Release v0.5.6 (#723)

* feat: add version number in UI

* feat: add version number in UI

* feat: add version number in footer

* Update Footer.tsx

More concise, cleaner message

---------

Co-authored-by: Danny Avila <110412045+danny-avila@users.noreply.github.com>

.devcontainer/devcontainer.json

@@ -0,0 +1,57 @@
+// {
+// 	"name": "LibreChat_dev",
+// 	// Update the 'dockerComposeFile' list if you have more compose files or use different names.
+// 	"dockerComposeFile": "docker-compose.yml",
+// 	// The 'service' property is the name of the service for the container that VS Code should
+// 	// use. Update this value and .devcontainer/docker-compose.yml to the real service name.
+// 	"service": "librechat",
+// 	// The 'workspaceFolder' property is the path VS Code should open by default when
+// 	// connected. Corresponds to a volume mount in .devcontainer/docker-compose.yml
+// 	"workspaceFolder": "/workspace"
+//     //,
+// 	// // Set *default* container specific settings.json values on container create.
+// 	// "settings": {},
+// 	// // Add the IDs of extensions you want installed when the container is created.
+// 	// "extensions": [],
+// 	// Uncomment the next line if you want to keep your containers running after VS Code shuts down.
+// 	// "shutdownAction": "none",
+// 	// Uncomment the next line to use 'postCreateCommand' to run commands after the container is created.
+// 	// "postCreateCommand": "uname -a",
+// 	// Comment out to connect as root instead. To add a non-root user, see: https://aka.ms/vscode-remote/containers/non-root.
+// 	// "remoteUser": "vscode"
+// }
+{
+    // "name": "LibreChat_dev",
+    "dockerComposeFile": "docker-compose.yml",
+    "service": "app",
+    // "image": "node:19-alpine",
+    // "workspaceFolder": "/workspaces",
+    "workspaceFolder": "/workspace",
+    // Set *default* container specific settings.json values on container create.
+    // "overrideCommand": true,
+    "customizations": {
+        "vscode": {
+            "extensions": [],
+            "settings": {
+                "terminal.integrated.profiles.linux": {
+                    "bash": null
+                }
+            }
+        }
+    },
+    "postCreateCommand": ""
+    // "workspaceMount": "src=${localWorkspaceFolder},dst=/code,type=bind,consistency=cached"
+
+    // "runArgs": [
+    //     "--cap-add=SYS_PTRACE", "--security-opt", "seccomp=unconfined",
+    //     "-v", "/tmp/.X11-unix:/tmp/.X11-unix",
+    //     "-v", "${env:XAUTHORITY}:/root/.Xauthority:rw",
+    //     "-v", "/home/${env:USER}/.cdh:/root/.cdh",
+    //     "-e", "DISPLAY=${env:DISPLAY}",
+    //     "--name=tgw_assistant_backend_dev",
+    //     "--network=host"
+    // ],
+    // "settings": {
+    //     "terminal.integrated.shell.linux": "/bin/bash"
+    // },
+}

.devcontainer/docker-compose.yml

@@ -0,0 +1,76 @@
+version: '3.4'
+
+services:
+  app:
+    # container_name: LibreChat_dev
+    image: node:19-alpine
+    # Using a Dockerfile is optional, but included for completeness.
+    # build: 
+    #   context: .
+    #   dockerfile: Dockerfile
+    #   # [Optional] You can use build args to set options. e.g. 'VARIANT' below affects the image in the Dockerfile
+    #   args: 
+    #     VARIANT: buster
+    network_mode: "host"
+    # ports:
+    #   - 3080:3080               # Change it to 9000:3080 to use nginx
+    extra_hosts: # if you are running APIs on docker you need access to, you will need to uncomment this line and next
+    - "host.docker.internal:host-gateway"
+
+    volumes:
+    #   # This is where VS Code should expect to find your project's source code and the value of "workspaceFolder" in .devcontainer/devcontainer.json
+      - ..:/workspace:cached
+    #   # - /app/client/node_modules
+    #   # - ./api:/app/api
+    #   # - ./.env:/app/.env
+    #   # - ./.env.development:/app/.env.development
+    #   # - ./.env.production:/app/.env.production
+    #   # - /app/api/node_modules
+
+    #   # Uncomment the next line to use Docker from inside the container. See https://aka.ms/vscode-remote/samples/docker-from-docker-compose for details.
+    #   # - /var/run/docker.sock:/var/run/docker.sock 
+
+    # Runs app on the same network as the service container, allows "forwardPorts" in devcontainer.json function.
+    # network_mode: service:another-service
+    
+    # Use "forwardPorts" in **devcontainer.json** to forward an app port locally. 
+    # (Adding the "ports" property to this file will not forward from a Codespace.)
+
+    # Uncomment the next line to use a non-root user for all processes - See https://aka.ms/vscode-remote/containers/non-root for details.
+    # user: vscode
+
+    # Uncomment the next four lines if you will use a ptrace-based debugger like C++, Go, and Rust.
+    # cap_add:
+    #   - SYS_PTRACE
+    # security_opt:
+    #   - seccomp:unconfined
+
+    # Overrides default command so things don't shut down after the process ends.
+    command: /bin/sh -c "while sleep 1000; do :; done"  
+
+  mongodb:
+    container_name: chat-mongodb
+    network_mode: "host"
+    # ports:
+    #   - 27018:27017
+    image: mongo
+  #   restart: always
+    volumes:
+      - ./data-node:/data/db
+    command: mongod --noauth
+  meilisearch:
+    container_name: chat-meilisearch
+    image: getmeili/meilisearch:v1.0
+    network_mode: "host"
+    # ports:
+    #   - 7700:7700
+    # env_file:
+    #   - .env
+    environment:
+      - SEARCH=false
+      - MEILI_HOST=http://0.0.0.0:7700
+      - MEILI_HTTP_ADDR=0.0.0.0:7700
+      - MEILI_MASTER_KEY=5c71cf56d672d009e36070b5bc5e47b743535ae55c818ae3b735bb6ebfb4ba63
+    volumes:
+      - ./meili_data:/meili_data
+  

.dockerignore

@@ -1,2 +1,5 @@
 **/node_modules
-api/.env
+client/dist/images
+data-node
+.env
+**/.env

.env.example

@@ -0,0 +1,263 @@
+##########################
+# Server configuration: 
+##########################
+
+APP_TITLE=LibreChat
+
+# The server will listen to localhost:3080 by default. You can change the target IP as you want. 
+# If you want to make this server available externally, for example to share the server with others 
+# or expose this from a Docker container, set host to 0.0.0.0 or your external IP interface. 
+# Tips: Setting host to 0.0.0.0 means listening on all interfaces. It's not a real IP.  
+# Use localhost:port rather than 0.0.0.0:port to access the server. 
+# Set Node env to development if running in dev mode.
+HOST=localhost
+PORT=3080
+
+# 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 LibreChat. 
+MONGO_URI=mongodb://127.0.0.1:27018/LibreChat
+
+##########################
+# OpenAI Endpoint: 
+##########################
+
+# Access key from OpenAI platform. 
+# 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-16k,gpt-3.5-turbo-0301,text-davinci-003,gpt-4,gpt-4-0314,gpt-4-0613
+
+# Reverse proxy settings for OpenAI: 
+# https://github.com/waylaidwanderer/node-chatgpt-api#using-a-reverse-proxy 
+# OPENAI_REVERSE_PROXY=
+
+##########################
+# AZURE Endpoint:   
+##########################
+
+# 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}`;
+# 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_API_KEY=
+# AZURE_OPENAI_API_INSTANCE_NAME=
+# AZURE_OPENAI_API_DEPLOYMENT_NAME=
+# AZURE_OPENAI_API_VERSION=
+# AZURE_OPENAI_API_COMPLETIONS_DEPLOYMENT_NAME=
+# AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME=
+
+# Identify the available models, separated by commas *without spaces*. 
+# The first will be default. 
+# Leave it blank to use internal settings. 
+AZURE_OPENAI_MODELS=gpt-3.5-turbo,gpt-4
+
+# To use Azure with the Plugins endpoint, you need the variables above, and uncomment the following variable:
+# NOTE: This may not work as expected and Azure OpenAI may not support OpenAI Functions yet
+# Omit/leave it commented to use the default OpenAI API
+
+# PLUGINS_USE_AZURE="true"
+
+##########################
+# BingAI Endpoint:   
+##########################
+
+# Also used for Sydney and jailbreak
+# 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"
+
+# BingAI Host: 
+# Necessary for some people in different countries, e.g. China (https://cn.bing.com) 
+# Leave it blank to use default server. 
+# BINGAI_HOST=https://cn.bing.com 
+
+##########################
+# ChatGPT Endpoint: 
+##########################
+
+# ChatGPT Browser Client (free but use at your own risk) 
+# Access token from https://chat.openai.com/api/auth/session 
+# Exposes your access token to `CHATGPT_REVERSE_PROXY`
+# Set to "user_provided" to allow the user to provide its token from the UI.
+# Leave it blank to disable this endpoint 
+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,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 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>
+
+##########################
+# Anthropic Endpoint: 
+##########################
+# Access key from https://console.anthropic.com/
+# Leave it blank to disable this feature.
+# Set to "user_provided" to allow the user to provide their API key from the UI.
+# Note that access to claude-1 may potentially become unavailable with the release of claude-2.
+ANTHROPIC_API_KEY="user_provided"
+ANTHROPIC_MODELS=claude-1,claude-instant-1,claude-2
+
+#############################
+# Plugins:
+#############################
+
+# Identify the available models, separated by commas *without spaces*. 
+# The first will be default. 
+# Leave it blank to use internal settings. 
+# PLUGIN_MODELS=gpt-3.5-turbo,gpt-3.5-turbo-16k,gpt-3.5-turbo-0301,gpt-4,gpt-4-0314,gpt-4-0613
+
+# 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/LibreChat/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.
+# See detailed instructions here: https://github.com/danny-avila/LibreChat/blob/main/docs/features/plugins/stable_diffusion.md
+# Use "http://127.0.0.1:7860" with local install and "http://host.docker.internal:7860" for docker
+SD_WEBUI_URL=http://host.docker.internal: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: 
+##########################
+
+# ENABLING SEARCH MESSAGES/CONVOS 
+# Requires the installation of the free self-hosted Meilisearch or a paid Remote Plan (Remote not tested) 
+# The easiest setup for this is through docker-compose, which takes care of it for you. 
+SEARCH=true
+
+# HIGHLY RECOMMENDED: Disable anonymized telemetry analytics for MeiliSearch for absolute privacy.
+MEILI_NO_ANALYTICS=true
+
+# REQUIRED FOR SEARCH: MeiliSearch Host, mainly for the API server to connect to the search server. 
+# Replace '0.0.0.0' with 'meilisearch' if serving MeiliSearch with docker-compose. 
+MEILI_HOST=http://0.0.0.0:7700
+
+# REQUIRED FOR SEARCH: MeiliSearch HTTP Address, mainly for docker-compose to expose the search server. 
+# Replace '0.0.0.0' with 'meilisearch' if serving MeiliSearch with docker-compose. 
+MEILI_HTTP_ADDR=0.0.0.0:7700
+
+# REQUIRED FOR SEARCH: In production env., a secure key is needed. You can generate your own. 
+# This master key must be at least 16 bytes, composed of valid UTF-8 characters. 
+# MeiliSearch will throw an error and refuse to launch if no master key is provided, 
+# or if it is under 16 bytes. MeiliSearch will suggest a secure autogenerated master key.
+# Using docker, it seems recognized as production so use a secure key.
+# This is a ready made secure key for docker-compose, you can replace it with your own.
+MEILI_MASTER_KEY=DrhYf7zENyR6AlUCKmnz0eYASOQdl6zxH7s7MKFSfFCt
+
+##########################
+# User System:
+##########################
+
+# Allow Public Registration
+ALLOW_REGISTRATION=true
+
+# Allow Social Registration
+ALLOW_SOCIAL_LOGIN=false
+
+# 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/
+GOOGLE_CLIENT_ID=
+GOOGLE_CLIENT_SECRET=
+GOOGLE_CALLBACK_URL=/oauth/google/callback
+
+# OpenID:
+# See OpenID provider to get the below values
+# Create random string for OPENID_SESSION_SECRET
+# For Azure AD
+#   ISSUER:  https://login.microsoftonline.com/(tenant id)/v2.0/
+#   SCOPE:   openid profile email
+OPENID_CLIENT_ID=
+OPENID_CLIENT_SECRET=
+OPENID_ISSUER=
+OPENID_SESSION_SECRET=
+OPENID_SCOPE="openid profile email"
+OPENID_CALLBACK_URL=/oauth/openid/callback
+# If LABEL and URL are left empty, then the default OpenID label and logo are used.
+OPENID_BUTTON_LABEL=
+OPENID_IMAGE_URL=
+
+# 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
+
+# Github:
+# Get the Client ID and Secret from your Discord Application
+# Add your Discord Client ID and Client Secret here:
+
+GITHUB_CLIENT_ID=your_client_id
+GITHUB_CLIENT_SECRET=your_client_secret
+GITHUB_CALLBACK_URL=/oauth/github/callback # this should be the same for everyone
+
+# Discord:
+# Get the Client ID and Secret from your Discord Application
+# Add your Github Client ID and Client Secret here:
+
+DISCORD_CLIENT_ID=your_client_id
+DISCORD_CLIENT_SECRET=your_client_secret
+DISCORD_CALLBACK_URL=/oauth/discord/callback # this should be the same for everyone
+
+###########################
+# Application Domains
+###########################
+
+# Note: 
+# Server = Backend 
+# Client = Public (the client is the url you visit)
+# For the Google login to work in dev mode, you will need to change DOMAIN_SERVER to localhost:3090 or place it in .env.development
+
+DOMAIN_CLIENT=http://localhost:3080
+DOMAIN_SERVER=http://localhost:3080

