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@@ -1,2 +1,4 @@
|
||||
**/node_modules
|
||||
api/.env
|
||||
.env
|
||||
client/dist/images
|
||||
@@ -10,27 +10,27 @@
|
||||
# Set Node env to development if running in dev mode.
|
||||
HOST=localhost
|
||||
PORT=3080
|
||||
NODE_ENV=production
|
||||
|
||||
# Change this to proxy any API request.
|
||||
# It's useful if your machine has difficulty calling the original API server.
|
||||
# PROXY=
|
||||
|
||||
# Change this to your MongoDB URI if different. I recommend appending chatgpt-clone.
|
||||
MONGO_URI=mongodb://127.0.0.1:27017/chatgpt-clone
|
||||
# Change this to your MongoDB URI if different. I recommend appending LibreChat.
|
||||
MONGO_URI=mongodb://127.0.0.1:27017/LibreChat
|
||||
|
||||
##########################
|
||||
# OpenAI Endpoint:
|
||||
##########################
|
||||
|
||||
# Access key from OpenAI platform.
|
||||
# Leave it blank to disable this feature.
|
||||
OPENAI_KEY=
|
||||
# Leave it blank to disable this feature.
|
||||
# Set to "user_provided" to allow the user to provide their API key from the UI.
|
||||
OPENAI_API_KEY=user_provided
|
||||
|
||||
# Identify the available models, separated by commas *without spaces*.
|
||||
# The first will be default.
|
||||
# Leave it blank to use internal settings.
|
||||
OPENAI_MODELS=gpt-3.5-turbo,gpt-3.5-turbo-0301,text-davinci-003,gpt-4
|
||||
OPENAI_MODELS=gpt-3.5-turbo,gpt-3.5-turbo-0301,text-davinci-003,gpt-4,gpt-4-0314
|
||||
|
||||
# Reverse proxy settings for OpenAI:
|
||||
# https://github.com/waylaidwanderer/node-chatgpt-api#using-a-reverse-proxy
|
||||
@@ -42,24 +42,26 @@ OPENAI_MODELS=gpt-3.5-turbo,gpt-3.5-turbo-0301,text-davinci-003,gpt-4
|
||||
|
||||
# To use Azure with this project, set the following variables. These will be used to build the API URL.
|
||||
# Chat completion:
|
||||
# `https://{AZURE_OPENAI_API_INSTANCE_NAME}.openai.azure.com/openai/deployments/{AZURE_OPENAI_API_DEPLOYMENT_NAME}/chat/completions?api-version={AZURE_OPENAI_API_VERSION}`;
|
||||
# `https://{AZURE_OPENAI_API_INSTANCE_NAME}.openai.azure.com/openai/deployments/{AZURE_OPENAI_API_DEPLOYMENT_NAME}/chat/completions?api-version={AZURE_OPENAI_API_VERSION}`;
|
||||
# You should also consider changing the `OPENAI_MODELS` variable above to the models available in your instance/deployment.
|
||||
# Note: I've noticed that the Azure API is much faster than the OpenAI API, so the streaming looks almost instantaneous.
|
||||
# Note "AZURE_OPENAI_API_COMPLETIONS_DEPLOYMENT_NAME" and "AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME" are optional but might be used in the future
|
||||
|
||||
# AZURE_OPENAI_API_KEY=
|
||||
# AZURE_OPENAI_API_INSTANCE_NAME=
|
||||
# AZURE_OPENAI_API_DEPLOYMENT_NAME=
|
||||
# AZURE_OPENAI_API_VERSION=
|
||||
# AZURE_OPENAI_API_COMPLETIONS_DEPLOYMENT_NAME= # Optional, but may be used in future updates
|
||||
# AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME= # Optional, but may be used in future updates
|
||||
# AZURE_OPENAI_API_COMPLETIONS_DEPLOYMENT_NAME=
|
||||
# AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME=
|
||||
|
||||
##########################
|
||||
# BingAI Endpoint:
|
||||
##########################
|
||||
|
||||
# Also used for Sydney and jailbreak
|
||||
|
||||
# BingAI Tokens: the "_U" cookies value from bing.com
|
||||
# To get your Access token for Bing, login to https://www.bing.com
|
||||
# Use dev tools or an extension while logged into the site to copy the content of the _U cookie.
|
||||
#If this fails, follow these instructions https://github.com/danny-avila/LibreChat/issues/370#issuecomment-1560382302 to provide the full cookie strings.
|
||||
# Set to "user_provided" to allow the user to provide its token from the UI.
|
||||
# Leave it blank to disable this endpoint.
|
||||
BINGAI_TOKEN="user_provided"
|
||||
@@ -82,12 +84,56 @@ CHATGPT_TOKEN="user_provided"
|
||||
|
||||
# Identify the available models, separated by commas. The first will be default.
|
||||
# Leave it blank to use internal settings.
|
||||
CHATGPT_MODELS=text-davinci-002-render-sha,text-davinci-002-render-paid,gpt-4
|
||||
CHATGPT_MODELS=text-davinci-002-render-sha,gpt-4
|
||||
# NOTE: you can add gpt-4-plugins, gpt-4-code-interpreter, and gpt-4-browsing to the list above and use the models for these features;
|
||||
# however, the view/display portion of these features are not supported, but you can use the underlying models, which have higher token context
|
||||
# Also: text-davinci-002-render-paid is deprecated as of May 2023
|
||||
|
||||
# Reverse proxy settings for ChatGPT
|
||||
# https://github.com/waylaidwanderer/node-chatgpt-api#using-a-reverse-proxy
|
||||
# By default, the server will use the node-chatgpt-api recommended proxy (a third party server).
|
||||
# CHATGPT_REVERSE_PROXY=
|
||||
# Reverse proxy setting for OpenAI
|
||||
# https://github.com/waylaidwanderer/node-chatgpt-api#using-a-reverse-proxy
|
||||
# By default it will use the node-chatgpt-api recommended proxy, (it's a third party server)
|
||||
# CHATGPT_REVERSE_PROXY=<YOUR REVERSE PROXY>
|
||||
|
||||
#############################
|
||||
# Plugins:
|
||||
#############################
|
||||
|
||||
# For securely storing credentials, you need a fixed key and IV. You can set them here for prod and dev environments
|
||||
# If you don't set them, the app will crash on startup.
|
||||
# You need a 32-byte key (64 characters in hex) and 16-byte IV (32 characters in hex)
|
||||
# Use this replit to generate some quickly: https://replit.com/@daavila/crypto#index.js
|
||||
# Here are some examples (THESE ARE NOT SECURE!)
|
||||
CREDS_KEY=f34be427ebb29de8d88c107a71546019685ed8b241d8f2ed00c3df97ad2566f0
|
||||
CREDS_IV=e2341419ec3dd3d19b13a1a87fafcbfb
|
||||
|
||||
|
||||
# AI-Assisted Google Search
|
||||
# This bot supports searching google for answers to your questions with assistance from GPT!
|
||||
# See detailed instructions here: https://github.com/danny-avila/chatgpt-clone/blob/main/docs/features/plugins/google_search.md
|
||||
GOOGLE_API_KEY=
|
||||
GOOGLE_CSE_ID=
|
||||
|
||||
# StableDiffusion WebUI
|
||||
# This bot supports StableDiffusion WebUI, using it's API to generated requested images.
|
||||
SD_WEBUI_URL=http://0.0.0.0:7860
|
||||
|
||||
##########################
|
||||
# PaLM (Google) Endpoint:
|
||||
##########################
|
||||
|
||||
# Follow the instruction here to setup:
|
||||
# https://github.com/danny-avila/LibreChat/blob/main/docs/install/apis_and_tokens.md
|
||||
|
||||
PALM_KEY="user_provided"
|
||||
|
||||
# In case you need a reverse proxy for this endpoint:
|
||||
# GOOGLE_REVERSE_PROXY=
|
||||
|
||||
##########################
|
||||
# Proxy: To be Used by all endpoints
|
||||
##########################
|
||||
|
||||
PROXY=
|
||||
|
||||
##########################
|
||||
# Search:
|
||||
@@ -118,6 +164,10 @@ MEILI_MASTER_KEY=DrhYf7zENyR6AlUCKmnz0eYASOQdl6zxH7s7MKFSfFCt
|
||||
# User System:
|
||||
##########################
|
||||
|
||||
# JWT Secrets
|
||||
JWT_SECRET=secret
|
||||
JWT_REFRESH_SECRET=secret
|
||||
|
||||
# Google:
|
||||
# Add your Google Client ID and Secret here, you must register an app with Google Cloud to get these values
|
||||
# https://cloud.google.com/
|
||||
@@ -125,22 +175,32 @@ GOOGLE_CLIENT_ID=
|
||||
GOOGLE_CLIENT_SECRET=
|
||||
GOOGLE_CALLBACK_URL=/oauth/google/callback
|
||||
|
||||
#JWT:
|
||||
JWT_SECRET_DEV=secret
|
||||
|
||||
# Add a secure secret for production if deploying to live domain.
|
||||
JWT_SECRET_PROD=secret
|
||||
|
||||
# Set the expiration delay for the secure cookie with the JWT token
|
||||
# Delay is in millisecond e.g. 7 days is 1000*60*60*24*7
|
||||
SESSION_EXPIRY=1000 * 60 * 60 * 24 * 7
|
||||
SESSION_EXPIRY=(1000 * 60 * 60 * 24) * 7
|
||||
|
||||
# Site URLs:
|
||||
# Don't forget to set Node env to development in the Server configuration section above
|
||||
# if you want to run in dev mode
|
||||
CLIENT_URL_DEV=http://localhost:3090
|
||||
SERVER_URL_DEV=http://localhost:3080
|
||||
###########################
|
||||
# Application Domains
|
||||
###########################
|
||||
|
||||
# Change these values to domain if deploying:
|
||||
CLIENT_URL_PROD=http://localhost:3080
|
||||
SERVER_URL_PROD=http://localhost:3080
|
||||
# Note: server = backend, client = public (the client is the url you visit)
|
||||
# For the google login to work in dev mode, you will likely need to change DOMAIN_SERVER to localhost:3090 or place it in .env.development
|
||||
|
||||
DOMAIN_CLIENT=http://localhost:3080
|
||||
DOMAIN_SERVER=http://localhost:3080
|
||||
|
||||
###########################
|
||||
# Frontend Configuration (Vite):
|
||||
###########################
|
||||
|
||||
# Custom app name, this text will be displayed in the landing page and the footer.
|
||||
VITE_APP_TITLE="LibreChat"
|
||||
|
||||
# Enable Social Login
|
||||
# This enables/disables the Login with Google button on the login page.
|
||||
# Set to true if you have registered the app with google cloud services
|
||||
# and have set the GOOGLE_CLIENT_ID and GOOGLE_CLIENT_SECRET in the /api/.env file
|
||||
VITE_SHOW_GOOGLE_LOGIN_OPTION=false
|
||||
|
||||
# Allow Public Registration
|
||||
ALLOW_REGISTRATION=true
|
||||
115
.eslintrc.js
Normal file
115
.eslintrc.js
Normal file
@@ -0,0 +1,115 @@
|
||||
module.exports = {
|
||||
env: {
|
||||
browser: true,
|
||||
es2021: true,
|
||||
node: true,
|
||||
commonjs: true,
|
||||
es6: true
|
||||
},
|
||||
extends: [
|
||||
'eslint:recommended',
|
||||
'plugin:react/recommended',
|
||||
'plugin:react-hooks/recommended',
|
||||
"plugin:jest/recommended",
|
||||
'prettier'
|
||||
],
|
||||
parser: '@typescript-eslint/parser',
|
||||
parserOptions: {
|
||||
ecmaVersion: 'latest',
|
||||
sourceType: 'module',
|
||||
ecmaFeatures: {
|
||||
jsx: true
|
||||
}
|
||||
},
|
||||
plugins: ['react', 'react-hooks', '@typescript-eslint'],
|
||||
rules: {
|
||||
'react/react-in-jsx-scope': 'off',
|
||||
'@typescript-eslint/ban-ts-comment': ['error', { 'ts-ignore': 'allow-with-description' }],
|
||||
indent: ['error', 2, { SwitchCase: 1 }],
|
||||
'max-len': [
|
||||
'error',
|
||||
{
|
||||
code: 150,
|
||||
ignoreStrings: true,
|
||||
ignoreTemplateLiterals: true,
|
||||
ignoreComments: true
|
||||
}
|
||||
],
|
||||
'linebreak-style': 0,
|
||||
// "arrow-parens": [2, "as-needed", { requireForBlockBody: true }],
|
||||
// 'no-plusplus': ['error', { allowForLoopAfterthoughts: true }],
|
||||
'no-console': 'off',
|
||||
'import/extensions': 'off',
|
||||
'no-use-before-define': [
|
||||
'error',
|
||||
{
|
||||
functions: false
|
||||
}
|
||||
],
|
||||
'no-promise-executor-return': 'off',
|
||||
'no-param-reassign': 'off',
|
||||
'no-continue': 'off',
|
||||
'no-restricted-syntax': 'off',
|
||||
'react/prop-types': ['off'],
|
||||
'react/display-name': ['off']
|
||||
},
|
||||
overrides: [
|
||||
{
|
||||
files: ['**/*.ts', '**/*.tsx'],
|
||||
rules: {
|
||||
'no-unused-vars': 'off', // off because it conflicts with '@typescript-eslint/no-unused-vars'
|
||||
'react/display-name': 'off',
|
||||
'@typescript-eslint/no-unused-vars': 'warn'
|
||||
}
|
||||
},
|
||||
{
|
||||
files: ['rollup.config.js', '.eslintrc.js', 'jest.config.js'],
|
||||
env: {
|
||||
node: true,
|
||||
}
|
||||
},
|
||||
{
|
||||
files: [
|
||||
'**/*.test.js',
|
||||
'**/*.test.jsx',
|
||||
'**/*.test.ts',
|
||||
'**/*.test.tsx',
|
||||
'**/*.spec.js',
|
||||
'**/*.spec.jsx',
|
||||
'**/*.spec.ts',
|
||||
'**/*.spec.tsx',
|
||||
'setupTests.js'
|
||||
],
|
||||
env: {
|
||||
jest: true,
|
||||
node: true
|
||||
},
|
||||
rules: {
|
||||
'react/display-name': 'off',
|
||||
'react/prop-types': 'off',
|
||||
'react/no-unescaped-entities': 'off'
|
||||
}
|
||||
},
|
||||
{
|
||||
files: '**/*.+(ts)',
|
||||
parser: '@typescript-eslint/parser',
|
||||
parserOptions: {
|
||||
project: './client/tsconfig.json'
|
||||
},
|
||||
plugins: ['@typescript-eslint/eslint-plugin', 'jest'],
|
||||
extends: [
|
||||
'plugin:@typescript-eslint/eslint-recommended',
|
||||
'plugin:@typescript-eslint/recommended'
|
||||
]
|
||||
}
|
||||
],
|
||||
settings: {
|
||||
react: {
|
||||
createClass: 'createReactClass', // Regex for Component Factory to use,
|
||||
// default to "createReactClass"
|
||||
pragma: 'React', // Pragma to use, default to "React"
|
||||
fragment: 'Fragment', // Fragment to use (may be a property of <pragma>), default to "Fragment"
|
||||
version: 'detect' // React version. "detect" automatically picks the version you have installed.
|
||||
}
|
||||
}
|
||||
};
|
||||
64
.github/ISSUE_TEMPLATE/BUG-REPORT.yml
vendored
Normal file
64
.github/ISSUE_TEMPLATE/BUG-REPORT.yml
vendored
Normal file
@@ -0,0 +1,64 @@
|
||||
name: Bug Report
|
||||
description: File a bug report
|
||||
title: "[Bug]: "
|
||||
labels: ["bug"]
|
||||
body:
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
Thanks for taking the time to fill out this bug report!
|
||||
- type: input
|
||||
id: contact
|
||||
attributes:
|
||||
label: Contact Details
|
||||
description: How can we get in touch with you if we need more info?
|
||||
placeholder: ex. email@example.com
|
||||
validations:
|
||||
required: false
|
||||
- type: textarea
|
||||
id: what-happened
|
||||
attributes:
|
||||
label: What happened?
|
||||
description: Also tell us, what did you expect to happen?
|
||||
placeholder: Please give as many details as possible
|
||||
validations:
|
||||
required: true
|
||||
- type: textarea
|
||||
id: steps-to-reproduce
|
||||
attributes:
|
||||
label: Steps to Reproduce
|
||||
description: Please list the steps needed to reproduce the issue.
|
||||
placeholder: "1. Step 1\n2. Step 2\n3. Step 3"
|
||||
validations:
|
||||
required: true
|
||||
- type: dropdown
|
||||
id: browsers
|
||||
attributes:
|
||||
label: What browsers are you seeing the problem on?
|
||||
multiple: true
|
||||
options:
|
||||
- Firefox
|
||||
- Chrome
|
||||
- Safari
|
||||
- Microsoft Edge
|
||||
- Mobile (iOS)
|
||||
- Mobile (Android)
|
||||
- type: textarea
|
||||
id: logs
|
||||
attributes:
|
||||
label: Relevant log output
|
||||
description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
|
||||
render: shell
|
||||
- type: textarea
|
||||
id: screenshots
|
||||
attributes:
|
||||
label: Screenshots
|
||||
description: If applicable, add screenshots to help explain your problem. You can drag and drop, paste images directly here or link to them.
|
||||
- type: checkboxes
|
||||
id: terms
|
||||
attributes:
|
||||
label: Code of Conduct
|
||||
description: By submitting this issue, you agree to follow our [Code of Conduct](https://github.com/danny-avila/chatgpt-clone/blob/main/documents/contributions/code_of_conduct.md)
|
||||
options:
|
||||
- label: I agree to follow this project's Code of Conduct
|
||||
required: true
|
||||
57
.github/ISSUE_TEMPLATE/FEATURE-REQUEST.yml
vendored
Normal file
57
.github/ISSUE_TEMPLATE/FEATURE-REQUEST.yml
vendored
Normal file
@@ -0,0 +1,57 @@
|
||||
name: Feature Request
|
||||
description: File a feature request
|
||||
title: "Enhancement: "
|
||||
labels: ["enhancement"]
|
||||
body:
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
Thank you for taking the time to fill this out!
|
||||
- type: input
|
||||
id: contact
|
||||
attributes:
|
||||
label: Contact Details
|
||||
description: How can we contact you if we need more information?
|
||||
placeholder: ex. email@example.com
|
||||
validations:
|
||||
required: false
|
||||
- type: textarea
|
||||
id: what
|
||||
attributes:
|
||||
label: What features would you like to see added?
|
||||
description: Please provide as many details as possible.
|
||||
placeholder: Please provide as many details as possible.
|
||||
validations:
|
||||
required: true
|
||||
- type: textarea
|
||||
id: details
|
||||
attributes:
|
||||
label: More details
|
||||
description: Please provide additional details if needed.
|
||||
placeholder: Please provide additional details if needed.
|
||||
validations:
|
||||
required: true
|
||||
- type: dropdown
|
||||
id: subject
|
||||
attributes:
|
||||
label: Which components are impacted by your request?
|
||||
multiple: true
|
||||
options:
|
||||
- General
|
||||
- UI
|
||||
- Endpoints
|
||||
- Plugins
|
||||
- Other
|
||||
- type: textarea
|
||||
id: screenshots
|
||||
attributes:
|
||||
label: Pictures
|
||||
description: If relevant, please include images to help clarify your request. You can drag and drop images directly here, paste them, or provide a link to them.
|
||||
- type: checkboxes
|
||||
id: terms
|
||||
attributes:
|
||||
label: Code of Conduct
|
||||
description: By submitting this issue, you agree to follow our [Code of Conduct](https://github.com/danny-avila/chatgpt-clone/blob/main/documents/contributions/code_of_conduct.md)
|
||||
options:
|
||||
- label: I agree to follow this project's Code of Conduct
|
||||
required: true
|
||||
58
.github/ISSUE_TEMPLATE/QUESTION.yml
vendored
Normal file
58
.github/ISSUE_TEMPLATE/QUESTION.yml
vendored
Normal file
@@ -0,0 +1,58 @@
|
||||
name: Question
|
||||
description: Ask your question
|
||||
title: "[Question]: "
|
||||
labels: ["question"]
|
||||
body:
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
Thanks for taking the time to fill this!
|
||||
- type: input
|
||||
id: contact
|
||||
attributes:
|
||||
label: Contact Details
|
||||
description: How can we get in touch with you if we need more info?
|
||||
placeholder: ex. email@example.com
|
||||
validations:
|
||||
required: false
|
||||
- type: textarea
|
||||
id: what-is-your-question
|
||||
attributes:
|
||||
label: What is your question?
|
||||
description: Please give as many details as possible
|
||||
placeholder: Please give as many details as possible
|
||||
validations:
|
||||
required: true
|
||||
- type: textarea
|
||||
id: more-details
|
||||
attributes:
|
||||
label: More Details
|
||||
description: Please provide more details if needed.
|
||||
placeholder: Please provide more details if needed.
|
||||
validations:
|
||||
required: true
|
||||
- type: dropdown
|
||||
id: browsers
|
||||
attributes:
|
||||
label: What is the main subject of your question?
|
||||
multiple: true
|
||||
options:
|
||||
- Documentation
|
||||
- Installation
|
||||
- UI
|
||||
- Endpoints
|
||||
- User System/OAuth
|
||||
- Other
|
||||
- type: textarea
|
||||
id: screenshots
|
||||
attributes:
|
||||
label: Screenshots
|
||||
description: If applicable, add screenshots to help explain your problem. You can drag and drop, paste images directly here or link to them.
|
||||
- type: checkboxes
|
||||
id: terms
|
||||
attributes:
|
||||
label: Code of Conduct
|
||||
description: By submitting this issue, you agree to follow our [Code of Conduct](https://github.com/danny-avila/chatgpt-clone/blob/main/documents/contributions/code_of_conduct.md)
|
||||
options:
|
||||
- label: I agree to follow this project's Code of Conduct
|
||||
required: true
|
||||
47
.github/dependabot.yml
vendored
Normal file
47
.github/dependabot.yml
vendored
Normal file
@@ -0,0 +1,47 @@
|
||||
# To get started with Dependabot version updates, you'll need to specify which
|
||||
# package ecosystems to update and where the package manifests are located.
|
||||
# Please see the documentation for all configuration options:
|
||||
# https://docs.github.com/github/administering-a-repository/configuration-options-for-dependency-updates
|
||||
|
||||
version: 2
|
||||
updates:
|
||||
- package-ecosystem: "npm" # See documentation for possible values
|
||||
directory: "/api" # Location of package manifests
|
||||
target-branch: "develop"
|
||||
versioning-strategy: increase-if-necessary
|
||||
schedule:
|
||||
interval: "weekly"
|
||||
allow:
|
||||
# Allow both direct and indirect updates for all packages
|
||||
- dependency-type: "all"
|
||||
commit-message:
|
||||
prefix: "npm api prod"
|
||||
prefix-development: "npm api dev"
|
||||
include: "scope"
|
||||
- package-ecosystem: "npm" # See documentation for possible values
|
||||
directory: "/client" # Location of package manifests
|
||||
target-branch: "develop"
|
||||
versioning-strategy: increase-if-necessary
|
||||
schedule:
|
||||
interval: "weekly"
|
||||
allow:
|
||||
# Allow both direct and indirect updates for all packages
|
||||
- dependency-type: "all"
|
||||
commit-message:
|
||||
prefix: "npm client prod"
|
||||
prefix-development: "npm client dev"
|
||||
include: "scope"
|
||||
- package-ecosystem: "npm" # See documentation for possible values
|
||||
directory: "/" # Location of package manifests
|
||||
target-branch: "develop"
|
||||
versioning-strategy: increase-if-necessary
|
||||
schedule:
|
||||
interval: "weekly"
|
||||
allow:
|
||||
# Allow both direct and indirect updates for all packages
|
||||
- dependency-type: "all"
|
||||
commit-message:
|
||||
prefix: "npm all prod"
|
||||
prefix-development: "npm all dev"
|
||||
include: "scope"
|
||||
|
||||
2
.github/playwright.yml
vendored
2
.github/playwright.yml
vendored
@@ -13,7 +13,7 @@ jobs:
|
||||
BINGAI_TOKEN: ${{ secrets.BINGAI_TOKEN }}
|
||||
CHATGPT_TOKEN: ${{ secrets.CHATGPT_TOKEN }}
|
||||
MONGO_URI: ${{ secrets.MONGO_URI }}
|
||||
OPENAI_KEY: ${{ secrets.OPENAI_KEY }}
|
||||
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/setup-node@v3
|
||||
|
||||
@@ -1,40 +1,35 @@
|
||||
Please include a summary of the changes and the related issue. Please also include relevant motivation and context. List any dependencies that are required for this change.
|
||||
|
||||
Fixes # (issue)
|
||||
|
||||
## Type of change
|
||||
|
||||
Please delete options that are not relevant.
|
||||
|
||||
- [ ] Bug fix (non-breaking change which fixes an issue)
|
||||
- [ ] New feature (non-breaking change which adds functionality)
|
||||
- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
|
||||
- [ ] This change requires a documentation update
|
||||
|
||||
# How Has This Been Tested?
|
||||
|
||||
Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce. Please also list any relevant details for your test configuration
|
||||
|
||||
- [ ] Test A
|
||||
- [ ] Test B
|
||||
|
||||
**Test Configuration**:
|
||||
* Firmware version:
|
||||
* Hardware:
|
||||
* Toolchain:
|
||||
* SDK:
|
||||
|
||||
# Checklist:
|
||||
|
||||
- [ ] My code follows the style guidelines of this project
|
||||
- [ ] I have performed a self-review of my code
|
||||
- [ ] I have commented my code, particularly in hard-to-understand areas
|
||||
- [ ] I have made corresponding changes to the documentation
|
||||
- [ ] My changes generate no new warnings
|
||||
- [ ] I have added tests that prove my fix is effective or that my feature works
|
||||
- [ ] New and existing unit tests pass locally with my changes
|
||||
- [ ] Any dependent changes have been merged and published in downstream modules
|
||||
|
||||
##
|
||||
|
||||
## [Go Back to ReadMe](../../README.md)
|
||||
Please include a summary of the changes and the related issue. Please also include relevant motivation and context. List any dependencies that are required for this change.
|
||||
|
||||
|
||||
|
||||
## Type of change
|
||||
|
||||
Please delete options that are not relevant.
|
||||
|
||||
- [ ] Bug fix (non-breaking change which fixes an issue)
|
||||
- [ ] New feature (non-breaking change which adds functionality)
|
||||
- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
|
||||
- [ ] This change requires a documentation update
|
||||
- [ ] Documentation update
|
||||
|
||||
|
||||
## How Has This Been Tested?
|
||||
|
||||
Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce. Please also list any relevant details for your test configuration:
|
||||
##
|
||||
|
||||
|
||||
### **Test Configuration**:
|
||||
##
|
||||
|
||||
|
||||
## Checklist:
|
||||
|
||||
- [ ] My code follows the style guidelines of this project
|
||||
- [ ] I have performed a self-review of my code
|
||||
- [ ] I have commented my code, particularly in hard-to-understand areas
|
||||
- [ ] I have made corresponding changes to the documentation
|
||||
- [ ] My changes generate no new warnings
|
||||
- [ ] I have added tests that prove my fix is effective or that my feature works
|
||||
- [ ] New and existing unit tests pass locally with my changes
|
||||
- [ ] Any dependent changes have been merged and published in downstream modules
|
||||
8
.gitignore
vendored
8
.gitignore
vendored
@@ -26,6 +26,7 @@ dist/
|
||||
public/main.js
|
||||
public/main.js.map
|
||||
public/main.js.LICENSE.txt
|
||||
client/public/images/
|
||||
client/public/main.js
|
||||
client/public/main.js.map
|
||||
client/public/main.js.LICENSE.txt
|
||||
@@ -48,6 +49,9 @@ bower_components/
|
||||
# Environment
|
||||
.npmrc
|
||||
.env
|
||||
!.env.example
|
||||
!.env.test.example
|
||||
.env*
|
||||
cache.json
|
||||
api/data/
|
||||
owner.yml
|
||||
@@ -59,8 +63,10 @@ src/style - official.css
|
||||
/playwright/.cache/
|
||||
.DS_Store
|
||||
*.code-workspace
|
||||
.idea
|
||||
junit.xml
|
||||
|
||||
# meilisearch
|
||||
meilisearch
|
||||
data.ms/*
|
||||
|
||||
auth.json
|
||||
|
||||
5
.husky/pre-commit
Executable file
5
.husky/pre-commit
Executable file
@@ -0,0 +1,5 @@
|
||||
#!/usr/bin/env sh
|
||||
. "$(dirname -- "$0")/_/husky.sh"
|
||||
|
||||
npx lint-staged
|
||||
|
||||
19
.prettierrc.js
Normal file
19
.prettierrc.js
Normal file
@@ -0,0 +1,19 @@
|
||||
module.exports = {
|
||||
printWidth: 100,
|
||||
useTabs: false,
|
||||
tabWidth: 2,
|
||||
semi: true,
|
||||
singleQuote: true,
|
||||
// bracketSpacing: false,
|
||||
trailingComma: 'none',
|
||||
arrowParens: 'always',
|
||||
embeddedLanguageFormatting: 'auto',
|
||||
insertPragma: false,
|
||||
proseWrap: 'preserve',
|
||||
quoteProps: 'as-needed',
|
||||
requirePragma: false,
|
||||
rangeStart: 0,
|
||||
endOfLine: 'auto',
|
||||
jsxBracketSameLine: false,
|
||||
jsxSingleQuote: false,
|
||||
};
|
||||
83
CHANGELOG.md
83
CHANGELOG.md
@@ -1,83 +0,0 @@
|
||||
# # Changelog
|
||||
<details open>
|
||||
<summary><strong>2023-05-11</strong></summary>
|
||||
|
||||
**Released [v0.4.2](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.4.2)**
|
||||
|
||||
ChatGPT-Clone received some important upgrades and improvements. A new contributor, [@qcgm1978](https://github.com/qcgm1978), makes their first contribution by adding a null check for adaptiveCards variable. Additionally, support for titling conversations with the Azure endpoint is added by [@danny-avila](https://github.com/danny-avila) in PR [#234](https://github.com/danny-avila/chatgpt-clone/pull/234). In PR [#235](https://github.com/danny-avila/chatgpt-clone/pull/235), [@danny-avila](https://github.com/danny-avila) also makes some necessary fixes to titling, quotation marks, and endpoints being unavailable with only the Azure key provided. The logging system is now powered by Pino and sanitization, thanks to [@danorlando](https://github.com/danorlando) in PR [#227](https://github.com/danny-avila/chatgpt-clone/pull/227). To bulletproof the Docker container, the .dockerignore file is updated to include the client/.env file by [@danny-avila](https://github.com/danny-avila) in PR [#241](https://github.com/danny-avila/chatgpt-clone/pull/241). This issue was brought to our attention on discord.
|
||||
|
||||
There is active work on the new Plugins feature, converting the frontend to Typescript, and looking to integrate Palm2, google's new generative AI accessible via API, to the project as a new endpoint.
|
||||
|
||||
You can check the full changelog in between [v0.4.1](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.4.1) and [v0.4.2](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.4.2) [here](https://github.com/danny-avila/chatgpt-clone/compare/v0.4.1...v0.4.2)."
|
||||
|
||||
For discussion and suggestion you can join us: **[community discord server](https://discord.gg/NGaa9RPCft)**
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary><strong>2023-05-09</strong></summary>
|
||||
|
||||
**Released [v0.4.1](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.4.1)**
|
||||
|
||||
* update user system section of readme by @danorlando in #207
|
||||
* remove github-passport and update package.lock files by @danorlando in #208
|
||||
* Update README.md by @fuegovic in #209
|
||||
* fix: fix browser refresh redirecting to /chat/new by @danorlando in #210
|
||||
* fix: fix issue with validation when google account has multiple spaces in username by @danorlando in #211
|
||||
* chore: update docker image version to use latest by @danny-avila in #218
|
||||
* update documentation structure by @fuegovic in #220
|
||||
* Feat: Add Azure support by @danny-avila in #219
|
||||
* Update Message.js by @DavidDev1334 in #191
|
||||
|
||||
⚠️ **IMPORTANT :** Since V0.4.0 You should register and login with a local account (email and password) for the first time sign-up. if you use login for the first time with a social login account (eg. Google, facebook, etc.), the conversations and presets that you created before the user system was implemented will NOT be migrated to that account.
|
||||
|
||||
⚠️ **Breaking - new Env Variables :** Since V0.4.0 You will need to add the new env variables from .env.example for the app to work, even if you're not using multiple users for your purposes.
|
||||
|
||||
For discussion and suggestion you can join us: **[community discord server](https://discord.gg/NGaa9RPCft)**
|
||||
</details>
|
||||
<details>
|
||||
<summary><strong>2023-05-07</strong></summary>
|
||||
|
||||
**Released [v0.4.0](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.4.0)**, Introducing User/Auth System and OAuth2/Social Login! You can now register and login with an email account or use Google login. Your your previous conversations and presets will migrate to your new profile upon creation. Check out the details in the [User/Auth System](#userauth-system) section of the README.md.
|
||||
|
||||
⚠️ **IMPORTANT :** You should register and login with a local account (email and password) for the first time sign-up. if you use login for the first time with a social login account (eg. Google, facebook, etc.), the conversations and presets that you created before the user system was implemented will NOT be migrated to that account.
|
||||
|
||||
⚠️ **Breaking - new Env Variables :** You will need to add the new env variables from .env.example for the app to work, even if you're not using multiple users for your purposes.
|
||||
|
||||
For discussion and suggestion you can join us: **[community discord server](https://discord.gg/NGaa9RPCft)**
|
||||
</details>
|
||||
|
||||
|
||||
<details>
|
||||
<summary><strong>2023-04-05</strong></summary>
|
||||
|
||||
**Released [v0.3.0](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.3.0)**, Introducing more customization for both OpenAI & BingAI conversations! This is one of the biggest updates yet and will make integrating future LLM's a lot easier, providing a lot of customization features as well, including sharing presets! Please feel free to share them in the **[community discord server](https://discord.gg/NGaa9RPCft)**
|
||||
</details>
|
||||
|
||||
|
||||
<details>
|
||||
<summary><strong>2023-03-23</strong></summary>
|
||||
|
||||
**Released [v0.1.0](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.1.0)**, **searching messages/conversations is live!** Up next is more custom parameters for customGpt's. Join the discord server for more immediate assistance and update: **[community discord server](https://discord.gg/NGaa9RPCft)**
|
||||
</details>
|
||||
|
||||
|
||||
<details>
|
||||
<summary><strong>2023-03-22</strong></summary>
|
||||
|
||||
**Released [v0.0.6](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.0.6)**, the latest stable release before **Searching messages** goes live tomorrow. See exact updates to date in the tag link. By request, there is now also a **[community discord server](https://s
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary><strong>2023-03-20</strong></summary>
|
||||
|
||||
**Searching messages** is almost here as I test more of its functionality. There've been a lot of great features requested and great contributions and I will work on some soon, namely, further customizing the custom gpt params with sliders similar to the OpenAI playground, and including the custom params and system messages available to Bing.
|
||||
|
||||
The above features are next and then I will have to focus on building the **test environment.** I would **greatly appreciate** help in this area with any test environment you're familiar with (mocha, chai, jest, playwright, puppeteer). This is to aid in the velocity of contributing and to save time I spend debugging.
|
||||
|
||||
On that note, I had to switch the default branch due to some breaking changes that haven't been straight forward to debug, mainly related to node-chat-gpt the main dependency of the project. Thankfully, my working branch, now switched to default as main, is working as expected.
|
||||
</details>
|
||||
|
||||
|
||||
##
|
||||
|
||||
## [Go Back to ReadMe](README.md)
|
||||
@@ -59,8 +59,8 @@ representative at an online or offline event.
|
||||
## Enforcement
|
||||
|
||||
Instances of abusive, harassing, or otherwise unacceptable behavior may be
|
||||
reported to the community leaders responsible for enforcement at
|
||||
https://t.me/proffapt.
|
||||
reported to the community leaders responsible for enforcement here on GitHub or
|
||||
on the official [Discord Server](https://discord.gg/uDyZ5Tzhct).
|
||||
All complaints will be reviewed and investigated promptly and fairly.
|
||||
|
||||
All community leaders are obligated to respect the privacy and security of the
|
||||
@@ -129,4 +129,4 @@ https://www.contributor-covenant.org/translations.
|
||||
|
||||
##
|
||||
|
||||
## [Go Back to ReadMe](../../README.md)
|
||||
## [Go Back to ReadMe](README.md)
|
||||
@@ -5,11 +5,19 @@ such as bug reports, documentation improvements, feature requests, and code cont
|
||||
|
||||
## Contributing Guidelines
|
||||
|
||||
When contributing to this repository, please first discuss the change you wish to make via [issue](https://github.com/danny-avila/chatgpt-clone/issues) or
|
||||
join our discord [Discord community](https://discord.gg/NGaa9RPCft).
|
||||
If the feature you would like to contribute has not already received prior approval from the project maintainers (ie. the feature is currently on the roadmap or on the [trello board]()), please submit a proposal in the [proposals category](https://github.com/danny-avila/chatgpt-clone/discussions/categories/proposals) of the discussions board before beginning work on it.
|
||||
- Proposals should include specific implementation details including areas of the application that will be effected by the change inlcuding designs if applicable, and any other relevant information that might be required for a speedy review.
|
||||
- Proposals are not required for small changes, bug fixes, or documentation improvements.
|
||||
- Small changes and bug fixes should be tied to an [issue](https://github.com/danny-avila/chatgpt-clone/issues) and included in the corresponding pull request for tracking purposes.
|
||||
|
||||
*Please note that a pull request involving a feature that has not been reviewed and approved by the project maintainers may be rejected.*
|
||||
|
||||
If you would like to discuss the changes you wish to make, join our [Discord community](https://discord.gg/uDyZ5Tzhct).
|
||||
|
||||
## Our Standards
|
||||
|
||||
Please read our [Coding Standards and Conventions](docs/contributions/coding_conventions.md) before beginning on a contribution.
|
||||
|
||||
Examples of behavior that contributes to creating a positive environment
|
||||
include:
|
||||
|
||||
@@ -172,6 +180,6 @@ Apply the following naming conventions to branches, labels, and other Git-relate
|
||||
|
||||
##
|
||||
|
||||
## [Go Back to ReadMe](../../README.md)
|
||||
## [Go Back to ReadMe](README.md)
|
||||
|
||||
|
||||
@@ -1,26 +0,0 @@
|
||||
# Contributors List
|
||||
|
||||
We appreciate all the contributors who helped make this project possible:
|
||||
|
||||
- danny-avila (Admin)
|
||||
- wtlyu (Contributor)
|
||||
- danorlando (Contributor)
|
||||
- alfredo-f (Contributor)
|
||||
- HyunggyuJang (Contributor)
|
||||
- fuegovic (Contributor)
|
||||
- DavidDev1334
|
||||
- toordog (Contributor)
|
||||
- heathriel (External Contributor)
|
||||
- hackreactor-bot (Contributor)
|
||||
- git-bruh (Contributor)
|
||||
- zhangsean (Contributor)
|
||||
- llk89 (Contributor)
|
||||
- adamrb (Contributor)
|
||||
|
||||
|
||||
|
||||
If you have contributed to this project and would like to be added to the list of contributors, please submit a pull request updating this file with your name and GitHub username.
