Chore/refractor (#4454)
* markdown files and env examples cleanup * components update * update jsonlines description * server refractor * update telemetry * add execute custom node * add ui refractor * add username and password authenticate * correctly retrieve past images in agentflowv2 * disable e2e temporarily * add existing username and password authenticate * update migration to default workspace * update todo * blob storage migrating * throw error on agent tool call error * add missing execution import * add referral * chore: add error message when importData is undefined * migrate api keys to db * fix: data too long for column executionData * migrate api keys from json to db at init * add info on account setup * update docstore missing fields --------- Co-authored-by: chungyau97 <chungyau97@gmail.com>
This commit is contained in:
Henry Heng
GitHub
parent
e35a126b46
commit
5a37227d14
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@ -1,33 +0,0 @@
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name: autoSyncMergedPullRequest
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||||
on:
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||||
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!
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||||
- name: Repository Dispatch
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||||
uses: peter-evans/repository-dispatch@v3
|
||||
with:
|
||||
token: ${{ secrets.AUTOSYNC_TOKEN }}
|
||||
repository: ${{ secrets.AUTOSYNC_CH_URL }}
|
||||
event-type: ${{ secrets.AUTOSYNC_PR_EVENT_TYPE }}
|
||||
client-payload: >-
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||||
{
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||||
"ref": "${{ github.ref }}",
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||||
"prNumber": "${{ github.event.pull_request.number }}",
|
||||
"prTitle": "${{ github.event.pull_request.title }}",
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||||
"prDescription": "",
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||||
"sha": "${{ github.sha }}"
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||||
}
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||||
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@ -1,36 +0,0 @@
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name: autoSyncSingleCommit
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||||
on:
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push:
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branches:
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- main
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jobs:
|
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doNotAutoSyncSingleCommit:
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if: github.event.commits[1] != null
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- name: IGNORE autoSyncSingleCommit
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run: |
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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.
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autoSyncSingleCommit:
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if: github.event.commits[1] == null
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- name: autoSyncSingleCommit
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env:
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GITHUB_CONTEXT: ${{ toJSON(github) }}
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run: |
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echo Autosync a single commit with id: ${{ github.sha }} from openSource main branch towards cloud hosted version.
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- name: Repository Dispatch
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uses: peter-evans/repository-dispatch@v3
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with:
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token: ${{ secrets.AUTOSYNC_TOKEN }}
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repository: ${{ secrets.AUTOSYNC_CH_URL }}
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event-type: ${{ secrets.AUTOSYNC_SC_EVENT_TYPE }}
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client-payload: >-
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{
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"ref": "${{ github.ref }}",
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"sha": "${{ github.sha }}",
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"commitMessage": "${{ github.event.commits[0].id }}"
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}
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@ -3,6 +3,22 @@ name: Docker Image CI
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on:
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workflow_dispatch:
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inputs:
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registry:
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description: 'Container Registry to push the image to.'
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type: choice
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required: true
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default: 'aws_ecr'
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options:
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- 'docker_hub'
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- 'aws_ecr'
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environment:
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description: 'Environment to push the image to.'
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required: true
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default: 'dev'
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type: choice
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options:
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- dev
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- prod
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node_version:
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description: 'Node.js version to build this image with.'
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type: choice
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@ -19,25 +35,57 @@ on:
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jobs:
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docker:
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runs-on: ubuntu-latest
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environment: ${{ github.event.inputs.environment }}
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steps:
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- name: Set default values
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id: defaults
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run: |
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echo "registry=${{ github.event.inputs.registry || 'aws_ecr' }}" >> $GITHUB_OUTPUT
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echo "node_version=${{ github.event.inputs.node_version || '20' }}" >> $GITHUB_OUTPUT
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echo "tag_version=${{ github.event.inputs.tag_version || 'latest' }}" >> $GITHUB_OUTPUT
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- name: Checkout
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uses: actions/checkout@v4.1.1
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- name: Set up QEMU
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uses: docker/setup-qemu-action@v3.0.0
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3.0.0
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# ------------------------
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# Login Steps (conditional)
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# ------------------------
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- name: Login to Docker Hub
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if: steps.defaults.outputs.registry == 'docker_hub'
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uses: docker/login-action@v3
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||||
with:
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username: ${{ secrets.DOCKERHUB_USERNAME }}
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||||
password: ${{ secrets.DOCKERHUB_TOKEN }}
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||||
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- name: Configure AWS Credentials
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||||
if: steps.defaults.outputs.registry == 'aws_ecr'
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uses: aws-actions/configure-aws-credentials@v3
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||||
with:
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||||
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
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aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
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aws-region: ${{ secrets.AWS_REGION }}
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||||
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||||
- name: Login to Amazon ECR
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||||
if: steps.defaults.outputs.registry == 'aws_ecr'
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||||
uses: aws-actions/amazon-ecr-login@v1
|
||||
|
||||
# -------------------------
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||||
# Build and push (conditional tags)
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||||
# -------------------------
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||||
- name: Build and push
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||||
uses: docker/build-push-action@v5.3.0
|
||||
with:
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||||
context: .
|
||||
file: ./docker/Dockerfile
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||||
file: Dockerfile
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||||
build-args: |
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||||
NODE_VERSION=${{github.event.inputs.node_version}}
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||||
NODE_VERSION=${{ steps.defaults.outputs.node_version }}
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||||
platforms: linux/amd64,linux/arm64
|
||||
push: true
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||||
tags: flowiseai/flowise:${{github.event.inputs.tag_version}}
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||||
tags: |
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||||
${{ steps.defaults.outputs.registry == 'docker_hub' && format('flowiseai/flowise:{0}', steps.defaults.outputs.tag_version) || 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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||||
|
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@ -6,6 +6,7 @@ on:
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|||
pull_request:
|
||||
branches:
|
||||
- '*'
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||||
workflow_dispatch:
|
||||
permissions:
|
||||
contents: read
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||||
jobs:
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||||
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@ -31,6 +32,8 @@ jobs:
|
|||
- run: pnpm install
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||||
- run: pnpm lint
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||||
- run: pnpm build
|
||||
env:
|
||||
NODE_OPTIONS: '--max_old_space_size=4096'
|
||||
- name: Cypress install
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||||
run: pnpm cypress install
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||||
- name: Install dependencies (Cypress Action)
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||||
|
|
|
|||
|
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@ -8,13 +8,12 @@ on:
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|||
pull_request:
|
||||
branches:
|
||||
- '*'
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||||
|
||||
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 .