.eslintrc.js

@@ -0,0 +1,118 @@
+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',
+  ],
+  ignorePatterns: ['client/dist/**/*', 'client/public/**/*', 'e2e/playwright-report/**/*'],
+  parser: '@typescript-eslint/parser',
+  parserOptions: {
+    ecmaVersion: 'latest',
+    sourceType: 'module',
+    ecmaFeatures: {
+      jsx: true,
+    },
+  },
+  plugins: ['react', 'react-hooks', '@typescript-eslint', 'import'],
+  rules: {
+    'react/react-in-jsx-scope': 'off',
+    '@typescript-eslint/ban-ts-comment': ['error', { 'ts-ignore': 'allow' }],
+    indent: ['error', 2, { SwitchCase: 1 }],
+    'max-len': [
+      'error',
+      {
+        code: 120,
+        ignoreStrings: true,
+        ignoreTemplateLiterals: true,
+        ignoreComments: true,
+      },
+    ],
+    'import/no-cycle': 'error',
+    'linebreak-style': 0,
+    curly: ['error', 'all'],
+    semi: ['error', 'always'],
+    'no-trailing-spaces': 'error',
+    'object-curly-spacing': ['error', 'always'],
+    'no-multiple-empty-lines': ['error', { max: 1 }],
+    'comma-dangle': ['error', 'always-multiline'],
+    // "arrow-parens": [2, "as-needed", { requireForBlockBody: true }],
+    // 'no-plusplus': ['error', { allowForLoopAfterthoughts: true }],
+    'no-console': 'off',
+    'import/extensions': 'off',
+    'no-promise-executor-return': 'off',
+    'no-param-reassign': 'off',
+    'no-continue': 'off',
+    'no-restricted-syntax': 'off',
+    'react/prop-types': ['off'],
+    'react/display-name': ['off'],
+    quotes: ['error', 'single'],
+  },
+  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.
+    },
+  },
+};

.github/ISSUE_TEMPLATE/BUG-REPORT.yml

@@ -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/LibreChat/blob/main/CODE_OF_CONDUCT.md)
+      options:
+        - label: I agree to follow this project's Code of Conduct
+          required: true

.github/ISSUE_TEMPLATE/FEATURE-REQUEST.yml

@@ -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/LibreChat/blob/main/CODE_OF_CONDUCT.md)
+      options:
+        - label: I agree to follow this project's Code of Conduct
+          required: true

.github/ISSUE_TEMPLATE/QUESTION.yml

@@ -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/LibreChat/blob/main/CODE_OF_CONDUCT.md)
+      options:
+        - label: I agree to follow this project's Code of Conduct
+          required: true

.github/dependabot.yml

@@ -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: "dev"
+    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: "dev"
+    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: "dev"
+    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" 
+     

.github/playwright.yml

@@ -1,72 +1,62 @@
 name: Playwright Tests
 on:
   push:
-    branches: [ main ]
+    branches: [feat/playwright-jest-cicd]
   pull_request:
-    branches: [ main ]
+    branches: [feat/playwright-jest-cicd]
 jobs:
   tests_e2e:
-    name: Run end-to-end tests
+    name: Run Playwright tests
     timeout-minutes: 60
     runs-on: ubuntu-latest
     env:
-      BINGAI_TOKEN: ${{ secrets.BINGAI_TOKEN }}
-      CHATGPT_TOKEN: ${{ secrets.CHATGPT_TOKEN }}
+      #   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 }}
+      E2E_USER_EMAIL: ${{ secrets.E2E_USER_EMAIL }}
+      E2E_USER_PASSWORD: ${{ secrets.E2E_USER_PASSWORD }}
+      JWT_SECRET: ${{ secrets.JWT_SECRET }}
+      CREDS_KEY: ${{ secrets.CREDS_KEY }}
+      CREDS_IV: ${{ secrets.CREDS_IV }}
+      # NODE_ENV: ${{ vars.NODE_ENV }}
+      DOMAIN_CLIENT: ${{ vars.DOMAIN_CLIENT }}
+      DOMAIN_SERVER: ${{ vars.DOMAIN_SERVER }}
+    # PALM_KEY: ${{ secrets.PALM_KEY }}
     steps:
-    - uses: actions/checkout@v3
-    - uses: actions/setup-node@v3
-      with:
-        node-version: 18
-        cache: 'npm'
+      - uses: actions/checkout@v3
+      - uses: actions/setup-node@v3
+        with:
+          node-version: 18
+          cache: 'npm'
 
-    - name: Cache API dependencies
-      uses: actions/cache@v2
-      with:
-        path: ./api/node_modules
-        key: api-${{ runner.os }}-node-${{ hashFiles('./api/package-lock.json') }}
-        restore-keys: |
-          api-${{ runner.os }}-node-
+      - name: Install global dependencies
+        run: npm ci --ignore-scripts
 
-    - name: Install API dependencies
-      working-directory: ./api
-      run: npm ci
+      - name: Install API dependencies
+        working-directory: ./api
+        run: npm ci --ignore-scripts
 
-    - name: Cache Client dependencies
-      uses: actions/cache@v2
-      with:
-        path: ./client/node_modules
-        key: client-${{ runner.os }}-node-${{ hashFiles('./client/package-lock.json') }}
-        restore-keys: |
-          client-${{ runner.os }}-node-
+      - name: Install Client dependencies
+        working-directory: ./client
+        run: npm ci --ignore-scripts
 
-    - name: Install Client dependencies
-      working-directory: ./client
-      run: npm ci
+      - name: Build Client
+        run: cd client && npm run build:ci
 
-    - name: Build Client
-      working-directory: ./client
-      run: npm run build
+      - name: Install Playwright Browsers
+        run: npx playwright install --with-deps && npm install -D @playwright/test
 
-    - name: Install global dependencies
-      run: npm ci
+      - name: Start server
+        run: |
+          npm run backend & sleep 10
 
-    - name: Install Playwright Browsers
-      run: npx playwright install --with-deps
+      - name: Run Playwright tests
+        run: npx playwright test --config=e2e/playwright.config.ts
 
-    - name: Start API server
-      working-directory: ./api
-      run: |
-        npm run start &
-        sleep 10 # Wait for the server to start
-
-    - name: Run Playwright tests
-      run: npx playwright test
-
-    - uses: actions/upload-artifact@v3
-      if: always()
-      with:
-        name: playwright-report
-        path: e2e/playwright-report/
-        retention-days: 30
+      - uses: actions/upload-artifact@v3
+        if: always()
+        with:
+          name: playwright-report
+          path: e2e/playwright-report/
+          retention-days: 30

.github/pull_request_template.md

@@ -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

.github/workflows/backend-review.yml

@@ -0,0 +1,44 @@
+name: Backend Unit Tests
+on:
+  push:
+    branches:
+      - main
+      - dev
+      - release/*
+  pull_request:
+    branches:
+      - main
+      - dev
+      - release/*
+jobs:
+  tests_Backend:
+    name: Run Backend unit tests
+    timeout-minutes: 60
+    runs-on: ubuntu-latest
+    env:
+      MONGO_URI: ${{ secrets.MONGO_URI }}
+      OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+      JWT_SECRET: ${{ secrets.JWT_SECRET }}
+      CREDS_KEY: ${{ secrets.CREDS_KEY }}
+      CREDS_IV: ${{ secrets.CREDS_IV }}
+    steps:
+      - uses: actions/checkout@v2
+      - name: Use Node.js 19.x
+        uses: actions/setup-node@v3
+        with:
+          node-version: 19.x
+          cache: 'npm'
+
+      - name: Install dependencies
+        run: npm ci
+
+      # - name: Install Linux X64 Sharp
+      #   run: npm install --platform=linux --arch=x64 --verbose sharp
+
+      - name: Run unit tests
+        run: cd api && npm run test:ci
+
+      - name: Run linters
+        uses: wearerequired/lint-action@v2
+        with:
+          eslint: true

.github/workflows/build.yml

@@ -0,0 +1,38 @@
+name: Linux_Container_Workflow
+
+on:
+  workflow_dispatch:
+
+env:
+  RUNNER_VERSION: 2.293.0
+
+jobs:
+  build-and-push:
+    runs-on: ubuntu-latest
+    steps:
+      # checkout the repo
+      - name: 'Checkout GitHub Action'
+        uses: actions/checkout@main
+
+      - name: 'Login via Azure CLI'
+        uses: azure/login@v1
+        with:
+          creds: ${{ secrets.AZURE_CREDENTIALS }}
+
+      - name: 'Build GitHub Runner container image'
+        uses: azure/docker-login@v1
+        with:
+          login-server: ${{ secrets.REGISTRY_LOGIN_SERVER }}
+          username: ${{ secrets.REGISTRY_USERNAME }}
+          password: ${{ secrets.REGISTRY_PASSWORD }}
+      - run: |
+          docker build --build-arg RUNNER_VERSION=${{ env.RUNNER_VERSION }} -t ${{ secrets.REGISTRY_LOGIN_SERVER }}/pwd9000-github-runner-lin:${{ env.RUNNER_VERSION }} .
+
+      - name: 'Push container image to ACR'
+        uses: azure/docker-login@v1
+        with:
+          login-server: ${{ secrets.REGISTRY_LOGIN_SERVER }}
+          username: ${{ secrets.REGISTRY_USERNAME }}
+          password: ${{ secrets.REGISTRY_PASSWORD }}
+      - run: |
+          docker push ${{ secrets.REGISTRY_LOGIN_SERVER }}/pwd9000-github-runner-lin:${{ env.RUNNER_VERSION }}

.github/workflows/container.yml

@@ -0,0 +1,47 @@
+name: Docker Compose Build on Tag
+
+# The workflow is triggered when a tag is pushed
+on:
+  push:
+    tags:
+      - "*"
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+      # Check out the repository
+      - name: Checkout
+        uses: actions/checkout@v2
+
+      # Set up Docker
+      - name: Set up Docker
+        uses: docker/setup-buildx-action@v1
+
+      # Log in to GitHub Container Registry
+      - name: Log in to GitHub Container Registry
+        uses: docker/login-action@v2
+        with:
+          registry: ghcr.io
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      # Run docker-compose build
+      - name: Build Docker images
+        run: |
+          cp .env.example .env
+          docker-compose build
+
+      # Get Tag Name
+      - name: Get Tag Name
+        id: tag_name
+        run: echo "TAG_NAME=${GITHUB_REF/refs\/tags\//}" >> $GITHUB_ENV
+
+      # Tag it properly before push to github
+      - name: tag image and push
+        run: |
+          docker tag librechat:latest ghcr.io/${{ github.repository_owner }}/librechat:${{ env.TAG_NAME }}
+          docker push ghcr.io/${{ github.repository_owner }}/librechat:${{ env.TAG_NAME }}
+          docker tag librechat:latest ghcr.io/${{ github.repository_owner }}/librechat:latest
+          docker push ghcr.io/${{ github.repository_owner }}/librechat:latest

.github/workflows/deploy.yml

@@ -0,0 +1,38 @@
+name: Deploy_GHRunner_Linux_ACI
+
+on:
+  workflow_dispatch:
+
+env:
+  RUNNER_VERSION: 2.293.0
+  ACI_RESOURCE_GROUP: 'Demo-ACI-GitHub-Runners-RG'
+  ACI_NAME: 'gh-runner-linux-01'
+  DNS_NAME_LABEL: 'gh-lin-01'
+  GH_OWNER: ${{ github.repository_owner }}
+  GH_REPOSITORY: 'LibreChat' #Change here to deploy self hosted runner ACI to another repo.
+
+jobs:
+  deploy-gh-runner-aci:
+    runs-on: ubuntu-latest
+    steps:
+      # checkout the repo
+      - name: 'Checkout GitHub Action'
+        uses: actions/checkout@main
+
+      - name: 'Login via Azure CLI'
+        uses: azure/login@v1
+        with:
+          creds: ${{ secrets.AZURE_CREDENTIALS }}
+
+      - name: 'Deploy to Azure Container Instances'
+        uses: 'azure/aci-deploy@v1'
+        with:
+          resource-group: ${{ env.ACI_RESOURCE_GROUP }}
+          image: ${{ secrets.REGISTRY_LOGIN_SERVER }}/pwd9000-github-runner-lin:${{ env.RUNNER_VERSION }}
+          registry-login-server: ${{ secrets.REGISTRY_LOGIN_SERVER }}
+          registry-username: ${{ secrets.REGISTRY_USERNAME }}
+          registry-password: ${{ secrets.REGISTRY_PASSWORD }}
+          name: ${{ env.ACI_NAME }}
+          dns-name-label: ${{ env.DNS_NAME_LABEL }}
+          environment-variables: GH_TOKEN=${{ secrets.PAT_TOKEN }} GH_OWNER=${{ env.GH_OWNER }} GH_REPOSITORY=${{ env.GH_REPOSITORY }}
+          location: 'eastus'