|
||||
|
||||
##
|
||||
|
||||
## [Go Back to ReadMe](README.md)
|
||||
56
Dockerfile
56
Dockerfile
@@ -1,38 +1,30 @@
|
||||
FROM node:19-alpine AS react-client
|
||||
WORKDIR /client
|
||||
# copy package.json into the container at /client
|
||||
COPY /client/.env /client/.env
|
||||
COPY /client/package*.json /client/
|
||||
# install dependencies
|
||||
# Base node image
|
||||
FROM node:19-alpine AS node
|
||||
COPY . /app
|
||||
# Install dependencies
|
||||
WORKDIR /app
|
||||
RUN npm ci
|
||||
# Copy the current directory contents into the container at /client
|
||||
COPY /client/ /client/
|
||||
# Set the memory limit for Node.js
|
||||
ENV NODE_OPTIONS="--max-old-space-size=2048"
|
||||
# Build artifacts
|
||||
RUN npm run build
|
||||
|
||||
FROM node:19-alpine AS node-api
|
||||
WORKDIR /api
|
||||
# copy package.json into the container at /api
|
||||
COPY /api/package*.json /api/
|
||||
# install dependencies
|
||||
RUN npm ci
|
||||
# Copy the current directory contents into the container at /api
|
||||
COPY /api/ /api/
|
||||
# Copy the client side code
|
||||
COPY --from=react-client /client/dist /client/dist
|
||||
# Make port 3080 available to the world outside this container
|
||||
# Frontend variables as build args
|
||||
ARG VITE_APP_TITLE
|
||||
ARG VITE_SHOW_GOOGLE_LOGIN_OPTION
|
||||
|
||||
# You will need to add your VITE variables to the docker-compose file
|
||||
ENV VITE_APP_TITLE=$VITE_APP_TITLE
|
||||
ENV VITE_SHOW_GOOGLE_LOGIN_OPTION=$VITE_SHOW_GOOGLE_LOGIN_OPTION
|
||||
|
||||
# React client build
|
||||
ENV NODE_OPTIONS="--max-old-space-size=2048"
|
||||
RUN npm run frontend
|
||||
|
||||
# Node API setup
|
||||
EXPOSE 3080
|
||||
# Expose the server to 0.0.0.0
|
||||
ENV HOST=0.0.0.0
|
||||
# Run the app when the container launches
|
||||
CMD ["npm", "start"]
|
||||
CMD ["npm", "run", "backend"]
|
||||
|
||||
# Optional: for client with nginx routing
|
||||
FROM nginx:stable-alpine AS nginx-client
|
||||
WORKDIR /usr/share/nginx/html
|
||||
COPY --from=react-client /client/dist /usr/share/nginx/html
|
||||
# Add your nginx.conf
|
||||
COPY /client/nginx.conf /etc/nginx/conf.d/default.conf
|
||||
ENTRYPOINT ["nginx", "-g", "daemon off;"]
|
||||
# FROM nginx:stable-alpine AS nginx-client
|
||||
# WORKDIR /usr/share/nginx/html
|
||||
# COPY --from=node /app/client/dist /usr/share/nginx/html
|
||||
# COPY client/nginx.conf /etc/nginx/conf.d/default.conf
|
||||
# ENTRYPOINT ["nginx", "-g", "daemon off;"]
|
||||
|
||||
141
README.md
141
README.md
@@ -1,135 +1,152 @@
|
||||
|
||||
<p align="center">
|
||||
<a href="https://discord.gg/NGaa9RPCft">
|
||||
<picture>
|
||||
<source media="(prefers-color-scheme: dark)" srcset="https://user-images.githubusercontent.com/110412045/228325485-9d3e618f-a980-44fe-89e9-d6d39164680e.png">
|
||||
<img src="https://user-images.githubusercontent.com/110412045/228325485-9d3e618f-a980-44fe-89e9-d6d39164680e.png" height="128">
|
||||
</picture>
|
||||
<h1 align="center">ChatGPT Clone</h1>
|
||||
<h1 align="center">LibreChat</h1>
|
||||
</a>
|
||||
</p>
|
||||
|
||||
<p align="center">
|
||||
<a aria-label="Join the community on Discord" href="https://discord.gg/NGaa9RPCft">
|
||||
<img alt="" src="https://img.shields.io/badge/Join%20the%20community-blueviolet.svg?style=for-the-badge&logo=DISCORD&labelColor=000000&logoWidth=20">
|
||||
<a href="https://discord.gg/NGaa9RPCft">
|
||||
<img src="https://img.shields.io/discord/1086345563026489514?label=&logo=discord&style=for-the-badge&logoWidth=20&labelColor=000000&color=blueviolet">
|
||||
</a>
|
||||
<a aria-label="Sponsors" href="#sponsors">
|
||||
<img alt="" src="https://img.shields.io/badge/SPONSORS-brightgreen.svg?style=for-the-badge&labelColor=000000&logoWidth=20">
|
||||
</a>
|
||||
</p>
|
||||
|
||||
## All AI Conversations under One Roof. ##
|
||||
Assistant AIs are the future and OpenAI revolutionized this movement with ChatGPT. While numerous UIs exist, this app commemorates the original styling of ChatGPT, with the ability to integrate any current/future AI models, while integrating and improving upon original client features, such as conversation/message search and prompt templates (currently WIP). Through this clone, you can avoid ChatGPT Plus in favor of free or pay-per-call APIs. I will soon deploy a demo of this app. Feel free to contribute, clone, or fork. Currently dockerized.
|
||||
## All-In-One AI Conversations with LibreChat ##
|
||||
LibreChat brings together the future of assistant AIs with the revolutionary technology of OpenAI's ChatGPT. Celebrating the original styling, LibreChat gives you the ability to integrate multiple AI models. It also integrates and enhances original client features such as conversation and message search, prompt templates and plugins.
|
||||
|
||||
With LibreChat, you no longer need to opt for ChatGPT Plus and can instead use free or pay-per-call APIs. We welcome contributions, cloning, and forking to enhance the capabilities of this advanced chatbot platform.
|
||||
|
||||
|
||||
<!--  -->
|
||||
https://github.com/danny-avila/LibreChat/assets/110412045/c1eb0c0f-41f6-4335-b982-84b278b53d59
|
||||
|
||||
# Features
|
||||
|
||||
- Response streaming identical to ChatGPT through server-sent events
|
||||
- UI from original ChatGPT, including Dark mode
|
||||
- AI model selection (through 3 endpoints: OpenAI API, BingAI, and ChatGPT Browser)
|
||||
- Create, Save, & Share custom presets for OpenAI and BingAI endpoints - [More info on customization here](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.3.0)
|
||||
- Edit and Resubmit messages just like the official site (with conversation branching)
|
||||
- AI model selection (through 5 endpoints: OpenAI API, BingAI, ChatGPT Browser, PaLM2, Plugins)
|
||||
- Create, Save, & Share custom presets - [More info on prompt presets here](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.3.0)
|
||||
- Edit and Resubmit messages with conversation branching
|
||||
- Search all messages/conversations - [More info here](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.1.0)
|
||||
- Integrating plugins soon
|
||||
- Plugins now available (including web access, image generation and more)
|
||||
|
||||
##
|
||||
# Sponsors
|
||||
---
|
||||
# ⚠️ **Breaking Changes** ⚠️
|
||||
Note: These changes only apply to users who are updating from a previous version of the app.
|
||||
|
||||
Sponsored by <a href="https://github.com/DavidDev1334"><b>@DavidDev1334</b></a>, <a href="https://github.com/mjtechguy"><b>@mjtechguy</b></a>, <a href="https://github.com/Pharrcyde"><b>@Pharrcyde</b></a>, & <a href="https://github.com/fuegovic"><b>@fuegovic</b></a>
|
||||
- We have simplified the configuration process by using a single `.env` file in the root folder instead of separate `/api/.env` and `/client/.env` files.
|
||||
- If you had installed a previous version, you can run `npm run upgrade` to automatically copy the content of both files to the new `.env` file and backup the old ones in the root dir.
|
||||
- If you are installing the project for the first time, it's recommend you run the installation script `npm run install` to guide your local setup (otherwise continue to use docker)
|
||||
- The docker-compose file had some change. Review the [new docker instructions](docs\install\docker_install.md) to make sure you are setup properly. This is still the simplest and most effective method.
|
||||
- The upgrade script requires both `/api/.env` and `/client/.env` files to run properly. If you get an error about a missing client env file, just rename the `/client/.env.example` file to `/client/.env` and run the script again.
|
||||
- We have renamed the `OPENAI_KEY` variable to `OPENAI_API_KEY` to match the official documentation. The upgrade script should do this automatically for you, but please double-check that your key is correct in the new `.env` file.
|
||||
- After running the upgrade script, the `OPENAI_API_KEY` variable might be placed in a different section in the new `.env` file than before. This does not affect the functionality of the app, but if you want to keep it organized, you can look for it near the bottom of the file and move it to its usual section.
|
||||
|
||||
##
|
||||
|
||||
<details open>
|
||||
<summary><strong>2023-05-11</strong></summary>
|
||||
|
||||
**Released [v0.4.2](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.4.2)**
|
||||
|
||||
ChatGPT-Clone received some important upgrades and improvements. A new contributor, [@qcgm1978](https://github.com/qcgm1978), makes their first contribution by adding a null check for adaptiveCards variable. Additionally, support for titling conversations with the Azure endpoint is added by [@danny-avila](https://github.com/danny-avila) in PR [#234](https://github.com/danny-avila/chatgpt-clone/pull/234). In PR [#235](https://github.com/danny-avila/chatgpt-clone/pull/235), [@danny-avila](https://github.com/danny-avila) also makes some necessary fixes to titling, quotation marks, and endpoints being unavailable with only the Azure key provided. The logging system is now powered by Pino and sanitization, thanks to [@danorlando](https://github.com/danorlando) in PR [#227](https://github.com/danny-avila/chatgpt-clone/pull/227). To bulletproof the Docker container, the .dockerignore file is updated to include the client/.env file by [@danny-avila](https://github.com/danny-avila) in PR [#241](https://github.com/danny-avila/chatgpt-clone/pull/241). This issue was brought to our attention on discord.
|
||||
- For enhanced security, we are now asking for crypto keys for securely storing credentials in the `.env` file. Crypto keys are used to encrypt and decrypt sensitive data such as passwords and access keys. If you don't set them, the app will crash on startup.
|
||||
- You need to fill the following variables in the `.env` file with 32-byte (64 characters in hex) or 16-byte (32 characters in hex) values:
|
||||
- `CREDS_KEY` (32-byte)
|
||||
- `CREDS_IV` (16-byte)
|
||||
- `JWT_SECRET` (32-byte, optional but recommended)
|
||||
- You can use this replit to generate some crypto keys quickly: https://replit.com/@daavila/crypto#index.js
|
||||
- Make sure you keep your crypto keys safe and don't share them with anyone.
|
||||
|
||||
There is active work on the new Plugins feature, converting the frontend to Typescript, and looking to integrate Palm2, google's new generative AI accessible via API, to the project as a new endpoint.
|
||||
We apologize for any inconvenience caused by these changes. We hope you enjoy the new and improved version of our app!
|
||||
|
||||
You can check the full changelog in between [v0.4.1](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.4.1) and [v0.4.2](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.4.2) [here](https://github.com/danny-avila/chatgpt-clone/compare/v0.4.1...v0.4.2)."
|
||||
---
|
||||
|
||||
⚠️ **IMPORTANT :** Since V0.4.0 You should register and login with a local account (email and password) for the first time sign-up. if you use login for the first time with a social login account (eg. Google, facebook, etc.), the conversations and presets that you created before the user system was implemented will NOT be migrated to that account.
|
||||
## Changelog
|
||||
- Keep up with the latest updates by visiting the releases page - [Releases](https://github.com/danny-avila/LibreChat/releases)
|
||||
|
||||
⚠️ **Breaking - new Env Variables :** Since V0.4.0 You will need to add the new env variables from .env.example for the app to work, even if you're not using multiple users for your purposes.
|
||||
|
||||
For discussion and suggestion you can join us: **[community discord server](https://discord.gg/NGaa9RPCft)**
|
||||
</details>
|
||||
|
||||
[Past Updates](CHANGELOG.md)
|
||||
##
|
||||
---
|
||||
|
||||
<h1>Table of Contents</h1>
|
||||
|
||||
<details open>
|
||||
<summary><strong>Getting Started</strong></summary>
|
||||
|
||||
* [Docker Install](/documents/install/docker_install.md)
|
||||
* [Linux Install](documents/install/linux_install.md)
|
||||
* [Mac Install](documents/install/mac_install.md)
|
||||
* [Windows Install](documents/install/windows_install.md)
|
||||
* [Docker Install](/docs/install/docker_install.md)
|
||||
* [Linux Install](docs/install/linux_install.md)
|
||||
* [Mac Install](docs/install/mac_install.md)
|
||||
* [Windows Install](docs/install/windows_install.md)
|
||||
* [APIs and Tokens](docs/install/apis_and_tokens.md)
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary><strong>General Information</strong></summary>
|
||||
|
||||
* [Project Origin](documents/general_info/project_origin.md)
|
||||
* [Roadmap](documents/general_info/roadmap.md)
|
||||
* [Tech Stack](documents/general_info/tech_stack.md)
|
||||
* [Code of Conduct](CODE_OF_CONDUCT.md)
|
||||
* [Project Origin](docs/general_info/project_origin.md)
|
||||
* [Multilingual Information](docs/general_info/multilingual_information.md)
|
||||
* [Tech Stack](docs/general_info/tech_stack.md)
|
||||
* [Changelog](CHANGELOG.md)
|
||||
* [Bing Jailbreak Info](documents/general_info/bing_jailbreak_info.md)
|
||||
* [Bing Jailbreak Info](docs/general_info/bing_jailbreak_info.md)
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary><strong>Features</strong></summary>
|
||||
|
||||
* [User Auth System](documents/features/user_auth_system.md)
|
||||
* [Proxy](documents/features/proxy.md)
|
||||
* **Plugins**
|
||||
* [Introduction](docs/features/plugins/introduction.md)
|
||||
* [Google](docs/features/plugins/google_search.md)
|
||||
* [Stable Diffusion](docs/features/plugins/stable_diffusion.md)
|
||||
* [Wolfram](docs/features/plugins/wolfram.md)
|
||||
* [Make Your Own Plugin](docs/features/plugins/make_your_own.md)
|
||||
|
||||
* [User Auth System](docs/features/user_auth_system.md)
|
||||
* [Proxy](docs/features/proxy.md)
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary><strong>Cloud Deployment</strong></summary>
|
||||
|
||||
* [Heroku](documents/deployment/heroku.md)
|
||||
* [Heroku](docs/deployment/heroku.md)
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary><strong>Contributions</strong></summary>
|
||||
|
||||
* [Code of Conduct](documents/contributions/code_of_conduct.md)
|
||||
* [Contributor Guidelines](documents/contributions/contributor_guidelines.md)
|
||||
* [Documentation Guidelines](documents/contributions/documentation_guidelines.md)
|
||||
* [Testing](documents/contributions/testing.md)
|
||||
* [Pull Request Template](documents/contributions/pull_request_template.md)
|
||||
* [Contributors](CONTRIBUTORS.md)
|
||||
* [Contributor Guidelines](CONTRIBUTING.md)
|
||||
* [Documentation Guidelines](docs/contributions/documentation_guidelines.md)
|
||||
* [Code Standards and Conventions](docs/contributions/coding_conventions.md)
|
||||
* [Testing](docs/contributions/testing.md)
|
||||
* [Security](SECURITY.md)
|
||||
* [Trello Board](https://trello.com/b/17z094kq/chatgpt-clone)
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary><strong>Report Templates</strong></summary>
|
||||
|
||||
* [Bug Report Template](documents/report_templates/bug_report_template.md)
|
||||
* [Custom Issue Template](documents/report_templates/custom_issue_template.md)
|
||||
* [Feature Request Template](documents/report_templates/feature_request_template.md)
|
||||
</details>
|
||||
---
|
||||
|
||||
##
|
||||
### [Alternative Documentation](https://chatgpt-clone.gitbook.io/chatgpt-clone-docs/get-started/docker)
|
||||
## Star History
|
||||
|
||||
##
|
||||
[](https://star-history.com/#danny-avila/chatgpt-clone&Date)
|
||||
|
||||
## Contributing
|
||||
---
|
||||
|
||||
## Sponsors
|
||||
|
||||
Sponsored by <a href="https://github.com/DavidDev1334"><b>@DavidDev1334</b></a>, <a href="https://github.com/mjtechguy"><b>@mjtechguy</b></a>, <a href="https://github.com/Pharrcyde"><b>@Pharrcyde</b></a>, & <a href="https://github.com/fuegovic"><b>@fuegovic</b></a>
|
||||
|
||||
---
|
||||
|
||||
## Contributors
|
||||
Contributions and suggestions bug reports and fixes are welcome!
|
||||
Please read the documentation before you do!
|
||||
|
||||
---
|
||||
|
||||
For new features, components, or extensions, please open an issue and discuss before sending a PR.
|
||||
|
||||
- Join the [Discord community](https://discord.gg/NGaa9RPCft)
|
||||
|
||||
## License
|
||||
This project is licensed under the [MIT License](LICENSE.md).
|
||||
##
|
||||
- Join the [Discord community](https://discord.gg/uDyZ5Tzhct)
|
||||
|
||||
This project exists in its current state thanks to all the people who contribute
|
||||
---
|
||||
<a href="https://github.com/danny-avila/chatgpt-clone/graphs/contributors">
|
||||
<img src="https://contrib.rocks/image?repo=danny-avila/chatgpt-clone" />
|
||||
</a>
|
||||
|
||||
55
SECURITY.md
Normal file
55
SECURITY.md
Normal file
@@ -0,0 +1,55 @@
|
||||
# Security Policy
|
||||
|
||||
## Reporting a Vulnerability
|
||||
We take security seriously and appreciate the efforts of security researchers to improve the security of our codebase.
|
||||
If you discover a security vulnerability within our project, please follow these guidelines to report it to us:
|
||||
|
||||
**Note: Only report sensible vulnerability report details via Github Security Advisory System. Every other communication channel are public and should be used only to initiate first contact and to initiate a private communication channel.**
|
||||
|
||||
### Communication channels
|
||||
- **Option 1: GitHub Security Advisory System**: We encourage you to use GitHub's Security Advisory system to report any security vulnerabilities you find. This allows us to receive vulnerability reports directly through GitHub. You can find more information on how to submit a security advisory report in the [GitHub Security Advisories documentation](https://docs.github.com/en/code-security/getting-started-with-security-vulnerability-alerts/about-github-security-advisories).
|
||||
- **Option 2: Github issues**: You can initiate first contact via Github Issues. **Please note that initial contact through Discord should not include any sensitive details.**
|
||||
- **Option 3: Discord Server**: You can join our [Discord community](https://discord.gg/5rbRxn4uME) and initiate first contact in the `#issues` channel. **Please note that initial contact through Discord should not include any sensitive details.**
|
||||
|
||||
_After initial contact, we will use this initial contact to establish a private communication channel for further discussion._
|
||||
|
||||
|
||||
### When submitting a vulnerability report, please provide us with the following information:
|
||||
- A clear description of the vulnerability, including steps to reproduce it
|
||||
- The version(s) of the project affected by the vulnerability
|
||||
- Any additional information that may be useful for understanding and addressing the issue
|
||||
We will make every effort to acknowledge your report within 72 hours and keep you informed of its progress towards resolution.
|
||||
|
||||
|
||||
## Security Updates and Patching
|
||||
We are committed to maintaining the security of our open-source project named LibreChat and promptly addressing any identified vulnerabilities. To ensure the security of our project, we follow these practices:
|
||||
- We prioritize security updates for the current major release of our software.
|
||||
- We actively monitor the GitHub Security Advisory system and the `#issues` channel on Discord for any vulnerability reports.
|
||||
- We promptly review and validate reported vulnerabilities and take appropriate actions to address them.
|
||||
- We release security patches and updates in a timely manner to mitigate any identified vulnerabilities.
|
||||
|
||||
Please note that as a security-conscious community, we may not always disclose detailed information about security issues until we have determined that doing so would not put our users or the project at risk. We appreciate your understanding and cooperation in these matters.
|
||||
|
||||
## Scope
|
||||
This security policy applies to the following GitHub repository:
|
||||
- Repository: [LibreChat](https://github.com/danny-avila/chatgpt-clone)
|
||||
|
||||
## Contact
|
||||
If you have any questions or concerns regarding the security of our project, please join our [Discord community](https://discord.gg/NGaa9RPCft) and report them in the appropriate channel.
|
||||
You can also reach out to us by [opening an issue](https://github.com/danny-avila/chatgpt-clone/issues/new) on GitHub.
|
||||
Please note that the response time may vary depending on the nature and severity of the inquiry.
|
||||
|
||||
## Acknowledgments
|
||||
We would like to express our gratitude to the security researchers and community members who help us improve the security of our project. Your contributions are invaluable, and we sincerely appreciate your efforts.
|
||||
|
||||
## Bug Bounty Program
|
||||
We do not currently have a bug bounty program in place. However, we welcome and appreciate any security-related contributions through pull requests (PRs) that address vulnerabilities in our codebase.
|
||||
We believe in the power of collaboration to improve the security of our project and invite you to join us in making it more robust.
|
||||
|
||||
|
||||
**Reference**
|
||||
- https://cheatsheetseries.owasp.org/cheatsheets/Vulnerability_Disclosure_Cheat_Sheet.html
|
||||
|
||||
##
|
||||
|
||||
## [Go Back to ReadMe](README.md)
|
||||
@@ -1,39 +0,0 @@
|
||||
module.exports = {
|
||||
env: {
|
||||
es2021: true,
|
||||
node: true
|
||||
},
|
||||
extends: ['eslint:recommended'],
|
||||
overrides: [],
|
||||
parserOptions: {
|
||||
ecmaVersion: 'latest',
|
||||
sourceType: 'module'
|
||||
},
|
||||
rules: {
|
||||
indent: ['error', 2, { SwitchCase: 1 }],
|
||||
'max-len': [
|
||||
'error',
|
||||
{
|
||||
code: 150,
|
||||
ignoreStrings: true,
|
||||
ignoreTemplateLiterals: true,
|
||||
ignoreComments: true
|
||||
}
|
||||
],
|
||||
'linebreak-style': 0,
|
||||
'arrow-parens': [2, 'as-needed', { requireForBlockBody: true }],
|
||||
// 'no-plusplus': ['error', { allowForLoopAfterthoughts: true }],
|
||||
'no-console': 'off',
|
||||
'import/extensions': 'off',
|
||||
'no-use-before-define': [
|
||||
'error',
|
||||
{
|
||||
functions: false
|
||||
}
|
||||
],
|
||||
'no-promise-executor-return': 'off',
|
||||
'no-param-reassign': 'off',
|
||||
'no-continue': 'off',
|
||||
'no-restricted-syntax': 'off'
|
||||
}
|
||||
};
|
||||
@@ -1,22 +0,0 @@
|
||||
{
|
||||
"arrowParens": "always",
|
||||
"bracketSpacing": true,
|
||||
"endOfLine": "lf",
|
||||
"htmlWhitespaceSensitivity": "css",
|
||||
"insertPragma": false,
|
||||
"singleAttributePerLine": true,
|
||||
"bracketSameLine": false,
|
||||
"jsxBracketSameLine": false,
|
||||
"jsxSingleQuote": false,
|
||||
"printWidth": 110,
|
||||
"proseWrap": "preserve",
|
||||
"quoteProps": "as-needed",
|
||||
"requirePragma": false,
|
||||
"semi": true,
|
||||
"singleQuote": true,
|
||||
"tabWidth": 2,
|
||||
"trailingComma": "none",
|
||||
"useTabs": false,
|
||||
"vueIndentScriptAndStyle": false,
|
||||
"parser": "babel"
|
||||
}
|
||||
@@ -16,16 +16,17 @@ const askBing = async ({
|
||||
token,
|
||||
onProgress
|
||||
}) => {
|
||||
const { BingAIClient } = await import('og-chatgpt-api');
|
||||
const { BingAIClient } = await import('@waylaidwanderer/chatgpt-api');
|
||||
const store = {
|
||||
store: new KeyvFile({ filename: './data/cache.json' })
|
||||
};
|
||||
|
||||
const bingAIClient = new BingAIClient({
|
||||
// "_U" cookie from bing.com
|
||||
userToken: process.env.BINGAI_TOKEN == 'user_provided' ? token : process.env.BINGAI_TOKEN ?? null,
|
||||
// userToken:
|
||||
// process.env.BINGAI_TOKEN == 'user_provided' ? token : process.env.BINGAI_TOKEN ?? null,
|
||||
// If the above doesn't work, provide all your cookies as a string instead
|
||||
// cookies: '',
|
||||
cookies: process.env.BINGAI_TOKEN == 'user_provided' ? token : process.env.BINGAI_TOKEN ?? null,
|
||||
debug: false,
|
||||
cache: store,
|
||||
host: process.env.BINGAI_HOST || null,
|
||||
|
||||
@@ -8,19 +8,22 @@ const browserClient = async ({
|
||||
model,
|
||||
token,
|
||||
onProgress,
|
||||
onEventMessage,
|
||||
abortController,
|
||||
userId
|
||||
}) => {
|
||||
const { ChatGPTBrowserClient } = await import('og-chatgpt-api');
|
||||
const { ChatGPTBrowserClient } = await import('@waylaidwanderer/chatgpt-api');
|
||||
const store = {
|
||||
store: new KeyvFile({ filename: './data/cache.json' })
|
||||
};
|
||||
|
||||
const clientOptions = {
|
||||
// Warning: This will expose your access token to a third party. Consider the risks before using this.
|
||||
reverseProxyUrl: process.env.CHATGPT_REVERSE_PROXY || 'https://ai.fakeopen.com/api/conversation',
|
||||
reverseProxyUrl:
|
||||
process.env.CHATGPT_REVERSE_PROXY || 'https://ai.fakeopen.com/api/conversation',
|
||||
// Access token from https://chat.openai.com/api/auth/session
|
||||
accessToken: process.env.CHATGPT_TOKEN == 'user_provided' ? token : process.env.CHATGPT_TOKEN ?? null,
|
||||
accessToken:
|
||||
process.env.CHATGPT_TOKEN == 'user_provided' ? token : process.env.CHATGPT_TOKEN ?? null,
|
||||
model: model,
|
||||
debug: false,
|
||||
proxy: process.env.PROXY || null,
|
||||
@@ -28,7 +31,7 @@ const browserClient = async ({
|
||||
};
|
||||
|
||||
const client = new ChatGPTBrowserClient(clientOptions, store);
|
||||
let options = { onProgress, abortController };
|
||||
let options = { onProgress, onEventMessage, abortController };
|
||||
|
||||
if (!!parentMessageId && !!conversationId) {
|
||||
options = { ...options, parentMessageId, conversationId };
|
||||
|
||||
@@ -1,12 +1,16 @@
|
||||
require('dotenv').config();
|
||||
const { KeyvFile } = require('keyv-file');
|
||||
const { genAzureEndpoint } = require('../../utils/genAzureEndpoints');
|
||||
const { genAzureChatCompletion } = require('../../utils/genAzureEndpoints');
|
||||
const tiktoken = require('@dqbd/tiktoken');
|
||||
const tiktokenModels = require('../../utils/tiktokenModels');
|
||||
const encoding_for_model = tiktoken.encoding_for_model;
|
||||
|
||||
const askClient = async ({
|
||||
text,
|
||||
parentMessageId,
|
||||
conversationId,
|
||||
model,
|
||||
oaiApiKey,
|
||||
chatGptLabel,
|
||||
promptPrefix,
|
||||
temperature,
|
||||
@@ -23,12 +27,17 @@ const askClient = async ({
|
||||
};
|
||||
|
||||
const azure = process.env.AZURE_OPENAI_API_KEY ? true : false;
|
||||
|
||||
let promptText = 'You are ChatGPT, a large language model trained by OpenAI.';
|
||||
if (promptPrefix) {
|
||||
promptText = promptPrefix;
|
||||
}
|
||||
const maxContextTokens = model === 'gpt-4-32k' ? 32767 : model.startsWith('gpt-4') ? 8191 : 4095; // 1 less than maximum
|
||||
const clientOptions = {
|
||||
reverseProxyUrl: process.env.OPENAI_REVERSE_PROXY || null,
|
||||
azure,
|
||||
maxContextTokens,
|
||||
modelOptions: {
|
||||
model: model,
|
||||
model,
|
||||
temperature,
|
||||
top_p,
|
||||
presence_penalty,
|
||||
@@ -36,30 +45,49 @@ const askClient = async ({
|
||||
},
|
||||
chatGptLabel,
|
||||
promptPrefix,
|
||||
proxy: process.env.PROXY || null,
|
||||
debug: false
|
||||
proxy: process.env.PROXY || null
|
||||
// debug: true
|
||||
};
|
||||
|
||||
let apiKey = process.env.OPENAI_KEY;
|
||||
let apiKey = oaiApiKey ? oaiApiKey : process.env.OPENAI_API_KEY || null;
|
||||
|
||||
if (azure) {
|
||||
apiKey = process.env.AZURE_OPENAI_API_KEY;
|
||||
clientOptions.reverseProxyUrl = genAzureEndpoint({
|
||||
azureOpenAIApiInstanceName: process.env.AZURE_OPENAI_API_INSTANCE_NAME,
|
||||
azureOpenAIApiDeploymentName: process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME,
|
||||
apiKey = oaiApiKey ? oaiApiKey : process.env.AZURE_OPENAI_API_KEY || null;
|
||||
clientOptions.reverseProxyUrl = genAzureChatCompletion({
|
||||
azureOpenAIApiInstanceName: process.env.AZURE_OPENAI_API_INSTANCE_NAME,
|
||||
azureOpenAIApiDeploymentName: process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME,
|
||||
azureOpenAIApiVersion: process.env.AZURE_OPENAI_API_VERSION
|
||||
});
|
||||
}
|
||||
|
||||
const client = new ChatGPTClient(apiKey, clientOptions, store);
|
||||
|
||||
|
||||
const options = {
|
||||
onProgress,
|
||||
abortController,
|
||||
...(parentMessageId && conversationId ? { parentMessageId, conversationId } : {})
|
||||
};
|
||||
|
||||
let usage = {};
|
||||
let enc = null;
|
||||
try {
|
||||
enc = encoding_for_model(tiktokenModels.has(model) ? model : 'gpt-3.5-turbo');
|
||||
usage.prompt_tokens = (enc.encode(promptText)).length + (enc.encode(text)).length;
|
||||
} catch (e) {
|
||||
console.log('Error encoding prompt text', e);
|
||||
}
|
||||
|
||||
const res = await client.sendMessage(text, { ...options, userId });
|
||||
|
||||
try {
|
||||
usage.completion_tokens = (enc.encode(res.response)).length;
|
||||
enc.free();
|
||||
usage.total_tokens = usage.prompt_tokens + usage.completion_tokens;
|
||||
res.usage = usage;
|
||||
} catch (e) {
|
||||
console.log('Error encoding response text', e);
|
||||
}
|
||||
|
||||
return res;
|
||||
};
|
||||
|
||||
|
||||
89
api/app/clients/chatgpt-client.tokens.js
Normal file
89
api/app/clients/chatgpt-client.tokens.js
Normal file
@@ -0,0 +1,89 @@
|
||||
require('dotenv').config();
|
||||
|
||||
const run = async () => {
|
||||
const { ChatGPTClient } = await import('@waylaidwanderer/chatgpt-api');
|
||||
const text = `
|
||||
The standard Lorem Ipsum passage, used since the 1500s
|
||||
|
||||
"Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum."
|
||||
Section 1.10.32 of "de Finibus Bonorum et Malorum", written by Cicero in 45 BC
|
||||
|
||||
"Sed ut perspiciatis unde omnis iste natus error sit voluptatem accusantium doloremque laudantium, totam rem aperiam, eaque ipsa quae ab illo inventore veritatis et quasi architecto beatae vitae dicta sunt explicabo. Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut odit aut fugit, sed quia consequuntur magni dolores eos qui ratione voluptatem sequi nesciunt. Neque porro quisquam est, qui dolorem ipsum quia dolor sit amet, consectetur, adipisci velit, sed quia non numquam eius modi tempora incidunt ut labore et dolore magnam aliquam quaerat voluptatem. Ut enim ad minima veniam, quis nostrum exercitationem ullam corporis suscipit laboriosam, nisi ut aliquid ex ea commodi consequatur? Quis autem vel eum iure reprehenderit qui in ea voluptate velit esse quam nihil molestiae consequatur, vel illum qui dolorem eum fugiat quo voluptas nulla pariatur?"
|
||||
1914 translation by H. Rackham
|
||||
|
||||
"But I must explain to you how all this mistaken idea of denouncing pleasure and praising pain was born and I will give you a complete account of the system, and expound the actual teachings of the great explorer of the truth, the master-builder of human happiness. No one rejects, dislikes, or avoids pleasure itself, because it is pleasure, but because those who do not know how to pursue pleasure rationally encounter consequences that are extremely painful. Nor again is there anyone who loves or pursues or desires to obtain pain of itself, because it is pain, but because occasionally circumstances occur in which toil and pain can procure him some great pleasure. To take a trivial example, which of us ever undertakes laborious physical exercise, except to obtain some advantage from it? But who has any right to find fault with a man who chooses to enjoy a pleasure that has no annoying consequences, or one who avoids a pain that produces no resultant pleasure?"
|
||||
Section 1.10.33 of "de Finibus Bonorum et Malorum", written by Cicero in 45 BC
|
||||
|
||||
"At vero eos et accusamus et iusto odio dignissimos ducimus qui blanditiis praesentium voluptatum deleniti atque corrupti quos dolores et quas molestias excepturi sint occaecati cupiditate non provident, similique sunt in culpa qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio. Nam libero tempore, cum soluta nobis est eligendi optio cumque nihil impedit quo minus id quod maxime placeat facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet ut et voluptates repudiandae sint et molestiae non recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat."
|
||||
1914 translation by H. Rackham
|
||||
|
||||
"On the other hand, we denounce with righteous indignation and dislike men who are so beguiled and demoralized by the charms of pleasure of the moment, so blinded by desire, that they cannot foresee the pain and trouble that are bound to ensue; and equal blame belongs to those who fail in their duty through weakness of will, which is the same as saying through shrinking from toil and pain. These cases are perfectly simple and easy to distinguish. In a free hour, when our power of choice is untrammelled and when nothing prevents our being able to do what we like best, every pleasure is to be welcomed and every pain avoided. But in certain circumstances and owing to the claims of duty or the obligations of business it will frequently occur that pleasures have to be repudiated and annoyances accepted. The wise man therefore always holds in these matters to this principle of selection: he rejects pleasures to secure other greater pleasures, or else he endures pains to avoid worse pains."
|
||||
`;
|
||||
const model = 'gpt-3.5-turbo';
|
||||
const maxContextTokens = model === 'gpt-4' ? 8191 : model === 'gpt-4-32k' ? 32767 : 4095; // 1 less than maximum
|
||||
const clientOptions = {
|
||||
reverseProxyUrl: process.env.OPENAI_REVERSE_PROXY || null,
|
||||
maxContextTokens,
|
||||
modelOptions: {
|
||||
model,
|
||||
},
|
||||
proxy: process.env.PROXY || null,
|
||||
debug: true
|
||||
};
|
||||
|
||||
let apiKey = process.env.OPENAI_API_KEY;
|
||||
|
||||
const maxMemory = 0.05 * 1024 * 1024 * 1024;
|
||||
|
||||
// Calculate initial percentage of memory used
|
||||
const initialMemoryUsage = process.memoryUsage().heapUsed;
|
||||
|
||||
|
||||
function printProgressBar(percentageUsed) {
|
||||
const filledBlocks = Math.round(percentageUsed / 2); // Each block represents 2%
|
||||
const emptyBlocks = 50 - filledBlocks; // Total blocks is 50 (each represents 2%), so the rest are empty
|
||||
const progressBar = '[' + '█'.repeat(filledBlocks) + ' '.repeat(emptyBlocks) + '] ' + percentageUsed.toFixed(2) + '%';
|
||||
console.log(progressBar);
|
||||
}
|
||||
|
||||
const iterations = 16000;
|
||||
console.time('loopTime');
|
||||
// Trying to catch the error doesn't help; all future calls will immediately crash
|
||||
for (let i = 0; i < iterations; i++) {
|
||||
try {
|
||||
console.log(`Iteration ${i}`);
|
||||
const client = new ChatGPTClient(apiKey, clientOptions);
|
||||
|
||||
client.getTokenCount(text);
|
||||
// const encoder = client.constructor.getTokenizer('cl100k_base');
|
||||
// console.log(`Iteration ${i}: call encode()...`);
|
||||
// encoder.encode(text, 'all');
|
||||
// encoder.free();
|
||||
|
||||
const memoryUsageDuringLoop = process.memoryUsage().heapUsed;
|
||||
const percentageUsed = memoryUsageDuringLoop / maxMemory * 100;
|
||||
printProgressBar(percentageUsed);
|
||||
|
||||
if (i === (iterations - 1)) {
|
||||
console.log(' done');
|
||||
// encoder.free();
|
||||
}
|
||||
} catch (e) {
|
||||
console.log(`caught error! in Iteration ${i}`);
|
||||
console.log(e);
|
||||
}
|
||||
}
|
||||
|
||||
console.timeEnd('loopTime');
|
||||
// Calculate final percentage of memory used
|
||||
const finalMemoryUsage = process.memoryUsage().heapUsed;
|
||||
// const finalPercentageUsed = finalMemoryUsage / maxMemory * 100;
|
||||
console.log(`Initial memory usage: ${initialMemoryUsage / 1024 / 1024} megabytes`);
|
||||
console.log(`Final memory usage: ${finalMemoryUsage / 1024 / 1024} megabytes`);
|
||||
setTimeout(() => {
|
||||
const memoryUsageAfterTimeout = process.memoryUsage().heapUsed;
|
||||
console.log(`Post timeout: ${memoryUsageAfterTimeout / 1024 / 1024} megabytes`);
|
||||
} , 10000);
|
||||
}
|
||||
|
||||
run();
|
||||
397
api/app/google/GoogleClient.js
Normal file
397
api/app/google/GoogleClient.js
Normal file
@@ -0,0 +1,397 @@
|
||||
const crypto = require('crypto');
|
||||
const TextStream = require('../stream');
|
||||
const { google } = require('googleapis');
|
||||
const { Agent, ProxyAgent } = require('undici');
|
||||
const { getMessages, saveMessage, saveConvo } = require('../../models');
|
||||
const {
|
||||
encoding_for_model: encodingForModel,
|
||||
get_encoding: getEncoding
|
||||
} = require('@dqbd/tiktoken');
|
||||
|
||||
const tokenizersCache = {};
|
||||
|
||||
class GoogleAgent {
|
||||
constructor(credentials, options = {}) {
|
||||
this.client_email = credentials.client_email;
|
||||
this.project_id = credentials.project_id;
|
||||
this.private_key = credentials.private_key;
|
||||
this.setOptions(options);
|
||||
this.currentDateString = new Date().toLocaleDateString('en-us', {
|
||||
year: 'numeric',
|
||||
month: 'long',
|
||||
day: 'numeric'
|
||||
});
|
||||
}
|
||||
|
||||
constructUrl() {
|
||||
return `https://us-central1-aiplatform.googleapis.com/v1/projects/${this.project_id}/locations/us-central1/publishers/google/models/${this.modelOptions.model}:predict`;
|
||||
}
|
||||
|
||||
setOptions(options) {
|
||||
if (this.options && !this.options.replaceOptions) {
|
||||
// nested options aren't spread properly, so we need to do this manually
|
||||
this.options.modelOptions = {
|
||||
...this.options.modelOptions,
|
||||
...options.modelOptions
|
||||
};
|
||||
delete options.modelOptions;
|
||||
// now we can merge options
|
||||
this.options = {
|
||||
...this.options,
|
||||
...options
|
||||
};
|
||||
} else {
|
||||
this.options = options;
|
||||
}
|
||||
|
||||
this.options.examples = this.options.examples.filter(
|
||||
(obj) => obj.input.content !== '' && obj.output.content !== ''
|
||||
);
|
||||
|
||||
const modelOptions = this.options.modelOptions || {};
|
||||
this.modelOptions = {
|
||||
...modelOptions,
|
||||
// set some good defaults (check for undefined in some cases because they may be 0)
|
||||
model: modelOptions.model || 'chat-bison',
|
||||
temperature: typeof modelOptions.temperature === 'undefined' ? 0.2 : modelOptions.temperature, // 0 - 1, 0.2 is recommended
|
||||
topP: typeof modelOptions.topP === 'undefined' ? 0.95 : modelOptions.topP, // 0 - 1, default: 0.95
|
||||
topK: typeof modelOptions.topK === 'undefined' ? 40 : modelOptions.topK // 1-40, default: 40
|
||||
// stop: modelOptions.stop // no stop method for now
|
||||
};
|
||||
|
||||
this.isChatModel = this.modelOptions.model.startsWith('chat-');
|
||||
const { isChatModel } = this;
|
||||
this.isTextModel = this.modelOptions.model.startsWith('text-');
|
||||
const { isTextModel } = this;
|
||||
|
||||
this.maxContextTokens = this.options.maxContextTokens || (isTextModel ? 8000 : 4096);
|
||||
// The max prompt tokens is determined by the max context tokens minus the max response tokens.
|
||||
// Earlier messages will be dropped until the prompt is within the limit.
|
||||
this.maxResponseTokens = this.modelOptions.maxOutputTokens || 1024;
|
||||
this.maxPromptTokens =
|
||||
this.options.maxPromptTokens || this.maxContextTokens - this.maxResponseTokens;
|
||||
|
||||
if (this.maxPromptTokens + this.maxResponseTokens > this.maxContextTokens) {
|
||||
throw new Error(
|
||||
`maxPromptTokens + maxOutputTokens (${this.maxPromptTokens} + ${this.maxResponseTokens} = ${
|
||||
this.maxPromptTokens + this.maxResponseTokens
|
||||
}) must be less than or equal to maxContextTokens (${this.maxContextTokens})`
|
||||
);
|
||||
}
|
||||
|
||||
this.userLabel = this.options.userLabel || 'User';
|
||||
this.modelLabel = this.options.modelLabel || 'Assistant';
|
||||
|
||||
if (isChatModel) {
|
||||
// Use these faux tokens to help the AI understand the context since we are building the chat log ourselves.
|
||||
// Trying to use "<|im_start|>" causes the AI to still generate "<" or "<|" at the end sometimes for some reason,
|
||||
// without tripping the stop sequences, so I'm using "||>" instead.
|
||||
this.startToken = '||>';
|
||||
this.endToken = '';
|
||||
this.gptEncoder = this.constructor.getTokenizer('cl100k_base');
|
||||
} else if (isTextModel) {
|
||||
this.startToken = '<|im_start|>';
|
||||
this.endToken = '<|im_end|>';
|
||||
this.gptEncoder = this.constructor.getTokenizer('text-davinci-003', true, {
|
||||
'<|im_start|>': 100264,
|
||||
'<|im_end|>': 100265
|
||||
});
|
||||
} else {
|
||||
// Previously I was trying to use "<|endoftext|>" but there seems to be some bug with OpenAI's token counting
|
||||
// system that causes only the first "<|endoftext|>" to be counted as 1 token, and the rest are not treated
|
||||
// as a single token. So we're using this instead.