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||||
|
|
|
|||
|
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@ -125,15 +125,11 @@ Flowise support different environment variables to configure your instance. You
|
|||
| 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` |
|
||||
|
|
|
|||
14
LICENSE.md
14
LICENSE.md
|
|
@ -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
|
||||
|
||||
|
|
|
|||
15
README.md
15
README.md
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|
@ -31,12 +31,6 @@ 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
|
||||
|
|
@ -138,15 +132,6 @@ 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)
|
||||
|
|
|
|||
|
|
@ -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=""
|
||||
|
|
@ -20,34 +16,37 @@ BLOB_STORAGE_PATH=/root/.flowise/storage
|
|||
# DATABASE_SSL=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)
|
||||
# TOOL_FUNCTION_BUILTIN_DEP=crypto,fs
|
||||
# TOOL_FUNCTION_EXTERNAL_DEP=moment,lodash
|
||||
|
||||
# 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 +58,69 @@ 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
|
||||
|
||||
# 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 +131,21 @@ 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
|
||||
|
|
|
|||
|
|
@ -9,26 +9,11 @@ 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:
|
||||
|
||||
- DATABASE_PATH=/root/.flowise
|
||||
- APIKEY_PATH=/root/.flowise
|
||||
- LOG_PATH=/root/.flowise/logs
|
||||
- SECRETKEY_PATH=/root/.flowise
|
||||
- BLOB_STORAGE_PATH=/root/.flowise/storage
|
||||
|
|
|
|||
|
|
@ -8,8 +8,6 @@ services:
|
|||
- 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=${DEBUG}
|
||||
- DATABASE_PATH=${DATABASE_PATH}
|
||||
|
|
@ -21,10 +19,13 @@ 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=${APIKEY_PATH}
|
||||
- SECRETKEY_PATH=${SECRETKEY_PATH}
|
||||
- FLOWISE_SECRETKEY_OVERWRITE=${FLOWISE_SECRETKEY_OVERWRITE}
|
||||
- SECRETKEY_STORAGE_TYPE=${SECRETKEY_STORAGE_TYPE}
|
||||
- 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}
|
||||
- LOG_LEVEL=${LOG_LEVEL}
|
||||
- LOG_PATH=${LOG_PATH}
|
||||
- BLOB_STORAGE_PATH=${BLOB_STORAGE_PATH}
|
||||
|
|
|
|||
|
|
@ -8,8 +8,6 @@ services:
|
|||
- PORT=${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_PATH=${DATABASE_PATH}
|
||||
|
|
@ -21,8 +19,6 @@ services:
|
|||
- DATABASE_PASSWORD=${DATABASE_PASSWORD}
|
||||
- DATABASE_SSL=${DATABASE_SSL}
|
||||
- DATABASE_SSL_KEY_BASE64=${DATABASE_SSL_KEY_BASE64}
|
||||
- APIKEY_STORAGE_TYPE=${APIKEY_STORAGE_TYPE}
|
||||
- APIKEY_PATH=${APIKEY_PATH}
|
||||
- SECRETKEY_PATH=${SECRETKEY_PATH}
|
||||
- FLOWISE_SECRETKEY_OVERWRITE=${FLOWISE_SECRETKEY_OVERWRITE}
|
||||
- LOG_LEVEL=${LOG_LEVEL}
|
||||
|
|
|
|||
|
|
@ -119,16 +119,12 @@ Flowise 在一个单一的单体存储库中有 3 个不同的模块。
|
|||
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 | |
|
||||
| ---------------------------- | ------------------------------------------------------- | ----------------------------------------------- | ----------------------------------- | --- | --- |
|
||||
| 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` |
|
||||
| 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` |
|
||||
|
|
|
|||
|
|
@ -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
|
||||
|
|
|
|||
|
|
@ -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)
|
||||
|
|
|
|||
|
|
@ -31,12 +31,6 @@
|
|||
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
|
||||
|
|
@ -138,15 +132,6 @@ Flowise 在單個 mono 存儲庫中有 3 個不同的模塊。
|
|||
|
||||
任何代碼更改都會自動重新加載應用程序 [http://localhost:8080](http://localhost:8080)
|
||||
|
||||
## 🔒 認證
|
||||
|
||||
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)
|
||||
|
|
|
|||
|
|
@ -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)
|
||||
|
|
|
|||
|
|
@ -20,6 +20,7 @@
|
|||
"start-worker": "run-script-os",
|
||||
"start-worker:windows": "cd packages/server/bin && run worker",
|
||||
"start-worker:default": "cd packages/server/bin && ./run worker",
|
||||
"test": "turbo run test",
|
||||
"clean": "pnpm --filter \"./packages/**\" clean",
|
||||
"nuke": "pnpm --filter \"./packages/**\" nuke && rimraf node_modules .turbo",
|
||||
"format": "prettier --write \"**/*.{ts,tsx,md}\"",
|
||||
|
|
|
|||
|
|
@ -0,0 +1,165 @@
|
|||
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)}`
|
||||
}
|
||||
|
|
@ -0,0 +1,186 @@
|
|||
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
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,172 @@
|
|||
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 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
|
||||
}
|
||||
}
|
||||
}
|
||||
let modelConfig = await getModelConfigByModelName(MODEL_TYPE.CHAT, selectedProvider, selectedModel)
|
||||
if (modelConfig) {
|
||||
val.push(JSON.stringify({ cost_values: modelConfig }))
|
||||
} else {
|
||||
modelConfig = await getModelConfigByModelName(MODEL_TYPE.LLM, 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)
|
||||
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
|
||||
}
|
||||
]
|
||||
}
|
||||
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
|
||||
}
|
||||
}
|
||||
|
|
@ -427,7 +427,8 @@ class Agent_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 = {
|
||||
|
|
|
|||
|
|
@ -152,7 +152,7 @@ class CustomFunction_Agentflow implements INode {
|
|||
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,
|
||||
|
|
|
|||
|
|
@ -127,7 +127,8 @@ 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'
|
||||
|
|
|
|||
|
|
@ -119,7 +119,8 @@ 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 = {
|
||||
|
|
|
|||
|
|
@ -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')
|
||||
|
|
@ -319,7 +319,7 @@ export const getPastChatHistoryImageMessages = async (
|
|||
const imageContents: MessageContentImageUrl[] = []
|
||||
for (const upload of uploads) {
|
||||
if (upload.type === 'stored-file' && upload.mime.startsWith('image/')) {
|
||||
const fileData = await getFileFromStorage(upload.name, options.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')
|
||||
|
||||
|
|
|
|||
|
|
@ -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,
|
||||
|
|
@ -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,
|
||||
|
|
|
|||
|
|
@ -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,
|
||||
|
|
|
|||
|
|
@ -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 = {}
|
||||
|
|
|
|||
|
|
@ -130,7 +130,7 @@ 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 = {}
|
||||
|
|
@ -288,7 +288,7 @@ 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
|
||||
})
|
||||
|
||||
|
|
|
|||
|
|
@ -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) {
|
||||
|
|
|
|||
|
|
@ -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({
|
||||
|
|
|
|||
|
|
@ -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) {
|
||||
|
|
@ -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 }
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -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
|
||||
})
|
||||
|
||||
|
|
|
|||
|
|
@ -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
|
||||
})
|
||||
|
||||
|
|
|
|||
|
|
@ -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
|
||||
})
|
||||
|
||||
|
|
|
|||
|
|
@ -98,7 +98,7 @@ 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 +129,7 @@ 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
|
||||
|
|
|
|||
|
|
@ -71,7 +71,7 @@ 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 +114,9 @@ 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 +129,7 @@ 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
|
||||
})
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -87,7 +87,7 @@ 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 +119,7 @@ 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
|
||||
|
|
|
|||
|
|
@ -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 = ''
|
||||
|
|
|
|||
|
|
@ -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[] = []
|
||||
|
|
|
|||
|
|
@ -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]
|
||||
|
||||
|
|
|
|||
|
|
@ -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[]
|
||||
|
|
|
|||
|
|
@ -66,7 +66,7 @@ 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 +95,7 @@ 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) {
|
||||
|
|
|
|||
|
|
@ -74,7 +74,7 @@ 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 +101,7 @@ 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) {
|
||||
|
|
|
|||
|
|
@ -53,7 +53,7 @@ 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 +80,7 @@ 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) {
|
||||
|
|
|
|||
|
|
@ -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
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -55,7 +55,7 @@ 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 +84,7 @@ 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) {
|
||||
|
|
|
|||
|
|
@ -4,13 +4,13 @@ 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
|
||||
|
||||
Source code in this repository is made available under the [Apache License Version 2.0](https://github.com/FlowiseAI/Flowise/blob/master/LICENSE.md).
|
||||
Source code in this repository is made available under the [Apache License Version 2.0](https://github.com/FlowiseAI/Flowise/blob/master/LICENSE.md).
|
||||
|
|
|
|||
|
|
@ -216,6 +216,10 @@ class GoogleGenerativeAI_ChatModels implements INode {
|
|||
streaming: streaming ?? true
|
||||
}
|
||||
|
||||
// this extra metadata is needed, as langchain does not show the model name in the callbacks.
|
||||
obj.metadata = {
|
||||
fw_model_name: customModelName || modelName
|
||||
}
|
||||
if (maxOutputTokens) obj.maxOutputTokens = parseInt(maxOutputTokens, 10)
|
||||
if (topP) obj.topP = parseFloat(topP)
|
||||
if (topK) obj.topK = parseFloat(topK)
|
||||
|
|
|
|||
|
|
@ -161,12 +161,13 @@ class ChatIBMWatsonx_ChatModels implements INode {
|
|||
watsonxAIBearerToken
|
||||
}
|
||||
|
||||
const obj: ChatWatsonxInput & WatsonxAuth = {
|
||||
const obj = {
|
||||
...auth,
|
||||
streaming: streaming ?? true,
|
||||
model: modelName,
|
||||
temperature: temperature ? parseFloat(temperature) : undefined
|
||||
}
|
||||
} as ChatWatsonxInput & WatsonxAuth
|
||||
|
||||
if (cache) obj.cache = cache
|
||||
if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
|
||||
if (frequencyPenalty) obj.frequencyPenalty = parseInt(frequencyPenalty, 10)
|
||||
|
|
|
|||
|
|
@ -123,6 +123,7 @@ class Cheerio_DocumentLoaders implements INode {
|
|||
const selectedLinks = nodeData.inputs?.selectedLinks as string[]
|
||||
let limit = parseInt(nodeData.inputs?.limit as string)
|
||||
const output = nodeData.outputs?.output as string
|
||||
const orgId = options.orgId
|
||||
|
||||
const _omitMetadataKeys = nodeData.inputs?.omitMetadataKeys as string
|
||||
|
||||
|
|
@ -149,7 +150,8 @@ class Cheerio_DocumentLoaders implements INode {
|
|||
try {
|
||||
let docs: IDocument[] = []
|
||||
if (url.endsWith('.pdf')) {
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`CheerioWebBaseLoader does not support PDF files: ${url}`)
|
||||
if (process.env.DEBUG === 'true')
|
||||
options.logger.info(`[${orgId}]: CheerioWebBaseLoader does not support PDF files: ${url}`)
|
||||
return docs
|
||||
}
|
||||
const loader = new CheerioWebBaseLoader(url, params)
|
||||
|
|
@ -161,7 +163,8 @@ class Cheerio_DocumentLoaders implements INode {
|
|||
}
|
||||
return docs
|
||||
} catch (err) {
|
||||
if (process.env.DEBUG === 'true') options.logger.error(`error in CheerioWebBaseLoader: ${err.message}, on page: ${url}`)
|
||||
if (process.env.DEBUG === 'true')
|
||||
options.logger.error(`[${orgId}]: Error in CheerioWebBaseLoader: ${err.message}, on page: ${url}`)
|
||||
return []
|
||||
}
|
||||
}
|
||||
|
|
@ -169,7 +172,7 @@ class Cheerio_DocumentLoaders implements INode {
|
|||
let docs: IDocument[] = []
|
||||
|
||||
if (relativeLinksMethod) {
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`Start ${relativeLinksMethod}`)
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`[${orgId}]: Start CheerioWebBaseLoader ${relativeLinksMethod}`)
|
||||
// if limit is 0 we don't want it to default to 10 so we check explicitly for null or undefined
|
||||
// so when limit is 0 we can fetch all the links
|
||||
if (limit === null || limit === undefined) limit = 10
|
||||
|
|
@ -180,15 +183,18 @@ class Cheerio_DocumentLoaders implements INode {
|
|||
: relativeLinksMethod === 'webCrawl'