.github/workflows/dev-images.yml

@@ -0,0 +1,51 @@
+name: Docker Dev Images Build
+
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - main
+    paths:
+      - 'api/**'
+      - 'client/**'
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+      # Check out the repository
+      - name: Checkout
+        uses: actions/checkout@v2
+
+      # Set up Docker
+      - name: Set up Docker
+        uses: docker/setup-buildx-action@v1
+
+      # Log in to GitHub Container Registry
+      - name: Log in to GitHub Container Registry
+        uses: docker/login-action@v2
+        with:
+          registry: ghcr.io
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      # Build Docker images
+      - name: Build Docker images
+        run: |
+          cp .env.example .env
+          docker build -f Dockerfile.multi --target api-build -t librechat-dev-api .
+          docker build -f Dockerfile -t librechat-dev .
+
+      # Tag and push the images to GitHub Container Registry
+      - name: Tag and push images
+        run: |
+          docker tag librechat-dev-api:latest ghcr.io/${{ github.repository_owner }}/librechat-dev-api:${{ github.sha }}
+          docker push ghcr.io/${{ github.repository_owner }}/librechat-dev-api:${{ github.sha }}
+          docker tag librechat-dev-api:latest ghcr.io/${{ github.repository_owner }}/librechat-dev-api:latest
+          docker push ghcr.io/${{ github.repository_owner }}/librechat-dev-api:latest
+
+          docker tag librechat-dev:latest ghcr.io/${{ github.repository_owner }}/librechat-dev:${{ github.sha }}
+          docker push ghcr.io/${{ github.repository_owner }}/librechat-dev:${{ github.sha }}
+          docker tag librechat-dev:latest ghcr.io/${{ github.repository_owner }}/librechat-dev:latest
+          docker push ghcr.io/${{ github.repository_owner }}/librechat-dev:latest

.github/workflows/frontend-review.yml

@@ -0,0 +1,34 @@
+#github action to run unit tests for frontend with jest
+name: Frontend Unit Tests
+on:
+  push:
+    branches: 
+      - main
+      - dev
+      - release/*
+  pull_request:
+    branches: 
+      - main
+      - dev
+      - release/*
+jobs:
+  tests_frontend:
+    name: Run frontend unit tests
+    timeout-minutes: 60
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - name: Use Node.js 19.x
+        uses: actions/setup-node@v3
+        with:
+          node-version: 19.x
+          cache: 'npm'
+
+      - name: Install dependencies
+        run: npm ci
+
+      - name: Build Client
+        run: npm run frontend:ci
+
+      - name: Run unit tests
+        run: cd client && npm run test:ci

.github/workflows/mkdocs.yaml

@@ -0,0 +1,24 @@
+name: mkdocs
+on:
+  push:
+    branches:
+      - main
+permissions:
+  contents: write
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+      - uses: actions/setup-python@v4
+        with:
+          python-version: 3.x
+      - run: echo "cache_id=$(date --utc '+%V')" >> $GITHUB_ENV 
+      - uses: actions/cache@v3
+        with:
+          key: mkdocs-material-${{ env.cache_id }}
+          path: .cache
+          restore-keys: |
+            mkdocs-material-
+      - run: pip install mkdocs-material 
+      - run: mkdocs gh-deploy --force

.gitignore

@@ -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
@@ -38,6 +39,7 @@ meili_data/
 api/node_modules/
 client/node_modules/
 bower_components/
+types/
 
 # Floobits
 .floo
@@ -47,7 +49,9 @@ bower_components/
 
 # Environment
 .npmrc
-.env
+.env*
+!**/.env.example
+!**/.env.test.example
 cache.json
 api/data/
 owner.yml
@@ -60,8 +64,15 @@ src/style - official.css
 .DS_Store
 *.code-workspace
 .idea
+*.pem
+config.local.ts
+**/storageState.json
+junit.xml
 
 # meilisearch
 meilisearch
 data.ms/*
+auth.json
 
+/packages/ux-shared/
+/images

.husky/pre-commit

@@ -0,0 +1,5 @@
+#!/usr/bin/env sh
+. "$(dirname -- "$0")/_/husky.sh"
+[ -n "$CI" ] && exit 0
+npx lint-staged
+

.prettierrc.js

@@ -0,0 +1,20 @@
+module.exports = {
+  plugins: ['prettier-plugin-tailwindcss'],
+  printWidth: 100,
+  tabWidth: 2,
+  useTabs: false,
+  semi: true,
+  singleQuote: true,
+  // bracketSpacing: false,
+  trailingComma: 'all',
+  arrowParens: 'always',
+  embeddedLanguageFormatting: 'auto',
+  insertPragma: false,
+  proseWrap: 'preserve',
+  quoteProps: 'as-needed',
+  requirePragma: false,
+  rangeStart: 0,
+  endOfLine: 'auto',
+  jsxBracketSameLine: false,
+  jsxSingleQuote: false,
+};

CHANGELOG.md

@@ -1,136 +0,0 @@
-# # Changelog
-<details open>
-<summary><strong>2023-05-14</strong></summary>
- 
-**Released [v0.4.4](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.4.4):**
-
-1. The Msg Clipboard was changed to a checkmark for improved user experience by @techwithanirudh in PR [#247](https://github.com/danny-avila/chatgpt-clone/pull/247).
-2. A typo in the auth.json path for accessing Google Palm was corrected by @antonme in PR [#266](https://github.com/danny-avila/chatgpt-clone/pull/266).
-3. @techwithanirudh added a Popup Menu to save sidebar space in PR [#260](https://github.com/danny-avila/chatgpt-clone/pull/260). 
-4. The default pageSize in Conversation.js was increased from 12 to 14 by @danny-avila in PR [#267](https://github.com/danny-avila/chatgpt-clone/pull/267).
-5. Fonts were updated by @techwithanirudh in PR [#261](https://github.com/danny-avila/chatgpt-clone/pull/261).
-6. Font file paths in style.css were changed by @danny-avila in PR [#268](https://github.com/danny-avila/chatgpt-clone/pull/268).
-7. Code was fixed to adjust max_tokens according to model selection by @p4w4n in PR [#263](https://github.com/danny-avila/chatgpt-clone/pull/263).
-8. Various improvements were made, such as fixing react errors and adjusting the mobile view, by @danny-avila in PR [#269](https://github.com/danny-avila/chatgpt-clone/pull/269).
-
-New contributors to the project include:
-
-- @techwithanirudh, who made their first contribution in PR [#247](https://github.com/danny-avila/chatgpt-clone/pull/247).
-- @antonme, who made their first contribution in PR [#266](https://github.com/danny-avila/chatgpt-clone/pull/266).
-- @p4w4n, who made their first contribution in PR [#263](https://github.com/danny-avila/chatgpt-clone/pull/263).
-
-The [full changelog can be found here](https://github.com/danny-avila/chatgpt-clone/compare/v0.4.3...v0.4.4)
-</details>
- <details>
-<summary><strong>2023-05-13</strong></summary>
- 
-**Released [v0.4.3](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.4.3) which now supports Google's PaLM 2!**
-  
-  ![image](https://github.com/danny-avila/chatgpt-clone/assets/110412045/ec5e8ff3-6c3a-4f25-9687-d8558435d094)
- 
-**How to Setup PaLM 2 (via Google Cloud Vertex AI API)**
-
-- Enable the Vertex AI API on Google Cloud:
-- - https://console.cloud.google.com/vertex-ai
-- Create a Service Account:
-- - https://console.cloud.google.com/projectselector/iam-admin/serviceaccounts/create?walkthrough_id=iam--create-service-account#step_index=1
-- Make sure to click 'Create and Continue' to give at least the 'Vertex AI User' role.
-- Create a JSON key, rename as 'auth.json' and save it in /api/data/.
-
-**Alternatively**
-
-- In your ./api/.env file, set PALM_KEY as "user_provided" to allow the user to provide a Service Account key JSON from the UI.
-- They will follow the steps above except for renaming the file, simply importing the JSON when prompted.
-- The key is sent to the server but never saved except in your local storage
-
-**Note:**
-
-- Vertex AI does not (yet) support response streaming for text generations, so response may seem to take long when generating a lot of text.
-- Text streaming is simulated
-
-
-You can check the full changelog in between v0.4.2 and v0.4.3 [here](https://github.com/danny-avila/chatgpt-clone/compare/v0.4.2...v0.4.3).
-</details>
-
-<details>
-<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)

CODE_OF_CONDUCT.md

@@ -1,4 +1,4 @@
-# Contributor Covenant Code of Conduct
+# Contributor Covenant Code of Conduct
 
 ## Our Pledge
 
@@ -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
@@ -127,6 +127,6 @@ For answers to common questions about this code of conduct, see the FAQ at
 https://www.contributor-covenant.org/faq. Translations are available at
 https://www.contributor-covenant.org/translations.
 
-##
+---
 
-## [Go Back to ReadMe](../../README.md)
+## [Go Back to ReadMe](README.md)

CONTRIBUTING.md

@@ -0,0 +1,100 @@
+# Contributor Guidelines
+
+Thank you to all the contributors who have helped make this project possible! We welcome various types of contributions, such as bug reports, documentation improvements, feature requests, and code contributions.
+
+## Contributing Guidelines
+
+If the feature you would like to contribute has not already received prior approval from the project maintainers (i.e., 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/LibreChat/discussions/categories/proposals) of the discussions board before beginning work on it. The proposals should include specific implementation details, including areas of the application that will be affected by the change (including designs if applicable), and any other relevant information that might be required for a speedy review. However, 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/LibreChat/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. We appreciate your understanding and cooperation.
+
+If you would like to discuss the changes you wish to make, join our [Discord community](https://discord.gg/uDyZ5Tzhct), where you can engage with other contributors and seek guidance from the community.
+
+## Our Standards
+
+We strive to maintain a positive and inclusive environment within our project community. We expect all contributors to adhere to the following standards:
+
+- Using welcoming and inclusive language.
+- Being respectful of differing viewpoints and experiences.
+- Gracefully accepting constructive criticism.
+- Focusing on what is best for the community.
+- Showing empathy towards other community members.
+
+Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that do not align with these standards.
+
+## To contribute to this project, please adhere to the following guidelines:
+
+## 1. Git Workflow
+
+We utilize a GitFlow workflow to manage changes to this project's codebase. Follow these general steps when contributing code:
+
+1. Fork the repository and create a new branch with a descriptive slash-based name (e.g., `new/feature/x`).
+2. Implement your changes and ensure that all tests pass.
+3. Commit your changes using conventional commit messages with GitFlow flags. Begin the commit message with a tag indicating the change type, such as "feat" (new feature), "fix" (bug fix), "docs" (documentation), or "refactor" (code refactoring), followed by a brief summary of the changes (e.g., `feat: Add new feature X to the project`).
+4. Submit a pull request with a clear and concise description of your changes and the reasons behind them.
+5. We will review your pull request, provide feedback as needed, and eventually merge the approved changes into the main branch.
+
+## 2. Commit Message Format
+
+We have defined precise rules for formatting our Git commit messages. This format leads to an easier-to-read commit history. Each commit message consists of a header, a body, and an optional footer.
+
+### Commit Message Header
+
+The header is mandatory and must conform to the following format:
+
+```
+<type>(<scope>): <short summary>
+```
+
+- `<type>`: Must be one of the following:
+  - **build**: Changes that affect the build system or external dependencies.
+  - **ci**: Changes to our CI configuration files and script.
+  - **docs**: Documentation-only changes.
+  - **feat**: A new feature.
+  - **fix**: A bug fix.
+  - **perf**: A code change that improves performance.
+  - **refactor**: A code change that neither fixes a bug nor adds a feature.
+  - **test**: Adding missing tests or correcting existing tests.
+
+- `<scope>`: Optional. Indicates the scope of the commit, such as `common`, `plays`, `infra`, etc.
+
+- `<short summary>`: A brief, concise summary of the change in the present tense. It should not be capitalized and should not end with a period.
+
+### Commit Message Body
+
+The body is mandatory for all commits except for those of type "docs". When the body is present, it must be at least 20 characters long and should explain the motivation behind the change. You can include a comparison of the previous behavior with the new behavior to illustrate the impact of the change.
+
+### Commit Message Footer
+
+The footer is optional and can contain information about breaking changes, deprecations, and references to related GitHub issues, Jira tickets, or other pull requests. For example, you can include a "BREAKING CHANGE" section that describes a breaking change along with migration instructions. Additionally, you can include a "Closes" section to reference the issue or pull request that this commit closes or is related to.
+
+### Revert commits
+
+If the commit reverts a previous commit, it should begin with `revert: `, followed by the header of the reverted commit. The commit message body should include the SHA of the commit being reverted and a clear description of the reason for reverting the commit.
+
+## 3. Pull Request Process
+
+When submitting a pull request, please follow these guidelines:
+
+- Ensure that any installation or build dependencies are removed before the end of the layer when doing a build.
+- Update the README.md with details of changes to the interface, including new environment variables, exposed ports, useful file locations, and container parameters.
+- Increase the version numbers in any example files and the README.md to reflect the new version that the pull request represents. We use [SemVer](http://semver.org/) for versioning.
+
+Ensure that your changes meet the following criteria:
+
+- All tests pass.
+- The code is well-formatted and adheres to our coding standards.
+- The commit history is clean and easy to follow. You can use `git rebase` or `git merge --squash` to clean your commit history before submitting the pull request.
+- The pull request description clearly outlines the changes and the reasons behind them. Be sure to include the steps to test the pull request.
+
+## 4. Naming Conventions
+
+Apply the following naming conventions to branches, labels, and other Git-related entities:
+
+- Branch names: Descriptive and slash-based (e.g., `new/feature/x`).
+- Labels: Descriptive and snake_case (e.g., `bug_fix`).
+- Directories and file names: Descriptive and snake_case (e.g., `config_file.yaml`).
+
+---
+
+## [Go Back to ReadMe](README.md)

