha }} from openSource main branch towards cloud hosted version.
- name: Repository Dispatch
uses: peter-evans/repository-dispatch@v3
with:
token: ${{ secrets.AUTOSYNC_TOKEN }}
repository: ${{ secrets.AUTOSYNC_CH_URL }}
event-type: ${{ secrets.AUTOSYNC_SC_EVENT_TYPE }}
client-payload: >-
{
"ref": "${{ github.ref }}",
"sha": "${{ github.sha }}",
"commitMessage": "${{ github.event.commits[0].id }}"
}

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.github/workflows/docker-image-dockerhub.yml vendored Normal file
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@ -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 }}

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@ -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) }}

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@ -1,43 +0,0 @@
name: Docker Image CI
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: 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: ${{ secrets.DOCKERHUB_TOKEN }}
- name: Build and push
uses: docker/build-push-action@v5.3.0
with:
context: .
file: ./docker/Dockerfile
build-args: |
NODE_VERSION=${{github.event.inputs.node_version}}
platforms: linux/amd64,linux/arm64
push: true
tags: flowiseai/flowise:${{github.event.inputs.tag_version}}

3
.github/workflows/main.yml vendored
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@ -6,6 +6,7 @@ on:
pull_request:
branches:
- '*'
workflow_dispatch:
permissions:
contents: read
jobs:
@ -31,6 +32,8 @@ jobs:
- run: pnpm install
- run: pnpm lint
- run: pnpm build
env:
NODE_OPTIONS: '--max_old_space_size=4096'
- name: Cypress install
run: pnpm cypress install
- name: Install dependencies (Cypress Action)

5
.github/workflows/test_docker_build.yml vendored
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@ -8,13 +8,12 @@ on:
pull_request:
branches:
- '*'
workflow_dispatch:
jobs:
build:
runs-on: ubuntu-latest
env:
PUPPETEER_SKIP_DOWNLOAD: true
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- run: docker build --no-cache -t flowise .

84
CONTRIBUTING.md
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@ -114,54 +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_USERNAME | Username to login | String | |
| FLOWISE_PASSWORD | Password to login | 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 |
| APIKEY_STORAGE_TYPE | To store api keys on a JSON file or database. Default is `json` | Enum String: `json`, `db` | `json` |
| APIKEY_PATH | Location where api keys are saved when `APIKEY_STORAGE_TYPE` is `json` | String | `your-path/Flowise/packages/server` |
| 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:

37
Dockerfile
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@ -5,33 +5,40 @@
# 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

14
LICENSE.md
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@ -1,6 +1,14 @@
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
Copyright (c) 2023-present FlowiseAI, Inc.
Portions of this software are licensed as follows:
- All content that resides under https://github.com/FlowiseAI/Flowise/tree/main/packages/server/src/enterprise directory and files with explicit copyright notice such as [IdentityManager.ts](https://github.com/FlowiseAI/Flowise/tree/main/packages/server/src/IdentityManager.ts) are licensed under [Commercial License](https://github.com/FlowiseAI/Flowise/tree/main/packages/server/src/enterprise/LICENSE.md).
- All third party components incorporated into the FlowiseAI Software are licensed under the original license provided by the owner of the applicable component.
- Content outside of the above mentioned directories or restrictions above is available under the "Apache 2.0" license as defined below.
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION

78
README.md
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@ -5,6 +5,8 @@
<img src="https://github.com/FlowiseAI/Flowise/blob/main/images/flowise_dark.svg#gh-dark-mode-only">
</p>
<div align="center">
[![Release Notes](https://img.shields.io/github/release/FlowiseAI/Flowise)](https://github.com/FlowiseAI/Flowise/releases)
[![Discord](https://img.shields.io/discord/1087698854775881778?label=Discord&logo=discord)](https://discord.gg/jbaHfsRVBW)
[![Twitter Follow](https://img.shields.io/twitter/follow/FlowiseAI?style=social)](https://twitter.com/FlowiseAI)
@ -13,10 +15,25 @@
English | [繁體中文](./i18n/README-TW.md) | [简体中文](./i18n/README-ZH.md) | [日本語](./i18n/README-JA.md) | [한국어](./i18n/README-KR.md)
</div>
<h3>Build AI Agents, Visually</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>
## 📚 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
Download and Install [NodeJS](https://nodejs.org/en/download) >= 18.15.0
@ -31,12 +48,6 @@ Download and Install [NodeJS](https://nodejs.org/en/download) >= 18.15.0
npx flowise start
```
With username & password
```bash
npx flowise start --FLOWISE_USERNAME=user --FLOWISE_PASSWORD=1234
```
3. Open [http://localhost:3000](http://localhost:3000)
## 🐳 Docker
@ -53,9 +64,11 @@ 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
@ -63,6 +76,7 @@ Download and Install [NodeJS](https://nodejs.org/en/download) >= 18.15.0
```
3. Stop image:
```bash
docker stop flowise
```
@ -85,13 +99,13 @@ Flowise has 3 different modules in a single mono repository.
### Setup
1. Clone the repository
1. Clone the repository:
```bash
git clone https://github.com/FlowiseAI/Flowise.git
```
2. Go into repository folder
2. Go into repository folder:
```bash
cd Flowise
@ -111,10 +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>
@ -130,7 +158,7 @@ Flowise has 3 different modules in a single mono repository.
- Create `.env` file and specify the `VITE_PORT` (refer to `.env.example`) in `packages/ui`
- Create `.env` file and specify the `PORT` (refer to `.env.example`) in `packages/server`
- Run
- Run:
```bash
pnpm dev
@ -138,22 +166,13 @@ Flowise has 3 different modules in a single mono repository.
Any code changes will reload the app automatically on [http://localhost:8080](http://localhost:8080)
## 🔒 Authentication
To enable app level authentication, add `FLOWISE_USERNAME` and `FLOWISE_PASSWORD` to the `.env` file in `packages/server`:
```
FLOWISE_USERNAME=user
FLOWISE_PASSWORD=1234
```
## 🌱 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://github.com/FlowiseAI/Flowise/blob/main/CONTRIBUTING.md#-env-variables)
Flowise supports different environment variables to configure your instance. You can specify the following variables in the `.env` file inside `packages/server` folder. Read [more](https://github.com/FlowiseAI/Flowise/blob/main/CONTRIBUTING.md#-env-variables)
## 📖 Documentation
[Flowise Docs](https://docs.flowiseai.com/)
You can view the Flowise Docs [here](https://docs.flowiseai.com/)
## 🌐 Self Host
@ -171,6 +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)
@ -195,11 +218,11 @@ Deploy Flowise self-hosted in your existing infrastructure, we support various [
## ☁️ Flowise Cloud
[Get Started with Flowise Cloud](https://flowiseai.com/)
Get Started with [Flowise Cloud](https://flowiseai.com/).
## 🙋 Support
Feel free to ask any questions, raise problems, and request new features in [discussion](https://github.com/FlowiseAI/Flowise/discussions)
Feel free to ask any questions, raise problems, and request new features in [Discussion](https://github.com/FlowiseAI/Flowise/discussions).
## 🙌 Contributing
@ -207,9 +230,10 @@ Thanks go to these awesome contributors
<a href="https://github.com/FlowiseAI/Flowise/graphs/contributors">
<img src="https://contrib.rocks/image?repo=FlowiseAI/Flowise" />
</a>
</a><br><br>
See [Contributing Guide](CONTRIBUTING.md). Reach out to us at [Discord](https://discord.gg/jbaHfsRVBW) if you have any questions or issues.
See [contributing guide](CONTRIBUTING.md). Reach out to us at [Discord](https://discord.gg/jbaHfsRVBW) if you have any questions or issues.
[![Star History Chart](https://api.star-history.com/svg?repos=FlowiseAI/Flowise&type=Timeline)](https://star-history.com/#FlowiseAI/Flowise&Date)
## 📄 License

46
SECURITY.md
View File

@ -2,39 +2,37 @@
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
- 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
- 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
- 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.

149
docker/.env.example
View File

@ -1,16 +1,12 @@
PORT=3000
# APIKEY_PATH=/your_apikey_path/.flowise # (will be deprecated by end of 2025)
############################################################################################################
############################################## DATABASE ####################################################
############################################################################################################
DATABASE_PATH=/root/.flowise
APIKEY_PATH=/root/.flowise
SECRETKEY_PATH=/root/.flowise
LOG_PATH=/root/.flowise/logs
BLOB_STORAGE_PATH=/root/.flowise/storage
# APIKEY_STORAGE_TYPE=json (json | db)
# NUMBER_OF_PROXIES= 1
# CORS_ORIGINS=*
# IFRAME_ORIGINS=*
# DATABASE_TYPE=postgres
# DATABASE_PORT=5432
# DATABASE_HOST=""
@ -18,36 +14,43 @@ BLOB_STORAGE_PATH=/root/.flowise/storage
# DATABASE_USER=root
# DATABASE_PASSWORD=mypassword
# DATABASE_SSL=true
# DATABASE_REJECT_UNAUTHORIZED=true
# DATABASE_SSL_KEY_BASE64=<Self signed certificate in BASE64>
############################################################################################################
############################################## SECRET KEYS #################################################
############################################################################################################
# SECRETKEY_STORAGE_TYPE=local #(local | aws)
# SECRETKEY_PATH=/your_api_key_path/.flowise
# FLOWISE_SECRETKEY_OVERWRITE=myencryptionkey
SECRETKEY_PATH=/root/.flowise
# FLOWISE_SECRETKEY_OVERWRITE=myencryptionkey # (if you want to overwrite the secret key)
# SECRETKEY_AWS_ACCESS_KEY=<your-access-key>
# SECRETKEY_AWS_SECRET_KEY=<your-secret-key>
# SECRETKEY_AWS_REGION=us-west-2
# SECRETKEY_AWS_NAME=FlowiseEncryptionKey
# FLOWISE_USERNAME=user
# FLOWISE_PASSWORD=1234
# FLOWISE_SECRETKEY_OVERWRITE=myencryptionkey
# FLOWISE_FILE_SIZE_LIMIT=50mb
############################################################################################################
############################################## LOGGING #####################################################
############################################################################################################
# DEBUG=true
# LOG_LEVEL=info (error | warn | info | verbose | debug)
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
# LANGCHAIN_TRACING_V2=true
# LANGCHAIN_ENDPOINT=https://api.smith.langchain.com
# LANGCHAIN_API_KEY=your_api_key
# LANGCHAIN_PROJECT=your_project
# Uncomment the following line to enable model list config, load the list of models from your local config file
# see https://raw.githubusercontent.com/FlowiseAI/Flowise/main/packages/components/models.json for the format
# MODEL_LIST_CONFIG_JSON=/your_model_list_config_file_path
############################################################################################################
############################################## STORAGE #####################################################
############################################################################################################
# STORAGE_TYPE=local (local | s3 | gcs)
# BLOB_STORAGE_PATH=/your_storage_path/.flowise/storage
BLOB_STORAGE_PATH=/root/.flowise/storage
# S3_STORAGE_BUCKET_NAME=flowise
# S3_STORAGE_ACCESS_KEY_ID=<your-access-key>
# S3_STORAGE_SECRET_ACCESS_KEY=<your-secret-key>
@ -59,12 +62,70 @@ BLOB_STORAGE_PATH=/root/.flowise/storage
# GOOGLE_CLOUD_STORAGE_BUCKET_NAME=<the-bucket-name>
# GOOGLE_CLOUD_UNIFORM_BUCKET_ACCESS=true
# SHOW_COMMUNITY_NODES=true
# DISABLED_NODES=bufferMemory,chatOpenAI (comma separated list of node names to disable)
######################
# METRICS COLLECTION
#######################
############################################################################################################
############################################## SETTINGS ####################################################
############################################################################################################
# NUMBER_OF_PROXIES= 1
# CORS_ORIGINS=*
# IFRAME_ORIGINS=*
# FLOWISE_FILE_SIZE_LIMIT=50mb
# SHOW_COMMUNITY_NODES=true
# DISABLE_FLOWISE_TELEMETRY=true
# DISABLED_NODES=bufferMemory,chatOpenAI (comma separated list of node names to disable)
# Uncomment the following line to enable model list config, load the list of models from your local config file
# see https://raw.githubusercontent.com/FlowiseAI/Flowise/main/packages/components/models.json for the format
# MODEL_LIST_CONFIG_JSON=/your_model_list_config_file_path
############################################################################################################
############################################ AUTH PARAMETERS ###############################################
############################################################################################################
# APP_URL=http://localhost:3000
# SMTP_HOST=smtp.host.com
# SMTP_PORT=465
# SMTP_USER=smtp_user
# SMTP_PASSWORD=smtp_password
# SMTP_SECURE=true
# ALLOW_UNAUTHORIZED_CERTS=false
# SENDER_EMAIL=team@example.com
JWT_AUTH_TOKEN_SECRET='AABBCCDDAABBCCDDAABBCCDDAABBCCDDAABBCCDD'
JWT_REFRESH_TOKEN_SECRET='AABBCCDDAABBCCDDAABBCCDDAABBCCDDAABBCCDD'
JWT_ISSUER='ISSUER'
JWT_AUDIENCE='AUDIENCE'
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
# PASSWORD_SALT_HASH_ROUNDS=10
# TOKEN_HASH_SECRET='popcorn'
# WORKSPACE_INVITE_TEMPLATE_PATH=/path/to/custom/workspace_invite.hbs
############################################################################################################
############################################# ENTERPRISE ###################################################
############################################################################################################
# LICENSE_URL=
# FLOWISE_EE_LICENSE_KEY=
# OFFLINE=
############################################################################################################
########################################### METRICS COLLECTION #############################################
############################################################################################################
# POSTHOG_PUBLIC_API_KEY=your_posthog_public_api_key
# ENABLE_METRICS=false
# METRICS_PROVIDER=prometheus # prometheus | open_telemetry
# METRICS_INCLUDE_NODE_METRICS=true # default is true
@ -75,15 +136,21 @@ BLOB_STORAGE_PATH=/root/.flowise/storage
# METRICS_OPEN_TELEMETRY_PROTOCOL=http # http | grpc | proto (default is http)
# METRICS_OPEN_TELEMETRY_DEBUG=true # default is false
# Uncomment the following lines to enable global agent proxy
# see https://www.npmjs.com/package/global-agent for more details
############################################################################################################
############################################### PROXY ######################################################
############################################################################################################
# Uncomment the following lines to enable global agent proxy, see https://www.npmjs.com/package/global-agent for more details
# GLOBAL_AGENT_HTTP_PROXY=CorporateHttpProxyUrl
# GLOBAL_AGENT_HTTPS_PROXY=CorporateHttpsProxyUrl
# GLOBAL_AGENT_NO_PROXY=ExceptionHostsToBypassProxyIfNeeded
######################
# QUEUE CONFIGURATION
#######################
############################################################################################################
########################################### QUEUE CONFIGURATION ############################################
############################################################################################################
# MODE=queue #(queue | main)
# QUEUE_NAME=flowise-queue
# QUEUE_REDIS_EVENT_STREAM_MAX_LEN=100000
@ -101,3 +168,13 @@ BLOB_STORAGE_PATH=/root/.flowise/storage
# REDIS_CA=
# REDIS_KEEP_ALIVE=
# 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)

49
docker/README.md
View File

@ -9,28 +9,43 @@ Starts Flowise from [DockerHub Image](https://hub.docker.com/r/flowiseai/flowise
3. Open [http://localhost:3000](http://localhost:3000)
4. You can bring the containers down by `docker compose stop`
## 🔒 Authentication
1. Create `.env` file and specify the `PORT`, `FLOWISE_USERNAME`, and `FLOWISE_PASSWORD` (refer to `.env.example`)
2. Pass `FLOWISE_USERNAME` and `FLOWISE_PASSWORD` to the `docker-compose.yml` file:
```
environment:
- PORT=${PORT}
- FLOWISE_USERNAME=${FLOWISE_USERNAME}
- FLOWISE_PASSWORD=${FLOWISE_PASSWORD}
```
3. `docker compose up -d`
4. Open [http://localhost:3000](http://localhost:3000)
5. You can bring the containers down by `docker compose stop`
## 🌱 Env Variables
If you like to persist your data (flows, logs, apikeys, credentials), set these variables in the `.env` file inside `docker` folder:
If you like to persist your data (flows, logs, credentials, storage), set these variables in the `.env` file inside `docker` folder:
- DATABASE_PATH=/root/.flowise
- APIKEY_PATH=/root/.flowise
- LOG_PATH=/root/.flowise/logs
- 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:
### Building from source:
You can build the images for worker and main from scratch with:
```
docker compose -f docker-compose-queue-source.yml up -d
```
Monitor Health:
```
docker compose -f docker-compose-queue-source.yml ps
```
### From pre-built images:
You can also use the pre-built images:
```
docker compose -f docker-compose-queue-prebuilt.yml up -d
```
Monitor Health:
```
docker compose -f docker-compose-queue-prebuilt.yml ps
```