|
||||
this.startToken = '||>';
|
||||
this.endToken = '';
|
||||
try {
|
||||
this.gptEncoder = this.constructor.getTokenizer(this.modelOptions.model, true);
|
||||
} catch {
|
||||
this.gptEncoder = this.constructor.getTokenizer('text-davinci-003', true);
|
||||
}
|
||||
}
|
||||
|
||||
if (!this.modelOptions.stop) {
|
||||
const stopTokens = [this.startToken];
|
||||
if (this.endToken && this.endToken !== this.startToken) {
|
||||
stopTokens.push(this.endToken);
|
||||
}
|
||||
stopTokens.push(`\n${this.userLabel}:`);
|
||||
stopTokens.push('<|diff_marker|>');
|
||||
// I chose not to do one for `modelLabel` because I've never seen it happen
|
||||
this.modelOptions.stop = stopTokens;
|
||||
}
|
||||
|
||||
if (this.options.reverseProxyUrl) {
|
||||
this.completionsUrl = this.options.reverseProxyUrl;
|
||||
} else {
|
||||
this.completionsUrl = this.constructUrl();
|
||||
}
|
||||
|
||||
return this;
|
||||
}
|
||||
|
||||
static getTokenizer(encoding, isModelName = false, extendSpecialTokens = {}) {
|
||||
if (tokenizersCache[encoding]) {
|
||||
return tokenizersCache[encoding];
|
||||
}
|
||||
let tokenizer;
|
||||
if (isModelName) {
|
||||
tokenizer = encodingForModel(encoding, extendSpecialTokens);
|
||||
} else {
|
||||
tokenizer = getEncoding(encoding, extendSpecialTokens);
|
||||
}
|
||||
tokenizersCache[encoding] = tokenizer;
|
||||
return tokenizer;
|
||||
}
|
||||
|
||||
async getClient() {
|
||||
const scopes = ['https://www.googleapis.com/auth/cloud-platform'];
|
||||
const jwtClient = new google.auth.JWT(this.client_email, null, this.private_key, scopes);
|
||||
|
||||
jwtClient.authorize((err) => {
|
||||
if (err) {
|
||||
console.log(err);
|
||||
throw err;
|
||||
}
|
||||
});
|
||||
|
||||
return jwtClient;
|
||||
}
|
||||
|
||||
buildPayload(input, { messages = [] }) {
|
||||
let payload = {
|
||||
instances: [
|
||||
{
|
||||
messages: [...messages, { author: this.userLabel, content: input }]
|
||||
}
|
||||
],
|
||||
parameters: this.options.modelOptions
|
||||
};
|
||||
|
||||
if (this.options.promptPrefix) {
|
||||
payload.instances[0].context = this.options.promptPrefix;
|
||||
}
|
||||
|
||||
if (this.options.examples.length > 0) {
|
||||
payload.instances[0].examples = this.options.examples;
|
||||
}
|
||||
|
||||
if (this.isTextModel) {
|
||||
payload.instances = [
|
||||
{
|
||||
prompt: input
|
||||
}
|
||||
];
|
||||
}
|
||||
|
||||
if (this.options.debug) {
|
||||
console.debug('buildPayload');
|
||||
console.dir(payload, { depth: null });
|
||||
}
|
||||
|
||||
return payload;
|
||||
}
|
||||
|
||||
async getCompletion(input, messages = [], abortController = null) {
|
||||
if (!abortController) {
|
||||
abortController = new AbortController();
|
||||
}
|
||||
const { debug } = this.options;
|
||||
const url = this.completionsUrl;
|
||||
if (debug) {
|
||||
console.debug();
|
||||
console.debug(url);
|
||||
console.debug(this.modelOptions);
|
||||
console.debug();
|
||||
}
|
||||
const opts = {
|
||||
method: 'POST',
|
||||
agent: new Agent({
|
||||
bodyTimeout: 0,
|
||||
headersTimeout: 0
|
||||
}),
|
||||
signal: abortController.signal
|
||||
};
|
||||
|
||||
if (this.options.proxy) {
|
||||
opts.agent = new ProxyAgent(this.options.proxy);
|
||||
}
|
||||
|
||||
const client = await this.getClient();
|
||||
const payload = this.buildPayload(input, { messages });
|
||||
const res = await client.request({ url, method: 'POST', data: payload });
|
||||
console.dir(res.data, { depth: null });
|
||||
return res.data;
|
||||
}
|
||||
|
||||
async loadHistory(conversationId, parentMessageId = null) {
|
||||
if (this.options.debug) {
|
||||
console.debug('Loading history for conversation', conversationId, parentMessageId);
|
||||
}
|
||||
|
||||
if (!parentMessageId) {
|
||||
return [];
|
||||
}
|
||||
|
||||
const messages = (await getMessages({ conversationId })) || [];
|
||||
|
||||
if (messages.length === 0) {
|
||||
this.currentMessages = [];
|
||||
return [];
|
||||
}
|
||||
|
||||
const orderedMessages = this.constructor.getMessagesForConversation(messages, parentMessageId);
|
||||
return orderedMessages.map((message) => {
|
||||
return {
|
||||
author: message.isCreatedByUser ? this.userLabel : this.modelLabel,
|
||||
content: message.content
|
||||
};
|
||||
});
|
||||
}
|
||||
|
||||
async saveMessageToDatabase(message, user = null) {
|
||||
await saveMessage({ ...message, unfinished: false });
|
||||
await saveConvo(user, {
|
||||
conversationId: message.conversationId,
|
||||
endpoint: 'google',
|
||||
...this.modelOptions
|
||||
});
|
||||
}
|
||||
|
||||
async sendMessage(message, opts = {}) {
|
||||
if (opts && typeof opts === 'object') {
|
||||
this.setOptions(opts);
|
||||
}
|
||||
console.log('sendMessage', message, opts);
|
||||
|
||||
const user = opts.user || null;
|
||||
const conversationId = opts.conversationId || crypto.randomUUID();
|
||||
const parentMessageId = opts.parentMessageId || '00000000-0000-0000-0000-000000000000';
|
||||
const userMessageId = opts.overrideParentMessageId || crypto.randomUUID();
|
||||
const responseMessageId = crypto.randomUUID();
|
||||
const messages = await this.loadHistory(conversationId, this.options?.parentMessageId);
|
||||
|
||||
const userMessage = {
|
||||
messageId: userMessageId,
|
||||
parentMessageId,
|
||||
conversationId,
|
||||
sender: 'User',
|
||||
text: message,
|
||||
isCreatedByUser: true
|
||||
};
|
||||
|
||||
if (typeof opts?.getIds === 'function') {
|
||||
opts.getIds({
|
||||
userMessage,
|
||||
conversationId,
|
||||
responseMessageId
|
||||
});
|
||||
}
|
||||
|
||||
console.log('userMessage', userMessage);
|
||||
|
||||
await this.saveMessageToDatabase(userMessage, user);
|
||||
let reply = '';
|
||||
let blocked = false;
|
||||
try {
|
||||
const result = await this.getCompletion(message, messages, opts.abortController);
|
||||
blocked = result?.predictions?.[0]?.safetyAttributes?.blocked;
|
||||
reply =
|
||||
result?.predictions?.[0]?.candidates?.[0]?.content ||
|
||||
result?.predictions?.[0]?.content ||
|
||||
'';
|
||||
if (blocked === true) {
|
||||
reply = `Google blocked a proper response to your message:\n${JSON.stringify(
|
||||
result.predictions[0].safetyAttributes
|
||||
)}${reply.length > 0 ? `\nAI Response:\n${reply}` : ''}`;
|
||||
}
|
||||
if (this.options.debug) {
|
||||
console.debug('result');
|
||||
console.debug(result);
|
||||
}
|
||||
} catch (err) {
|
||||
console.error(err);
|
||||
}
|
||||
|
||||
if (this.options.debug) {
|
||||
console.debug('options');
|
||||
console.debug(this.options);
|
||||
}
|
||||
|
||||
if (!blocked) {
|
||||
const textStream = new TextStream(reply, { delay: 0.5 });
|
||||
await textStream.processTextStream(opts.onProgress);
|
||||
}
|
||||
|
||||
const responseMessage = {
|
||||
messageId: responseMessageId,
|
||||
conversationId,
|
||||
parentMessageId: userMessage.messageId,
|
||||
sender: 'PaLM2',
|
||||
text: reply,
|
||||
error: blocked,
|
||||
isCreatedByUser: false
|
||||
};
|
||||
|
||||
await this.saveMessageToDatabase(responseMessage, user);
|
||||
return responseMessage;
|
||||
}
|
||||
|
||||
getTokenCount(text) {
|
||||
return this.gptEncoder.encode(text, 'all').length;
|
||||
}
|
||||
|
||||
/**
|
||||
* Algorithm adapted from "6. Counting tokens for chat API calls" of
|
||||
* https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
|
||||
*
|
||||
* An additional 2 tokens need to be added for metadata after all messages have been counted.
|
||||
*
|
||||
* @param {*} message
|
||||
*/
|
||||
getTokenCountForMessage(message) {
|
||||
// Map each property of the message to the number of tokens it contains
|
||||
const propertyTokenCounts = Object.entries(message).map(([key, value]) => {
|
||||
// Count the number of tokens in the property value
|
||||
const numTokens = this.getTokenCount(value);
|
||||
|
||||
// Subtract 1 token if the property key is 'name'
|
||||
const adjustment = key === 'name' ? 1 : 0;
|
||||
return numTokens - adjustment;
|
||||
});
|
||||
|
||||
// Sum the number of tokens in all properties and add 4 for metadata
|
||||
return propertyTokenCounts.reduce((a, b) => a + b, 4);
|
||||
}
|
||||
|
||||
/**
|
||||
* Iterate through messages, building an array based on the parentMessageId.
|
||||
* Each message has an id and a parentMessageId. The parentMessageId is the id of the message that this message is a reply to.
|
||||
* @param messages
|
||||
* @param parentMessageId
|
||||
* @returns {*[]} An array containing the messages in the order they should be displayed, starting with the root message.
|
||||
*/
|
||||
static getMessagesForConversation(messages, parentMessageId) {
|
||||
const orderedMessages = [];
|
||||
let currentMessageId = parentMessageId;
|
||||
while (currentMessageId) {
|
||||
// eslint-disable-next-line no-loop-func
|
||||
const message = messages.find((m) => m.messageId === currentMessageId);
|
||||
if (!message) {
|
||||
break;
|
||||
}
|
||||
orderedMessages.unshift(message);
|
||||
currentMessageId = message.parentMessageId;
|
||||
}
|
||||
|
||||
if (orderedMessages.length === 0) {
|
||||
return [];
|
||||
}
|
||||
|
||||
return orderedMessages.map((msg) => ({
|
||||
isCreatedByUser: msg.isCreatedByUser,
|
||||
content: msg.text
|
||||
}));
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = GoogleAgent;
|
||||
904
api/app/langchain/ChatAgent.js
Normal file
904
api/app/langchain/ChatAgent.js
Normal file
@@ -0,0 +1,904 @@
|
||||
const crypto = require('crypto');
|
||||
const { genAzureChatCompletion } = require('../../utils/genAzureEndpoints');
|
||||
const {
|
||||
encoding_for_model: encodingForModel,
|
||||
get_encoding: getEncoding
|
||||
} = require('@dqbd/tiktoken');
|
||||
const { fetchEventSource } = require('@waylaidwanderer/fetch-event-source');
|
||||
const { Agent, ProxyAgent } = require('undici');
|
||||
const TextStream = require('../stream');
|
||||
const { ChatOpenAI } = require('langchain/chat_models/openai');
|
||||
const { CallbackManager } = require('langchain/callbacks');
|
||||
const { HumanChatMessage, AIChatMessage } = require('langchain/schema');
|
||||
const { initializeCustomAgent } = require('./agents/CustomAgent/initializeCustomAgent');
|
||||
const { getMessages, saveMessage, saveConvo } = require('../../models');
|
||||
const { loadTools, SelfReflectionTool } = require('./tools');
|
||||
const {
|
||||
instructions,
|
||||
imageInstructions,
|
||||
errorInstructions,
|
||||
completionInstructions
|
||||
} = require('./instructions');
|
||||
|
||||
const tokenizersCache = {};
|
||||
|
||||
class ChatAgent {
|
||||
constructor(apiKey, options = {}) {
|
||||
this.tools = [];
|
||||
this.actions = [];
|
||||
this.openAIApiKey = apiKey;
|
||||
this.azure = options.azure || false;
|
||||
if (this.azure) {
|
||||
const { azureOpenAIApiInstanceName, azureOpenAIApiDeploymentName, azureOpenAIApiVersion } =
|
||||
this.azure;
|
||||
this.azureEndpoint = genAzureChatCompletion({
|
||||
azureOpenAIApiInstanceName,
|
||||
azureOpenAIApiDeploymentName,
|
||||
azureOpenAIApiVersion
|
||||
});
|
||||
}
|
||||
this.setOptions(options);
|
||||
this.executor = null;
|
||||
this.currentDateString = new Date().toLocaleDateString('en-us', {
|
||||
year: 'numeric',
|
||||
month: 'long',
|
||||
day: 'numeric'
|
||||
});
|
||||
}
|
||||
|
||||
getActions(input = null) {
|
||||
let output = 'Internal thoughts & actions taken:\n"';
|
||||
let actions = input || this.actions;
|
||||
|
||||
if (actions[0]?.action) {
|
||||
actions = actions.map((step) => ({
|
||||
log: `${step.action.log}\nObservation: ${step.observation}`
|
||||
}));
|
||||
}
|
||||
|
||||
actions.forEach((actionObj, index) => {
|
||||
output += `${actionObj.log}`;
|
||||
if (index < actions.length - 1) {
|
||||
output += '\n';
|
||||
}
|
||||
});
|
||||
|
||||
return output + '"';
|
||||
}
|
||||
|
||||
buildErrorInput(message, errorMessage) {
|
||||
const log = errorMessage.includes('Could not parse LLM output:')
|
||||
? `A formatting error occurred with your response to the human's last message. You didn't follow the formatting instructions. Remember to ${instructions}`
|
||||
: `You encountered an error while replying to the human's last message. Attempt to answer again or admit an answer cannot be given.\nError: ${errorMessage}`;
|
||||
|
||||
return `
|
||||
${log}
|
||||
|
||||
${this.getActions()}
|
||||
|
||||
Human's last message: ${message}
|
||||
`;
|
||||
}
|
||||
|
||||
buildPromptPrefix(result, message) {
|
||||
if ((result.output && result.output.includes('N/A')) || result.output === undefined) {
|
||||
return null;
|
||||
}
|
||||
|
||||
if (
|
||||
result?.intermediateSteps?.length === 1 &&
|
||||
result?.intermediateSteps[0]?.action?.toolInput === 'N/A'
|
||||
) {
|
||||
return null;
|
||||
}
|
||||
|
||||
const internalActions =
|
||||
result?.intermediateSteps?.length > 0
|
||||
? this.getActions(result.intermediateSteps)
|
||||
: 'Internal Actions Taken: None';
|
||||
|
||||
const toolBasedInstructions = internalActions.toLowerCase().includes('image')
|
||||
? imageInstructions
|
||||
: '';
|
||||
|
||||
const errorMessage = result.errorMessage ? `${errorInstructions} ${result.errorMessage}\n` : '';
|
||||
|
||||
const preliminaryAnswer =
|
||||
result.output?.length > 0 ? `Preliminary Answer: "${result.output.trim()}"` : '';
|
||||
const prefix = preliminaryAnswer
|
||||
? `review and improve the answer you generated using plugins in response to the User Message below. The answer hasn't been sent to the user yet.`
|
||||
: 'respond to the User Message below based on your preliminary thoughts & actions.';
|
||||
|
||||
return `As ChatGPT, ${prefix}${errorMessage}\n${internalActions}
|
||||
${preliminaryAnswer}
|
||||
Reply conversationally to the User based on your ${
|
||||
preliminaryAnswer ? 'preliminary answer, ' : ''
|
||||
}internal actions, thoughts, and observations, making improvements wherever possible, but do not modify URLs.
|
||||
${
|
||||
preliminaryAnswer
|
||||
? ''
|
||||
: '\nIf there is an incomplete thought or action, you are expected to complete it in your response now.\n'
|
||||
}You must cite sources if you are using any web links. ${toolBasedInstructions}
|
||||
Only respond with your conversational reply to the following User Message:
|
||||
"${message}"`;
|
||||
}
|
||||
|
||||
setOptions(options) {
|
||||
if (this.options && !this.options.replaceOptions) {
|
||||
// nested options aren't spread properly, so we need to do this manually
|
||||
this.options.modelOptions = {
|
||||
...this.options.modelOptions,
|
||||
...options.modelOptions
|
||||
};
|
||||
this.options.agentOptions = {
|
||||
...this.options.agentOptions,
|
||||
...options.agentOptions
|
||||
};
|
||||
delete options.modelOptions;
|
||||
delete options.agentOptions;
|
||||
// now we can merge options
|
||||
this.options = {
|
||||
...this.options,
|
||||
...options
|
||||
};
|
||||
} else {
|
||||
this.options = options;
|
||||
}
|
||||
|
||||
this.agentOptions = this.options.agentOptions || {};
|
||||
this.agentIsGpt3 = this.agentOptions.model.startsWith('gpt-3');
|
||||
const modelOptions = this.options.modelOptions || {};
|
||||
this.modelOptions = {
|
||||
...modelOptions,
|
||||
model: modelOptions.model || 'gpt-3.5-turbo',
|
||||
temperature: typeof modelOptions.temperature === 'undefined' ? 0.8 : modelOptions.temperature,
|
||||
top_p: typeof modelOptions.top_p === 'undefined' ? 1 : modelOptions.top_p,
|
||||
presence_penalty:
|
||||
typeof modelOptions.presence_penalty === 'undefined' ? 0 : modelOptions.presence_penalty,
|
||||
frequency_penalty:
|
||||
typeof modelOptions.frequency_penalty === 'undefined' ? 0 : modelOptions.frequency_penalty,
|
||||
stop: modelOptions.stop
|
||||
};
|
||||
|
||||
this.isChatGptModel = this.modelOptions.model.startsWith('gpt-');
|
||||
this.isGpt3 = this.modelOptions.model.startsWith('gpt-3');
|
||||
this.maxContextTokens = this.modelOptions.model === 'gpt-4-32k' ? 32767 : this.modelOptions.model.startsWith('gpt-4') ? 8191 : 4095,
|
||||
|
||||
// Reserve 1024 tokens for the response.
|
||||
// The max prompt tokens is determined by the max context tokens minus the max response tokens.
|
||||
// Earlier messages will be dropped until the prompt is within the limit.
|
||||
this.maxResponseTokens = this.modelOptions.max_tokens || 1024;
|
||||
this.maxPromptTokens =
|
||||
this.options.maxPromptTokens || this.maxContextTokens - this.maxResponseTokens;
|
||||
|
||||
if (this.maxPromptTokens + this.maxResponseTokens > this.maxContextTokens) {
|
||||
throw new Error(
|
||||
`maxPromptTokens + max_tokens (${this.maxPromptTokens} + ${this.maxResponseTokens} = ${
|
||||
this.maxPromptTokens + this.maxResponseTokens
|
||||
}) must be less than or equal to maxContextTokens (${this.maxContextTokens})`
|
||||
);
|
||||
}
|
||||
|
||||
this.userLabel = this.options.userLabel || 'User';
|
||||
this.chatGptLabel = this.options.chatGptLabel || 'ChatGPT';
|
||||
|
||||
// Use these faux tokens to help the AI understand the context since we are building the chat log ourselves.
|
||||
// Trying to use "<|im_start|>" causes the AI to still generate "<" or "<|" at the end sometimes for some reason,
|
||||
// without tripping the stop sequences, so I'm using "||>" instead.
|
||||
this.startToken = '||>';
|
||||
this.endToken = '';
|
||||
this.gptEncoder = this.constructor.getTokenizer('cl100k_base');
|
||||
this.completionsUrl = 'https://api.openai.com/v1/chat/completions';
|
||||
this.reverseProxyUrl = this.options.reverseProxyUrl || process.env.OPENAI_REVERSE_PROXY;
|
||||
|
||||
if (this.reverseProxyUrl) {
|
||||
this.completionsUrl = this.reverseProxyUrl;
|
||||
this.langchainProxy = this.reverseProxyUrl.substring(0, this.reverseProxyUrl.indexOf('v1') + 'v1'.length)
|
||||
}
|
||||
|
||||
if (this.azureEndpoint) {
|
||||
this.completionsUrl = this.azureEndpoint;
|
||||
}
|
||||
|
||||
if (this.azureEndpoint && this.options.debug) {
|
||||
console.debug(`Using Azure endpoint: ${this.azureEndpoint}`, this.azure);
|
||||
}
|
||||
}
|
||||
|
||||
static getTokenizer(encoding, isModelName = false, extendSpecialTokens = {}) {
|
||||
if (tokenizersCache[encoding]) {
|
||||
return tokenizersCache[encoding];
|
||||
}
|
||||
let tokenizer;
|
||||
if (isModelName) {
|
||||
tokenizer = encodingForModel(encoding, extendSpecialTokens);
|
||||
} else {
|
||||
tokenizer = getEncoding(encoding, extendSpecialTokens);
|
||||
}
|
||||
tokenizersCache[encoding] = tokenizer;
|
||||
return tokenizer;
|
||||
}
|
||||
|
||||
async getCompletion(input, onProgress, abortController = null) {
|
||||
if (!abortController) {
|
||||
abortController = new AbortController();
|
||||
}
|
||||
|
||||
const modelOptions = this.modelOptions;
|
||||
if (typeof onProgress === 'function') {
|
||||
modelOptions.stream = true;
|
||||
}
|
||||
if (this.isChatGptModel) {
|
||||
modelOptions.messages = input;
|
||||
} else {
|
||||
modelOptions.prompt = input;
|
||||
}
|
||||
const { debug } = this.options;
|
||||
const url = this.completionsUrl;
|
||||
if (debug) {
|
||||
console.debug();
|
||||
console.debug(url);
|
||||
console.debug(modelOptions);
|
||||
console.debug();
|
||||
}
|
||||
const opts = {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json'
|
||||
},
|
||||
body: JSON.stringify(modelOptions),
|
||||
dispatcher: new Agent({
|
||||
bodyTimeout: 0,
|
||||
headersTimeout: 0
|
||||
})
|
||||
};
|
||||
|
||||
if (this.azureEndpoint) {
|
||||
opts.headers['api-key'] = this.azure.azureOpenAIApiKey;
|
||||
} else if (this.openAIApiKey) {
|
||||
opts.headers.Authorization = `Bearer ${this.openAIApiKey}`;
|
||||
}
|
||||
|
||||
if (this.options.proxy) {
|
||||
opts.dispatcher = new ProxyAgent(this.options.proxy);
|
||||
}
|
||||
|
||||
if (modelOptions.stream) {
|
||||
// eslint-disable-next-line no-async-promise-executor
|
||||
return new Promise(async (resolve, reject) => {
|
||||
try {
|
||||
let done = false;
|
||||
await fetchEventSource(url, {
|
||||
...opts,
|
||||
signal: abortController.signal,
|
||||
async onopen(response) {
|
||||
if (response.status === 200) {
|
||||
return;
|
||||
}
|
||||
if (debug) {
|
||||
// console.debug(response);
|
||||
}
|
||||
let error;
|
||||
try {
|
||||
const body = await response.text();
|
||||
error = new Error(`Failed to send message. HTTP ${response.status} - ${body}`);
|
||||
error.status = response.status;
|
||||
error.json = JSON.parse(body);
|
||||
} catch {
|
||||
error = error || new Error(`Failed to send message. HTTP ${response.status}`);
|
||||
}
|
||||
throw error;
|
||||
},
|
||||
onclose() {
|
||||
if (debug) {
|
||||
console.debug('Server closed the connection unexpectedly, returning...');
|
||||
}
|
||||
// workaround for private API not sending [DONE] event
|
||||
if (!done) {
|
||||
onProgress('[DONE]');
|
||||
abortController.abort();
|
||||
resolve();
|
||||
}
|
||||
},
|
||||
onerror(err) {
|
||||
if (debug) {
|
||||
console.debug(err);
|
||||
}
|
||||
// rethrow to stop the operation
|
||||
throw err;
|
||||
},
|
||||
onmessage(message) {
|
||||
if (debug) {
|
||||
// console.debug(message);
|
||||
}
|
||||
if (!message.data || message.event === 'ping') {
|
||||
return;
|
||||
}
|
||||
if (message.data === '[DONE]') {
|
||||
onProgress('[DONE]');
|
||||
abortController.abort();
|
||||
resolve();
|
||||
done = true;
|
||||
return;
|
||||
}
|
||||
onProgress(JSON.parse(message.data));
|
||||
}
|
||||
});
|
||||
} catch (err) {
|
||||
reject(err);
|
||||
}
|
||||
});
|
||||
}
|
||||
const response = await fetch(url, {
|
||||
...opts,
|
||||
signal: abortController.signal
|
||||
});
|
||||
if (response.status !== 200) {
|
||||
const body = await response.text();
|
||||
const error = new Error(`Failed to send message. HTTP ${response.status} - ${body}`);
|
||||
error.status = response.status;
|
||||
try {
|
||||
error.json = JSON.parse(body);
|
||||
} catch {
|
||||
error.body = body;
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
return response.json();
|
||||
}
|
||||
|
||||
async loadHistory(conversationId, parentMessageId = null) {
|
||||
if (this.options.debug) {
|
||||
console.debug('Loading history for conversation', conversationId, parentMessageId);
|
||||
}
|
||||
|
||||
const messages = (await getMessages({ conversationId })) || [];
|
||||
|
||||
if (messages.length === 0) {
|
||||
this.currentMessages = [];
|
||||
return [];
|
||||
}
|
||||
|
||||
const orderedMessages = this.constructor.getMessagesForConversation(messages, parentMessageId);
|
||||
// Convert Message documents into appropriate ChatMessage instances
|
||||
const chatMessages = orderedMessages.map((msg) =>
|
||||
msg?.isCreatedByUser || msg?.role.toLowerCase() === 'user'
|
||||
? new HumanChatMessage(msg.text)
|
||||
: new AIChatMessage(msg.text)
|
||||
);
|
||||
|
||||
this.currentMessages = orderedMessages;
|
||||
|
||||
return chatMessages;
|
||||
}
|
||||
|
||||
async saveMessageToDatabase(message, user = null) {
|
||||
await saveMessage({ ...message, unfinished: false });
|
||||
await saveConvo(user, {
|
||||
conversationId: message.conversationId,
|
||||
endpoint: 'gptPlugins',
|
||||
chatGptLabel: this.options.chatGptLabel,
|
||||
promptPrefix: this.options.promptPrefix,
|
||||
...this.modelOptions,
|
||||
agentOptions: this.agentOptions
|
||||
});
|
||||
}
|
||||
|
||||
saveLatestAction(action) {
|
||||
this.actions.push(action);
|
||||
}
|
||||
|
||||
async initialize({ user, message, onAgentAction, onChainEnd, signal }) {
|
||||
const modelOptions = {
|
||||
modelName: this.agentOptions.model,
|
||||
temperature: this.agentOptions.temperature
|
||||
};
|
||||
|
||||
const configOptions = {};
|
||||
|
||||
if (this.langchainProxy) {
|
||||
configOptions.basePath = this.langchainProxy;
|
||||
}
|
||||
|
||||
const model = this.azure
|
||||
? new ChatOpenAI({
|
||||
...this.azure,
|
||||
...modelOptions
|
||||
})
|
||||
: new ChatOpenAI(
|
||||
{
|
||||
openAIApiKey: this.openAIApiKey,
|
||||
...modelOptions
|
||||
},
|
||||
configOptions
|
||||
// {
|
||||
// basePath: 'http://localhost:8080/v1'
|
||||
// }
|
||||
);
|
||||
|
||||
if (this.options.debug) {
|
||||
console.debug(`<-----Agent Model: ${model.modelName} | Temp: ${model.temperature}----->`);
|
||||
}
|
||||
|
||||
this.availableTools = await loadTools({
|
||||
user,
|
||||
model,
|
||||
tools: this.options.tools,
|
||||
options: {
|
||||
openAIApiKey: this.openAIApiKey
|
||||
}
|
||||
});
|
||||
// load tools
|
||||
for (const tool of this.options.tools) {
|
||||
const validTool = this.availableTools[tool];
|
||||
|
||||
if (tool === 'plugins') {
|
||||
const plugins = await validTool();
|
||||
this.tools = [...this.tools, ...plugins];
|
||||
} else if (validTool) {
|
||||
this.tools.push(await validTool());
|
||||
}
|
||||
}
|
||||
|
||||
if (this.options.debug) {
|
||||
console.debug('Requested Tools');
|
||||
console.debug(this.options.tools);
|
||||
console.debug('Loaded Tools');
|
||||
console.debug(this.tools.map((tool) => tool.name));
|
||||
}
|
||||
|
||||
if (this.tools.length > 0) {
|
||||
this.tools.push(new SelfReflectionTool({ message, isGpt3: false }));
|
||||
} else if (this.tools.length === 0) {
|
||||
return;
|
||||
}
|
||||
|
||||
const handleAction = (action, callback = null) => {
|
||||
this.saveLatestAction(action);
|
||||
|
||||
if (this.options.debug) {
|
||||
console.debug('Latest Agent Action ', this.actions[this.actions.length - 1]);
|
||||
}
|
||||
|
||||
if (typeof callback === 'function') {
|
||||
callback(action);
|
||||
}
|
||||
};
|
||||
|
||||
// initialize agent
|
||||
this.executor = await initializeCustomAgent({
|
||||
model,
|
||||
signal,
|
||||
tools: this.tools,
|
||||
pastMessages: this.pastMessages,
|
||||
currentDateString: this.currentDateString,
|
||||
verbose: this.options.debug,
|
||||
returnIntermediateSteps: true,
|
||||
callbackManager: CallbackManager.fromHandlers({
|
||||
async handleAgentAction(action) {
|
||||
handleAction(action, onAgentAction);
|
||||
},
|
||||
async handleChainEnd(action) {
|
||||
if (typeof onChainEnd === 'function') {
|
||||
onChainEnd(action);
|
||||
}
|
||||
}
|
||||
})
|
||||
});
|
||||
|
||||
if (this.options.debug) {
|
||||
console.debug('Loaded agent.');
|
||||
}
|
||||
}
|
||||
|
||||
async sendApiMessage(messages, userMessage, opts = {}) {
|
||||
// Doing it this way instead of having each message be a separate element in the array seems to be more reliable,
|
||||
// especially when it comes to keeping the AI in character. It also seems to improve coherency and context retention.
|
||||
let payload = await this.buildPrompt({
|
||||
messages: [
|
||||
...messages,
|
||||
{
|
||||
messageId: userMessage.messageId,
|
||||
parentMessageId: userMessage.parentMessageId,
|
||||
role: 'User',
|
||||
text: userMessage.text
|
||||
}
|
||||
],
|
||||
...opts
|
||||
});
|
||||
|
||||
let reply = '';
|
||||
let result = {};
|
||||
if (typeof opts.onProgress === 'function') {
|
||||
await this.getCompletion(
|
||||
payload,
|
||||
(progressMessage) => {
|
||||
if (progressMessage === '[DONE]') {
|
||||
return;
|
||||
}
|
||||
const token = this.isChatGptModel
|
||||
? progressMessage.choices[0].delta.content
|
||||
: progressMessage.choices[0].text;
|
||||
// first event's delta content is always undefined
|
||||
if (!token) {
|
||||
return;
|
||||
}
|
||||
|
||||
if (token === this.endToken) {
|
||||
return;
|
||||
}
|
||||
opts.onProgress(token);
|
||||
reply += token;
|
||||
},
|
||||
opts.abortController || new AbortController()
|
||||
);
|
||||
} else {
|
||||
result = await this.getCompletion(
|
||||
payload,
|
||||
null,
|
||||
opts.abortController || new AbortController()
|
||||
);
|
||||
if (this.options.debug) {
|
||||
console.debug(JSON.stringify(result));
|
||||
}
|
||||
if (this.isChatGptModel) {
|
||||
reply = result.choices[0].message.content;
|
||||
} else {
|
||||
reply = result.choices[0].text.replace(this.endToken, '');
|
||||
}
|
||||
}
|
||||
|
||||
if (this.options.debug) {
|
||||
console.debug();
|
||||
}
|
||||
|
||||
return reply.trim();
|
||||
}
|
||||
|
||||
async executorCall(message, signal) {
|
||||
let errorMessage = '';
|
||||
const maxAttempts = 1;
|
||||
|
||||
for (let attempts = 1; attempts <= maxAttempts; attempts++) {
|
||||
const errorInput = this.buildErrorInput(message, errorMessage);
|
||||
const input = attempts > 1 ? errorInput : message;
|
||||
|
||||
if (this.options.debug) {
|
||||
console.debug(`Attempt ${attempts} of ${maxAttempts}`);
|
||||
}
|
||||
|
||||
if (this.options.debug && errorMessage.length > 0) {
|
||||
console.debug('Caught error, input:', input);
|
||||
}
|
||||
|
||||
try {
|
||||
this.result = await this.executor.call({ input, signal });
|
||||
break; // Exit the loop if the function call is successful
|
||||
} catch (err) {
|
||||
console.error(err);
|
||||
errorMessage = err.message;
|
||||
if (attempts === maxAttempts) {
|
||||
this.result.output = `Encountered an error while attempting to respond. Error: ${err.message}`;
|
||||
this.result.intermediateSteps = this.actions;
|
||||
this.result.errorMessage = errorMessage;
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
async sendMessage(message, opts = {}) {
|
||||
if (opts && typeof opts === 'object') {
|
||||
this.setOptions(opts);
|
||||
}
|
||||
console.log('sendMessage', message, opts);
|
||||
|
||||
const user = opts.user || null;
|
||||
const { onAgentAction, onChainEnd, onProgress } = opts;
|
||||
const conversationId = opts.conversationId || crypto.randomUUID();
|
||||
const parentMessageId = opts.parentMessageId || '00000000-0000-0000-0000-000000000000';
|
||||
const userMessageId = opts.overrideParentMessageId || crypto.randomUUID();
|
||||
const responseMessageId = crypto.randomUUID();
|
||||
this.pastMessages = await this.loadHistory(conversationId, this.options?.parentMessageId);
|
||||
|
||||
const userMessage = {
|
||||
messageId: userMessageId,
|
||||
parentMessageId,
|
||||
conversationId,
|
||||
sender: 'User',
|
||||
text: message,
|
||||
isCreatedByUser: true
|
||||
};
|
||||
|
||||
if (typeof opts?.getIds === 'function') {
|
||||
opts.getIds({
|
||||
userMessage,
|
||||
conversationId,
|
||||
responseMessageId
|
||||
});
|
||||
}
|
||||
|
||||
if (typeof opts?.onStart === 'function') {
|
||||
opts.onStart(userMessage);
|
||||
}
|
||||
|
||||
await this.saveMessageToDatabase(userMessage, user);
|
||||
|
||||
this.result = {};
|
||||
const responseMessage = {
|
||||
messageId: responseMessageId,
|
||||
conversationId,
|
||||
parentMessageId: userMessage.messageId,
|
||||
isCreatedByUser: false,
|
||||
model: this.modelOptions.model,
|
||||
sender: 'ChatGPT'
|
||||
};
|
||||
|
||||
if (this.options.debug) {
|
||||
console.debug('options');
|
||||
console.debug(this.options);
|
||||
}
|
||||
|
||||
const completionMode = this.options.tools.length === 0;
|
||||
if (!completionMode) {
|
||||
await this.initialize({
|
||||
user,
|
||||
message,
|
||||
onAgentAction,
|
||||
onChainEnd,
|
||||
signal: opts.abortController.signal
|
||||
});
|
||||
await this.executorCall(message, opts.abortController.signal);
|
||||
}
|
||||
|
||||
// If message was aborted mid-generation
|
||||
if (this.result?.errorMessage?.length > 0 && this.result?.errorMessage?.includes('cancel')) {
|
||||
responseMessage.text = 'Cancelled.';
|
||||
await this.saveMessageToDatabase(responseMessage, user);
|
||||
return { ...responseMessage, ...this.result };
|
||||
}
|
||||
|
||||
if (!this.agentIsGpt3 && this.result.output) {
|
||||
responseMessage.text = this.result.output;
|
||||
await this.saveMessageToDatabase(responseMessage, user);
|
||||
const textStream = new TextStream(this.result.output);
|
||||
await textStream.processTextStream(onProgress);
|
||||
return { ...responseMessage, ...this.result };
|
||||
}
|
||||
|
||||
if (this.options.debug) {
|
||||
console.debug('this.result', this.result);
|
||||
}
|
||||
|
||||
const userProvidedPrefix = completionMode && this.options?.promptPrefix?.length > 0;
|
||||
const promptPrefix = userProvidedPrefix
|
||||
? this.options.promptPrefix
|
||||
: this.buildPromptPrefix(this.result, message);
|
||||
|
||||
if (this.options.debug) {
|
||||
console.debug('promptPrefix', promptPrefix);
|
||||
}
|
||||
|
||||
const finalReply = await this.sendApiMessage(this.currentMessages, userMessage, { ...opts, completionMode, promptPrefix });
|
||||
responseMessage.text = finalReply;
|
||||
await this.saveMessageToDatabase(responseMessage, user);
|
||||
return { ...responseMessage, ...this.result };
|
||||
}
|
||||
|
||||
async buildPrompt({ messages, promptPrefix: _promptPrefix, completionMode = false, isChatGptModel = true }) {
|
||||
if (this.options.debug) {
|
||||
console.debug('buildPrompt messages', messages);
|
||||
}
|
||||
|
||||
const orderedMessages = messages;
|
||||
let promptPrefix = _promptPrefix;
|
||||
if (promptPrefix) {
|
||||
promptPrefix = promptPrefix.trim();
|
||||
// If the prompt prefix doesn't end with the end token, add it.
|
||||
if (!promptPrefix.endsWith(`${this.endToken}`)) {
|
||||
promptPrefix = `${promptPrefix.trim()}${this.endToken}\n\n`;
|
||||
}
|
||||
promptPrefix = `${this.startToken}Instructions:\n${promptPrefix}`;
|
||||
} else {
|
||||
promptPrefix = `${this.startToken}${completionInstructions} ${this.currentDateString}${this.endToken}\n\n`;
|
||||
}
|
||||
|
||||
const promptSuffix = `${this.startToken}${this.chatGptLabel}:\n`; // Prompt ChatGPT to respond.
|
||||
|
||||
const instructionsPayload = {
|
||||
role: 'system',
|
||||
name: 'instructions',
|
||||
content: promptPrefix
|
||||
};
|
||||
|
||||
const messagePayload = {
|
||||
role: 'system',
|
||||
content: promptSuffix
|
||||
};
|
||||
|
||||
if (this.isGpt3) {
|
||||
instructionsPayload.role = 'user';
|
||||
messagePayload.role = 'user';
|
||||
}
|
||||
|
||||
if (this.isGpt3 && completionMode) {
|
||||
instructionsPayload.content += `\n${promptSuffix}`;
|
||||
}
|
||||
|
||||
// testing if this works with browser endpoint
|
||||
if (!this.isGpt3 && this.reverseProxyUrl) {
|
||||
instructionsPayload.role = 'user';
|
||||
}
|
||||
|
||||
let currentTokenCount;
|
||||
if (isChatGptModel) {
|
||||
currentTokenCount =
|
||||
this.getTokenCountForMessage(instructionsPayload) +
|
||||
this.getTokenCountForMessage(messagePayload);
|
||||
} else {
|
||||
currentTokenCount = this.getTokenCount(`${promptPrefix}${promptSuffix}`);
|
||||
}
|
||||
let promptBody = '';
|
||||
const maxTokenCount = this.maxPromptTokens;
|
||||
|
||||
// Iterate backwards through the messages, adding them to the prompt until we reach the max token count.
|
||||
// Do this within a recursive async function so that it doesn't block the event loop for too long.
|
||||
const buildPromptBody = async () => {
|
||||
if (currentTokenCount < maxTokenCount && orderedMessages.length > 0) {
|
||||
const message = orderedMessages.pop();
|
||||
// const roleLabel = message.role === 'User' ? this.userLabel : this.chatGptLabel;
|
||||
const roleLabel = message.role;
|
||||
let messageString = `${this.startToken}${roleLabel}:\n${message.text}${this.endToken}\n`;
|
||||
let newPromptBody;
|
||||
if (promptBody || isChatGptModel) {
|
||||
newPromptBody = `${messageString}${promptBody}`;
|
||||
} else {
|
||||
// Always insert prompt prefix before the last user message, if not gpt-3.5-turbo.
|
||||
// This makes the AI obey the prompt instructions better, which is important for custom instructions.
|
||||
// After a bunch of testing, it doesn't seem to cause the AI any confusion, even if you ask it things
|
||||
// like "what's the last thing I wrote?".
|
||||
newPromptBody = `${promptPrefix}${messageString}${promptBody}`;
|
||||
}
|
||||
|
||||
const tokenCountForMessage = this.getTokenCount(messageString);
|
||||
const newTokenCount = currentTokenCount + tokenCountForMessage;
|
||||
if (newTokenCount > maxTokenCount) {
|
||||
if (promptBody) {
|
||||
// This message would put us over the token limit, so don't add it.
|
||||
return false;
|
||||
}
|
||||
// This is the first message, so we can't add it. Just throw an error.
|
||||
throw new Error(
|
||||
`Prompt is too long. Max token count is ${maxTokenCount}, but prompt is ${newTokenCount} tokens long.`
|
||||
);
|
||||
}
|
||||
promptBody = newPromptBody;
|
||||
currentTokenCount = newTokenCount;
|
||||
// wait for next tick to avoid blocking the event loop
|
||||
await new Promise((resolve) => setTimeout(resolve, 0));
|
||||
return buildPromptBody();
|
||||
}
|
||||
return true;
|
||||
};
|
||||
|
||||
await buildPromptBody();
|
||||
|
||||
// const prompt = `${promptBody}${promptSuffix}`;
|
||||
const prompt = promptBody;
|
||||
if (isChatGptModel) {
|
||||
messagePayload.content = prompt;
|
||||
// Add 2 tokens for metadata after all messages have been counted.
|
||||
currentTokenCount += 2;
|
||||
}
|
||||
|
||||
if (this.isGpt3 && messagePayload.content.length > 0) {
|
||||
const context = `Chat History:\n`;
|
||||
messagePayload.content = `${context}${prompt}`;
|
||||
currentTokenCount += this.getTokenCount(context);
|
||||
}
|
||||
|
||||
// Use up to `this.maxContextTokens` tokens (prompt + response), but try to leave `this.maxTokens` tokens for the response.