|
||||
? await webCrawl(url, limit)
|
||||
: await xmlScrape(url, limit)
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`pages: ${JSON.stringify(pages)}, length: ${pages.length}`)
|
||||
if (process.env.DEBUG === 'true')
|
||||
options.logger.info(`[${orgId}]: CheerioWebBaseLoader pages: ${JSON.stringify(pages)}, length: ${pages.length}`)
|
||||
if (!pages || pages.length === 0) throw new Error('No relative links found')
|
||||
for (const page of pages) {
|
||||
docs.push(...(await cheerioLoader(page)))
|
||||
}
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`Finish ${relativeLinksMethod}`)
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`[${orgId}]: Finish CheerioWebBaseLoader ${relativeLinksMethod}`)
|
||||
} else if (selectedLinks && selectedLinks.length > 0) {
|
||||
if (process.env.DEBUG === 'true')
|
||||
options.logger.info(`pages: ${JSON.stringify(selectedLinks)}, length: ${selectedLinks.length}`)
|
||||
options.logger.info(
|
||||
`[${orgId}]: CheerioWebBaseLoader pages: ${JSON.stringify(selectedLinks)}, length: ${selectedLinks.length}`
|
||||
)
|
||||
for (const page of selectedLinks.slice(0, limit)) {
|
||||
docs.push(...(await cheerioLoader(page)))
|
||||
}
|
||||
|
|
|
|||
|
|
@ -107,9 +107,9 @@ class Csv_DocumentLoaders implements INode {
|
|||
return { files, fromStorage }
|
||||
}
|
||||
|
||||
async getFileData(file: string, { chatflowid }: { chatflowid: string }, fromStorage?: boolean) {
|
||||
async getFileData(file: string, { orgId, chatflowid }: { orgId: string; chatflowid: string }, fromStorage?: boolean) {
|
||||
if (fromStorage) {
|
||||
return getFileFromStorage(file, chatflowid)
|
||||
return getFileFromStorage(file, orgId, chatflowid)
|
||||
} else {
|
||||
const splitDataURI = file.split(',')
|
||||
splitDataURI.pop()
|
||||
|
|
@ -126,6 +126,7 @@ class Csv_DocumentLoaders implements INode {
|
|||
|
||||
let docs: IDocument[] = []
|
||||
|
||||
const orgId = options.orgId
|
||||
const chatflowid = options.chatflowid
|
||||
|
||||
const { files, fromStorage } = this.getFiles(nodeData)
|
||||
|
|
@ -133,7 +134,7 @@ class Csv_DocumentLoaders implements INode {
|
|||
for (const file of files) {
|
||||
if (!file) continue
|
||||
|
||||
const fileData = await this.getFileData(file, { chatflowid }, fromStorage)
|
||||
const fileData = await this.getFileData(file, { orgId, chatflowid }, fromStorage)
|
||||
const blob = new Blob([fileData])
|
||||
const loader = new CSVLoader(blob, columnName.trim().length === 0 ? undefined : columnName.trim())
|
||||
|
||||
|
|
|
|||
|
|
@ -72,7 +72,7 @@ class CustomDocumentLoader_DocumentLoaders implements INode {
|
|||
const appDataSource = options.appDataSource as DataSource
|
||||
const databaseEntities = options.databaseEntities as IDatabaseEntity
|
||||
|
||||
const variables = await getVars(appDataSource, databaseEntities, nodeData)
|
||||
const variables = await getVars(appDataSource, databaseEntities, nodeData, options)
|
||||
const flow = {
|
||||
chatflowId: options.chatflowid,
|
||||
sessionId: options.sessionId,
|
||||
|
|
|
|||
|
|
@ -60,7 +60,8 @@ class DocStore_DocumentLoaders 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 === 'SYNC') {
|
||||
const obj = {
|
||||
|
|
|
|||
|
|
@ -96,11 +96,12 @@ class Docx_DocumentLoaders 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)
|
||||
const blob = new Blob([fileData])
|
||||
const loader = new DocxLoader(blob)
|
||||
|
||||
|
|
|
|||
|
|
@ -118,10 +118,11 @@ class Epub_DocumentLoaders implements INode {
|
|||
files = fileName.startsWith('[') && fileName.endsWith(']') ? JSON.parse(fileName) : [fileName]
|
||||
|
||||
const chatflowid = options.chatflowid
|
||||
const orgId = options.orgId
|
||||
|
||||
for (const file of files) {
|
||||
if (!file) continue
|
||||
const fileData = await getFileFromStorage(file, chatflowid)
|
||||
const fileData = await getFileFromStorage(file, orgId, chatflowid)
|
||||
const tempFilePath = path.join(tempDir, `${Date.now()}_${file}`)
|
||||
fs.writeFileSync(tempFilePath, fileData)
|
||||
await this.extractDocs(usage, tempFilePath, textSplitter, docs)
|
||||
|
|
|
|||
|
|
@ -144,6 +144,7 @@ class File_DocumentLoaders implements INode {
|
|||
} else {
|
||||
files = [fileName]
|
||||
}
|
||||
const orgId = options.orgId
|
||||
const chatflowid = options.chatflowid
|
||||
|
||||
// specific to createAttachment to get files from chatId
|
||||
|
|
@ -151,14 +152,14 @@ class File_DocumentLoaders implements INode {
|
|||
if (retrieveAttachmentChatId) {
|
||||
for (const file of files) {
|
||||
if (!file) continue
|
||||
const fileData = await getFileFromStorage(file, chatflowid, options.chatId)
|
||||
const fileData = await getFileFromStorage(file, orgId, chatflowid, options.chatId)
|
||||
const blob = new Blob([fileData])
|
||||
fileBlobs.push({ blob, ext: file.split('.').pop() || '' })
|
||||
}
|
||||
} else {
|
||||
for (const file of files) {
|
||||
if (!file) continue
|
||||
const fileData = await getFileFromStorage(file, chatflowid)
|
||||
const fileData = await getFileFromStorage(file, orgId, chatflowid)
|
||||
const blob = new Blob([fileData])
|
||||
fileBlobs.push({ blob, ext: file.split('.').pop() || '' })
|
||||
}
|
||||
|
|
|
|||
|
|
@ -146,11 +146,12 @@ class Json_DocumentLoaders 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)
|
||||
const blob = new Blob([fileData])
|
||||
const loader = new JSONLoader(blob, pointers.length != 0 ? pointers : undefined, metadata)
|
||||
|
||||
|
|
|
|||
|
|
@ -135,11 +135,12 @@ class Jsonlines_DocumentLoaders 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)
|
||||
const blob = new Blob([fileData])
|
||||
const loader = new JSONLinesLoader(blob, pointer, metadata)
|
||||
|
||||
|
|
|
|||
|
|
@ -122,11 +122,12 @@ class Pdf_DocumentLoaders 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)
|
||||
const bf = Buffer.from(fileData)
|
||||
await this.extractDocs(usage, bf, legacyBuild, textSplitter, docs)
|
||||
}
|
||||
|
|
|
|||
|
|
@ -159,6 +159,7 @@ class Playwright_DocumentLoaders implements INode {
|
|||
let waitForSelector = nodeData.inputs?.waitForSelector as string
|
||||
const _omitMetadataKeys = nodeData.inputs?.omitMetadataKeys as string
|
||||
const output = nodeData.outputs?.output as string
|
||||
const orgId = options.orgId
|
||||
|
||||
let omitMetadataKeys: string[] = []
|
||||
if (_omitMetadataKeys) {
|
||||
|
|
@ -202,13 +203,14 @@ class Playwright_DocumentLoaders implements INode {
|
|||
}
|
||||
return docs
|
||||
} catch (err) {
|
||||
if (process.env.DEBUG === 'true') options.logger.error(`error in PlaywrightWebBaseLoader: ${err.message}, on page: ${url}`)
|
||||
if (process.env.DEBUG === 'true')
|
||||
options.logger.error(`[${orgId}]: Error in PlaywrightWebBaseLoader: ${err.message}, on page: ${url}`)
|
||||
}
|
||||
}
|
||||
|
||||
let docs: IDocument[] = []
|
||||
if (relativeLinksMethod) {
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`Start ${relativeLinksMethod}`)
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`[${orgId}]: Start PlaywrightWebBaseLoader ${relativeLinksMethod}`)
|
||||
// if limit is 0 we don't want it to default to 10 so we check explicitly for null or undefined
|
||||
// so when limit is 0 we can fetch all the links
|
||||
if (limit === null || limit === undefined) limit = 10
|
||||
|
|
@ -219,15 +221,18 @@ class Playwright_DocumentLoaders implements INode {
|
|||
: relativeLinksMethod === 'webCrawl'
|
||||
? await webCrawl(url, limit)
|
||||
: await xmlScrape(url, limit)
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`pages: ${JSON.stringify(pages)}, length: ${pages.length}`)
|
||||
if (process.env.DEBUG === 'true')
|
||||
options.logger.info(`[${orgId}]: PlaywrightWebBaseLoader pages: ${JSON.stringify(pages)}, length: ${pages.length}`)
|
||||
if (!pages || pages.length === 0) throw new Error('No relative links found')
|
||||
for (const page of pages) {
|
||||
docs.push(...(await playwrightLoader(page)))
|
||||
}
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`Finish ${relativeLinksMethod}`)
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`[${orgId}]: Finish PlaywrightWebBaseLoader ${relativeLinksMethod}`)
|
||||
} else if (selectedLinks && selectedLinks.length > 0) {
|
||||
if (process.env.DEBUG === 'true')
|
||||
options.logger.info(`pages: ${JSON.stringify(selectedLinks)}, length: ${selectedLinks.length}`)
|
||||
options.logger.info(
|
||||
`[${orgId}]: PlaywrightWebBaseLoader pages: ${JSON.stringify(selectedLinks)}, length: ${selectedLinks.length}`
|
||||
)
|
||||
for (const page of selectedLinks.slice(0, limit)) {
|
||||
docs.push(...(await playwrightLoader(page)))
|
||||
}
|
||||
|
|
|
|||
|
|
@ -155,6 +155,7 @@ class Puppeteer_DocumentLoaders implements INode {
|
|||
let waitForSelector = nodeData.inputs?.waitForSelector as string
|
||||
const _omitMetadataKeys = nodeData.inputs?.omitMetadataKeys as string
|
||||
const output = nodeData.outputs?.output as string
|
||||
const orgId = options.orgId
|
||||
|
||||
let omitMetadataKeys: string[] = []
|
||||
if (_omitMetadataKeys) {
|
||||
|
|
@ -198,13 +199,14 @@ class Puppeteer_DocumentLoaders implements INode {
|
|||
}
|
||||
return docs
|
||||
} catch (err) {
|
||||
if (process.env.DEBUG === 'true') options.logger.error(`error in PuppeteerWebBaseLoader: ${err.message}, on page: ${url}`)
|
||||
if (process.env.DEBUG === 'true')
|
||||
options.logger.error(`[${orgId}]: Error in PuppeteerWebBaseLoader: ${err.message}, on page: ${url}`)
|
||||
}
|
||||
}
|
||||
|
||||
let docs: IDocument[] = []
|
||||
if (relativeLinksMethod) {
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`Start ${relativeLinksMethod}`)
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`[${orgId}]: Start PuppeteerWebBaseLoader ${relativeLinksMethod}`)
|
||||
// if limit is 0 we don't want it to default to 10 so we check explicitly for null or undefined
|
||||
// so when limit is 0 we can fetch all the links
|
||||
if (limit === null || limit === undefined) limit = 10
|
||||
|
|
@ -215,15 +217,18 @@ class Puppeteer_DocumentLoaders implements INode {
|
|||
: relativeLinksMethod === 'webCrawl'
|
||||
? await webCrawl(url, limit)
|
||||
: await xmlScrape(url, limit)
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`pages: ${JSON.stringify(pages)}, length: ${pages.length}`)
|
||||
if (process.env.DEBUG === 'true')
|
||||
options.logger.info(`[${orgId}]: PuppeteerWebBaseLoader pages: ${JSON.stringify(pages)}, length: ${pages.length}`)
|
||||
if (!pages || pages.length === 0) throw new Error('No relative links found')
|
||||
for (const page of pages) {
|
||||
docs.push(...(await puppeteerLoader(page)))
|
||||
}
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`Finish ${relativeLinksMethod}`)
|
||||
if (process.env.DEBUG === 'true') options.logger.info(`[${orgId}]: Finish PuppeteerWebBaseLoader ${relativeLinksMethod}`)
|
||||
} else if (selectedLinks && selectedLinks.length > 0) {
|
||||
if (process.env.DEBUG === 'true')
|
||||
options.logger.info(`pages: ${JSON.stringify(selectedLinks)}, length: ${selectedLinks.length}`)
|
||||
options.logger.info(
|
||||
`[${orgId}]: PuppeteerWebBaseLoader pages: ${JSON.stringify(selectedLinks)}, length: ${selectedLinks.length}`
|
||||
)
|
||||
for (const page of selectedLinks.slice(0, limit)) {
|
||||
docs.push(...(await puppeteerLoader(page)))
|
||||
}
|
||||
|
|
|
|||
|
|
@ -4,10 +4,10 @@ DS File Loarder integration for Flowise
|
|||
|
||||
## 🌱 Env Variables
|
||||
|
||||
| Variable | Description | Type | Default |
|
||||
| ---------------------------- | ----------------------------------------------------------------------------------------------- | ------------------------------------------------ | ----------------------------------- |
|
||||
| UNSTRUCTURED_API_URL | Default `unstructuredApiUrl` for S3 File Loader | String | http://localhost:8000/general/v0/general |
|
||||
| Variable | Description | Type | Default |
|
||||
| -------------------- | ----------------------------------------------- | ------ | ---------------------------------------- |
|
||||
| UNSTRUCTURED_API_URL | Default `unstructuredApiUrl` for S3 File Loader | String | http://localhost:8000/general/v0/general |
|
||||
|
||||
## License
|
||||
|
||||
Source code in this repository is made available under the [Apache License Version 2.0](https://github.com/FlowiseAI/Flowise/blob/master/LICENSE.md).