316
docker/docker-compose-queue-prebuilt.yml Normal file
View File

@ -0,0 +1,316 @@
version: '3.1'
services:
redis:
image: redis:alpine
container_name: flowise-redis
ports:
- '6379:6379'
volumes:
- redis_data:/data
networks:
- flowise-net
restart: always
flowise:
image: flowiseai/flowise:latest
container_name: flowise-main
restart: always
ports:
- '${PORT:-3000}:${PORT:-3000}'
volumes:
- ~/.flowise:/root/.flowise
environment:
# --- Essential Flowise Vars ---
- PORT=${PORT:-3000}
- DATABASE_PATH=${DATABASE_PATH:-/root/.flowise}
- DATABASE_TYPE=${DATABASE_TYPE}
- DATABASE_PORT=${DATABASE_PORT}
- DATABASE_HOST=${DATABASE_HOST}
- DATABASE_NAME=${DATABASE_NAME}
- DATABASE_USER=${DATABASE_USER}
- DATABASE_PASSWORD=${DATABASE_PASSWORD}
- DATABASE_SSL=${DATABASE_SSL}
- DATABASE_SSL_KEY_BASE64=${DATABASE_SSL_KEY_BASE64}
# SECRET KEYS
- SECRETKEY_STORAGE_TYPE=${SECRETKEY_STORAGE_TYPE}
- SECRETKEY_PATH=${SECRETKEY_PATH}
- FLOWISE_SECRETKEY_OVERWRITE=${FLOWISE_SECRETKEY_OVERWRITE}
- SECRETKEY_AWS_ACCESS_KEY=${SECRETKEY_AWS_ACCESS_KEY}
- SECRETKEY_AWS_SECRET_KEY=${SECRETKEY_AWS_SECRET_KEY}
- SECRETKEY_AWS_REGION=${SECRETKEY_AWS_REGION}
- SECRETKEY_AWS_NAME=${SECRETKEY_AWS_NAME}
# LOGGING
- DEBUG=${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/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}
- BLOB_STORAGE_PATH=${BLOB_STORAGE_PATH}
- S3_STORAGE_BUCKET_NAME=${S3_STORAGE_BUCKET_NAME}
- S3_STORAGE_ACCESS_KEY_ID=${S3_STORAGE_ACCESS_KEY_ID}
- S3_STORAGE_SECRET_ACCESS_KEY=${S3_STORAGE_SECRET_ACCESS_KEY}
- S3_STORAGE_REGION=${S3_STORAGE_REGION}
- S3_ENDPOINT_URL=${S3_ENDPOINT_URL}
- S3_FORCE_PATH_STYLE=${S3_FORCE_PATH_STYLE}
- GOOGLE_CLOUD_STORAGE_CREDENTIAL=${GOOGLE_CLOUD_STORAGE_CREDENTIAL}
- GOOGLE_CLOUD_STORAGE_PROJ_ID=${GOOGLE_CLOUD_STORAGE_PROJ_ID}
- GOOGLE_CLOUD_STORAGE_BUCKET_NAME=${GOOGLE_CLOUD_STORAGE_BUCKET_NAME}
- GOOGLE_CLOUD_UNIFORM_BUCKET_ACCESS=${GOOGLE_CLOUD_UNIFORM_BUCKET_ACCESS}
# SETTINGS
- NUMBER_OF_PROXIES=${NUMBER_OF_PROXIES}
- CORS_ORIGINS=${CORS_ORIGINS}
- IFRAME_ORIGINS=${IFRAME_ORIGINS}
- FLOWISE_FILE_SIZE_LIMIT=${FLOWISE_FILE_SIZE_LIMIT}
- SHOW_COMMUNITY_NODES=${SHOW_COMMUNITY_NODES}
- DISABLE_FLOWISE_TELEMETRY=${DISABLE_FLOWISE_TELEMETRY}
- DISABLED_NODES=${DISABLED_NODES}
- MODEL_LIST_CONFIG_JSON=${MODEL_LIST_CONFIG_JSON}
# AUTH PARAMETERS
- APP_URL=${APP_URL}
- JWT_AUTH_TOKEN_SECRET=${JWT_AUTH_TOKEN_SECRET}
- JWT_REFRESH_TOKEN_SECRET=${JWT_REFRESH_TOKEN_SECRET}
- JWT_ISSUER=${JWT_ISSUER}
- JWT_AUDIENCE=${JWT_AUDIENCE}
- JWT_TOKEN_EXPIRY_IN_MINUTES=${JWT_TOKEN_EXPIRY_IN_MINUTES}
- JWT_REFRESH_TOKEN_EXPIRY_IN_MINUTES=${JWT_REFRESH_TOKEN_EXPIRY_IN_MINUTES}
- EXPIRE_AUTH_TOKENS_ON_RESTART=${EXPIRE_AUTH_TOKENS_ON_RESTART}
- EXPRESS_SESSION_SECRET=${EXPRESS_SESSION_SECRET}
- 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=${SMTP_HOST}
- SMTP_PORT=${SMTP_PORT}
- SMTP_USER=${SMTP_USER}
- SMTP_PASSWORD=${SMTP_PASSWORD}
- SMTP_SECURE=${SMTP_SECURE}
- ALLOW_UNAUTHORIZED_CERTS=${ALLOW_UNAUTHORIZED_CERTS}
- SENDER_EMAIL=${SENDER_EMAIL}
# ENTERPRISE
- LICENSE_URL=${LICENSE_URL}
- FLOWISE_EE_LICENSE_KEY=${FLOWISE_EE_LICENSE_KEY}
- OFFLINE=${OFFLINE}
- INVITE_TOKEN_EXPIRY_IN_HOURS=${INVITE_TOKEN_EXPIRY_IN_HOURS}
- WORKSPACE_INVITE_TEMPLATE_PATH=${WORKSPACE_INVITE_TEMPLATE_PATH}
# METRICS COLLECTION
- POSTHOG_PUBLIC_API_KEY=${POSTHOG_PUBLIC_API_KEY}
- ENABLE_METRICS=${ENABLE_METRICS}
- METRICS_PROVIDER=${METRICS_PROVIDER}
- METRICS_INCLUDE_NODE_METRICS=${METRICS_INCLUDE_NODE_METRICS}
- METRICS_SERVICE_NAME=${METRICS_SERVICE_NAME}
- METRICS_OPEN_TELEMETRY_METRIC_ENDPOINT=${METRICS_OPEN_TELEMETRY_METRIC_ENDPOINT}
- METRICS_OPEN_TELEMETRY_PROTOCOL=${METRICS_OPEN_TELEMETRY_PROTOCOL}
- METRICS_OPEN_TELEMETRY_DEBUG=${METRICS_OPEN_TELEMETRY_DEBUG}
# PROXY
- GLOBAL_AGENT_HTTP_PROXY=${GLOBAL_AGENT_HTTP_PROXY}
- GLOBAL_AGENT_HTTPS_PROXY=${GLOBAL_AGENT_HTTPS_PROXY}
- GLOBAL_AGENT_NO_PROXY=${GLOBAL_AGENT_NO_PROXY}
# --- Queue Configuration (Main Instance) ---
- MODE=${MODE:-queue}
- QUEUE_NAME=${QUEUE_NAME:-flowise-queue}
- QUEUE_REDIS_EVENT_STREAM_MAX_LEN=${QUEUE_REDIS_EVENT_STREAM_MAX_LEN}
- WORKER_CONCURRENCY=${WORKER_CONCURRENCY}
- REMOVE_ON_AGE=${REMOVE_ON_AGE}
- REMOVE_ON_COUNT=${REMOVE_ON_COUNT}
- REDIS_URL=${REDIS_URL:-redis://redis:6379}
- REDIS_HOST=${REDIS_HOST}
- REDIS_PORT=${REDIS_PORT}
- REDIS_USERNAME=${REDIS_USERNAME}
- REDIS_PASSWORD=${REDIS_PASSWORD}
- REDIS_TLS=${REDIS_TLS}
- REDIS_CERT=${REDIS_CERT}
- REDIS_KEY=${REDIS_KEY}
- REDIS_CA=${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:${PORT:-3000}/api/v1/ping']
interval: 10s
timeout: 5s
retries: 5
start_period: 30s
entrypoint: /bin/sh -c "sleep 3; flowise start"
depends_on:
- redis
networks:
- flowise-net
flowise-worker:
image: flowiseai/flowise-worker:latest
container_name: flowise-worker
restart: always
volumes:
- ~/.flowise:/root/.flowise
environment:
# --- Essential Flowise Vars ---
- WORKER_PORT=${WORKER_PORT:-5566}
- DATABASE_PATH=${DATABASE_PATH:-/root/.flowise}
- DATABASE_TYPE=${DATABASE_TYPE}
- DATABASE_PORT=${DATABASE_PORT}
- DATABASE_HOST=${DATABASE_HOST}
- DATABASE_NAME=${DATABASE_NAME}
- DATABASE_USER=${DATABASE_USER}
- DATABASE_PASSWORD=${DATABASE_PASSWORD}
- DATABASE_SSL=${DATABASE_SSL}
- DATABASE_SSL_KEY_BASE64=${DATABASE_SSL_KEY_BASE64}
# SECRET KEYS
- SECRETKEY_STORAGE_TYPE=${SECRETKEY_STORAGE_TYPE}
- SECRETKEY_PATH=${SECRETKEY_PATH}
- FLOWISE_SECRETKEY_OVERWRITE=${FLOWISE_SECRETKEY_OVERWRITE}
- SECRETKEY_AWS_ACCESS_KEY=${SECRETKEY_AWS_ACCESS_KEY}
- SECRETKEY_AWS_SECRET_KEY=${SECRETKEY_AWS_SECRET_KEY}
- SECRETKEY_AWS_REGION=${SECRETKEY_AWS_REGION}
- SECRETKEY_AWS_NAME=${SECRETKEY_AWS_NAME}
# LOGGING
- DEBUG=${DEBUG}
- LOG_PATH=${LOG_PATH}
- LOG_LEVEL=${LOG_LEVEL}
- LOG_SANITIZE_BODY_FIELDS=${LOG_SANITIZE_BODY_FIELDS}
- LOG_SANITIZE_HEADER_FIELDS=${LOG_SANITIZE_HEADER_FIELDS}
# CUSTOM TOOL/FUNCTION DEPENDENCIES
- TOOL_FUNCTION_BUILTIN_DEP=${TOOL_FUNCTION_BUILTIN_DEP}
- TOOL_FUNCTION_EXTERNAL_DEP=${TOOL_FUNCTION_EXTERNAL_DEP}
- ALLOW_BUILTIN_DEP=${ALLOW_BUILTIN_DEP}
# STORAGE
- STORAGE_TYPE=${STORAGE_TYPE}
- BLOB_STORAGE_PATH=${BLOB_STORAGE_PATH}
- S3_STORAGE_BUCKET_NAME=${S3_STORAGE_BUCKET_NAME}
- S3_STORAGE_ACCESS_KEY_ID=${S3_STORAGE_ACCESS_KEY_ID}
- S3_STORAGE_SECRET_ACCESS_KEY=${S3_STORAGE_SECRET_ACCESS_KEY}
- S3_STORAGE_REGION=${S3_STORAGE_REGION}
- S3_ENDPOINT_URL=${S3_ENDPOINT_URL}
- S3_FORCE_PATH_STYLE=${S3_FORCE_PATH_STYLE}
- GOOGLE_CLOUD_STORAGE_CREDENTIAL=${GOOGLE_CLOUD_STORAGE_CREDENTIAL}
- GOOGLE_CLOUD_STORAGE_PROJ_ID=${GOOGLE_CLOUD_STORAGE_PROJ_ID}
- GOOGLE_CLOUD_STORAGE_BUCKET_NAME=${GOOGLE_CLOUD_STORAGE_BUCKET_NAME}
- GOOGLE_CLOUD_UNIFORM_BUCKET_ACCESS=${GOOGLE_CLOUD_UNIFORM_BUCKET_ACCESS}
# SETTINGS
- NUMBER_OF_PROXIES=${NUMBER_OF_PROXIES}
- CORS_ORIGINS=${CORS_ORIGINS}
- IFRAME_ORIGINS=${IFRAME_ORIGINS}
- FLOWISE_FILE_SIZE_LIMIT=${FLOWISE_FILE_SIZE_LIMIT}
- SHOW_COMMUNITY_NODES=${SHOW_COMMUNITY_NODES}
- DISABLE_FLOWISE_TELEMETRY=${DISABLE_FLOWISE_TELEMETRY}
- DISABLED_NODES=${DISABLED_NODES}
- MODEL_LIST_CONFIG_JSON=${MODEL_LIST_CONFIG_JSON}
# AUTH PARAMETERS
- APP_URL=${APP_URL}
- JWT_AUTH_TOKEN_SECRET=${JWT_AUTH_TOKEN_SECRET}
- JWT_REFRESH_TOKEN_SECRET=${JWT_REFRESH_TOKEN_SECRET}
- JWT_ISSUER=${JWT_ISSUER}
- JWT_AUDIENCE=${JWT_AUDIENCE}
- JWT_TOKEN_EXPIRY_IN_MINUTES=${JWT_TOKEN_EXPIRY_IN_MINUTES}
- JWT_REFRESH_TOKEN_EXPIRY_IN_MINUTES=${JWT_REFRESH_TOKEN_EXPIRY_IN_MINUTES}
- EXPIRE_AUTH_TOKENS_ON_RESTART=${EXPIRE_AUTH_TOKENS_ON_RESTART}
- EXPRESS_SESSION_SECRET=${EXPRESS_SESSION_SECRET}
- PASSWORD_RESET_TOKEN_EXPIRY_IN_MINS=${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}
- SMTP_PORT=${SMTP_PORT}
- SMTP_USER=${SMTP_USER}
- SMTP_PASSWORD=${SMTP_PASSWORD}
- SMTP_SECURE=${SMTP_SECURE}
- ALLOW_UNAUTHORIZED_CERTS=${ALLOW_UNAUTHORIZED_CERTS}
- SENDER_EMAIL=${SENDER_EMAIL}
# ENTERPRISE
- LICENSE_URL=${LICENSE_URL}
- FLOWISE_EE_LICENSE_KEY=${FLOWISE_EE_LICENSE_KEY}
- OFFLINE=${OFFLINE}
- INVITE_TOKEN_EXPIRY_IN_HOURS=${INVITE_TOKEN_EXPIRY_IN_HOURS}
- WORKSPACE_INVITE_TEMPLATE_PATH=${WORKSPACE_INVITE_TEMPLATE_PATH}
# METRICS COLLECTION
- POSTHOG_PUBLIC_API_KEY=${POSTHOG_PUBLIC_API_KEY}
- ENABLE_METRICS=${ENABLE_METRICS}
- METRICS_PROVIDER=${METRICS_PROVIDER}
- METRICS_INCLUDE_NODE_METRICS=${METRICS_INCLUDE_NODE_METRICS}
- METRICS_SERVICE_NAME=${METRICS_SERVICE_NAME}
- METRICS_OPEN_TELEMETRY_METRIC_ENDPOINT=${METRICS_OPEN_TELEMETRY_METRIC_ENDPOINT}
- METRICS_OPEN_TELEMETRY_PROTOCOL=${METRICS_OPEN_TELEMETRY_PROTOCOL}
- METRICS_OPEN_TELEMETRY_DEBUG=${METRICS_OPEN_TELEMETRY_DEBUG}
# PROXY
- GLOBAL_AGENT_HTTP_PROXY=${GLOBAL_AGENT_HTTP_PROXY}
- GLOBAL_AGENT_HTTPS_PROXY=${GLOBAL_AGENT_HTTPS_PROXY}
- GLOBAL_AGENT_NO_PROXY=${GLOBAL_AGENT_NO_PROXY}
# --- Queue Configuration (Worker Instance) ---
- MODE=${MODE:-queue}
- QUEUE_NAME=${QUEUE_NAME:-flowise-queue}
- QUEUE_REDIS_EVENT_STREAM_MAX_LEN=${QUEUE_REDIS_EVENT_STREAM_MAX_LEN}
- WORKER_CONCURRENCY=${WORKER_CONCURRENCY}
- REMOVE_ON_AGE=${REMOVE_ON_AGE}
- REMOVE_ON_COUNT=${REMOVE_ON_COUNT}
- REDIS_URL=${REDIS_URL:-redis://redis:6379}
- REDIS_HOST=${REDIS_HOST}
- REDIS_PORT=${REDIS_PORT}
- REDIS_USERNAME=${REDIS_USERNAME}
- REDIS_PASSWORD=${REDIS_PASSWORD}
- REDIS_TLS=${REDIS_TLS}
- REDIS_CERT=${REDIS_CERT}
- REDIS_KEY=${REDIS_KEY}
- 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
timeout: 5s
retries: 5
start_period: 30s
entrypoint: /bin/sh -c "node /app/healthcheck/healthcheck.js & sleep 5 && pnpm run start-worker"
depends_on:
- redis
- flowise
networks:
- flowise-net
volumes:
redis_data:
driver: local
networks:
flowise-net:
driver: bridge

71
docker/docker-compose-queue-source.yml Normal file
View File

@ -0,0 +1,71 @@
version: '3.1'
services:
redis:
image: redis:alpine
container_name: flowise-redis
ports:
- '6379:6379'
volumes:
- redis_data:/data
networks:
- flowise-net
flowise:
container_name: flowise-main
build:
context: .. # Build using the Dockerfile in the root directory
dockerfile: docker/Dockerfile
ports:
- '${PORT}:${PORT}'
volumes:
# Mount local .flowise to container's default location
- ../.flowise:/root/.flowise
environment:
# --- Essential Flowise Vars ---
- PORT=${PORT:-3000}
- DATABASE_PATH=/root/.flowise
- SECRETKEY_PATH=/root/.flowise
- LOG_PATH=/root/.flowise/logs
- BLOB_STORAGE_PATH=/root/.flowise/storage
# --- Queue Vars (Main Instance) ---
- MODE=queue
- QUEUE_NAME=flowise-queue # Ensure this matches worker
- REDIS_URL=redis://redis:6379 # Use service name 'redis'
depends_on:
- redis
networks:
- flowise-net
flowise-worker:
container_name: flowise-worker
build:
context: .. # Build context is still the root
dockerfile: docker/worker/Dockerfile # Ensure this path is correct
volumes:
# Mount same local .flowise to worker
- ../.flowise:/root/.flowise
environment:
# --- Essential Flowise Vars ---
- WORKER_PORT=${WORKER_PORT:-5566} # Port for worker healthcheck
- DATABASE_PATH=/root/.flowise
- SECRETKEY_PATH=/root/.flowise
- LOG_PATH=/root/.flowise/logs
- BLOB_STORAGE_PATH=/root/.flowise/storage
# --- Queue Vars (Main Instance) ---
- MODE=queue
- QUEUE_NAME=flowise-queue # Ensure this matches worker
- REDIS_URL=redis://redis:6379 # Use service name 'redis'
depends_on:
- redis
- flowise
networks:
- flowise-net
volumes:
redis_data:
driver: local
networks:
flowise-net:
driver: bridge

109
docker/docker-compose.yml
View File

@ -2,16 +2,12 @@ version: '3.1'
services:
flowise:
image: flowiseai/flowise
image: flowiseai/flowise:latest
restart: always
environment:
- PORT=${PORT}
- CORS_ORIGINS=${CORS_ORIGINS}
- IFRAME_ORIGINS=${IFRAME_ORIGINS}
- FLOWISE_USERNAME=${FLOWISE_USERNAME}
- FLOWISE_PASSWORD=${FLOWISE_PASSWORD}
- FLOWISE_FILE_SIZE_LIMIT=${FLOWISE_FILE_SIZE_LIMIT}
- DEBUG=${DEBUG}
# DATABASE
- DATABASE_PATH=${DATABASE_PATH}
- DATABASE_TYPE=${DATABASE_TYPE}
- DATABASE_PORT=${DATABASE_PORT}
@ -21,35 +17,122 @@ services:
- DATABASE_PASSWORD=${DATABASE_PASSWORD}
- DATABASE_SSL=${DATABASE_SSL}
- DATABASE_SSL_KEY_BASE64=${DATABASE_SSL_KEY_BASE64}
- APIKEY_STORAGE_TYPE=${APIKEY_STORAGE_TYPE}
- APIKEY_PATH=${APIKEY_PATH}
# SECRET KEYS
- SECRETKEY_STORAGE_TYPE=${SECRETKEY_STORAGE_TYPE}
- SECRETKEY_PATH=${SECRETKEY_PATH}
- FLOWISE_SECRETKEY_OVERWRITE=${FLOWISE_SECRETKEY_OVERWRITE}
- LOG_LEVEL=${LOG_LEVEL}
- SECRETKEY_AWS_ACCESS_KEY=${SECRETKEY_AWS_ACCESS_KEY}
- SECRETKEY_AWS_SECRET_KEY=${SECRETKEY_AWS_SECRET_KEY}
- SECRETKEY_AWS_REGION=${SECRETKEY_AWS_REGION}
- SECRETKEY_AWS_NAME=${SECRETKEY_AWS_NAME}
# LOGGING
- DEBUG=${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/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}
- BLOB_STORAGE_PATH=${BLOB_STORAGE_PATH}
- S3_STORAGE_BUCKET_NAME=${S3_STORAGE_BUCKET_NAME}
- S3_STORAGE_ACCESS_KEY_ID=${S3_STORAGE_ACCESS_KEY_ID}
- S3_STORAGE_SECRET_ACCESS_KEY=${S3_STORAGE_SECRET_ACCESS_KEY}
- S3_STORAGE_REGION=${S3_STORAGE_REGION}
- S3_ENDPOINT_URL=${S3_ENDPOINT_URL}
- S3_FORCE_PATH_STYLE=${S3_FORCE_PATH_STYLE}
- GOOGLE_CLOUD_STORAGE_CREDENTIAL=${GOOGLE_CLOUD_STORAGE_CREDENTIAL}
- GOOGLE_CLOUD_STORAGE_PROJ_ID=${GOOGLE_CLOUD_STORAGE_PROJ_ID}
- GOOGLE_CLOUD_STORAGE_BUCKET_NAME=${GOOGLE_CLOUD_STORAGE_BUCKET_NAME}
- GOOGLE_CLOUD_UNIFORM_BUCKET_ACCESS=${GOOGLE_CLOUD_UNIFORM_BUCKET_ACCESS}
# SETTINGS
- NUMBER_OF_PROXIES=${NUMBER_OF_PROXIES}
- CORS_ORIGINS=${CORS_ORIGINS}
- IFRAME_ORIGINS=${IFRAME_ORIGINS}
- FLOWISE_FILE_SIZE_LIMIT=${FLOWISE_FILE_SIZE_LIMIT}
- SHOW_COMMUNITY_NODES=${SHOW_COMMUNITY_NODES}
- DISABLE_FLOWISE_TELEMETRY=${DISABLE_FLOWISE_TELEMETRY}
- DISABLED_NODES=${DISABLED_NODES}
- MODEL_LIST_CONFIG_JSON=${MODEL_LIST_CONFIG_JSON}
# AUTH PARAMETERS
- APP_URL=${APP_URL}
- JWT_AUTH_TOKEN_SECRET=${JWT_AUTH_TOKEN_SECRET}
- JWT_REFRESH_TOKEN_SECRET=${JWT_REFRESH_TOKEN_SECRET}
- JWT_ISSUER=${JWT_ISSUER}
- JWT_AUDIENCE=${JWT_AUDIENCE}
- JWT_TOKEN_EXPIRY_IN_MINUTES=${JWT_TOKEN_EXPIRY_IN_MINUTES}
- JWT_REFRESH_TOKEN_EXPIRY_IN_MINUTES=${JWT_REFRESH_TOKEN_EXPIRY_IN_MINUTES}
- EXPIRE_AUTH_TOKENS_ON_RESTART=${EXPIRE_AUTH_TOKENS_ON_RESTART}
- EXPRESS_SESSION_SECRET=${EXPRESS_SESSION_SECRET}
- 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=${SMTP_HOST}
- SMTP_PORT=${SMTP_PORT}
- SMTP_USER=${SMTP_USER}
- SMTP_PASSWORD=${SMTP_PASSWORD}
- SMTP_SECURE=${SMTP_SECURE}
- ALLOW_UNAUTHORIZED_CERTS=${ALLOW_UNAUTHORIZED_CERTS}
- SENDER_EMAIL=${SENDER_EMAIL}
# ENTERPRISE
- LICENSE_URL=${LICENSE_URL}
- FLOWISE_EE_LICENSE_KEY=${FLOWISE_EE_LICENSE_KEY}
- OFFLINE=${OFFLINE}
- INVITE_TOKEN_EXPIRY_IN_HOURS=${INVITE_TOKEN_EXPIRY_IN_HOURS}
- WORKSPACE_INVITE_TEMPLATE_PATH=${WORKSPACE_INVITE_TEMPLATE_PATH}
# METRICS COLLECTION
- POSTHOG_PUBLIC_API_KEY=${POSTHOG_PUBLIC_API_KEY}
- ENABLE_METRICS=${ENABLE_METRICS}
- METRICS_PROVIDER=${METRICS_PROVIDER}
- METRICS_INCLUDE_NODE_METRICS=${METRICS_INCLUDE_NODE_METRICS}
- METRICS_SERVICE_NAME=${METRICS_SERVICE_NAME}
- METRICS_OPEN_TELEMETRY_METRIC_ENDPOINT=${METRICS_OPEN_TELEMETRY_METRIC_ENDPOINT}
- METRICS_OPEN_TELEMETRY_PROTOCOL=${METRICS_OPEN_TELEMETRY_PROTOCOL}
- METRICS_OPEN_TELEMETRY_DEBUG=${METRICS_OPEN_TELEMETRY_DEBUG}
# PROXY
- GLOBAL_AGENT_HTTP_PROXY=${GLOBAL_AGENT_HTTP_PROXY}
- GLOBAL_AGENT_HTTPS_PROXY=${GLOBAL_AGENT_HTTPS_PROXY}
- GLOBAL_AGENT_NO_PROXY=${GLOBAL_AGENT_NO_PROXY}
- DISABLED_NODES=${DISABLED_NODES}
# QUEUE CONFIGURATION
- MODE=${MODE}
- WORKER_CONCURRENCY=${WORKER_CONCURRENCY}
- QUEUE_NAME=${QUEUE_NAME}
- QUEUE_REDIS_EVENT_STREAM_MAX_LEN=${QUEUE_REDIS_EVENT_STREAM_MAX_LEN}
- WORKER_CONCURRENCY=${WORKER_CONCURRENCY}
- REMOVE_ON_AGE=${REMOVE_ON_AGE}
- REMOVE_ON_COUNT=${REMOVE_ON_COUNT}
- REDIS_URL=${REDIS_URL}
- REDIS_HOST=${REDIS_HOST}
- REDIS_PORT=${REDIS_PORT}
- REDIS_PASSWORD=${REDIS_PASSWORD}
- REDIS_USERNAME=${REDIS_USERNAME}
- REDIS_PASSWORD=${REDIS_PASSWORD}
- REDIS_TLS=${REDIS_TLS}
- REDIS_CERT=${REDIS_CERT}
- REDIS_KEY=${REDIS_KEY}
- 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:

180
docker/worker/.env.example Normal file
View File

@ -0,0 +1,180 @@
WORKER_PORT=5566
# APIKEY_PATH=/your_apikey_path/.flowise # (will be deprecated by end of 2025)
############################################################################################################
############################################## DATABASE ####################################################
############################################################################################################
DATABASE_PATH=/root/.flowise
# DATABASE_TYPE=postgres
# DATABASE_PORT=5432
# DATABASE_HOST=""
# DATABASE_NAME=flowise
# DATABASE_USER=root
# DATABASE_PASSWORD=mypassword
# DATABASE_SSL=true
# DATABASE_REJECT_UNAUTHORIZED=true
# DATABASE_SSL_KEY_BASE64=<Self signed certificate in BASE64>
############################################################################################################
############################################## SECRET KEYS #################################################
############################################################################################################
# SECRETKEY_STORAGE_TYPE=local #(local | aws)
SECRETKEY_PATH=/root/.flowise
# FLOWISE_SECRETKEY_OVERWRITE=myencryptionkey # (if you want to overwrite the secret key)
# SECRETKEY_AWS_ACCESS_KEY=<your-access-key>
# SECRETKEY_AWS_SECRET_KEY=<your-secret-key>
# SECRETKEY_AWS_REGION=us-west-2
# SECRETKEY_AWS_NAME=FlowiseEncryptionKey
############################################################################################################
############################################## LOGGING #####################################################
############################################################################################################
# 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
############################################################################################################
############################################## STORAGE #####################################################
############################################################################################################
# STORAGE_TYPE=local (local | s3 | gcs)
BLOB_STORAGE_PATH=/root/.flowise/storage
# S3_STORAGE_BUCKET_NAME=flowise
# S3_STORAGE_ACCESS_KEY_ID=<your-access-key>
# S3_STORAGE_SECRET_ACCESS_KEY=<your-secret-key>
# S3_STORAGE_REGION=us-west-2
# S3_ENDPOINT_URL=<custom-s3-endpoint-url>
# S3_FORCE_PATH_STYLE=false
# GOOGLE_CLOUD_STORAGE_CREDENTIAL=/the/keyfilename/path
# GOOGLE_CLOUD_STORAGE_PROJ_ID=<your-gcp-project-id>
# GOOGLE_CLOUD_STORAGE_BUCKET_NAME=<the-bucket-name>
# GOOGLE_CLOUD_UNIFORM_BUCKET_ACCESS=true
############################################################################################################
############################################## SETTINGS ####################################################
############################################################################################################
# NUMBER_OF_PROXIES= 1
# CORS_ORIGINS=*
# IFRAME_ORIGINS=*
# FLOWISE_FILE_SIZE_LIMIT=50mb
# SHOW_COMMUNITY_NODES=true
# DISABLE_FLOWISE_TELEMETRY=true
# DISABLED_NODES=bufferMemory,chatOpenAI (comma separated list of node names to disable)
# Uncomment the following line to enable model list config, load the list of models from your local config file
# see https://raw.githubusercontent.com/FlowiseAI/Flowise/main/packages/components/models.json for the format
# MODEL_LIST_CONFIG_JSON=/your_model_list_config_file_path
############################################################################################################
############################################ AUTH PARAMETERS ###############################################
############################################################################################################
# APP_URL=http://localhost:3000
# SMTP_HOST=smtp.host.com
# SMTP_PORT=465
# SMTP_USER=smtp_user
# SMTP_PASSWORD=smtp_password
# SMTP_SECURE=true
# ALLOW_UNAUTHORIZED_CERTS=false
# SENDER_EMAIL=team@example.com
JWT_AUTH_TOKEN_SECRET='AABBCCDDAABBCCDDAABBCCDDAABBCCDDAABBCCDD'
JWT_REFRESH_TOKEN_SECRET='AABBCCDDAABBCCDDAABBCCDDAABBCCDDAABBCCDD'
JWT_ISSUER='ISSUER'
JWT_AUDIENCE='AUDIENCE'
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
# PASSWORD_SALT_HASH_ROUNDS=10
# TOKEN_HASH_SECRET='popcorn'
# WORKSPACE_INVITE_TEMPLATE_PATH=/path/to/custom/workspace_invite.hbs
############################################################################################################
############################################# ENTERPRISE ###################################################
############################################################################################################
# LICENSE_URL=
# FLOWISE_EE_LICENSE_KEY=
# OFFLINE=
############################################################################################################
########################################### METRICS COLLECTION #############################################
############################################################################################################
# POSTHOG_PUBLIC_API_KEY=your_posthog_public_api_key
# ENABLE_METRICS=false
# METRICS_PROVIDER=prometheus # prometheus | open_telemetry
# METRICS_INCLUDE_NODE_METRICS=true # default is true
# METRICS_SERVICE_NAME=FlowiseAI
# ONLY NEEDED if METRICS_PROVIDER=open_telemetry
# METRICS_OPEN_TELEMETRY_METRIC_ENDPOINT=http://localhost:4318/v1/metrics
# METRICS_OPEN_TELEMETRY_PROTOCOL=http # http | grpc | proto (default is http)
# METRICS_OPEN_TELEMETRY_DEBUG=true # default is false
############################################################################################################
############################################### PROXY ######################################################
############################################################################################################
# Uncomment the following lines to enable global agent proxy, see https://www.npmjs.com/package/global-agent for more details
# GLOBAL_AGENT_HTTP_PROXY=CorporateHttpProxyUrl
# GLOBAL_AGENT_HTTPS_PROXY=CorporateHttpsProxyUrl
# GLOBAL_AGENT_NO_PROXY=ExceptionHostsToBypassProxyIfNeeded
############################################################################################################
########################################### QUEUE CONFIGURATION ############################################
############################################################################################################
# MODE=queue #(queue | main)
# QUEUE_NAME=flowise-queue
# QUEUE_REDIS_EVENT_STREAM_MAX_LEN=100000
# WORKER_CONCURRENCY=100000
# REMOVE_ON_AGE=86400
# REMOVE_ON_COUNT=10000
# REDIS_URL=
# REDIS_HOST=localhost
# REDIS_PORT=6379
# REDIS_USERNAME=
# REDIS_PASSWORD=
# REDIS_TLS=
# REDIS_CERT=
# REDIS_KEY=
# REDIS_CA=
# REDIS_KEEP_ALIVE=
# 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)

49
docker/worker/Dockerfile Normal file
View File

@ -0,0 +1,49 @@
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 and curl for container-level health checks
RUN apk add --no-cache chromium curl
#install PNPM globally
RUN 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
# Copy app source
COPY . .
RUN pnpm install
RUN pnpm build
# --- Healthcheck Setup ---
WORKDIR /app/healthcheck
COPY docker/worker/healthcheck/package.json .
RUN npm install --omit=dev
COPY docker/worker/healthcheck/healthcheck.js .
# --- End Healthcheck Setup ---
# Set the main working directory back
WORKDIR /usr/src
# Environment variables for port configuration
ENV WORKER_PORT=5566
# Expose port (can be overridden by env var)
EXPOSE ${WORKER_PORT}
# Start healthcheck in background and flowise worker in foreground
CMD ["/bin/sh", "-c", "node /app/healthcheck/healthcheck.js & sleep 5 && pnpm run start-worker"]

10
docker/worker/README.md
View File

@ -18,7 +18,11 @@ Here’s an overview of the process:
## Setting up Worker:
1. Copy paste the same `.env` file used to setup main server. Change the `PORT` to other available port numbers. Ex: 5566
2. `docker compose up -d`
3. Open [http://localhost:5566](http://localhost:5566)
1. Navigate to `docker/worker` folder
2. In the `.env.example`, setup all the necessary env variables for `QUEUE CONFIGURATION`. Env variables for worker must match the one for main server. Change the `WORKER_PORT` to other available port numbers to listen for healthcheck. Ex: 5566
3. `docker compose up -d`
4. You can bring the worker container down by `docker compose stop`
## Entrypoint:
Different from main server image which is using `flowise start`, entrypoint for worker is `pnpm run start-worker`. This is because the worker's [Dockerfile](./Dockerfile) build the image from source files via `pnpm build` instead of npm registry via `RUN npm install -g flowise`.