|
||||
this.modelOptions.max_tokens = Math.min(
|
||||
this.maxContextTokens - currentTokenCount,
|
||||
this.maxResponseTokens
|
||||
);
|
||||
|
||||
if (this.isGpt3 && !completionMode) {
|
||||
messagePayload.content += promptSuffix;
|
||||
return [instructionsPayload, messagePayload];
|
||||
}
|
||||
|
||||
if (isChatGptModel) {
|
||||
const result = [messagePayload, instructionsPayload];
|
||||
return result.filter((message) => message.content.length > 0);
|
||||
}
|
||||
|
||||
this.completionPromptTokens = currentTokenCount;
|
||||
return prompt;
|
||||
}
|
||||
|
||||
getTokenCount(text) {
|
||||
return this.gptEncoder.encode(text, 'all').length;
|
||||
}
|
||||
|
||||
/**
|
||||
* Algorithm adapted from "6. Counting tokens for chat API calls" of
|
||||
* https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
|
||||
*
|
||||
* An additional 2 tokens need to be added for metadata after all messages have been counted.
|
||||
*
|
||||
* @param {*} message
|
||||
*/
|
||||
getTokenCountForMessage(message) {
|
||||
// Map each property of the message to the number of tokens it contains
|
||||
const propertyTokenCounts = Object.entries(message).map(([key, value]) => {
|
||||
// Count the number of tokens in the property value
|
||||
const numTokens = this.getTokenCount(value);
|
||||
|
||||
// Subtract 1 token if the property key is 'name'
|
||||
const adjustment = key === 'name' ? 1 : 0;
|
||||
return numTokens - adjustment;
|
||||
});
|
||||
|
||||
// Sum the number of tokens in all properties and add 4 for metadata
|
||||
return propertyTokenCounts.reduce((a, b) => a + b, 4);
|
||||
}
|
||||
|
||||
/**
|
||||
* Iterate through messages, building an array based on the parentMessageId.
|
||||
* Each message has an id and a parentMessageId. The parentMessageId is the id of the message that this message is a reply to.
|
||||
* @param messages
|
||||
* @param parentMessageId
|
||||
* @returns {*[]} An array containing the messages in the order they should be displayed, starting with the root message.
|
||||
*/
|
||||
static getMessagesForConversation(messages, parentMessageId) {
|
||||
const orderedMessages = [];
|
||||
let currentMessageId = parentMessageId;
|
||||
while (currentMessageId) {
|
||||
// eslint-disable-next-line no-loop-func
|
||||
const message = messages.find((m) => m.messageId === currentMessageId);
|
||||
if (!message) {
|
||||
break;
|
||||
}
|
||||
orderedMessages.unshift(message);
|
||||
currentMessageId = message.parentMessageId;
|
||||
}
|
||||
|
||||
if (orderedMessages.length === 0) {
|
||||
return [];
|
||||
}
|
||||
|
||||
return orderedMessages.map((msg) => ({
|
||||
messageId: msg.messageId,
|
||||
parentMessageId: msg.parentMessageId,
|
||||
role: msg.isCreatedByUser ? 'User' : 'ChatGPT',
|
||||
text: msg.text
|
||||
}));
|
||||
}
|
||||
|
||||
/**
|
||||
* Extracts the action tool values from the intermediate steps array.
|
||||
* Each step object in the array contains an action object with a tool property.
|
||||
* This function returns an array of tool values.
|
||||
*
|
||||
* @param {Object[]} intermediateSteps - An array of intermediate step objects.
|
||||
* @returns {string} An string of action tool values from each step.
|
||||
*/
|
||||
extractToolValues(intermediateSteps) {
|
||||
const tools = intermediateSteps.map((step) => step.action.tool);
|
||||
|
||||
if (tools.length === 0) {
|
||||
return '';
|
||||
}
|
||||
|
||||
const uniqueTools = [...new Set(tools)];
|
||||
|
||||
if (tools.length === 1) {
|
||||
return tools[0] + ' plugin';
|
||||
}
|
||||
|
||||
return uniqueTools.join(' plugin, ');
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = ChatAgent;
|
||||
92
api/app/langchain/ChatAgent.test.js
Normal file
92
api/app/langchain/ChatAgent.test.js
Normal file
@@ -0,0 +1,92 @@
|
||||
const mongoose = require('mongoose');
|
||||
const ChatAgent = require('./ChatAgent');
|
||||
const connectDb = require('../../lib/db/connectDb');
|
||||
const Conversation = require('../../models/Conversation');
|
||||
|
||||
describe('ChatAgent', () => {
|
||||
let TestAgent;
|
||||
let options = {
|
||||
tools: [],
|
||||
modelOptions: {
|
||||
model: 'gpt-3.5-turbo',
|
||||
temperature: 0,
|
||||
max_tokens: 2
|
||||
},
|
||||
agentOptions: {
|
||||
model: 'gpt-3.5-turbo',
|
||||
}
|
||||
};
|
||||
let parentMessageId;
|
||||
let conversationId;
|
||||
const userMessage = 'Hello, ChatGPT!';
|
||||
const apiKey = process.env.OPENAI_API_KEY;
|
||||
|
||||
beforeAll(async () => {
|
||||
await connectDb();
|
||||
});
|
||||
|
||||
beforeEach(() => {
|
||||
TestAgent = new ChatAgent(apiKey, options);
|
||||
});
|
||||
|
||||
afterAll(async () => {
|
||||
// Delete the messages and conversation created by the test
|
||||
await Conversation.deleteConvos(null, { conversationId });
|
||||
await mongoose.connection.close();
|
||||
});
|
||||
|
||||
test('initializes ChatAgent without crashing', () => {
|
||||
expect(TestAgent).toBeInstanceOf(ChatAgent);
|
||||
});
|
||||
|
||||
test('check setOptions function', () => {
|
||||
expect(TestAgent.agentIsGpt3).toBe(true);
|
||||
});
|
||||
|
||||
describe('sendMessage', () => {
|
||||
test('sendMessage should return a response message', async () => {
|
||||
const expectedResult = expect.objectContaining({
|
||||
sender: 'ChatGPT',
|
||||
text: expect.any(String),
|
||||
isCreatedByUser: false,
|
||||
messageId: expect.any(String),
|
||||
parentMessageId: expect.any(String),
|
||||
conversationId: expect.any(String)
|
||||
});
|
||||
|
||||
const response = await TestAgent.sendMessage(userMessage);
|
||||
console.log(response);
|
||||
parentMessageId = response.messageId;
|
||||
conversationId = response.conversationId;
|
||||
expect(response).toEqual(expectedResult);
|
||||
});
|
||||
|
||||
test('sendMessage should work with provided conversationId and parentMessageId', async () => {
|
||||
const userMessage = 'Second message in the conversation';
|
||||
const opts = {
|
||||
conversationId,
|
||||
parentMessageId
|
||||
};
|
||||
|
||||
const expectedResult = expect.objectContaining({
|
||||
sender: 'ChatGPT',
|
||||
text: expect.any(String),
|
||||
isCreatedByUser: false,
|
||||
messageId: expect.any(String),
|
||||
parentMessageId: expect.any(String),
|
||||
conversationId: opts.conversationId
|
||||
});
|
||||
|
||||
const response = await TestAgent.sendMessage(userMessage, opts);
|
||||
parentMessageId = response.messageId;
|
||||
expect(response.conversationId).toEqual(conversationId);
|
||||
expect(response).toEqual(expectedResult);
|
||||
});
|
||||
|
||||
test('should return chat history', async () => {
|
||||
const chatMessages = await TestAgent.loadHistory(conversationId, parentMessageId);
|
||||
expect(TestAgent.currentMessages).toHaveLength(4);
|
||||
expect(chatMessages[0].text).toEqual(userMessage);
|
||||
});
|
||||
});
|
||||
});
|
||||
50
api/app/langchain/agents/CustomAgent/CustomAgent.js
Normal file
50
api/app/langchain/agents/CustomAgent/CustomAgent.js
Normal file
@@ -0,0 +1,50 @@
|
||||
const { ZeroShotAgent } = require('langchain/agents');
|
||||
const { PromptTemplate, renderTemplate } = require('langchain/prompts');
|
||||
const { gpt3, gpt4 } = require('./instructions');
|
||||
|
||||
class CustomAgent extends ZeroShotAgent {
|
||||
constructor(input) {
|
||||
super(input);
|
||||
}
|
||||
|
||||
_stop() {
|
||||
return [`\nObservation:`, `\nObservation 1:`];
|
||||
}
|
||||
|
||||
static createPrompt(tools, opts = {}) {
|
||||
const { currentDateString, model } = opts;
|
||||
const inputVariables = ['input', 'chat_history', 'agent_scratchpad'];
|
||||
|
||||
let prefix, instructions, suffix;
|
||||
if (model.startsWith('gpt-3')) {
|
||||
prefix = gpt3.prefix;
|
||||
instructions = gpt3.instructions;
|
||||
suffix = gpt3.suffix;
|
||||
} else if (model.startsWith('gpt-4')) {
|
||||
prefix = gpt4.prefix;
|
||||
instructions = gpt4.instructions;
|
||||
suffix = gpt4.suffix;
|
||||
}
|
||||
|
||||
const toolStrings = tools
|
||||
.filter((tool) => tool.name !== 'self-reflection')
|
||||
.map((tool) => `${tool.name}: ${tool.description}`)
|
||||
.join('\n');
|
||||
const toolNames = tools.map((tool) => tool.name);
|
||||
const formatInstructions = (0, renderTemplate)(instructions, 'f-string', {
|
||||
tool_names: toolNames
|
||||
});
|
||||
const template = [
|
||||
`Date: ${currentDateString}\n${prefix}`,
|
||||
toolStrings,
|
||||
formatInstructions,
|
||||
suffix
|
||||
].join('\n\n');
|
||||
return new PromptTemplate({
|
||||
template,
|
||||
inputVariables
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = CustomAgent;
|
||||
@@ -0,0 +1,56 @@
|
||||
const CustomAgent = require('./CustomAgent');
|
||||
const { CustomOutputParser } = require('./outputParser');
|
||||
const { AgentExecutor } = require('langchain/agents');
|
||||
const { LLMChain } = require('langchain/chains');
|
||||
const { BufferMemory, ChatMessageHistory } = require('langchain/memory');
|
||||
const {
|
||||
ChatPromptTemplate,
|
||||
SystemMessagePromptTemplate,
|
||||
HumanMessagePromptTemplate
|
||||
} = require('langchain/prompts');
|
||||
|
||||
const initializeCustomAgent = async ({
|
||||
tools,
|
||||
model,
|
||||
pastMessages,
|
||||
currentDateString,
|
||||
...rest
|
||||
}) => {
|
||||
let prompt = CustomAgent.createPrompt(tools, { currentDateString, model: model.modelName });
|
||||
|
||||
const chatPrompt = ChatPromptTemplate.fromPromptMessages([
|
||||
new SystemMessagePromptTemplate(prompt),
|
||||
HumanMessagePromptTemplate.fromTemplate(`{chat_history}
|
||||
Query: {input}
|
||||
{agent_scratchpad}`)
|
||||
]);
|
||||
|
||||
const outputParser = new CustomOutputParser({ tools });
|
||||
|
||||
const memory = new BufferMemory({
|
||||
chatHistory: new ChatMessageHistory(pastMessages),
|
||||
// returnMessages: true, // commenting this out retains memory
|
||||
memoryKey: 'chat_history',
|
||||
humanPrefix: 'User',
|
||||
aiPrefix: 'Assistant',
|
||||
inputKey: 'input',
|
||||
outputKey: 'output'
|
||||
});
|
||||
|
||||
const llmChain = new LLMChain({
|
||||
prompt: chatPrompt,
|
||||
llm: model
|
||||
});
|
||||
|
||||
const agent = new CustomAgent({
|
||||
llmChain,
|
||||
outputParser,
|
||||
allowedTools: tools.map((tool) => tool.name)
|
||||
});
|
||||
|
||||
return AgentExecutor.fromAgentAndTools({ agent, tools, memory, ...rest });
|
||||
};
|
||||
|
||||
module.exports = {
|
||||
initializeCustomAgent
|
||||
};
|
||||
203
api/app/langchain/agents/CustomAgent/instructions.js
Normal file
203
api/app/langchain/agents/CustomAgent/instructions.js
Normal file
@@ -0,0 +1,203 @@
|
||||
/*
|
||||
module.exports = `You are ChatGPT, a Large Language model with useful tools.
|
||||
|
||||
Talk to the human and provide meaningful answers when questions are asked.
|
||||
|
||||
Use the tools when you need them, but use your own knowledge if you are confident of the answer. Keep answers short and concise.
|
||||
|
||||
A tool is not usually needed for creative requests, so do your best to answer them without tools.
|
||||
|
||||
Avoid repeating identical answers if it appears before. Only fulfill the human's requests, do not create extra steps beyond what the human has asked for.
|
||||
|
||||
Your input for 'Action' should be the name of tool used only.
|
||||
|
||||
Be honest. If you can't answer something, or a tool is not appropriate, say you don't know or answer to the best of your ability.
|
||||
|
||||
Attempt to fulfill the human's requests in as few actions as possible`;
|
||||
*/
|
||||
|
||||
// module.exports = `You are ChatGPT, a highly knowledgeable and versatile large language model.
|
||||
|
||||
// Engage with the Human conversationally, providing concise and meaningful answers to questions. Utilize built-in tools when necessary, except for creative requests, where relying on your own knowledge is preferred. Aim for variety and avoid repetitive answers.
|
||||
|
||||
// For your 'Action' input, state the name of the tool used only, and honor user requests without adding extra steps. Always be honest; if you cannot provide an appropriate answer or tool, admit that or do your best.
|
||||
|
||||
// Strive to meet the user's needs efficiently with minimal actions.`;
|
||||
|
||||
// import {
|
||||
// BasePromptTemplate,
|
||||
// BaseStringPromptTemplate,
|
||||
// SerializedBasePromptTemplate,
|
||||
// renderTemplate,
|
||||
// } from "langchain/prompts";
|
||||
|
||||
// prefix: `You are ChatGPT, a highly knowledgeable and versatile large language model.
|
||||
// Your objective is to help users by understanding their intent and choosing the best action. Prioritize direct, specific responses. Use concise, varied answers and rely on your knowledge for creative tasks. Utilize tools when needed, and structure results for machine compatibility.
|
||||
// prefix: `Objective: to comprehend human intentions based on user input and available tools. Goal: identify the best action to directly address the human's query. In your subsequent steps, you will utilize the chosen action. You may select multiple actions and list them in a meaningful order. Prioritize actions that directly relate to the user's query over general ones. Ensure that the generated thought is highly specific and explicit to best match the user's expectations. Construct the result in a manner that an online open-API would most likely expect. Provide concise and meaningful answers to human queries. Utilize tools when necessary. Relying on your own knowledge is preferred for creative requests. Aim for variety and avoid repetitive answers.
|
||||
|
||||
// # Available Actions & Tools:
|
||||
// N/A: no suitable action, use your own knowledge.`,
|
||||
// suffix: `Remember, all your responses MUST adhere to the described format and only respond if the format is followed. Output exactly with the requested format, avoiding any other text as this will be parsed by a machine. Following 'Action:', provide only one of the actions listed above. If a tool is not necessary, deduce this quickly and finish your response. Honor the human's requests without adding extra steps. Carry out tasks in the sequence written by the human. Always be honest; if you cannot provide an appropriate answer or tool, do your best with your own knowledge. Strive to meet the user's needs efficiently with minimal actions.`;
|
||||
|
||||
module.exports = {
|
||||
'gpt3-v1': {
|
||||
prefix: `Objective: Understand human intentions using user input and available tools. Goal: Identify the most suitable actions to directly address user queries.
|
||||
|
||||
When responding:
|
||||
- Choose actions relevant to the user's query, using multiple actions in a logical order if needed.
|
||||
- Prioritize direct and specific thoughts to meet user expectations.
|
||||
- Format results in a way compatible with open-API expectations.
|
||||
- Offer concise, meaningful answers to user queries.
|
||||
- Use tools when necessary but rely on your own knowledge for creative requests.
|
||||
- Strive for variety, avoiding repetitive responses.
|
||||
|
||||
# Available Actions & Tools:
|
||||
N/A: No suitable action; use your own knowledge.`,
|
||||
instructions: `Always adhere to the following format in your response to indicate actions taken:
|
||||
|
||||
Thought: Summarize your thought process.
|
||||
Action: Select an action from [{tool_names}].
|
||||
Action Input: Define the action's input.
|
||||
Observation: Report the action's result.
|
||||
|
||||
Repeat steps 1-4 as needed, in order. When not using a tool, use N/A for Action, provide the result as Action Input, and include an Observation.
|
||||
|
||||
Upon reaching the final answer, use this format after completing all necessary actions:
|
||||
|
||||
Thought: Indicate that you've determined the final answer.
|
||||
Final Answer: Present the answer to the user's query.`,
|
||||
suffix: `Keep these guidelines in mind when crafting your response:
|
||||
- Strictly adhere to the Action format for all responses, as they will be machine-parsed.
|
||||
- If a tool is unnecessary, quickly move to the Thought/Final Answer format.
|
||||
- Follow the logical sequence provided by the user without adding extra steps.
|
||||
- Be honest; if you can't provide an appropriate answer using the given tools, use your own knowledge.
|
||||
- Aim for efficiency and minimal actions to meet the user's needs effectively.`,
|
||||
},
|
||||
'gpt3-v2': {
|
||||
prefix: `Objective: Understand the human's query with available actions & tools. Let's work this out in a step by step way to be sure we fulfill the query.
|
||||
|
||||
When responding:
|
||||
- Choose actions relevant to the user's query, using multiple actions in a logical order if needed.
|
||||
- Prioritize direct and specific thoughts to meet user expectations.
|
||||
- Format results in a way compatible with open-API expectations.
|
||||
- Offer concise, meaningful answers to user queries.
|
||||
- Use tools when necessary but rely on your own knowledge for creative requests.
|
||||
- Strive for variety, avoiding repetitive responses.
|
||||
|
||||
# Available Actions & Tools:
|
||||
N/A: No suitable action; use your own knowledge.`,
|
||||
instructions: `I want you to respond with this format and this format only, without comments or explanations, to indicate actions taken:
|
||||
\`\`\`
|
||||
Thought: Summarize your thought process.
|
||||
Action: Select an action from [{tool_names}].
|
||||
Action Input: Define the action's input.
|
||||
Observation: Report the action's result.
|
||||
\`\`\`
|
||||
|
||||
Repeat the format for each action as needed. When not using a tool, use N/A for Action, provide the result as Action Input, and include an Observation.
|
||||
|
||||
Upon reaching the final answer, use this format after completing all necessary actions:
|
||||
\`\`\`
|
||||
Thought: Indicate that you've determined the final answer.
|
||||
Final Answer: A conversational reply to the user's query as if you were answering them directly.
|
||||
\`\`\``,
|
||||
suffix: `Keep these guidelines in mind when crafting your response:
|
||||
- Strictly adhere to the Action format for all responses, as they will be machine-parsed.
|
||||
- If a tool is unnecessary, quickly move to the Thought/Final Answer format.
|
||||
- Follow the logical sequence provided by the user without adding extra steps.
|
||||
- Be honest; if you can't provide an appropriate answer using the given tools, use your own knowledge.
|
||||
- Aim for efficiency and minimal actions to meet the user's needs effectively.`,
|
||||
},
|
||||
gpt3: {
|
||||
prefix: `Objective: Understand the human's query with available actions & tools. Let's work this out in a step by step way to be sure we fulfill the query.
|
||||
|
||||
Use available actions and tools judiciously.
|
||||
|
||||
# Available Actions & Tools:
|
||||
N/A: No suitable action; use your own knowledge.`,
|
||||
instructions: `I want you to respond with this format and this format only, without comments or explanations, to indicate actions taken:
|
||||
\`\`\`
|
||||
Thought: Your thought process.
|
||||
Action: Action from [{tool_names}].
|
||||
Action Input: Action's input.
|
||||
Observation: Action's result.
|
||||
\`\`\`
|
||||
|
||||
For each action, repeat the format. If no tool is used, use N/A for Action, and provide the result as Action Input.
|
||||
|
||||
Finally, complete with:
|
||||
\`\`\`
|
||||
Thought: Convey final answer determination.
|
||||
Final Answer: Reply to user's query conversationally.
|
||||
\`\`\``,
|
||||
suffix: `Remember:
|
||||
- Adhere to the Action format strictly for parsing.
|
||||
- Transition quickly to Thought/Final Answer format when a tool isn't needed.
|
||||
- Follow user's logic without superfluous steps.
|
||||
- If unable to use tools for a fitting answer, use your knowledge.
|
||||
- Strive for efficient, minimal actions.`,
|
||||
},
|
||||
'gpt4-v1': {
|
||||
prefix: `Objective: Understand the human's query with available actions & tools. Let's work this out in a step by step way to be sure we fulfill the query.
|
||||
|
||||
When responding:
|
||||
- Choose actions relevant to the query, using multiple actions in a step by step way.
|
||||
- Prioritize direct and specific thoughts to meet user expectations.
|
||||
- Be precise and offer meaningful answers to user queries.
|
||||
- Use tools when necessary but rely on your own knowledge for creative requests.
|
||||
- Strive for variety, avoiding repetitive responses.
|
||||
|
||||
# Available Actions & Tools:
|
||||
N/A: No suitable action; use your own knowledge.`,
|
||||
instructions: `I want you to respond with this format and this format only, without comments or explanations, to indicate actions taken:
|
||||
\`\`\`
|
||||
Thought: Summarize your thought process.
|
||||
Action: Select an action from [{tool_names}].
|
||||
Action Input: Define the action's input.
|
||||
Observation: Report the action's result.
|
||||
\`\`\`
|
||||
|
||||
Repeat the format for each action as needed. When not using a tool, use N/A for Action, provide the result as Action Input, and include an Observation.
|
||||
|
||||
Upon reaching the final answer, use this format after completing all necessary actions:
|
||||
\`\`\`
|
||||
Thought: Indicate that you've determined the final answer.
|
||||
Final Answer: A conversational reply to the user's query as if you were answering them directly.
|
||||
\`\`\``,
|
||||
suffix: `Keep these guidelines in mind when crafting your final response:
|
||||
- Strictly adhere to the Action format for all responses.
|
||||
- If a tool is unnecessary, quickly move to the Thought/Final Answer format, only if no further actions are possible or necessary.
|
||||
- Follow the logical sequence provided by the user without adding extra steps.
|
||||
- Be honest: if you can't provide an appropriate answer using the given tools, use your own knowledge.
|
||||
- Aim for efficiency and minimal actions to meet the user's needs effectively.`,
|
||||
},
|
||||
gpt4: {
|
||||
prefix: `Objective: Understand the human's query with available actions & tools. Let's work this out in a step by step way to be sure we fulfill the query.
|
||||
|
||||
Use available actions and tools judiciously.
|
||||
|
||||
# Available Actions & Tools:
|
||||
N/A: No suitable action; use your own knowledge.`,
|
||||
instructions: `Respond in this specific format without extraneous comments:
|
||||
\`\`\`
|
||||
Thought: Your thought process.
|
||||
Action: Action from [{tool_names}].
|
||||
Action Input: Action's input.
|
||||
Observation: Action's result.
|
||||
\`\`\`
|
||||
|
||||
For each action, repeat the format. If no tool is used, use N/A for Action, and provide the result as Action Input.
|
||||
|
||||
Finally, complete with:
|
||||
\`\`\`
|
||||
Thought: Indicate that you've determined the final answer.
|
||||
Final Answer: A conversational reply to the user's query, including your full answer.
|
||||
\`\`\``,
|
||||
suffix: `Remember:
|
||||
- Adhere to the Action format strictly for parsing.
|
||||
- Transition quickly to Thought/Final Answer format when a tool isn't needed.
|
||||
- Follow user's logic without superfluous steps.
|
||||
- If unable to use tools for a fitting answer, use your knowledge.
|
||||
- Strive for efficient, minimal actions.`,
|
||||
},
|
||||
};
|
||||
218
api/app/langchain/agents/CustomAgent/outputParser.js
Normal file
218
api/app/langchain/agents/CustomAgent/outputParser.js
Normal file
@@ -0,0 +1,218 @@
|
||||
const { ZeroShotAgentOutputParser } = require('langchain/agents');
|
||||
|
||||
class CustomOutputParser extends ZeroShotAgentOutputParser {
|
||||
constructor(fields) {
|
||||
super(fields);
|
||||
this.tools = fields.tools;
|
||||
this.longestToolName = '';
|
||||
for (const tool of this.tools) {
|
||||
if (tool.name.length > this.longestToolName.length) {
|
||||
this.longestToolName = tool.name;
|
||||
}
|
||||
}
|
||||
this.finishToolNameRegex = /(?:the\s+)?final\s+answer:\s*/i;
|
||||
this.actionValues =
|
||||
/(?:Action(?: [1-9])?:) ([\s\S]*?)(?:\n(?:Action Input(?: [1-9])?:) ([\s\S]*?))?$/i;
|
||||
this.actionInputRegex = /(?:Action Input(?: *\d*):) ?([\s\S]*?)$/i;
|
||||
this.thoughtRegex = /(?:Thought(?: *\d*):) ?([\s\S]*?)$/i;
|
||||
}
|
||||
|
||||
getValidTool(text) {
|
||||
let result = false;
|
||||
for (const tool of this.tools) {
|
||||
const { name } = tool;
|
||||
const toolIndex = text.indexOf(name);
|
||||
if (toolIndex !== -1) {
|
||||
result = name;
|
||||
break;
|
||||
}
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
checkIfValidTool(text) {
|
||||
let isValidTool = false;
|
||||
for (const tool of this.tools) {
|
||||
const { name } = tool;
|
||||
if (text === name) {
|
||||
isValidTool = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
return isValidTool;
|
||||
}
|
||||
|
||||
async parse(text) {
|
||||
const finalMatch = text.match(this.finishToolNameRegex);
|
||||
// if (text.includes(this.finishToolName)) {
|
||||
// const parts = text.split(this.finishToolName);
|
||||
// const output = parts[parts.length - 1].trim();
|
||||
// return {
|
||||
// returnValues: { output },
|
||||
// log: text
|
||||
// };
|
||||
// }
|
||||
|
||||
if (finalMatch) {
|
||||
const output = text.substring(finalMatch.index + finalMatch[0].length).trim();
|
||||
return {
|
||||
returnValues: { output },
|
||||
log: text
|
||||
};
|
||||
}
|
||||
|
||||
const match = this.actionValues.exec(text); // old v2
|
||||
|
||||
if (!match) {
|
||||
console.log(
|
||||
'\n\n<----------------------HIT NO MATCH PARSING ERROR---------------------->\n\n',
|
||||
match
|
||||
);
|
||||
const thoughts = text.replace(/[tT]hought:/, '').split('\n');
|
||||
// return {
|
||||
// tool: 'self-reflection',
|
||||
// toolInput: thoughts[0],
|
||||
// log: thoughts.slice(1).join('\n')
|
||||
// };
|
||||
|
||||
return {
|
||||
returnValues: { output: thoughts[0] },
|
||||
log: thoughts.slice(1).join('\n')
|
||||
};
|
||||
}
|
||||
|
||||
let selectedTool = match?.[1].trim().toLowerCase();
|
||||
|
||||
if (match && selectedTool === 'n/a') {
|
||||
console.log(
|
||||
'\n\n<----------------------HIT N/A PARSING ERROR---------------------->\n\n',
|
||||
match
|
||||
);
|
||||
return {
|
||||
tool: 'self-reflection',
|
||||
toolInput: match[2]?.trim().replace(/^"+|"+$/g, '') ?? '',
|
||||
log: text
|
||||
};
|
||||
}
|
||||
|
||||
let toolIsValid = this.checkIfValidTool(selectedTool);
|
||||
if (match && !toolIsValid) {
|
||||
console.log(
|
||||
'\n\n<----------------Tool invalid: Re-assigning Selected Tool---------------->\n\n',
|
||||
match
|
||||
);
|
||||
selectedTool = this.getValidTool(selectedTool);
|
||||
}
|
||||
|
||||
if (match && !selectedTool) {
|
||||
console.log(
|
||||
'\n\n<----------------------HIT INVALID TOOL PARSING ERROR---------------------->\n\n',
|
||||
match
|
||||
);
|
||||
selectedTool = 'self-reflection';
|
||||
}
|
||||
|
||||
if (match && !match[2]) {
|
||||
console.log(
|
||||
'\n\n<----------------------HIT NO ACTION INPUT PARSING ERROR---------------------->\n\n',
|
||||
match
|
||||
);
|
||||
|
||||
// In case there is no action input, let's double-check if there is an action input in 'text' variable
|
||||
const actionInputMatch = this.actionInputRegex.exec(text);
|
||||
const thoughtMatch = this.thoughtRegex.exec(text);
|
||||
if (actionInputMatch) {
|
||||
return {
|
||||
tool: selectedTool,
|
||||
toolInput: actionInputMatch[1].trim(),
|
||||
log: text
|
||||
};
|
||||
}
|
||||
|
||||
if (thoughtMatch && !actionInputMatch) {
|
||||
return {
|
||||
tool: selectedTool,
|
||||
toolInput: thoughtMatch[1].trim(),
|
||||
log: text
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
if (match && selectedTool.length > this.longestToolName.length) {
|
||||
console.log('\n\n<----------------------HIT LONG PARSING ERROR---------------------->\n\n');
|
||||
|
||||
let action, input, thought;
|
||||
let firstIndex = Infinity;
|
||||
|
||||
for (const tool of this.tools) {
|
||||
const { name } = tool;
|
||||
const toolIndex = text.indexOf(name);
|
||||
if (toolIndex !== -1 && toolIndex < firstIndex) {
|
||||
firstIndex = toolIndex;
|
||||
action = name;
|
||||
}
|
||||
}
|
||||
|
||||
// In case there is no action input, let's double-check if there is an action input in 'text' variable
|
||||
const actionInputMatch = this.actionInputRegex.exec(text);
|
||||
if (action && actionInputMatch) {
|
||||
console.log(
|
||||
'\n\n<------Matched Action Input in Long Parsing Error------>\n\n',
|
||||
actionInputMatch
|
||||
);
|
||||
return {
|
||||
tool: action,
|
||||
toolInput: actionInputMatch[1].trim().replaceAll('"', ''),
|
||||
log: text
|
||||
};
|
||||
}
|
||||
|
||||
if (action) {
|
||||
const actionEndIndex = text.indexOf('Action:', firstIndex + action.length);
|
||||
const inputText = text
|
||||
.slice(firstIndex + action.length, actionEndIndex !== -1 ? actionEndIndex : undefined)
|
||||
.trim();
|
||||
const inputLines = inputText.split('\n');
|
||||
input = inputLines[0];
|
||||
if (inputLines.length > 1) {
|
||||
thought = inputLines.slice(1).join('\n');
|
||||
}
|
||||
const returnValues = {
|
||||
tool: action,
|
||||
toolInput: input,
|
||||
log: thought || inputText
|
||||
};
|
||||
|
||||
const inputMatch = this.actionValues.exec(returnValues.log); //new
|
||||
if (inputMatch) {
|
||||
console.log('inputMatch');
|
||||
console.dir(inputMatch, { depth: null });
|
||||
returnValues.toolInput = inputMatch[1].replaceAll('"', '').trim();
|
||||
returnValues.log = returnValues.log.replace(this.actionValues, '');
|
||||
}
|
||||
|
||||
return returnValues;
|
||||
} else {
|
||||
console.log('No valid tool mentioned.', this.tools, text);
|
||||
return {
|
||||
tool: 'self-reflection',
|
||||
toolInput: 'Hypothetical actions: \n"' + text + '"\n',
|
||||
log: 'Thought: I need to look at my hypothetical actions and try one'
|
||||
};
|
||||
}
|
||||
|
||||
// if (action && input) {
|
||||
// console.log('Action:', action);
|
||||
// console.log('Input:', input);
|
||||
// }
|
||||
}
|
||||
|
||||
return {
|
||||
tool: selectedTool,
|
||||
toolInput: match[2]?.trim()?.replace(/^"+|"+$/g, '') ?? '',
|
||||
log: text
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = { CustomOutputParser };
|
||||
@@ -0,0 +1,77 @@
|
||||
const {
|
||||
ChainStepExecutor,
|
||||
LLMPlanner,
|
||||
PlanOutputParser,
|
||||
PlanAndExecuteAgentExecutor
|
||||
} = require('langchain/experimental/plan_and_execute');
|
||||
const { LLMChain } = require('langchain/chains');
|
||||
const { ChatAgent, AgentExecutor } = require('langchain/agents');
|
||||
const { BufferMemory, ChatMessageHistory } = require('langchain/memory');
|
||||
const {
|
||||
ChatPromptTemplate,
|
||||
SystemMessagePromptTemplate,
|
||||
HumanMessagePromptTemplate
|
||||
} = require('langchain/prompts');
|
||||
|
||||
const DEFAULT_STEP_EXECUTOR_HUMAN_CHAT_MESSAGE_TEMPLATE = `{chat_history}
|
||||
|
||||
Previous steps: {previous_steps}
|
||||
Current objective: {current_step}
|
||||
{agent_scratchpad}
|
||||
You may extract and combine relevant data from your previous steps when responding to me.`;
|
||||
|
||||
const PLANNER_SYSTEM_PROMPT_MESSAGE_TEMPLATE = [
|
||||
`Let's first understand the problem and devise a plan to solve the problem.`,
|
||||
`Please output the plan starting with the header "Plan:"`,
|
||||
`and then followed by a numbered list of steps.`,
|
||||
`Please make the plan the minimum number of steps required`,
|
||||
`to answer the query or complete the task accurately and precisely.`,
|
||||
`Your steps should be general, and should not require a specific method to solve a step. If the task is a question,`,
|
||||
`the final step in the plan must be the following: "Given the above steps taken,`,
|
||||
`please respond to the original query."`,
|
||||
`At the end of your plan, say "<END_OF_PLAN>"`
|
||||
].join(' ');
|
||||
|
||||
const PLANNER_CHAT_PROMPT = /* #__PURE__ */ ChatPromptTemplate.fromPromptMessages([
|
||||
/* #__PURE__ */ SystemMessagePromptTemplate.fromTemplate(PLANNER_SYSTEM_PROMPT_MESSAGE_TEMPLATE),
|
||||
/* #__PURE__ */ HumanMessagePromptTemplate.fromTemplate(`{input}`)
|
||||
]);
|
||||
|
||||
const initializePAEAgent = async ({ tools: _tools, model: llm, pastMessages, ...rest }) => {
|
||||
//removed currentDateString
|
||||
const tools = _tools.filter((tool) => tool.name !== 'self-reflection');
|
||||
|
||||
const memory = new BufferMemory({
|
||||
chatHistory: new ChatMessageHistory(pastMessages),
|
||||
// returnMessages: true, // commenting this out retains memory
|
||||
memoryKey: 'chat_history',
|
||||
humanPrefix: 'User',
|
||||
aiPrefix: 'Assistant',
|
||||
inputKey: 'input',
|
||||
outputKey: 'output'
|
||||
});
|
||||
|
||||
const plannerLlmChain = new LLMChain({
|
||||
llm,
|
||||
prompt: PLANNER_CHAT_PROMPT,
|
||||
memory
|
||||
});
|
||||
const planner = new LLMPlanner(plannerLlmChain, new PlanOutputParser());
|
||||
|
||||
const agent = ChatAgent.fromLLMAndTools(llm, tools, {
|
||||
humanMessageTemplate: DEFAULT_STEP_EXECUTOR_HUMAN_CHAT_MESSAGE_TEMPLATE
|
||||
});
|
||||
|
||||
const stepExecutor = new ChainStepExecutor(
|
||||
AgentExecutor.fromAgentAndTools({ agent, tools, memory, ...rest })
|
||||
);
|
||||
|
||||
return new PlanAndExecuteAgentExecutor({
|
||||
planner,
|
||||
stepExecutor
|
||||
});
|
||||
};
|
||||
|
||||
module.exports = {
|
||||
initializePAEAgent
|
||||
};
|
||||
31
api/app/langchain/demos/demo-aiplugin.js
Normal file
31
api/app/langchain/demos/demo-aiplugin.js
Normal file
@@ -0,0 +1,31 @@
|
||||
require('dotenv').config();
|
||||
const { ChatOpenAI } = require( "langchain/chat_models/openai");
|
||||
const { initializeAgentExecutorWithOptions } = require( "langchain/agents");
|
||||
const HttpRequestTool = require('../tools/HttpRequestTool');
|
||||
const AIPluginTool = require('../tools/AIPluginTool');
|
||||
|
||||
const run = async () => {
|
||||
const openAIApiKey = process.env.OPENAI_API_KEY;
|
||||
const tools = [
|
||||
new HttpRequestTool(),
|
||||
await AIPluginTool.fromPluginUrl(
|
||||
"https://www.klarna.com/.well-known/ai-plugin.json", new ChatOpenAI({ temperature: 0, openAIApiKey })
|
||||
),
|
||||
];
|
||||
const agent = await initializeAgentExecutorWithOptions(
|
||||
tools,
|
||||
new ChatOpenAI({ temperature: 0, openAIApiKey }),
|
||||
{ agentType: "chat-zero-shot-react-description", verbose: true }
|
||||
);
|
||||
|
||||
const result = await agent.call({
|
||||
input: "what t shirts are available in klarna?",
|
||||
});
|
||||
|
||||
console.log({ result });
|
||||
};
|
||||
|
||||
(async () => {
|
||||
await run();
|
||||
})();
|
||||
|
||||
47
api/app/langchain/demos/demo-yaml.js
Normal file
47
api/app/langchain/demos/demo-yaml.js
Normal file
@@ -0,0 +1,47 @@
|
||||
require('dotenv').config();
|
||||
|
||||
const fs = require( "fs");
|
||||
const yaml = require( "js-yaml");
|
||||
const { OpenAI } = require( "langchain/llms/openai");
|
||||
const { JsonSpec } = require( "langchain/tools");
|
||||
const { createOpenApiAgent, OpenApiToolkit } = require( "langchain/agents");
|
||||
|
||||
const run = async () => {
|
||||
let data;
|
||||
try {
|
||||
const yamlFile = fs.readFileSync("./app/langchain/demos/klarna.yaml", "utf8");
|
||||
data = yaml.load(yamlFile);
|
||||
if (!data) {
|
||||
throw new Error("Failed to load OpenAPI spec");
|
||||
}
|
||||
} catch (e) {
|
||||
console.error(e);
|
||||
return;
|
||||
}
|
||||
|
||||
const headers = {
|
||||
"Content-Type": "application/json",
|
||||
// Authorization: `Bearer ${process.env.OPENAI_API_KEY}`,
|
||||
};
|
||||
const model = new OpenAI({ temperature: 0 });
|
||||
const toolkit = new OpenApiToolkit(new JsonSpec(data), model, headers);
|
||||
const executor = createOpenApiAgent(model, toolkit, { verbose: true });
|
||||
|
||||
const input = `Find me some medium sized blue shirts`;
|
||||
console.log(`Executing with input "${input}"...`);
|
||||
|
||||
const result = await executor.call({ input });
|
||||
console.log(`Got output ${result.output}`);
|
||||
|
||||
console.log(
|
||||
`Got intermediate steps ${JSON.stringify(
|
||||
result.intermediateSteps,
|
||||
null,
|
||||
2
|
||||
)}`
|
||||
);
|
||||
};
|
||||
|
||||
(async () => {
|
||||
await run();
|
||||
})();
|
||||
79
api/app/langchain/demos/klarna.yaml
Normal file
79
api/app/langchain/demos/klarna.yaml
Normal file
@@ -0,0 +1,79 @@
|
||||
openapi: 3.0.1
|
||||
servers:
|
||||
- url: https://www.klarna.com/us/shopping
|
||||
info:
|
||||
title: Open AI Klarna product Api
|
||||
version: v0
|
||||
x-apisguru-categories:
|
||||
- ecommerce
|
||||
x-logo:
|
||||
url: https://www.klarna.com/static/img/social-prod-imagery-blinds-beauty-default.jpg
|
||||
x-origin:
|
||||
- format: openapi
|
||||
url: https://www.klarna.com/us/shopping/public/openai/v0/api-docs/
|
||||
version: "3.0"
|
||||
x-providerName: klarna.com
|
||||
x-serviceName: openai
|
||||
tags:
|
||||
- description: Open AI Product Endpoint. Query for products.
|
||||
name: open-ai-product-endpoint
|
||||
paths:
|
||||
/public/openai/v0/products:
|
||||
get:
|
||||
deprecated: false
|
||||
operationId: productsUsingGET
|
||||
parameters:
|
||||
- description: A precise query that matches one very small category or product that needs to be searched for to find the products the user is looking for. If the user explicitly stated what they want, use that as a query. The query is as specific as possible to the product name or category mentioned by the user in its singular form, and don't contain any clarifiers like latest, newest, cheapest, budget, premium, expensive or similar. The query is always taken from the latest topic, if there is a new topic a new query is started.