|
||||
Source code in this repository is made available under the [Apache License Version 2.0](https://github.com/FlowiseAI/Flowise/blob/master/LICENSE.md).
|
||||
|
|
|
|||
|
|
@ -98,11 +98,12 @@ class Text_DocumentLoaders 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)
|
||||
const blob = new Blob([fileData])
|
||||
const loader = new TextLoader(blob)
|
||||
|
||||
|
|
|
|||
|
|
@ -4,10 +4,10 @@ Unstructured File Loader integration for Flowise
|
|||
|
||||
## 🌱 Env Variables
|
||||
|
||||
| Variable | Description | Type | Default |
|
||||
| ---------------------------- | ----------------------------------------------------------------------------------------------- | ------------------------------------------------ | ----------------------------------- |
|
||||
| UNSTRUCTURED_API_URL | Default `apiUrl` for Unstructured File/Floder Loader | String | http://localhost:8000/general/v0/general |
|
||||
| Variable | Description | Type | Default |
|
||||
| -------------------- | ---------------------------------------------------- | ------ | ---------------------------------------- |
|
||||
| UNSTRUCTURED_API_URL | Default `apiUrl` for Unstructured File/Floder Loader | String | http://localhost:8000/general/v0/general |
|
||||
|
||||
## License
|
||||
|
||||
Source code in this repository is made available under the [Apache License Version 2.0](https://github.com/FlowiseAI/Flowise/blob/master/LICENSE.md).
|
||||
Source code in this repository is made available under the [Apache License Version 2.0](https://github.com/FlowiseAI/Flowise/blob/master/LICENSE.md).
|
||||
|
|
|
|||
|
|
@ -532,11 +532,12 @@ class UnstructuredFile_DocumentLoaders 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)
|
||||
const loaderDocs = await loader.loadAndSplitBuffer(fileData, file)
|
||||
docs.push(...loaderDocs)
|
||||
}
|
||||
|
|
|
|||
|
|
@ -4,13 +4,13 @@ Azure OpenAI Embedding 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_EMBEDDINGS_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_EMBEDDINGS_DEPLOYMENT_NAME | Default `credential.azureOpenAIApiDeploymentName` for Azure OpenAI Model | String | |
|
||||
| AZURE_OPENAI_API_VERSION | Default `credential.azureOpenAIApiVersion` for Azure OpenAI Model | String | |
|
||||
|
||||
## License
|
||||
|
||||
Source code in this repository is made available under the [Apache License Version 2.0](https://github.com/FlowiseAI/Flowise/blob/master/LICENSE.md).
|
||||
Source code in this repository is made available under the [Apache License Version 2.0](https://github.com/FlowiseAI/Flowise/blob/master/LICENSE.md).
|
||||
|
|
|
|||
|
|
@ -10,6 +10,7 @@ import {
|
|||
} from '../../../src/Interface'
|
||||
import { Metadata, BaseRetriever, LLM, ContextChatEngine, ChatMessage, NodeWithScore } from 'llamaindex'
|
||||
import { reformatSourceDocuments } from '../EngineUtils'
|
||||
import { EvaluationRunTracerLlama } from '../../../evaluation/EvaluationRunTracerLlama'
|
||||
|
||||
class ContextChatEngine_LlamaIndex implements INode {
|
||||
label: string
|
||||
|
|
@ -93,6 +94,9 @@ class ContextChatEngine_LlamaIndex implements INode {
|
|||
|
||||
const chatEngine = new ContextChatEngine({ chatModel: model, retriever: vectorStoreRetriever })
|
||||
|
||||
// these are needed for evaluation runs
|
||||
await EvaluationRunTracerLlama.injectEvaluationMetadata(nodeData, options, chatEngine)
|
||||
|
||||
const msgs = (await memory.getChatMessages(this.sessionId, false, prependMessages)) as IMessage[]
|
||||
for (const message of msgs) {
|
||||
if (message.type === 'apiMessage') {
|
||||
|
|
|
|||
|
|
@ -9,6 +9,7 @@ import {
|
|||
IServerSideEventStreamer
|
||||
} from '../../../src/Interface'
|
||||
import { LLM, ChatMessage, SimpleChatEngine } from 'llamaindex'
|
||||
import { EvaluationRunTracerLlama } from '../../../evaluation/EvaluationRunTracerLlama'
|
||||
|
||||
class SimpleChatEngine_LlamaIndex implements INode {
|
||||
label: string
|
||||
|
|
@ -78,6 +79,9 @@ class SimpleChatEngine_LlamaIndex implements INode {
|
|||
|
||||
const chatEngine = new SimpleChatEngine({ llm: model })
|
||||
|
||||
// these are needed for evaluation runs
|
||||
await EvaluationRunTracerLlama.injectEvaluationMetadata(nodeData, options, chatEngine)
|
||||
|
||||
const msgs = (await memory.getChatMessages(this.sessionId, false, prependMessages)) as IMessage[]
|
||||
for (const message of msgs) {
|
||||
if (message.type === 'apiMessage') {
|
||||
|
|
|
|||
|
|
@ -10,6 +10,7 @@ import {
|
|||
NodeWithScore
|
||||
} from 'llamaindex'
|
||||
import { reformatSourceDocuments } from '../EngineUtils'
|
||||
import { EvaluationRunTracerLlama } from '../../../evaluation/EvaluationRunTracerLlama'
|
||||
|
||||
class QueryEngine_LlamaIndex implements INode {
|
||||
label: string
|
||||
|
|
@ -72,6 +73,8 @@ class QueryEngine_LlamaIndex implements INode {
|
|||
let sourceNodes: NodeWithScore<Metadata>[] = []
|
||||
let isStreamingStarted = false
|
||||
|
||||
await EvaluationRunTracerLlama.injectEvaluationMetadata(nodeData, options, queryEngine)
|
||||
|
||||
const shouldStreamResponse = options.shouldStreamResponse
|
||||
const sseStreamer: IServerSideEventStreamer = options.sseStreamer as IServerSideEventStreamer
|
||||
const chatId = options.chatId
|
||||
|
|
|
|||
|
|
@ -15,6 +15,7 @@ import {
|
|||
NodeWithScore
|
||||
} from 'llamaindex'
|
||||
import { reformatSourceDocuments } from '../EngineUtils'
|
||||
import { EvaluationRunTracerLlama } from '../../../evaluation/EvaluationRunTracerLlama'
|
||||
|
||||
class SubQuestionQueryEngine_LlamaIndex implements INode {
|
||||
label: string
|
||||
|
|
@ -89,6 +90,8 @@ class SubQuestionQueryEngine_LlamaIndex implements INode {
|
|||
let sourceNodes: NodeWithScore<Metadata>[] = []
|
||||
let isStreamingStarted = false
|
||||
|
||||
await EvaluationRunTracerLlama.injectEvaluationMetadata(nodeData, options, queryEngine)
|
||||
|
||||
const shouldStreamResponse = options.shouldStreamResponse
|
||||
const sseStreamer: IServerSideEventStreamer = options.sseStreamer as IServerSideEventStreamer
|
||||
const chatId = options.chatId
|
||||
|
|
|
|||
|
|
@ -4,13 +4,13 @@ Azure OpenAI LLM integration for Flowise
|
|||
|
||||
## 🌱 Env Variables
|
||||
|
||||
| Variable | Description | Type | Default |
|
||||
| ---------------------------- | ----------------------------------------------------------------------------------------------- | ------------------------------------------------ | ----------------------------------- |
|
||||
| AZURE_OPENAI_API_KEY | Default `credential.azureOpenAIApiKey` for Azure OpenAI LLM | String | |
|
||||
| AZURE_OPENAI_API_INSTANCE_NAME | Default `credential.azureOpenAIApiInstanceName` for Azure OpenAI LLM | String | |
|
||||
| AZURE_OPENAI_API_DEPLOYMENT_NAME | Default `credential.azureOpenAIApiDeploymentName` for Azure OpenAI LLM | String | |
|
||||
| AZURE_OPENAI_API_VERSION | Default `credential.azureOpenAIApiVersion` for Azure OpenAI LLM | String | |
|
||||
| Variable | Description | Type | Default |
|
||||
| -------------------------------- | ---------------------------------------------------------------------- | ------ | ------- |
|
||||
| AZURE_OPENAI_API_KEY | Default `credential.azureOpenAIApiKey` for Azure OpenAI LLM | String | |
|
||||
| AZURE_OPENAI_API_INSTANCE_NAME | Default `credential.azureOpenAIApiInstanceName` for Azure OpenAI LLM | String | |
|
||||
| AZURE_OPENAI_API_DEPLOYMENT_NAME | Default `credential.azureOpenAIApiDeploymentName` for Azure OpenAI LLM | String | |
|
||||
| AZURE_OPENAI_API_VERSION | Default `credential.azureOpenAIApiVersion` for Azure OpenAI LLM | String | |
|
||||
|
||||
## License
|
||||
|
||||
Source code in this repository is made available under the [Apache License Version 2.0](https://github.com/FlowiseAI/Flowise/blob/master/LICENSE.md).