121
docker/worker/docker-compose.yml
View File

@ -2,16 +2,12 @@ version: '3.1'
services:
flowise:
image: flowiseai/flowise
image: flowiseai/flowise-worker:latest
restart: always
environment:
- PORT=${PORT}
- CORS_ORIGINS=${CORS_ORIGINS}
- IFRAME_ORIGINS=${IFRAME_ORIGINS}
- FLOWISE_USERNAME=${FLOWISE_USERNAME}
- FLOWISE_PASSWORD=${FLOWISE_PASSWORD}
- FLOWISE_FILE_SIZE_LIMIT=${FLOWISE_FILE_SIZE_LIMIT}
- DEBUG=${DEBUG}
- WORKER_PORT=${WORKER_PORT:-5566}
# DATABASE
- DATABASE_PATH=${DATABASE_PATH}
- DATABASE_TYPE=${DATABASE_TYPE}
- DATABASE_PORT=${DATABASE_PORT}
@ -21,37 +17,130 @@ services:
- DATABASE_PASSWORD=${DATABASE_PASSWORD}
- DATABASE_SSL=${DATABASE_SSL}
- DATABASE_SSL_KEY_BASE64=${DATABASE_SSL_KEY_BASE64}
- APIKEY_STORAGE_TYPE=${APIKEY_STORAGE_TYPE}
- APIKEY_PATH=${APIKEY_PATH}
# SECRET KEYS
- SECRETKEY_STORAGE_TYPE=${SECRETKEY_STORAGE_TYPE}
- SECRETKEY_PATH=${SECRETKEY_PATH}
- FLOWISE_SECRETKEY_OVERWRITE=${FLOWISE_SECRETKEY_OVERWRITE}
- LOG_LEVEL=${LOG_LEVEL}
- SECRETKEY_AWS_ACCESS_KEY=${SECRETKEY_AWS_ACCESS_KEY}
- SECRETKEY_AWS_SECRET_KEY=${SECRETKEY_AWS_SECRET_KEY}
- SECRETKEY_AWS_REGION=${SECRETKEY_AWS_REGION}
- SECRETKEY_AWS_NAME=${SECRETKEY_AWS_NAME}
# LOGGING
- DEBUG=${DEBUG}
- LOG_PATH=${LOG_PATH}
- LOG_LEVEL=${LOG_LEVEL}
- LOG_SANITIZE_BODY_FIELDS=${LOG_SANITIZE_BODY_FIELDS}
- LOG_SANITIZE_HEADER_FIELDS=${LOG_SANITIZE_HEADER_FIELDS}
# CUSTOM TOOL/FUNCTION DEPENDENCIES
- TOOL_FUNCTION_BUILTIN_DEP=${TOOL_FUNCTION_BUILTIN_DEP}
- TOOL_FUNCTION_EXTERNAL_DEP=${TOOL_FUNCTION_EXTERNAL_DEP}
- ALLOW_BUILTIN_DEP=${ALLOW_BUILTIN_DEP}
# STORAGE
- STORAGE_TYPE=${STORAGE_TYPE}
- BLOB_STORAGE_PATH=${BLOB_STORAGE_PATH}
- S3_STORAGE_BUCKET_NAME=${S3_STORAGE_BUCKET_NAME}
- S3_STORAGE_ACCESS_KEY_ID=${S3_STORAGE_ACCESS_KEY_ID}
- S3_STORAGE_SECRET_ACCESS_KEY=${S3_STORAGE_SECRET_ACCESS_KEY}
- S3_STORAGE_REGION=${S3_STORAGE_REGION}
- S3_ENDPOINT_URL=${S3_ENDPOINT_URL}
- S3_FORCE_PATH_STYLE=${S3_FORCE_PATH_STYLE}
- GOOGLE_CLOUD_STORAGE_CREDENTIAL=${GOOGLE_CLOUD_STORAGE_CREDENTIAL}
- GOOGLE_CLOUD_STORAGE_PROJ_ID=${GOOGLE_CLOUD_STORAGE_PROJ_ID}
- GOOGLE_CLOUD_STORAGE_BUCKET_NAME=${GOOGLE_CLOUD_STORAGE_BUCKET_NAME}
- GOOGLE_CLOUD_UNIFORM_BUCKET_ACCESS=${GOOGLE_CLOUD_UNIFORM_BUCKET_ACCESS}
# SETTINGS
- NUMBER_OF_PROXIES=${NUMBER_OF_PROXIES}
- CORS_ORIGINS=${CORS_ORIGINS}
- IFRAME_ORIGINS=${IFRAME_ORIGINS}
- FLOWISE_FILE_SIZE_LIMIT=${FLOWISE_FILE_SIZE_LIMIT}
- SHOW_COMMUNITY_NODES=${SHOW_COMMUNITY_NODES}
- DISABLE_FLOWISE_TELEMETRY=${DISABLE_FLOWISE_TELEMETRY}
- DISABLED_NODES=${DISABLED_NODES}
- MODEL_LIST_CONFIG_JSON=${MODEL_LIST_CONFIG_JSON}
# AUTH PARAMETERS
- APP_URL=${APP_URL}
- JWT_AUTH_TOKEN_SECRET=${JWT_AUTH_TOKEN_SECRET}
- JWT_REFRESH_TOKEN_SECRET=${JWT_REFRESH_TOKEN_SECRET}
- JWT_ISSUER=${JWT_ISSUER}
- JWT_AUDIENCE=${JWT_AUDIENCE}
- JWT_TOKEN_EXPIRY_IN_MINUTES=${JWT_TOKEN_EXPIRY_IN_MINUTES}
- JWT_REFRESH_TOKEN_EXPIRY_IN_MINUTES=${JWT_REFRESH_TOKEN_EXPIRY_IN_MINUTES}
- EXPIRE_AUTH_TOKENS_ON_RESTART=${EXPIRE_AUTH_TOKENS_ON_RESTART}
- EXPRESS_SESSION_SECRET=${EXPRESS_SESSION_SECRET}
- PASSWORD_RESET_TOKEN_EXPIRY_IN_MINS=${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}
- SMTP_PORT=${SMTP_PORT}
- SMTP_USER=${SMTP_USER}
- SMTP_PASSWORD=${SMTP_PASSWORD}
- SMTP_SECURE=${SMTP_SECURE}
- ALLOW_UNAUTHORIZED_CERTS=${ALLOW_UNAUTHORIZED_CERTS}
- SENDER_EMAIL=${SENDER_EMAIL}
# ENTERPRISE
- LICENSE_URL=${LICENSE_URL}
- FLOWISE_EE_LICENSE_KEY=${FLOWISE_EE_LICENSE_KEY}
- OFFLINE=${OFFLINE}
- INVITE_TOKEN_EXPIRY_IN_HOURS=${INVITE_TOKEN_EXPIRY_IN_HOURS}
- WORKSPACE_INVITE_TEMPLATE_PATH=${WORKSPACE_INVITE_TEMPLATE_PATH}
# METRICS COLLECTION
- POSTHOG_PUBLIC_API_KEY=${POSTHOG_PUBLIC_API_KEY}
- ENABLE_METRICS=${ENABLE_METRICS}
- METRICS_PROVIDER=${METRICS_PROVIDER}
- METRICS_INCLUDE_NODE_METRICS=${METRICS_INCLUDE_NODE_METRICS}
- METRICS_SERVICE_NAME=${METRICS_SERVICE_NAME}
- METRICS_OPEN_TELEMETRY_METRIC_ENDPOINT=${METRICS_OPEN_TELEMETRY_METRIC_ENDPOINT}
- METRICS_OPEN_TELEMETRY_PROTOCOL=${METRICS_OPEN_TELEMETRY_PROTOCOL}
- METRICS_OPEN_TELEMETRY_DEBUG=${METRICS_OPEN_TELEMETRY_DEBUG}
# PROXY
- GLOBAL_AGENT_HTTP_PROXY=${GLOBAL_AGENT_HTTP_PROXY}
- GLOBAL_AGENT_HTTPS_PROXY=${GLOBAL_AGENT_HTTPS_PROXY}
- GLOBAL_AGENT_NO_PROXY=${GLOBAL_AGENT_NO_PROXY}
- DISABLED_NODES=${DISABLED_NODES}
# QUEUE CONFIGURATION
- MODE=${MODE}
- WORKER_CONCURRENCY=${WORKER_CONCURRENCY}
- QUEUE_NAME=${QUEUE_NAME}
- QUEUE_REDIS_EVENT_STREAM_MAX_LEN=${QUEUE_REDIS_EVENT_STREAM_MAX_LEN}
- WORKER_CONCURRENCY=${WORKER_CONCURRENCY}
- REMOVE_ON_AGE=${REMOVE_ON_AGE}
- REMOVE_ON_COUNT=${REMOVE_ON_COUNT}
- REDIS_URL=${REDIS_URL}
- REDIS_HOST=${REDIS_HOST}
- REDIS_PORT=${REDIS_PORT}
- REDIS_PASSWORD=${REDIS_PASSWORD}
- REDIS_USERNAME=${REDIS_USERNAME}
- REDIS_PASSWORD=${REDIS_PASSWORD}
- REDIS_TLS=${REDIS_TLS}
- REDIS_CERT=${REDIS_CERT}
- REDIS_KEY=${REDIS_KEY}
- REDIS_CA=${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}'
- '${WORKER_PORT}:${WORKER_PORT}'
healthcheck:
test: ['CMD', 'curl', '-f', 'http://localhost:${WORKER_PORT}/healthz']
interval: 10s
timeout: 5s
retries: 5
start_period: 30s
volumes:
- ~/.flowise:/root/.flowise
entrypoint: /bin/sh -c "sleep 3; flowise worker"
entrypoint: /bin/sh -c "node /app/healthcheck/healthcheck.js & sleep 5 && pnpm run start-worker"

13
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View File

@ -0,0 +1,13 @@
const express = require('express')
const app = express()
const port = process.env.WORKER_PORT || 5566
app.get('/healthz', (req, res) => {
res.status(200).send('OK')
})
app.listen(port, () => {
// eslint-disable-next-line no-console
console.log(`Healthcheck server listening on port ${port}`)
})

13
docker/worker/healthcheck/package.json Normal file
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@ -0,0 +1,13 @@
{
"name": "flowise-worker-healthcheck",
"version": "1.0.0",
"description": "Simple healthcheck server for Flowise worker",
"main": "healthcheck.js",
"private": true,
"scripts": {
"start": "node healthcheck.js"
},
"dependencies": {
"express": "^4.19.2"
}
}

64
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View File

@ -112,45 +112,41 @@ 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
Flowise 支持不同的环境变量来配置您的实例。您可以在 `packages/server` 文件夹中的 `.env` 文件中指定以下变量。阅读[更多信息](https://docs.flowiseai.com/environment-variables)
| 变量名 | 描述 | 类型 | 默认值 |
| ---------------------------- | ------------------------------------------------------- | ----------------------------------------------- | ----------------------------------- | --- |
| PORT | Flowise 运行的 HTTP 端口 | 数字 | 3000 |
| FLOWISE_USERNAME | 登录用户名 | 字符串 | |
| FLOWISE_PASSWORD | 登录密码 | 字符串 | |
| FLOWISE_FILE_SIZE_LIMIT | 上传文件大小限制 | 字符串 | 50mb | |
| DEBUG | 打印组件的日志 | 布尔值 | |
| LOG_PATH | 存储日志文件的位置 | 字符串 | `your-path/Flowise/logs` |
| LOG_LEVEL | 日志的不同级别 | 枚举字符串: `error`, `info`, `verbose`, `debug` | `info` |
| APIKEY_STORAGE_TYPE | 存储 API 密钥的存储类型 | 枚举字符串: `json`, `db` | `json` |
| APIKEY_PATH | 存储 API 密钥的位置, 当`APIKEY_STORAGE_TYPE`是`json` | 字符串 | `your-path/Flowise/packages/server` |
| TOOL_FUNCTION_BUILTIN_DEP | 用于工具函数的 NodeJS 内置模块 | 字符串 | |
| TOOL_FUNCTION_EXTERNAL_DEP | 用于工具函数的外部模块 | 字符串 | |
| DATABASE_TYPE | 存储 flowise 数据的数据库类型 | 枚举字符串: `sqlite`, `mysql`, `postgres` | `sqlite` |
| DATABASE_PATH | 数据库保存的位置（当 DATABASE_TYPE 是 sqlite 时） | 字符串 | `your-home-dir/.flowise` |
| DATABASE_HOST | 主机 URL 或 IP 地址（当 DATABASE_TYPE 不是 sqlite 时） | 字符串 | |
| DATABASE_PORT | 数据库端口（当 DATABASE_TYPE 不是 sqlite 时） | 字符串 | |
| DATABASE_USERNAME | 数据库用户名（当 DATABASE_TYPE 不是 sqlite 时） | 字符串 | |
| DATABASE_PASSWORD | 数据库密码（当 DATABASE_TYPE 不是 sqlite 时） | 字符串 | |
| DATABASE_NAME | 数据库名称（当 DATABASE_TYPE 不是 sqlite 时） | 字符串 | |
| SECRETKEY_PATH | 保存加密密钥（用于加密/解密凭据）的位置 | 字符串 | `your-path/Flowise/packages/server` |
| FLOWISE_SECRETKEY_OVERWRITE | 加密密钥用于替代存储在 SECRETKEY_PATH 中的密钥 | 字符串 |
| MODEL_LIST_CONFIG_JSON | 加载模型的位置 | 字符 | `/your_model_list_config_file_path` |
| STORAGE_TYPE | 上传文件的存储类型 | 枚举字符串: `local`, `s3` | `local` |
| BLOB_STORAGE_PATH | 上传文件存储的本地文件夹路径, 当`STORAGE_TYPE`是`local` | 字符串 | `your-home-dir/.flowise/storage` |
| S3_STORAGE_BUCKET_NAME | S3 存储文件夹路径, 当`STORAGE_TYPE`是`s3` | 字符串 | |
| S3_STORAGE_ACCESS_KEY_ID | AWS 访问密钥 (Access Key) | 字符串 | |
| S3_STORAGE_SECRET_ACCESS_KEY | AWS 密钥 (Secret Key) | 字符串 | |
| S3_STORAGE_REGION | S3 存储地区 | 字符串 | |
| S3_ENDPOINT_URL | S3 端点 URL | 字符串 | |
| S3_FORCE_PATH_STYLE | 将其设置为 true 以强制请求使用路径样式寻址 | 布尔值 | false |
| SHOW_COMMUNITY_NODES | 显示由社区创建的节点 | 布尔值 | |
| DISABLED_NODES | 从界面中隐藏节点（以逗号分隔的节点名称列表） | 字符串 | |
| 变量名 | 描述 | 类型 | 默认值 |
| ------------------------------ | -------------------------------------------------------- | ----------------------------------------------- | ----------------------------------- |
| `PORT` | Flowise 运行的 HTTP 端口 | 数字 | 3000 |
| `FLOWISE_FILE_SIZE_LIMIT` | 上传文件大小限制 | 字符串 | 50mb |
| `DEBUG` | 打印组件的日志 | 布尔值 | |
| `LOG_PATH` | 存储日志文件的位置 | 字符串 | `your-path/Flowise/logs` |
| `LOG_LEVEL` | 日志的不同级别 | 枚举字符串: `error`, `info`, `verbose`, `debug` | `info` |
| `TOOL_FUNCTION_BUILTIN_DEP` | 用于工具函数的 NodeJS 内置模块 | 字符串 | |
| `TOOL_FUNCTION_EXTERNAL_DEP` | 用于工具函数的外部模块 | 字符串 | |
| `DATABASE_TYPE` | 存储 Flowise 数据的数据库类型 | 枚举字符串: `sqlite`, `mysql`, `postgres` | `sqlite` |
| `DATABASE_PATH` | 数据库保存的位置（当 `DATABASE_TYPE` 是 sqlite 时） | 字符串 | `your-home-dir/.flowise` |
| `DATABASE_HOST` | 主机 URL 或 IP 地址（当 `DATABASE_TYPE` 不是 sqlite 时） | 字符串 | |
| `DATABASE_PORT` | 数据库端口（当 `DATABASE_TYPE` 不是 sqlite 时） | 字符串 | |
| `DATABASE_USERNAME` | 数据库用户名（当 `DATABASE_TYPE` 不是 sqlite 时） | 字符串 | |
| `DATABASE_PASSWORD` | 数据库密码（当 `DATABASE_TYPE` 不是 sqlite 时） | 字符串 | |
| `DATABASE_NAME` | 数据库名称（当 `DATABASE_TYPE` 不是 sqlite 时） | 字符串 | |
| `SECRETKEY_PATH` | 保存加密密钥（用于加密/解密凭据）的位置 | 字符串 | `your-path/Flowise/packages/server` |
| `FLOWISE_SECRETKEY_OVERWRITE` | 加密密钥用于替代存储在 `SECRETKEY_PATH` 中的密钥 | 字符串 | |
| `MODEL_LIST_CONFIG_JSON` | 加载模型的位置 | 字符串 | `/your_model_list_config_file_path` |
| `STORAGE_TYPE` | 上传文件的存储类型 | 枚举字符串: `local`, `s3` | `local` |
| `BLOB_STORAGE_PATH` | 本地上传文件存储路径（当 `STORAGE_TYPE` 为 `local`） | 字符串 | `your-home-dir/.flowise/storage` |
| `S3_STORAGE_BUCKET_NAME` | S3 存储文件夹路径（当 `STORAGE_TYPE` 为 `s3`） | 字符串 | |
| `S3_STORAGE_ACCESS_KEY_ID` | AWS 访问密钥 (Access Key) | 字符串 | |
| `S3_STORAGE_SECRET_ACCESS_KEY` | AWS 密钥 (Secret Key) | 字符串 | |
| `S3_STORAGE_REGION` | S3 存储地区 | 字符串 | |
| `S3_ENDPOINT_URL` | S3 端点 URL | 字符串 | |
| `S3_FORCE_PATH_STYLE` | 设置为 true 以强制请求使用路径样式寻址 | 布尔值 | false |
| `SHOW_COMMUNITY_NODES` | 显示由社区创建的节点 | 布尔值 | |
| `DISABLED_NODES` | 从界面中隐藏节点（以逗号分隔的节点名称列表） | 字符串 | |
您也可以在使用 `npx` 时指定环境变量。例如：

19
i18n/README-JA.md
View File

@ -31,12 +31,6 @@
npx flowise start
```
ユーザー名とパスワードを入力
```bash
npx flowise start --FLOWISE_USERNAME=user --FLOWISE_PASSWORD=1234
```
3. [http://localhost:3000](http://localhost:3000) を開く
## 🐳 Docker
@ -127,15 +121,6 @@ Flowise には、3 つの異なるモジュールが 1 つの mono リポジト
コードの変更は [http://localhost:8080](http://localhost:8080) に自動的にアプリをリロードします
## 🔒 認証
アプリレベルの認証を有効にするには、 `FLOWISE_USERNAME` と `FLOWISE_PASSWORD` を `packages/server` の `.env` ファイルに追加します:
```
FLOWISE_USERNAME=user
FLOWISE_PASSWORD=1234
```
## 🌱 環境変数
Flowise は、インスタンスを設定するためのさまざまな環境変数をサポートしています。`packages/server` フォルダ内の `.env` ファイルで以下の変数を指定することができる。[続き](https://github.com/FlowiseAI/Flowise/blob/main/CONTRIBUTING.md#-env-variables)を読む
@ -197,9 +182,9 @@ Flowise は、インスタンスを設定するためのさまざまな環境変
<img src="https://contrib.rocks/image?repo=FlowiseAI/Flowise" />
</a>
[コントリビューティングガイド](CONTRIBUTING.md)を参照してください。質問や問題があれば、[Discord](https://discord.gg/jbaHfsRVBW) までご連絡ください。
[コントリビューティングガイド](../CONTRIBUTING.md)を参照してください。質問や問題があれば、[Discord](https://discord.gg/jbaHfsRVBW) までご連絡ください。
[![Star History Chart](https://api.star-history.com/svg?repos=FlowiseAI/Flowise&type=Timeline)](https://star-history.com/#FlowiseAI/Flowise&Date)
## 📄 ライセンス
このリポジトリのソースコードは、[Apache License Version 2.0](LICENSE.md)の下で利用可能です。
このリポジトリのソースコードは、[Apache License Version 2.0](../LICENSE.md)の下で利用可能です。

19
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View File

@ -31,12 +31,6 @@
npx flowise start
```
사용자 이름과 비밀번호로 시작하기
```bash
npx flowise start --FLOWISE_USERNAME=user --FLOWISE_PASSWORD=1234
```
3. [http://localhost:3000](http://localhost:3000) URL 열기
## 🐳 도커(Docker)를 활용하여 시작하기
@ -127,15 +121,6 @@ Flowise는 단일 리포지토리에 3개의 서로 다른 모듈이 있습니
코드가 변경되면 [http://localhost:8080](http://localhost:8080)에서 자동으로 애플리케이션을 새로고침 합니다.
## 🔒 인증
애플리케이션 수준의 인증을 사용하려면 `packages/server`의 `.env` 파일에 `FLOWISE_USERNAME` 및 `FLOWISE_PASSWORD`를 추가합니다:
```
FLOWISE_USERNAME=user
FLOWISE_PASSWORD=1234
```
## 🌱 환경 변수
Flowise는 인스턴스 구성을 위한 다양한 환경 변수를 지원합니다. `packages/server` 폴더 내 `.env` 파일에 다양한 환경 변수를 지정할 수 있습니다. [자세히 보기](https://github.com/FlowiseAI/Flowise/blob/main/CONTRIBUTING.md#-env-variables)
@ -197,9 +182,9 @@ Flowise는 인스턴스 구성을 위한 다양한 환경 변수를 지원합니
<img src="https://contrib.rocks/image?repo=FlowiseAI/Flowise" />
</a>
[contributing guide](CONTRIBUTING.md)를 살펴보세요. 디스코드 [Discord](https://discord.gg/jbaHfsRVBW) 채널에서도 이슈나 질의응답을 진행하실 수 있습니다.
[contributing guide](../CONTRIBUTING.md)를 살펴보세요. 디스코드 [Discord](https://discord.gg/jbaHfsRVBW) 채널에서도 이슈나 질의응답을 진행하실 수 있습니다.
[![Star History Chart](https://api.star-history.com/svg?repos=FlowiseAI/Flowise&type=Timeline)](https://star-history.com/#FlowiseAI/Flowise&Date)
## 📄 라이센스
본 리포지토리의 소스코드는 [Apache License Version 2.0](LICENSE.md) 라이센스가 적용됩니다.
본 리포지토리의 소스코드는 [Apache License Version 2.0](../LICENSE.md) 라이센스가 적용됩니다.