CONTRIBUTORS.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)

Dockerfile

@@ -1,38 +1,26 @@
-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
-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
+# Base node image
+FROM node:19-alpine AS node
 
-FROM node:19-alpine AS node-api
-WORKDIR /api
-# copy package.json into the container at /api
-COPY /api/package*.json /api/
-# install dependencies
+# Install curl for health check
+RUN apk --no-cache add curl
+
+COPY . /app
+# Install dependencies
+WORKDIR /app
 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
+
+# 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;"]

Dockerfile.multi

@@ -0,0 +1,32 @@
+# Build API, Client and Data Provider
+FROM node:19-alpine AS base
+
+WORKDIR /app
+COPY config/loader.js ./config/
+RUN npm install dotenv
+
+WORKDIR /app/api
+COPY api/package*.json ./
+COPY api/ ./
+RUN npm install
+
+# React client build
+FROM base AS client-build
+WORKDIR /app/client
+COPY ./client/ ./
+
+RUN npm install
+ENV NODE_OPTIONS="--max-old-space-size=2048"
+RUN npm run build
+
+# Node API setup
+FROM base AS api-build
+COPY --from=client-build /app/client/dist /app/client/dist
+EXPOSE 3080
+ENV HOST=0.0.0.0
+CMD ["node", "server/index.js"]
+
+# Nginx setup
+FROM nginx:1.21.1-alpine AS prod-stage
+COPY ./client/nginx.conf /etc/nginx/conf.d/default.conf
+CMD ["nginx", "-g", "daemon off;"]

LICENSE.md

@@ -1,7 +1,9 @@
-# MIT License
+# MIT License
 
 Copyright (c) 2023 Danny Avila
-##
+
+---
+
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal
 in the Software without restriction, including without limitation the rights
@@ -22,6 +24,6 @@ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
 
-##
+---
 
 ## [Go Back to ReadMe](README.md)

README.md

@@ -1,176 +1,153 @@
-
 <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>
+  <a href="https://docs.librechat.ai">
+    <img src="docs/assets/LibreChat.svg" height="256">
+  </a>
+  <a href="https://docs.librechat.ai">
+    <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&logoColor=white&labelColor=000000&color=blueviolet">
+  </a>
+  <a href="https://www.youtube.com/@LibreChat"> 
+    <img
+      src="https://img.shields.io/badge/YOUTUBE-red.svg?style=for-the-badge&logo=youtube&logoColor=white&labelColor=000000&logoWidth=20">
+  </a>
+  <a href="https://docs.librechat.ai"> 
+    <img
+      src="https://img.shields.io/badge/DOCS-blue.svg?style=for-the-badge&logo=read-the-docs&logoColor=white&labelColor=000000&logoWidth=20">
   </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">
+    <img
+      src="https://img.shields.io/badge/SPONSORS-brightgreen.svg?style=for-the-badge&logo=github-sponsors&logoColor=white&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.
   
-  ![clone3](https://user-images.githubusercontent.com/110412045/230538752-9b99dc6e-cd02-483a-bff0-6c6e780fa7ae.gif)
+<!-- https://github.com/danny-avila/LibreChat/assets/110412045/c1eb0c0f-41f6-4335-b982-84b278b53d59 -->
+
+[![Watch the video](https://img.youtube.com/vi/pNIOs1ovsXw/maxresdefault.jpg)](https://youtu.be/pNIOs1ovsXw)
+Click on the thumbnail to open the video☝️
 
 # 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)
-- Search all messages/conversations - [More info here](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.1.0)
-- Integrating plugins soon
-
-##
-# 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>
-
-##
-
-## **Google's PaLM 2 is now supported as of [v0.4.3](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.4.3)**
-  
-  ![image](https://github.com/danny-avila/chatgpt-clone/assets/110412045/ec5e8ff3-6c3a-4f25-9687-d8558435d094)
- 
-<details>
-<summary><strong>How to Setup PaLM 2 (via Google Cloud Vertex AI API)</strong></summary>
-- Enable the Vertex AI API on Google Cloud:
-- - https://console.cloud.google.com/vertex-ai
-- Create a Service Account:
-- - https://console.cloud.google.com/projectselector/iam-admin/serviceaccounts/create?walkthrough_id=iam--create-service-account#step_index=1
-- Make sure to click 'Create and Continue' to give at least the 'Vertex AI User' role.
-- Create a JSON key, rename as 'auth.json' and save it in /api/data/.
-
-**Alternatively**
-
-- In your ./api/.env file, set PALM_KEY as "user_provided" to allow the user to provide a Service Account key JSON from the UI.
-- They will follow the steps above except for renaming the file, simply importing the JSON when prompted.
-- The key is sent to the server but never saved except in your local storage
-
-**Note:**
-
-- Vertex AI does not (yet) support response streaming for text generations, so response may seem to take long when generating a lot of text.
-- Text streaming is simulated
-</details>
+- AI model selection: OpenAI API, BingAI, ChatGPT Browser, PaLM2, Anthropic (Claude), Plugins
+- Create, Save, & Share custom presets - [More info on prompt presets here](https://github.com/danny-avila/LibreChat/releases/tag/v0.3.0)
+- Edit and Resubmit messages with conversation branching
+- Search all messages/conversations - [More info here](https://github.com/danny-avila/LibreChat/releases/tag/v0.1.0)
+- Plugins now available (including web access, image generation and more)
 
 ---
 
-<details open>
-<summary><strong>2023-05-14</strong></summary>
+## ⚠️ [Breaking Changes](docs/general_info/breaking_changes.md) ⚠️
+**Applies to [v0.5.4](docs/general_info/breaking_changes.md#v054) & [v0.5.5](docs/general_info/breaking_changes.md#v055)**
 
-**Released [v0.4.4](https://github.com/danny-avila/chatgpt-clone/releases/tag/v0.4.4):**
+**Please read this before updating from a previous version**
 
-1. The Msg Clipboard was changed to a checkmark for improved user experience by @techwithanirudh in PR [#247](https://github.com/danny-avila/chatgpt-clone/pull/247).
-2. A typo in the auth.json path for accessing Google Palm was corrected by @antonme in PR [#266](https://github.com/danny-avila/chatgpt-clone/pull/266).
-3. @techwithanirudh added a Popup Menu to save sidebar space in PR [#260](https://github.com/danny-avila/chatgpt-clone/pull/260). 
-4. The default pageSize in Conversation.js was increased from 12 to 14 by @danny-avila in PR [#267](https://github.com/danny-avila/chatgpt-clone/pull/267).
-5. Fonts were updated by @techwithanirudh in PR [#261](https://github.com/danny-avila/chatgpt-clone/pull/261).
-6. Font file paths in style.css were changed by @danny-avila in PR [#268](https://github.com/danny-avila/chatgpt-clone/pull/268).
-7. Code was fixed to adjust max_tokens according to model selection by @p4w4n in PR [#263](https://github.com/danny-avila/chatgpt-clone/pull/263).
-8. Various improvements were made, such as fixing react errors and adjusting the mobile view, by @danny-avila in PR [#269](https://github.com/danny-avila/chatgpt-clone/pull/269).
+---
 
-New contributors to the project include:
+## Changelog 
+Keep up with the latest updates by visiting the releases page - [Releases](https://github.com/danny-avila/LibreChat/releases)
 
-- @techwithanirudh, who made their first contribution in PR [#247](https://github.com/danny-avila/chatgpt-clone/pull/247).
-- @antonme, who made their first contribution in PR [#266](https://github.com/danny-avila/chatgpt-clone/pull/266).
-- @p4w4n, who made their first contribution in PR [#263](https://github.com/danny-avila/chatgpt-clone/pull/263).
-
-The [full changelog can be found here](https://github.com/danny-avila/chatgpt-clone/compare/v0.4.3...v0.4.4)
-
-⚠️ **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>
-
-[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)
+  * Installation
+    * [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)
+  * Configuration
+    * [APIs and Tokens](docs/install/apis_and_tokens.md)
+    * [User Auth System](docs/install/user_auth_system.md)
+    * [Online MongoDB Database](docs/install/mongodb.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)
-  * [Changelog](CHANGELOG.md)
-  * [Bing Jailbreak Info](documents/general_info/bing_jailbreak_info.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)   
 </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)
+    * [Using official ChatGPT Plugins](docs/features/plugins/chatgpt_plugins_openapi.md)
+
+  * [Proxy](docs/features/proxy.md)
+  * [Bing Jailbreak](docs/features/bing_jailbreak.md)
 </details>
 
 <details>
   <summary><strong>Cloud Deployment</strong></summary>
 
-  * [Heroku](documents/deployment/heroku.md)
+  * [Hetzner](docs/deployment/hetzner_ubuntu.md)
+  * [Heroku](docs/deployment/heroku.md)
+  * [Linode](docs/deployment/linode.md)
+  * [Cloudflare](docs/deployment/cloudflare.md)
+  * [Ngrok](docs/deployment/ngrok.md)
+  * [Render](docs/deployment/render.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)
-  * [Trello Board](https://trello.com/b/17z094kq/chatgpt-clone)
+  * [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/LibreChate)
 </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)
-
-##
-
-## Contributing
-
-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).
-##
+---
 
 ## Star History
 
-[![Star History Chart](https://api.star-history.com/svg?repos=danny-avila/chatgpt-clone&type=Date)](https://star-history.com/#danny-avila/chatgpt-clone&Date)
+[![Star History Chart](https://api.star-history.com/svg?repos=danny-avila/LibreChat&type=Date)](https://star-history.com/#danny-avila/LibreChat&Date)
+
+---
+
+## Sponsors
+
+  Sponsored by <a href="https://github.com/mjtechguy"><b>@mjtechguy</b></a>, <a href="https://github.com/SphaeroX"><b>@SphaeroX</b></a>, <a href="https://github.com/DavidDev1334"><b>@DavidDev1334</b></a>, <a href="https://github.com/fuegovic"><b>@fuegovic</b></a>, <a href="https://github.com/Pharrcyde"><b>@Pharrcyde</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/uDyZ5Tzhct)
+
+This project exists in its current state thanks to all the people who contribute
+---
+<a href="https://github.com/danny-avila/LibreChat/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=danny-avila/LibreChat" />
+</a>