|
||||
Source code in this repository is made available under the [Apache License Version 2.0](https://github.com/FlowiseAI/Flowise/blob/master/LICENSE.md).
|
||||
|
|
|
|||
|
|
@ -108,6 +108,7 @@ class AgentMemory_Memory implements INode {
|
|||
const databaseType = nodeData.inputs?.databaseType as string
|
||||
const databaseEntities = options.databaseEntities as IDatabaseEntity
|
||||
const chatflowid = options.chatflowid as string
|
||||
const orgId = options.orgId as string
|
||||
const appDataSource = options.appDataSource as DataSource
|
||||
|
||||
let additionalConfiguration = {}
|
||||
|
|
@ -135,7 +136,8 @@ class AgentMemory_Memory implements INode {
|
|||
threadId,
|
||||
appDataSource,
|
||||
databaseEntities,
|
||||
chatflowid
|
||||
chatflowid,
|
||||
orgId
|
||||
}
|
||||
const recordManager = new SqliteSaver(args)
|
||||
return recordManager
|
||||
|
|
@ -159,7 +161,8 @@ class AgentMemory_Memory implements INode {
|
|||
threadId,
|
||||
appDataSource,
|
||||
databaseEntities,
|
||||
chatflowid
|
||||
chatflowid,
|
||||
orgId
|
||||
}
|
||||
const recordManager = new PostgresSaver(args)
|
||||
return recordManager
|
||||
|
|
@ -184,7 +187,8 @@ class AgentMemory_Memory implements INode {
|
|||
threadId,
|
||||
appDataSource,
|
||||
databaseEntities,
|
||||
chatflowid
|
||||
chatflowid,
|
||||
orgId
|
||||
}
|
||||
const recordManager = new MySQLSaver(args)
|
||||
return recordManager
|
||||
|
|
|
|||
|
|
@ -65,6 +65,7 @@ class MySQLAgentMemory_Memory implements INode {
|
|||
const databaseEntities = options.databaseEntities as IDatabaseEntity
|
||||
const chatflowid = options.chatflowid as string
|
||||
const appDataSource = options.appDataSource as DataSource
|
||||
const orgId = options.orgId as string
|
||||
|
||||
let additionalConfiguration = {}
|
||||
if (additionalConfig) {
|
||||
|
|
@ -102,7 +103,8 @@ class MySQLAgentMemory_Memory implements INode {
|
|||
threadId,
|
||||
appDataSource,
|
||||
databaseEntities,
|
||||
chatflowid
|
||||
chatflowid,
|
||||
orgId
|
||||
}
|
||||
const recordManager = new MySQLSaver(args)
|
||||
return recordManager
|
||||
|
|
|
|||
|
|
@ -242,7 +242,7 @@ export class MySQLSaver extends BaseCheckpointSaver implements MemoryMethods {
|
|||
}
|
||||
|
||||
if (returnBaseMessages) {
|
||||
return await mapChatMessageToBaseMessage(chatMessage)
|
||||
return await mapChatMessageToBaseMessage(chatMessage, this.config.orgId)
|
||||
}
|
||||
|
||||
let returnIMessages: IMessage[] = []
|
||||
|
|
|
|||
|
|
@ -65,6 +65,7 @@ class PostgresAgentMemory_Memory implements INode {
|
|||
const databaseEntities = options.databaseEntities as IDatabaseEntity
|
||||
const chatflowid = options.chatflowid as string
|
||||
const appDataSource = options.appDataSource as DataSource
|
||||
const orgId = options.orgId as string
|
||||
|
||||
let additionalConfiguration = {}
|
||||
if (additionalConfig) {
|
||||
|
|
@ -101,7 +102,8 @@ class PostgresAgentMemory_Memory implements INode {
|
|||
threadId,
|
||||
appDataSource,
|
||||
databaseEntities,
|
||||
chatflowid
|
||||
chatflowid,
|
||||
orgId
|
||||
}
|
||||
const recordManager = new PostgresSaver(args)
|
||||
return recordManager
|
||||
|
|
|
|||
|
|
@ -283,7 +283,7 @@ CREATE TABLE IF NOT EXISTS ${tableName} (
|
|||
}
|
||||
|
||||
if (returnBaseMessages) {
|
||||
return await mapChatMessageToBaseMessage(chatMessage)
|
||||
return await mapChatMessageToBaseMessage(chatMessage, this.config.orgId)
|
||||
}
|
||||
|
||||
let returnIMessages: IMessage[] = []
|
||||
|
|
|
|||
|
|
@ -51,6 +51,7 @@ class SQLiteAgentMemory_Memory implements INode {
|
|||
const databaseEntities = options.databaseEntities as IDatabaseEntity
|
||||
const chatflowid = options.chatflowid as string
|
||||
const appDataSource = options.appDataSource as DataSource
|
||||
const orgId = options.orgId as string
|
||||
|
||||
let additionalConfiguration = {}
|
||||
if (additionalConfig) {
|
||||
|
|
@ -76,7 +77,8 @@ class SQLiteAgentMemory_Memory implements INode {
|
|||
threadId,
|
||||
appDataSource,
|
||||
databaseEntities,
|
||||
chatflowid
|
||||
chatflowid,
|
||||
orgId
|
||||
}
|
||||
|
||||
const recordManager = new SqliteSaver(args)
|
||||
|
|
|
|||
|
|
@ -266,7 +266,7 @@ CREATE TABLE IF NOT EXISTS ${tableName} (
|
|||
}
|
||||
|
||||
if (returnBaseMessages) {
|
||||
return await mapChatMessageToBaseMessage(chatMessage)
|
||||
return await mapChatMessageToBaseMessage(chatMessage, this.config.orgId)
|
||||
}
|
||||
|
||||
let returnIMessages: IMessage[] = []
|
||||
|
|
|
|||
|
|
@ -9,6 +9,7 @@ export type SaverOptions = {
|
|||
appDataSource: DataSource
|
||||
databaseEntities: IDatabaseEntity
|
||||
chatflowid: string
|
||||
orgId: string
|
||||
}
|
||||
|
||||
export interface CheckpointTuple {
|
||||
|
|
|
|||
|
|
@ -61,6 +61,7 @@ class BufferMemory_Memory implements INode {
|
|||
const appDataSource = options.appDataSource as DataSource
|
||||
const databaseEntities = options.databaseEntities as IDatabaseEntity
|
||||
const chatflowid = options.chatflowid as string
|
||||
const orgId = options.orgId as string
|
||||
|
||||
return new BufferMemoryExtended({
|
||||
returnMessages: true,
|
||||
|
|
@ -68,7 +69,8 @@ class BufferMemory_Memory implements INode {
|
|||
sessionId,
|
||||
appDataSource,
|
||||
databaseEntities,
|
||||
chatflowid
|
||||
chatflowid,
|
||||
orgId
|
||||
})
|
||||
}
|
||||
}
|
||||
|
|
@ -78,12 +80,14 @@ interface BufferMemoryExtendedInput {
|
|||
appDataSource: DataSource
|
||||
databaseEntities: IDatabaseEntity
|
||||
chatflowid: string
|
||||
orgId: string
|
||||
}
|
||||
|
||||
class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
||||
appDataSource: DataSource
|
||||
databaseEntities: IDatabaseEntity
|
||||
chatflowid: string
|
||||
orgId: string
|
||||
sessionId = ''
|
||||
|
||||
constructor(fields: BufferMemoryInput & BufferMemoryExtendedInput) {
|
||||
|
|
@ -92,6 +96,7 @@ class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
|||
this.appDataSource = fields.appDataSource
|
||||
this.databaseEntities = fields.databaseEntities
|
||||
this.chatflowid = fields.chatflowid
|
||||
this.orgId = fields.orgId
|
||||
}
|
||||
|
||||
async getChatMessages(
|
||||
|
|
@ -117,7 +122,7 @@ class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
|||
}
|
||||
|
||||
if (returnBaseMessages) {
|
||||
return await mapChatMessageToBaseMessage(chatMessage)
|
||||
return await mapChatMessageToBaseMessage(chatMessage, this.orgId)
|
||||
}
|
||||
|
||||
let returnIMessages: IMessage[] = []
|
||||
|
|
|
|||
|
|
@ -69,6 +69,7 @@ class BufferWindowMemory_Memory implements INode {
|
|||
const appDataSource = options.appDataSource as DataSource
|
||||
const databaseEntities = options.databaseEntities as IDatabaseEntity
|
||||
const chatflowid = options.chatflowid as string
|
||||
const orgId = options.orgId as string
|
||||
|
||||
const obj: Partial<BufferWindowMemoryInput> & BufferMemoryExtendedInput = {
|
||||
returnMessages: true,
|
||||
|
|
@ -77,7 +78,8 @@ class BufferWindowMemory_Memory implements INode {
|
|||
k: parseInt(k, 10),
|
||||
appDataSource,
|
||||
databaseEntities,
|
||||
chatflowid
|
||||
chatflowid,
|
||||
orgId
|
||||
}
|
||||
|
||||
return new BufferWindowMemoryExtended(obj)
|
||||
|
|
@ -89,12 +91,14 @@ interface BufferMemoryExtendedInput {
|
|||
appDataSource: DataSource
|
||||
databaseEntities: IDatabaseEntity
|
||||
chatflowid: string
|
||||
orgId: string
|
||||
}
|
||||
|
||||
class BufferWindowMemoryExtended extends FlowiseWindowMemory implements MemoryMethods {
|
||||
appDataSource: DataSource
|
||||
databaseEntities: IDatabaseEntity
|
||||
chatflowid: string
|
||||