63
i18n/README-TW.md
View File

@ -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>
@ -31,28 +31,22 @@
npx flowise start
```
使用用戶名和密碼
```bash
npx flowise start --FLOWISE_USERNAME=user --FLOWISE_PASSWORD=1234
```
3. 打開 [http://localhost:3000](http://localhost:3000)
## 🐳 Docker
### 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 .
```
@ -69,7 +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
@ -85,33 +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
@ -124,9 +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`）
@ -136,28 +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)
## 🔒 認證
## 🌱 環境變數
要啟用應用級別的身份驗證，請在 `packages/server` 中的 `.env` 文件中添加 `FLOWISE_USERNAME` 和 `FLOWISE_PASSWORD`：
```
FLOWISE_USERNAME=user
FLOWISE_PASSWORD=1234
```
## 🌱 環境變量
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)
@ -193,9 +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
@ -209,9 +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。

19
i18n/README-ZH.md
View File

@ -31,12 +31,6 @@
npx flowise start
```
使用用户名和密码
```bash
npx flowise start --FLOWISE_USERNAME=user --FLOWISE_PASSWORD=1234
```
3. 打开 [http://localhost:3000](http://localhost:3000)
## 🐳 Docker
@ -127,15 +121,6 @@ Flowise 在一个单一的代码库中有 3 个不同的模块。
任何代码更改都会自动重新加载应用程序，访问 [http://localhost:8080](http://localhost:8080)
## 🔒 认证
要启用应用程序级身份验证，在 `packages/server` 的 `.env` 文件中添加 `FLOWISE_USERNAME` 和 `FLOWISE_PASSWORD`：
```
FLOWISE_USERNAME=user
FLOWISE_PASSWORD=1234
```
## 🌱 环境变量
Flowise 支持不同的环境变量来配置您的实例。您可以在 `packages/server` 文件夹中的 `.env` 文件中指定以下变量。了解更多信息，请阅读[文档](https://github.com/FlowiseAI/Flowise/blob/main/CONTRIBUTING.md#-env-variables)
@ -197,8 +182,8 @@ Flowise 支持不同的环境变量来配置您的实例。您可以在 `package
<img src="https://contrib.rocks/image?repo=FlowiseAI/Flowise" />
</a>
参见[贡献指南](CONTRIBUTING.md)。如果您有任何问题或问题，请在[Discord](https://discord.gg/jbaHfsRVBW)上与我们联系。
参见[贡献指南](CONTRIBUTING-ZH.md)。如果您有任何问题或问题，请在[Discord](https://discord.gg/jbaHfsRVBW)上与我们联系。
## 📄 许可证
此代码库中的源代码在[Apache License Version 2.0 许可证](LICENSE.md)下提供。
此代码库中的源代码在[Apache License Version 2.0 许可证](../LICENSE.md)下提供。

30
metrics/otel/compose.yaml
View File

@ -1,15 +1,17 @@
version: "2"
version: '2'
services:
otel-collector:
image: otel/opentelemetry-collector-contrib
command: ["--config=/etc/otelcol-contrib/config.yaml", "--feature-gates=-exporter.datadogexporter.DisableAPMStats", "${OTELCOL_ARGS}"]
volumes:
- ./otel.config.yml:/etc/otelcol-contrib/config.yaml
ports:
- 1888:1888 # pprof extension
- 8888:8888 # Prometheus metrics exposed by the Collector
- 8889:8889 # Prometheus exporter metrics
- 13133:13133 # health_check extension
- 4317:4317 # OTLP gRPC receiver
- 4318:4318 # OTLP http receiver
- 55679:55679 # zpages extension
otel-collector:
read_only: true
image: otel/opentelemetry-collector-contrib
command:
['--config=/etc/otelcol-contrib/config.yaml', '--feature-gates=-exporter.datadogexporter.DisableAPMStats', '${OTELCOL_ARGS}']
volumes:
- ./otel.config.yml:/etc/otelcol-contrib/config.yaml
ports:
- 1888:1888 # pprof extension
- 8888:8888 # Prometheus metrics exposed by the Collector
- 8889:8889 # Prometheus exporter metrics
- 13133:13133 # health_check extension
- 4317:4317 # OTLP gRPC receiver
- 4318:4318 # OTLP http receiver
- 55679:55679 # zpages extension

18
package.json
View File

@ -1,6 +1,6 @@
{
"name": "flowise",
"version": "3.0.0",
"version": "3.0.11",
"private": true,
"homepage": "https://flowiseai.com",
"workspaces": [
@ -20,6 +20,10 @@
"start-worker": "run-script-os",
"start-worker:windows": "cd packages/server/bin && run worker",
"start-worker:default": "cd packages/server/bin && ./run worker",
"user": "run-script-os",
"user:windows": "cd packages/server/bin && run user",
"user:default": "cd packages/server/bin && ./run user",
"test": "turbo run test",
"clean": "pnpm --filter \"./packages/**\" clean",
"nuke": "pnpm --filter \"./packages/**\" nuke && rimraf node_modules .turbo",
"format": "prettier --write \"**/*.{ts,tsx,md}\"",
@ -62,20 +66,26 @@
"sqlite3"
],
"overrides": {
"axios": "1.7.9",
"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",
"nth-check": "2.1.1",
"path-to-regexp": "0.1.12",
"prismjs": "1.29.0",
"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"
"webpack-dev-middleware": "7.4.2",
"ws": "8.18.3",
"xlsx": "https://cdn.sheetjs.com/xlsx-0.20.3/xlsx-0.20.3.tgz"
}
},
"engines": {
@ -85,7 +95,7 @@
"resolutions": {
"@google/generative-ai": "^0.24.0",
"@grpc/grpc-js": "^1.10.10",
"@langchain/core": "0.3.37",
"@langchain/core": "0.3.61",
"@qdrant/openapi-typescript-fetch": "1.2.6",
"openai": "4.96.0",
"protobufjs": "7.4.0"

2
packages/api-documentation/package.json
View File

@ -1,6 +1,6 @@
{
"name": "flowise-api",
"version": "1.0.2",
"version": "1.0.3",
"description": "Flowise API documentation server",
"scripts": {
"build": "tsc",

193
packages/api-documentation/src/yml/swagger.yml
View File

@ -1216,15 +1216,18 @@ paths:
security:
- bearerAuth: []
operationId: createPrediction
summary: Create a new prediction
description: Create a new prediction
summary: Send message to flow and get AI response
description: |
Send a message to your flow and receive an AI-generated response. This is the primary endpoint for interacting with your flows and assistants.
**Authentication**: API key may be required depending on flow settings.
parameters:
- in: path
name: id
required: true
schema:
type: string
description: Chatflow ID
description: Flow ID - the unique identifier of your flow
example: 'your-flow-id'
requestBody:
content:
application/json:
@ -1236,24 +1239,36 @@ paths:
properties:
question:
type: string
description: Question to ask during the prediction process
description: Question/message to send to the flow
example: 'Analyze this uploaded file and summarize its contents'
files:
type: array
items:
type: string
format: binary
description: Files to be uploaded
modelName:
description: Files to be uploaded (images, audio, documents, etc.)
streaming:
type: boolean
description: Enable streaming responses
default: false
overrideConfig:
type: string
nullable: true
example: ''
description: Other override configurations
description: JSON string of configuration overrides
example: '{"sessionId":"user-123","temperature":0.7}'
history:
type: string
description: JSON string of conversation history
example: '[{"role":"userMessage","content":"Hello"},{"role":"apiMessage","content":"Hi there!"}]'
humanInput:
type: string
description: JSON string of human input for resuming execution
example: '{"type":"proceed","feedback":"Continue with the plan"}'
required:
- question
required: true
responses:
'200':
description: Prediction created successfully
description: Successful prediction response
content:
application/json:
schema:
@ -1261,45 +1276,106 @@ paths:
properties:
text:
type: string
description: The result of the prediction
description: The AI-generated response text
example: 'Artificial intelligence (AI) is a branch of computer science that focuses on creating systems capable of performing tasks that typically require human intelligence.'
json:
type: object
description: The result of the prediction in JSON format if available
description: The result in JSON format if available (for structured outputs)
nullable: true
question:
type: string
description: The question asked during the prediction process
description: The original question/message sent to the flow
example: 'What is artificial intelligence?'
chatId:
type: string
description: The chat ID associated with the prediction
description: Unique identifier for the chat session
example: 'chat-12345'
chatMessageId:
type: string
description: The chat message ID associated with the prediction
description: Unique identifier for this specific message
example: 'msg-67890'
sessionId:
type: string
description: The session ID associated with the prediction
description: Session identifier for conversation continuity
example: 'user-session-123'
nullable: true
memoryType:
type: string
description: The memory type associated with the prediction
description: Type of memory used for conversation context
example: 'Buffer Memory'
nullable: true
sourceDocuments:
type: array
description: Documents retrieved from vector store (if RAG is enabled)
items:
$ref: '#/components/schemas/Document'
nullable: true
usedTools:
type: array
description: Tools that were invoked during the response generation
items:
$ref: '#/components/schemas/UsedTool'
fileAnnotations:
type: array
items:
$ref: '#/components/schemas/FileAnnotation'
nullable: true
'400':
description: Invalid input provided
description: Bad Request - Invalid input provided or request format is incorrect
content:
application/json:
schema:
type: object
properties:
error:
type: string
example: 'Invalid request format. Check required fields and parameter types.'
'401':
description: Unauthorized - API key required or invalid
content:
application/json:
schema:
type: object
properties:
error:
type: string
example: 'Unauthorized access. Please verify your API key.'
'404':
description: Chatflow not found
description: Not Found - Chatflow with specified ID does not exist
content:
application/json:
schema:
type: object
properties:
error:
type: string
example: 'Chatflow not found. Please verify the chatflow ID.'
'413':
description: Payload Too Large - Request payload exceeds size limits
content:
application/json:
schema:
type: object
properties:
error:
type: string
example: 'Request payload too large. Please reduce file sizes or split large requests.'
'422':
description: Validation error
description: Validation Error - Request validation failed
content:
application/json:
schema:
type: object
properties:
error:
type: string
example: 'Validation failed. Check parameter requirements and data types.'
'500':
description: Internal server error
description: Internal Server Error - Flow configuration or execution error
content:
application/json:
schema:
type: object
properties:
error:
type: string
example: 'Internal server error. Check flow configuration and node settings.'
/tools:
post:
tags:
@ -2011,13 +2087,33 @@ components:
properties:
question:
type: string
description: The question being asked
description: The question/message to send to the flow
example: 'What is artificial intelligence?'
form:
type: object
description: The form object to send to the flow (alternative to question for Agentflow V2)
additionalProperties: true
example:
title: 'Example'
count: 1
streaming:
type: boolean
description: Enable streaming responses for real-time output
default: false
example: false
overrideConfig:
type: object
description: The configuration to override the default prediction settings (optional)
description: Override flow configuration and pass variables at runtime
additionalProperties: true
example:
sessionId: 'user-session-123'
temperature: 0.7
maxTokens: 500
vars:
user_name: 'Alice'
history:
type: array
description: The history messages to be prepended (optional)
description: Previous conversation messages for context
items:
type: object
properties:
@ -2030,8 +2126,14 @@ components:
type: string
description: The content of the message
example: 'Hello, how can I help you?'
example:
- role: 'apiMessage'
content: "Hello! I'm an AI assistant. How can I help you today?"
- role: 'userMessage'
content: "Hi, my name is Sarah and I'm learning about AI"
uploads:
type: array
description: Files to upload (images, audio, documents, etc.)
items:
type: object
properties:
@ -2051,7 +2153,42 @@ components:
mime:
type: string
description: The MIME type of the file or resource
enum:
[
'image/png',
'image/jpeg',
'image/jpg',
'image/gif',
'image/webp',
'audio/mp4',
'audio/webm',
'audio/wav',
'audio/mpeg',
'audio/ogg',
'audio/aac'
]
example: 'image/png'
example:
- type: 'file'
name: 'example.png'
data: 'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABgAAAAYCAYAAADgdz34AAABjElEQVRIS+2Vv0oDQRDG'
mime: 'image/png'
humanInput:
type: object
description: Return human feedback and resume execution from a stopped checkpoint
properties:
type:
type: string
enum: [proceed, reject]
description: Type of human input response
example: 'reject'
feedback:
type: string
description: Feedback to the last output
example: 'Include more emoji'
example:
type: 'reject'
feedback: 'Include more emoji'
Tool:
type: object

23
packages/components/credentials/AgentflowApi.credential.ts Normal file
View File

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

23
packages/components/credentials/CometApi.credential.ts Normal file
View File

@ -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 }

26
packages/components/credentials/ElevenLabsApi.credential.ts Normal file
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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 }

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packages/components/credentials/GmailOAuth2.credential.ts Normal file
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import { INodeParams, INodeCredential } from '../src/Interface'
const scopes = [
'https://www.googleapis.com/auth/gmail.readonly',
'https://www.googleapis.com/auth/gmail.compose',
'https://www.googleapis.com/auth/gmail.modify',
'https://www.googleapis.com/auth/gmail.labels'
]
class GmailOAuth2 implements INodeCredential {
label: string
name: string
version: number
inputs: INodeParams[]
description: string
constructor() {
this.label = 'Gmail OAuth2'
this.name = 'gmailOAuth2'
this.version = 1.0
this.description =
'You can find the setup instructions <a target="_blank" href="https://docs.flowiseai.com/integrations/langchain/tools/gmail">here</a>'
this.inputs = [
{
label: 'Authorization URL',
name: 'authorizationUrl',
type: 'string',
default: 'https://accounts.google.com/o/oauth2/v2/auth'
},
{
label: 'Access Token URL',
name: 'accessTokenUrl',
type: 'string',
default: 'https://oauth2.googleapis.com/token'
},
{
label: 'Client ID',
name: 'clientId',
type: 'string'
},
{
label: 'Client Secret',
name: 'clientSecret',
type: 'password'
},
{
label: 'Additional Parameters',
name: 'additionalParameters',
type: 'string',
default: 'access_type=offline&prompt=consent',
hidden: true
},
{
label: 'Scope',
name: 'scope',
type: 'string',
hidden: true,
default: scopes.join(' ')
}
]
}
}
module.exports = { credClass: GmailOAuth2 }

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packages/components/credentials/GoogleCalendarOAuth2.credential.ts Normal file
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import { INodeParams, INodeCredential } from '../src/Interface'
const scopes = ['https://www.googleapis.com/auth/calendar', 'https://www.googleapis.com/auth/calendar.events']
class GoogleCalendarOAuth2 implements INodeCredential {
label: string
name: string
version: number
inputs: INodeParams[]
description: string
constructor() {
this.label = 'Google Calendar OAuth2'
this.name = 'googleCalendarOAuth2'
this.version = 1.0
this.description =
'You can find the setup instructions <a target="_blank" href="https://docs.flowiseai.com/integrations/langchain/tools/google-calendar">here</a>'
this.inputs = [
{
label: 'Authorization URL',
name: 'authorizationUrl',
type: 'string',
default: 'https://accounts.google.com/o/oauth2/v2/auth'
},
{
label: 'Access Token URL',
name: 'accessTokenUrl',
type: 'string',
default: 'https://oauth2.googleapis.com/token'
},
{
label: 'Client ID',
name: 'clientId',
type: 'string'
},
{
label: 'Client Secret',
name: 'clientSecret',
type: 'password'
},
{
label: 'Additional Parameters',
name: 'additionalParameters',
type: 'string',
default: 'access_type=offline&prompt=consent',
hidden: true
},
{
label: 'Scope',
name: 'scope',
type: 'string',
hidden: true,
default: scopes.join(' ')
}
]
}
}
module.exports = { credClass: GoogleCalendarOAuth2 }

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packages/components/credentials/GoogleDocsOAuth2.credential.ts Normal file
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import { INodeParams, INodeCredential } from '../src/Interface'
const scopes = [
'https://www.googleapis.com/auth/documents',
'https://www.googleapis.com/auth/drive',
'https://www.googleapis.com/auth/drive.file'
]
class GoogleDocsOAuth2 implements INodeCredential {
label: string
name: string
version: number
inputs: INodeParams[]
description: string
constructor() {
this.label = 'Google Docs OAuth2'
this.name = 'googleDocsOAuth2'
this.version = 1.0
this.description =
'You can find the setup instructions <a target="_blank" href="https://docs.flowiseai.com/integrations/langchain/tools/google-sheets">here</a>'
this.inputs = [
{
label: 'Authorization URL',
name: 'authorizationUrl',
type: 'string',
default: 'https://accounts.google.com/o/oauth2/v2/auth'
},
{
label: 'Access Token URL',
name: 'accessTokenUrl',
type: 'string',
default: 'https://oauth2.googleapis.com/token'
},
{
label: 'Client ID',
name: 'clientId',
type: 'string'
},
{
label: 'Client Secret',
name: 'clientSecret',
type: 'password'
},
{
label: 'Additional Parameters',
name: 'additionalParameters',
type: 'string',
default: 'access_type=offline&prompt=consent',
hidden: true
},
{
label: 'Scope',
name: 'scope',
type: 'string',
hidden: true,
default: scopes.join(' ')
}
]
}
}
module.exports = { credClass: GoogleDocsOAuth2 }

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packages/components/credentials/GoogleDriveOAuth2.credential.ts Normal file
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import { INodeParams, INodeCredential } from '../src/Interface'
const scopes = [
'https://www.googleapis.com/auth/drive',
'https://www.googleapis.com/auth/drive.appdata',
'https://www.googleapis.com/auth/drive.photos.readonly'
]
class GoogleDriveOAuth2 implements INodeCredential {
label: string
name: string
version: number
inputs: INodeParams[]
description: string
constructor() {
this.label = 'Google Drive OAuth2'
this.name = 'googleDriveOAuth2'
this.version = 1.0
this.description =
'You can find the setup instructions <a target="_blank" href="https://docs.flowiseai.com/integrations/langchain/tools/google-drive">here</a>'
this.inputs = [
{
label: 'Authorization URL',
name: 'authorizationUrl',
type: 'string',
default: 'https://accounts.google.com/o/oauth2/v2/auth'
},
{
label: 'Access Token URL',
name: 'accessTokenUrl',
type: 'string',
default: 'https://oauth2.googleapis.com/token'
},
{
label: 'Client ID',
name: 'clientId',
type: 'string'
},
{
label: 'Client Secret',
name: 'clientSecret',
type: 'password'
},
{
label: 'Additional Parameters',
name: 'additionalParameters',
type: 'string',
default: 'access_type=offline&prompt=consent',
hidden: true
},
{
label: 'Scope',
name: 'scope',
type: 'string',
hidden: true,
default: scopes.join(' ')
}
]
}
}
module.exports = { credClass: GoogleDriveOAuth2 }

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packages/components/credentials/GoogleSheetsOAuth2.credential.ts Normal file
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import { INodeParams, INodeCredential } from '../src/Interface'
const scopes = [
'https://www.googleapis.com/auth/drive.file',
'https://www.googleapis.com/auth/spreadsheets',
'https://www.googleapis.com/auth/drive.metadata'
]
class GoogleSheetsOAuth2 implements INodeCredential {
label: string
name: string
version: number
inputs: INodeParams[]
description: string
constructor() {
this.label = 'Google Sheets OAuth2'
this.name = 'googleSheetsOAuth2'
this.version = 1.0
this.description =
'You can find the setup instructions <a target="_blank" href="https://docs.flowiseai.com/integrations/langchain/tools/google-sheets">here</a>'
this.inputs = [
{
label: 'Authorization URL',
name: 'authorizationUrl',
type: 'string',
default: 'https://accounts.google.com/o/oauth2/v2/auth'
},
{
label: 'Access Token URL',
name: 'accessTokenUrl',
type: 'string',
default: 'https://oauth2.googleapis.com/token'
},
{
label: 'Client ID',
name: 'clientId',
type: 'string'
},
{
label: 'Client Secret',
name: 'clientSecret',
type: 'password'
},
{
label: 'Additional Parameters',
name: 'additionalParameters',
type: 'string',
default: 'access_type=offline&prompt=consent',
hidden: true
},
{
label: 'Scope',
name: 'scope',
type: 'string',
hidden: true,
default: scopes.join(' ')
}
]
}
}
module.exports = { credClass: GoogleSheetsOAuth2 }

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packages/components/credentials/MicrosoftOutlookOAuth2.credential.ts Normal file
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import { INodeParams, INodeCredential } from '../src/Interface'
const scopes = [
'openid',
'offline_access',
'Contacts.Read',
'Contacts.ReadWrite',
'Calendars.Read',
'Calendars.Read.Shared',
'Calendars.ReadWrite',
'Mail.Read',
'Mail.ReadWrite',
'Mail.ReadWrite.Shared',
'Mail.Send',
'Mail.Send.Shared',
'MailboxSettings.Read'
]
class MsoftOutlookOAuth2 implements INodeCredential {
label: string
name: string
version: number
description: string
inputs: INodeParams[]
constructor() {
this.label = 'Microsoft Outlook OAuth2'
this.name = 'microsoftOutlookOAuth2'
this.version = 1.0
this.description =
'You can find the setup instructions <a target="_blank" href="https://docs.flowiseai.com/integrations/langchain/tools/microsoft-outlook">here</a>'
this.inputs = [
{
label: 'Authorization URL',
name: 'authorizationUrl',
type: 'string',
default: 'https://login.microsoftonline.com/<tenantId>/oauth2/v2.0/authorize'
},
{
label: 'Access Token URL',
name: 'accessTokenUrl',
type: 'string',
default: 'https://login.microsoftonline.com/<tenantId>/oauth2/v2.0/token'
},
{
label: 'Client ID',
name: 'clientId',
type: 'string'
},
{
label: 'Client Secret',
name: 'clientSecret',
type: 'password'
},
{
label: 'Scope',
name: 'scope',
type: 'string',
hidden: true,
default: scopes.join(' ')
}
]
}
}
module.exports = { credClass: MsoftOutlookOAuth2 }

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packages/components/credentials/MicrosoftTeamsOAuth2.credential.ts Normal file
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import { INodeParams, INodeCredential } from '../src/Interface'
// Comprehensive scopes for Microsoft Teams operations
const scopes = [
// Basic authentication
'openid',
'offline_access',
// User permissions
'User.Read',
'User.ReadWrite.All',
// Teams and Groups
'Group.ReadWrite.All',
'Team.ReadBasic.All',
'Team.Create',
'TeamMember.ReadWrite.All',
// Channels
'Channel.ReadBasic.All',
'Channel.Create',
'Channel.Delete.All',
'ChannelMember.ReadWrite.All',
// Chat operations
'Chat.ReadWrite',
'Chat.Create',
'ChatMember.ReadWrite',
// Messages
'ChatMessage.Send',
'ChatMessage.Read',
'ChannelMessage.Send',
'ChannelMessage.Read.All',
// Reactions and advanced features
'TeamsActivity.Send'
]
class MsoftTeamsOAuth2 implements INodeCredential {
label: string
name: string
version: number
inputs: INodeParams[]
description: string
constructor() {
this.label = 'Microsoft Teams OAuth2'
this.name = 'microsoftTeamsOAuth2'
this.version = 1.0
this.description =
'You can find the setup instructions <a target="_blank" href="https://docs.flowiseai.com/integrations/langchain/tools/microsoft-teams">here</a>'
this.inputs = [
{
label: 'Authorization URL',
name: 'authorizationUrl',
type: 'string',
default: 'https://login.microsoftonline.com/<tenantId>/oauth2/v2.0/authorize'
},
{
label: 'Access Token URL',
name: 'accessTokenUrl',
type: 'string',
default: 'https://login.microsoftonline.com/<tenantId>/oauth2/v2.0/token'
},
{
label: 'Client ID',
name: 'clientId',
type: 'string'
},
{
label: 'Client Secret',
name: 'clientSecret',
type: 'password'
},
{
label: 'Scope',
name: 'scope',
type: 'string',
hidden: true,
default: scopes.join(' ')
}
]
}
}
module.exports = { credClass: MsoftTeamsOAuth2 }

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packages/components/credentials/OxylabsApi.credential.ts Normal file
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import { INodeParams, INodeCredential } from '../src/Interface'
class OxylabsApiCredential implements INodeCredential {
label: string
name: string
version: number
description: string
inputs: INodeParams[]
constructor() {
this.label = 'Oxylabs API'