SECURITY.md

@@ -0,0 +1,63 @@
+# Security Policy
+
+At LibreChat, we prioritize the security of our project and value the contributions of security researchers in helping us improve the security of our codebase. If you discover a security vulnerability within our project, we appreciate your responsible disclosure. Please follow the guidelines below to report any vulnerabilities to us:
+
+**Note: Only report sensitive vulnerability details via the appropriate private communication channels mentioned below. Public channels, such as GitHub issues and Discord, should be used for initiating contact and establishing private communication channels.**
+
+## Communication Channels
+
+When reporting a security vulnerability, you have the following options to reach out to us:
+
+- **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. For more information on how to submit a security advisory report, please refer to 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. However, please note that initial contact through GitHub Issues 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. However, please ensure that initial contact through Discord does not include any sensitive details.
+
+_After the initial contact, we will 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 strive to acknowledge vulnerability reports within 72 hours and will keep you informed of the progress towards resolution.
+
+## Security Updates and Patching
+
+We are committed to maintaining the security of our open-source project, LibreChat, and promptly addressing any identified vulnerabilities. To ensure the security of our project, we adhere to the following 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/LibreChat)
+
+## 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/LibreChat/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 currently do not 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)

api/.env.example

@@ -1,173 +0,0 @@
-##########################
-# Server configuration: 
-##########################
-
-# The server will listen to localhost:3080 by default. You can change the target IP as you want. 
-# If you want to make this server available externally, for example to share the server with others 
-# or expose this from a Docker container, set host to 0.0.0.0 or your external IP interface. 
-# Tips: Setting host to 0.0.0.0 means listening on all interfaces. It's not a real IP.  
-# Use localhost:port rather than 0.0.0.0:port to access the server. 
-# 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
-
-##########################
-# OpenAI Endpoint: 
-##########################
-
-# Access key from OpenAI platform. 
-# Leave it blank to disable this feature. 
-OPENAI_KEY=
-
-# 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
-
-# Reverse proxy settings for OpenAI: 
-# https://github.com/waylaidwanderer/node-chatgpt-api#using-a-reverse-proxy 
-# OPENAI_REVERSE_PROXY=
-
-##########################
-# AZURE Endpoint:   
-##########################
-
-# 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}`;
-# 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.
-
-# 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
-
-##########################
-# BingAI Endpoint:   
-##########################
-
-# Also used for Sydney and jailbreak
-
-# BingAI Tokens: the "_U" cookies value from bing.com 
-# 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"
-
-# BingAI Host: 
-# Necessary for some people in different countries, e.g. China (https://cn.bing.com) 
-# Leave it blank to use default server. 
-# BINGAI_HOST=https://cn.bing.com 
-
-##########################
-# ChatGPT Endpoint: 
-##########################
-
-# ChatGPT Browser Client (free but use at your own risk) 
-# Access token from https://chat.openai.com/api/auth/session 
-# Exposes your access token to `CHATGPT_REVERSE_PROXY`
-# Set to "user_provided" to allow the user to provide its token from the UI.
-# Leave it blank to disable this endpoint 
-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
-
-# 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= 
-
-##########################
-# PaLM (Google) Endpoint: 
-##########################
-
-# PaLM 2 Client (via Google Cloud Vertex AI API)
-# Steps:
-    # Enable the Vertex AI API on Google Cloud:
-        # https://console.cloud.google.com/vertex-ai
-    # Create a Service Account:
-        # https://console.cloud.google.com/projectselector/iam-admin/serviceaccounts/create?walkthrough_id=iam--create-service-account#step_index=1
-    # Make sure to click 'Create and Continue' to give at least the 'Vertex AI User' role.
-    # Create a JSON key, rename as 'auth.json' and save it in /api/data/.
-# Alternatively
-    # Uncomment below PALM_KEY and set as "user_provided" to allow the user to provide a Service Account key JSON from the UI.
-    # They will follow the steps above except for renaming the file.
-# Leave blank or omit to disable this endpoint 
-
-# 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: 
-##########################
-
-# ENABLING SEARCH MESSAGES/CONVOS 
-# Requires the installation of the free self-hosted Meilisearch or a paid Remote Plan (Remote not tested) 
-# The easiest setup for this is through docker-compose, which takes care of it for you. 
-SEARCH=false
-
-# REQUIRED FOR SEARCH: MeiliSearch Host, mainly for the API server to connect to the search server. 
-# Replace '0.0.0.0' with 'meilisearch' if serving MeiliSearch with docker-compose. 
-MEILI_HOST=http://0.0.0.0:7700
-
-# REQUIRED FOR SEARCH: MeiliSearch HTTP Address, mainly for docker-compose to expose the search server. 
-# Replace '0.0.0.0' with 'meilisearch' if serving MeiliSearch with docker-compose. 
-MEILI_HTTP_ADDR=0.0.0.0:7700
-
-# REQUIRED FOR SEARCH: In production env., a secure key is needed. You can generate your own. 
-# This master key must be at least 16 bytes, composed of valid UTF-8 characters. 
-# MeiliSearch will throw an error and refuse to launch if no master key is provided, 
-# or if it is under 16 bytes. MeiliSearch will suggest a secure autogenerated master key.
-# Using docker, it seems recognized as production so use a secure key.
-# This is a ready made secure key for docker-compose, you can replace it with your own.
-MEILI_MASTER_KEY=DrhYf7zENyR6AlUCKmnz0eYASOQdl6zxH7s7MKFSfFCt
-
-##########################
-# User System:
-##########################
-
-# 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/
-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
-
-# 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
-
-# Change these values to domain if deploying:
-CLIENT_URL_PROD=http://localhost:3080
-SERVER_URL_PROD=http://localhost:3080

api/.eslintrc.js

@@ -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'
-  }
-};

api/.prettierrc

@@ -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"
-}

api/app/bingai.js

@@ -14,22 +14,23 @@ const askBing = async ({
   invocationId,
   toneStyle,
   token,
-  onProgress
+  onProgress,
 }) => {
-  const { BingAIClient } = await import('og-chatgpt-api');
+  const { BingAIClient } = await import('@waylaidwanderer/chatgpt-api');
   const store = {
-    store: new KeyvFile({ filename: './data/cache.json' })
+    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,
-    proxy: process.env.PROXY || null
+    proxy: process.env.PROXY || null,
   });
 
   let options = {};
@@ -38,23 +39,43 @@ const askBing = async ({
     jailbreakConversationId = false;
   }
 
-  if (jailbreak)
+  if (jailbreak) {
     options = {
       jailbreakConversationId: jailbreakConversationId || jailbreak,
       context,
       systemMessage,
       parentMessageId,
       toneStyle,
-      onProgress
+      onProgress,
+      clientOptions: {
+        features: {
+          genImage: {
+            server: {
+              enable: true,
+              type: 'markdown_list',
+            },
+          },
+        },
+      },
     };
-  else {
+  } else {
     options = {
       conversationId,
       context,
       systemMessage,
       parentMessageId,
       toneStyle,
-      onProgress
+      onProgress,
+      clientOptions: {
+        features: {
+          genImage: {
+            server: {
+              enable: true,
+              type: 'markdown_list',
+            },
+          },
+        },
+      },
     };
 
     // don't give those parameters for new conversation

api/app/chatgpt-browser.js

@@ -8,27 +8,30 @@ const browserClient = async ({
   model,
   token,
   onProgress,
+  onEventMessage,
   abortController,
-  userId
+  userId,
 }) => {
-  const { ChatGPTBrowserClient } = await import('og-chatgpt-api');
+  const { ChatGPTBrowserClient } = await import('@waylaidwanderer/chatgpt-api');
   const store = {
-    store: new KeyvFile({ filename: './data/cache.json' })
+    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,
-    user: userId
+    user: userId,
   };
 
   const client = new ChatGPTBrowserClient(clientOptions, store);
-  let options = { onProgress, abortController };
+  let options = { onProgress, onEventMessage, abortController };
 
   if (!!parentMessageId && !!conversationId) {
     options = { ...options, parentMessageId, conversationId };

api/app/clients/AnthropicClient.js

@@ -0,0 +1,324 @@
+const Keyv = require('keyv');
+// const { Agent, ProxyAgent } = require('undici');
+const BaseClient = require('./BaseClient');
+const {
+  encoding_for_model: encodingForModel,
+  get_encoding: getEncoding,
+} = require('@dqbd/tiktoken');
+const Anthropic = require('@anthropic-ai/sdk');
+
+const HUMAN_PROMPT = '\n\nHuman:';
+const AI_PROMPT = '\n\nAssistant:';
+
+const tokenizersCache = {};
+
+class AnthropicClient extends BaseClient {
+  constructor(apiKey, options = {}, cacheOptions = {}) {
+    super(apiKey, options, cacheOptions);
+    cacheOptions.namespace = cacheOptions.namespace || 'anthropic';
+    this.conversationsCache = new Keyv(cacheOptions);
+    this.apiKey = apiKey || process.env.ANTHROPIC_API_KEY;
+    this.sender = 'Anthropic';
+    this.userLabel = HUMAN_PROMPT;
+    this.assistantLabel = AI_PROMPT;
+    this.setOptions(options);
+  }
+
+  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;
+    }
+
+    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 || 'claude-1',
+      temperature: typeof modelOptions.temperature === 'undefined' ? 0.7 : modelOptions.temperature, // 0 - 1, 0.7 is recommended
+      topP: typeof modelOptions.topP === 'undefined' ? 0.7 : modelOptions.topP, // 0 - 1, default: 0.7
+      topK: typeof modelOptions.topK === 'undefined' ? 40 : modelOptions.topK, // 1-40, default: 40
+      stop: modelOptions.stop, // no stop method for now
+    };
+
+    this.maxContextTokens = this.options.maxContextTokens || 99999;
+    this.maxResponseTokens = this.modelOptions.maxOutputTokens || 1500;
+    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.startToken = '||>';
+    this.endToken = '';
+    this.gptEncoder = this.constructor.getTokenizer('cl100k_base');
+
+    if (!this.modelOptions.stop) {
+      const stopTokens = [this.startToken];
+      if (this.endToken && this.endToken !== this.startToken) {
+        stopTokens.push(this.endToken);
+      }
+      stopTokens.push(`${this.userLabel}`);
+      stopTokens.push('<|diff_marker|>');
+
+      this.modelOptions.stop = stopTokens;
+    }
+
+    return this;
+  }
+
+  getClient() {
+    if (this.options.reverseProxyUrl) {
+      return new Anthropic({
+        apiKey: this.apiKey,
+        baseURL: this.options.reverseProxyUrl,
+      });
+    } else {
+      return new Anthropic({
+        apiKey: this.apiKey,
+      });
+    }
+  }
+
+  async buildMessages(messages, parentMessageId) {
+    const orderedMessages = this.constructor.getMessagesForConversation(messages, parentMessageId);
+    if (this.options.debug) {
+      console.debug('AnthropicClient: orderedMessages', orderedMessages, parentMessageId);
+    }
+
+    const formattedMessages = orderedMessages.map((message) => ({
+      author: message.isCreatedByUser ? this.userLabel : this.assistantLabel,
+      content: message?.content ?? message.text,
+    }));
+
+    let identityPrefix = '';
+    if (this.options.userLabel) {
+      identityPrefix = `\nHuman's name: ${this.options.userLabel}`;
+    }
+
+    if (this.options.modelLabel) {
+      identityPrefix = `${identityPrefix}\nYou are ${this.options.modelLabel}`;
+    }
+
+    let promptPrefix = (this.options.promptPrefix || '').trim();
+    if (promptPrefix) {
+      // If the prompt prefix doesn't end with the end token, add it.
+      if (!promptPrefix.endsWith(`${this.endToken}`)) {
+        promptPrefix = `${promptPrefix.trim()}${this.endToken}\n\n`;
+      }
+      promptPrefix = `\nContext:\n${promptPrefix}`;
+    }
+
+    if (identityPrefix) {
+      promptPrefix = `${identityPrefix}${promptPrefix}`;
+    }
+
+    const promptSuffix = `${promptPrefix}${this.assistantLabel}\n`; // Prompt AI to respond.
+    let currentTokenCount = this.getTokenCount(promptSuffix);
+
+    let promptBody = '';
+    const maxTokenCount = this.maxPromptTokens;
+
+    const context = [];
+
+    // Iterate backwards through the messages, adding them to the prompt until we reach the max token count.
+    // Do this within a recursive async function so that it doesn't block the event loop for too long.
+    // Also, remove the next message when the message that puts us over the token limit is created by the user.
+    // Otherwise, remove only the exceeding message. This is due to Anthropic's strict payload rule to start with "Human:".
+    const nextMessage = {
+      remove: false,
+      tokenCount: 0,
+      messageString: '',
+    };
+
+    const buildPromptBody = async () => {
+      if (currentTokenCount < maxTokenCount && formattedMessages.length > 0) {
+        const message = formattedMessages.pop();
+        const isCreatedByUser = message.author === this.userLabel;
+        const messageString = `${message.author}\n${message.content}${this.endToken}\n`;
+        let newPromptBody = `${messageString}${promptBody}`;
+
+        context.unshift(message);
+
+        const tokenCountForMessage = this.getTokenCount(messageString);
+        const newTokenCount = currentTokenCount + tokenCountForMessage;
+
+        if (!isCreatedByUser) {
+          nextMessage.messageString = messageString;
+          nextMessage.tokenCount = tokenCountForMessage;
+        }
+
+        if (newTokenCount > maxTokenCount) {
+          if (!promptBody) {
+            // 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 ${newTokenCount} tokens long.`,
+            );
+          }
+
+          // Otherwise, ths message would put us over the token limit, so don't add it.
+          // if created by user, remove next message, otherwise remove only this message
+          if (isCreatedByUser) {
+            nextMessage.remove = true;
+          }
+
+          return false;
+        }
+        promptBody = newPromptBody;
+        currentTokenCount = newTokenCount;
+        // wait for next tick to avoid blocking the event loop
+        await new Promise((resolve) => setImmediate(resolve));
+        return buildPromptBody();
+      }
+      return true;
+    };
+
+    await buildPromptBody();
+
+    if (nextMessage.remove) {
+      promptBody = promptBody.replace(nextMessage.messageString, '');
+      currentTokenCount -= nextMessage.tokenCount;
+      context.shift();
+    }
+
+    const prompt = `${promptBody}${promptSuffix}`;
+    // Add 2 tokens for metadata after all messages have been counted.
+    currentTokenCount += 2;
+
+    // Use up to `this.maxContextTokens` tokens (prompt + response), but try to leave `this.maxTokens` tokens for the response.
+    this.modelOptions.maxOutputTokens = Math.min(
+      this.maxContextTokens - currentTokenCount,
+      this.maxResponseTokens,
+    );
+
+    return { prompt, context };
+  }
+
+  getCompletion() {
+    console.log('AnthropicClient doesn\'t use getCompletion (all handled in sendCompletion)');
+  }
+
+  // TODO: implement abortController usage
+  async sendCompletion(payload, { onProgress, abortController }) {
+    if (!abortController) {
+      abortController = new AbortController();
+    }
+
+    const { signal } = abortController;
+
+    const modelOptions = { ...this.modelOptions };
+    if (typeof onProgress === 'function') {
+      modelOptions.stream = true;
+    }
+
+    const { debug } = this.options;
+    if (debug) {
+      console.debug();
+      console.debug(modelOptions);
+      console.debug();
+    }
+
+    const client = this.getClient();
+    const metadata = {
+      user_id: this.user,
+    };
+
+    let text = '';
+    const requestOptions = {
+      prompt: payload,
+      model: this.modelOptions.model,
+      stream: this.modelOptions.stream || true,
+      max_tokens_to_sample: this.modelOptions.maxOutputTokens || 1500,
+      metadata,
+      ...modelOptions,
+    };
+    if (this.options.debug) {
+      console.log('AnthropicClient: requestOptions');
+      console.dir(requestOptions, { depth: null });
+    }
+    const response = await client.completions.create(requestOptions);
+
+    signal.addEventListener('abort', () => {
+      if (this.options.debug) {
+        console.log('AnthropicClient: message aborted!');
+      }
+      response.controller.abort();
+    });
+
+    for await (const completion of response) {
+      if (this.options.debug) {
+        // Uncomment to debug message stream
+        // console.debug(completion);
+      }
+      text += completion.completion;
+      onProgress(completion.completion);
+    }
+
+    signal.removeEventListener('abort', () => {
+      if (this.options.debug) {
+        console.log('AnthropicClient: message aborted!');
+      }
+      response.controller.abort();
+    });
+
+    return text.trim();
+  }
+
+  // I commented this out because I will need to refactor this for the BaseClient/all clients
+  // getMessageMapMethod() {
+  //   return ((message) => ({
+  //     author: message.isCreatedByUser ? this.userLabel : this.assistantLabel,
+  //     content: message?.content ?? message.text
+  //   })).bind(this);
+  // }
+
+  getSaveOptions() {
+    return {
+      promptPrefix: this.options.promptPrefix,
+      modelLabel: this.options.modelLabel,
+      ...this.modelOptions,
+    };
+  }
+
+  getBuildMessagesOptions() {
+    if (this.options.debug) {
+      console.log('AnthropicClient doesn\'t use getBuildMessagesOptions');
+    }
+  }
+
+  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;
+  }
+
+  getTokenCount(text) {
+    return this.gptEncoder.encode(text, 'all').length;
+  }
+}
+
+module.exports = AnthropicClient;