orgId: string
|
||||
sessionId = ''
|
||||
|
||||
constructor(fields: BufferWindowMemoryInput & BufferMemoryExtendedInput) {
|
||||
|
|
@ -103,6 +107,7 @@ class BufferWindowMemoryExtended extends FlowiseWindowMemory implements MemoryMe
|
|||
this.appDataSource = fields.appDataSource
|
||||
this.databaseEntities = fields.databaseEntities
|
||||
this.chatflowid = fields.chatflowid
|
||||
this.orgId = fields.orgId
|
||||
}
|
||||
|
||||
async getChatMessages(
|
||||
|
|
@ -134,7 +139,7 @@ class BufferWindowMemoryExtended extends FlowiseWindowMemory implements MemoryMe
|
|||
}
|
||||
|
||||
if (returnBaseMessages) {
|
||||
return await mapChatMessageToBaseMessage(chatMessage)
|
||||
return await mapChatMessageToBaseMessage(chatMessage, this.orgId)
|
||||
}
|
||||
|
||||
let returnIMessages: IMessage[] = []
|
||||
|
|
|
|||
|
|
@ -78,6 +78,7 @@ class ConversationSummaryBufferMemory_Memory implements INode {
|
|||
const appDataSource = options.appDataSource as DataSource
|
||||
const databaseEntities = options.databaseEntities as IDatabaseEntity
|
||||
const chatflowid = options.chatflowid as string
|
||||
const orgId = options.orgId as string
|
||||
|
||||
const obj: ConversationSummaryBufferMemoryInput & BufferMemoryExtendedInput = {
|
||||
llm: model,
|
||||
|
|
@ -87,7 +88,8 @@ class ConversationSummaryBufferMemory_Memory implements INode {
|
|||
returnMessages: true,
|
||||
appDataSource,
|
||||
databaseEntities,
|
||||
chatflowid
|
||||
chatflowid,
|
||||
orgId
|
||||
}
|
||||
|
||||
return new ConversationSummaryBufferMemoryExtended(obj)
|
||||
|
|
@ -99,12 +101,14 @@ interface BufferMemoryExtendedInput {
|
|||
appDataSource: DataSource
|
||||
databaseEntities: IDatabaseEntity
|
||||
chatflowid: string
|
||||
orgId: string
|
||||
}
|
||||
|
||||
class ConversationSummaryBufferMemoryExtended extends FlowiseSummaryBufferMemory implements MemoryMethods {
|
||||
appDataSource: DataSource
|
||||
databaseEntities: IDatabaseEntity
|
||||
chatflowid: string
|
||||
orgId: string
|
||||
sessionId = ''
|
||||
|
||||
constructor(fields: ConversationSummaryBufferMemoryInput & BufferMemoryExtendedInput) {
|
||||
|
|
@ -113,6 +117,7 @@ class ConversationSummaryBufferMemoryExtended extends FlowiseSummaryBufferMemory
|
|||
this.appDataSource = fields.appDataSource
|
||||
this.databaseEntities = fields.databaseEntities
|
||||
this.chatflowid = fields.chatflowid
|
||||
this.orgId = fields.orgId
|
||||
}
|
||||
|
||||
async getChatMessages(
|
||||
|
|
@ -137,7 +142,7 @@ class ConversationSummaryBufferMemoryExtended extends FlowiseSummaryBufferMemory
|
|||
chatMessage.unshift(...prependMessages)
|
||||
}
|
||||
|
||||
let baseMessages = await mapChatMessageToBaseMessage(chatMessage)
|
||||
let baseMessages = await mapChatMessageToBaseMessage(chatMessage, this.orgId)
|
||||
|
||||
// Prune baseMessages if it exceeds max token limit
|
||||
if (this.movingSummaryBuffer) {
|
||||
|
|
|
|||
|
|
@ -69,6 +69,7 @@ class ConversationSummaryMemory_Memory implements INode {
|
|||
const appDataSource = options.appDataSource as DataSource
|
||||
const databaseEntities = options.databaseEntities as IDatabaseEntity
|
||||
const chatflowid = options.chatflowid as string
|
||||
const orgId = options.orgId as string
|
||||
|
||||
const obj: ConversationSummaryMemoryInput & BufferMemoryExtendedInput = {
|
||||
llm: model,
|
||||
|
|
@ -77,7 +78,8 @@ class ConversationSummaryMemory_Memory implements INode {
|
|||
sessionId,
|
||||
appDataSource,
|
||||
databaseEntities,
|
||||
chatflowid
|
||||
chatflowid,
|
||||
orgId
|
||||
}
|
||||
|
||||
return new ConversationSummaryMemoryExtended(obj)
|
||||
|
|
@ -89,12 +91,14 @@ interface BufferMemoryExtendedInput {
|
|||
appDataSource: DataSource
|
||||
databaseEntities: IDatabaseEntity
|
||||
chatflowid: string
|
||||
orgId: string
|
||||
}
|
||||
|
||||
class ConversationSummaryMemoryExtended extends FlowiseSummaryMemory implements MemoryMethods {
|
||||
appDataSource: DataSource
|
||||
databaseEntities: IDatabaseEntity
|
||||
chatflowid: string
|
||||
orgId: string
|
||||
sessionId = ''
|
||||
|
||||
constructor(fields: ConversationSummaryMemoryInput & BufferMemoryExtendedInput) {
|
||||
|
|
@ -103,6 +107,7 @@ class ConversationSummaryMemoryExtended extends FlowiseSummaryMemory implements
|
|||
this.appDataSource = fields.appDataSource
|
||||
this.databaseEntities = fields.databaseEntities
|
||||
this.chatflowid = fields.chatflowid
|
||||
this.orgId = fields.orgId
|
||||
}
|
||||
|
||||
async getChatMessages(
|
||||
|
|
@ -128,7 +133,7 @@ class ConversationSummaryMemoryExtended extends FlowiseSummaryMemory implements
|
|||
chatMessage.unshift(...prependMessages)
|
||||
}
|
||||
|
||||
const baseMessages = await mapChatMessageToBaseMessage(chatMessage)
|
||||
const baseMessages = await mapChatMessageToBaseMessage(chatMessage, this.orgId)
|
||||
|
||||
// Get summary
|
||||
if (this.llm && typeof this.llm !== 'string') {
|
||||
|
|
|
|||
|
|
@ -125,6 +125,8 @@ const initializeDynamoDB = async (nodeData: INodeData, options: ICommonObject):
|
|||
config
|
||||
})
|
||||
|
||||
const orgId = options.orgId as string
|
||||
|
||||
const memory = new BufferMemoryExtended({
|
||||
memoryKey: memoryKey ?? 'chat_history',
|
||||
chatHistory: dynamoDb,
|
||||
|
|
@ -132,7 +134,8 @@ const initializeDynamoDB = async (nodeData: INodeData, options: ICommonObject):
|
|||
dynamodbClient: client,
|
||||
tableName,
|
||||
partitionKey,
|
||||
dynamoKey: { [partitionKey]: { S: sessionId } }
|
||||
dynamoKey: { [partitionKey]: { S: sessionId } },
|
||||
orgId
|
||||
})
|
||||
return memory
|
||||
}
|
||||
|
|
@ -143,6 +146,7 @@ interface BufferMemoryExtendedInput {
|
|||
tableName: string
|
||||
partitionKey: string
|
||||
dynamoKey: Record<string, AttributeValue>
|
||||
orgId: string
|
||||
}
|
||||
|
||||
interface DynamoDBSerializedChatMessage {
|
||||
|
|
@ -165,6 +169,7 @@ class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
|||
private dynamoKey: Record<string, AttributeValue>
|
||||
private messageAttributeName: string
|
||||
sessionId = ''
|
||||
orgId = ''
|
||||
dynamodbClient: DynamoDBClient
|
||||
|
||||
constructor(fields: BufferMemoryInput & BufferMemoryExtendedInput) {
|
||||
|
|
@ -174,6 +179,7 @@ class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
|||
this.tableName = fields.tableName
|
||||
this.partitionKey = fields.partitionKey
|
||||
this.dynamoKey = fields.dynamoKey
|
||||
this.orgId = fields.orgId
|
||||
}
|
||||
|
||||
overrideDynamoKey(overrideSessionId = '') {
|
||||
|
|
@ -260,7 +266,7 @@ class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
|||
.filter((x): x is StoredMessage => x.type !== undefined && x.data.content !== undefined)
|
||||
const baseMessages = messages.map(mapStoredMessageToChatMessage)
|
||||
if (prependMessages?.length) {
|
||||
baseMessages.unshift(...(await mapChatMessageToBaseMessage(prependMessages)))
|
||||
baseMessages.unshift(...(await mapChatMessageToBaseMessage(prependMessages, this.orgId)))
|
||||
}
|
||||
return returnBaseMessages ? baseMessages : convertBaseMessagetoIMessage(baseMessages)
|
||||
}
|
||||
|
|
|
|||
|
|
@ -151,6 +151,7 @@ class Mem0_Memory implements INode {
|
|||
const initializeMem0 = async (nodeData: INodeData, options: ICommonObject): Promise<BaseMem0Memory> => {
|
||||
const initialUserId = nodeData.inputs?.user_id as string
|
||||
const useFlowiseChatId = nodeData.inputs?.useFlowiseChatId as boolean
|
||||
const orgId = options.orgId as string
|
||||
|
||||
if (!useFlowiseChatId && !initialUserId) {
|
||||
throw new Error('User ID field cannot be empty when "Use Flowise Chat ID" is OFF.')