this.name = 'oxylabsApi'
this.version = 1.0
this.description = 'Oxylabs API credentials description, to add more info'
this.inputs = [
{
label: 'Oxylabs Username',
name: 'username',
type: 'string'
},
{
label: 'Oxylabs Password',
name: 'password',
type: 'password'
}
]
}
}
module.exports = { credClass: OxylabsApiCredential }

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packages/components/credentials/SambanovaApi.credential.ts Normal file
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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 }

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packages/components/credentials/TeradataBearerToken.credential.ts Normal file
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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 }

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packages/components/credentials/TeradataTD2.credential.ts Normal file
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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 }

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packages/components/credentials/TeradataVectorStoreApi.credential.ts Normal file
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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 }

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import { RunCollectorCallbackHandler } from '@langchain/core/tracers/run_collector'
import { Run } from '@langchain/core/tracers/base'
import { EvaluationRunner } from './EvaluationRunner'
import { encoding_for_model, get_encoding } from '@dqbd/tiktoken'
export class EvaluationRunTracer extends RunCollectorCallbackHandler {
evaluationRunId: string
model: string
constructor(id: string) {
super()
this.evaluationRunId = id
}
async persistRun(run: Run): Promise<void> {
return super.persistRun(run)
}
countPromptTokens = (encoding: any, run: Run): number => {
let promptTokenCount = 0
if (encoding) {
if (run.inputs?.messages?.length > 0 && run.inputs?.messages[0]?.length > 0) {
run.inputs.messages[0].map((message: any) => {
let content = message.content
? message.content
: message.SystemMessage?.content
? message.SystemMessage.content
: message.HumanMessage?.content
? message.HumanMessage.content
: message.AIMessage?.content
? message.AIMessage.content
: undefined
promptTokenCount += content ? encoding.encode(content).length : 0
})
}
if (run.inputs?.prompts?.length > 0) {
const content = run.inputs.prompts[0]
promptTokenCount += content ? encoding.encode(content).length : 0
}
}
return promptTokenCount
}
countCompletionTokens = (encoding: any, run: Run): number => {
let completionTokenCount = 0
if (encoding) {
if (run.outputs?.generations?.length > 0 && run.outputs?.generations[0]?.length > 0) {
run.outputs?.generations[0].map((chunk: any) => {
let content = chunk.text ? chunk.text : chunk.message?.content ? chunk.message?.content : undefined
completionTokenCount += content ? encoding.encode(content).length : 0
})
}
}
return completionTokenCount
}
extractModelName = (run: Run): string => {
return (
(run?.serialized as any)?.kwargs?.model ||
(run?.serialized as any)?.kwargs?.model_name ||
(run?.extra as any)?.metadata?.ls_model_name ||
(run?.extra as any)?.metadata?.fw_model_name
)
}
onLLMEnd?(run: Run): void | Promise<void> {
if (run.name) {
let provider = run.name
if (provider === 'BedrockChat') {
provider = 'awsChatBedrock'
}
EvaluationRunner.addMetrics(
this.evaluationRunId,
JSON.stringify({
provider: provider
})
)
}
let model = this.extractModelName(run)
if (run.outputs?.llmOutput?.tokenUsage) {
const tokenUsage = run.outputs?.llmOutput?.tokenUsage
if (tokenUsage) {
const metric = {
completionTokens: tokenUsage.completionTokens,
promptTokens: tokenUsage.promptTokens,
model: model,
totalTokens: tokenUsage.totalTokens
}
EvaluationRunner.addMetrics(this.evaluationRunId, JSON.stringify(metric))
}
} else if (
run.outputs?.generations?.length > 0 &&
run.outputs?.generations[0].length > 0 &&
run.outputs?.generations[0][0]?.message?.usage_metadata?.total_tokens
) {
const usage_metadata = run.outputs?.generations[0][0]?.message?.usage_metadata
if (usage_metadata) {
const metric = {
completionTokens: usage_metadata.output_tokens,
promptTokens: usage_metadata.input_tokens,
model: model || this.model,
totalTokens: usage_metadata.total_tokens
}
EvaluationRunner.addMetrics(this.evaluationRunId, JSON.stringify(metric))
}
} else {
let encoding: any = undefined
let promptInputTokens = 0
let completionTokenCount = 0
try {
encoding = encoding_for_model(model as any)
promptInputTokens = this.countPromptTokens(encoding, run)
completionTokenCount = this.countCompletionTokens(encoding, run)
} catch (e) {
try {
// as tiktoken will fail for non openai models, assume that is 'cl100k_base'
encoding = get_encoding('cl100k_base')
promptInputTokens = this.countPromptTokens(encoding, run)
completionTokenCount = this.countCompletionTokens(encoding, run)
} catch (e) {
// stay silent
}
}
const metric = {
completionTokens: completionTokenCount,
promptTokens: promptInputTokens,
model: model,
totalTokens: promptInputTokens + completionTokenCount
}
EvaluationRunner.addMetrics(this.evaluationRunId, JSON.stringify(metric))
//cleanup
this.model = ''
}
}
async onRunUpdate(run: Run): Promise<void> {
const json = {
[run.run_type]: elapsed(run)
}
let metric = JSON.stringify(json)
if (metric) {
EvaluationRunner.addMetrics(this.evaluationRunId, metric)
}
if (run.run_type === 'llm') {
let model = this.extractModelName(run)
if (model) {
EvaluationRunner.addMetrics(this.evaluationRunId, JSON.stringify({ model: model }))
this.model = model
}
// OpenAI non streaming models
const estimatedTokenUsage = run.outputs?.llmOutput?.estimatedTokenUsage
if (estimatedTokenUsage && typeof estimatedTokenUsage === 'object' && Object.keys(estimatedTokenUsage).length > 0) {
EvaluationRunner.addMetrics(this.evaluationRunId, estimatedTokenUsage)
}
}
}
}
function elapsed(run: Run) {
if (!run.end_time) return ''
const elapsed = run.end_time - run.start_time
return `${elapsed.toFixed(2)}`
}

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import { ChatMessage, LLMEndEvent, LLMStartEvent, LLMStreamEvent, MessageContentTextDetail, RetrievalEndEvent, Settings } from 'llamaindex'
import { EvaluationRunner } from './EvaluationRunner'
import { additionalCallbacks, ICommonObject, INodeData } from '../src'
import { RetrievalStartEvent } from 'llamaindex/dist/type/llm/types'
import { AgentEndEvent, AgentStartEvent } from 'llamaindex/dist/type/agent/types'
import { encoding_for_model } from '@dqbd/tiktoken'
import { MessageContent } from '@langchain/core/messages'
export class EvaluationRunTracerLlama {
evaluationRunId: string
static cbInit = false
static startTimes = new Map<string, number>()
static models = new Map<string, string>()
static tokenCounts = new Map<string, number>()
constructor(id: string) {
this.evaluationRunId = id
EvaluationRunTracerLlama.constructCallBacks()
}
static constructCallBacks = () => {
if (!EvaluationRunTracerLlama.cbInit) {
Settings.callbackManager.on('llm-start', (event: LLMStartEvent) => {
const evalID = (event as any).reason.parent?.caller?.evaluationRunId || (event as any).reason.caller?.evaluationRunId
if (!evalID) return
const model = (event as any).reason?.caller?.model
if (model) {
EvaluationRunTracerLlama.models.set(evalID, model)
try {
const encoding = encoding_for_model(model)
if (encoding) {
const { messages } = event.detail.payload
let tokenCount = messages.reduce((count: number, message: ChatMessage) => {
return count + encoding.encode(extractText(message.content)).length
}, 0)
EvaluationRunTracerLlama.tokenCounts.set(evalID + '_promptTokens', tokenCount)
EvaluationRunTracerLlama.tokenCounts.set(evalID + '_outputTokens', 0)
}
} catch (e) {
// catch the error and continue to work.
}
}
EvaluationRunTracerLlama.startTimes.set(evalID + '_llm', event.timeStamp)
})
Settings.callbackManager.on('llm-end', (event: LLMEndEvent) => {
this.calculateAndSetMetrics(event, 'llm')
})
Settings.callbackManager.on('llm-stream', (event: LLMStreamEvent) => {
const evalID = (event as any).reason.parent?.caller?.evaluationRunId || (event as any).reason.caller?.evaluationRunId
if (!evalID) return
const { chunk } = event.detail.payload
const { delta } = chunk
const model = (event as any).reason?.caller?.model
try {
const encoding = encoding_for_model(model)
if (encoding) {
let tokenCount = EvaluationRunTracerLlama.tokenCounts.get(evalID + '_outputTokens') || 0
tokenCount += encoding.encode(extractText(delta)).length
EvaluationRunTracerLlama.tokenCounts.set(evalID + '_outputTokens', tokenCount)
}
} catch (e) {
// catch the error and continue to work.
}
})
Settings.callbackManager.on('retrieve-start', (event: RetrievalStartEvent) => {
const evalID = (event as any).reason.parent?.caller?.evaluationRunId || (event as any).reason.caller?.evaluationRunId
if (evalID) {
EvaluationRunTracerLlama.startTimes.set(evalID + '_retriever', event.timeStamp)
}
})
Settings.callbackManager.on('retrieve-end', (event: RetrievalEndEvent) => {
this.calculateAndSetMetrics(event, 'retriever')
})
Settings.callbackManager.on('agent-start', (event: AgentStartEvent) => {
const evalID = (event as any).reason.parent?.caller?.evaluationRunId || (event as any).reason.caller?.evaluationRunId
if (evalID) {
EvaluationRunTracerLlama.startTimes.set(evalID + '_agent', event.timeStamp)
}
})
Settings.callbackManager.on('agent-end', (event: AgentEndEvent) => {
this.calculateAndSetMetrics(event, 'agent')
})
EvaluationRunTracerLlama.cbInit = true
}
}
private static calculateAndSetMetrics(event: any, label: string) {
const evalID = event.reason.parent?.caller?.evaluationRunId || event.reason.caller?.evaluationRunId
if (!evalID) return
const startTime = EvaluationRunTracerLlama.startTimes.get(evalID + '_' + label) as number
let model =
(event as any).reason?.caller?.model || (event as any).reason?.caller?.llm?.model || EvaluationRunTracerLlama.models.get(evalID)
if (event.detail.payload?.response?.message && model) {
try {
const encoding = encoding_for_model(model)
if (encoding) {
let tokenCount = EvaluationRunTracerLlama.tokenCounts.get(evalID + '_outputTokens') || 0
tokenCount += encoding.encode(event.detail.payload.response?.message?.content || '').length
EvaluationRunTracerLlama.tokenCounts.set(evalID + '_outputTokens', tokenCount)
}
} catch (e) {
// catch the error and continue to work.
}
}
// Anthropic
if (event.detail?.payload?.response?.raw?.usage) {
const usage = event.detail.payload.response.raw.usage
if (usage.output_tokens) {
const metric = {
completionTokens: usage.output_tokens,
promptTokens: usage.input_tokens,
model: model,
totalTokens: usage.input_tokens + usage.output_tokens
}
EvaluationRunner.addMetrics(evalID, JSON.stringify(metric))
} else if (usage.completion_tokens) {
const metric = {
completionTokens: usage.completion_tokens,
promptTokens: usage.prompt_tokens,
model: model,
totalTokens: usage.total_tokens
}
EvaluationRunner.addMetrics(evalID, JSON.stringify(metric))
}
} else if (event.detail?.payload?.response?.raw['amazon-bedrock-invocationMetrics']) {
const usage = event.detail?.payload?.response?.raw['amazon-bedrock-invocationMetrics']
const metric = {
completionTokens: usage.outputTokenCount,
promptTokens: usage.inputTokenCount,
model: event.detail?.payload?.response?.raw.model,
totalTokens: usage.inputTokenCount + usage.outputTokenCount
}
EvaluationRunner.addMetrics(evalID, JSON.stringify(metric))
} else {
const metric = {
[label]: (event.timeStamp - startTime).toFixed(2),
completionTokens: EvaluationRunTracerLlama.tokenCounts.get(evalID + '_outputTokens'),
promptTokens: EvaluationRunTracerLlama.tokenCounts.get(evalID + '_promptTokens'),
model: model || EvaluationRunTracerLlama.models.get(evalID) || '',
totalTokens:
(EvaluationRunTracerLlama.tokenCounts.get(evalID + '_outputTokens') || 0) +
(EvaluationRunTracerLlama.tokenCounts.get(evalID + '_promptTokens') || 0)
}
EvaluationRunner.addMetrics(evalID, JSON.stringify(metric))
}
//cleanup
EvaluationRunTracerLlama.startTimes.delete(evalID + '_' + label)
EvaluationRunTracerLlama.startTimes.delete(evalID + '_outputTokens')
EvaluationRunTracerLlama.startTimes.delete(evalID + '_promptTokens')
EvaluationRunTracerLlama.models.delete(evalID)
}
static async injectEvaluationMetadata(nodeData: INodeData, options: ICommonObject, callerObj: any) {
if (options.evaluationRunId && callerObj) {
// these are needed for evaluation runs
options.llamaIndex = true
await additionalCallbacks(nodeData, options)
Object.defineProperty(callerObj, 'evaluationRunId', {
enumerable: true,
configurable: true,
writable: true,
value: options.evaluationRunId
})
}
}
}
// from https://github.com/run-llama/LlamaIndexTS/blob/main/packages/core/src/llm/utils.ts
export function extractText(message: MessageContent): string {
if (typeof message !== 'string' && !Array.isArray(message)) {
console.warn('extractText called with non-MessageContent message, this is likely a bug.')
return `${message}`
} else if (typeof message !== 'string' && Array.isArray(message)) {
// message is of type MessageContentDetail[] - retrieve just the text parts and concatenate them
// so we can pass them to the context generator
return message
.filter((c): c is MessageContentTextDetail => c.type === 'text')
.map((c) => c.text)
.join('\n\n')
} else {
return message
}
}

226
packages/components/evaluation/EvaluationRunner.ts Normal file
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@ -0,0 +1,226 @@
import axios from 'axios'
import { v4 as uuidv4 } from 'uuid'
import { ICommonObject } from '../src'
import { getModelConfigByModelName, MODEL_TYPE } from '../src/modelLoader'
export class EvaluationRunner {
static metrics = new Map<string, string[]>()
static getCostMetrics = async (selectedProvider: string, selectedModel: string) => {
let modelConfig = await getModelConfigByModelName(MODEL_TYPE.CHAT, selectedProvider, selectedModel)
if (modelConfig) {
if (modelConfig['cost_values']) {
return modelConfig.cost_values
}
return { cost_values: modelConfig }
} else {
modelConfig = await getModelConfigByModelName(MODEL_TYPE.LLM, selectedProvider, selectedModel)
if (modelConfig) {
if (modelConfig['cost_values']) {
return modelConfig.cost_values
}
return { cost_values: modelConfig }
}
}
return undefined
}
static async getAndDeleteMetrics(id: string) {
const val = EvaluationRunner.metrics.get(id)
if (val) {
try {
//first lets get the provider and model
let selectedModel = undefined
let selectedProvider = undefined
if (val && val.length > 0) {
let modelName = ''
let providerName = ''
for (let i = 0; i < val.length; i++) {
const metric = val[i]
if (typeof metric === 'object') {
modelName = metric['model']
providerName = metric['provider']
} else {
modelName = JSON.parse(metric)['model']
providerName = JSON.parse(metric)['provider']
}
if (modelName) {
selectedModel = modelName
}
if (providerName) {
selectedProvider = providerName
}
}
}
if (selectedProvider && selectedModel) {
const modelConfig = await EvaluationRunner.getCostMetrics(selectedProvider, selectedModel)
if (modelConfig) {
val.push(JSON.stringify({ cost_values: modelConfig }))
}
}
} catch (error) {
//stay silent
}
}
EvaluationRunner.metrics.delete(id)
return val
}
static addMetrics(id: string, metric: string) {
if (EvaluationRunner.metrics.has(id)) {
EvaluationRunner.metrics.get(id)?.push(metric)
} else {
EvaluationRunner.metrics.set(id, [metric])
}
}
baseURL = ''
constructor(baseURL: string) {
this.baseURL = baseURL
}
getChatflowApiKey(chatflowId: string, apiKeys: { chatflowId: string; apiKey: string }[] = []) {
return apiKeys.find((item) => item.chatflowId === chatflowId)?.apiKey || ''
}
public async runEvaluations(data: ICommonObject) {
const chatflowIds = JSON.parse(data.chatflowId)
const returnData: ICommonObject = {}
returnData.evaluationId = data.evaluationId
returnData.runDate = new Date()
returnData.rows = []
for (let i = 0; i < data.dataset.rows.length; i++) {
returnData.rows.push({
input: data.dataset.rows[i].input,
expectedOutput: data.dataset.rows[i].output,
itemNo: data.dataset.rows[i].sequenceNo,
evaluations: [],
status: 'pending'
})
}
for (let i = 0; i < chatflowIds.length; i++) {
const chatflowId = chatflowIds[i]
await this.evaluateChatflow(chatflowId, this.getChatflowApiKey(chatflowId, data.apiKeys), data, returnData)
}
return returnData
}
async evaluateChatflow(chatflowId: string, apiKey: string, data: any, returnData: any) {
for (let i = 0; i < data.dataset.rows.length; i++) {
const item = data.dataset.rows[i]
const uuid = uuidv4()
const headers: any = {
'X-Request-ID': uuid,
'X-Flowise-Evaluation': 'true'
}
if (apiKey) {
headers['Authorization'] = `Bearer ${apiKey}`
}
let axiosConfig = {
headers: headers
}
let startTime = performance.now()
const runData: any = {}
runData.chatflowId = chatflowId
runData.startTime = startTime
const postData: any = { question: item.input, evaluationRunId: uuid, evaluation: true }
if (data.sessionId) {
postData.overrideConfig = { sessionId: data.sessionId }
}
try {
let response = await axios.post(`${this.baseURL}/api/v1/prediction/${chatflowId}`, postData, axiosConfig)
let agentFlowMetrics: any[] = []
if (response?.data?.agentFlowExecutedData) {
for (let i = 0; i < response.data.agentFlowExecutedData.length; i++) {
const agentFlowExecutedData = response.data.agentFlowExecutedData[i]
const input_tokens = agentFlowExecutedData?.data?.output?.usageMetadata?.input_tokens || 0
const output_tokens = agentFlowExecutedData?.data?.output?.usageMetadata?.output_tokens || 0
const total_tokens =
agentFlowExecutedData?.data?.output?.usageMetadata?.total_tokens || input_tokens + output_tokens
const metrics: any = {
promptTokens: input_tokens,
completionTokens: output_tokens,
totalTokens: total_tokens,
provider:
agentFlowExecutedData.data?.input?.llmModelConfig?.llmModel ||
agentFlowExecutedData.data?.input?.agentModelConfig?.agentModel,
model:
agentFlowExecutedData.data?.input?.llmModelConfig?.modelName ||
agentFlowExecutedData.data?.input?.agentModelConfig?.modelName,
nodeLabel: agentFlowExecutedData?.nodeLabel,
nodeId: agentFlowExecutedData?.nodeId
}
if (metrics.provider && metrics.model) {
const modelConfig = await EvaluationRunner.getCostMetrics(metrics.provider, metrics.model)
if (modelConfig) {
metrics.cost_values = {
input_cost: (modelConfig.cost_values.input_cost || 0) * (input_tokens / 1000),
output_cost: (modelConfig.cost_values.output_cost || 0) * (output_tokens / 1000)
}
metrics.cost_values.total_cost = metrics.cost_values.input_cost + metrics.cost_values.output_cost
}
}
agentFlowMetrics.push(metrics)
}
}
const endTime = performance.now()
const timeTaken = (endTime - startTime).toFixed(2)
if (response?.data?.metrics) {
runData.metrics = response.data.metrics
runData.metrics.push({
apiLatency: timeTaken
})
} else {
runData.metrics = [
{
apiLatency: timeTaken
}
]
}
if (agentFlowMetrics.length > 0) {
runData.nested_metrics = agentFlowMetrics
}
runData.status = 'complete'
let resultText = ''
if (response.data.text) resultText = response.data.text
else if (response.data.json) resultText = '```json\n' + JSON.stringify(response.data.json, null, 2)
else resultText = JSON.stringify(response.data, null, 2)
runData.actualOutput = resultText
runData.latency = timeTaken
runData.error = ''
} catch (error: any) {
runData.status = 'error'
runData.actualOutput = ''
runData.error = error?.response?.data?.message
? error.response.data.message
: error?.message
? error.message
: 'Unknown error'
try {
if (runData.error.indexOf('-') > -1) {
// if there is a dash, remove all content before
runData.error = 'Error: ' + runData.error.substr(runData.error.indexOf('-') + 1).trim()
}
} catch (error) {
//stay silent
}
const endTime = performance.now()
const timeTaken = (endTime - startTime).toFixed(2)
runData.metrics = [
{
apiLatency: timeTaken
}
]
runData.latency = timeTaken
}
runData.uuid = uuid
returnData.rows[i].evaluations.push(runData)
}
return returnData
}
}

15
packages/components/jest.config.js Normal file
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@ -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'
}
}

349
packages/components/models.json
View File

@ -3,6 +3,41 @@
{
"name": "awsChatBedrock",
"models": [
{
"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 +315,30 @@
{
"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 +416,18 @@
"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 +487,38 @@
"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-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 +526,13 @@
"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 +628,29 @@
"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-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",
@ -581,6 +697,42 @@
{
"name": "chatGoogleVertexAI",
"models": [
{
"label": "gemini-3-pro-preview",
"name": "gemini-3-pro-preview",
"input_cost": 0.00002,
"output_cost": 0.00012
},
{
"label": "gemini-2.5-pro",
"name": "gemini-2.5-pro",
"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",
"input_cost": 1e-7,
"output_cost": 4e-7
},
{
"label": "gemini-2.0-flash-lite",
"name": "gemini-2.0-flash-lite-001",
"input_cost": 7.5e-8,
"output_cost": 3e-7
},
{
"label": "gemini-1.5-flash-002",
"name": "gemini-1.5-flash-002",
@ -617,6 +769,27 @@
"input_cost": 1.25e-7,
"output_cost": 3.75e-7
},
{
"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",
@ -673,11 +846,63 @@
"input_cost": 2.5e-7,
"output_cost": 1.25e-6
}
],
"regions": [
{ "label": "us-east1", "name": "us-east1" },
{ "label": "us-east4", "name": "us-east4" },
{ "label": "us-central1", "name": "us-central1" },
{ "label": "us-west1", "name": "us-west1" },
{ "label": "europe-west4", "name": "europe-west4" },
{ "label": "europe-west1", "name": "europe-west1" },
{ "label": "europe-west3", "name": "europe-west3" },
{ "label": "europe-west2", "name": "europe-west2" },
{ "label": "asia-east1", "name": "asia-east1" },
{ "label": "asia-southeast1", "name": "asia-southeast1" },
{ "label": "asia-northeast1", "name": "asia-northeast1" },
{ "label": "asia-south1", "name": "asia-south1" },
{ "label": "australia-southeast1", "name": "australia-southeast1" },
{ "label": "southamerica-east1", "name": "southamerica-east1" },
{ "label": "africa-south1", "name": "africa-south1" },
{ "label": "asia-east2", "name": "asia-east2" },
{ "label": "asia-northeast2", "name": "asia-northeast2" },
{ "label": "asia-northeast3", "name": "asia-northeast3" },
{ "label": "asia-south2", "name": "asia-south2" },
{ "label": "asia-southeast2", "name": "asia-southeast2" },
{ "label": "australia-southeast2", "name": "australia-southeast2" },
{ "label": "europe-central2", "name": "europe-central2" },
{ "label": "europe-north1", "name": "europe-north1" },
{ "label": "europe-north2", "name": "europe-north2" },
{ "label": "europe-southwest1", "name": "europe-southwest1" },
{ "label": "europe-west10", "name": "europe-west10" },
{ "label": "europe-west12", "name": "europe-west12" },
{ "label": "europe-west6", "name": "europe-west6" },
{ "label": "europe-west8", "name": "europe-west8" },
{ "label": "europe-west9", "name": "europe-west9" },
{ "label": "me-central1", "name": "me-central1" },
{ "label": "me-central2", "name": "me-central2" },
{ "label": "me-west1", "name": "me-west1" },
{ "label": "northamerica-northeast1", "name": "northamerica-northeast1" },
{ "label": "northamerica-northeast2", "name": "northamerica-northeast2" },
{ "label": "northamerica-south1", "name": "northamerica-south1" },
{ "label": "southamerica-west1", "name": "southamerica-west1" },
{ "label": "us-east5", "name": "us-east5" },
{ "label": "us-south1", "name": "us-south1" },
{ "label": "us-west2", "name": "us-west2" },
{ "label": "us-west3", "name": "us-west3" },
{ "label": "us-west4", "name": "us-west4" }
]
},
{
"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"
@ -789,6 +1014,30 @@
{
"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",
@ -1217,6 +1466,18 @@
"name": "mistral-large-2402",
"input_cost": 0.002,