api/app/clients/BaseClient.js

@@ -0,0 +1,561 @@
+const crypto = require('crypto');
+const TextStream = require('./TextStream');
+const { RecursiveCharacterTextSplitter } = require('langchain/text_splitter');
+const { ChatOpenAI } = require('langchain/chat_models/openai');
+const { loadSummarizationChain } = require('langchain/chains');
+const { refinePrompt } = require('./prompts/refinePrompt');
+const { getConvo, getMessages, saveMessage, updateMessage, saveConvo } = require('../../models');
+
+class BaseClient {
+  constructor(apiKey, options = {}) {
+    this.apiKey = apiKey;
+    this.sender = options.sender || 'AI';
+    this.contextStrategy = null;
+    this.currentDateString = new Date().toLocaleDateString('en-us', {
+      year: 'numeric',
+      month: 'long',
+      day: 'numeric',
+    });
+  }
+
+  setOptions() {
+    throw new Error('Method \'setOptions\' must be implemented.');
+  }
+
+  getCompletion() {
+    throw new Error('Method \'getCompletion\' must be implemented.');
+  }
+
+  async sendCompletion() {
+    throw new Error('Method \'sendCompletion\' must be implemented.');
+  }
+
+  getSaveOptions() {
+    throw new Error('Subclasses must implement getSaveOptions');
+  }
+
+  async buildMessages() {
+    throw new Error('Subclasses must implement buildMessages');
+  }
+
+  getBuildMessagesOptions() {
+    throw new Error('Subclasses must implement getBuildMessagesOptions');
+  }
+
+  async generateTextStream(text, onProgress, options = {}) {
+    const stream = new TextStream(text, options);
+    await stream.processTextStream(onProgress);
+  }
+
+  async setMessageOptions(opts = {}) {
+    if (opts && typeof opts === 'object') {
+      this.setOptions(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 saveOptions = this.getSaveOptions();
+    this.abortController = opts.abortController || new AbortController();
+    this.currentMessages = (await this.loadHistory(conversationId, parentMessageId)) ?? [];
+
+    return {
+      ...opts,
+      user,
+      conversationId,
+      parentMessageId,
+      userMessageId,
+      responseMessageId,
+      saveOptions,
+    };
+  }
+
+  createUserMessage({ messageId, parentMessageId, conversationId, text }) {
+    const userMessage = {
+      messageId,
+      parentMessageId,
+      conversationId,
+      sender: 'User',
+      text,
+      isCreatedByUser: true,
+    };
+    return userMessage;
+  }
+
+  async handleStartMethods(message, opts) {
+    const { user, conversationId, parentMessageId, userMessageId, responseMessageId, saveOptions } =
+      await this.setMessageOptions(opts);
+
+    const userMessage = this.createUserMessage({
+      messageId: userMessageId,
+      parentMessageId,
+      conversationId,
+      text: message,
+    });
+
+    if (typeof opts?.getIds === 'function') {
+      opts.getIds({
+        userMessage,
+        conversationId,
+        responseMessageId,
+      });
+    }
+
+    if (typeof opts?.onStart === 'function') {
+      opts.onStart(userMessage);
+    }
+
+    return {
+      ...opts,
+      user,
+      conversationId,
+      responseMessageId,
+      saveOptions,
+      userMessage,
+    };
+  }
+
+  addInstructions(messages, instructions) {
+    const payload = [];
+    if (!instructions) {
+      return messages;
+    }
+    if (messages.length > 1) {
+      payload.push(...messages.slice(0, -1));
+    }
+
+    payload.push(instructions);
+
+    if (messages.length > 0) {
+      payload.push(messages[messages.length - 1]);
+    }
+
+    return payload;
+  }
+
+  async handleTokenCountMap(tokenCountMap) {
+    if (this.currentMessages.length === 0) {
+      return;
+    }
+
+    for (let i = 0; i < this.currentMessages.length; i++) {
+      // Skip the last message, which is the user message.
+      if (i === this.currentMessages.length - 1) {
+        break;
+      }
+
+      const message = this.currentMessages[i];
+      const { messageId } = message;
+      const update = {};
+
+      if (messageId === tokenCountMap.refined?.messageId) {
+        if (this.options.debug) {
+          console.debug(`Adding refined props to ${messageId}.`);
+        }
+
+        update.refinedMessageText = tokenCountMap.refined.content;
+        update.refinedTokenCount = tokenCountMap.refined.tokenCount;
+      }
+
+      if (message.tokenCount && !update.refinedTokenCount) {
+        if (this.options.debug) {
+          console.debug(`Skipping ${messageId}: already had a token count.`);
+        }
+        continue;
+      }
+
+      const tokenCount = tokenCountMap[messageId];
+      if (tokenCount) {
+        message.tokenCount = tokenCount;
+        update.tokenCount = tokenCount;
+        await this.updateMessageInDatabase({ messageId, ...update });
+      }
+    }
+  }
+
+  concatenateMessages(messages) {
+    return messages.reduce((acc, message) => {
+      const nameOrRole = message.name ?? message.role;
+      return acc + `${nameOrRole}:\n${message.content}\n\n`;
+    }, '');
+  }
+
+  async refineMessages(messagesToRefine, remainingContextTokens) {
+    const model = new ChatOpenAI({ temperature: 0 });
+    const chain = loadSummarizationChain(model, {
+      type: 'refine',
+      verbose: this.options.debug,
+      refinePrompt,
+    });
+    const splitter = new RecursiveCharacterTextSplitter({
+      chunkSize: 1500,
+      chunkOverlap: 100,
+    });
+    const userMessages = this.concatenateMessages(
+      messagesToRefine.filter((m) => m.role === 'user'),
+    );
+    const assistantMessages = this.concatenateMessages(
+      messagesToRefine.filter((m) => m.role !== 'user'),
+    );
+    const userDocs = await splitter.createDocuments([userMessages], [], {
+      chunkHeader: 'DOCUMENT NAME: User Message\n\n---\n\n',
+      appendChunkOverlapHeader: true,
+    });
+    const assistantDocs = await splitter.createDocuments([assistantMessages], [], {
+      chunkHeader: 'DOCUMENT NAME: Assistant Message\n\n---\n\n',
+      appendChunkOverlapHeader: true,
+    });
+    // const chunkSize = Math.round(concatenatedMessages.length / 512);
+    const input_documents = userDocs.concat(assistantDocs);
+    if (this.options.debug) {
+      console.debug('Refining messages...');
+    }
+    try {
+      const res = await chain.call({
+        input_documents,
+        signal: this.abortController.signal,
+      });
+
+      const refinedMessage = {
+        role: 'assistant',
+        content: res.output_text,
+        tokenCount: this.getTokenCount(res.output_text),
+      };
+
+      if (this.options.debug) {
+        console.debug('Refined messages', refinedMessage);
+        console.debug(
+          `remainingContextTokens: ${remainingContextTokens}, after refining: ${
+            remainingContextTokens - refinedMessage.tokenCount
+          }`,
+        );
+      }
+
+      return refinedMessage;
+    } catch (e) {
+      console.error('Error refining messages');
+      console.error(e);
+      return null;
+    }
+  }
+
+  /**
+   * This method processes an array of messages and returns a context of messages that fit within a token limit.
+   * It iterates over the messages from newest to oldest, adding them to the context until the token limit is reached.
+   * If the token limit would be exceeded by adding a message, that message and possibly the previous one are added to a separate array of messages to refine.
+   * The method uses `push` and `pop` operations for efficient array manipulation, and reverses the arrays at the end to maintain the original order of the messages.
+   * The method also includes a mechanism to avoid blocking the event loop by waiting for the next tick after each iteration.
+   *
+   * @param {Array} messages - An array of messages, each with a `tokenCount` property. The messages should be ordered from oldest to newest.
+   * @returns {Object} An object with three properties: `context`, `remainingContextTokens`, and `messagesToRefine`. `context` is an array of messages that fit within the token limit. `remainingContextTokens` is the number of tokens remaining within the limit after adding the messages to the context. `messagesToRefine` is an array of messages that were not added to the context because they would have exceeded the token limit.
+   */
+  async getMessagesWithinTokenLimit(messages) {
+    let currentTokenCount = 0;
+    let context = [];
+    let messagesToRefine = [];
+    let refineIndex = -1;
+    let remainingContextTokens = this.maxContextTokens;
+
+    for (let i = messages.length - 1; i >= 0; i--) {
+      const message = messages[i];
+      const newTokenCount = currentTokenCount + message.tokenCount;
+      const exceededLimit = newTokenCount > this.maxContextTokens;
+      let shouldRefine = exceededLimit && this.shouldRefineContext;
+      let refineNextMessage = i !== 0 && i !== 1 && context.length > 0;
+
+      if (shouldRefine) {
+        messagesToRefine.push(message);
+
+        if (refineIndex === -1) {
+          refineIndex = i;
+        }
+
+        if (refineNextMessage) {
+          refineIndex = i + 1;
+          const removedMessage = context.pop();
+          messagesToRefine.push(removedMessage);
+          currentTokenCount -= removedMessage.tokenCount;
+          remainingContextTokens = this.maxContextTokens - currentTokenCount;
+          refineNextMessage = false;
+        }
+
+        continue;
+      } else if (exceededLimit) {
+        break;
+      }
+
+      context.push(message);
+      currentTokenCount = newTokenCount;
+      remainingContextTokens = this.maxContextTokens - currentTokenCount;
+      await new Promise((resolve) => setImmediate(resolve));
+    }
+
+    return {
+      context: context.reverse(),
+      remainingContextTokens,
+      messagesToRefine: messagesToRefine.reverse(),
+      refineIndex,
+    };
+  }
+
+  async handleContextStrategy({ instructions, orderedMessages, formattedMessages }) {
+    let payload = this.addInstructions(formattedMessages, instructions);
+    let orderedWithInstructions = this.addInstructions(orderedMessages, instructions);
+    let { context, remainingContextTokens, messagesToRefine, refineIndex } =
+      await this.getMessagesWithinTokenLimit(payload);
+
+    payload = context;
+    let refinedMessage;
+
+    // if (messagesToRefine.length > 0) {
+    //   refinedMessage = await this.refineMessages(messagesToRefine, remainingContextTokens);
+    //   payload.unshift(refinedMessage);
+    //   remainingContextTokens -= refinedMessage.tokenCount;
+    // }
+    // if (remainingContextTokens <= instructions?.tokenCount) {
+    //   if (this.options.debug) {
+    //     console.debug(`Remaining context (${remainingContextTokens}) is less than instructions token count: ${instructions.tokenCount}`);
+    //   }
+
+    //   ({ context, remainingContextTokens, messagesToRefine, refineIndex } = await this.getMessagesWithinTokenLimit(payload));
+    //   payload = context;
+    // }
+
+    // Calculate the difference in length to determine how many messages were discarded if any
+    let diff = orderedWithInstructions.length - payload.length;
+
+    if (this.options.debug) {
+      console.debug('<---------------------------------DIFF--------------------------------->');
+      console.debug(
+        `Difference between payload (${payload.length}) and orderedWithInstructions (${orderedWithInstructions.length}): ${diff}`,
+      );
+      console.debug(
+        'remainingContextTokens, this.maxContextTokens (1/2)',
+        remainingContextTokens,
+        this.maxContextTokens,
+      );
+    }
+
+    // If the difference is positive, slice the orderedWithInstructions array
+    if (diff > 0) {
+      orderedWithInstructions = orderedWithInstructions.slice(diff);
+    }
+
+    if (messagesToRefine.length > 0) {
+      refinedMessage = await this.refineMessages(messagesToRefine, remainingContextTokens);
+      payload.unshift(refinedMessage);
+      remainingContextTokens -= refinedMessage.tokenCount;
+    }
+
+    if (this.options.debug) {
+      console.debug(
+        'remainingContextTokens, this.maxContextTokens (2/2)',
+        remainingContextTokens,
+        this.maxContextTokens,
+      );
+    }
+
+    let tokenCountMap = orderedWithInstructions.reduce((map, message, index) => {
+      if (!message.messageId) {
+        return map;
+      }
+
+      if (index === refineIndex) {
+        map.refined = { ...refinedMessage, messageId: message.messageId };
+      }
+
+      map[message.messageId] = payload[index].tokenCount;
+      return map;
+    }, {});
+
+    const promptTokens = this.maxContextTokens - remainingContextTokens;
+
+    if (this.options.debug) {
+      console.debug('<-------------------------PAYLOAD/TOKEN COUNT MAP------------------------->');
+      console.debug('Payload:', payload);
+      console.debug('Token Count Map:', tokenCountMap);
+      console.debug('Prompt Tokens', promptTokens, remainingContextTokens, this.maxContextTokens);
+    }
+
+    return { payload, tokenCountMap, promptTokens, messages: orderedWithInstructions };
+  }
+
+  async sendMessage(message, opts = {}) {
+    const { user, conversationId, responseMessageId, saveOptions, userMessage } =
+      await this.handleStartMethods(message, opts);
+
+    this.user = user;
+    // It's not necessary to push to currentMessages
+    // depending on subclass implementation of handling messages
+    this.currentMessages.push(userMessage);
+
+    let {
+      prompt: payload,
+      tokenCountMap,
+      promptTokens,
+    } = await this.buildMessages(
+      this.currentMessages,
+      // When the userMessage is pushed to currentMessages, the parentMessage is the userMessageId.
+      // this only matters when buildMessages is utilizing the parentMessageId, and may vary on implementation
+      userMessage.messageId,
+      this.getBuildMessagesOptions(opts),
+    );
+
+    if (this.options.debug) {
+      console.debug('payload');
+      console.debug(payload);
+    }
+
+    if (tokenCountMap) {
+      console.dir(tokenCountMap, { depth: null });
+      if (tokenCountMap[userMessage.messageId]) {
+        userMessage.tokenCount = tokenCountMap[userMessage.messageId];
+        console.log('userMessage.tokenCount', userMessage.tokenCount);
+        console.log('userMessage', userMessage);
+      }
+
+      payload = payload.map((message) => {
+        const messageWithoutTokenCount = message;
+        delete messageWithoutTokenCount.tokenCount;
+        return messageWithoutTokenCount;
+      });
+      this.handleTokenCountMap(tokenCountMap);
+    }
+
+    await this.saveMessageToDatabase(userMessage, saveOptions, user);
+    const responseMessage = {
+      messageId: responseMessageId,
+      conversationId,
+      parentMessageId: userMessage.messageId,
+      isCreatedByUser: false,
+      model: this.modelOptions.model,
+      sender: this.sender,
+      text: await this.sendCompletion(payload, opts),
+      promptTokens,
+    };
+
+    if (tokenCountMap && this.getTokenCountForResponse) {
+      responseMessage.tokenCount = this.getTokenCountForResponse(responseMessage);
+      responseMessage.completionTokens = responseMessage.tokenCount;
+    }
+    await this.saveMessageToDatabase(responseMessage, saveOptions, user);
+    delete responseMessage.tokenCount;
+    return responseMessage;
+  }
+
+  async getConversation(conversationId, user = null) {
+    return await getConvo(user, conversationId);
+  }
+
+  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) {
+      return [];
+    }
+
+    let mapMethod = null;
+    if (this.getMessageMapMethod) {
+      mapMethod = this.getMessageMapMethod();
+    }
+
+    return this.constructor.getMessagesForConversation(messages, parentMessageId, mapMethod);
+  }
+
+  async saveMessageToDatabase(message, endpointOptions, user = null) {
+    await saveMessage({ ...message, unfinished: false, cancelled: false });
+    await saveConvo(user, {
+      conversationId: message.conversationId,
+      endpoint: this.options.endpoint,
+      ...endpointOptions,
+    });
+  }
+
+  async updateMessageInDatabase(message) {
+    await updateMessage(message);
+  }
+
+  /**
+   * 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, mapMethod = null) {
+    if (!messages || messages.length === 0) {
+      return [];
+    }
+
+    const orderedMessages = [];
+    let currentMessageId = parentMessageId;
+    while (currentMessageId) {
+      const message = messages.find((msg) => {
+        const messageId = msg.messageId ?? msg.id;
+        return messageId === currentMessageId;
+      });
+      if (!message) {
+        break;
+      }
+      orderedMessages.unshift(message);
+      currentMessageId = message.parentMessageId;
+    }
+
+    if (mapMethod) {
+      return orderedMessages.map(mapMethod);
+    }
+
+    return orderedMessages;
+  }
+
+  /**
+   * 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) {
+    let tokensPerMessage;
+    let nameAdjustment;
+    if (this.modelOptions.model.startsWith('gpt-4')) {
+      tokensPerMessage = 3;
+      nameAdjustment = 1;
+    } else {
+      tokensPerMessage = 4;
+      nameAdjustment = -1;
+    }
+
+    if (this.options.debug) {
+      console.debug('getTokenCountForMessage', message);
+    }
+
+    // Map each property of the message to the number of tokens it contains
+    const propertyTokenCounts = Object.entries(message).map(([key, value]) => {
+      if (key === 'tokenCount' || typeof value !== 'string') {
+        return 0;
+      }
+      // Count the number of tokens in the property value
+      const numTokens = this.getTokenCount(value);
+
+      // Adjust by `nameAdjustment` tokens if the property key is 'name'
+      const adjustment = key === 'name' ? nameAdjustment : 0;
+      return numTokens + adjustment;
+    });
+
+    if (this.options.debug) {
+      console.debug('propertyTokenCounts', propertyTokenCounts);
+    }
+
+    // Sum the number of tokens in all properties and add `tokensPerMessage` for metadata
+    return propertyTokenCounts.reduce((a, b) => a + b, tokensPerMessage);
+  }
+}
+
+module.exports = BaseClient;