|
||||
|
|
@ -198,7 +199,8 @@ const initializeMem0 = async (nodeData: INodeData, options: ICommonObject): Prom
|
|||
databaseEntities: options.databaseEntities as IDatabaseEntity,
|
||||
chatflowid: options.chatflowid as string,
|
||||
searchOnly: (nodeData.inputs?.searchOnly as boolean) || false,
|
||||
useFlowiseChatId: useFlowiseChatId
|
||||
useFlowiseChatId: useFlowiseChatId,
|
||||
orgId: orgId
|
||||
}
|
||||
|
||||
return new Mem0MemoryExtended(obj)
|
||||
|
|
@ -207,11 +209,13 @@ const initializeMem0 = async (nodeData: INodeData, options: ICommonObject): Prom
|
|||
interface Mem0MemoryExtendedInput extends Mem0MemoryInput {
|
||||
memoryOptions?: MemoryOptions | SearchOptions
|
||||
useFlowiseChatId: boolean
|
||||
orgId: string
|
||||
}
|
||||
|
||||
class Mem0MemoryExtended extends BaseMem0Memory implements MemoryMethods {
|
||||
initialUserId: string
|
||||
userId: string
|
||||
orgId: string
|
||||
memoryKey: string
|
||||
inputKey: string
|
||||
appDataSource: DataSource
|
||||
|
|
@ -233,6 +237,7 @@ class Mem0MemoryExtended extends BaseMem0Memory implements MemoryMethods {
|
|||
this.chatflowid = fields.chatflowid
|
||||
this.searchOnly = fields.searchOnly
|
||||
this.useFlowiseChatId = fields.useFlowiseChatId
|
||||
this.orgId = fields.orgId
|
||||
}
|
||||
|
||||
// Selects Mem0 user_id based on toggle state (Flowise chat ID or input field)
|
||||
|
|
@ -337,7 +342,7 @@ class Mem0MemoryExtended extends BaseMem0Memory implements MemoryMethods {
|
|||
console.warn('Mem0 history is not a string, cannot prepend directly.')
|
||||
}
|
||||
|
||||
return await mapChatMessageToBaseMessage(chatMessage)
|
||||
return await mapChatMessageToBaseMessage(chatMessage, this.orgId)
|
||||
}
|
||||
|
||||
return returnIMessages
|
||||
|
|
|
|||
|
|
@ -88,9 +88,12 @@ const initializeMongoDB = async (nodeData: INodeData, options: ICommonObject): P
|
|||
const mongoDBConnectUrl = getCredentialParam('mongoDBConnectUrl', credentialData, nodeData)
|
||||
const driverInfo = { name: 'Flowise', version: (await getVersion()).version }
|
||||
|
||||
const orgId = options.orgId as string
|
||||
|
||||
return new BufferMemoryExtended({
|
||||
memoryKey: memoryKey ?? 'chat_history',
|
||||
sessionId,
|
||||
orgId,
|
||||
mongoConnection: {
|
||||
databaseName,
|
||||
collectionName,
|
||||
|
|
@ -102,6 +105,7 @@ const initializeMongoDB = async (nodeData: INodeData, options: ICommonObject): P
|
|||
|
||||
interface BufferMemoryExtendedInput {
|
||||
sessionId: string
|
||||
orgId: string
|
||||
mongoConnection: {
|
||||
databaseName: string
|
||||
collectionName: string
|
||||
|
|
@ -112,6 +116,7 @@ interface BufferMemoryExtendedInput {
|
|||
|
||||
class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
||||
sessionId = ''
|
||||
orgId = ''
|
||||
mongoConnection: {
|
||||
databaseName: string
|
||||
collectionName: string
|
||||
|
|
@ -122,6 +127,7 @@ class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
|||
constructor(fields: BufferMemoryInput & BufferMemoryExtendedInput) {
|
||||
super(fields)
|
||||
this.sessionId = fields.sessionId
|
||||
this.orgId = fields.orgId
|
||||
this.mongoConnection = fields.mongoConnection
|
||||
}
|
||||
|
||||
|
|
@ -138,7 +144,7 @@ class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
|||
const messages = document?.messages || []
|
||||
const baseMessages = messages.map(mapStoredMessageToChatMessage)
|
||||
if (prependMessages?.length) {
|
||||
baseMessages.unshift(...(await mapChatMessageToBaseMessage(prependMessages)))
|
||||
baseMessages.unshift(...(await mapChatMessageToBaseMessage(prependMessages, this.orgId)))
|
||||
}
|
||||
|
||||
await client.close()
|
||||
|
|
|
|||
|
|
@ -88,6 +88,7 @@ const initializeRedis = async (nodeData: INodeData, options: ICommonObject): Pro
|
|||
|
||||
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
|
||||
const redisUrl = getCredentialParam('redisUrl', credentialData, nodeData)
|
||||
const orgId = options.orgId as string
|
||||
|
||||
const redisOptions = redisUrl
|
||||
? redisUrl
|
||||
|
|
@ -104,7 +105,8 @@ const initializeRedis = async (nodeData: INodeData, options: ICommonObject): Pro
|
|||
sessionId,
|
||||
windowSize,
|
||||
sessionTTL,
|
||||
redisOptions
|
||||
redisOptions,
|
||||
orgId
|
||||
})
|
||||
|
||||
return memory
|
||||
|
|
@ -114,11 +116,13 @@ interface BufferMemoryExtendedInput {
|
|||
sessionId: string
|
||||
windowSize?: number
|
||||
sessionTTL?: number
|
||||
orgId: string
|
||||
redisOptions: RedisOptions | string
|
||||
}
|
||||
|
||||
class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
||||
sessionId = ''
|
||||
orgId = ''
|
||||
windowSize?: number
|
||||
sessionTTL?: number
|
||||
redisOptions: RedisOptions | string
|
||||
|
|
@ -128,6 +132,7 @@ class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
|||
this.sessionId = fields.sessionId
|
||||
this.windowSize = fields.windowSize
|
||||
this.sessionTTL = fields.sessionTTL
|
||||
this.orgId = fields.orgId
|
||||
this.redisOptions = fields.redisOptions
|
||||
}
|
||||
|
||||
|
|
@ -165,7 +170,7 @@ class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
|||
const orderedMessages = rawStoredMessages.reverse().map((message) => JSON.parse(message))
|
||||
const baseMessages = orderedMessages.map(mapStoredMessageToChatMessage)
|
||||
if (prependMessages?.length) {
|
||||
baseMessages.unshift(...(await mapChatMessageToBaseMessage(prependMessages)))
|
||||
baseMessages.unshift(...(await mapChatMessageToBaseMessage(prependMessages, this.orgId)))
|
||||
}
|
||||
return returnBaseMessages ? baseMessages : convertBaseMessagetoIMessage(baseMessages)
|
||||
})
|
||||
|
|
|
|||
|
|
@ -100,13 +100,14 @@ const initalizeUpstashRedis = async (nodeData: INodeData, options: ICommonObject
|
|||
sessionTTL,
|
||||
client
|
||||
})
|
||||
|
||||
const orgId = options.orgId as string
|
||||
const memory = new BufferMemoryExtended({
|
||||
memoryKey: memoryKey ?? 'chat_history',
|
||||
chatHistory: redisChatMessageHistory,
|
||||
sessionId,
|
||||
sessionTTL,
|
||||
redisClient: client
|
||||
redisClient: client,
|
||||
orgId
|
||||
})
|
||||
|
||||
return memory
|
||||
|
|
@ -115,11 +116,13 @@ const initalizeUpstashRedis = async (nodeData: INodeData, options: ICommonObject
|
|||
interface BufferMemoryExtendedInput {
|
||||
redisClient: Redis
|
||||
sessionId: string
|
||||
orgId: string
|
||||
sessionTTL?: number
|
||||
}
|
||||
|
||||
class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
||||
sessionId = ''
|
||||
orgId = ''
|
||||
redisClient: Redis
|
||||
sessionTTL?: number
|
||||
|
||||
|
|
@ -128,6 +131,7 @@ class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
|||
this.sessionId = fields.sessionId
|
||||
this.redisClient = fields.redisClient
|
||||
this.sessionTTL = fields.sessionTTL
|
||||
this.orgId = fields.orgId
|
||||
}
|
||||
|
||||
async getChatMessages(
|
||||
|
|
@ -143,7 +147,7 @@ class BufferMemoryExtended extends FlowiseMemory implements MemoryMethods {
|
|||
const previousMessages = orderedMessages.filter((x): x is StoredMessage => x.type !== undefined && x.data.content !== undefined)
|
||||
const baseMessages = previousMessages.map(mapStoredMessageToChatMessage)
|
||||
if (prependMessages?.length) {
|
||||
baseMessages.unshift(...(await mapChatMessageToBaseMessage(prependMessages)))
|
||||
baseMessages.unshift(...(await mapChatMessageToBaseMessage(prependMessages, this.orgId)))
|
||||
}
|
||||
return returnBaseMessages ? baseMessages : convertBaseMessagetoIMessage(baseMessages)
|
||||
}
|
||||
|
|
|
|||
|
|
@ -119,6 +119,7 @@ const initializeZep = async (nodeData: INodeData, options: ICommonObject): Promi
|
|||
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
|
||||
const apiKey = getCredentialParam('apiKey', credentialData, nodeData)
|
||||
|
||||
const orgId = options.orgId as string
|
||||
const obj: ZepMemoryInput & ZepMemoryExtendedInput = {
|
||||
baseURL,
|
||||
aiPrefix,
|
||||
|
|
@ -127,6 +128,7 @@ const initializeZep = async (nodeData: INodeData, options: ICommonObject): Promi
|
|||
memoryKey,
|
||||
inputKey,
|
||||
sessionId,
|
||||
orgId,
|
||||
k: k ? parseInt(k, 10) : undefined
|
||||
}
|
||||
if (apiKey) obj.apiKey = apiKey
|
||||
|
|
@ -136,14 +138,17 @@ const initializeZep = async (nodeData: INodeData, options: ICommonObject): Promi
|
|||
|
||||
interface ZepMemoryExtendedInput {
|
||||
k?: number
|
||||
orgId: string
|
||||
}
|
||||
|
||||
class ZepMemoryExtended extends ZepMemory implements MemoryMethods {
|
||||
lastN?: number
|
||||
orgId = ''
|
||||
|
||||
constructor(fields: ZepMemoryInput & ZepMemoryExtendedInput) {
|
||||
super(fields)
|
||||
this.lastN = fields.k
|
||||
this.orgId = fields.orgId
|
||||
}
|
||||
|
||||
async loadMemoryVariables(values: InputValues, overrideSessionId = ''): Promise<MemoryVariables> {
|
||||
|
|
@ -176,7 +181,7 @@ class ZepMemoryExtended extends ZepMemory implements MemoryMethods {
|
|||
const memoryVariables = await this.loadMemoryVariables({}, id)
|
||||
const baseMessages = memoryVariables[this.memoryKey]
|
||||
if (prependMessages?.length) {
|
||||
baseMessages.unshift(...(await mapChatMessageToBaseMessage(prependMessages)))
|
||||