"output_cost": 0.006
},
{
"label": "codestral-latsest",
"name": "codestral-latest",
"input_cost": 0.0002,
"output_cost": 0.0006
},
{
"label": "devstral-small-2505",
"name": "devstral-small-2505",
"input_cost": 0.0001,
"output_cost": 0.0003
}
]
},
@ -1511,6 +1772,18 @@
"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
}
]
},
@ -1711,29 +1984,65 @@
"name": "googlevertexaiEmbeddings",
"models": [
{
"label": "multimodalembedding",
"name": "multimodalembedding"
"label": "gemini-embedding-001",
"name": "gemini-embedding-001"
},
{
"label": "text-embedding-004",
"name": "text-embedding-004"
},
{
"label": "text-embedding-005",
"name": "text-embedding-005"
},
{
"label": "text-multilingual-embedding-002",
"name": "text-multilingual-embedding-002"
},
{
"label": "textembedding-gecko@001",
"name": "textembedding-gecko@001"
},
{
"label": "textembedding-gecko@latest",
"name": "textembedding-gecko@latest"
},
{
"label": "textembedding-gecko-multilingual@latest",
"name": "textembedding-gecko-multilingual@latest"
}
],
"regions": [
{ "label": "us-east1", "name": "us-east1" },
{ "label": "us-east4", "name": "us-east4" },
{ "label": "us-central1", "name": "us-central1" },
{ "label": "us-west1", "name": "us-west1" },
{ "label": "europe-west4", "name": "europe-west4" },
{ "label": "europe-west1", "name": "europe-west1" },
{ "label": "europe-west3", "name": "europe-west3" },
{ "label": "europe-west2", "name": "europe-west2" },
{ "label": "asia-east1", "name": "asia-east1" },
{ "label": "asia-southeast1", "name": "asia-southeast1" },
{ "label": "asia-northeast1", "name": "asia-northeast1" },
{ "label": "asia-south1", "name": "asia-south1" },
{ "label": "australia-southeast1", "name": "australia-southeast1" },
{ "label": "southamerica-east1", "name": "southamerica-east1" },
{ "label": "africa-south1", "name": "africa-south1" },
{ "label": "asia-east2", "name": "asia-east2" },
{ "label": "asia-northeast2", "name": "asia-northeast2" },
{ "label": "asia-northeast3", "name": "asia-northeast3" },
{ "label": "asia-south2", "name": "asia-south2" },
{ "label": "asia-southeast2", "name": "asia-southeast2" },
{ "label": "australia-southeast2", "name": "australia-southeast2" },
{ "label": "europe-central2", "name": "europe-central2" },
{ "label": "europe-north1", "name": "europe-north1" },
{ "label": "europe-north2", "name": "europe-north2" },
{ "label": "europe-southwest1", "name": "europe-southwest1" },
{ "label": "europe-west10", "name": "europe-west10" },
{ "label": "europe-west12", "name": "europe-west12" },
{ "label": "europe-west6", "name": "europe-west6" },
{ "label": "europe-west8", "name": "europe-west8" },
{ "label": "europe-west9", "name": "europe-west9" },
{ "label": "me-central1", "name": "me-central1" },
{ "label": "me-central2", "name": "me-central2" },
{ "label": "me-west1", "name": "me-west1" },
{ "label": "northamerica-northeast1", "name": "northamerica-northeast1" },
{ "label": "northamerica-northeast2", "name": "northamerica-northeast2" },
{ "label": "northamerica-south1", "name": "northamerica-south1" },
{ "label": "southamerica-west1", "name": "southamerica-west1" },
{ "label": "us-east5", "name": "us-east5" },
{ "label": "us-south1", "name": "us-south1" },
{ "label": "us-west2", "name": "us-west2" },
{ "label": "us-west3", "name": "us-west3" },
{ "label": "us-west4", "name": "us-west4" }
]
},
{

1518
packages/components/nodes/agentflow/Agent/Agent.ts
View File

File diff suppressed because it is too large Load Diff

7
packages/components/nodes/agentflow/Condition/Condition.ts
View File

@ -1,4 +1,5 @@
import { CommonType, ICommonObject, ICondition, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
import removeMarkdown from 'remove-markdown'
class Condition_Agentflow implements INode {
label: string
@ -300,8 +301,8 @@ class Condition_Agentflow implements INode {
value2 = parseFloat(_value2 as string) || 0
break
default: // string
value1 = _value1 as string
value2 = _value2 as string
value1 = removeMarkdown((_value1 as string) || '')
value2 = removeMarkdown((_value2 as string) || '')
}
const compareOperationResult = compareOperationFunctions[operation](value1, value2)
@ -316,7 +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: '',

62
packages/components/nodes/agentflow/ConditionAgent/ConditionAgent.ts
View File

@ -27,7 +27,7 @@ class ConditionAgent_Agentflow implements INode {
constructor() {
this.label = 'Condition Agent'
this.name = 'conditionAgentAgentflow'
this.version = 1.0
this.version = 1.1
this.type = 'ConditionAgent'
this.category = 'Agent Flows'
this.description = `Utilize an agent to split flows based on dynamic conditions`
@ -80,6 +80,26 @@ class ConditionAgent_Agentflow implements INode {
scenario: ''
}
]
},
{
label: 'Override System Prompt',
name: 'conditionAgentOverrideSystemPrompt',
type: 'boolean',
description: 'Override initial system prompt for Condition Agent',
optional: true
},
{
label: 'Node System Prompt',
name: 'conditionAgentSystemPrompt',
type: 'string',
rows: 4,
optional: true,
acceptVariable: true,
default: CONDITION_AGENT_SYSTEM_PROMPT,
description: 'Expert use only. Modifying this can significantly alter agent behavior. Leave default if unsure',
show: {
conditionAgentOverrideSystemPrompt: true
}
}
/*{
label: 'Enable Memory',
@ -242,6 +262,12 @@ class ConditionAgent_Agentflow implements INode {
const conditionAgentInput = nodeData.inputs?.conditionAgentInput as string
let input = conditionAgentInput || question
const conditionAgentInstructions = nodeData.inputs?.conditionAgentInstructions as string
const conditionAgentSystemPrompt = nodeData.inputs?.conditionAgentSystemPrompt as string
const conditionAgentOverrideSystemPrompt = nodeData.inputs?.conditionAgentOverrideSystemPrompt as boolean
let systemPrompt = CONDITION_AGENT_SYSTEM_PROMPT
if (conditionAgentSystemPrompt && conditionAgentOverrideSystemPrompt) {
systemPrompt = conditionAgentSystemPrompt
}
// Extract memory and configuration options
const enableMemory = nodeData.inputs?.conditionAgentEnableMemory as boolean
@ -277,31 +303,15 @@ class ConditionAgent_Agentflow implements INode {
const messages: BaseMessageLike[] = [
{
role: 'system',
content: CONDITION_AGENT_SYSTEM_PROMPT
content: systemPrompt
},
{
role: 'user',
content: `{"input": "Hello", "scenarios": ["user is asking about AI", "default"], "instruction": "Your task is to check and see if user is asking topic about AI"}`
content: `{"input": "Hello", "scenarios": ["user is asking about AI", "user is not asking about AI"], "instruction": "Your task is to check if the user is asking about AI."}`
},
{
role: 'assistant',
content: `\`\`\`json\n{"output": "default"}\n\`\`\``
},
{
role: 'user',
content: `{"input": "What is AIGC?", "scenarios": ["user is asking about AI", "default"], "instruction": "Your task is to check and see if user is asking topic about AI"}`
},
{
role: 'assistant',
content: `\`\`\`json\n{"output": "user is asking about AI"}\n\`\`\``
},
{
role: 'user',
content: `{"input": "Can you explain deep learning?", "scenarios": ["user is interested in AI topics", "default"], "instruction": "Determine if the user is interested in learning about AI"}`
},
{
role: 'assistant',
content: `\`\`\`json\n{"output": "user is interested in AI topics"}\n\`\`\``
content: `\`\`\`json\n{"output": "user is not asking about AI"}\n\`\`\``
}
]
// Use to store messages with image file references as we do not want to store the base64 data into database
@ -374,15 +384,19 @@ class ConditionAgent_Agentflow implements INode {
)
}
let calledOutputName = 'default'
let calledOutputName: string
try {
const parsedResponse = this.parseJsonMarkdown(response.content as string)
if (!parsedResponse.output) {
throw new Error('Missing "output" key in response')
if (!parsedResponse.output || typeof parsedResponse.output !== 'string') {
throw new Error('LLM response is missing the "output" key or it is not a string.')
}
calledOutputName = parsedResponse.output
} catch (error) {
console.warn(`Failed to parse LLM response: ${error}. Using default output.`)
throw new Error(
`Failed to parse a valid scenario from the LLM's response. Please check if the model is capable of following JSON output instructions. Raw LLM Response: "${
response.content as string
}"`
)
}
// Clean up empty inputs

79
packages/components/nodes/agentflow/CustomFunction/CustomFunction.ts
View File

@ -8,8 +8,7 @@ import {
INodeParams,
IServerSideEventStreamer
} from '../../../src/Interface'
import { availableDependencies, defaultAllowBuiltInDep, getVars, prepareSandboxVars } from '../../../src/utils'
import { NodeVM } from '@flowiseai/nodevm'
import { getVars, executeJavaScriptCode, createCodeExecutionSandbox, processTemplateVariables } from '../../../src/utils'
import { updateFlowState } from '../utils'
interface ICustomFunctionInputVariables {
@ -19,9 +18,9 @@ interface ICustomFunctionInputVariables {
const exampleFunc = `/*
* You can use any libraries imported in Flowise
* You can use properties specified in Input Schema as variables. Ex: Property = userid, Variable = $userid
* You can use properties specified in Input Variables with the prefix $. For example: $foo
* You can get default flow config: $flow.sessionId, $flow.chatId, $flow.chatflowId, $flow.input, $flow.state
* You can get custom variables: $vars.<variable-name>
* You can get global variables: $vars.<variable-name>
* Must return a string value at the end of function
*/
@ -146,77 +145,51 @@ 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)
const variables = await getVars(appDataSource, databaseEntities, nodeData, options)
const flow = {
chatflowId: options.chatflowid,
sessionId: options.sessionId,
chatId: options.chatId,
input
input,
state
}
let sandbox: any = {
$input: input,
util: undefined,
Symbol: undefined,
child_process: undefined,
fs: undefined,
process: undefined
}
sandbox['$vars'] = prepareSandboxVars(variables)
sandbox['$flow'] = flow
// Create additional sandbox variables for custom function inputs
const additionalSandbox: ICommonObject = {}
for (const item of functionInputVariables) {
const variableName = item.variableName
const variableValue = item.variableValue
sandbox[`$${variableName}`] = variableValue
additionalSandbox[`$${variableName}`] = variableValue
}
const builtinDeps = process.env.TOOL_FUNCTION_BUILTIN_DEP
? defaultAllowBuiltInDep.concat(process.env.TOOL_FUNCTION_BUILTIN_DEP.split(','))
: defaultAllowBuiltInDep
const externalDeps = process.env.TOOL_FUNCTION_EXTERNAL_DEP ? process.env.TOOL_FUNCTION_EXTERNAL_DEP.split(',') : []
const deps = availableDependencies.concat(externalDeps)
const sandbox = createCodeExecutionSandbox(input, variables, flow, additionalSandbox)
const nodeVMOptions = {
console: 'inherit',
sandbox,
require: {
external: { modules: deps },
builtin: builtinDeps
},
eval: false,
wasm: false,
timeout: 10000
} as any
// Setup streaming function if needed
const streamOutput = isStreamable
? (output: string) => {
const sseStreamer: IServerSideEventStreamer = options.sseStreamer
sseStreamer.streamTokenEvent(chatId, output)
}
: undefined
const vm = new NodeVM(nodeVMOptions)
try {
const response = await vm.run(`module.exports = async function() {${javascriptFunction}}()`, __dirname)
const response = await executeJavaScriptCode(javascriptFunction, sandbox, {
libraries: ['axios'],
streamOutput
})
let finalOutput = response
if (typeof response === 'object') {
finalOutput = JSON.stringify(response, null, 2)
}
if (isStreamable) {
const sseStreamer: IServerSideEventStreamer = options.sseStreamer
sseStreamer.streamTokenEvent(chatId, finalOutput)
// Update flow state if needed
let newState = { ...state }
if (_customFunctionUpdateState && Array.isArray(_customFunctionUpdateState) && _customFunctionUpdateState.length > 0) {
newState = updateFlowState(state, _customFunctionUpdateState)
}
// 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,

36
packages/components/nodes/agentflow/ExecuteFlow/ExecuteFlow.ts
View File

@ -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 = 1.1
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',
@ -127,7 +128,8 @@ class ExecuteFlow_Agentflow implements INode {
return returnData
}
const chatflows = await appDataSource.getRepository(databaseEntities['ChatFlow']).find()
const searchOptions = options.searchOptions || {}
const chatflows = await appDataSource.getRepository(databaseEntities['ChatFlow']).findBy(searchOptions)
for (let i = 0; i < chatflows.length; i += 1) {
let cfType = 'Chatflow'
@ -161,12 +163,15 @@ 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[]) ?? []
@ -180,7 +185,8 @@ class ExecuteFlow_Agentflow implements INode {
if (selectedFlowId === options.chatflowid) throw new Error('Cannot call the same agentflow!')
let headers: Record<string, string> = {
'Content-Type': 'application/json'
'Content-Type': 'application/json',
'flowise-tool': 'true'
}
if (chatflowApiKey) headers = { ...headers, Authorization: `Bearer ${chatflowApiKey}` }
@ -214,13 +220,7 @@ 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 = []

46
packages/components/nodes/agentflow/HTTP/HTTP.ts
View File

@ -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
@ -21,7 +22,7 @@ class HTTP_Agentflow implements INode {
constructor() {
this.label = 'HTTP'
this.name = 'httpAgentflow'
this.version = 1.0
this.version = 1.1
this.type = 'HTTP'
this.category = 'Agent Flows'
this.description = 'Send a HTTP request'
@ -66,12 +67,14 @@ class HTTP_Agentflow implements INode {
{
label: 'URL',
name: 'url',
type: 'string'
type: 'string',
acceptVariable: true
},
{
label: 'Headers',
name: 'headers',
type: 'array',
acceptVariable: true,
array: [
{
label: 'Key',
@ -83,7 +86,8 @@ class HTTP_Agentflow implements INode {
label: 'Value',
name: 'value',
type: 'string',
default: ''
default: '',
acceptVariable: true
}
],
optional: true
@ -92,6 +96,7 @@ class HTTP_Agentflow implements INode {
label: 'Query Params',
name: 'queryParams',
type: 'array',
acceptVariable: true,
array: [
{
label: 'Key',
@ -103,7 +108,8 @@ class HTTP_Agentflow implements INode {
label: 'Value',
name: 'value',
type: 'string',
default: ''
default: '',
acceptVariable: true
}
],
optional: true
@ -147,6 +153,7 @@ class HTTP_Agentflow implements INode {
label: 'Body',
name: 'body',
type: 'array',
acceptVariable: true,
show: {
bodyType: ['xWwwFormUrlencoded', 'formData']
},
@ -161,7 +168,8 @@ class HTTP_Agentflow implements INode {
label: 'Value',
name: 'value',
type: 'string',
default: ''
default: '',
acceptVariable: true
}
],
optional: true
@ -220,14 +228,14 @@ class HTTP_Agentflow implements INode {
// Add credentials if provided
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
if (credentialData && Object.keys(credentialData).length !== 0) {
const basicAuthUsername = getCredentialParam('username', credentialData, nodeData)
const basicAuthPassword = getCredentialParam('password', credentialData, nodeData)
const basicAuthUsername = getCredentialParam('basicAuthUsername', credentialData, nodeData)
const basicAuthPassword = getCredentialParam('basicAuthPassword', credentialData, nodeData)
const bearerToken = getCredentialParam('token', credentialData, nodeData)
const apiKeyName = getCredentialParam('key', credentialData, nodeData)
const apiKeyValue = getCredentialParam('value', credentialData, nodeData)
// Determine which type of auth to use based on available credentials
if (basicAuthUsername && basicAuthPassword) {
if (basicAuthUsername || basicAuthPassword) {
// Basic Auth
const auth = Buffer.from(`${basicAuthUsername}:${basicAuthPassword}`).toString('base64')
requestHeaders['Authorization'] = `Basic ${auth}`
@ -266,10 +274,11 @@ class HTTP_Agentflow implements INode {
// Handle request body based on body type
if (method !== 'GET' && body) {
switch (bodyType) {
case 'json':
requestConfig.data = typeof body === 'string' ? JSON.parse(body) : body
case 'json': {
requestConfig.data = typeof body === 'string' ? parseJsonBody(body) : body
requestHeaders['Content-Type'] = 'application/json'
break
}
case 'raw':
requestConfig.data = body
break
@ -284,14 +293,14 @@ class HTTP_Agentflow implements INode {
break
}
case 'xWwwFormUrlencoded':
requestConfig.data = querystring.stringify(typeof body === 'string' ? JSON.parse(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
@ -330,6 +339,9 @@ class HTTP_Agentflow implements INode {
} catch (error) {
console.error('HTTP Request Error:', error)
const errorMessage =
error.response?.data?.message || error.response?.data?.error || error.message || 'An error occurred during the HTTP request'
// Format error response
const errorResponse: any = {
id: nodeData.id,
@ -347,7 +359,7 @@ class HTTP_Agentflow implements INode {
},
error: {
name: error.name || 'Error',
message: error.message || 'An error occurred during the HTTP request'
message: errorMessage
},
state
}
@ -360,7 +372,7 @@ class HTTP_Agentflow implements INode {
errorResponse.error.headers = error.response.headers
}
throw new Error(error)
throw new Error(errorMessage)
}
}
}

9
packages/components/nodes/agentflow/HumanInput/HumanInput.ts
View File

@ -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 {

12
packages/components/nodes/agentflow/Iteration/Iteration.ts
View File

@ -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')

285
packages/components/nodes/agentflow/LLM/LLM.ts
View File

@ -1,10 +1,9 @@
import { BaseChatModel } from '@langchain/core/language_models/chat_models'
import { ICommonObject, INode, INodeData, INodeOptionsValue, INodeParams, IServerSideEventStreamer } from '../../../src/Interface'
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 {
getPastChatHistoryImageMessages,
getUniqueImageMessages,
@ -12,7 +11,8 @@ import {
replaceBase64ImagesWithFileReferences,
updateFlowState
} from '../utils'
import { get } from 'lodash'
import { processTemplateVariables, configureStructuredOutput } from '../../../src/utils'
import { flatten } from 'lodash'
class LLM_Agentflow implements INode {
label: string
@ -262,6 +262,7 @@ class LLM_Agentflow implements INode {
}`,
description: 'JSON schema for the structured output',
optional: true,
hideCodeExecute: true,
show: {
'llmStructuredOutput[$index].type': 'jsonArray'
}
@ -358,6 +359,7 @@ class LLM_Agentflow implements INode {
const state = options.agentflowRuntime?.state as ICommonObject
const pastChatHistory = (options.pastChatHistory as BaseMessageLike[]) ?? []
const runtimeChatHistory = (options.agentflowRuntime?.chatHistory as BaseMessageLike[]) ?? []
const prependedChatHistory = options.prependedChatHistory as IMessage[]
const chatId = options.chatId as string
// Initialize the LLM model instance
@ -381,11 +383,27 @@ class LLM_Agentflow implements INode {
// Use to keep track of past messages with image file references
let pastImageMessagesWithFileRef: BaseMessageLike[] = []
// Prepend history ONLY if it is the first node
if (prependedChatHistory.length > 0 && !runtimeChatHistory.length) {
for (const msg of prependedChatHistory) {
const role: string = msg.role === 'apiMessage' ? 'assistant' : 'user'
const content: string = msg.content ?? ''
messages.push({
role,
content
})
}
}
for (const msg of llmMessages) {
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 })
}
}
}
@ -410,7 +428,7 @@ class LLM_Agentflow implements INode {
/*
* If this is the first node:
* - Add images to messages if exist
* - Add user message
* - Add user message if it does not exist in the llmMessages array
*/
if (options.uploads) {
const imageContents = await getUniqueImageMessages(options, messages, modelConfig)
@ -421,7 +439,7 @@ class LLM_Agentflow implements INode {
}
}
if (input && typeof input === 'string') {
if (input && typeof input === 'string' && !llmMessages.some((msg) => msg.role === 'user')) {
messages.push({
role: 'user',
content: input
@ -433,7 +451,7 @@ class LLM_Agentflow implements INode {
// 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
@ -460,11 +478,15 @@ 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)
}
}
@ -486,8 +508,15 @@ class LLM_Agentflow implements INode {
}
// Prepare final response and output object
const finalResponse = (response.content as string) ?? JSON.stringify(response, null, 2)
const output = this.prepareOutputObject(response, finalResponse, startTime, endTime, timeDelta)
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)
}
const output = this.prepareOutputObject(response, finalResponse, startTime, endTime, timeDelta, isStructuredOutput)
// End analytics tracking
if (analyticHandlers && llmIds) {
@ -500,36 +529,7 @@ class LLM_Agentflow implements INode {
}
// 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
}
}
}
}
}
newState = processTemplateVariables(newState, finalResponse)
// Replace the actual messages array with one that includes the file references for images instead of base64 data
const messagesWithFileReferences = replaceBase64ImagesWithFileReferences(
@ -545,7 +545,19 @@ class LLM_Agentflow implements INode {
inputMessages.push(...runtimeImageMessagesWithFileRef)
}
if (input && typeof input === 'string') {
inputMessages.push({ role: 'user', content: input })
if (!enableMemory) {
if (!llmMessages.some((msg) => msg.role === 'user')) {
inputMessages.push({ role: 'user', content: input })
} else {
llmMessages.map((msg) => {
if (msg.role === 'user') {
inputMessages.push({ role: 'user', content: msg.content })
}
})
}
} else {
inputMessages.push({ role: 'user', content: input })
}
}
}
@ -742,59 +754,6 @@ 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
*/
@ -811,16 +770,20 @@ 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)
@ -841,7 +804,8 @@ class LLM_Agentflow implements INode {
finalResponse: string,
startTime: number,
endTime: number,
timeDelta: number
timeDelta: number,
isStructuredOutput: boolean
): any {
const output: any = {
content: finalResponse,
@ -860,6 +824,15 @@ class LLM_Agentflow implements INode {
output.usageMetadata = response.usage_metadata
}
if (isStructuredOutput && typeof response === 'object') {
const structuredOutput = response as Record<string, any>
for (const key in structuredOutput) {
if (structuredOutput[key] !== undefined && structuredOutput[key] !== null) {
output[key] = structuredOutput[key]
}
}
}
return output
}
@ -870,7 +843,12 @@ 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) {
@ -879,107 +857,6 @@ 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 }

69
packages/components/nodes/agentflow/Loop/Loop.ts
View File

@ -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 = 1.1
this.type = 'Loop'
this.category = 'Agent Flows'
this.description = 'Loop back to a previous node'
@ -40,6 +41,40 @@ 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',
freeSolo: true
},
{
label: 'Value',
name: 'value',
type: 'string',
acceptVariable: true,
acceptNodeOutputAsVariable: true
}
]
}
]
}
@ -58,12 +93,20 @@ 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 +118,34 @@ 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

13
packages/components/nodes/agentflow/Retriever/Retriever.ts
View File

@ -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'
@ -119,7 +120,8 @@ class Retriever_Agentflow implements INode {
return returnData
}
const stores = await appDataSource.getRepository(databaseEntities['DocumentStore']).find()
const searchOptions = options.searchOptions || {}
const stores = await appDataSource.getRepository(databaseEntities['DocumentStore']).findBy(searchOptions)
for (const store of stores) {
if (store.status === 'UPSERTED') {
const obj = {
@ -196,14 +198,7 @@ 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,

21
packages/components/nodes/agentflow/Start/Start.ts
View File

@ -18,7 +18,7 @@ class Start_Agentflow implements INode {
constructor() {
this.label = 'Start'
this.name = 'startAgentflow'
this.version = 1.0
this.version = 1.1
this.type = 'Start'
this.category = 'Agent Flows'
this.description = 'Starting point of the agentflow'
@ -153,6 +153,13 @@ class Start_Agentflow implements INode {
optional: true
}
]
},
{
label: 'Persist State',
name: 'startPersistState',
type: 'boolean',