|
||||
in: query
|
||||
name: q
|
||||
required: true
|
||||
schema:
|
||||
type: string
|
||||
- description: number of products returned
|
||||
in: query
|
||||
name: size
|
||||
required: false
|
||||
schema:
|
||||
type: integer
|
||||
- description: maximum price of the matching product in local currency, filters results
|
||||
in: query
|
||||
name: budget
|
||||
required: false
|
||||
schema:
|
||||
type: integer
|
||||
responses:
|
||||
"200":
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
$ref: "#/components/schemas/ProductResponse"
|
||||
description: Products found
|
||||
"503":
|
||||
description: one or more services are unavailable
|
||||
summary: API for fetching Klarna product information
|
||||
tags:
|
||||
- open-ai-product-endpoint
|
||||
components:
|
||||
schemas:
|
||||
Product:
|
||||
properties:
|
||||
attributes:
|
||||
items:
|
||||
type: string
|
||||
type: array
|
||||
name:
|
||||
type: string
|
||||
price:
|
||||
type: string
|
||||
url:
|
||||
type: string
|
||||
title: Product
|
||||
type: object
|
||||
ProductResponse:
|
||||
properties:
|
||||
products:
|
||||
items:
|
||||
$ref: "#/components/schemas/Product"
|
||||
type: array
|
||||
title: ProductResponse
|
||||
type: object
|
||||
32
api/app/langchain/demos/planExecutor.js
Normal file
32
api/app/langchain/demos/planExecutor.js
Normal file
@@ -0,0 +1,32 @@
|
||||
require('dotenv').config();
|
||||
const { Calculator } = require('langchain/tools/calculator');
|
||||
const { SerpAPI } = require('langchain/tools');
|
||||
const { ChatOpenAI } = require('langchain/chat_models/openai');
|
||||
const { PlanAndExecuteAgentExecutor } = require('langchain/experimental/plan_and_execute');
|
||||
|
||||
const tools = [
|
||||
new Calculator(),
|
||||
new SerpAPI(process.env.SERPAPI_API_KEY || '', {
|
||||
location: 'Austin,Texas,United States',
|
||||
hl: 'en',
|
||||
gl: 'us'
|
||||
})
|
||||
];
|
||||
const model = new ChatOpenAI({
|
||||
temperature: 0,
|
||||
modelName: 'gpt-3.5-turbo',
|
||||
verbose: true,
|
||||
openAIApiKey: process.env.OPENAI_API_KEY
|
||||
});
|
||||
const executor = PlanAndExecuteAgentExecutor.fromLLMAndTools({
|
||||
llm: model,
|
||||
tools
|
||||
});
|
||||
|
||||
(async () => {
|
||||
const result = await executor.call({
|
||||
input: `Who is the current president of the United States? What is their current age raised to the second power?`
|
||||
});
|
||||
|
||||
console.log({ result });
|
||||
})();
|
||||
7305
api/app/langchain/demos/spotify.yaml
Normal file
7305
api/app/langchain/demos/spotify.yaml
Normal file
File diff suppressed because it is too large
Load Diff
6
api/app/langchain/instructions.js
Normal file
6
api/app/langchain/instructions.js
Normal file
@@ -0,0 +1,6 @@
|
||||
module.exports = {
|
||||
instructions: `Remember, all your responses MUST be in the format described. Do not respond unless it's in the format described, using the structure of Action, Action Input, etc.`,
|
||||
errorInstructions: `\nYou encountered an error in attempting a response. The user is not aware of the error so you shouldn't mention it.\nReview the actions taken carefully in case there is a partial or complete answer within them.\nError Message:`,
|
||||
imageInstructions: 'You must include the exact image paths from above, formatted in Markdown syntax: ',
|
||||
completionInstructions: `Instructions:\nYou are ChatGPT, a large language model trained by OpenAI. Respond conversationally.\nCurrent date:`,
|
||||
};
|
||||
237
api/app/langchain/tools/AIPluginTool.js
Normal file
237
api/app/langchain/tools/AIPluginTool.js
Normal file
@@ -0,0 +1,237 @@
|
||||
const { Tool } = require('langchain/tools');
|
||||
const yaml = require('js-yaml');
|
||||
|
||||
/*
|
||||
export interface AIPluginToolParams {
|
||||
name: string;
|
||||
description: string;
|
||||
apiSpec: string;
|
||||
openaiSpec: string;
|
||||
model: BaseLanguageModel;
|
||||
}
|
||||
|
||||
|
||||
export interface PathParameter {
|
||||
name: string;
|
||||
description: string;
|
||||
}
|
||||
|
||||
export interface Info {
|
||||
title: string;
|
||||
description: string;
|
||||
version: string;
|
||||
}
|
||||
export interface PathMethod {
|
||||
summary: string;
|
||||
operationId: string;
|
||||
parameters?: PathParameter[];
|
||||
}
|
||||
|
||||
interface ApiSpec {
|
||||
openapi: string;
|
||||
info: Info;
|
||||
paths: { [key: string]: { [key: string]: PathMethod } };
|
||||
}
|
||||
*/
|
||||
|
||||
function isJson(str) {
|
||||
try {
|
||||
JSON.parse(str);
|
||||
} catch (e) {
|
||||
return false;
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
function convertJsonToYamlIfApplicable(spec) {
|
||||
if (isJson(spec)) {
|
||||
const jsonData = JSON.parse(spec);
|
||||
return yaml.dump(jsonData);
|
||||
}
|
||||
return spec;
|
||||
}
|
||||
|
||||
function extractShortVersion(openapiSpec) {
|
||||
openapiSpec = convertJsonToYamlIfApplicable(openapiSpec);
|
||||
try {
|
||||
const fullApiSpec = yaml.load(openapiSpec);
|
||||
const shortApiSpec = {
|
||||
openapi: fullApiSpec.openapi,
|
||||
info: fullApiSpec.info,
|
||||
paths: {}
|
||||
};
|
||||
|
||||
for (let path in fullApiSpec.paths) {
|
||||
shortApiSpec.paths[path] = {};
|
||||
for (let method in fullApiSpec.paths[path]) {
|
||||
shortApiSpec.paths[path][method] = {
|
||||
summary: fullApiSpec.paths[path][method].summary,
|
||||
operationId: fullApiSpec.paths[path][method].operationId,
|
||||
parameters: fullApiSpec.paths[path][method].parameters?.map((parameter) => ({
|
||||
name: parameter.name,
|
||||
description: parameter.description
|
||||
}))
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
return yaml.dump(shortApiSpec);
|
||||
} catch (e) {
|
||||
console.log(e);
|
||||
return '';
|
||||
}
|
||||
}
|
||||
function printOperationDetails(operationId, openapiSpec) {
|
||||
openapiSpec = convertJsonToYamlIfApplicable(openapiSpec);
|
||||
let returnText = '';
|
||||
try {
|
||||
let doc = yaml.load(openapiSpec);
|
||||
let servers = doc.servers;
|
||||
let paths = doc.paths;
|
||||
let components = doc.components;
|
||||
|
||||
for (let path in paths) {
|
||||
for (let method in paths[path]) {
|
||||
let operation = paths[path][method];
|
||||
if (operation.operationId === operationId) {
|
||||
returnText += `The API request to do for operationId "${operationId}" is:\n`;
|
||||
returnText += `Method: ${method.toUpperCase()}\n`;
|
||||
|
||||
let url = servers[0].url + path;
|
||||
returnText += `Path: ${url}\n`;
|
||||
|
||||
returnText += 'Parameters:\n';
|
||||
if (operation.parameters) {
|
||||
for (let param of operation.parameters) {
|
||||
let required = param.required ? '' : ' (optional),';
|
||||
returnText += `- ${param.name} (${param.in},${required} ${param.schema.type}): ${param.description}\n`;
|
||||
}
|
||||
} else {
|
||||
returnText += ' None\n';
|
||||
}
|
||||
returnText += '\n';
|
||||
|
||||
let responseSchema = operation.responses['200'].content['application/json'].schema;
|
||||
|
||||
// Check if schema is a reference
|
||||
if (responseSchema.$ref) {
|
||||
// Extract schema name from reference
|
||||
let schemaName = responseSchema.$ref.split('/').pop();
|
||||
// Look up schema in components
|
||||
responseSchema = components.schemas[schemaName];
|
||||
}
|
||||
|
||||
returnText += 'Response schema:\n';
|
||||
returnText += '- Type: ' + responseSchema.type + '\n';
|
||||
returnText += '- Additional properties:\n';
|
||||
returnText += ' - Type: ' + responseSchema.additionalProperties?.type + '\n';
|
||||
if (responseSchema.additionalProperties?.properties) {
|
||||
returnText += ' - Properties:\n';
|
||||
for (let prop in responseSchema.additionalProperties.properties) {
|
||||
returnText += ` - ${prop} (${responseSchema.additionalProperties.properties[prop].type}): Description not provided in OpenAPI spec\n`;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
if (returnText === '') {
|
||||
returnText += `No operation with operationId "${operationId}" found.`;
|
||||
}
|
||||
return returnText;
|
||||
} catch (e) {
|
||||
console.log(e);
|
||||
return '';
|
||||
}
|
||||
}
|
||||
|
||||
class AIPluginTool extends Tool {
|
||||
/*
|
||||
private _name: string;
|
||||
private _description: string;
|
||||
apiSpec: string;
|
||||
openaiSpec: string;
|
||||
model: BaseLanguageModel;
|
||||
*/
|
||||
|
||||
get name() {
|
||||
return this._name;
|
||||
}
|
||||
|
||||
get description() {
|
||||
return this._description;
|
||||
}
|
||||
|
||||
constructor(params) {
|
||||
super();
|
||||
this._name = params.name;
|
||||
this._description = params.description;
|
||||
this.apiSpec = params.apiSpec;
|
||||
this.openaiSpec = params.openaiSpec;
|
||||
this.model = params.model;
|
||||
}
|
||||
|
||||
async _call(input) {
|
||||
let date = new Date();
|
||||
let fullDate = `Date: ${date.getDate()}/${
|
||||
date.getMonth() + 1
|
||||
}/${date.getFullYear()}, Time: ${date.getHours()}:${date.getMinutes()}:${date.getSeconds()}`;
|
||||
const prompt = `${fullDate}\nQuestion: ${input} \n${this.apiSpec}.`;
|
||||
console.log(prompt);
|
||||
const gptResponse = await this.model.predict(prompt);
|
||||
let operationId = gptResponse.match(/operationId: (.*)/)?.[1];
|
||||
if (!operationId) {
|
||||
return 'No operationId found in the response';
|
||||
}
|
||||
if (operationId == 'No API path found to answer the question') {
|
||||
return 'No API path found to answer the question';
|
||||
}
|
||||
|
||||
let openApiData = printOperationDetails(operationId, this.openaiSpec);
|
||||
|
||||
return openApiData;
|
||||
}
|
||||
|
||||
static async fromPluginUrl(url, model) {
|
||||
const aiPluginRes = await fetch(url, {});
|
||||
if (!aiPluginRes.ok) {
|
||||
throw new Error(`Failed to fetch plugin from ${url} with status ${aiPluginRes.status}`);
|
||||
}
|
||||
const aiPluginJson = await aiPluginRes.json();
|
||||
const apiUrlRes = await fetch(aiPluginJson.api.url, {});
|
||||
if (!apiUrlRes.ok) {
|
||||
throw new Error(
|
||||
`Failed to fetch API spec from ${aiPluginJson.api.url} with status ${apiUrlRes.status}`
|
||||
);
|
||||
}
|
||||
const apiUrlJson = await apiUrlRes.text();
|
||||
const shortApiSpec = extractShortVersion(apiUrlJson);
|
||||
return new AIPluginTool({
|
||||
name: aiPluginJson.name_for_model.toLowerCase(),
|
||||
description: `A \`tool\` to learn the API documentation for ${aiPluginJson.name_for_model.toLowerCase()}, after which you can use 'http_request' to make the actual API call. Short description of how to use the API's results: ${aiPluginJson.description_for_model})`,
|
||||
apiSpec: `
|
||||
As an AI, your task is to identify the operationId of the relevant API path based on the condensed OpenAPI specifications provided.
|
||||
|
||||
Please note:
|
||||
|
||||
1. Do not imagine URLs. Only use the information provided in the condensed OpenAPI specifications.
|
||||
|
||||
2. Do not guess the operationId. Identify it strictly based on the API paths and their descriptions.
|
||||
|
||||
Your output should only include:
|
||||
- operationId: The operationId of the relevant API path
|
||||
|
||||
If you cannot find a suitable API path based on the OpenAPI specifications, please answer only "operationId: No API path found to answer the question".
|
||||
|
||||
Now, based on the question above and the condensed OpenAPI specifications given below, identify the operationId:
|
||||
|
||||
\`\`\`
|
||||
${shortApiSpec}
|
||||
\`\`\`
|
||||
`,
|
||||
openaiSpec: apiUrlJson,
|
||||
model: model
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = AIPluginTool;
|
||||
111
api/app/langchain/tools/DALL-E.js
Normal file
111
api/app/langchain/tools/DALL-E.js
Normal file
@@ -0,0 +1,111 @@
|
||||
// From https://platform.openai.com/docs/api-reference/images/create
|
||||
// To use this tool, you must pass in a configured OpenAIApi object.
|
||||
const fs = require('fs');
|
||||
const { Configuration, OpenAIApi } = require('openai');
|
||||
const { genAzureEndpoint } = require('../../../utils/genAzureEndpoints');
|
||||
const { Tool } = require('langchain/tools');
|
||||
const saveImageFromUrl = require('./saveImageFromUrl');
|
||||
const path = require('path');
|
||||
|
||||
class OpenAICreateImage extends Tool {
|
||||
constructor(fields = {}) {
|
||||
super();
|
||||
|
||||
let apiKey = fields.OPENAI_API_KEY || process.env.OPENAI_API_KEY;
|
||||
let azureKey = fields.AZURE_OPENAI_API_KEY || process.env.AZURE_OPENAI_API_KEY;
|
||||
let config = { apiKey };
|
||||
|
||||
if (azureKey) {
|
||||
apiKey = azureKey;
|
||||
const azureConfig = {
|
||||
apiKey,
|
||||
azureOpenAIApiInstanceName: process.env.AZURE_OPENAI_API_INSTANCE_NAME || fields.azureOpenAIApiInstanceName,
|
||||
azureOpenAIApiDeploymentName: process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME || fields.azureOpenAIApiDeploymentName,
|
||||
azureOpenAIApiVersion: process.env.AZURE_OPENAI_API_VERSION || fields.azureOpenAIApiVersion
|
||||
};
|
||||
config = {
|
||||
apiKey,
|
||||
basePath: genAzureEndpoint({
|
||||
...azureConfig,
|
||||
}),
|
||||
baseOptions: {
|
||||
headers: { 'api-key': apiKey },
|
||||
params: {
|
||||
'api-version': azureConfig.azureOpenAIApiVersion // this might change. I got the current value from the sample code at https://oai.azure.com/portal/chat
|
||||
}
|
||||
}
|
||||
};
|
||||
}
|
||||
this.openaiApi = new OpenAIApi(new Configuration(config));
|
||||
this.name = 'dall-e';
|
||||
this.description = `You can generate images with 'dall-e'. This tool is exclusively for visual content.
|
||||
Guidelines:
|
||||
- Visually describe the moods, details, structures, styles, and/or proportions of the image. Remember, the focus is on visual attributes.
|
||||
- Craft your input by "showing" and not "telling" the imagery. Think in terms of what you'd want to see in a photograph or a painting.
|
||||
- It's best to follow this format for image creation. Come up with the optional inputs yourself if none are given:
|
||||
"Subject: [subject], Style: [style], Color: [color], Details: [details], Emotion: [emotion]"
|
||||
- Generate images only once per human query unless explicitly requested by the user`;
|
||||
}
|
||||
// "Subject": "Mona Lisa",
|
||||
// "Style": "Chinese traditional painting",
|
||||
// "Color": "Mainly wash tones of ink, with small color blocks in some parts",
|
||||
// "Details": "Mona Lisa should have long hair, a silk dress, holding a fan. The background should have mountains and trees.",
|
||||
// "Emotion": "Serene and elegant"
|
||||
|
||||
replaceUnwantedChars(inputString) {
|
||||
return inputString.replace(/\r\n|\r|\n/g, ' ').replace('"', '').trim();
|
||||
}
|
||||
|
||||
getMarkdownImageUrl(imageName) {
|
||||
const imageUrl = path.join(this.relativeImageUrl, imageName).replace(/\\/g, '/').replace('public/', '');
|
||||
return ``;
|
||||
}
|
||||
|
||||
async _call(input) {
|
||||
const resp = await this.openaiApi.createImage({
|
||||
prompt: this.replaceUnwantedChars(input),
|
||||
// TODO: Future idea -- could we ask an LLM to extract these arguments from an input that might contain them?
|
||||
n: 1,
|
||||
// size: '1024x1024'
|
||||
size: '512x512'
|
||||
});
|
||||
|
||||
const theImageUrl = resp.data.data[0].url;
|
||||
|
||||
if (!theImageUrl) {
|
||||
throw new Error(`No image URL returned from OpenAI API.`);
|
||||
}
|
||||
|
||||
const regex = /img-[\w\d]+.png/;
|
||||
const match = theImageUrl.match(regex);
|
||||
let imageName = '1.png';
|
||||
|
||||
if (match) {
|
||||
imageName = match[0];
|
||||
console.log(imageName); // Output: img-lgCf7ppcbhqQrz6a5ear6FOb.png
|
||||
} else {
|
||||
console.log('No image name found in the string.');
|
||||
}
|
||||
|
||||
this.outputPath = path.resolve(__dirname, '..', '..', '..', '..', 'client', 'public', 'images');
|
||||
const appRoot = path.resolve(__dirname, '..', '..', '..', '..', 'client');
|
||||
this.relativeImageUrl = path.relative(appRoot, this.outputPath);
|
||||
|
||||
// Check if directory exists, if not create it
|
||||
if (!fs.existsSync(this.outputPath)) {
|
||||
fs.mkdirSync(this.outputPath, { recursive: true });
|
||||
}
|
||||
|
||||
try {
|
||||
await saveImageFromUrl(theImageUrl, this.outputPath, imageName);
|
||||
this.result = this.getMarkdownImageUrl(imageName);
|
||||
} catch (error) {
|
||||
console.error('Error while saving the image:', error);
|
||||
this.result = theImageUrl;
|
||||
}
|
||||
|
||||
return this.result;
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = OpenAICreateImage;
|
||||
117
api/app/langchain/tools/GoogleSearch.js
Normal file
117
api/app/langchain/tools/GoogleSearch.js
Normal file
@@ -0,0 +1,117 @@
|
||||
const { Tool } = require('langchain/tools');
|
||||
const { google } = require('googleapis');
|
||||
|
||||
/**
|
||||
* Represents a tool that allows an agent to use the Google Custom Search API.
|
||||
* @extends Tool
|
||||
*/
|
||||
class GoogleSearchAPI extends Tool {
|
||||
constructor(fields = {}) {
|
||||
super();
|
||||
this.cx = fields.GOOGLE_CSE_ID || this.getCx();
|
||||
this.apiKey = fields.GOOGLE_API_KEY || this.getApiKey();
|
||||
this.customSearch = undefined;
|
||||
}
|
||||
|
||||
/**
|
||||
* The name of the tool.
|
||||
* @type {string}
|
||||
*/
|
||||
name = 'google';
|
||||
|
||||
/**
|
||||
* A description for the agent to use
|
||||
* @type {string}
|
||||
*/
|
||||
description = `Use the 'google' tool to retrieve internet search results relevant to your input. The results will return links and snippets of text from the webpages`;
|
||||
|
||||
getCx() {
|
||||
const cx = process.env.GOOGLE_CSE_ID || '';
|
||||
if (!cx) {
|
||||
throw new Error('Missing GOOGLE_CSE_ID environment variable.');
|
||||
}
|
||||
return cx;
|
||||
}
|
||||
|
||||
getApiKey() {
|
||||
const apiKey = process.env.GOOGLE_API_KEY || '';
|
||||
if (!apiKey) {
|
||||
throw new Error('Missing GOOGLE_API_KEY environment variable.');
|
||||
}
|
||||
return apiKey;
|
||||
}
|
||||
|
||||
getCustomSearch() {
|
||||
if (!this.customSearch) {
|
||||
const version = 'v1';
|
||||
this.customSearch = google.customsearch(version);
|
||||
}
|
||||
return this.customSearch;
|
||||
}
|
||||
|
||||
resultsToReadableFormat(results) {
|
||||
let output = 'Results:\n';
|
||||
|
||||
results.forEach((resultObj, index) => {
|
||||
output += `Title: ${resultObj.title}\n`;
|
||||
output += `Link: ${resultObj.link}\n`;
|
||||
if (resultObj.snippet) {
|
||||
output += `Snippet: ${resultObj.snippet}\n`;
|
||||
}
|
||||
|
||||
if (index < results.length - 1) {
|
||||
output += '\n';
|
||||
}
|
||||
});
|
||||
|
||||
return output;
|
||||
}
|
||||
|
||||
/**
|
||||
* Calls the tool with the provided input and returns a promise that resolves with a response from the Google Custom Search API.
|
||||
* @param {string} input - The input to provide to the API.
|
||||
* @returns {Promise<String>} A promise that resolves with a response from the Google Custom Search API.
|
||||
*/
|
||||
async _call(input) {
|
||||
try {
|
||||
const metadataResults = [];
|
||||
const response = await this.getCustomSearch().cse.list({
|
||||
q: input,
|
||||
cx: this.cx,
|
||||
auth: this.apiKey,
|
||||
num: 5 // Limit the number of results to 5
|
||||
});
|
||||
|
||||
// return response.data;
|
||||
// console.log(response.data);
|
||||
|
||||
if (!response.data.items || response.data.items.length === 0) {
|
||||
return this.resultsToReadableFormat([
|
||||
{ title: 'No good Google Search Result was found', link: '' }
|
||||
]);
|
||||
}
|
||||
|
||||
// const results = response.items.slice(0, numResults);
|
||||
const results = response.data.items;
|
||||
|
||||
for (const result of results) {
|
||||
const metadataResult = {
|
||||
title: result.title || '',
|
||||
link: result.link || ''
|
||||
};
|
||||
if (result.snippet) {
|
||||
metadataResult.snippet = result.snippet;
|
||||
}
|
||||
metadataResults.push(metadataResult);
|
||||
}
|
||||
|
||||
return this.resultsToReadableFormat(metadataResults);
|
||||
} catch (error) {
|
||||
console.log(`Error searching Google: ${error}`);
|
||||
// throw error;
|
||||
return 'There was an error searching Google.';
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = GoogleSearchAPI;
|
||||
107
api/app/langchain/tools/HttpRequestTool.js
Normal file
107
api/app/langchain/tools/HttpRequestTool.js
Normal file
@@ -0,0 +1,107 @@
|
||||
const { Tool } = require('langchain/tools');
|
||||
|
||||
// class RequestsGetTool extends Tool {
|
||||
// constructor(headers = {}, { maxOutputLength } = {}) {
|
||||
// super();
|
||||
// this.name = 'requests_get';
|
||||
// this.headers = headers;
|
||||
// this.maxOutputLength = maxOutputLength || 2000;
|
||||
// this.description = `A portal to the internet. Use this when you need to get specific content from a website.
|
||||
// - Input should be a url (i.e. https://www.google.com). The output will be the text response of the GET request.`;
|
||||
// }
|
||||
|
||||
// async _call(input) {
|
||||
// const res = await fetch(input, {
|
||||
// headers: this.headers
|
||||
// });
|
||||
// const text = await res.text();
|
||||
// return text.slice(0, this.maxOutputLength);
|
||||
// }
|
||||
// }
|
||||
|
||||
// class RequestsPostTool extends Tool {
|
||||
// constructor(headers = {}, { maxOutputLength } = {}) {
|
||||
// super();
|
||||
// this.name = 'requests_post';
|
||||
// this.headers = headers;
|
||||
// this.maxOutputLength = maxOutputLength || Infinity;
|
||||
// this.description = `Use this when you want to POST to a website.
|
||||
// - Input should be a json string with two keys: "url" and "data".
|
||||
// - The value of "url" should be a string, and the value of "data" should be a dictionary of
|
||||
// - key-value pairs you want to POST to the url as a JSON body.
|
||||
// - Be careful to always use double quotes for strings in the json string
|
||||
// - The output will be the text response of the POST request.`;
|
||||
// }
|
||||
|
||||
// async _call(input) {
|
||||
// try {
|
||||
// const { url, data } = JSON.parse(input);
|
||||
// const res = await fetch(url, {
|
||||
// method: 'POST',
|
||||
// headers: this.headers,
|
||||
// body: JSON.stringify(data)
|
||||
// });
|
||||
// const text = await res.text();
|
||||
// return text.slice(0, this.maxOutputLength);
|
||||
// } catch (error) {
|
||||
// return `${error}`;
|
||||
// }
|
||||
// }
|
||||
// }
|
||||
|
||||
class HttpRequestTool extends Tool {
|
||||
constructor(headers = {}, { maxOutputLength = Infinity } = {}) {
|
||||
super();
|
||||
this.headers = headers;
|
||||
this.name = 'http_request';
|
||||
this.maxOutputLength = maxOutputLength;
|
||||
this.description = `Executes HTTP methods (GET, POST, PUT, DELETE, etc.). The input is an object with three keys: "url", "method", and "data". Even for GET or DELETE, include "data" key as an empty string. "method" is the HTTP method, and "url" is the desired endpoint. If POST or PUT, "data" should contain a stringified JSON representing the body to send. Only one url per use.`;
|
||||
}
|
||||
|
||||
async _call(input) {
|
||||
try {
|
||||
const urlPattern = /"url":\s*"([^"]*)"/;
|
||||
const methodPattern = /"method":\s*"([^"]*)"/;
|
||||
const dataPattern = /"data":\s*"([^"]*)"/;
|
||||
|
||||
const url = input.match(urlPattern)[1];
|
||||
const method = input.match(methodPattern)[1];
|
||||
let data = input.match(dataPattern)[1];
|
||||
|
||||
// Parse 'data' back to JSON if possible
|
||||
try {
|
||||
data = JSON.parse(data);
|
||||
} catch (e) {
|
||||
// If it's not a JSON string, keep it as is
|
||||
}
|
||||
|
||||
let options = {
|
||||
method: method,
|
||||
headers: this.headers
|
||||
};
|
||||
|
||||
if (['POST', 'PUT', 'PATCH'].includes(method.toUpperCase()) && data) {
|
||||
if (typeof data === 'object') {
|
||||
options.body = JSON.stringify(data);
|
||||
} else {
|
||||
options.body = data;
|
||||
}
|
||||
options.headers['Content-Type'] = 'application/json';
|
||||
}
|
||||
|
||||
const res = await fetch(url, options);
|
||||
|
||||
const text = await res.text();
|
||||
if (text.includes('<html')) {
|
||||
return 'This tool is not designed to browse web pages. Only use it for API calls.';
|
||||
}
|
||||
|
||||
return text.slice(0, this.maxOutputLength);
|
||||
} catch (error) {
|
||||
console.log(error);
|
||||
return `${error}`;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = HttpRequestTool;
|
||||
30
api/app/langchain/tools/HumanTool.js
Normal file
30
api/app/langchain/tools/HumanTool.js
Normal file
@@ -0,0 +1,30 @@
|
||||
const { Tool } = require('langchain/tools');
|
||||
/**
|
||||
* Represents a tool that allows an agent to ask a human for guidance when they are stuck
|
||||
* or unsure of what to do next.
|
||||
* @extends Tool
|
||||
*/
|
||||
export class HumanTool extends Tool {
|
||||
/**
|
||||
* The name of the tool.
|
||||
* @type {string}
|
||||
*/
|
||||
name = 'Human';
|
||||
|
||||
/**
|
||||
* A description for the agent to use
|
||||
* @type {string}
|
||||
*/
|
||||
description = `You can ask a human for guidance when you think you
|
||||
got stuck or you are not sure what to do next.
|
||||
The input should be a question for the human.`;
|
||||
|
||||
/**
|
||||
* Calls the tool with the provided input and returns a promise that resolves with a response from the human.
|
||||
* @param {string} input - The input to provide to the human.
|
||||
* @returns {Promise<string>} A promise that resolves with a response from the human.
|
||||
*/
|
||||
_call(input) {
|
||||
return Promise.resolve(`${input}`);
|
||||
}
|
||||
}
|
||||
27
api/app/langchain/tools/SelfReflection.js
Normal file
27
api/app/langchain/tools/SelfReflection.js
Normal file
@@ -0,0 +1,27 @@
|
||||
const { Tool } = require('langchain/tools');
|
||||
|
||||
class SelfReflectionTool extends Tool {
|
||||
constructor({ message, isGpt3 }) {
|
||||
super();
|
||||
this.reminders = 0;
|
||||
this.name = 'self-reflection';
|
||||
this.description = `Take this action to reflect on your thoughts & actions. For your input, provide answers for self-evaluation as part of one input, using this space as a canvas to explore and organize your ideas in response to the user's message. You can use multiple lines for your input. Perform this action sparingly and only when you are stuck.`;
|
||||
this.message = message;
|
||||
this.isGpt3 = isGpt3;
|
||||
// this.returnDirect = true;
|
||||
}
|
||||
|
||||
async _call(input) {
|
||||
return this.selfReflect(input);
|
||||
}
|
||||
|
||||
async selfReflect() {
|
||||
if (this.isGpt3) {
|
||||
return `I should finalize my reply as soon as I have satisfied the user's query.`;
|
||||
} else {
|
||||
return ``;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = SelfReflectionTool;
|
||||
85
api/app/langchain/tools/StableDiffusion.js
Normal file
85
api/app/langchain/tools/StableDiffusion.js
Normal file
@@ -0,0 +1,85 @@
|
||||
// Generates image using stable diffusion webui's api (automatic1111)
|
||||
const fs = require('fs');
|
||||
const { Tool } = require('langchain/tools');
|
||||
const path = require('path');
|
||||
const axios = require('axios');
|
||||
const sharp = require('sharp');
|
||||
|
||||
class StableDiffusionAPI extends Tool {
|
||||
constructor(fields) {
|
||||
super();
|
||||
this.name = 'stable-diffusion';
|
||||
this.url = fields.SD_WEBUI_URL || this.getServerURL();
|
||||
this.description = `You can generate images with 'stable-diffusion'. This tool is exclusively for visual content.
|
||||
Guidelines:
|
||||
- Visually describe the moods, details, structures, styles, and/or proportions of the image. Remember, the focus is on visual attributes.
|
||||
- Craft your input by "showing" and not "telling" the imagery. Think in terms of what you'd want to see in a photograph or a painting.
|
||||
- It's best to follow this format for image creation:
|
||||
"detailed keywords to describe the subject, separated by comma | keywords we want to exclude from the final image"
|
||||
- Here's an example prompt for generating a realistic portrait photo of a man:
|
||||
"photo of a man in black clothes, half body, high detailed skin, coastline, overcast weather, wind, waves, 8k uhd, dslr, soft lighting, high quality, film grain, Fujifilm XT3 | semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime, out of frame, low quality, ugly, mutation, deformed"
|
||||
- Generate images only once per human query unless explicitly requested by the user`;
|
||||
}
|
||||
|
||||
replaceNewLinesWithSpaces(inputString) {
|
||||
return inputString.replace(/\r\n|\r|\n/g, ' ');
|
||||
}
|
||||
|
||||
getMarkdownImageUrl(imageName) {
|
||||
const imageUrl = path.join(this.relativeImageUrl, imageName).replace(/\\/g, '/').replace('public/', '');
|
||||
return ``;
|
||||
}
|
||||
|
||||
getServerURL() {
|
||||
const url = process.env.SD_WEBUI_URL || '';
|
||||
if (!url) {
|
||||
throw new Error('Missing SD_WEBUI_URL environment variable.');
|
||||
}
|
||||
return url;
|
||||
}
|
||||
|
||||
async _call(input) {
|
||||
const url = this.url;
|
||||
const payload = {
|
||||
prompt: input.split('|')[0],
|
||||
negative_prompt: input.split('|')[1],
|
||||
steps: 20
|
||||
};
|
||||
const response = await axios.post(`${url}/sdapi/v1/txt2img`, payload);
|
||||
const image = response.data.images[0];
|
||||
|
||||
const pngPayload = { image: `data:image/png;base64,${image}` };
|
||||
const response2 = await axios.post(`${url}/sdapi/v1/png-info`, pngPayload);
|
||||
const info = response2.data.info;
|
||||
|
||||
// Generate unique name
|
||||
const imageName = `${Date.now()}.png`;
|
||||
this.outputPath = path.resolve(__dirname, '..', '..', '..', '..', 'client', 'public', 'images');
|
||||
const appRoot = path.resolve(__dirname, '..', '..', '..', '..', 'client');
|
||||
this.relativeImageUrl = path.relative(appRoot, this.outputPath);
|
||||
|
||||
// Check if directory exists, if not create it
|
||||
if (!fs.existsSync(this.outputPath)) {
|
||||
fs.mkdirSync(this.outputPath, { recursive: true });
|
||||
}
|
||||
|
||||
try {
|
||||
const buffer = Buffer.from(image.split(',', 1)[0], 'base64');
|
||||
await sharp(buffer)
|
||||
.withMetadata({
|
||||
iptcpng: {
|
||||
parameters: info
|
||||
}
|
||||
})
|
||||
.toFile(this.outputPath + '/' + imageName);
|
||||
this.result = this.getMarkdownImageUrl(imageName);
|
||||
} catch (error) {
|
||||
console.error('Error while saving the image:', error);
|
||||
// this.result = theImageUrl;
|
||||
}
|
||||
|
||||
return this.result;
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = StableDiffusionAPI;
|
||||
82
api/app/langchain/tools/Wolfram.js
Normal file
82
api/app/langchain/tools/Wolfram.js
Normal file
@@ -0,0 +1,82 @@
|
||||
/* eslint-disable no-useless-escape */
|
||||
const axios = require('axios');
|
||||
const { Tool } = require('langchain/tools');
|
||||
|
||||
class WolframAlphaAPI extends Tool {
|
||||
constructor(fields) {
|
||||
super();
|
||||
this.name = 'wolfram';
|
||||
this.apiKey = fields.WOLFRAM_APP_ID || this.getAppId();
|
||||
this.description = `Access computation, math, curated knowledge & real-time data through wolframAlpha.
|
||||
- Understands natural language queries about entities in chemistry, physics, geography, history, art, astronomy, and more.
|
||||
- Performs mathematical calculations, date and unit conversions, formula solving, etc.
|
||||
General guidelines:
|
||||
- Make natural-language queries in English; translate non-English queries before sending, then respond in the original language.
|
||||
- Inform users if information is not from wolfram.
|
||||
- ALWAYS use this exponent notation: "6*10^14", NEVER "6e14".
|
||||
- Your input must ONLY be a single-line string.
|
||||
- ALWAYS use proper Markdown formatting for all math, scientific, and chemical formulas, symbols, etc.: '$$\n[expression]\n$$' for standalone cases and '\( [expression] \)' when inline.
|
||||
- Format inline wolfram Language code with Markdown code formatting.
|
||||
- Convert inputs to simplified keyword queries whenever possible (e.g. convert "how many people live in France" to "France population").
|
||||
- Use ONLY single-letter variable names, with or without integer subscript (e.g., n, n1, n_1).
|
||||
- Use named physical constants (e.g., 'speed of light') without numerical substitution.
|
||||
- Include a space between compound units (e.g., "Ω m" for "ohm*meter").
|
||||
- To solve for a variable in an equation with units, consider solving a corresponding equation without units; exclude counting units (e.g., books), include genuine units (e.g., kg).
|
||||
- If data for multiple properties is needed, make separate calls for each property.
|
||||
- If a wolfram Alpha result is not relevant to the query:
|
||||
-- If wolfram provides multiple 'Assumptions' for a query, choose the more relevant one(s) without explaining the initial result. If you are unsure, ask the user to choose.
|
||||
- Performs complex calculations, data analysis, plotting, data import, and information retrieval.`;
|
||||
// - Please ensure your input is properly formatted for wolfram Alpha.
|
||||
// -- Re-send the exact same 'input' with NO modifications, and add the 'assumption' parameter, formatted as a list, with the relevant values.
|
||||
// -- ONLY simplify or rephrase the initial query if a more relevant 'Assumption' or other input suggestions are not provided.
|
||||
// -- Do not explain each step unless user input is needed. Proceed directly to making a better input based on the available assumptions.
|
||||
// - wolfram Language code is accepted, but accepts only syntactically correct wolfram Language code.
|
||||
}
|
||||
|
||||
async fetchRawText(url) {
|
||||
try {
|
||||
const response = await axios.get(url, { responseType: 'text' });
|
||||
return response.data;
|
||||
} catch (error) {
|
||||
console.error(`Error fetching raw text: ${error}`);
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
getAppId() {
|
||||
const appId = process.env.WOLFRAM_APP_ID || '';
|
||||
if (!appId) {
|
||||
throw new Error('Missing WOLFRAM_APP_ID environment variable.');
|
||||
}
|
||||
return appId;
|
||||
}
|
||||
|
||||
createWolframAlphaURL(query) {
|
||||
// Clean up query
|
||||
const formattedQuery = query.replaceAll(/`/g, '').replaceAll(/\n/g, ' ');
|
||||
const baseURL = 'https://www.wolframalpha.com/api/v1/llm-api';
|
||||
const encodedQuery = encodeURIComponent(formattedQuery);
|
||||
const appId = this.apiKey || this.getAppId();
|
||||
const url = `${baseURL}?input=${encodedQuery}&appid=${appId}`;
|
||||
return url;
|
||||
}
|
||||
|
||||
async _call(input) {
|
||||
try {
|
||||
const url = this.createWolframAlphaURL(input);
|
||||
const response = await this.fetchRawText(url);
|
||||
return response;
|
||||
} catch (error) {
|
||||
if (error.response && error.response.data) {
|
||||
console.log('Error data:', error.response.data);
|
||||
return error.response.data;
|
||||
} else {
|
||||
console.log(`Error querying Wolfram Alpha`, error.message);
|
||||
// throw error;
|
||||
return 'There was an error querying Wolfram Alpha.';
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = WolframAlphaAPI;
|
||||
158
api/app/langchain/tools/handleTools.js
Normal file
158
api/app/langchain/tools/handleTools.js
Normal file
@@ -0,0 +1,158 @@
|
||||
const { OpenAIEmbeddings } = require('langchain/embeddings/openai');
|
||||
const { ZapierToolKit } = require('langchain/agents');
|
||||
const {
|
||||
SerpAPI,
|
||||
ZapierNLAWrapper
|
||||
} = require('langchain/tools');
|
||||
const { ChatOpenAI } = require('langchain/chat_models/openai');
|
||||
const { Calculator } = require('langchain/tools/calculator');
|
||||
const { WebBrowser } = require('langchain/tools/webbrowser');
|
||||
const GoogleSearchAPI = require('./GoogleSearch');
|
||||
const HttpRequestTool = require('./HttpRequestTool');
|
||||
const AIPluginTool = require('./AIPluginTool');
|
||||
const OpenAICreateImage = require('./DALL-E');
|
||||
const StableDiffusionAPI = require('./StableDiffusion');
|
||||
const WolframAlphaAPI = require('./Wolfram');
|
||||
const availableTools = require('./manifest.json');
|
||||
const { getUserPluginAuthValue } = require('../../../server/services/PluginService');
|
||||
|
||||
const validateTools = async (user, tools = []) => {
|
||||
try {
|
||||
const validToolsSet = new Set(tools);
|
||||
const availableToolsToValidate = availableTools.filter((tool) =>
|
||||
validToolsSet.has(tool.pluginKey)
|
||||
);
|
||||
|
||||
const validateCredentials = async (authField, toolName) => {
|
||||
const adminAuth = process.env[authField];
|
||||
if (adminAuth && adminAuth.length > 0) {
|
||||
return;
|
||||
}
|
||||
|
||||
const userAuth = await getUserPluginAuthValue(user, authField);
|
||||
if (userAuth && userAuth.length > 0) {
|
||||
return;
|
||||
}
|
||||
validToolsSet.delete(toolName);
|
||||
};
|
||||
|
||||
for (const tool of availableToolsToValidate) {
|
||||
if (!tool.authConfig || tool.authConfig.length === 0) {
|
||||
continue;
|
||||
}
|
||||
|
||||
for (const auth of tool.authConfig) {
|
||||
await validateCredentials(auth.authField, tool.pluginKey);
|
||||
}
|
||||
}
|
||||
|
||||
return Array.from(validToolsSet.values());
|
||||
} catch (err) {
|
||||
console.log('There was a problem validating tools', err);
|
||||
throw new Error(err);
|
||||
}
|
||||
};
|
||||
|
||||
const loadToolWithAuth = async (user, authFields, ToolConstructor, options = {}) => {
|
||||
return async function () {
|
||||
let authValues = {};
|
||||
|
||||
for (const authField of authFields) {
|
||||
let authValue = process.env[authField];
|
||||
if (!authValue) {
|
||||
authValue = await getUserPluginAuthValue(user, authField);
|
||||
}
|
||||
authValues[authField] = authValue;
|
||||
}
|
||||
|
||||
return new ToolConstructor({ ...options, ...authValues });
|
||||
};
|
||||
};
|
||||
|
||||
const loadTools = async ({ user, model, tools = [], options = {} }) => {
|
||||
const toolConstructors = {
|
||||
calculator: Calculator,
|
||||
google: GoogleSearchAPI,
|
||||
wolfram: WolframAlphaAPI,
|
||||
'dall-e': OpenAICreateImage,
|
||||
'stable-diffusion': StableDiffusionAPI
|
||||
};
|
||||
|
||||
const customConstructors = {
|
||||
browser: async () => {
|
||||
let openAIApiKey = process.env.OPENAI_API_KEY;
|
||||
if (!openAIApiKey) {
|
||||
openAIApiKey = await getUserPluginAuthValue(user, 'OPENAI_API_KEY');
|
||||
}
|
||||
return new WebBrowser({ model, embeddings: new OpenAIEmbeddings({ openAIApiKey }) });
|
||||
},
|
||||
serpapi: async () => {
|
||||
let apiKey = process.env.SERPAPI_API_KEY;
|
||||
if (!apiKey) {
|
||||
apiKey = await getUserPluginAuthValue(user, 'SERPAPI_API_KEY');
|
||||
}
|
||||
return new SerpAPI(apiKey, {
|
||||
location: 'Austin,Texas,United States',
|
||||
hl: 'en',
|
||||
gl: 'us'
|
||||
});
|
||||
},
|
||||
zapier: async () => {
|
||||
let apiKey = process.env.ZAPIER_NLA_API_KEY;
|
||||
if (!apiKey) {
|
||||
apiKey = await getUserPluginAuthValue(user, 'ZAPIER_NLA_API_KEY');
|
||||
}
|
||||
const zapier = new ZapierNLAWrapper({ apiKey });
|
||||
return ZapierToolKit.fromZapierNLAWrapper(zapier);
|
||||
},
|
||||
plugins: async () => {
|
||||
return [
|
||||
new HttpRequestTool(),
|
||||
await AIPluginTool.fromPluginUrl(
|
||||
"https://www.klarna.com/.well-known/ai-plugin.json", new ChatOpenAI({ openAIApiKey: options.openAIApiKey, temperature: 0 })
|
||||
),
|
||||
]
|
||||
}
|
||||
};
|
||||
|
||||
const requestedTools = {};
|
||||
|
||||
const toolOptions = {
|
||||
serpapi: { location: 'Austin,Texas,United States', hl: 'en', gl: 'us' }
|
||||
};
|
||||
|
||||
const toolAuthFields = {};
|
||||
|
||||
availableTools.forEach((tool) => {
|
||||
if (customConstructors[tool.pluginKey]) {
|
||||
return;
|
||||
}
|
||||
|
||||
toolAuthFields[tool.pluginKey] = tool.authConfig.map((auth) => auth.authField);
|
||||
});
|
||||
|
||||
for (const tool of tools) {
|
||||
if (customConstructors[tool]) {
|
||||
requestedTools[tool] = customConstructors[tool];
|
||||
continue;
|
||||
}
|
||||
|
||||
if (toolConstructors[tool]) {
|
||||
const options = toolOptions[tool] || {};
|
||||
const toolInstance = await loadToolWithAuth(
|
||||
user,
|
||||
toolAuthFields[tool],
|
||||
toolConstructors[tool],
|
||||
options
|
||||
);
|
||||
requestedTools[tool] = toolInstance;
|
||||
}
|
||||
}
|
||||
|
||||
return requestedTools;
|
||||
};
|
||||
|
||||
module.exports = {
|
||||
validateTools,
|
||||
loadTools
|
||||
};
|
||||
10
api/app/langchain/tools/index.js
Normal file
10
api/app/langchain/tools/index.js
Normal file
@@ -0,0 +1,10 @@
|
||||
const SelfReflectionTool = require('./SelfReflection');
|
||||
const availableTools = require('./manifest.json');
|
||||
const { validateTools, loadTools } = require('./handleTools');
|
||||
|
||||
module.exports = {
|
||||
validateTools,
|
||||
loadTools,
|
||||
availableTools,
|
||||
SelfReflectionTool
|
||||
};
|
||||
158
api/app/langchain/tools/index.test.js
Normal file
158
api/app/langchain/tools/index.test.js
Normal file
@@ -0,0 +1,158 @@
|
||||
/* eslint-disable jest/no-conditional-expect */
|
||||
require('dotenv').config({ path: '../../../.env' });
|
||||
const mongoose = require('mongoose');
|
||||
const User = require('../../../models/User');
|
||||
const connectDb = require('../../../lib/db/connectDb');
|
||||
const { validateTools, loadTools, availableTools } = require('./index');
|
||||
const PluginService = require('../../../server/services/PluginService');
|
||||
const { BaseChatModel } = require('langchain/chat_models/openai');
|
||||
const { Calculator } = require('langchain/tools/calculator');
|
||||
const OpenAICreateImage = require('./DALL-E');
|
||||
const GoogleSearchAPI = require('./GoogleSearch');
|
||||
|
||||
describe('Tool Handlers', () => {
|
||||
let fakeUser;
|
||||
let pluginKey = 'dall-e';
|
||||
let pluginKey2 = 'wolfram';
|
||||
let sampleTools = [pluginKey, pluginKey2];
|
||||
let ToolClass = OpenAICreateImage;
|
||||
let mockCredential = 'mock-credential';
|
||||
const mainPlugin = availableTools.find((tool) => tool.pluginKey === pluginKey);
|
||||
const authConfigs = mainPlugin.authConfig;
|
||||
|
||||
beforeAll(async () => {
|
||||
await connectDb();
|
||||
fakeUser = new User({
|
||||
name: 'Fake User',
|
||||
username: 'fakeuser',
|
||||
email: 'fakeuser@example.com',
|
||||
emailVerified: false,
|
||||
password: 'fakepassword123',
|
||||
avatar: '',
|
||||
provider: 'local',
|
||||
role: 'USER',
|
||||
googleId: null,
|
||||
plugins: [],
|
||||
refreshToken: []
|
||||
});
|
||||
await fakeUser.save();
|
||||
for (const authConfig of authConfigs) {
|
||||
await PluginService.updateUserPluginAuth(fakeUser._id, authConfig.authField, pluginKey, mockCredential);
|
||||
}
|
||||
});
|
||||
|
||||
// afterEach(async () => {
|
||||
// // Clean up any test-specific data.