api/app/clients/ChatGPTClient.js

@@ -0,0 +1,587 @@
+const crypto = require('crypto');
+const Keyv = require('keyv');
+const {
+  encoding_for_model: encodingForModel,
+  get_encoding: getEncoding,
+} = require('@dqbd/tiktoken');
+const { fetchEventSource } = require('@waylaidwanderer/fetch-event-source');
+const { Agent, ProxyAgent } = require('undici');
+const BaseClient = require('./BaseClient');
+
+const CHATGPT_MODEL = 'gpt-3.5-turbo';
+const tokenizersCache = {};
+
+class ChatGPTClient extends BaseClient {
+  constructor(apiKey, options = {}, cacheOptions = {}) {
+    super(apiKey, options, cacheOptions);
+
+    cacheOptions.namespace = cacheOptions.namespace || 'chatgpt';
+    this.conversationsCache = new Keyv(cacheOptions);
+    this.setOptions(options);
+  }
+
+  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;
+    }
+
+    if (this.options.openaiApiKey) {
+      this.apiKey = this.options.openaiApiKey;
+    }
+
+    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 || CHATGPT_MODEL,
+      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' ? 1 : modelOptions.presence_penalty,
+      stop: modelOptions.stop,
+    };
+
+    this.isChatGptModel = this.modelOptions.model.startsWith('gpt-');
+    const { isChatGptModel } = this;
+    this.isUnofficialChatGptModel =
+      this.modelOptions.model.startsWith('text-chat') ||
+      this.modelOptions.model.startsWith('text-davinci-002-render');
+    const { isUnofficialChatGptModel } = this;
+
+    // Davinci models have a max context length of 4097 tokens.
+    this.maxContextTokens = this.options.maxContextTokens || (isChatGptModel ? 4095 : 4097);
+    // I decided to 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';
+
+    if (isChatGptModel) {
+      // 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 (isUnofficialChatGptModel) {
+      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 `chatGptLabel` because I've never seen it happen
+      this.modelOptions.stop = stopTokens;
+    }
+
+    if (this.options.reverseProxyUrl) {
+      this.completionsUrl = this.options.reverseProxyUrl;
+    } else if (isChatGptModel) {
+      this.completionsUrl = 'https://api.openai.com/v1/chat/completions';
+    } else {
+      this.completionsUrl = 'https://api.openai.com/v1/completions';
+    }
+
+    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 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.apiKey && this.options.azure) {
+      opts.headers['api-key'] = this.apiKey;
+    } else if (this.apiKey) {
+      opts.headers.Authorization = `Bearer ${this.apiKey}`;
+    }
+
+    if (this.options.headers) {
+      opts.headers = { ...opts.headers, ...this.options.headers };
+    }
+
+    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} - ${body}`);
+      error.status = response.status;
+      try {
+        error.json = JSON.parse(body);
+      } catch {
+        error.body = body;
+      }
+      throw error;
+    }
+    return response.json();
+  }
+
+  async generateTitle(userMessage, botMessage) {
+    const instructionsPayload = {
+      role: 'system',
+      content: `Write an extremely concise subtitle for this conversation with no more than a few words. All words should be capitalized. Exclude punctuation.
+
+||>Message:
+${userMessage.message}
+||>Response:
+${botMessage.message}
+
+||>Title:`,
+    };
+
+    const titleGenClientOptions = JSON.parse(JSON.stringify(this.options));
+    titleGenClientOptions.modelOptions = {
+      model: 'gpt-3.5-turbo',
+      temperature: 0,
+      presence_penalty: 0,
+      frequency_penalty: 0,
+    };
+    const titleGenClient = new ChatGPTClient(this.apiKey, titleGenClientOptions);
+    const result = await titleGenClient.getCompletion([instructionsPayload], null);
+    // remove any non-alphanumeric characters, replace multiple spaces with 1, and then trim
+    return result.choices[0].message.content
+      .replace(/[^a-zA-Z0-9' ]/g, '')
+      .replace(/\s+/g, ' ')
+      .trim();
+  }
+
+  async sendMessage(message, opts = {}) {
+    if (opts.clientOptions && typeof opts.clientOptions === 'object') {
+      this.setOptions(opts.clientOptions);
+    }
+
+    const conversationId = opts.conversationId || crypto.randomUUID();
+    const parentMessageId = opts.parentMessageId || crypto.randomUUID();
+
+    let conversation =
+      typeof opts.conversation === 'object'
+        ? opts.conversation
+        : await this.conversationsCache.get(conversationId);
+
+    let isNewConversation = false;
+    if (!conversation) {
+      conversation = {
+        messages: [],
+        createdAt: Date.now(),
+      };
+      isNewConversation = true;
+    }
+
+    const shouldGenerateTitle = opts.shouldGenerateTitle && isNewConversation;
+
+    const userMessage = {
+      id: crypto.randomUUID(),
+      parentMessageId,
+      role: 'User',
+      message,
+    };
+    conversation.messages.push(userMessage);
+
+    // 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.
+    const { prompt: payload, context } = await this.buildPrompt(
+      conversation.messages,
+      userMessage.id,
+      {
+        isChatGptModel: this.isChatGptModel,
+        promptPrefix: opts.promptPrefix,
+      },
+    );
+
+    if (this.options.keepNecessaryMessagesOnly) {
+      conversation.messages = context;
+    }
+
+    let reply = '';
+    let result = null;
+    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 (this.options.debug) {
+            console.debug(token);
+          }
+          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, '');
+      }
+    }
+
+    // avoids some rendering issues when using the CLI app
+    if (this.options.debug) {
+      console.debug();
+    }
+
+    reply = reply.trim();
+
+    const replyMessage = {
+      id: crypto.randomUUID(),
+      parentMessageId: userMessage.id,
+      role: 'ChatGPT',
+      message: reply,
+    };
+    conversation.messages.push(replyMessage);
+
+    const returnData = {
+      response: replyMessage.message,
+      conversationId,
+      parentMessageId: replyMessage.parentMessageId,
+      messageId: replyMessage.id,
+      details: result || {},
+    };
+
+    if (shouldGenerateTitle) {
+      conversation.title = await this.generateTitle(userMessage, replyMessage);
+      returnData.title = conversation.title;
+    }
+
+    await this.conversationsCache.set(conversationId, conversation);
+
+    if (this.options.returnConversation) {
+      returnData.conversation = conversation;
+    }
+
+    return returnData;
+  }
+
+  async buildPrompt(messages, parentMessageId, { isChatGptModel = false, promptPrefix = null }) {
+    const orderedMessages = this.constructor.getMessagesForConversation(messages, parentMessageId);
+
+    promptPrefix = (promptPrefix || this.options.promptPrefix || '').trim();
+    if (promptPrefix) {
+      // 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 {
+      const currentDateString = new Date().toLocaleDateString('en-us', {
+        year: 'numeric',
+        month: 'long',
+        day: 'numeric',
+      });
+      promptPrefix = `${this.startToken}Instructions:\nYou are ChatGPT, a large language model trained by OpenAI. Respond conversationally.\nCurrent date: ${currentDateString}${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,
+    };
+
+    let currentTokenCount;
+    if (isChatGptModel) {
+      currentTokenCount =
+        this.getTokenCountForMessage(instructionsPayload) +
+        this.getTokenCountForMessage(messagePayload);
+    } else {
+      currentTokenCount = this.getTokenCount(`${promptPrefix}${promptSuffix}`);
+    }
+    let promptBody = '';
+    const maxTokenCount = this.maxPromptTokens;
+
+    const context = [];
+
+    // 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?.isCreatedByUser || message?.role?.toLowerCase() === 'user'
+            ? this.userLabel
+            : this.chatGptLabel;
+        const messageString = `${this.startToken}${roleLabel}:\n${
+          message?.text ?? message?.message
+        }${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}`;
+        }
+
+        context.unshift(message);
+
+        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 ${newTokenCount} tokens long.`,
+          );
+        }
+        promptBody = newPromptBody;
+        currentTokenCount = newTokenCount;
+        // wait for next tick to avoid blocking the event loop
+        await new Promise((resolve) => setImmediate(resolve));
+        return buildPromptBody();
+      }
+      return true;
+    };
+
+    await buildPromptBody();
+
+    const prompt = `${promptBody}${promptSuffix}`;
+    if (isChatGptModel) {
+      messagePayload.content = prompt;
+      // Add 2 tokens for metadata after all messages have been counted.
+      currentTokenCount += 2;
+    }
+
+    // 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.options.debug) {
+      console.debug(`Prompt : ${prompt}`);
+    }
+
+    if (isChatGptModel) {
+      return { prompt: [instructionsPayload, messagePayload], context };
+    }
+    return { prompt, context };
+  }
+
+  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) {
+    let tokensPerMessage;
+    let nameAdjustment;
+    if (this.modelOptions.model.startsWith('gpt-4')) {
+      tokensPerMessage = 3;
+      nameAdjustment = 1;
+    } else {
+      tokensPerMessage = 4;
+      nameAdjustment = -1;
+    }
+
+    // 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);
+
+      // Adjust by `nameAdjustment` tokens if the property key is 'name'
+      const adjustment = key === 'name' ? nameAdjustment : 0;
+      return numTokens + adjustment;
+    });
+
+    // Sum the number of tokens in all properties and add `tokensPerMessage` for metadata
+    return propertyTokenCounts.reduce((a, b) => a + b, tokensPerMessage);
+  }
+}
+
+module.exports = ChatGPTClient;