description: 'Persist the state in the same session',
optional: true
}
]
}
@ -161,6 +168,7 @@ class Start_Agentflow implements INode {
const _flowState = nodeData.inputs?.startState as string
const startInputType = nodeData.inputs?.startInputType as string
const startEphemeralMemory = nodeData.inputs?.startEphemeralMemory as boolean
const startPersistState = nodeData.inputs?.startPersistState as boolean
let flowStateArray = []
if (_flowState) {
@ -176,6 +184,13 @@ class Start_Agentflow implements INode {
flowState[state.key] = state.value
}
const runtimeState = options.agentflowRuntime?.state as ICommonObject
if (startPersistState === true && runtimeState && Object.keys(runtimeState).length) {
for (const state in runtimeState) {
flowState[state] = runtimeState[state]
}
}
const inputData: ICommonObject = {}
const outputData: ICommonObject = {}
@ -202,6 +217,10 @@ class Start_Agentflow implements INode {
outputData.ephemeralMemory = true
}
if (startPersistState) {
outputData.persistState = true
}
const returnOutput = {
id: nodeData.id,
name: this.name,

91
packages/components/nodes/agentflow/Tool/Tool.ts
View File

@ -1,7 +1,8 @@
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 } from '../../../src/agents'
import { ARTIFACTS_PREFIX, TOOL_ARGS_PREFIX } from '../../../src/agents'
import zodToJsonSchema from 'zod-to-json-schema'
interface IToolInputArgs {
@ -28,7 +29,7 @@ class Tool_Agentflow implements INode {
constructor() {
this.label = 'Tool'
this.name = 'toolAgentflow'
this.version = 1.0
this.version = 1.1
this.type = 'Tool'
this.category = 'Agent Flows'
this.description = 'Tools allow LLM to interact with external systems'
@ -37,7 +38,7 @@ class Tool_Agentflow implements INode {
this.inputs = [
{
label: 'Tool',
name: 'selectedTool',
name: 'toolAgentflowSelectedTool',
type: 'asyncOptions',
loadMethod: 'listTools',
loadConfig: true
@ -64,7 +65,7 @@ class Tool_Agentflow implements INode {
}
],
show: {
selectedTool: '.+'
toolAgentflowSelectedTool: '.+'
}
},
{
@ -124,8 +125,11 @@ class Tool_Agentflow implements INode {
},
async listToolInputArgs(nodeData: INodeData, options: ICommonObject): Promise<INodeOptionsValue[]> {
const currentNode = options.currentNode as ICommonObject
const selectedTool = currentNode?.inputs?.selectedTool as string
const selectedToolConfig = currentNode?.inputs?.selectedToolConfig as ICommonObject
const selectedTool = (currentNode?.inputs?.selectedTool as string) || (currentNode?.inputs?.toolAgentflowSelectedTool as string)
const selectedToolConfig =
(currentNode?.inputs?.selectedToolConfig as ICommonObject) ||
(currentNode?.inputs?.toolAgentflowSelectedToolConfig as ICommonObject) ||
{}
const nodeInstanceFilePath = options.componentNodes[selectedTool].filePath as string
@ -158,7 +162,7 @@ class Tool_Agentflow implements INode {
toolInputArgs = { properties: allProperties }
} else {
// Handle single tool instance
toolInputArgs = toolInstance.schema ? zodToJsonSchema(toolInstance.schema) : {}
toolInputArgs = toolInstance.schema ? zodToJsonSchema(toolInstance.schema as any) : {}
}
if (toolInputArgs && Object.keys(toolInputArgs).length > 0) {
@ -183,8 +187,11 @@ class Tool_Agentflow implements INode {
}
async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<any> {
const selectedTool = nodeData.inputs?.selectedTool as string
const selectedToolConfig = nodeData.inputs?.selectedToolConfig as ICommonObject
const selectedTool = (nodeData.inputs?.selectedTool as string) || (nodeData.inputs?.toolAgentflowSelectedTool as string)
const selectedToolConfig =
(nodeData?.inputs?.selectedToolConfig as ICommonObject) ||
(nodeData?.inputs?.toolAgentflowSelectedToolConfig as ICommonObject) ||
{}
const toolInputArgs = nodeData.inputs?.toolInputArgs as IToolInputArgs[]
const _toolUpdateState = nodeData.inputs?.toolUpdateState
@ -220,13 +227,55 @@ class Tool_Agentflow implements INode {
const toolInstance = (await newToolNodeInstance.init(newNodeData, '', options)) as Tool | Tool[]
let toolCallArgs: Record<string, any> = {}
const parseInputValue = (value: string): any => {
if (typeof value !== 'string') {
return value
}
// Remove escape characters (backslashes before special characters)
// ex: \["a", "b", "c", "d", "e"\]
let cleanedValue = value
.replace(/\\"/g, '"') // \" -> "
.replace(/\\\\/g, '\\') // \\ -> \
.replace(/\\\[/g, '[') // \[ -> [
.replace(/\\\]/g, ']') // \] -> ]
.replace(/\\\{/g, '{') // \{ -> {
.replace(/\\\}/g, '}') // \} -> }
// Try to parse as JSON if it looks like JSON/array
if (
(cleanedValue.startsWith('[') && cleanedValue.endsWith(']')) ||
(cleanedValue.startsWith('{') && cleanedValue.endsWith('}'))
) {
try {
return JSON.parse(cleanedValue)
} catch (e) {
// If parsing fails, return the cleaned value
return cleanedValue
}
}
return cleanedValue
}
if (newToolNodeInstance.transformNodeInputsToToolArgs) {
const defaultParams = newToolNodeInstance.transformNodeInputsToToolArgs(newNodeData)
toolCallArgs = {
...defaultParams,
...toolCallArgs
}
}
for (const item of toolInputArgs) {
const variableName = item.inputArgName
const variableValue = item.inputArgValue
toolCallArgs[variableName] = variableValue
toolCallArgs[variableName] = parseInputValue(variableValue)
}
const flowConfig = {
chatflowId: options.chatflowid,
sessionId: options.sessionId,
chatId: options.chatId,
input: input,
@ -262,6 +311,17 @@ class Tool_Agentflow implements INode {
}
}
let toolInput
if (typeof toolOutput === 'string' && toolOutput.includes(TOOL_ARGS_PREFIX)) {
const [output, args] = toolOutput.split(TOOL_ARGS_PREFIX)
toolOutput = output
try {
toolInput = JSON.parse(args)
} catch (e) {
console.error('Error parsing tool input from tool:', e)
}
}
if (typeof toolOutput === 'object') {
toolOutput = JSON.stringify(toolOutput, null, 2)
}
@ -271,20 +331,13 @@ 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,
name: this.name,
input: {
toolInputArgs: toolInputArgs,
toolInputArgs: toolInput ?? toolInputArgs,
selectedTool: selectedTool
},
output: {

69
packages/components/nodes/agentflow/prompt.ts
View File

@ -39,37 +39,38 @@ export const DEFAULT_HUMAN_INPUT_DESCRIPTION_HTML = `<p>Summarize the conversati
</ul>
`
export const CONDITION_AGENT_SYSTEM_PROMPT = `You are part of a multi-agent system designed to make agent coordination and execution easy. Your task is to analyze the given input and select one matching scenario from a provided set of scenarios. If none of the scenarios match the input, you should return "default."
- **Input**: A string representing the user's query or message.
- **Scenarios**: A list of predefined scenarios that relate to the input.
- **Instruction**: Determine if the input fits any of the scenarios.
## Steps
1. **Read the input string** and the list of scenarios.
2. **Analyze the content of the input** to identify its main topic or intention.
3. **Compare the input with each scenario**:
- If a scenario matches the main topic of the input, select that scenario.
- If no scenarios match, prepare to output "\`\`\`json\n{"output": "default"}\`\`\`"
4. **Output the result**: If a match is found, return the corresponding scenario in JSON; otherwise, return "\`\`\`json\n{"output": "default"}\`\`\`"
## Output Format
Output should be a JSON object that either names the matching scenario or returns "\`\`\`json\n{"output": "default"}\`\`\`" if no scenarios match. No explanation is needed.
## Examples
1. **Input**: {"input": "Hello", "scenarios": ["user is asking about AI", "default"], "instruction": "Your task is to check and see if user is asking topic about AI"}
**Output**: "\`\`\`json\n{"output": "default"}\`\`\`"
2. **Input**: {"input": "What is AIGC?", "scenarios": ["user is asking about AI", "default"], "instruction": "Your task is to check and see if user is asking topic about AI"}
**Output**: "\`\`\`json\n{"output": "user is asking about AI"}\`\`\`"
3. **Input**: {"input": "Can you explain deep learning?", "scenarios": ["user is interested in AI topics", "default"], "instruction": "Determine if the user is interested in learning about AI"}
**Output**: "\`\`\`json\n{"output": "user is interested in AI topics"}\`\`\`"
## Note
- Ensure that the input scenarios align well with potential user queries for accurate matching
- DO NOT include anything other than the JSON in your response.
`
export const CONDITION_AGENT_SYSTEM_PROMPT = `<p>You are part of a multi-agent system designed to make agent coordination and execution easy. Your task is to analyze the given input and select one matching scenario from a provided set of scenarios.</p>
<ul>
<li><strong>Input</strong>: A string representing the user's query, message or data.</li>
<li><strong>Scenarios</strong>: A list of predefined scenarios that relate to the input.</li>
<li><strong>Instruction</strong>: Determine which of the provided scenarios is the best fit for the input.</li>
</ul>
<h2>Steps</h2>
<ol>
<li><strong>Read the input string</strong> and the list of scenarios.</li>
<li><strong>Analyze the content of the input</strong> to identify its main topic or intention.</li>
<li><strong>Compare the input with each scenario</strong>: Evaluate how well the input's topic or intention aligns with each of the provided scenarios and select the one that is the best fit.</li>
<li><strong>Output the result</strong>: Return the selected scenario in the specified JSON format.</li>
</ol>
<h2>Output Format</h2>
<p>Output should be a JSON object that names the selected scenario, like this: <code>{"output": "<selected_scenario_name>"}</code>. No explanation is needed.</p>
<h2>Examples</h2>
<ol>
<li>
<p><strong>Input</strong>: <code>{"input": "Hello", "scenarios": ["user is asking about AI", "user is not asking about AI"], "instruction": "Your task is to check if the user is asking about AI."}</code></p>
<p><strong>Output</strong>: <code>{"output": "user is not asking about AI"}</code></p>
</li>
<li>
<p><strong>Input</strong>: <code>{"input": "What is AIGC?", "scenarios": ["user is asking about AI", "user is asking about the weather"], "instruction": "Your task is to check and see if the user is asking a topic about AI."}</code></p>
<p><strong>Output</strong>: <code>{"output": "user is asking about AI"}</code></p>
</li>
<li>
<p><strong>Input</strong>: <code>{"input": "Can you explain deep learning?", "scenarios": ["user is interested in AI topics", "user wants to order food"], "instruction": "Determine if the user is interested in learning about AI."}</code></p>
<p><strong>Output</strong>: <code>{"output": "user is interested in AI topics"}</code></p>
</li>
</ol>
<h2>Note</h2>
<ul>
<li>Ensure that the input scenarios align well with potential user queries for accurate matching.</li>
<li>DO NOT include anything other than the JSON in your response.</li>
</ul>`

89
packages/components/nodes/agentflow/utils.ts
View File

@ -4,7 +4,7 @@ import { getFileFromStorage } from '../../src/storageUtils'
import { ICommonObject, IFileUpload } from '../../src/Interface'
import { BaseMessageLike } from '@langchain/core/messages'
import { IFlowState } from './Interface.Agentflow'
import { mapMimeTypeToInputField } from '../../src/utils'
import { handleEscapeCharacters, mapMimeTypeToInputField } from '../../src/utils'
export const addImagesToMessages = async (
options: ICommonObject,
@ -18,7 +18,7 @@ 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.chatflowid, options.chatId)
const contents = await getFileFromStorage(upload.name, 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')
@ -90,7 +90,7 @@ export const processMessagesWithImages = async (
hasImageReferences = true
try {
// Get file contents from storage
const contents = await getFileFromStorage(item.name, options.chatflowid, options.chatId)
const contents = await getFileFromStorage(item.name, options.orgId, options.chatflowid, options.chatId)
// Create base64 data URL
const base64Data = 'data:' + item.mime + ';base64,' + contents.toString('base64')
@ -313,13 +313,16 @@ 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.chatflowid, options.chatId)
const fileData = await getFileFromStorage(upload.name, 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')
@ -343,7 +346,8 @@ export const getPastChatHistoryImageMessages = async (
const nodeOptions = {
retrieveAttachmentChatId: true,
chatflowid: options.chatflowid,
chatId: options.chatId
chatId: options.chatId,
orgId: options.orgId
}
let fileInputFieldFromMimeType = 'txtFile'
fileInputFieldFromMimeType = mapMimeTypeToInputField(upload.mime)
@ -353,26 +357,87 @@ export const getPastChatHistoryImageMessages = async (
}
}
const documents: string = await fileLoaderNodeInstance.init(nodeData, '', nodeOptions)
messageWithFileUploads += `<doc name='${upload.name}'>${documents}</doc>\n\n`
messageWithFileUploads += `<doc name='${upload.name}'>${handleEscapeCharacters(documents, true)}</doc>\n\n`
}
}
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
@ -394,9 +459,9 @@ export const getPastChatHistoryImageMessages = async (
/**
* 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
}

8
packages/components/nodes/agents/AirtableAgent/AirtableAgent.ts
View File

@ -128,7 +128,7 @@ class Airtable_Agents implements INode {
let base64String = Buffer.from(JSON.stringify(airtableData)).toString('base64')
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbacks = await additionalCallbacks(nodeData, options)
const pyodide = await LoadPyodide()
@ -163,7 +163,7 @@ json.dumps(my_dict)`
const chain = new LLMChain({
llm: model,
prompt: PromptTemplate.fromTemplate(systemPrompt),
verbose: process.env.DEBUG === 'true'
verbose: process.env.DEBUG === 'true' ? true : false
})
const inputs = {
dict: dataframeColDict,
@ -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}"`)
}
}
@ -192,7 +192,7 @@ json.dumps(my_dict)`
const chain = new LLMChain({
llm: model,
prompt: PromptTemplate.fromTemplate(finalSystemPrompt),
verbose: process.env.DEBUG === 'true'
verbose: process.env.DEBUG === 'true' ? true : false
})
const inputs = {
question: input,

2
packages/components/nodes/agents/AutoGPT/AutoGPT.ts
View File

@ -23,6 +23,7 @@ class AutoGPT_Agents implements INode {
category: string
baseClasses: string[]
inputs: INodeParams[]
badge: string
constructor() {
this.label = 'AutoGPT'
@ -30,6 +31,7 @@ class AutoGPT_Agents implements INode {
this.version = 2.0
this.type = 'AutoGPT'
this.category = 'Agents'
this.badge = 'DEPRECATING'
this.icon = 'autogpt.svg'
this.description = 'Autonomous agent with chain of thoughts for self-guided task completion'
this.baseClasses = ['AutoGPT']

2
packages/components/nodes/agents/BabyAGI/BabyAGI.ts
View File

@ -15,6 +15,7 @@ class BabyAGI_Agents implements INode {
category: string
baseClasses: string[]
inputs: INodeParams[]
badge: string
constructor() {
this.label = 'BabyAGI'
@ -23,6 +24,7 @@ class BabyAGI_Agents implements INode {
this.type = 'BabyAGI'
this.category = 'Agents'
this.icon = 'babyagi.svg'
this.badge = 'DEPRECATING'
this.description = 'Task Driven Autonomous Agent which creates new task and reprioritizes task list based on objective'
this.baseClasses = ['BabyAGI']
this.inputs = [

9
packages/components/nodes/agents/CSVAgent/CSVAgent.ts
View File

@ -97,7 +97,7 @@ class CSV_Agents implements INode {
}
}
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const shouldStreamResponse = options.shouldStreamResponse
const sseStreamer: IServerSideEventStreamer = options.sseStreamer as IServerSideEventStreamer
const chatId = options.chatId
@ -114,11 +114,12 @@ class CSV_Agents implements INode {
} else {
files = [fileName]
}
const orgId = options.orgId
const chatflowid = options.chatflowid
for (const file of files) {
if (!file) continue
const fileData = await getFileFromStorage(file, chatflowid)
const fileData = await getFileFromStorage(file, orgId, chatflowid)
base64String += fileData.toString('base64')
}
} else {
@ -170,7 +171,7 @@ json.dumps(my_dict)`
const chain = new LLMChain({
llm: model,
prompt: PromptTemplate.fromTemplate(systemPrompt),
verbose: process.env.DEBUG === 'true'
verbose: process.env.DEBUG === 'true' ? true : false
})
const inputs = {
dict: dataframeColDict,
@ -201,7 +202,7 @@ json.dumps(my_dict)`
prompt: PromptTemplate.fromTemplate(
systemMessagePrompt ? `${systemMessagePrompt}\n${finalSystemPrompt}` : finalSystemPrompt
),
verbose: process.env.DEBUG === 'true'
verbose: process.env.DEBUG === 'true' ? true : false
})
const inputs = {
question: input,

2
packages/components/nodes/agents/ConversationalAgent/ConversationalAgent.ts
View File

@ -132,7 +132,7 @@ class ConversationalAgent_Agents implements INode {
}
const executor = await prepareAgent(nodeData, options, { sessionId: this.sessionId, chatId: options.chatId, input })
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbacks = await additionalCallbacks(nodeData, options)
let res: ChainValues = {}

98
packages/components/nodes/agents/ConversationalRetrievalToolAgent/ConversationalRetrievalToolAgent.ts
View File

@ -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> {
@ -130,7 +153,7 @@ class ConversationalRetrievalToolAgent_Agents implements INode {
const executor = await prepareAgent(nodeData, options, { sessionId: this.sessionId, chatId: options.chatId, input })
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbacks = await additionalCallbacks(nodeData, options)
let res: ChainValues = {}
@ -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
}
@ -288,11 +366,13 @@ const prepareAgent = async (
sessionId: flowObj?.sessionId,
chatId: flowObj?.chatId,
input: flowObj?.input,
verbose: process.env.DEBUG === 'true',
verbose: process.env.DEBUG === 'true' ? true : false,
maxIterations: maxIterations ? parseFloat(maxIterations) : undefined
})
return executor
}
module.exports = { nodeClass: ConversationalRetrievalToolAgent_Agents }
module.exports = {
nodeClass: ConversationalRetrievalToolAgent_Agents
}

8
packages/components/nodes/agents/LlamaIndexAgents/AnthropicAgent/AnthropicAgent_LlamaIndex.ts
View File

@ -2,6 +2,7 @@ import { flatten } from 'lodash'
import { MessageContentTextDetail, ChatMessage, AnthropicAgent, Anthropic } from 'llamaindex'
import { getBaseClasses } from '../../../../src/utils'
import { FlowiseMemory, ICommonObject, IMessage, INode, INodeData, INodeParams, IUsedTool } from '../../../../src/Interface'
import { EvaluationRunTracerLlama } from '../../../../evaluation/EvaluationRunTracerLlama'
class AnthropicAgent_LlamaIndex_Agents implements INode {
label: string
@ -96,13 +97,16 @@ class AnthropicAgent_LlamaIndex_Agents implements INode {
tools,
llm: model,
chatHistory: chatHistory,
verbose: process.env.DEBUG === 'true'
verbose: process.env.DEBUG === 'true' ? true : false
})
// these are needed for evaluation runs
await EvaluationRunTracerLlama.injectEvaluationMetadata(nodeData, options, agent)
let text = ''
const usedTools: IUsedTool[] = []
const response = await agent.chat({ message: input, chatHistory, verbose: process.env.DEBUG === 'true' })
const response = await agent.chat({ message: input, chatHistory, verbose: process.env.DEBUG === 'true' ? true : false })
if (response.sources.length) {
for (const sourceTool of response.sources) {

11
packages/components/nodes/agents/LlamaIndexAgents/OpenAIToolAgent/OpenAIToolAgent_LlamaIndex.ts
View File

@ -1,6 +1,7 @@
import { flatten } from 'lodash'
import { ChatMessage, OpenAI, OpenAIAgent } from 'llamaindex'
import { getBaseClasses } from '../../../../src/utils'
import { EvaluationRunTracerLlama } from '../../../../evaluation/EvaluationRunTracerLlama'
import {
FlowiseMemory,
ICommonObject,
@ -107,9 +108,12 @@ class OpenAIFunctionAgent_LlamaIndex_Agents implements INode {
tools,
llm: model,
chatHistory: chatHistory,
verbose: process.env.DEBUG === 'true'
verbose: process.env.DEBUG === 'true' ? true : false
})
// these are needed for evaluation runs
await EvaluationRunTracerLlama.injectEvaluationMetadata(nodeData, options, agent)
let text = ''
let isStreamingStarted = false
const usedTools: IUsedTool[] = []
@ -119,10 +123,9 @@ class OpenAIFunctionAgent_LlamaIndex_Agents implements INode {
message: input,
chatHistory,
stream: true,
verbose: process.env.DEBUG === 'true'
verbose: process.env.DEBUG === 'true' ? true : false
})
for await (const chunk of stream) {
//console.log('chunk', chunk)
text += chunk.response.delta
if (!isStreamingStarted) {
isStreamingStarted = true
@ -147,7 +150,7 @@ class OpenAIFunctionAgent_LlamaIndex_Agents implements INode {
}
}
} else {
const response = await agent.chat({ message: input, chatHistory, verbose: process.env.DEBUG === 'true' })
const response = await agent.chat({ message: input, chatHistory, verbose: process.env.DEBUG === 'true' ? true : false })
if (response.sources.length) {
for (const sourceTool of response.sources) {
usedTools.push({

149
packages/components/nodes/agents/OpenAIAssistant/OpenAIAssistant.ts
View File

@ -107,7 +107,11 @@ class OpenAIAssistant_Agents implements INode {
return returnData
}
const assistants = await appDataSource.getRepository(databaseEntities['Assistant']).find()
const searchOptions = options.searchOptions || {}
const assistants = await appDataSource.getRepository(databaseEntities['Assistant']).findBy({
...searchOptions,
type: 'OPENAI'
})
for (let i = 0; i < assistants.length; i += 1) {
const assistantDetails = JSON.parse(assistants[i].details)
@ -130,13 +134,14 @@ class OpenAIAssistant_Agents implements INode {
const selectedAssistantId = nodeData.inputs?.selectedAssistant as string
const appDataSource = options.appDataSource as DataSource
const databaseEntities = options.databaseEntities as IDatabaseEntity
const orgId = options.orgId
const assistant = await appDataSource.getRepository(databaseEntities['Assistant']).findOneBy({
id: selectedAssistantId
})
if (!assistant) {
options.logger.error(`Assistant ${selectedAssistantId} not found`)
options.logger.error(`[${orgId}]: Assistant ${selectedAssistantId} not found`)
return
}
@ -149,7 +154,7 @@ class OpenAIAssistant_Agents implements INode {
chatId
})
if (!chatmsg) {
options.logger.error(`Chat Message with Chat Id: ${chatId} not found`)
options.logger.error(`[${orgId}]: Chat Message with Chat Id: ${chatId} not found`)
return
}
sessionId = chatmsg.sessionId
@ -160,21 +165,21 @@ class OpenAIAssistant_Agents implements INode {
const credentialData = await getCredentialData(assistant.credential ?? '', options)
const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, nodeData)
if (!openAIApiKey) {
options.logger.error(`OpenAI ApiKey not found`)
options.logger.error(`[${orgId}]: OpenAI ApiKey not found`)
return
}
const openai = new OpenAI({ apiKey: openAIApiKey })
options.logger.info(`Clearing OpenAI Thread ${sessionId}`)
options.logger.info(`[${orgId}]: Clearing OpenAI Thread ${sessionId}`)
try {
if (sessionId && sessionId.startsWith('thread_')) {
await openai.beta.threads.del(sessionId)
options.logger.info(`Successfully cleared OpenAI Thread ${sessionId}`)
options.logger.info(`[${orgId}]: Successfully cleared OpenAI Thread ${sessionId}`)
} else {
options.logger.error(`Error clearing OpenAI Thread ${sessionId}`)
options.logger.error(`[${orgId}]: Error clearing OpenAI Thread ${sessionId}`)
}
} catch (e) {
options.logger.error(`Error clearing OpenAI Thread ${sessionId}`)
options.logger.error(`[${orgId}]: Error clearing OpenAI Thread ${sessionId}`)
}
}
@ -190,6 +195,17 @@ class OpenAIAssistant_Agents implements INode {
const shouldStreamResponse = options.shouldStreamResponse
const sseStreamer: IServerSideEventStreamer = options.sseStreamer as IServerSideEventStreamer
const chatId = options.chatId
const checkStorage = options.checkStorage
? (options.checkStorage as (orgId: string, subscriptionId: string, usageCacheManager: any) => Promise<void>)
: undefined
const updateStorageUsage = options.updateStorageUsage
? (options.updateStorageUsage as (
orgId: string,
workspaceId: string,
totalSize: number,
usageCacheManager: any
) => Promise<void>)
: undefined
if (moderations && moderations.length > 0) {
try {
@ -380,17 +396,30 @@ class OpenAIAssistant_Agents implements INode {