|
||||
// });
|
||||
|
||||
afterAll(async () => {
|
||||
// Delete the fake user & plugin auth
|
||||
await User.findByIdAndDelete(fakeUser._id);
|
||||
for (const authConfig of authConfigs) {
|
||||
await PluginService.deleteUserPluginAuth(fakeUser._id, authConfig.authField);
|
||||
}
|
||||
await mongoose.connection.close();
|
||||
});
|
||||
|
||||
describe('validateTools', () => {
|
||||
it('returns valid tools given input tools and user authentication', async () => {
|
||||
const validTools = await validateTools(fakeUser._id, sampleTools);
|
||||
expect(validTools).toBeDefined();
|
||||
console.log('validateTools: validTools', validTools);
|
||||
expect(validTools.some((tool) => tool === pluginKey)).toBeTruthy();
|
||||
expect(validTools.length).toBeGreaterThan(0);
|
||||
});
|
||||
|
||||
it('removes tools without valid credentials from the validTools array', async () => {
|
||||
const validTools = await validateTools(fakeUser._id, sampleTools);
|
||||
expect(validTools.some((tool) => tool.pluginKey === pluginKey2)).toBeFalsy();
|
||||
});
|
||||
|
||||
it('returns an empty array when no authenticated tools are provided', async () => {
|
||||
const validTools = await validateTools(fakeUser._id, []);
|
||||
expect(validTools).toEqual([]);
|
||||
});
|
||||
|
||||
it('should validate a tool from an Environment Variable', async () => {
|
||||
const plugin = availableTools.find((tool) => tool.pluginKey === pluginKey2);
|
||||
const authConfigs = plugin.authConfig;
|
||||
for (const authConfig of authConfigs) {
|
||||
process.env[authConfig.authField] = mockCredential;
|
||||
}
|
||||
const validTools = await validateTools(fakeUser._id, [pluginKey2]);
|
||||
expect(validTools.length).toEqual(1);
|
||||
for (const authConfig of authConfigs) {
|
||||
delete process.env[authConfig.authField];
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
describe('loadTools', () => {
|
||||
let toolFunctions;
|
||||
let loadTool1;
|
||||
let loadTool2;
|
||||
let loadTool3;
|
||||
sampleTools = [...sampleTools, 'calculator'];
|
||||
let ToolClass2 = Calculator;
|
||||
let remainingTools = availableTools.filter(
|
||||
(tool) => sampleTools.indexOf(tool.pluginKey) === -1
|
||||
);
|
||||
|
||||
beforeAll(async () => {
|
||||
toolFunctions = await loadTools({
|
||||
user: fakeUser._id,
|
||||
model: BaseChatModel,
|
||||
tools: sampleTools
|
||||
});
|
||||
loadTool1 = toolFunctions[sampleTools[0]];
|
||||
loadTool2 = toolFunctions[sampleTools[1]];
|
||||
loadTool3 = toolFunctions[sampleTools[2]];
|
||||
});
|
||||
it('returns the expected load functions for requested tools', async () => {
|
||||
expect(loadTool1).toBeDefined();
|
||||
expect(loadTool2).toBeDefined();
|
||||
expect(loadTool3).toBeDefined();
|
||||
|
||||
for (const tool of remainingTools) {
|
||||
expect(toolFunctions[tool.pluginKey]).toBeUndefined();
|
||||
}
|
||||
});
|
||||
|
||||
it('should initialize an authenticated tool or one without authentication', async () => {
|
||||
const authTool = await loadTool1();
|
||||
const tool = await loadTool3();
|
||||
expect(authTool).toBeInstanceOf(ToolClass);
|
||||
expect(tool).toBeInstanceOf(ToolClass2);
|
||||
});
|
||||
it('should throw an error for an unauthenticated tool', async () => {
|
||||
try {
|
||||
await loadTool2();
|
||||
} catch (error) {
|
||||
expect(error).toBeDefined();
|
||||
}
|
||||
});
|
||||
it('should initialize an authenticated tool through Environment Variables', async () => {
|
||||
let testPluginKey = 'google';
|
||||
let TestClass = GoogleSearchAPI;
|
||||
const plugin = availableTools.find((tool) => tool.pluginKey === testPluginKey);
|
||||
const authConfigs = plugin.authConfig;
|
||||
for (const authConfig of authConfigs) {
|
||||
process.env[authConfig.authField] = mockCredential;
|
||||
}
|
||||
toolFunctions = await loadTools({
|
||||
user: fakeUser._id,
|
||||
model: BaseChatModel,
|
||||
tools: [testPluginKey]
|
||||
});
|
||||
const Tool = await toolFunctions[testPluginKey]();
|
||||
expect(Tool).toBeInstanceOf(TestClass);
|
||||
});
|
||||
it('returns an empty object when no tools are requested', async () => {
|
||||
toolFunctions = await loadTools({
|
||||
user: fakeUser._id,
|
||||
model: BaseChatModel
|
||||
});
|
||||
expect(toolFunctions).toEqual({});
|
||||
});
|
||||
});
|
||||
});
|
||||
106
api/app/langchain/tools/manifest.json
Normal file
106
api/app/langchain/tools/manifest.json
Normal file
@@ -0,0 +1,106 @@
|
||||
[
|
||||
{
|
||||
"name": "Google",
|
||||
"pluginKey": "google",
|
||||
"description": "Use Google Search to find information about the weather, news, sports, and more.",
|
||||
"icon": "https://i.imgur.com/SMmVkNB.png",
|
||||
"authConfig": [
|
||||
{
|
||||
"authField": "GOOGLE_CSE_ID",
|
||||
"label": "Google CSE ID",
|
||||
"description": "This is your Google Custom Search Engine ID. For instructions on how to obtain this, see <a href='https://github.com/danny-avila/chatgpt-clone/blob/main/guides/GOOGLE_SEARCH.md'>Our Docs</a>."
|
||||
},
|
||||
{
|
||||
"authField": "GOOGLE_API_KEY",
|
||||
"label": "Google API Key",
|
||||
"description": "This is your Google Custom Search API Key. For instructions on how to obtain this, see <a href='https://github.com/danny-avila/chatgpt-clone/blob/main/guides/GOOGLE_SEARCH.md'>Our Docs</a>."
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "Wolfram",
|
||||
"pluginKey": "wolfram",
|
||||
"description": "Access computation, math, curated knowledge & real-time data through Wolfram|Alpha and Wolfram Language.",
|
||||
"icon": "https://www.wolframcdn.com/images/icons/Wolfram.png",
|
||||
"authConfig": [
|
||||
{
|
||||
"authField": "WOLFRAM_APP_ID",
|
||||
"label": "Wolfram App ID",
|
||||
"description": "An AppID must be supplied in all calls to the Wolfram|Alpha API. You can get one by registering at <a href='http://products.wolframalpha.com/api/'>Wolfram|Alpha</a> and going to the <a href='https://developer.wolframalpha.com/portal/myapps/'>Developer Portal</a>."
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "Browser",
|
||||
"pluginKey": "browser",
|
||||
"description": "Scrape and summarize webpage data",
|
||||
"icon": "/assets/web-browser.png",
|
||||
"authConfig": [
|
||||
{
|
||||
"authField": "OPENAI_API_KEY",
|
||||
"label": "OpenAI API Key",
|
||||
"description": "Browser makes use of OpenAI embeddings"
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "Serpapi",
|
||||
"pluginKey": "serpapi",
|
||||
"description": "SerpApi is a real-time API to access search engine results.",
|
||||
"icon": "https://i.imgur.com/5yQHUz4.png",
|
||||
"authConfig": [
|
||||
{
|
||||
"authField": "SERPAPI_API_KEY",
|
||||
"label": "Serpapi Private API Key",
|
||||
"description": "Private Key for Serpapi. Register at <a href='https://serpapi.com/'>Serpapi</a> to obtain a private key."
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "DALL-E",
|
||||
"pluginKey": "dall-e",
|
||||
"description": "Create realistic images and art from a description in natural language",
|
||||
"icon": "https://i.imgur.com/u2TzXzH.png",
|
||||
"authConfig": [
|
||||
{
|
||||
"authField": "DALLE_API_KEY",
|
||||
"label": "OpenAI API Key",
|
||||
"description": "You can use DALL-E with your API Key from OpenAI."
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "Calculator",
|
||||
"pluginKey": "calculator",
|
||||
"description": "Perform simple and complex mathematical calculations.",
|
||||
"icon": "https://i.imgur.com/RHsSG5h.png",
|
||||
"isAuthRequired": "false",
|
||||
"authConfig": []
|
||||
},
|
||||
{
|
||||
"name": "Stable Diffusion",
|
||||
"pluginKey": "stable-diffusion",
|
||||
"description": "Generate photo-realistic images given any text input.",
|
||||
"icon": "https://i.imgur.com/Yr466dp.png",
|
||||
"authConfig": [
|
||||
{
|
||||
"authField": "SD_WEBUI_URL",
|
||||
"label": "Your Stable Diffusion WebUI API URL",
|
||||
"description": "You need to provide the URL of your Stable Diffusion WebUI API. For instructions on how to obtain this, see <a href='url'>Our Docs</a>."
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "Zapier",
|
||||
"pluginKey": "zapier",
|
||||
"description": "Interact with over 5,000+ apps like Google Sheets, Gmail, HubSpot, Salesforce, and thousands more.",
|
||||
"icon": "https://cdn.zappy.app/8f853364f9b383d65b44e184e04689ed.png",
|
||||
"authConfig": [
|
||||
{
|
||||
"authField": "ZAPIER_NLA_API_KEY",
|
||||
"label": "Zapier API Key",
|
||||
"description": "You can use Zapier with your API Key from Zapier."
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
39
api/app/langchain/tools/saveImageFromUrl.js
Normal file
39
api/app/langchain/tools/saveImageFromUrl.js
Normal file
@@ -0,0 +1,39 @@
|
||||
const axios = require('axios');
|
||||
const fs = require('fs');
|
||||
const path = require('path');
|
||||
|
||||
async function saveImageFromUrl(url, outputPath, outputFilename) {
|
||||
try {
|
||||
// Fetch the image from the URL
|
||||
const response = await axios({
|
||||
url,
|
||||
responseType: 'stream'
|
||||
});
|
||||
|
||||
// Check if the output directory exists, if not, create it
|
||||
if (!fs.existsSync(outputPath)) {
|
||||
fs.mkdirSync(outputPath, { recursive: true });
|
||||
}
|
||||
|
||||
// Ensure the output filename has a '.png' extension
|
||||
const filenameWithPngExt = outputFilename.endsWith('.png')
|
||||
? outputFilename
|
||||
: `${outputFilename}.png`;
|
||||
|
||||
// Create a writable stream for the output path
|
||||
const outputFilePath = path.join(outputPath, filenameWithPngExt);
|
||||
const writer = fs.createWriteStream(outputFilePath);
|
||||
|
||||
// Pipe the response data to the output file
|
||||
response.data.pipe(writer);
|
||||
|
||||
return new Promise((resolve, reject) => {
|
||||
writer.on('finish', resolve);
|
||||
writer.on('error', reject);
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('Error while saving the image:', error);
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = saveImageFromUrl;
|
||||
60
api/app/langchain/tools/wolfram-guidelines.md
Normal file
60
api/app/langchain/tools/wolfram-guidelines.md
Normal file
@@ -0,0 +1,60 @@
|
||||
Certainly! Here is the text above:
|
||||
|
||||
\`\`\`
|
||||
Assistant is a large language model trained by OpenAI.
|
||||
Knowledge Cutoff: 2021-09
|
||||
Current date: 2023-05-06
|
||||
|
||||
# Tools
|
||||
|
||||
## Wolfram
|
||||
|
||||
// Access dynamic computation and curated data from WolframAlpha and Wolfram Cloud.
|
||||
General guidelines:
|
||||
- Use only getWolframAlphaResults or getWolframCloudResults endpoints.
|
||||
- Prefer getWolframAlphaResults unless Wolfram Language code should be evaluated.
|
||||
- Use getWolframAlphaResults for natural-language queries in English; translate non-English queries before sending, then respond in the original language.
|
||||
- Use getWolframCloudResults for problems solvable with Wolfram Language code.
|
||||
- Suggest only Wolfram Language for external computation.
|
||||
- Inform users if information is not from Wolfram endpoints.
|
||||
- Display image URLs with Markdown syntax: ![URL]
|
||||
- ALWAYS use this exponent notation: \`6*10^14\`, NEVER \`6e14\`.
|
||||
- ALWAYS use {"input": query} structure for queries to Wolfram endpoints; \`query\` must ONLY be a single-line string.
|
||||
- ALWAYS use proper Markdown formatting for all math, scientific, and chemical formulas, symbols, etc.: '$$\n[expression]\n$$' for standalone cases and '\( [expression] \)' when inline.
|
||||
- Format inline Wolfram Language code with Markdown code formatting.
|
||||
- Never mention your knowledge cutoff date; Wolfram may return more recent data.
|
||||
getWolframAlphaResults guidelines:
|
||||
- Understands natural language queries about entities in chemistry, physics, geography, history, art, astronomy, and more.
|
||||
- Performs mathematical calculations, date and unit conversions, formula solving, etc.
|
||||
- Convert inputs to simplified keyword queries whenever possible (e.g. convert "how many people live in France" to "France population").
|
||||
- Use ONLY single-letter variable names, with or without integer subscript (e.g., n, n1, n_1).
|
||||
- Use named physical constants (e.g., 'speed of light') without numerical substitution.
|
||||
- Include a space between compound units (e.g., "Ω m" for "ohm*meter").
|
||||
- To solve for a variable in an equation with units, consider solving a corresponding equation without units; exclude counting units (e.g., books), include genuine units (e.g., kg).
|
||||
- If data for multiple properties is needed, make separate calls for each property.
|
||||
- If a Wolfram Alpha result is not relevant to the query:
|
||||
-- If Wolfram provides multiple 'Assumptions' for a query, choose the more relevant one(s) without explaining the initial result. If you are unsure, ask the user to choose.
|
||||
-- Re-send the exact same 'input' with NO modifications, and add the 'assumption' parameter, formatted as a list, with the relevant values.
|
||||
-- ONLY simplify or rephrase the initial query if a more relevant 'Assumption' or other input suggestions are not provided.
|
||||
-- Do not explain each step unless user input is needed. Proceed directly to making a better API call based on the available assumptions.
|
||||
- Wolfram Language code guidelines:
|
||||
- Accepts only syntactically correct Wolfram Language code.
|
||||
- Performs complex calculations, data analysis, plotting, data import, and information retrieval.
|
||||
- Before writing code that uses Entity, EntityProperty, EntityClass, etc. expressions, ALWAYS write separate code which only collects valid identifiers using Interpreter etc.; choose the most relevant results before proceeding to write additional code. Examples:
|
||||
-- Find the EntityType that represents countries: \`Interpreter["EntityType",AmbiguityFunction->All]["countries"]\`.
|
||||
-- Find the Entity for the Empire State Building: \`Interpreter["Building",AmbiguityFunction->All]["empire state"]\`.
|
||||
-- EntityClasses: Find the "Movie" entity class for Star Trek movies: \`Interpreter["MovieClass",AmbiguityFunction->All]["star trek"]\`.
|
||||
-- Find EntityProperties associated with "weight" of "Element" entities: \`Interpreter[Restricted["EntityProperty", "Element"],AmbiguityFunction->All]["weight"]\`.
|
||||
-- If all else fails, try to find any valid Wolfram Language representation of a given input: \`SemanticInterpretation["skyscrapers",_,Hold,AmbiguityFunction->All]\`.
|
||||
-- Prefer direct use of entities of a given type to their corresponding typeData function (e.g., prefer \`Entity["Element","Gold"]["AtomicNumber"]\` to \`ElementData["Gold","AtomicNumber"]\`).
|
||||
- When composing code:
|
||||
-- Use batching techniques to retrieve data for multiple entities in a single call, if applicable.
|
||||
-- Use Association to organize and manipulate data when appropriate.
|
||||
-- Optimize code for performance and minimize the number of calls to external sources (e.g., the Wolfram Knowledgebase)
|
||||
-- Use only camel case for variable names (e.g., variableName).
|
||||
-- Use ONLY double quotes around all strings, including plot labels, etc. (e.g., \`PlotLegends -> {"sin(x)", "cos(x)", "tan(x)"}\`).
|
||||
-- Avoid use of QuantityMagnitude.
|
||||
-- If unevaluated Wolfram Language symbols appear in API results, use \`EntityValue[Entity["WolframLanguageSymbol",symbol],{"PlaintextUsage","Options"}]\` to validate or retrieve usage information for relevant symbols; \`symbol\` may be a list of symbols.
|
||||
-- Apply Evaluate to complex expressions like integrals before plotting (e.g., \`Plot[Evaluate[Integrate[...]]]\`).
|
||||
- Remove all comments and formatting from code passed to the "input" parameter; for example: instead of \`square[x_] := Module[{result},\n result = x^2 (* Calculate the square *)\n]\`, send \`square[x_]:=Module[{result},result=x^2]\`.
|
||||
- In ALL responses that involve code, write ALL code in Wolfram Language; create Wolfram Language functions even if an implementation is already well known in another language.
|
||||
59
api/app/stream.js
Normal file
59
api/app/stream.js
Normal file
@@ -0,0 +1,59 @@
|
||||
const { Readable } = require('stream');
|
||||
|
||||
class TextStream extends Readable {
|
||||
constructor(text, options = {}) {
|
||||
super(options);
|
||||
this.text = text;
|
||||
this.currentIndex = 0;
|
||||
this.delay = options.delay || 20; // Time in milliseconds
|
||||
}
|
||||
|
||||
_read() {
|
||||
const minChunkSize = 2;
|
||||
const maxChunkSize = 4;
|
||||
const { delay } = this;
|
||||
|
||||
if (this.currentIndex < this.text.length) {
|
||||
setTimeout(() => {
|
||||
const remainingChars = this.text.length - this.currentIndex;
|
||||
const chunkSize = Math.min(this.randomInt(minChunkSize, maxChunkSize + 1), remainingChars);
|
||||
|
||||
const chunk = this.text.slice(this.currentIndex, this.currentIndex + chunkSize);
|
||||
this.push(chunk);
|
||||
this.currentIndex += chunkSize;
|
||||
}, delay);
|
||||
} else {
|
||||
this.push(null); // signal end of data
|
||||
}
|
||||
}
|
||||
|
||||
randomInt(min, max) {
|
||||
return Math.floor(Math.random() * (max - min)) + min;
|
||||
}
|
||||
|
||||
async processTextStream(onProgressCallback) {
|
||||
const streamPromise = new Promise((resolve, reject) => {
|
||||
this.on('data', (chunk) => {
|
||||
onProgressCallback(chunk.toString());
|
||||
});
|
||||
|
||||
this.on('end', () => {
|
||||
console.log('Stream ended');
|
||||
resolve();
|
||||
});
|
||||
|
||||
this.on('error', (err) => {
|
||||
reject(err);
|
||||
});
|
||||
});
|
||||
|
||||
try {
|
||||
await streamPromise;
|
||||
} catch (err) {
|
||||
console.error('Error processing text stream:', err);
|
||||
// Handle the error appropriately, e.g., return an error message or throw an error
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = TextStream;
|
||||
@@ -1,23 +1,23 @@
|
||||
const { Configuration, OpenAIApi } = require('openai');
|
||||
// const { Configuration, OpenAIApi } = require('openai');
|
||||
const _ = require('lodash');
|
||||
const { genAzureEndpoint } = require('../utils/genAzureEndpoints');
|
||||
const { genAzureChatCompletion } = require('../utils/genAzureEndpoints');
|
||||
|
||||
const proxyEnvToAxiosProxy = (proxyString) => {
|
||||
if (!proxyString) return null;
|
||||
// const proxyEnvToAxiosProxy = (proxyString) => {
|
||||
// if (!proxyString) return null;
|
||||
|
||||
const regex = /^([^:]+):\/\/(?:([^:@]*):?([^:@]*)@)?([^:]+)(?::(\d+))?/;
|
||||
const [, protocol, username, password, host, port] = proxyString.match(regex);
|
||||
const proxyConfig = {
|
||||
protocol,
|
||||
host,
|
||||
port: port ? parseInt(port) : undefined,
|
||||
auth: username && password ? { username, password } : undefined
|
||||
};
|
||||
// const regex = /^([^:]+):\/\/(?:([^:@]*):?([^:@]*)@)?([^:]+)(?::(\d+))?/;
|
||||
// const [, protocol, username, password, host, port] = proxyString.match(regex);
|
||||
// const proxyConfig = {
|
||||
// protocol,
|
||||
// host,
|
||||
// port: port ? parseInt(port) : undefined,
|
||||
// auth: username && password ? { username, password } : undefined
|
||||
// };
|
||||
|
||||
return proxyConfig;
|
||||
};
|
||||
// return proxyConfig;
|
||||
// };
|
||||
|
||||
const titleConvo = async ({ endpoint, text, response }) => {
|
||||
const titleConvo = async ({ text, response, oaiApiKey }) => {
|
||||
let title = 'New Chat';
|
||||
const ChatGPTClient = (await import('@waylaidwanderer/chatgpt-api')).default;
|
||||
|
||||
@@ -50,11 +50,11 @@ const titleConvo = async ({ endpoint, text, response }) => {
|
||||
frequency_penalty: 0
|
||||
};
|
||||
|
||||
let apiKey = process.env.OPENAI_KEY;
|
||||
let apiKey = oaiApiKey || process.env.OPENAI_API_KEY;
|
||||
|
||||
if (azure) {
|
||||
apiKey = process.env.AZURE_OPENAI_API_KEY;
|
||||
titleGenClientOptions.reverseProxyUrl = genAzureEndpoint({
|
||||
titleGenClientOptions.reverseProxyUrl = genAzureChatCompletion({
|
||||
azureOpenAIApiInstanceName: process.env.AZURE_OPENAI_API_INSTANCE_NAME,
|
||||
azureOpenAIApiDeploymentName: process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME,
|
||||
azureOpenAIApiVersion: process.env.AZURE_OPENAI_API_VERSION
|
||||
|
||||
@@ -3,7 +3,7 @@ const mongoose = require('mongoose');
|
||||
const MONGO_URI = process.env.MONGO_URI;
|
||||
|
||||
if (!MONGO_URI) {
|
||||
throw new Error('Please define the MONGO_URI environment variable inside .env.local');
|
||||
throw new Error('Please define the MONGO_URI environment variable');
|
||||
}
|
||||
|
||||
/**
|
||||
|
||||
@@ -110,7 +110,7 @@ async function migrateDb() {
|
||||
ret[0] = await migrateToStrictFollowParentMessageIdChain();
|
||||
ret[1] = await migrateToSupportBetterCustomization();
|
||||
|
||||
const isMigrated = !!ret.find(element => !element?.noNeed);
|
||||
const isMigrated = !!ret.find((element) => !element?.noNeed);
|
||||
|
||||
if (!isMigrated) console.log('[Migrate] Nothing to migrate');
|
||||
}
|
||||
|
||||
@@ -9,7 +9,7 @@ const citeText = (res, noLinks = false) => {
|
||||
citations.forEach((citation) => {
|
||||
const digit = citation.match(/\d+?/g)[0];
|
||||
// result = result.replaceAll(citation, `<sup>[${digit}](#) </sup>`);
|
||||
result = result.replaceAll(citation, `<sup>[${digit}](#) </sup>`);
|
||||
result = result.replaceAll(citation, `[^${digit}^](#)`);
|
||||
});
|
||||
|
||||
return result;
|
||||
@@ -21,7 +21,7 @@ const citeText = (res, noLinks = false) => {
|
||||
|
||||
citations.forEach((citation) => {
|
||||
const digit = citation.match(/\d+?/g)[0];
|
||||
result = result.replaceAll(citation, `<sup>[${digit}](${sources[digit - 1]}) </sup>`);
|
||||
result = result.replaceAll(citation, `[^${digit}^](${sources[digit - 1]})`);
|
||||
// result = result.replaceAll(citation, `<sup>[${digit}](${sources[digit - 1]}) </sup>`);
|
||||
});
|
||||
|
||||
|
||||
@@ -8,7 +8,7 @@ const getCitations = (res) => {
|
||||
let links = textBlocks[textBlocks.length - 1]?.text.match(regex);
|
||||
if (links?.length === 0 || !links) return '';
|
||||
links = links.map((link) => link.trim());
|
||||
return links.join('\n');
|
||||
return links.join('\n - ');
|
||||
};
|
||||
|
||||
module.exports = getCitations;
|
||||
module.exports = getCitations;
|
||||
|
||||
@@ -2,11 +2,11 @@ function mergeSort(arr, compareFn) {
|
||||
if (arr.length <= 1) {
|
||||
return arr;
|
||||
}
|
||||
|
||||
|
||||
const mid = Math.floor(arr.length / 2);
|
||||
const leftArr = arr.slice(0, mid);
|
||||
const rightArr = arr.slice(mid);
|
||||
|
||||
|
||||
return merge(mergeSort(leftArr, compareFn), mergeSort(rightArr, compareFn), compareFn);
|
||||
}
|
||||
|
||||
@@ -14,7 +14,7 @@ function merge(leftArr, rightArr, compareFn) {
|
||||
const result = [];
|
||||
let leftIndex = 0;
|
||||
let rightIndex = 0;
|
||||
|
||||
|
||||
while (leftIndex < leftArr.length && rightIndex < rightArr.length) {
|
||||
if (compareFn(leftArr[leftIndex], rightArr[rightIndex]) < 0) {
|
||||
result.push(leftArr[leftIndex++]);
|
||||
@@ -22,8 +22,8 @@ function merge(leftArr, rightArr, compareFn) {
|
||||
result.push(rightArr[rightIndex++]);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
return result.concat(leftArr.slice(leftIndex)).concat(rightArr.slice(rightIndex));
|
||||
}
|
||||
|
||||
module.exports = mergeSort;
|
||||
module.exports = mergeSort;
|
||||
|
||||
@@ -19,7 +19,7 @@ const requireLocalAuth = (req, res, next) => {
|
||||
}
|
||||
if (!user) {
|
||||
log({
|
||||
title: '(requireLocalAuth) Error: No user',
|
||||
title: '(requireLocalAuth) Error: No user'
|
||||
});
|
||||
return res.status(422).send(info);
|
||||
}
|
||||
|
||||
@@ -30,7 +30,7 @@ module.exports = {
|
||||
return { message: 'Error saving conversation' };
|
||||
}
|
||||
},
|
||||
getConvosByPage: async (user, pageNumber = 1, pageSize = 12) => {
|
||||
getConvosByPage: async (user, pageNumber = 1, pageSize = 14) => {
|
||||
try {
|
||||
const totalConvos = (await Conversation.countDocuments({ user })) || 1;
|
||||
const totalPages = Math.ceil(totalConvos / pageSize);
|
||||
@@ -45,7 +45,7 @@ module.exports = {
|
||||
return { message: 'Error getting conversations' };
|
||||
}
|
||||
},
|
||||
getConvosQueried: async (user, convoIds, pageNumber = 1, pageSize = 12) => {
|
||||
getConvosQueried: async (user, convoIds, pageNumber = 1, pageSize = 14) => {
|
||||
try {
|
||||
if (!convoIds || convoIds.length === 0) {
|
||||
return { conversations: [], pages: 1, pageNumber, pageSize };
|
||||
|
||||
@@ -2,7 +2,7 @@ const Message = require('./schema/messageSchema');
|
||||
|
||||
module.exports = {
|
||||
Message,
|
||||
|
||||
|
||||
async saveMessage({
|
||||
messageId,
|
||||
newMessageId,
|
||||
@@ -13,7 +13,9 @@ module.exports = {
|
||||
isCreatedByUser = false,
|
||||
error,
|
||||
unfinished,
|
||||
cancelled
|
||||
cancelled,
|
||||
plugin = null,
|
||||
model = null,
|
||||
}) {
|
||||
try {
|
||||
// may also need to update the conversation here
|
||||
@@ -28,11 +30,13 @@ module.exports = {
|
||||
isCreatedByUser,
|
||||
error,
|
||||
unfinished,
|
||||
cancelled
|
||||
cancelled,
|
||||
plugin,
|
||||
model
|
||||
},
|
||||
{ upsert: true, new: true }
|
||||
);
|
||||
|
||||
|
||||
return {
|
||||
messageId,
|
||||
conversationId,
|
||||
@@ -41,13 +45,12 @@ module.exports = {
|
||||
text,
|
||||
isCreatedByUser
|
||||
};
|
||||
|
||||
} catch (err) {
|
||||
console.error(`Error saving message: ${err}`);
|
||||
throw new Error('Failed to save message.');
|
||||
}
|
||||
},
|
||||
|
||||
|
||||
async deleteMessagesSince({ messageId, conversationId }) {
|
||||
try {
|
||||
const message = await Message.findOne({ messageId }).exec();
|
||||
@@ -57,27 +60,24 @@ module.exports = {
|
||||
.deleteMany({ createdAt: { $gt: message.createdAt } })
|
||||
.exec();
|
||||
}
|
||||
|
||||
} catch (err) {
|
||||
console.error(`Error deleting messages: ${err}`);
|
||||
throw new Error('Failed to delete messages.');
|
||||
}
|
||||
},
|
||||
|
||||
|
||||
async getMessages(filter) {
|
||||
try {
|
||||
return await Message.find(filter).sort({ createdAt: 1 }).exec();
|
||||
|
||||
} catch (err) {
|
||||
console.error(`Error getting messages: ${err}`);
|
||||
throw new Error('Failed to get messages.');
|
||||
}
|
||||
},
|
||||
|
||||
|
||||
async deleteMessages(filter) {
|
||||
try {
|
||||
return await Message.deleteMany(filter).exec();
|
||||
|
||||
} catch (err) {
|
||||
console.error(`Error deleting messages: ${err}`);
|
||||
throw new Error('Failed to delete messages.');
|
||||
|
||||
@@ -38,8 +38,8 @@ module.exports = {
|
||||
}
|
||||
},
|
||||
deletePresets: async (user, filter) => {
|
||||
let toRemove = await Preset.find({ ...filter, user }).select('presetId');
|
||||
const ids = toRemove.map(instance => instance.presetId);
|
||||
// let toRemove = await Preset.find({ ...filter, user }).select('presetId');
|
||||
// const ids = toRemove.map((instance) => instance.presetId);
|
||||
let deleteCount = await Preset.deleteMany({ ...filter, user }).exec();
|
||||
return deleteCount;
|
||||
}
|
||||
|
||||
@@ -1,18 +1,21 @@
|
||||
const mongoose = require('mongoose');
|
||||
|
||||
const promptSchema = mongoose.Schema({
|
||||
title: {
|
||||
type: String,
|
||||
required: true
|
||||
const promptSchema = mongoose.Schema(
|
||||
{
|
||||
title: {
|
||||
type: String,
|
||||
required: true
|
||||
},
|
||||
prompt: {
|
||||
type: String,
|
||||
required: true
|
||||
},
|
||||
category: {
|
||||
type: String
|
||||
}
|
||||
},
|
||||
prompt: {
|
||||
type: String,
|
||||
required: true
|
||||
},
|
||||
category: {
|
||||
type: String,
|
||||
},
|
||||
}, { timestamps: true });
|
||||
{ timestamps: true }
|
||||
);
|
||||
|
||||
const Prompt = mongoose.models.Prompt || mongoose.model('Prompt', promptSchema);
|
||||
|
||||
@@ -31,7 +34,7 @@ module.exports = {
|
||||
},
|
||||
getPrompts: async (filter) => {
|
||||
try {
|
||||
return await Prompt.find(filter).exec()
|
||||
return await Prompt.find(filter).exec();
|
||||
} catch (error) {
|
||||
console.error(error);
|
||||
return { prompt: 'Error getting prompts' };
|
||||
@@ -39,10 +42,10 @@ module.exports = {
|
||||
},
|
||||
deletePrompts: async (filter) => {
|
||||
try {
|
||||
return await Prompt.deleteMany(filter).exec()
|
||||
return await Prompt.deleteMany(filter).exec();
|
||||
} catch (error) {
|
||||
console.error(error);
|
||||
return { prompt: 'Error deleting prompts' };
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
@@ -65,10 +65,9 @@ const userSchema = mongoose.Schema(
|
||||
unique: true,
|
||||
sparse: true
|
||||
},
|
||||
facebookId: {
|
||||
type: String,
|
||||
unique: true,
|
||||
sparse: true
|
||||
plugins: {
|
||||
type: Array,
|
||||
default: []
|
||||
},
|
||||
refreshToken: {
|
||||
type: [Session]
|
||||
@@ -79,7 +78,7 @@ const userSchema = mongoose.Schema(
|
||||
|
||||
//Remove refreshToken from the response
|
||||
userSchema.set('toJSON', {
|
||||
transform: function (doc, ret, options) {
|
||||
transform: function (_doc, ret) {
|
||||
delete ret.refreshToken;
|
||||
return ret;
|
||||
}
|
||||
@@ -95,17 +94,12 @@ userSchema.methods.toJSON = function () {
|
||||
avatar: this.avatar,
|
||||
role: this.role,
|
||||
emailVerified: this.emailVerified,
|
||||
plugins: this.plugins,
|
||||
createdAt: this.createdAt,
|
||||
updatedAt: this.updatedAt
|
||||
};
|
||||
};
|
||||
|
||||
const isProduction = process.env.NODE_ENV === 'production';
|
||||
const secretOrKey = isProduction ? process.env.JWT_SECRET_PROD : process.env.JWT_SECRET_DEV;
|
||||
const refreshSecret = isProduction
|
||||
? process.env.REFRESH_TOKEN_SECRET_PROD
|
||||
: process.env.REFRESH_TOKEN_SECRET_DEV;
|
||||
|
||||
userSchema.methods.generateToken = function () {
|
||||
const token = jwt.sign(
|
||||
{
|
||||
@@ -114,7 +108,7 @@ userSchema.methods.generateToken = function () {
|
||||
provider: this.provider,
|
||||
email: this.email
|
||||
},
|
||||
secretOrKey,
|
||||
process.env.JWT_SECRET,
|
||||
{ expiresIn: eval(process.env.SESSION_EXPIRY) }
|
||||
);
|
||||
return token;
|
||||
@@ -128,7 +122,7 @@ userSchema.methods.generateRefreshToken = function () {
|
||||
provider: this.provider,
|
||||
email: this.email
|
||||
},
|
||||
refreshSecret,
|
||||
process.env.JWT_REFRESH_SECRET,
|
||||
{ expiresIn: eval(process.env.REFRESH_TOKEN_EXPIRY) }
|
||||
);
|
||||
return refreshToken;
|
||||
@@ -142,7 +136,6 @@ userSchema.methods.comparePassword = function (candidatePassword, callback) {
|
||||
};
|
||||
|
||||
module.exports.hashPassword = async (password) => {
|
||||
|
||||
const hashedPassword = await new Promise((resolve, reject) => {
|
||||
bcrypt.hash(password, 10, function (err, hash) {
|
||||
if (err) reject(err);
|
||||
@@ -169,7 +162,7 @@ module.exports.validateUser = (user) => {
|
||||
password: Joi.string().min(8).max(60).allow('').allow(null)
|
||||
};
|
||||
|
||||
return Joi.validate(user, schema);
|
||||
return schema.validate(user);
|
||||
};
|
||||
|
||||
const User = mongoose.model('User', userSchema);
|
||||
|
||||
@@ -19,10 +19,7 @@ const createMeiliMongooseModel = function ({ index, indexName, client, attribute
|
||||
static async clearMeiliIndex() {
|
||||
await index.delete();
|
||||
// await index.deleteAllDocuments();
|
||||
await this.collection.updateMany(
|
||||
{ _meiliIndex: true },
|
||||
{ $set: { _meiliIndex: false } }
|
||||
);
|
||||
await this.collection.updateMany({ _meiliIndex: true }, { $set: { _meiliIndex: false } });
|
||||
}
|
||||
|
||||
static async resetIndex() {
|
||||
@@ -57,7 +54,7 @@ const createMeiliMongooseModel = function ({ index, indexName, client, attribute
|
||||
// Find objects into mongodb matching `objectID` from Meili search
|
||||
const query = {};
|
||||
// query[primaryKey] = { $in: _.map(data.hits, primaryKey) };
|
||||
query[primaryKey] = _.map(data.hits, hit => cleanUpPrimaryKeyValue(hit[primaryKey]));
|
||||
query[primaryKey] = _.map(data.hits, (hit) => cleanUpPrimaryKeyValue(hit[primaryKey]));
|
||||
// console.log('query', query);
|
||||
const hitsFromMongoose = await this.find(
|
||||
query,
|
||||
@@ -67,7 +64,7 @@ const createMeiliMongooseModel = function ({ index, indexName, client, attribute
|
||||
return { ...results, [key]: 1 };
|
||||
},
|
||||
{ _id: 1 }
|
||||
),
|
||||
)
|
||||
);
|
||||
|
||||
// Add additional data from mongodb into Meili search hits
|
||||
@@ -198,8 +195,8 @@ module.exports = function mongoMeili(schema, options) {
|
||||
if (Object.prototype.hasOwnProperty.call(schema.obj, 'messages')) {
|
||||
console.log('Syncing convos...');
|
||||
mongoose.model('Conversation').syncWithMeili();
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
if (Object.prototype.hasOwnProperty.call(schema.obj, 'messageId')) {
|
||||