baseMessages.unshift(...(await mapChatMessageToBaseMessage(prependMessages, this.orgId)))
|
||||
}
|
||||
return returnBaseMessages ? baseMessages : convertBaseMessagetoIMessage(baseMessages)
|
||||
}
|
||||
|
|
|
|||
|
|
@ -113,6 +113,7 @@ const initializeZep = async (nodeData: INodeData, options: ICommonObject): Promi
|
|||
|
||||
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
|
||||
const apiKey = getCredentialParam('apiKey', credentialData, nodeData)
|
||||
const orgId = options.orgId as string
|
||||
const obj: ZepMemoryInput & ZepMemoryExtendedInput = {
|
||||
apiKey,
|
||||
aiPrefix,
|
||||
|
|
@ -121,7 +122,8 @@ const initializeZep = async (nodeData: INodeData, options: ICommonObject): Promi
|
|||
sessionId,
|
||||
inputKey,
|
||||
memoryType: memoryType,
|
||||
returnMessages: true
|
||||
returnMessages: true,
|
||||
orgId
|
||||
}
|
||||
|
||||
return new ZepMemoryExtended(obj)
|
||||
|
|
@ -129,14 +131,17 @@ const initializeZep = async (nodeData: INodeData, options: ICommonObject): Promi
|
|||
|
||||
interface ZepMemoryExtendedInput {
|
||||
memoryType?: 'perpetual' | 'message_window'
|
||||
orgId: string
|
||||
}
|
||||
|
||||
class ZepMemoryExtended extends ZepMemory implements MemoryMethods {
|
||||
memoryType: 'perpetual' | 'message_window'
|
||||
orgId: string
|
||||
|
||||
constructor(fields: ZepMemoryInput & ZepMemoryExtendedInput) {
|
||||
super(fields)
|
||||
this.memoryType = fields.memoryType ?? 'perpetual'
|
||||
this.orgId = fields.orgId
|
||||
}
|
||||
|
||||
async loadMemoryVariables(values: InputValues, overrideSessionId = ''): Promise<MemoryVariables> {
|
||||
|
|
@ -169,7 +174,7 @@ class ZepMemoryExtended extends ZepMemory implements MemoryMethods {
|
|||
const memoryVariables = await this.loadMemoryVariables({}, id)
|
||||
const baseMessages = memoryVariables[this.memoryKey]
|
||||
if (prependMessages?.length) {
|
||||
baseMessages.unshift(...(await mapChatMessageToBaseMessage(prependMessages)))
|
||||
baseMessages.unshift(...(await mapChatMessageToBaseMessage(prependMessages, this.orgId)))
|
||||
}
|
||||
return returnBaseMessages ? baseMessages : convertBaseMessagetoIMessage(baseMessages)
|
||||
}
|
||||
|
|
|
|||
|
|
@ -233,7 +233,7 @@ async function createAgent(
|
|||
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
|
||||
|
|
|
|||
|
|
@ -120,7 +120,7 @@ class ChatPromptTemplate_Prompts implements INode {
|
|||
) {
|
||||
const appDataSource = options.appDataSource as DataSource
|
||||
const databaseEntities = options.databaseEntities as IDatabaseEntity
|
||||
const vm = await getVM(appDataSource, databaseEntities, nodeData, {})
|
||||
const vm = await getVM(appDataSource, databaseEntities, nodeData, options, {})
|
||||
try {
|
||||
const response = await vm.run(`module.exports = async function() {${messageHistoryCode}}()`, __dirname)
|
||||
if (!Array.isArray(response)) throw new Error('Returned message history must be an array')
|
||||
|
|
|
|||
|
|
@ -680,7 +680,7 @@ async function createAgent(
|
|||
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
|
||||
|
|
@ -877,7 +877,7 @@ const getReturnOutput = async (nodeData: INodeData, input: string, options: ICom
|
|||
const updateStateMemory = nodeData.inputs?.updateStateMemory as string
|
||||
|
||||
const selectedTab = tabIdentifier ? tabIdentifier.split(`_${nodeData.id}`)[0] : 'updateStateMemoryUI'
|
||||
const variables = await getVars(appDataSource, databaseEntities, nodeData)
|
||||
const variables = await getVars(appDataSource, databaseEntities, nodeData, options)
|
||||
|
||||
const flow = {
|
||||
chatflowId: options.chatflowid,
|
||||
|
|
@ -930,7 +930,7 @@ const getReturnOutput = async (nodeData: INodeData, input: string, options: ICom
|
|||
throw new Error(e)
|
||||
}
|
||||
} else if (selectedTab === 'updateStateMemoryCode' && updateStateMemoryCode) {
|
||||
const vm = await getVM(appDataSource, databaseEntities, nodeData, flow)
|
||||
const vm = await getVM(appDataSource, databaseEntities, nodeData, options, flow)
|
||||
try {
|
||||
const response = await vm.run(`module.exports = async function() {${updateStateMemoryCode}}()`, __dirname)
|
||||
if (typeof response !== 'object') throw new Error('Return output must be an object')
|
||||
|
|
|
|||
|
|
@ -267,7 +267,7 @@ const runCondition = async (nodeData: INodeData, input: string, options: ICommon
|
|||
const tabIdentifier = nodeData.inputs?.[`${TAB_IDENTIFIER}_${nodeData.id}`] as string
|
||||
|
||||
const selectedTab = tabIdentifier ? tabIdentifier.split(`_${nodeData.id}`)[0] : 'conditionUI'
|
||||
const variables = await getVars(appDataSource, databaseEntities, nodeData)
|
||||
const variables = await getVars(appDataSource, databaseEntities, nodeData, options)
|
||||
|
||||
const flow = {
|
||||
chatflowId: options.chatflowid,
|
||||
|
|
@ -279,7 +279,7 @@ const runCondition = async (nodeData: INodeData, input: string, options: ICommon
|
|||
}
|
||||
|
||||
if (selectedTab === 'conditionFunction' && conditionFunction) {
|
||||
const vm = await getVM(appDataSource, databaseEntities, nodeData, flow)
|
||||
const vm = await getVM(appDataSource, databaseEntities, nodeData, options, flow)
|
||||
try {
|
||||
const response = await vm.run(`module.exports = async function() {${conditionFunction}}()`, __dirname)
|
||||
if (typeof response !== 'string') throw new Error('Condition function must return a string')
|
||||
|
|
|
|||
|
|
@ -540,7 +540,7 @@ const runCondition = async (
|
|||
result = { ...jsonResult, additional_kwargs: { nodeId: nodeData.id } }
|
||||
}
|
||||
|
||||
const variables = await getVars(appDataSource, databaseEntities, nodeData)
|
||||
const variables = await getVars(appDataSource, databaseEntities, nodeData, options)
|
||||
|
||||
const flow = {
|
||||
chatflowId: options.chatflowid,
|
||||
|
|
@ -553,7 +553,7 @@ const runCondition = async (
|
|||
}
|
||||
|
||||
if (selectedTab === 'conditionFunction' && conditionFunction) {
|
||||
const vm = await getVM(appDataSource, databaseEntities, nodeData, flow)
|
||||
const vm = await getVM(appDataSource, databaseEntities, nodeData, options, flow)
|
||||
try {
|
||||
const response = await vm.run(`module.exports = async function() {${conditionFunction}}()`, __dirname)
|
||||
if (typeof response !== 'string') throw new Error('Condition function must return a string')
|
||||
|
|
|
|||
|
|
@ -102,7 +102,7 @@ class CustomFunction_SeqAgents implements INode {
|
|||
if (!sequentialNodes || !sequentialNodes.length) throw new Error('Custom function must have a predecessor!')
|
||||
|
||||
const executeFunc = async (state: ISeqAgentsState) => {
|
||||
const variables = await getVars(appDataSource, databaseEntities, nodeData)
|
||||
const variables = await getVars(appDataSource, databaseEntities, nodeData, options)
|
||||
const flow = {
|
||||
chatflowId: options.chatflowid,
|
||||
sessionId: options.sessionId,
|
||||
|
|
|
|||
|
|
@ -141,7 +141,8 @@ class ExecuteFlow_SeqAgents 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) {
|
||||
const data = {
|
||||
|
|
@ -189,7 +190,7 @@ class ExecuteFlow_SeqAgents implements INode {
|
|||
const chatId = options.chatId
|
||||
|
||||
const executeFunc = async (state: ISeqAgentsState) => {
|
||||
const variables = await getVars(appDataSource, databaseEntities, nodeData)
|
||||
const variables = await getVars(appDataSource, databaseEntities, nodeData, options)
|
||||
|
||||
let flowInput = ''
|
||||
if (seqExecuteFlowInput === 'userQuestion') {
|
||||
|
|
@ -223,7 +224,7 @@ class ExecuteFlow_SeqAgents implements INode {
|
|||
}
|
||||
}
|
||||
|
||||
const options = {
|
||||
const callOptions = {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
|
|
@ -234,7 +235,7 @@ class ExecuteFlow_SeqAgents implements INode {
|
|||
|
||||
let sandbox: ICommonObject = {
|
||||
$input: flowInput,
|
||||
$callOptions: options,
|
||||
$callOptions: callOptions,
|
||||
$callBody: body,
|
||||
util: undefined,
|
||||
Symbol: undefined,
|
||||
|
|
|
|||
|
|
@ -668,7 +668,7 @@ const getReturnOutput = async (nodeData: INodeData, input: string, options: ICom
|
|||
const updateStateMemory = nodeData.inputs?.updateStateMemory as string
|
||||
|
||||
const selectedTab = tabIdentifier ? tabIdentifier.split(`_${nodeData.id}`)[0] : 'updateStateMemoryUI'
|
||||
const variables = await getVars(appDataSource, databaseEntities, nodeData)
|
||||
const variables = await getVars(appDataSource, databaseEntities, nodeData, options)
|
||||
|
||||
const flow = {
|
||||
chatflowId: options.chatflowid,
|
||||
|
|
@ -721,7 +721,7 @@ const getReturnOutput = async (nodeData: INodeData, input: string, options: ICom
|
|||
throw new Error(e)
|
||||
}
|
||||
} else if (selectedTab === 'updateStateMemoryCode' && updateStateMemoryCode) {
|
||||
const vm = await getVM(appDataSource, databaseEntities, nodeData, flow)
|
||||
const vm = await getVM(appDataSource, databaseEntities, nodeData, options, flow)
|
||||
try {
|
||||
const response = await vm.run(`module.exports = async function() {${updateStateMemoryCode}}()`, __dirname)
|
||||
if (typeof response !== 'object') throw new Error('Return output must be an object')
|
||||
|
|
|
|||
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Reference in New Issue