// eslint-disable-next-line no-useless-escape
const fileName = cited_file.filename.split(/[\/\\]/).pop() ?? cited_file.filename
if (!disableFileDownload) {
filePath = await downloadFile(
if (checkStorage)
await checkStorage(options.orgId, options.subscriptionId, options.usageCacheManager)
const { path, totalSize } = await downloadFile(
openAIApiKey,
cited_file,
fileName,
options.orgId,
options.chatflowid,
options.chatId
)
filePath = path
fileAnnotations.push({
filePath,
fileName
})
if (updateStorageUsage)
await updateStorageUsage(
options.orgId,
options.workspaceId,
totalSize,
options.usageCacheManager
)
}
} else {
const file_path = (annotation as OpenAI.Beta.Threads.Messages.FilePathAnnotation).file_path
@ -399,17 +428,30 @@ class OpenAIAssistant_Agents implements INode {
// eslint-disable-next-line no-useless-escape
const fileName = cited_file.filename.split(/[\/\\]/).pop() ?? cited_file.filename
if (!disableFileDownload) {
filePath = await downloadFile(
if (checkStorage)
await checkStorage(options.orgId, options.subscriptionId, options.usageCacheManager)
const { path, totalSize } = await downloadFile(
openAIApiKey,
cited_file,
fileName,
options.orgId,
options.chatflowid,
options.chatId
)
filePath = path
fileAnnotations.push({
filePath,
fileName
})
if (updateStorageUsage)
await updateStorageUsage(
options.orgId,
options.workspaceId,
totalSize,
options.usageCacheManager
)
}
}
}
@ -467,15 +509,21 @@ class OpenAIAssistant_Agents implements INode {
const fileId = chunk.image_file.file_id
const fileObj = await openai.files.retrieve(fileId)
const filePath = await downloadImg(
if (checkStorage) await checkStorage(options.orgId, options.subscriptionId, options.usageCacheManager)
const { filePath, totalSize } = await downloadImg(
openai,
fileId,
`${fileObj.filename}.png`,
options.orgId,
options.chatflowid,
options.chatId
)
artifacts.push({ type: 'png', data: filePath })
if (updateStorageUsage)
await updateStorageUsage(options.orgId, options.workspaceId, totalSize, options.usageCacheManager)
if (!isStreamingStarted) {
isStreamingStarted = true
if (sseStreamer) {
@ -530,7 +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: ${runThreadId}`
@ -655,7 +703,7 @@ class OpenAIAssistant_Agents implements INode {
toolOutput
})
} catch (e) {
await analyticHandlers.onToolEnd(toolIds, e)
await analyticHandlers.onToolError(toolIds, e)
console.error('Error executing tool', e)
clearInterval(timeout)
reject(
@ -776,7 +824,21 @@ class OpenAIAssistant_Agents implements INode {
// eslint-disable-next-line no-useless-escape
const fileName = cited_file.filename.split(/[\/\\]/).pop() ?? cited_file.filename
if (!disableFileDownload) {
filePath = await downloadFile(openAIApiKey, cited_file, fileName, options.chatflowid, options.chatId)
if (checkStorage) await checkStorage(options.orgId, options.subscriptionId, options.usageCacheManager)
const { path, totalSize } = await downloadFile(
openAIApiKey,
cited_file,
fileName,
options.orgId,
options.chatflowid,
options.chatId
)
filePath = path
if (updateStorageUsage)
await updateStorageUsage(options.orgId, options.workspaceId, totalSize, options.usageCacheManager)
fileAnnotations.push({
filePath,
fileName
@ -789,13 +851,27 @@ class OpenAIAssistant_Agents implements INode {
// eslint-disable-next-line no-useless-escape
const fileName = cited_file.filename.split(/[\/\\]/).pop() ?? cited_file.filename
if (!disableFileDownload) {
filePath = await downloadFile(
if (checkStorage)
await checkStorage(options.orgId, options.subscriptionId, options.usageCacheManager)
const { path, totalSize } = await downloadFile(
openAIApiKey,
cited_file,
fileName,
options.orgId,
options.chatflowid,
options.chatId
)
filePath = path
if (updateStorageUsage)
await updateStorageUsage(
options.orgId,
options.workspaceId,
totalSize,
options.usageCacheManager
)
fileAnnotations.push({
filePath,
fileName
@ -822,7 +898,20 @@ class OpenAIAssistant_Agents implements INode {
const fileId = content.image_file.file_id
const fileObj = await openai.files.retrieve(fileId)
const filePath = await downloadImg(openai, fileId, `${fileObj.filename}.png`, options.chatflowid, options.chatId)
if (checkStorage) await checkStorage(options.orgId, options.subscriptionId, options.usageCacheManager)
const { filePath, totalSize } = await downloadImg(
openai,
fileId,
`${fileObj.filename}.png`,
options.orgId,
options.chatflowid,
options.chatId
)
if (updateStorageUsage)
await updateStorageUsage(options.orgId, options.workspaceId, totalSize, options.usageCacheManager)
artifacts.push({ type: 'png', data: filePath })
}
}
@ -847,7 +936,13 @@ class OpenAIAssistant_Agents implements INode {
}
}
const downloadImg = async (openai: OpenAI, fileId: string, fileName: string, ...paths: string[]) => {
const downloadImg = async (
openai: OpenAI,
fileId: string,
fileName: string,
orgId: string,
...paths: string[]
): Promise<{ filePath: string; totalSize: number }> => {
const response = await openai.files.content(fileId)
// Extract the binary data from the Response object
@ -857,12 +952,18 @@ const downloadImg = async (openai: OpenAI, fileId: string, fileName: string, ...
const image_data_buffer = Buffer.from(image_data)
const mime = 'image/png'
const res = await addSingleFileToStorage(mime, image_data_buffer, fileName, ...paths)
const { path, totalSize } = await addSingleFileToStorage(mime, image_data_buffer, fileName, orgId, ...paths)
return res
return { filePath: path, totalSize }
}
const downloadFile = async (openAIApiKey: string, fileObj: any, fileName: string, ...paths: string[]) => {
const downloadFile = async (
openAIApiKey: string,
fileObj: any,
fileName: string,
orgId: string,
...paths: string[]
): Promise<{ path: string; totalSize: number }> => {
try {
const response = await fetch(`https://api.openai.com/v1/files/${fileObj.id}/content`, {
method: 'GET',
@ -880,10 +981,12 @@ const downloadFile = async (openAIApiKey: string, fileObj: any, fileName: string
const data_buffer = Buffer.from(data)
const mime = 'application/octet-stream'
return await addSingleFileToStorage(mime, data_buffer, fileName, ...paths)
const { path, totalSize } = await addSingleFileToStorage(mime, data_buffer, fileName, orgId, ...paths)
return { path, totalSize }
} catch (error) {
console.error('Error downloading or writing the file:', error)
return ''
return { path: '', totalSize: 0 }
}
}
@ -993,7 +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}`)
}

2
packages/components/nodes/agents/ReActAgentLLM/ReActAgentLLM.ts
View File

@ -97,7 +97,7 @@ class ReActAgentLLM_Agents implements INode {
const executor = new AgentExecutor({
agent,
tools,
verbose: process.env.DEBUG === 'true',
verbose: process.env.DEBUG === 'true' ? true : false,
maxIterations: maxIterations ? parseFloat(maxIterations) : undefined
})

4
packages/components/nodes/agents/ToolAgent/ToolAgent.ts
View File

@ -143,7 +143,7 @@ class ToolAgent_Agents implements INode {
const executor = await prepareAgent(nodeData, options, { sessionId: this.sessionId, chatId: options.chatId, input })
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbacks = await additionalCallbacks(nodeData, options)
// Add custom streaming handler if detailed streaming is enabled
@ -370,7 +370,7 @@ const prepareAgent = async (
sessionId: flowObj?.sessionId,
chatId: flowObj?.chatId,
input: flowObj?.input,
verbose: process.env.DEBUG === 'true',
verbose: process.env.DEBUG === 'true' ? true : false,
maxIterations: maxIterations ? parseFloat(maxIterations) : undefined
})

4
packages/components/nodes/agents/XMLAgent/XMLAgent.ts
View File

@ -138,7 +138,7 @@ class XMLAgent_Agents implements INode {
}
const executor = await prepareAgent(nodeData, options, { sessionId: this.sessionId, chatId: options.chatId, input })
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbacks = await additionalCallbacks(nodeData, options)
let res: ChainValues = {}
@ -278,7 +278,7 @@ const prepareAgent = async (
chatId: flowObj?.chatId,
input: flowObj?.input,
isXML: true,
verbose: process.env.DEBUG === 'true',
verbose: process.env.DEBUG === 'true' ? true : false,
maxIterations: maxIterations ? parseFloat(maxIterations) : undefined
})

6
packages/components/nodes/chains/ApiChain/GETApiChain.ts
View File

@ -26,6 +26,7 @@ class GETApiChain_Chains implements INode {
baseClasses: string[]
description: string
inputs: INodeParams[]
badge: string
constructor() {
this.label = 'GET API Chain'
@ -34,6 +35,7 @@ class GETApiChain_Chains implements INode {
this.type = 'GETApiChain'
this.icon = 'get.svg'
this.category = 'Chains'
this.badge = 'DEPRECATING'
this.description = 'Chain to run queries against GET API'
this.baseClasses = [this.type, ...getBaseClasses(APIChain)]
this.inputs = [
@ -98,7 +100,7 @@ class GETApiChain_Chains implements INode {
const ansPrompt = nodeData.inputs?.ansPrompt as string
const chain = await getAPIChain(apiDocs, model, headers, urlPrompt, ansPrompt)
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbacks = await additionalCallbacks(nodeData, options)
const shouldStreamResponse = options.shouldStreamResponse
const sseStreamer: IServerSideEventStreamer = options.sseStreamer as IServerSideEventStreamer
@ -129,7 +131,7 @@ const getAPIChain = async (documents: string, llm: BaseLanguageModel, headers: s
const chain = APIChain.fromLLMAndAPIDocs(llm, documents, {
apiUrlPrompt,
apiResponsePrompt,
verbose: process.env.DEBUG === 'true',
verbose: process.env.DEBUG === 'true' ? true : false,
headers: typeof headers === 'object' ? headers : headers ? JSON.parse(headers) : {}
})
return chain

9
packages/components/nodes/chains/ApiChain/OpenAPIChain.ts
View File

@ -17,6 +17,7 @@ class OpenApiChain_Chains implements INode {
baseClasses: string[]
description: string
inputs: INodeParams[]
badge: string
constructor() {
this.label = 'OpenAPI Chain'
@ -25,6 +26,7 @@ class OpenApiChain_Chains implements INode {
this.type = 'OpenAPIChain'
this.icon = 'openapi.svg'
this.category = 'Chains'
this.badge = 'DEPRECATING'
this.description = 'Chain that automatically select and call APIs based only on an OpenAPI spec'
this.baseClasses = [this.type, ...getBaseClasses(APIChain)]
this.inputs = [
@ -71,7 +73,7 @@ class OpenApiChain_Chains implements INode {
async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | object> {
const chain = await initChain(nodeData, options)
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbacks = await additionalCallbacks(nodeData, options)
const moderations = nodeData.inputs?.inputModeration as Moderation[]
const shouldStreamResponse = options.shouldStreamResponse
@ -114,8 +116,9 @@ const initChain = async (nodeData: INodeData, options: ICommonObject) => {
} else {
if (yamlFileBase64.startsWith('FILE-STORAGE::')) {
const file = yamlFileBase64.replace('FILE-STORAGE::', '')
const orgId = options.orgId
const chatflowid = options.chatflowid
const fileData = await getFileFromStorage(file, chatflowid)
const fileData = await getFileFromStorage(file, orgId, chatflowid)
yamlString = fileData.toString()
} else {
const splitDataURI = yamlFileBase64.split(',')
@ -128,7 +131,7 @@ const initChain = async (nodeData: INodeData, options: ICommonObject) => {
return await createOpenAPIChain(yamlString, {
llm: model,
headers: typeof headers === 'object' ? headers : headers ? JSON.parse(headers) : {},
verbose: process.env.DEBUG === 'true'
verbose: process.env.DEBUG === 'true' ? true : false
})
}

6
packages/components/nodes/chains/ApiChain/POSTApiChain.ts
View File

@ -15,6 +15,7 @@ class POSTApiChain_Chains implements INode {
baseClasses: string[]
description: string
inputs: INodeParams[]
badge: string
constructor() {
this.label = 'POST API Chain'
@ -23,6 +24,7 @@ class POSTApiChain_Chains implements INode {
this.type = 'POSTApiChain'
this.icon = 'post.svg'
this.category = 'Chains'
this.badge = 'DEPRECATING'
this.description = 'Chain to run queries against POST API'
this.baseClasses = [this.type, ...getBaseClasses(APIChain)]
this.inputs = [
@ -87,7 +89,7 @@ class POSTApiChain_Chains implements INode {
const ansPrompt = nodeData.inputs?.ansPrompt as string
const chain = await getAPIChain(apiDocs, model, headers, urlPrompt, ansPrompt)
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbacks = await additionalCallbacks(nodeData, options)
const shouldStreamResponse = options.shouldStreamResponse
@ -119,7 +121,7 @@ const getAPIChain = async (documents: string, llm: BaseLanguageModel, headers: s
const chain = APIChain.fromLLMAndAPIDocs(llm, documents, {
apiUrlPrompt,
apiResponsePrompt,
verbose: process.env.DEBUG === 'true',
verbose: process.env.DEBUG === 'true' ? true : false,
headers: typeof headers === 'object' ? headers : headers ? JSON.parse(headers) : {}
})
return chain

2
packages/components/nodes/chains/ConversationChain/ConversationChain.ts
View File

@ -132,7 +132,7 @@ class ConversationChain_Chains implements INode {
}
}
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const additionalCallback = await additionalCallbacks(nodeData, options)
let res = ''

11
packages/components/nodes/chains/ConversationalRetrievalQAChain/ConversationalRetrievalQAChain.ts
View File

@ -185,6 +185,7 @@ class ConversationalRetrievalQAChain_Chains implements INode {
const shouldStreamResponse = options.shouldStreamResponse
const sseStreamer: IServerSideEventStreamer = options.sseStreamer as IServerSideEventStreamer
const chatId = options.chatId
const orgId = options.orgId
let customResponsePrompt = responsePrompt
// If the deprecated systemMessagePrompt is still exists
@ -200,7 +201,8 @@ class ConversationalRetrievalQAChain_Chains implements INode {
memoryKey: 'chat_history',
appDataSource,
databaseEntities,
chatflowid
chatflowid,
orgId
})
}
@ -220,7 +222,7 @@ class ConversationalRetrievalQAChain_Chains implements INode {
const history = ((await memory.getChatMessages(this.sessionId, false, prependMessages)) as IMessage[]) ?? []
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const additionalCallback = await additionalCallbacks(nodeData, options)
let callbacks = [loggerHandler, ...additionalCallback]
@ -407,18 +409,21 @@ interface BufferMemoryExtendedInput {
appDataSource: DataSource
databaseEntities: IDatabaseEntity
chatflowid: string
orgId: string
}
class BufferMemory extends FlowiseMemory implements MemoryMethods {
appDataSource: DataSource
databaseEntities: IDatabaseEntity
chatflowid: string
orgId: string
constructor(fields: BufferMemoryInput & BufferMemoryExtendedInput) {
super(fields)
this.appDataSource = fields.appDataSource
this.databaseEntities = fields.databaseEntities
this.chatflowid = fields.chatflowid
this.orgId = fields.orgId
}
async getChatMessages(
@ -443,7 +448,7 @@ class BufferMemory extends FlowiseMemory implements MemoryMethods {
}
if (returnBaseMessages) {
return await mapChatMessageToBaseMessage(chatMessage)
return await mapChatMessageToBaseMessage(chatMessage, this.orgId)
}
let returnIMessages: IMessage[] = []

2
packages/components/nodes/chains/GraphCypherQAChain/GraphCypherQAChain.ts
View File

@ -215,7 +215,7 @@ class GraphCypherQA_Chain implements INode {
query: input
}
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbackHandlers = await additionalCallbacks(nodeData, options)
let callbacks = [loggerHandler, ...callbackHandlers]

2
packages/components/nodes/chains/LLMChain/LLMChain.ts
View File

@ -167,7 +167,7 @@ const runPrediction = async (
nodeData: INodeData,
disableStreaming?: boolean
) => {
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbacks = await additionalCallbacks(nodeData, options)
const moderations = nodeData.inputs?.inputModeration as Moderation[]

6
packages/components/nodes/chains/MultiPromptChain/MultiPromptChain.ts
View File

@ -16,11 +16,13 @@ class MultiPromptChain_Chains implements INode {
baseClasses: string[]
description: string
inputs: INodeParams[]
badge: string
constructor() {
this.label = 'Multi Prompt Chain'
this.name = 'multiPromptChain'
this.version = 2.0
this.badge = 'DEPRECATING'
this.type = 'MultiPromptChain'
this.icon = 'prompt.svg'
this.category = 'Chains'
@ -66,7 +68,7 @@ class MultiPromptChain_Chains implements INode {
promptNames,
promptDescriptions,
promptTemplates,
llmChainOpts: { verbose: process.env.DEBUG === 'true' }
llmChainOpts: { verbose: process.env.DEBUG === 'true' ? true : false }
})
return chain
@ -95,7 +97,7 @@ class MultiPromptChain_Chains implements INode {
}
const obj = { input }
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbacks = await additionalCallbacks(nodeData, options)
if (shouldStreamResponse) {

6
packages/components/nodes/chains/MultiRetrievalQAChain/MultiRetrievalQAChain.ts
View File

@ -15,12 +15,14 @@ class MultiRetrievalQAChain_Chains implements INode {
category: string
baseClasses: string[]
description: string
badge: string
inputs: INodeParams[]
constructor() {
this.label = 'Multi Retrieval QA Chain'
this.name = 'multiRetrievalQAChain'
this.version = 2.0
this.badge = 'DEPRECATING'
this.type = 'MultiRetrievalQAChain'
this.icon = 'qa.svg'
this.category = 'Chains'
@ -74,7 +76,7 @@ class MultiRetrievalQAChain_Chains implements INode {
retrieverNames,
retrieverDescriptions,
retrievers,
retrievalQAChainOpts: { verbose: process.env.DEBUG === 'true', returnSourceDocuments }
retrievalQAChainOpts: { verbose: process.env.DEBUG === 'true' ? true : false, returnSourceDocuments }
})
return chain
}
@ -101,7 +103,7 @@ class MultiRetrievalQAChain_Chains implements INode {
}
}
const obj = { input }
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbacks = await additionalCallbacks(nodeData, options)
if (shouldStreamResponse) {

6
packages/components/nodes/chains/RetrievalQAChain/RetrievalQAChain.ts
View File

@ -17,6 +17,7 @@ class RetrievalQAChain_Chains implements INode {
baseClasses: string[]
description: string
inputs: INodeParams[]
badge: string
constructor() {
this.label = 'Retrieval QA Chain'
@ -24,6 +25,7 @@ class RetrievalQAChain_Chains implements INode {
this.version = 2.0
this.type = 'RetrievalQAChain'
this.icon = 'qa.svg'
this.badge = 'DEPRECATING'
this.category = 'Chains'
this.description = 'QA chain to answer a question based on the retrieved documents'
this.baseClasses = [this.type, ...getBaseClasses(RetrievalQAChain)]
@ -53,7 +55,7 @@ class RetrievalQAChain_Chains implements INode {
const model = nodeData.inputs?.model as BaseLanguageModel
const vectorStoreRetriever = nodeData.inputs?.vectorStoreRetriever as BaseRetriever
const chain = RetrievalQAChain.fromLLM(model, vectorStoreRetriever, { verbose: process.env.DEBUG === 'true' })
const chain = RetrievalQAChain.fromLLM(model, vectorStoreRetriever, { verbose: process.env.DEBUG === 'true' ? true : false })
return chain
}
@ -80,7 +82,7 @@ class RetrievalQAChain_Chains implements INode {
const obj = {
query: input
}
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbacks = await additionalCallbacks(nodeData, options)
if (shouldStreamResponse) {

4
packages/components/nodes/chains/SqlDatabaseChain/SqlDatabaseChain.ts
View File

@ -194,7 +194,7 @@ class SqlDatabaseChain_Chains implements INode {
topK,
customPrompt
)
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbacks = await additionalCallbacks(nodeData, options)
if (shouldStreamResponse) {
@ -241,7 +241,7 @@ const getSQLDBChain = async (
const obj: SqlDatabaseChainInput = {
llm,
database: db,
verbose: process.env.DEBUG === 'true',
verbose: process.env.DEBUG === 'true' ? true : false,
topK: topK
}

6
packages/components/nodes/chains/VectorDBQAChain/VectorDBQAChain.ts
View File

@ -17,6 +17,7 @@ class VectorDBQAChain_Chains implements INode {
baseClasses: string[]
description: string
inputs: INodeParams[]
badge: string
constructor() {
this.label = 'VectorDB QA Chain'
@ -25,6 +26,7 @@ class VectorDBQAChain_Chains implements INode {
this.type = 'VectorDBQAChain'
this.icon = 'vectordb.svg'
this.category = 'Chains'
this.badge = 'DEPRECATING'
this.description = 'QA chain for vector databases'
this.baseClasses = [this.type, ...getBaseClasses(VectorDBQAChain)]
this.inputs = [
@ -55,7 +57,7 @@ class VectorDBQAChain_Chains implements INode {
const chain = VectorDBQAChain.fromLLM(model, vectorStore, {
k: (vectorStore as any)?.k ?? 4,
verbose: process.env.DEBUG === 'true'
verbose: process.env.DEBUG === 'true' ? true : false
})
return chain
}
@ -84,7 +86,7 @@ class VectorDBQAChain_Chains implements INode {
query: input
}
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId)
const callbacks = await additionalCallbacks(nodeData, options)
if (shouldStreamResponse) {

17
packages/components/nodes/chatmodels/AWSBedrock/AWSChatBedrock.ts
View File

@ -23,7 +23,7 @@ class AWSChatBedrock_ChatModels implements INode {
constructor() {
this.label = 'AWS ChatBedrock'
this.name = 'awsChatBedrock'
this.version = 6.0
this.version = 6.1
this.type = 'AWSChatBedrock'
this.icon = 'aws.svg'
this.category = 'Chat Models'
@ -100,6 +100,16 @@ class AWSChatBedrock_ChatModels implements INode {
'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: 'Latency Optimized',
name: 'latencyOptimized',
type: 'boolean',
description:
'Enable latency optimized configuration for supported models. Refer to the supported <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/latency-optimized-inference.html" target="_blank">latecny optimized models</a> for more details.',
default: false,
optional: true,
additionalParams: true
}
]
}
@ -122,6 +132,7 @@ class AWSChatBedrock_ChatModels implements INode {
const iMax_tokens_to_sample = nodeData.inputs?.max_tokens_to_sample as string
const cache = nodeData.inputs?.cache as BaseCache
const streaming = nodeData.inputs?.streaming as boolean
const latencyOptimized = nodeData.inputs?.latencyOptimized as boolean
const obj: ChatBedrockConverseInput = {
region: iRegion,
@ -131,6 +142,10 @@ class AWSChatBedrock_ChatModels implements INode {
streaming: streaming ?? true
}
if (latencyOptimized) {
obj.performanceConfig = { latency: 'optimized' }
}
/**
* Long-term credentials specified in LLM configuration are optional.
* Bedrock's credential provider falls back to the AWS SDK to fetch

67
packages/components/nodes/chatmodels/AzureChatOpenAI/AzureChatOpenAI.ts
View File

@ -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 = {

7
packages/components/nodes/chatmodels/AzureChatOpenAI/FlowiseAzureChatOpenAI.ts
View File

@ -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)
}
}

12
packages/components/nodes/chatmodels/AzureChatOpenAI/README.md
View File

@ -4,12 +4,12 @@ Azure OpenAI Chat Model integration for Flowise
## 🌱 Env Variables
| Variable | Description | Type | Default |
| ---------------------------- | ----------------------------------------------------------------------------------------------- | ------------------------------------------------ | ----------------------------------- |
| AZURE_OPENAI_API_KEY | Default `credential.azureOpenAIApiKey` for Azure OpenAI Model | String | |
| AZURE_OPENAI_API_INSTANCE_NAME | Default `credential.azureOpenAIApiInstanceName` for Azure OpenAI Model | String | |
| AZURE_OPENAI_API_DEPLOYMENT_NAME | Default `credential.azureOpenAIApiDeploymentName` for Azure OpenAI Model | String | |
| AZURE_OPENAI_API_VERSION | Default `credential.azureOpenAIApiVersion` for Azure OpenAI Model | String | |
| Variable | Description | Type | Default |
| -------------------------------- | ------------------------------------------------------------------------ | ------ | ------- |
| AZURE_OPENAI_API_KEY | Default `credential.azureOpenAIApiKey` for Azure OpenAI Model | String | |
| AZURE_OPENAI_API_INSTANCE_NAME | Default `credential.azureOpenAIApiInstanceName` for Azure OpenAI Model | String | |
| AZURE_OPENAI_API_DEPLOYMENT_NAME | Default `credential.azureOpenAIApiDeploymentName` for Azure OpenAI Model | String | |
| AZURE_OPENAI_API_VERSION | Default `credential.azureOpenAIApiVersion` for Azure OpenAI Model | String | |
## License

2
packages/components/nodes/chatmodels/ChatAnthropic/ChatAnthropic.ts
View File

@ -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
},

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