console.log('Syncing messages...');
|
||||
mongoose.model('Message').syncWithMeili();
|
||||
|
||||
@@ -1,62 +0,0 @@
|
||||
module.exports = {
|
||||
// endpoint: [azureOpenAI, openAI, bingAI, chatGPTBrowser]
|
||||
endpoint: {
|
||||
type: String,
|
||||
default: null,
|
||||
required: true
|
||||
},
|
||||
// for azureOpenAI, openAI, chatGPTBrowser only
|
||||
model: {
|
||||
type: String,
|
||||
default: null,
|
||||
required: false
|
||||
},
|
||||
// for azureOpenAI, openAI only
|
||||
chatGptLabel: {
|
||||
type: String,
|
||||
default: null,
|
||||
required: false
|
||||
},
|
||||
promptPrefix: {
|
||||
type: String,
|
||||
default: null,
|
||||
required: false
|
||||
},
|
||||
temperature: {
|
||||
type: Number,
|
||||
default: 1,
|
||||
required: false
|
||||
},
|
||||
top_p: {
|
||||
type: Number,
|
||||
default: 1,
|
||||
required: false
|
||||
},
|
||||
presence_penalty: {
|
||||
type: Number,
|
||||
default: 0,
|
||||
required: false
|
||||
},
|
||||
frequency_penalty: {
|
||||
type: Number,
|
||||
default: 0,
|
||||
required: false
|
||||
},
|
||||
// for bingai only
|
||||
jailbreak: {
|
||||
type: Boolean,
|
||||
default: false
|
||||
},
|
||||
context: {
|
||||
type: String,
|
||||
default: null
|
||||
},
|
||||
systemMessage: {
|
||||
type: String,
|
||||
default: null
|
||||
},
|
||||
toneStyle: {
|
||||
type: String,
|
||||
default: null
|
||||
}
|
||||
};
|
||||
@@ -1,6 +1,6 @@
|
||||
const mongoose = require('mongoose');
|
||||
const mongoMeili = require('../plugins/mongoMeili');
|
||||
const conversationPreset = require('./conversationPreset');
|
||||
const { conversationPreset } = require('./defaults');
|
||||
const convoSchema = mongoose.Schema(
|
||||
{
|
||||
conversationId: {
|
||||
@@ -20,8 +20,18 @@ const convoSchema = mongoose.Schema(
|
||||
default: null
|
||||
},
|
||||
messages: [{ type: mongoose.Schema.Types.ObjectId, ref: 'Message' }],
|
||||
// google only
|
||||
examples: [{ type: mongoose.Schema.Types.Mixed }],
|
||||
agentOptions: {
|
||||
type: mongoose.Schema.Types.Mixed,
|
||||
default: null
|
||||
},
|
||||
...conversationPreset,
|
||||
// for bingAI only
|
||||
bingConversationId: {
|
||||
type: String,
|
||||
default: null
|
||||
},
|
||||
jailbreakConversationId: {
|
||||
type: String,
|
||||
default: null
|
||||
|
||||
158
api/models/schema/defaults.js
Normal file
158
api/models/schema/defaults.js
Normal file
@@ -0,0 +1,158 @@
|
||||
const conversationPreset = {
|
||||
// endpoint: [azureOpenAI, openAI, bingAI, chatGPTBrowser]
|
||||
endpoint: {
|
||||
type: String,
|
||||
default: null,
|
||||
required: true
|
||||
},
|
||||
// for azureOpenAI, openAI, chatGPTBrowser only
|
||||
model: {
|
||||
type: String,
|
||||
default: null,
|
||||
required: false
|
||||
},
|
||||
// for azureOpenAI, openAI only
|
||||
chatGptLabel: {
|
||||
type: String,
|
||||
default: null,
|
||||
required: false
|
||||
},
|
||||
// for google only
|
||||
modelLabel: {
|
||||
type: String,
|
||||
default: null,
|
||||
required: false
|
||||
},
|
||||
promptPrefix: {
|
||||
type: String,
|
||||
default: null,
|
||||
required: false
|
||||
},
|
||||
temperature: {
|
||||
type: Number,
|
||||
default: 1,
|
||||
required: false
|
||||
},
|
||||
top_p: {
|
||||
type: Number,
|
||||
default: 1,
|
||||
required: false
|
||||
},
|
||||
// for google only
|
||||
topP: {
|
||||
type: Number,
|
||||
default: 0.95,
|
||||
required: false
|
||||
},
|
||||
topK: {
|
||||
type: Number,
|
||||
default: 40,
|
||||
required: false
|
||||
},
|
||||
maxOutputTokens: {
|
||||
type: Number,
|
||||
default: 1024,
|
||||
required: false
|
||||
},
|
||||
presence_penalty: {
|
||||
type: Number,
|
||||
default: 0,
|
||||
required: false
|
||||
},
|
||||
frequency_penalty: {
|
||||
type: Number,
|
||||
default: 0,
|
||||
required: false
|
||||
},
|
||||
// for bingai only
|
||||
jailbreak: {
|
||||
type: Boolean,
|
||||
default: false
|
||||
},
|
||||
context: {
|
||||
type: String,
|
||||
default: null
|
||||
},
|
||||
systemMessage: {
|
||||
type: String,
|
||||
default: null
|
||||
},
|
||||
toneStyle: {
|
||||
type: String,
|
||||
default: null
|
||||
}
|
||||
};
|
||||
|
||||
const agentOptions = {
|
||||
model: {
|
||||
type: String,
|
||||
default: null,
|
||||
required: false
|
||||
},
|
||||
// for azureOpenAI, openAI only
|
||||
chatGptLabel: {
|
||||
type: String,
|
||||
default: null,
|
||||
required: false
|
||||
},
|
||||
// for google only
|
||||
modelLabel: {
|
||||
type: String,
|
||||
default: null,
|
||||
required: false
|
||||
},
|
||||
promptPrefix: {
|
||||
type: String,
|
||||
default: null,
|
||||
required: false
|
||||
},
|
||||
temperature: {
|
||||
type: Number,
|
||||
default: 1,
|
||||
required: false
|
||||
},
|
||||
top_p: {
|
||||
type: Number,
|
||||
default: 1,
|
||||
required: false
|
||||
},
|
||||
// for google only
|
||||
topP: {
|
||||
type: Number,
|
||||
default: 0.95,
|
||||
required: false
|
||||
},
|
||||
topK: {
|
||||
type: Number,
|
||||
default: 40,
|
||||
required: false
|
||||
},
|
||||
maxOutputTokens: {
|
||||
type: Number,
|
||||
default: 1024,
|
||||
required: false
|
||||
},
|
||||
presence_penalty: {
|
||||
type: Number,
|
||||
default: 0,
|
||||
required: false
|
||||
},
|
||||
frequency_penalty: {
|
||||
type: Number,
|
||||
default: 0,
|
||||
required: false
|
||||
},
|
||||
context: {
|
||||
type: String,
|
||||
default: null
|
||||
},
|
||||
systemMessage: {
|
||||
type: String,
|
||||
default: null
|
||||
}
|
||||
};
|
||||
|
||||
module.exports = {
|
||||
conversationPreset,
|
||||
agentOptions
|
||||
};
|
||||
@@ -14,6 +14,9 @@ const messageSchema = mongoose.Schema(
|
||||
required: true,
|
||||
meiliIndex: true
|
||||
},
|
||||
model: {
|
||||
type: String
|
||||
},
|
||||
conversationSignature: {
|
||||
type: String
|
||||
// required: true
|
||||
@@ -60,6 +63,20 @@ const messageSchema = mongoose.Schema(
|
||||
required: false,
|
||||
select: false,
|
||||
default: false
|
||||
},
|
||||
plugin: {
|
||||
latest: {
|
||||
type: String,
|
||||
required: false
|
||||
},
|
||||
inputs: {
|
||||
type: [mongoose.Schema.Types.Mixed],
|
||||
required: false
|
||||
},
|
||||
outputs: {
|
||||
type: String,
|
||||
required: false
|
||||
}
|
||||
}
|
||||
},
|
||||
{ timestamps: true }
|
||||
|
||||
26
api/models/schema/pluginAuthSchema.js
Normal file
26
api/models/schema/pluginAuthSchema.js
Normal file
@@ -0,0 +1,26 @@
|
||||
const mongoose = require('mongoose');
|
||||
|
||||
const pluginAuthSchema = mongoose.Schema(
|
||||
{
|
||||
authField: {
|
||||
type: String,
|
||||
required: true,
|
||||
},
|
||||
value: {
|
||||
type: String,
|
||||
required: true
|
||||
},
|
||||
userId: {
|
||||
type: String,
|
||||
required: true
|
||||
},
|
||||
pluginKey: {
|
||||
type: String,
|
||||
}
|
||||
},
|
||||
{ timestamps: true }
|
||||
);
|
||||
|
||||
const PluginAuth = mongoose.models.Plugin || mongoose.model('PluginAuth', pluginAuthSchema);
|
||||
|
||||
module.exports = PluginAuth;
|
||||
@@ -1,5 +1,5 @@
|
||||
const mongoose = require('mongoose');
|
||||
const conversationPreset = require('./conversationPreset');
|
||||
const { conversationPreset } = require('./defaults');
|
||||
const presetSchema = mongoose.Schema(
|
||||
{
|
||||
presetId: {
|
||||
@@ -17,7 +17,13 @@ const presetSchema = mongoose.Schema(
|
||||
type: String,
|
||||
default: null
|
||||
},
|
||||
...conversationPreset
|
||||
// google only
|
||||
examples: [{ type: mongoose.Schema.Types.Mixed }],
|
||||
...conversationPreset,
|
||||
agentOptions: {
|
||||
type: mongoose.Schema.Types.Mixed,
|
||||
default: null
|
||||
}
|
||||
},
|
||||
{ timestamps: true }
|
||||
);
|
||||
|
||||
@@ -1,22 +1,22 @@
|
||||
const mongoose = require("mongoose");
|
||||
const mongoose = require('mongoose');
|
||||
const Schema = mongoose.Schema;
|
||||
|
||||
const tokenSchema = new Schema({
|
||||
userId: {
|
||||
type: Schema.Types.ObjectId,
|
||||
required: true,
|
||||
ref: "user",
|
||||
ref: 'user'
|
||||
},
|
||||
token: {
|
||||
type: String,
|
||||
required: true,
|
||||
required: true
|
||||
},
|
||||
createdAt: {
|
||||
type: Date,
|
||||
required: true,
|
||||
default: Date.now,
|
||||
expires: 900,
|
||||
},
|
||||
expires: 900
|
||||
}
|
||||
});
|
||||
|
||||
module.exports = mongoose.model("Token", tokenSchema);
|
||||
module.exports = mongoose.model('Token', tokenSchema);
|
||||
|
||||
10968
api/package-lock.json
generated
10968
api/package-lock.json
generated
File diff suppressed because it is too large
Load Diff
@@ -1,56 +1,63 @@
|
||||
{
|
||||
"name": "chatgpt-clone",
|
||||
"version": "0.4.2",
|
||||
"name": "chat-backend",
|
||||
"version": "0.4.8",
|
||||
"description": "",
|
||||
"main": "server/index.js",
|
||||
"scripts": {
|
||||
"start": "node server/index.js",
|
||||
"server-dev": "npx nodemon server/index.js"
|
||||
"start": "echo 'please run this from the root directory'",
|
||||
"server-dev": "echo 'please run this from the root directory'",
|
||||
"test2": "node --inspect app/langchain/test2.js",
|
||||
"test3": "node --inspect app/langchain/test3.js",
|
||||
"test4": "node --inspect app/langchain/test4.js",
|
||||
"test5": "node --inspect app/langchain/test5.js",
|
||||
"test8": "node --inspect app/langchain/test8.js",
|
||||
"langchain": "node app/langchain/test2.js"
|
||||
},
|
||||
"repository": {
|
||||
"type": "git",
|
||||
"url": "git+https://github.com/danny-avila/chatgpt-clone.git"
|
||||
"url": "git+https://github.com/danny-avila/LibreChat.git"
|
||||
},
|
||||
"keywords": [],
|
||||
"author": "",
|
||||
"license": "ISC",
|
||||
"bugs": {
|
||||
"url": "https://github.com/danny-avila/chatgpt-clone/issues"
|
||||
"url": "https://github.com/danny-avila/LibreChat/issues"
|
||||
},
|
||||
"homepage": "https://github.com/danny-avila/chatgpt-clone#readme",
|
||||
"homepage": "https://github.com/danny-avila/LibreChat#readme",
|
||||
"dependencies": {
|
||||
"@dqbd/tiktoken": "^1.0.2",
|
||||
"@keyv/mongo": "^2.1.8",
|
||||
"@waylaidwanderer/chatgpt-api": "github:danny-avila/node-chatgpt-api",
|
||||
"@waylaidwanderer/chatgpt-api": "^1.37.0",
|
||||
"axios": "^1.3.4",
|
||||
"bcrypt": "^5.1.0",
|
||||
"bcryptjs": "^2.4.3",
|
||||
"cheerio": "^1.0.0-rc.12",
|
||||
"cookie": "^0.5.0",
|
||||
"cookie-parser": "^1.4.6",
|
||||
"cors": "^2.8.5",
|
||||
"crypto": "^1.0.1",
|
||||
"dotenv": "^16.0.3",
|
||||
"eslint": "^8.36.0",
|
||||
"eslint": "^8.41.0",
|
||||
"express": "^4.18.2",
|
||||
"googleapis": "^118.0.0",
|
||||
"handlebars": "^4.7.7",
|
||||
"html": "^1.0.0",
|
||||
"joi": "^14.3.1",
|
||||
"joi": "^17.9.2",
|
||||
"js-yaml": "^4.1.0",
|
||||
"jsonwebtoken": "^9.0.0",
|
||||
"keyv": "^4.5.2",
|
||||
"keyv-file": "^0.2.0",
|
||||
"langchain": "^0.0.91",
|
||||
"lodash": "^4.17.21",
|
||||
"meilisearch": "^0.31.1",
|
||||
"mongoose": "^6.9.0",
|
||||
"meilisearch": "^0.33.0",
|
||||
"mongoose": "^7.1.1",
|
||||
"nodemailer": "^6.9.1",
|
||||
"og-chatgpt-api": "npm:@waylaidwanderer/chatgpt-api@^1.35.0",
|
||||
"openai": "^3.1.0",
|
||||
"openai": "^3.2.1",
|
||||
"passport": "^0.6.0",
|
||||
"passport-facebook": "^3.0.0",
|
||||
"passport-google-oauth20": "^2.0.0",
|
||||
"passport-jwt": "^4.0.1",
|
||||
"passport-local": "^1.0.0",
|
||||
"pino": "^8.12.1",
|
||||
"sanitize": "^2.1.2"
|
||||
"sanitize": "^2.1.2",
|
||||
"sharp": "^0.32.1"
|
||||
},
|
||||
"devDependencies": {
|
||||
"nodemon": "^2.0.20",
|
||||
|
||||
54
api/server/controllers/PluginController.js
Normal file
54
api/server/controllers/PluginController.js
Normal file
@@ -0,0 +1,54 @@
|
||||
// const { getAvailableToolsService } = require('../services/PluginService');
|
||||
const fs = require('fs');
|
||||
const path = require('path');
|
||||
|
||||
const filterUniquePlugins = (plugins) => {
|
||||
const seen = new Set();
|
||||
return plugins.filter((plugin) => {
|
||||
const duplicate = seen.has(plugin.pluginKey);
|
||||
seen.add(plugin.pluginKey);
|
||||
return !duplicate;
|
||||
});
|
||||
};
|
||||
|
||||
const isPluginAuthenticated = (plugin) => {
|
||||
if (!plugin.authConfig || plugin.authConfig.length === 0) {
|
||||
return false;
|
||||
}
|
||||
|
||||
return plugin.authConfig.every((authFieldObj) => {
|
||||
const envValue = process.env[authFieldObj.authField];
|
||||
return envValue && envValue.trim() !== '';
|
||||
});
|
||||
};
|
||||
|
||||
const getAvailablePluginsController = async (req, res) => {
|
||||
try {
|
||||
fs.readFile(
|
||||
path.join(__dirname, '..', '..', 'app', 'langchain', 'tools', 'manifest.json'),
|
||||
'utf8',
|
||||
(err, data) => {
|
||||
if (err) {
|
||||
res.status(500).json({ message: err.message });
|
||||
} else {
|
||||
const jsonData = JSON.parse(data);
|
||||
const uniquePlugins = filterUniquePlugins(jsonData);
|
||||
const authenticatedPlugins = uniquePlugins.map((plugin) => {
|
||||
if (isPluginAuthenticated(plugin)) {
|
||||
return { ...plugin, authenticated: true };
|
||||
} else {
|
||||
return plugin;
|
||||
}
|
||||
});
|
||||
res.status(200).json(authenticatedPlugins);
|
||||
}
|
||||
}
|
||||
);
|
||||
} catch (error) {
|
||||
res.status(500).json({ message: error.message });
|
||||
}
|
||||
};
|
||||
|
||||
module.exports = {
|
||||
getAvailablePluginsController
|
||||
};
|
||||
55
api/server/controllers/UserController.js
Normal file
55
api/server/controllers/UserController.js
Normal file
@@ -0,0 +1,55 @@
|
||||
const { updateUserPluginsService } = require('../services/UserService');
|
||||
const { updateUserPluginAuth, deleteUserPluginAuth } = require('../services/PluginService');
|
||||
|
||||
const getUserController = async (req, res) => {
|
||||
res.status(200).send(req.user);
|
||||
};
|
||||
|
||||
const updateUserPluginsController = async (req, res) => {
|
||||
const { user } = req;
|
||||
const { pluginKey, action, auth } = req.body;
|
||||
let authService;
|
||||
try {
|
||||
const userPluginsService = await updateUserPluginsService(user, pluginKey, action);
|
||||
|
||||
if (userPluginsService instanceof Error) {
|
||||
console.log(userPluginsService);
|
||||
const { status, message } = userPluginsService;
|
||||
res.status(status).send({ message });
|
||||
}
|
||||
if (auth) {
|
||||
const keys = Object.keys(auth);
|
||||
const values = Object.values(auth);
|
||||
if (action === 'install' && keys.length > 0) {
|
||||
for (let i = 0; i < keys.length; i++) {
|
||||
authService = await updateUserPluginAuth(user.id, keys[i], pluginKey, values[i]);
|
||||
if (authService instanceof Error) {
|
||||
console.log(authService);
|
||||
const { status, message } = authService;
|
||||
res.status(status).send({ message });
|
||||
}
|
||||
}
|
||||
}
|
||||
if (action === 'uninstall' && keys.length > 0) {
|
||||
for (let i = 0; i < keys.length; i++) {
|
||||
authService = await deleteUserPluginAuth(user.id, keys[i]);
|
||||
if (authService instanceof Error) {
|
||||
console.log(authService);
|
||||
const { status, message } = authService;
|
||||
res.status(status).send({ message });
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
res.status(200).send();
|
||||
} catch (err) {
|
||||
console.log(err);
|
||||
res.status(500).json({ message: err.message });
|
||||
}
|
||||
};
|
||||
|
||||
module.exports = {
|
||||
getUserController,
|
||||
updateUserPluginsController
|
||||
};
|
||||
@@ -1,57 +1,11 @@
|
||||
const {
|
||||
loginUser,
|
||||
logoutUser,
|
||||
registerUser,
|
||||
requestPasswordReset,
|
||||
resetPassword,
|
||||
} = require("../services/auth.service");
|
||||
resetPassword
|
||||
} = require('../services/auth.service');
|
||||
|
||||
const isProduction = process.env.NODE_ENV === 'production';
|
||||
|
||||
const loginController = async (req, res) => {
|
||||
try {
|
||||
const token = req.user.generateToken();
|
||||
const user = await loginUser(req.user)
|
||||
if(user) {
|
||||
res.cookie('token', token, {
|
||||
expires: new Date(Date.now() + eval(process.env.SESSION_EXPIRY)),
|
||||
httpOnly: false,
|
||||
secure: isProduction
|
||||
});
|
||||
res.status(200).send({ token, user });
|
||||
}
|
||||
else {
|
||||
return res.status(400).json({ message: 'Invalid credentials' });
|
||||
}
|
||||
}
|
||||
catch (err) {
|
||||
console.log(err);
|
||||
return res.status(500).json({ message: err.message });
|
||||
}
|
||||
};
|
||||
|
||||
const logoutController = async (req, res) => {
|
||||
const { signedCookies = {} } = req;
|
||||
const { refreshToken } = signedCookies;
|
||||
try {
|
||||
const logout = await logoutUser(req.user, refreshToken);
|
||||
console.log(logout)
|
||||
const { status, message } = logout;
|
||||
if (status === 200) {
|
||||
res.clearCookie('token');
|
||||
res.clearCookie('refreshToken');
|
||||
res.status(status).send({ message });
|
||||
}
|
||||
else {
|
||||
res.status(status).send({ message });
|
||||
}
|
||||
}
|
||||
catch (err) {
|
||||
console.log(err);
|
||||
return res.status(500).json({ message: err.message });
|
||||
}
|
||||
}
|
||||
|
||||
const registrationController = async (req, res) => {
|
||||
try {
|
||||
const response = await registerUser(req.body);
|
||||
@@ -65,13 +19,11 @@ const registrationController = async (req, res) => {
|
||||
secure: isProduction
|
||||
});
|
||||
res.status(status).send({ user });
|
||||
}
|
||||
else {
|
||||
} else {
|
||||
const { status, message } = response;
|
||||
res.status(status).send({ message });
|
||||
}
|
||||
}
|
||||
catch (err) {
|
||||
} catch (err) {
|
||||
console.log(err);
|
||||
return res.status(500).json({ message: err.message });
|
||||
}
|
||||
@@ -83,17 +35,13 @@ const getUserController = async (req, res) => {
|
||||
|
||||
const resetPasswordRequestController = async (req, res) => {
|
||||
try {
|
||||
const resetService = await requestPasswordReset(
|
||||
req.body.email
|
||||
);
|
||||
const resetService = await requestPasswordReset(req.body.email);
|
||||
if (resetService.link) {
|
||||
return res.status(200).json(resetService);
|
||||
}
|
||||
else {
|
||||
} else {
|
||||
return res.status(400).json(resetService);
|
||||
}
|
||||
}
|
||||
catch (e) {
|
||||
} catch (e) {
|
||||
console.log(e);
|
||||
return res.status(400).json({ message: e.message });
|
||||
}
|
||||
@@ -106,14 +54,12 @@ const resetPasswordController = async (req, res) => {
|
||||
req.body.token,
|
||||
req.body.password
|
||||
);
|
||||
if(resetPasswordService instanceof Error) {
|
||||
if (resetPasswordService instanceof Error) {
|
||||
return res.status(400).json(resetPasswordService);
|
||||
}
|
||||
else {
|
||||
} else {
|
||||
return res.status(200).json(resetPasswordService);
|
||||
}
|
||||
}
|
||||
catch (e) {
|
||||
} catch (e) {
|
||||
console.log(e);
|
||||
return res.status(400).json({ message: e.message });
|
||||
}
|
||||
@@ -171,10 +117,8 @@ const refreshController = async (req, res, next) => {
|
||||
|
||||
module.exports = {
|
||||
getUserController,
|
||||
loginController,
|
||||
logoutController,
|
||||
refreshController,
|
||||
registrationController,
|
||||
resetPasswordRequestController,
|
||||
resetPasswordController,
|
||||
};
|
||||
resetPasswordController
|
||||
};
|
||||
|
||||
39
api/server/controllers/auth/login.controller.js
Normal file
39
api/server/controllers/auth/login.controller.js
Normal file
@@ -0,0 +1,39 @@
|
||||
const User = require('../../../models/User');
|
||||
|
||||
const loginController = async (req, res) => {
|
||||
try {
|
||||
const user = await User.findById(
|
||||
req.user._id
|
||||
);
|
||||
|
||||
// If user doesn't exist, return error
|
||||
if (!user) { // typeof user !== User) { // this doesn't seem to resolve the User type ??
|
||||
return res.status(400).json({ message: 'Invalid credentials' });
|
||||
}
|
||||
|
||||
const token = req.user.generateToken();
|
||||
const expires = eval(process.env.SESSION_EXPIRY);
|
||||
|
||||
// Add token to cookie
|
||||
res.cookie(
|
||||
'token',
|
||||
token,
|
||||
{
|
||||
expires: new Date(Date.now() + expires),
|
||||
httpOnly: false,
|
||||
secure: process.env.NODE_ENV === 'production'
|
||||
}
|
||||
);
|
||||
|
||||
return res.status(200).send({ token, user });
|
||||
} catch (err) {
|
||||
console.log(err);
|
||||
}
|
||||
|
||||
// Generic error messages are safer
|
||||
return res.status(500).json({ message: 'Something went wrong' });
|
||||
};
|
||||
|
||||
module.exports = {
|
||||
loginController
|
||||
};
|
||||
21
api/server/controllers/auth/logout.controller.js
Normal file
21
api/server/controllers/auth/logout.controller.js
Normal file
@@ -0,0 +1,21 @@
|
||||
const logoutUser = require('../../services/auth.service');
|
||||
|
||||
const logoutController = async (req, res) => {
|
||||
const { signedCookies = {} } = req;
|
||||
const { refreshToken } = signedCookies;
|
||||
try {
|
||||
const logout = await logoutUser(req.user, refreshToken);
|
||||
const { status, message } = logout;
|
||||
res.clearCookie('token');
|
||||
res.clearCookie('refreshToken');
|
||||
return res.status(status).send({ message });
|
||||
|
||||
} catch (err) {
|
||||
console.log(err);
|
||||
return res.status(500).json({ message: err.message });
|
||||
}
|
||||
};
|
||||
|
||||
module.exports = {
|
||||
logoutController
|
||||
};
|
||||
@@ -10,8 +10,8 @@ const handleDuplicateKeyError = (err, res) => {
|
||||
//handle validation errors
|
||||
const handleValidationError = (err, res) => {
|
||||
console.log('congrats you hit the validation middleware');
|
||||
let errors = Object.values(err.errors).map(el => el.message);
|
||||
let fields = Object.values(err.errors).map(el => el.path);
|
||||
let errors = Object.values(err.errors).map((el) => el.message);
|
||||
let fields = Object.values(err.errors).map((el) => el.path);
|
||||
let code = 400;
|
||||
if (errors.length > 1) {
|
||||
const formattedErrors = errors.join(' ');
|
||||
|
||||
@@ -7,11 +7,14 @@ const cors = require('cors');
|
||||
const routes = require('./routes');
|
||||
const errorController = require('./controllers/error.controller');
|
||||
const passport = require('passport');
|
||||
|
||||
const port = process.env.PORT || 3080;
|
||||
const host = process.env.HOST || 'localhost';
|
||||
const projectPath = path.join(__dirname, '..', '..', 'client');
|
||||
|
||||
// Init the config and validate it
|
||||
const config = require('../../config/loader');
|
||||
config.validate(); // Validate the config
|
||||
|
||||
(async () => {
|
||||
await connectDb();
|
||||
console.log('Connected to MongoDB');
|
||||
@@ -23,6 +26,8 @@ const projectPath = path.join(__dirname, '..', '..', 'client');
|
||||
app.use(express.json());
|
||||
app.use(express.urlencoded({ extended: true }));
|
||||
app.use(express.static(path.join(projectPath, 'dist')));
|
||||
app.use(express.static(path.join(projectPath, 'public')));
|
||||
|
||||
app.set('trust proxy', 1); // trust first proxy
|
||||
app.use(cors());
|
||||
|
||||
@@ -30,15 +35,16 @@ const projectPath = path.join(__dirname, '..', '..', 'client');
|
||||
app.use(passport.initialize());
|
||||
require('../strategies/jwtStrategy');
|
||||
require('../strategies/localStrategy');
|
||||
if(process.env.GOOGLE_CLIENT_ID && process.env.GOOGLE_CLIENT_SECRET) {
|
||||
if (process.env.GOOGLE_CLIENT_ID && process.env.GOOGLE_CLIENT_SECRET) {
|
||||
require('../strategies/googleStrategy');
|
||||
}
|
||||
if(process.env.FACEBOOK_CLIENT_ID && process.env.FACEBOOK_CLIENT_SECRET) {
|
||||
if (process.env.FACEBOOK_CLIENT_ID && process.env.FACEBOOK_CLIENT_SECRET) {
|
||||
require('../strategies/facebookStrategy');
|
||||
}
|
||||
app.use('/oauth', routes.oauth)
|
||||
app.use('/oauth', routes.oauth);
|
||||
// api endpoint
|
||||
app.use('/api/auth', routes.auth);
|
||||
app.use('/api/user', routes.user);
|
||||
app.use('/api/search', routes.search);
|
||||
app.use('/api/ask', routes.ask);
|
||||
app.use('/api/messages', routes.messages);
|
||||
@@ -47,8 +53,7 @@ const projectPath = path.join(__dirname, '..', '..', 'client');
|
||||
app.use('/api/prompts', routes.prompts);
|
||||
app.use('/api/tokenizer', routes.tokenizer);
|
||||
app.use('/api/endpoints', routes.endpoints);
|
||||
|
||||
|
||||
app.use('/api/plugins', routes.plugins);
|
||||
|
||||
// static files
|
||||
app.get('/*', function (req, res) {
|
||||
@@ -60,14 +65,16 @@ const projectPath = path.join(__dirname, '..', '..', 'client');
|
||||
console.log(
|
||||
`Server listening on all interface at port ${port}. Use http://localhost:${port} to access it`
|
||||
);
|
||||
else console.log(`Server listening at http://${host == '0.0.0.0' ? 'localhost' : host}:${port}`);
|
||||
else
|
||||
console.log(`Server listening at http://${host == '0.0.0.0' ? 'localhost' : host}:${port}`);
|
||||
});
|
||||
})();
|
||||
|
||||
let messageCount = 0;
|
||||
process.on('uncaughtException', (err) => {
|
||||
if (!err.message.includes('fetch failed')) {
|
||||
console.error('There was an uncaught error:', err.message);
|
||||
console.error('There was an uncaught error:');
|
||||
console.error(err);
|
||||
}
|
||||
|
||||
if (err.message.includes('fetch failed')) {
|
||||
|
||||
@@ -40,7 +40,7 @@ router.post('/', requireJwtAuth, async (req, res) => {
|
||||
jailbreakConversationId: req.body?.jailbreakConversationId ?? null,
|
||||
systemMessage: req.body?.systemMessage ?? null,
|
||||
context: req.body?.context ?? null,
|
||||
toneStyle: req.body?.toneStyle ?? 'fast',
|
||||
toneStyle: req.body?.toneStyle ?? 'creative',
|
||||
token: req.body?.token ?? null
|
||||
};
|
||||
else
|
||||
@@ -51,7 +51,7 @@ router.post('/', requireJwtAuth, async (req, res) => {
|
||||
conversationSignature: req.body?.conversationSignature ?? null,
|
||||
clientId: req.body?.clientId ?? null,
|
||||
invocationId: req.body?.invocationId ?? null,
|
||||
toneStyle: req.body?.toneStyle ?? 'fast',
|
||||
toneStyle: req.body?.toneStyle ?? 'creative',
|
||||
token: req.body?.token ?? null
|
||||
};
|
||||
|
||||
@@ -110,7 +110,7 @@ const ask = async ({
|
||||
|
||||
try {
|
||||
let lastSavedTimestamp = 0;
|
||||
const { onProgress: progressCallback, getPartialText } = createOnProgress({
|
||||
const { onProgress: progressCallback } = createOnProgress({
|
||||
onProgress: ({ text }) => {
|
||||
const currentTimestamp = Date.now();
|
||||
if (currentTimestamp - lastSavedTimestamp > 500) {
|
||||
@@ -129,10 +129,15 @@ const ask = async ({
|
||||
}
|
||||
});
|
||||
const abortController = new AbortController();
|
||||
let bingConversationId = null;
|
||||
if (!isNewConversation) {
|
||||
const convo = await getConvo(req.user.id, conversationId);
|
||||
bingConversationId = convo.bingConversationId;
|
||||
}
|
||||
let response = await askBing({
|
||||
text,
|
||||
parentMessageId: userParentMessageId,
|
||||
conversationId,
|
||||
conversationId: bingConversationId ?? conversationId,
|
||||
...endpointOption,
|
||||
onProgress: progressCallback.call(null, {
|
||||
res,
|
||||
@@ -147,21 +152,25 @@ const ask = async ({
|
||||
const newConversationId = endpointOption?.jailbreak
|
||||
? response.jailbreakConversationId
|
||||
: response.conversationId || conversationId;
|
||||
const newUserMassageId = response.parentMessageId || response.details.requestId || userMessageId;
|
||||
const newUserMessageId =
|
||||
response.parentMessageId || response.details.requestId || userMessageId;
|
||||
const newResponseMessageId = response.messageId || response.details.messageId;
|
||||
|
||||
// STEP1 generate response message
|
||||
response.text = response.response || response.details.spokenText || '**Bing refused to answer.**';
|
||||
response.text =
|
||||
response.response || response.details.spokenText || '**Bing refused to answer.**';
|
||||
|
||||
let responseMessage = {
|
||||
conversationId: newConversationId,
|
||||
conversationId,
|
||||
bingConversationId: newConversationId,
|
||||
messageId: responseMessageId,
|
||||
newMessageId: newResponseMessageId,
|
||||
parentMessageId: overrideParentMessageId || newUserMassageId,
|
||||
parentMessageId: overrideParentMessageId || newUserMessageId,
|
||||
sender: endpointOption?.jailbreak ? 'Sydney' : 'BingAI',
|
||||
text: await handleText(response, true),
|
||||
suggestions:
|
||||
response.details.suggestedResponses && response.details.suggestedResponses.map((s) => s.text),
|
||||
response.details.suggestedResponses &&
|
||||
response.details.suggestedResponses.map((s) => s.text),
|
||||
unfinished: false,
|
||||
cancelled: false,
|
||||
error: false
|
||||
@@ -170,31 +179,7 @@ const ask = async ({
|
||||
await saveMessage(responseMessage);
|
||||
responseMessage.messageId = newResponseMessageId;
|
||||
|
||||
// STEP2 update the convosation.
|
||||
|
||||
// First update conversationId if needed
|
||||
// Note!
|
||||
// Bing API will not use our conversationId at the first time,
|
||||
// so change the placeholder conversationId to the real one.
|
||||
// Attition: the api will also create new conversationId while using invalid userMessage.parentMessageId,
|
||||
// but in this situation, don't change the conversationId, but create new convo.
|
||||
|
||||
let conversationUpdate = { conversationId: newConversationId, endpoint: 'bingAI' };
|
||||
if (conversationId != newConversationId)
|
||||
if (isNewConversation) {
|
||||
// change the conversationId to new one
|
||||
conversationUpdate = {
|
||||
...conversationUpdate,
|
||||
conversationId: conversationId,
|
||||
newConversationId: newConversationId
|
||||
};
|
||||
} else {
|
||||
// create new conversation
|
||||
conversationUpdate = {
|
||||
...conversationUpdate,
|
||||
...endpointOption
|
||||
};
|
||||
}
|
||||
let conversationUpdate = { conversationId, bingConversationId: newConversationId, endpoint: 'bingAI' };
|
||||
|
||||
if (endpointOption?.jailbreak) {
|
||||
conversationUpdate.jailbreak = true;
|
||||
@@ -207,16 +192,16 @@ const ask = async ({
|
||||
}
|
||||
|
||||
await saveConvo(req.user.id, conversationUpdate);
|
||||
conversationId = newConversationId;
|
||||
|
||||
// STEP3 update the user message
|
||||
userMessage.conversationId = newConversationId;
|
||||
userMessage.messageId = newUserMassageId;
|
||||
userMessage.messageId = newUserMessageId;
|
||||
|
||||
// If response has parentMessageId, the fake userMessage.messageId should be updated to the real one.
|
||||
if (!overrideParentMessageId)
|
||||
await saveMessage({ ...userMessage, messageId: userMessageId, newMessageId: newUserMassageId });
|
||||
userMessageId = newUserMassageId;
|
||||
await saveMessage({
|
||||
...userMessage,
|
||||
messageId: userMessageId,
|
||||
newMessageId: newUserMessageId
|
||||
});
|
||||
userMessageId = newUserMessageId;
|
||||
|
||||
sendMessage(res, {
|
||||
title: await getConvoTitle(req.user.id, conversationId),
|
||||
@@ -228,7 +213,11 @@ const ask = async ({
|
||||
res.end();
|
||||
|
||||
if (userParentMessageId == '00000000-0000-0000-0000-000000000000') {
|
||||
const title = await titleConvo({ endpoint: endpointOption?.endpoint, text, response: responseMessage });
|
||||
const title = await titleConvo({
|
||||
endpoint: endpointOption?.endpoint,
|
||||
text,
|
||||
response: responseMessage
|
||||
});
|
||||
|
||||
await saveConvo(req.user.id, {
|
||||
conversationId: conversationId,
|
||||
|
||||
@@ -76,7 +76,6 @@ const ask = async ({
|
||||
userMessage,
|
||||
endpointOption,
|
||||
conversationId,
|
||||
preSendRequest = true,
|
||||
overrideParentMessageId = null,
|
||||
req,
|
||||
res
|
||||
@@ -92,10 +91,8 @@ const ask = async ({
|
||||
'X-Accel-Buffering': 'no'
|
||||
});
|
||||
|
||||
if (preSendRequest) sendMessage(res, { message: userMessage, created: true });
|
||||
|
||||
let responseMessageId = crypto.randomUUID();
|
||||
|
||||
let getPartialMessage = null;
|
||||
try {
|
||||
let lastSavedTimestamp = 0;
|
||||
const { onProgress: progressCallback, getPartialText } = createOnProgress({
|
||||
@@ -116,15 +113,30 @@ const ask = async ({
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
getPartialMessage = getPartialText;
|
||||
const abortController = new AbortController();
|
||||
let response = await browserClient({
|
||||
text,
|
||||
parentMessageId: userParentMessageId,
|
||||
conversationId,
|
||||
...endpointOption,
|
||||
onProgress: progressCallback.call(null, { res, text }),
|
||||
abortController,
|
||||
userId
|
||||
userId,
|
||||
onProgress: progressCallback.call(null, { res, text }),
|
||||
onEventMessage: (eventMessage) => {
|
||||
let data = null;
|
||||
try {
|
||||
data = JSON.parse(eventMessage.data);
|
||||
} catch (e) {
|
||||
return;
|
||||
}
|
||||
|
||||
sendMessage(res, {
|
||||
message: { ...userMessage, conversationId: data.conversation_id },
|
||||
created: true
|
||||
});
|
||||
}
|
||||
});
|
||||
|
||||
console.log('CLIENT RESPONSE', response);
|
||||
@@ -180,7 +192,11 @@ const ask = async ({
|
||||
|
||||
// If response has parentMessageId, the fake userMessage.messageId should be updated to the real one.
|
||||
if (!overrideParentMessageId)
|
||||
await saveMessage({ ...userMessage, messageId: userMessageId, newMessageId: newUserMassageId });
|
||||
await saveMessage({
|
||||
...userMessage,
|
||||
messageId: userMessageId,
|
||||
newMessageId: newUserMassageId
|
||||
});
|
||||
userMessageId = newUserMassageId;
|
||||
|
||||
sendMessage(res, {
|
||||
@@ -208,8 +224,8 @@ const ask = async ({
|
||||
parentMessageId: overrideParentMessageId || userMessageId,
|
||||
unfinished: false,
|
||||
cancelled: false,
|
||||
error: true,
|
||||
text: error.message
|
||||
// error: true,
|
||||
text: `${getPartialMessage() ?? ''}\n\nError message: "${error.message}"`
|
||||
};
|
||||
await saveMessage(errorMessage);
|
||||
handleError(res, errorMessage);
|
||||
|
||||
279
api/server/routes/ask/askGPTPlugins.js
Normal file
279
api/server/routes/ask/askGPTPlugins.js
Normal file
@@ -0,0 +1,279 @@
|
||||
const express = require('express');
|
||||
const router = express.Router();
|
||||
const { titleConvo } = require('../../../app/');
|
||||
const { getOpenAIModels } = require('../endpoints');
|
||||
const ChatAgent = require('../../../app/langchain/ChatAgent');
|
||||
const { validateTools } = require('../../../app/langchain/tools');
|
||||
const { saveMessage, getConvoTitle, saveConvo, getConvo } = require('../../../models');
|
||||
const {
|
||||
handleError,
|
||||
sendMessage,
|
||||
createOnProgress,
|
||||
formatSteps,
|
||||
formatAction
|
||||
} = require('./handlers');
|
||||
const requireJwtAuth = require('../../../middleware/requireJwtAuth');
|
||||
|
||||
const abortControllers = new Map();
|
||||
|
||||
router.post('/abort', requireJwtAuth, async (req, res) => {
|
||||
const { abortKey } = req.body;
|
||||
console.log(`req.body`, req.body);
|
||||
if (!abortControllers.has(abortKey)) {
|
||||
return res.status(404).send('Request not found');
|
||||
}
|
||||
|
||||
const { abortController } = abortControllers.get(abortKey);
|
||||
|
||||
abortControllers.delete(abortKey);
|
||||
const ret = await abortController.abortAsk();
|
||||
console.log('Aborted request', abortKey);
|
||||
console.log('Aborted message:', ret);
|
||||
|
||||
res.send(JSON.stringify(ret));
|
||||
});
|
||||
|
||||
router.post('/', requireJwtAuth, async (req, res) => {
|
||||
const { endpoint, text, parentMessageId, conversationId } = req.body;
|
||||
if (text.length === 0) return handleError(res, { text: 'Prompt empty or too short' });
|
||||
if (endpoint !== 'gptPlugins') return handleError(res, { text: 'Illegal request' });
|
||||
|
||||
const agentOptions = req.body?.agentOptions ?? {
|
||||
model: 'gpt-3.5-turbo',
|
||||
// model: 'gpt-4', // for agent model
|
||||
temperature: 0,
|
||||
// top_p: 1,
|
||||
// presence_penalty: 0,
|
||||
// frequency_penalty: 0
|
||||
};
|
||||
|
||||
const tools = req.body?.tools.map((tool) => tool.pluginKey) ?? [];
|
||||
// build endpoint option
|
||||
const endpointOption = {
|
||||
chatGptLabel: tools.length === 0 ? req.body?.chatGptLabel ?? null : null,
|
||||
promptPrefix: tools.length === 0 ? req.body?.promptPrefix ?? null : null,
|
||||
tools,
|
||||
modelOptions: {
|
||||
model: req.body?.model ?? 'gpt-4',
|
||||
temperature: req.body?.temperature ?? 0,
|
||||
top_p: req.body?.top_p ?? 1,
|
||||
presence_penalty: req.body?.presence_penalty ?? 0,
|
||||
frequency_penalty: req.body?.frequency_penalty ?? 0
|
||||
},
|
||||
agentOptions
|
||||
};
|
||||
|
||||
const availableModels = getOpenAIModels();
|
||||
if (availableModels.find((model) => model === endpointOption.modelOptions.model) === undefined) {
|
||||
return handleError(res, { text: `Illegal request: model` });
|
||||
}
|
||||
|
||||
// console.log('ask log', {
|
||||
// text,
|
||||
// conversationId,
|
||||
// endpointOption
|
||||
// });
|
||||
|
||||
console.log('ask log');
|
||||
console.dir({ text, conversationId, endpointOption }, { depth: null });
|
||||
|
||||
// eslint-disable-next-line no-use-before-define
|
||||
return await ask({
|
||||
text,
|
||||
endpointOption,
|
||||
conversationId,
|
||||
parentMessageId,
|
||||
req,
|
||||
res
|
||||
});
|
||||
});
|
||||
|
||||
const ask = async ({ text, endpointOption, parentMessageId = null, conversationId, req, res }) => {
|
||||
res.writeHead(200, {
|
||||
Connection: 'keep-alive',
|
||||
'Content-Type': 'text/event-stream',
|
||||
'Cache-Control': 'no-cache, no-transform',
|
||||
'Access-Control-Allow-Origin': '*',
|
||||
'X-Accel-Buffering': 'no'
|
||||
});
|
||||
let userMessage;
|
||||
let userMessageId;
|
||||
let responseMessageId;
|
||||
let lastSavedTimestamp = 0;
|
||||
const newConvo = !conversationId;
|
||||
const { overrideParentMessageId = null } = req.body;
|
||||
const user = req.user.id;
|
||||
|
||||
const plugin = {
|
||||
loading: true,
|
||||
inputs: [],
|
||||
latest: null,
|
||||
outputs: null
|
||||
};
|
||||
|
||||
try {
|
||||
const getIds = (data) => {
|
||||
userMessage = data.userMessage;
|
||||
userMessageId = userMessage.messageId;
|
||||
responseMessageId = data.responseMessageId;
|
||||
if (!conversationId) {
|
||||
conversationId = data.conversationId;
|
||||
}
|
||||
};
|
||||
|
||||
const { onProgress: progressCallback, sendIntermediateMessage, getPartialText } = createOnProgress({
|
||||
onProgress: ({ text: partialText }) => {
|
||||
const currentTimestamp = Date.now();
|
||||
|
||||
if (plugin.loading === true) {
|
||||
plugin.loading = false;
|
||||
}
|
||||
|
||||
if (currentTimestamp - lastSavedTimestamp > 500) {
|
||||
lastSavedTimestamp = currentTimestamp;
|
||||
saveMessage({
|
||||
messageId: responseMessageId,
|
||||
sender: 'ChatGPT',
|
||||
conversationId,
|
||||
parentMessageId: overrideParentMessageId || userMessageId,
|
||||
text: partialText,
|
||||
model: endpointOption.modelOptions.model,
|
||||
unfinished: false,
|
||||
cancelled: true,
|
||||
error: false
|
||||
});
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
const abortController = new AbortController();
|
||||
abortController.abortAsk = async function () {
|
||||
this.abort();
|
||||
|
||||
const responseMessage = {
|
||||
messageId: responseMessageId,
|
||||
sender: endpointOption?.chatGptLabel || 'ChatGPT',
|
||||
conversationId,
|
||||
parentMessageId: overrideParentMessageId || userMessageId,
|
||||
text: getPartialText(),
|
||||
plugin: { ...plugin, loading: false },
|
||||
model: endpointOption.modelOptions.model,
|
||||
unfinished: false,
|
||||
cancelled: true,
|
||||
error: false,
|
||||
};
|
||||
|
||||
saveMessage(responseMessage);
|
||||
|
||||
return {
|
||||
title: await getConvoTitle(req.user.id, conversationId),
|
||||
final: true,
|
||||
conversation: await getConvo(req.user.id, conversationId),
|
||||
requestMessage: userMessage,
|
||||
responseMessage: responseMessage
|
||||
};
|
||||
};
|
||||
|
||||
const onStart = (userMessage) => {
|
||||
sendMessage(res, { message: userMessage, created: true });
|
||||
abortControllers.set(userMessage.conversationId, { abortController, ...endpointOption });
|
||||
}
|
||||
|
||||
endpointOption.tools = await validateTools(user, endpointOption.tools);
|
||||
const clientOptions = {
|
||||
debug: true,
|
||||
reverseProxyUrl: process.env.OPENAI_REVERSE_PROXY || null,
|
||||
proxy: process.env.PROXY || null,
|
||||
...endpointOption
|
||||
};
|
||||
|
||||
if (process.env.AZURE_OPENAI_API_KEY) {
|
||||
clientOptions.azure = {
|
||||
azureOpenAIApiKey: process.env.AZURE_OPENAI_API_KEY,
|
||||
azureOpenAIApiInstanceName: process.env.AZURE_OPENAI_API_INSTANCE_NAME,
|
||||
azureOpenAIApiDeploymentName: process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME,
|
||||
azureOpenAIApiVersion: process.env.AZURE_OPENAI_API_VERSION
|
||||
};
|
||||
}
|
||||
|
||||
const chatAgent = new ChatAgent(process.env.OPENAI_API_KEY, clientOptions);
|
||||
|
||||
const onAgentAction = (action) => {
|
||||
const formattedAction = formatAction(action);
|
||||
plugin.inputs.push(formattedAction);
|
||||
plugin.latest = formattedAction.plugin;
|
||||
saveMessage(userMessage);
|
||||
sendIntermediateMessage(res, { plugin });
|
||||
// console.log('PLUGIN ACTION', formattedAction);
|
||||
};
|
||||
|
||||
const onChainEnd = (data) => {
|
||||
let { intermediateSteps: steps } = data;
|
||||
plugin.outputs = steps && steps[0].action ? formatSteps(steps) : 'An error occurred.';
|
||||
plugin.loading = false;
|
||||
saveMessage(userMessage);
|
||||
sendIntermediateMessage(res, { plugin });
|
||||
// console.log('CHAIN END', plugin.outputs);
|
||||
};
|
||||
|
||||
let response = await chatAgent.sendMessage(text, {
|
||||
getIds,
|
||||
user,
|
||||
parentMessageId,
|
||||
conversationId,
|
||||
overrideParentMessageId,
|
||||
onAgentAction,
|
||||
onChainEnd,
|
||||
onStart,
|
||||
onProgress: progressCallback.call(null, {
|
||||
res,
|
||||
text,
|
||||
plugin,
|
||||
parentMessageId: overrideParentMessageId || userMessageId
|
||||
}),
|
||||
abortController
|
||||
});
|
||||
|
||||
if (overrideParentMessageId) {
|
||||
response.parentMessageId = overrideParentMessageId;
|
||||
}
|
||||
|
||||
// console.log('CLIENT RESPONSE');
|
||||
// console.dir(response, { depth: null });
|
||||
response.plugin = { ...plugin, loading: false };
|
||||
await saveMessage(response);
|
||||
|
||||
sendMessage(res, {
|
||||
title: await getConvoTitle(req.user.id, conversationId),
|
||||
final: true,
|
||||
conversation: await getConvo(req.user.id, conversationId),
|
||||
requestMessage: userMessage,
|
||||
responseMessage: response
|
||||
});
|
||||
res.end();
|
||||
|
||||
if (parentMessageId == '00000000-0000-0000-0000-000000000000' && newConvo) {
|
||||
const title = await titleConvo({ text, response });
|
||||
await saveConvo(req.user.id, {
|
||||
conversationId: conversationId,
|
||||
title
|
||||
});
|
||||
}
|
||||
} catch (error) {
|
||||
console.error(error);
|
||||
const errorMessage = {
|
||||
messageId: responseMessageId,
|
||||
sender: 'ChatGPT',
|
||||
conversationId,
|
||||
parentMessageId: userMessageId,
|
||||
unfinished: false,
|
||||
cancelled: false,
|
||||
error: true,
|
||||
text: error.message
|
||||
};
|
||||
await saveMessage(errorMessage);
|
||||
handleError(res, errorMessage);
|
||||
}
|
||||
};
|
||||
|
||||
module.exports = router;
|
||||
178
api/server/routes/ask/askGoogle.js
Normal file
178
api/server/routes/ask/askGoogle.js
Normal file
@@ -0,0 +1,178 @@
|
||||
const express = require('express');
|
||||
const router = express.Router();
|
||||
const crypto = require('crypto');
|
||||
const { titleConvo } = require('../../../app/');
|
||||
const GoogleClient = require('../../../app/google/GoogleClient');
|
||||
const { saveMessage, getConvoTitle, saveConvo, getConvo } = require('../../../models');
|
||||
const { handleError, sendMessage, createOnProgress } = require('./handlers');
|
||||
const requireJwtAuth = require('../../../middleware/requireJwtAuth');
|
||||
|
||||
router.post('/', requireJwtAuth, async (req, res) => {
|
||||
const { endpoint, text, parentMessageId, conversationId: oldConversationId } = req.body;
|
||||
if (text.length === 0) return handleError(res, { text: 'Prompt empty or too short' });
|
||||
if (endpoint !== 'google') return handleError(res, { text: 'Illegal request' });
|
||||
|
||||
// build endpoint option
|
||||
const endpointOption = {
|
||||
examples: req.body?.examples ?? [{ input: { content: '' }, output: { content: '' } }],
|
||||
promptPrefix: req.body?.promptPrefix ?? null,
|
||||
token: req.body?.token ?? null,
|
||||
modelOptions: {
|
||||
model: req.body?.model ?? 'chat-bison',
|
||||
modelLabel: req.body?.modelLabel ?? null,
|
||||
temperature: req.body?.temperature ?? 0.2,
|
||||
maxOutputTokens: req.body?.maxOutputTokens ?? 1024,
|
||||
topP: req.body?.topP ?? 0.95,
|
||||
topK: req.body?.topK ?? 40
|
||||
}
|
||||
};
|
||||
|
||||
const availableModels = ['chat-bison', 'text-bison'];
|
||||
if (availableModels.find((model) => model === endpointOption.modelOptions.model) === undefined) {
|
||||
return handleError(res, { text: `Illegal request: model` });
|
||||
}
|
||||
|
||||
const conversationId = oldConversationId || crypto.randomUUID();
|
||||
|
||||
// eslint-disable-next-line no-use-before-define
|
||||
return await ask({
|
||||
text,
|
||||
endpointOption,
|
||||
conversationId,
|
||||
parentMessageId,
|
||||
req,
|
||||
res
|
||||
});
|
||||
});
|
||||
|
||||
const ask = async ({ text, endpointOption, parentMessageId = null, conversationId, req, res }) => {
|
||||
res.writeHead(200, {
|
||||
Connection: 'keep-alive',
|
||||
'Content-Type': 'text/event-stream',
|
||||
'Cache-Control': 'no-cache, no-transform',
|
||||
'Access-Control-Allow-Origin': '*',
|
||||
'X-Accel-Buffering': 'no'
|
||||
});
|
||||
let userMessage;
|
||||
let userMessageId;
|
||||
let responseMessageId;
|
||||
let lastSavedTimestamp = 0;
|
||||
const { overrideParentMessageId = null } = req.body;
|
||||
|
||||
try {
|
||||
const getIds = (data) => {
|
||||
userMessage = data.userMessage;
|
||||
userMessageId = userMessage.messageId;
|
||||
responseMessageId = data.responseMessageId;
|
||||
if (!conversationId) {
|
||||
conversationId = data.conversationId;
|
||||
}
|
||||
|
||||
sendMessage(res, { message: userMessage, created: true });
|
||||
};
|
||||
|
||||
const { onProgress: progressCallback } = createOnProgress({
|
||||
onProgress: ({ text: partialText }) => {
|
||||
const currentTimestamp = Date.now();
|
||||
if (currentTimestamp - lastSavedTimestamp > 500) {
|
||||
lastSavedTimestamp = currentTimestamp;
|
||||
saveMessage({
|
||||
messageId: responseMessageId,
|
||||
sender: 'PaLM2',
|
||||
conversationId,
|
||||
parentMessageId: overrideParentMessageId || userMessageId,
|
||||
text: partialText,
|
||||
unfinished: true,
|
||||
cancelled: false,
|
||||
error: false
|
||||
});
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
const abortController = new AbortController();
|
||||
|
||||
let key;
|
||||
if (endpointOption.token) {
|
||||
key = JSON.parse(endpointOption.token);
|
||||
delete endpointOption.token;
|
||||
console.log('Using service account key provided by User for PaLM models');
|
||||
}
|
||||
|
||||
try {
|
||||
if (!key) {
|
||||
key = require('../../../data/auth.json');
|
||||
}
|
||||
} catch (e) {
|
||||
console.log("No 'auth.json' file (service account key) found in /api/data/ for PaLM models");
|
||||
}
|
||||
|
||||
const clientOptions = {
|
||||
// debug: true, // for testing
|
||||
reverseProxyUrl: process.env.GOOGLE_REVERSE_PROXY || null,
|
||||
proxy: process.env.PROXY || null,
|
||||
...endpointOption
|
||||
};
|
||||
|
||||
const client = new GoogleClient(key, clientOptions);
|
||||
|
||||
let response = await client.sendMessage(text, {
|
||||
getIds,
|
||||
user: req.user.id,
|
||||
conversationId,
|
||||
parentMessageId,
|
||||
overrideParentMessageId,
|
||||
onProgress: progressCallback.call(null, {
|
||||
res,
|
||||
text,
|
||||
parentMessageId: overrideParentMessageId || userMessageId
|
||||
}),
|
||||
abortController
|
||||
});
|
||||
|
||||
if (overrideParentMessageId) {
|
||||
response.parentMessageId = overrideParentMessageId;
|
||||
}
|
||||
|
||||
await saveConvo(req.user.id, {
|
||||
...endpointOption,
|
||||
...endpointOption.modelOptions,
|
||||
conversationId,
|
||||
endpoint: 'google'
|
||||
});
|
||||
|
||||
await saveMessage(response);
|
||||
sendMessage(res, {
|
||||
title: await getConvoTitle(req.user.id, conversationId),
|
||||
final: true,
|
||||
conversation: await getConvo(req.user.id, conversationId),
|
||||
requestMessage: userMessage,
|
||||
responseMessage: response
|
||||
});
|
||||
res.end();
|
||||
|
||||
if (parentMessageId == '00000000-0000-0000-0000-000000000000') {
|
||||
const title = await titleConvo({ text, response });
|
||||
await saveConvo(req.user.id, {
|
||||
conversationId,
|
||||
title
|
||||
});
|
||||
}
|
||||
} catch (error) {
|
||||
console.error(error);
|
||||
const errorMessage = {
|
||||
messageId: responseMessageId,
|
||||
sender: 'PaLM2',
|
||||
conversationId,
|
||||
parentMessageId,
|
||||
unfinished: false,
|
||||
cancelled: false,
|
||||
error: true,
|
||||
text: error.message
|
||||
};
|
||||
await saveMessage(errorMessage);
|
||||
handleError(res, errorMessage);
|
||||
}
|
||||
};
|
||||
|
||||
module.exports = router;
|
||||
@@ -64,7 +64,7 @@ router.post('/', requireJwtAuth, async (req, res) => {
|
||||
};
|
||||
|
||||
const availableModels = getOpenAIModels();
|
||||
if (availableModels.find(model => model === endpointOption.model) === undefined)
|
||||
if (availableModels.find((model) => model === endpointOption.model) === undefined)
|
||||
return handleError(res, { text: 'Illegal request: model' });
|
||||
|
||||
console.log('ask log', {
|
||||
@@ -169,11 +169,13 @@ const ask = async ({
|
||||
};
|
||||
const abortKey = conversationId;
|
||||
abortControllers.set(abortKey, { abortController, ...endpointOption });
|
||||
const oaiApiKey = req.body?.token ?? null;
|
||||
|
||||
let response = await askClient({
|
||||
text,
|
||||
parentMessageId: userParentMessageId,
|
||||
conversationId,
|
||||
oaiApiKey,
|
||||
...endpointOption,
|
||||
onProgress: progressCallback.call(null, {
|
||||
res,
|
||||
@@ -188,7 +190,7 @@ const ask = async ({
|
||||
console.log('CLIENT RESPONSE', response);
|
||||
|
||||
const newConversationId = response.conversationId || conversationId;
|
||||
const newUserMassageId = response.parentMessageId || userMessageId;
|
||||
const newUserMessageId = response.parentMessageId || userMessageId;
|
||||
const newResponseMessageId = response.messageId;
|
||||
|
||||
// STEP1 generate response message
|
||||
@@ -198,7 +200,7 @@ const ask = async ({
|
||||
conversationId: newConversationId,
|
||||
messageId: responseMessageId,
|
||||
newMessageId: newResponseMessageId,
|
||||
parentMessageId: overrideParentMessageId || newUserMassageId,
|
||||
parentMessageId: overrideParentMessageId || newUserMessageId,
|
||||
text: await handleText(response),
|
||||
sender: endpointOption?.chatGptLabel || 'ChatGPT',
|
||||
unfinished: false,
|
||||
@@ -232,12 +234,16 @@ const ask = async ({
|
||||
|
||||
// STEP3 update the user message
|
||||
userMessage.conversationId = newConversationId;
|
||||
userMessage.messageId = newUserMassageId;
|
||||
userMessage.messageId = newUserMessageId;
|
||||
|
||||
// If response has parentMessageId, the fake userMessage.messageId should be updated to the real one.
|
||||
if (!overrideParentMessageId)
|
||||
await saveMessage({ ...userMessage, messageId: userMessageId, newMessageId: newUserMassageId });
|
||||
userMessageId = newUserMassageId;
|
||||
await saveMessage({
|
||||
...userMessage,
|
||||
messageId: userMessageId,
|
||||
newMessageId: newUserMessageId
|
||||
});
|
||||
userMessageId = newUserMessageId;
|
||||
|
||||
sendMessage(res, {
|
||||
title: await getConvoTitle(req.user.id, conversationId),
|
||||
@@ -249,7 +255,12 @@ const ask = async ({
|
||||
res.end();
|
||||
|
||||
if (userParentMessageId == '00000000-0000-0000-0000-000000000000') {
|
||||
const title = await titleConvo({ endpoint: endpointOption?.endpoint, text, response: responseMessage });
|
||||
const title = await titleConvo({
|
||||
endpoint: endpointOption?.endpoint,
|
||||
text,
|
||||
response: responseMessage,
|
||||
oaiApiKey
|
||||
});
|
||||
await saveConvo(req.user.id, {
|
||||
conversationId: conversationId,
|
||||
title
|
||||
|
||||
@@ -1,20 +1,18 @@
|
||||
const _ = require('lodash');
|
||||
const citationRegex = /\[\^\d+?\^]/g;
|
||||
const backtick = /(?<!`)[`](?!`)/g;
|
||||
// const singleBacktick = /(?<!`)[`](?!`)/;
|
||||
const cursorDefault = '<span className="result-streaming">█</span>';
|
||||
const { getCitations, citeText } = require('../../../app');
|
||||
const cursor = '<span className="result-streaming">█</span>';
|
||||
|
||||
const handleError = (res, message) => {
|
||||
res.write(`event: error\ndata: ${JSON.stringify(message)}\n\n`);
|
||||
res.end();
|
||||
};
|
||||
|
||||
const sendMessage = (res, message) => {
|
||||
const sendMessage = (res, message, event = 'message') => {
|
||||
if (message.length === 0) {
|
||||
return;
|
||||
}
|
||||
res.write(`event: message\ndata: ${JSON.stringify(message)}\n\n`);
|
||||
res.write(`event: ${event}\ndata: ${JSON.stringify(message)}\n\n`);
|
||||
};
|
||||
|
||||
const createOnProgress = ({ onProgress: _onProgress }) => {
|
||||
@@ -22,11 +20,9 @@ const createOnProgress = ({ onProgress: _onProgress }) => {
|
||||
let code = '';
|
||||
let tokens = '';
|
||||
let precode = '';
|
||||
let blockCount = 0;
|
||||
let codeBlock = false;
|
||||
let cursor = cursorDefault;
|
||||
|
||||
const progressCallback = async (partial, { res, text, bing = false, ...rest }) => {
|
||||
const progressCallback = async (partial, { res, text, plugin, bing = false, ...rest }) => {
|
||||
let chunk = partial === text ? '' : partial;
|
||||
tokens += chunk;
|
||||
precode += chunk;
|
||||
@@ -38,7 +34,6 @@ const createOnProgress = ({ onProgress: _onProgress }) => {
|
||||
|
||||
if (precode.includes('```') && codeBlock) {
|
||||
codeBlock = false;
|
||||
cursor = cursorDefault;
|
||||
precode = precode.replace(/```/g, '');
|
||||
code = '';
|
||||
}
|
||||
@@ -46,14 +41,6 @@ const createOnProgress = ({ onProgress: _onProgress }) => {
|
||||
if (precode.includes('```') && code === '') {
|
||||
precode = precode.replace(/```/g, '');
|
||||
codeBlock = true;
|
||||
blockCount++;
|
||||
cursor = blockCount > 1 ? '█\n\n```' : '█\n\n';
|
||||
}
|
||||
|
||||
const backticks = precode.match(backtick);
|
||||
if (backticks && !codeBlock && cursor === cursorDefault) {
|
||||
precode = precode.replace(backtick, '');
|
||||
cursor = '█';
|
||||
}
|
||||
|
||||
if (tokens.match(/^\n/)) {
|
||||
@@ -64,10 +51,17 @@ const createOnProgress = ({ onProgress: _onProgress }) => {
|
||||
tokens = citeText(tokens, true);
|
||||
}
|
||||
|
||||
sendMessage(res, { text: tokens + cursor, message: true, initial: i === 0, ...rest });
|
||||
|
||||
_onProgress && _onProgress({ text: tokens, message: true, initial: i === 0, ...rest });
|
||||
const payload = { text: tokens, message: true, initial: i === 0, ...rest };
|
||||
if (plugin) {
|
||||
payload.plugin = plugin;
|
||||
}
|
||||
sendMessage(res, { ...payload, text: tokens });
|
||||
_onProgress && _onProgress(payload);
|
||||
i++;
|
||||
};
|
||||
|
||||
const sendIntermediateMessage = (res, payload) => {
|
||||
sendMessage(res, { text: tokens?.length === 0 ? cursor : tokens, message: true, initial: i === 0, ...payload });
|
||||
i++;
|
||||
};
|
||||
|
||||
@@ -79,24 +73,86 @@ const createOnProgress = ({ onProgress: _onProgress }) => {
|
||||
return tokens;
|
||||
};
|
||||
|
||||
return { onProgress, getPartialText };
|
||||
return { onProgress, getPartialText, sendIntermediateMessage };
|
||||
};
|
||||
|
||||
const handleText = async (response, bing = false) => {
|
||||
let { text } = response;
|
||||
// text = await detectCode(text);
|
||||
response.text = text;
|
||||
|
||||
if (bing) {
|
||||
// const hasCitations = response.response.match(citationRegex)?.length > 0;
|
||||
const links = getCitations(response);
|
||||
if (response.text.match(citationRegex)?.length > 0) {
|
||||
text = citeText(response);
|
||||
}
|
||||
text += links?.length > 0 ? `\n<small>${links}</small>` : '';
|
||||
text += links?.length > 0 ? `\n- ${links}` : '';
|
||||
}
|
||||
|
||||
return text;
|
||||
};
|
||||
|
||||
module.exports = { handleError, sendMessage, createOnProgress, handleText };
|
||||
function formatSteps(steps) {
|
||||
let output = '';
|
||||
|
||||
for (let i = 0; i < steps.length; i++) {
|
||||
const step = steps[i];
|
||||
const actionInput = step.action.toolInput;
|
||||
const observation = step.observation;
|
||||
|
||||
if (actionInput === 'N/A' || observation?.trim()?.length === 0) {
|
||||
continue;
|
||||
}
|
||||
|
||||
output += `Input: ${actionInput}\nOutput: ${observation}`;
|
||||
|
||||
if (steps.length > 1 && i !== steps.length - 1) {
|
||||
output += '\n---\n';
|
||||
}
|
||||
}
|
||||
|
||||
return output;
|
||||
}
|
||||
|
||||
function formatAction(action) {
|
||||
const capitalizeWords = (input) => {
|
||||
if (input === 'dall-e') {
|
||||
return 'DALL-E';
|
||||
}
|
||||
|
||||
return input
|
||||
.replace(/-/g, ' ')
|
||||
.split(' ')
|
||||
.map((word) => word.charAt(0).toUpperCase() + word.slice(1))
|
||||
.join(' ');
|
||||
};
|
||||
|
||||
const formattedAction = {
|
||||
plugin: capitalizeWords(action.tool) || action.tool,
|
||||
input: action.toolInput,
|
||||
thought: action.log.includes('Thought: ')
|
||||
? action.log.split('\n')[0].replace('Thought: ', '')
|
||||
: action.log.split('\n')[0]
|
||||
};
|
||||
|
||||
if (action.tool.toLowerCase() === 'self-reflection' || formattedAction.plugin === 'N/A') {
|
||||
formattedAction.inputStr = `{\n\tthought: ${formattedAction.input}${
|
||||
!formattedAction.thought.includes(formattedAction.input)
|
||||
? ' - ' + formattedAction.thought
|
||||
: ''
|
||||
}\n}`;
|
||||
formattedAction.inputStr = formattedAction.inputStr.replace('N/A - ', '');
|
||||
} else {
|
||||
formattedAction.inputStr = `{\n\tplugin: ${formattedAction.plugin}\n\tinput: ${formattedAction.input}\n\tthought: ${formattedAction.thought}\n}`;
|
||||
}
|
||||
|
||||
return formattedAction;
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
handleError,
|
||||
sendMessage,
|
||||
createOnProgress,
|
||||
handleText,
|
||||
formatSteps,
|
||||
formatAction
|
||||
};
|
||||
@@ -2,12 +2,16 @@ const express = require('express');
|
||||
const router = express.Router();
|
||||
// const askAzureOpenAI = require('./askAzureOpenAI';)
|
||||
const askOpenAI = require('./askOpenAI');
|
||||
const askGoogle = require('./askGoogle');
|
||||
const askBingAI = require('./askBingAI');
|
||||
const askChatGPTBrowser = require('./askChatGPTBrowser');
|
||||
const askGPTPlugins = require('./askGPTPlugins');
|
||||
|
||||
// router.use('/azureOpenAI', askAzureOpenAI);
|
||||
router.use('/openAI', askOpenAI);
|
||||
router.use('/google', askGoogle);
|
||||
router.use('/bingAI', askBingAI);
|
||||
router.use('/chatGPTBrowser', askChatGPTBrowser);
|
||||
router.use('/gptPlugins', askGPTPlugins);
|
||||
|
||||
module.exports = router;
|
||||
|
||||
@@ -3,22 +3,23 @@ const {
|
||||
resetPasswordRequestController,
|
||||
resetPasswordController,
|
||||
getUserController,
|
||||
loginController,
|
||||
logoutController,
|
||||
refreshController,
|
||||
registrationController,
|
||||
registrationController
|
||||
} = require('../controllers/auth.controller');
|
||||
const { loginController } = require('../controllers/auth/login.controller');
|
||||
const { logoutController } = require('../controllers/auth/logout.controller');
|
||||
const requireJwtAuth = require('../../middleware/requireJwtAuth');
|
||||
const requireLocalAuth = require('../../middleware/requireLocalAuth');
|
||||
|
||||
const router = express.Router();
|
||||
|
||||
//Local
|
||||
router.get('/user', requireJwtAuth, getUserController);
|
||||
router.post('/logout', requireJwtAuth, logoutController);
|
||||
router.post('/login', requireLocalAuth, loginController);
|
||||
router.post('/refresh', requireJwtAuth, refreshController);
|
||||
router.post('/register', registrationController);
|
||||
if (process.env.ALLOW_REGISTRATION) {
|
||||
router.post('/register', registrationController);
|
||||
}
|
||||
router.post('/requestPasswordReset', resetPasswordRequestController);
|
||||
router.post('/resetPassword', resetPasswordController);
|
||||
|
||||
|
||||
@@ -1,5 +1,6 @@
|
||||
const express = require('express');
|
||||
const router = express.Router();
|
||||
const { availableTools } = require('../../app/langchain/tools');
|
||||
|
||||
const getOpenAIModels = () => {
|
||||
let models = ['gpt-4', 'text-davinci-003', 'gpt-3.5-turbo', 'gpt-3.5-turbo-0301'];
|
||||
@@ -9,15 +10,44 @@ const getOpenAIModels = () => {
|
||||
};
|
||||
|
||||
const getChatGPTBrowserModels = () => {
|
||||
let models = ['text-davinci-002-render-sha', 'text-davinci-002-render-paid', 'gpt-4'];
|
||||
let models = ['text-davinci-002-render-sha', 'gpt-4'];
|
||||
if (process.env.CHATGPT_MODELS) models = String(process.env.CHATGPT_MODELS).split(',');
|
||||
|
||||
return models;
|
||||
};
|
||||
|
||||
router.get('/', function (req, res) {
|
||||
const azureOpenAI = !!process.env.AZURE_OPENAI_KEY;
|
||||
const openAI = process.env.OPENAI_KEY || process.env.AZURE_OPENAI_API_KEY ? { availableModels: getOpenAIModels() } : false;
|
||||
let i = 0;
|
||||
router.get('/', async function (req, res) {
|
||||
let key, palmUser;
|
||||
try {
|
||||
key = require('../../data/auth.json');
|
||||
} catch (e) {
|
||||
if (i === 0) {
|
||||
console.log("No 'auth.json' file (service account key) found in /api/data/ for PaLM models");
|
||||
i++;
|
||||
}
|
||||
}
|
||||
|
||||
if (process.env.PALM_KEY === 'user_provided') {
|
||||
palmUser = true;
|
||||
if (i <= 1) {
|
||||
console.log('User will provide key for PaLM models');
|
||||
i++;
|
||||
}
|
||||
}
|
||||
|
||||
const google =
|
||||
key || palmUser
|
||||
? { userProvide: palmUser, availableModels: ['chat-bison', 'text-bison'] }
|
||||
: false;
|
||||
const azureOpenAI = !!process.env.AZURE_OPENAI_API_KEY;
|
||||
const apiKey = process.env.OPENAI_API_KEY || process.env.AZURE_OPENAI_API_KEY;
|
||||
const openAI = apiKey
|
||||
? { availableModels: getOpenAIModels(), userProvide: apiKey === 'user_provided' }
|
||||
: false;
|
||||
const gptPlugins = apiKey
|
||||
? { availableModels: ['gpt-4', 'gpt-3.5-turbo', 'gpt-3.5-turbo-0301'], availableTools }
|
||||
: false;
|
||||
const bingAI = process.env.BINGAI_TOKEN
|
||||
? { userProvide: process.env.BINGAI_TOKEN == 'user_provided' }
|
||||
: false;
|
||||
@@ -28,7 +58,7 @@ router.get('/', function (req, res) {
|
||||
}
|
||||
: false;
|
||||
|
||||
res.send(JSON.stringify({ azureOpenAI, openAI, bingAI, chatGPTBrowser }));
|
||||
res.send(JSON.stringify({ azureOpenAI, openAI, google, bingAI, chatGPTBrowser, gptPlugins }));
|
||||
});
|
||||
|
||||
module.exports = { router, getOpenAIModels, getChatGPTBrowserModels };
|
||||
|
||||
@@ -8,6 +8,8 @@ const tokenizer = require('./tokenizer');
|
||||
const auth = require('./auth');
|
||||
const oauth = require('./oauth');
|
||||
const { router: endpoints } = require('./endpoints');
|
||||
const plugins = require('./plugins');
|
||||
const user = require('./user');
|
||||
|
||||
module.exports = {
|
||||
search,
|
||||
@@ -18,6 +20,8 @@ module.exports = {
|
||||
prompts,
|
||||
auth,
|
||||
oauth,
|
||||
user,
|
||||
tokenizer,
|
||||
endpoints,
|
||||
plugins
|
||||
};
|
||||
|
||||
@@ -1,12 +1,13 @@
|
||||
const passport = require('passport');
|
||||
const express = require('express');
|
||||
|
||||
const router = express.Router();
|
||||
const config = require('../../../config/loader');
|
||||
const domains = config.domains;
|
||||
const isProduction = config.isProduction;
|
||||
|
||||
const isProduction = process.env.NODE_ENV === 'production';
|
||||
const clientUrl = isProduction ? process.env.CLIENT_URL_PROD : process.env.CLIENT_URL_DEV;
|
||||
|
||||
// Social
|
||||
/**
|
||||
* Google Routes
|
||||
*/
|
||||
router.get(
|
||||
'/google',
|
||||
passport.authenticate('google', {
|
||||
@@ -18,7 +19,7 @@ router.get(
|
||||
router.get(
|
||||
'/google/callback',
|
||||
passport.authenticate('google', {
|
||||
failureRedirect: `${clientUrl}/login`,
|
||||
failureRedirect: `${domains.client}/login`,
|
||||
failureMessage: true,
|
||||
session: false,
|
||||
scope: ['openid', 'profile', 'email']
|
||||
@@ -30,7 +31,7 @@ router.get(
|
||||
httpOnly: false,
|
||||
secure: isProduction
|
||||
});
|
||||
res.redirect(clientUrl);
|
||||
res.redirect(domains.client);
|
||||
}
|
||||
);
|
||||
|
||||
@@ -45,7 +46,7 @@ router.get(
|
||||
router.get(
|
||||
'/facebook/callback',
|
||||
passport.authenticate('facebook', {
|
||||
failureRedirect: `${clientUrl}/login`,
|
||||
failureRedirect: `${domains.client}/login`,
|
||||
failureMessage: true,
|
||||
session: false,
|
||||
scope: ['public_profile', 'email']
|
||||
@@ -57,8 +58,8 @@ router.get(
|
||||
httpOnly: false,
|
||||
secure: isProduction
|
||||
});
|
||||
res.redirect(clientUrl);
|
||||
res.redirect(domains.client);
|
||||
}
|
||||
);
|
||||
|
||||
module.exports = router;
|
||||
module.exports = router;
|
||||
|
||||
9
api/server/routes/plugins.js
Normal file
9
api/server/routes/plugins.js
Normal file
@@ -0,0 +1,9 @@
|
||||
const express = require('express');
|
||||
const { getAvailablePluginsController } = require('../controllers/PluginController');
|
||||
const requireJwtAuth = require('../../middleware/requireJwtAuth');
|
||||
|
||||
const router = express.Router();
|
||||
|
||||
router.get('/', requireJwtAuth, getAvailablePluginsController);
|
||||
|
||||
module.exports = router;
|
||||
@@ -40,7 +40,7 @@ router.post('/delete', requireJwtAuth, async (req, res) => {
|
||||
try {
|
||||
await deletePresets(req.user.id, filter);
|
||||
|
||||
const presets = (await getPresets(req.user.id)).map(preset => preset.toObject());
|
||||
const presets = (await getPresets(req.user.id)).map((preset) => preset.toObject());
|
||||
|
||||
// console.log('delete preset response', presets);
|
||||
res.status(201).send(presets);
|
||||
|
||||
@@ -27,7 +27,9 @@ router.get('/', requireJwtAuth, async function (req, res) {
|
||||
console.log('cache hit', key);
|
||||
const cached = cache.get(key);
|
||||
const { pages, pageSize, messages } = cached;
|
||||
res.status(200).send({ conversations: cached[pageNumber], pages, pageNumber, pageSize, messages });
|
||||
res
|
||||
.status(200)
|
||||
.send({ conversations: cached[pageNumber], pages, pageNumber, pageSize, messages });
|
||||
return;
|
||||
} else {
|
||||
cache.clear();
|
||||
@@ -44,7 +46,7 @@ router.get('/', requireJwtAuth, async function (req, res) {
|
||||
},
|
||||
true
|
||||
)
|
||||
).hits.map(message => {
|
||||
).hits.map((message) => {
|
||||
const { _formatted, ...rest } = message;
|
||||
return {
|
||||
...rest,
|
||||
@@ -95,12 +97,12 @@ router.get('/clear', async function (req, res) {
|
||||
|
||||
router.get('/test', async function (req, res) {
|
||||
const { q } = req.query;
|
||||
const messages = (await Message.meiliSearch(q, { attributesToHighlight: ['text'] }, true)).hits.map(
|
||||
message => {
|
||||
const { _formatted, ...rest } = message;
|
||||
return { ...rest, searchResult: true, text: _formatted.text };
|
||||
}
|
||||
);
|
||||
const messages = (
|
||||
await Message.meiliSearch(q, { attributesToHighlight: ['text'] }, true)
|
||||
).hits.map((message) => {
|
||||
const { _formatted, ...rest } = message;
|
||||
return { ...rest, searchResult: true, text: _formatted.text };
|
||||
});
|
||||
res.send(messages);
|
||||
});
|
||||
|
||||
|
||||
10
api/server/routes/user.js
Normal file
10
api/server/routes/user.js
Normal file
@@ -0,0 +1,10 @@
|
||||
const express = require('express');
|
||||
const requireJwtAuth = require('../../middleware/requireJwtAuth');
|
||||
const { getUserController, updateUserPluginsController } = require('../controllers/UserController');
|
||||
|
||||
const router = express.Router();
|
||||
|
||||
router.get('/', requireJwtAuth, getUserController);
|
||||
router.post('/plugins', requireJwtAuth, updateUserPluginsController);
|
||||
|
||||
module.exports = router;
|
||||
84
api/server/services/PluginService.js
Normal file
84
api/server/services/PluginService.js
Normal file
@@ -0,0 +1,84 @@
|
||||
const PluginAuth = require('../../models/schema/pluginAuthSchema');
|
||||
const { encrypt, decrypt } = require('../../utils/crypto');
|
||||
|
||||
const getUserPluginAuthValue = async (user, authField) => {
|
||||
try {
|
||||
const pluginAuth = await PluginAuth.findOne({ user, authField });
|
||||
if (!pluginAuth) {
|
||||
return null;
|
||||
}
|
||||
const decryptedValue = decrypt(pluginAuth.value);
|
||||
return decryptedValue;
|
||||
} catch (err) {
|
||||
console.log(err);
|
||||
return err;
|
||||
}
|
||||
};
|
||||
|
||||
// const updateUserPluginAuth = async (userId, authField, pluginKey, value) => {
|
||||
// try {
|
||||
// const encryptedValue = encrypt(value);
|
||||
|
||||
// const pluginAuth = await PluginAuth.findOneAndUpdate(
|
||||
// { userId, authField },
|
||||
// {
|
||||
// $set: {
|
||||
// value: encryptedValue,
|
||||
// pluginKey
|
||||
// }
|
||||
// },
|
||||
// {
|
||||
// new: true,
|
||||
// upsert: true
|
||||
// }
|
||||
// );
|
||||
|
||||
// return pluginAuth;
|
||||
// } catch (err) {
|
||||
// console.log(err);
|
||||
// return err;
|
||||
// }
|
||||
// };
|
||||
|
||||
|
||||
const updateUserPluginAuth = async (userId, authField, pluginKey, value) => {
|
||||
try {
|
||||
const encryptedValue = encrypt(value);
|
||||
const pluginAuth = await PluginAuth.findOne({ userId, authField });
|
||||
if (pluginAuth) {
|
||||
const pluginAuth = await PluginAuth.updateOne(
|
||||
{ userId, authField },
|
||||
{ $set: { value: encryptedValue } }
|
||||
);
|
||||
return pluginAuth;
|
||||
} else {
|
||||
const newPluginAuth = await new PluginAuth({
|
||||
userId,
|
||||
authField,
|
||||
value: encryptedValue,
|
||||
pluginKey
|
||||
});
|
||||
newPluginAuth.save();
|
||||
return newPluginAuth;
|
||||
}
|
||||
} catch (err) {
|
||||
console.log(err);
|
||||
return err;
|
||||
}
|
||||
};
|
||||
|
||||
const deleteUserPluginAuth = async (userId, authField) => {
|
||||
try {
|
||||
const response = await PluginAuth.deleteOne({ userId, authField });
|
||||
return response;
|
||||
} catch (err) {
|
||||
console.log(err);
|
||||
return err;
|
||||
}
|
||||
};
|
||||
|
||||
module.exports = {
|
||||
getUserPluginAuthValue,
|
||||
updateUserPluginAuth,
|
||||
deleteUserPluginAuth
|
||||
};
|
||||
24
api/server/services/UserService.js
Normal file
24
api/server/services/UserService.js
Normal file
@@ -0,0 +1,24 @@
|
||||
const User = require('../../models/User');
|
||||
|
||||
const updateUserPluginsService = async (user, pluginKey, action) => {
|
||||
try {
|
||||
if (action === 'install') {
|
||||
const response = await User.updateOne(
|
||||
{ _id: user._id },
|
||||
{ $set: { plugins: [...user.plugins, pluginKey] } }
|
||||
);
|
||||
return response;
|
||||
} else if (action === 'uninstall') {
|
||||
const response = await User.updateOne(
|
||||
{ _id: user._id },
|
||||
{ $set: { plugins: user.plugins.filter((plugin) => plugin !== pluginKey) } }
|
||||
);
|
||||
return response;
|
||||
}
|
||||
} catch (err) {
|
||||
console.log(err);
|
||||
return err;
|
||||
}
|
||||
};
|
||||
|
||||
module.exports = { updateUserPluginsService };
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user