api/app/clients/GoogleClient.js

@@ -1,48 +1,62 @@
-const crypto = require('crypto');
-const TextStream = require('../stream');
+const BaseClient = require('./BaseClient');
 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 {
+  encoding_for_model: encodingForModel,
+  get_encoding: getEncoding,
+} = require('@dqbd/tiktoken');
 
 const tokenizersCache = {};
 
-class GoogleAgent {
+class GoogleClient extends BaseClient {
   constructor(credentials, options = {}) {
+    super('apiKey', options);
     this.client_email = credentials.client_email;
     this.project_id = credentials.project_id;
     this.private_key = credentials.private_key;
+    this.sender = 'PaLM2';
     this.setOptions(options);
-    this.currentDateString = new Date().toLocaleDateString('en-us', {
-      year: 'numeric',
-      month: 'long',
-      day: 'numeric'
-    });
   }
 
+  /* Google/PaLM2 specific methods */
   constructUrl() {
     return `https://us-central1-aiplatform.googleapis.com/v1/projects/${this.project_id}/locations/us-central1/publishers/google/models/${this.modelOptions.model}:predict`;
   }
 
+  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;
+  }
+
+  /* Required Client methods */
   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
+        ...options.modelOptions,
       };
       delete options.modelOptions;
       // now we can merge options
       this.options = {
         ...this.options,
-        ...options
+        ...options,
       };
     } else {
       this.options = options;
     }
 
     this.options.examples = this.options.examples.filter(
-      obj => obj.input.content !== '' && obj.output.content !== ''
+      (obj) => obj.input.content !== '' && obj.output.content !== '',
     );
 
     const modelOptions = this.options.modelOptions || {};
@@ -52,7 +66,7 @@ class GoogleAgent {
       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
+      topK: typeof modelOptions.topK === 'undefined' ? 40 : modelOptions.topK, // 1-40, default: 40
       // stop: modelOptions.stop // no stop method for now
     };
 
@@ -65,13 +79,14 @@ class GoogleAgent {
     // 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;
+    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})`
+        }) must be less than or equal to maxContextTokens (${this.maxContextTokens})`,
       );
     }
 
@@ -90,7 +105,7 @@ class GoogleAgent {
       this.endToken = '<|im_end|>';
       this.gptEncoder = this.constructor.getTokenizer('text-davinci-003', true, {
         '<|im_start|>': 100264,
-        '<|im_end|>': 100265
+        '<|im_end|>': 100265,
       });
     } else {
       // Previously I was trying to use "<|endoftext|>" but there seems to be some bug with OpenAI's token counting
@@ -125,42 +140,22 @@ class GoogleAgent {
     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;
+  getMessageMapMethod() {
+    return ((message) => ({
+      author: message?.author ?? (message.isCreatedByUser ? this.userLabel : this.modelLabel),
+      content: message?.content ?? message.text,
+    })).bind(this);
   }
 
-  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 = [] }) {
+  buildMessages(messages = []) {
+    const formattedMessages = messages.map(this.getMessageMapMethod());
     let payload = {
       instances: [
         {
-          messages: [...messages, { author: this.userLabel, content: input }]
-        }
+          messages: formattedMessages,
+        },
       ],
-      parameters: this.options.modelOptions
+      parameters: this.options.modelOptions,
     };
 
     if (this.options.promptPrefix) {
@@ -171,23 +166,24 @@ class GoogleAgent {
       payload.instances[0].examples = this.options.examples;
     }
 
+    /* TO-DO: text model needs more context since it can't process an array of messages */
     if (this.isTextModel) {
       payload.instances = [
         {
-          prompt: input
-        }
+          prompt: messages[messages.length - 1].content,
+        },
       ];
     }
 
     if (this.options.debug) {
-      console.debug('buildPayload');
+      console.debug('GoogleClient buildMessages');
       console.dir(payload, { depth: null });
     }
 
-    return payload;
+    return { prompt: payload };
   }
 
-  async getCompletion(input, messages = [], abortController = null) {
+  async getCompletion(payload, abortController = null) {
     if (!abortController) {
       abortController = new AbortController();
     }
@@ -203,9 +199,9 @@ class GoogleAgent {
       method: 'POST',
       agent: new Agent({
         bodyTimeout: 0,
-        headersTimeout: 0
+        headersTimeout: 0,
       }),
-      signal: abortController.signal
+      signal: abortController.signal,
     };
 
     if (this.options.proxy) {
@@ -213,88 +209,37 @@ class GoogleAgent {
     }
 
     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 = 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
+  getSaveOptions() {
+    return {
+      promptPrefix: this.options.promptPrefix,
+      modelLabel: this.options.modelLabel,
+      ...this.modelOptions,
     };
+  }
 
-    if (typeof opts?.getIds === 'function') {
-      opts.getIds({
-        userMessage,
-        conversationId,
-        responseMessageId
-      });
-    }
+  getBuildMessagesOptions() {
+    // console.log('GoogleClient doesn\'t use getBuildMessagesOptions');
+  }
 
-    console.log('userMessage', userMessage);
-
-    await this.saveMessageToDatabase(userMessage, user);
+  async sendCompletion(payload, opts = {}) {
+    console.log('GoogleClient: sendcompletion', payload, opts);
     let reply = '';
     let blocked = false;
     try {
-      const result = await this.getCompletion(message, messages, opts.abortController);
+      const result = await this.getCompletion(payload, opts.abortController);
       blocked = result?.predictions?.[0]?.safetyAttributes?.blocked;
-      reply = result?.predictions?.[0]?.candidates?.[0]?.content || result?.predictions?.[0]?.content || '';
+      reply =
+        result?.predictions?.[0]?.candidates?.[0]?.content ||
+        result?.predictions?.[0]?.content ||
+        '';
       if (blocked === true) {
         reply = `Google blocked a proper response to your message:\n${JSON.stringify(
-          result.predictions[0].safetyAttributes
+          result.predictions[0].safetyAttributes,
         )}${reply.length > 0 ? `\nAI Response:\n${reply}` : ''}`;
       }
       if (this.options.debug) {
@@ -305,86 +250,31 @@ class GoogleAgent {
       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);
+      await this.generateTextStream(reply, opts.onProgress, { delay: 0.5 });
     }
 
-    const responseMessage = {
-      messageId: responseMessageId,
-      conversationId,
-      parentMessageId: userMessage.messageId,
-      sender: 'PaLM2',
-      text: reply,
-      error: blocked,
-      isCreatedByUser: false
-    };
+    return reply.trim();
+  }
 
-    await this.saveMessageToDatabase(responseMessage, user);
-    return responseMessage;
+  /* TO-DO: Handle tokens with Google tokenization NOTE: these are required */
+  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;
   }
 
   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;
+module.exports = GoogleClient;

api/app/clients/OpenAIClient.js

@@ -0,0 +1,369 @@
+const BaseClient = require('./BaseClient');
+const ChatGPTClient = require('./ChatGPTClient');
+const {
+  encoding_for_model: encodingForModel,
+  get_encoding: getEncoding,
+} = require('@dqbd/tiktoken');
+const { maxTokensMap, genAzureChatCompletion } = require('../../utils');
+
+// Cache to store Tiktoken instances
+const tokenizersCache = {};
+// Counter for keeping track of the number of tokenizer calls
+let tokenizerCallsCount = 0;
+
+class OpenAIClient extends BaseClient {
+  constructor(apiKey, options = {}) {
+    super(apiKey, options);
+    this.ChatGPTClient = new ChatGPTClient();
+    this.buildPrompt = this.ChatGPTClient.buildPrompt.bind(this);
+    this.getCompletion = this.ChatGPTClient.getCompletion.bind(this);
+    this.sender = options.sender ?? 'ChatGPT';
+    this.contextStrategy = options.contextStrategy
+      ? options.contextStrategy.toLowerCase()
+      : 'discard';
+    this.shouldRefineContext = this.contextStrategy === 'refine';
+    this.azure = options.azure || false;
+    if (this.azure) {
+      this.azureEndpoint = genAzureChatCompletion(this.azure);
+    }
+    this.setOptions(options);
+  }
+
+  setOptions(options) {
+    if (this.options && !this.options.replaceOptions) {
+      this.options.modelOptions = {
+        ...this.options.modelOptions,
+        ...options.modelOptions,
+      };
+      delete options.modelOptions;
+      this.options = {
+        ...this.options,
+        ...options,
+      };
+    } else {
+      this.options = options;
+    }
+
+    if (this.options.openaiApiKey) {
+      this.apiKey = this.options.openaiApiKey;
+    }
+
+    const modelOptions = this.options.modelOptions || {};
+    if (!this.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' ? 1 : modelOptions.presence_penalty,
+        stop: modelOptions.stop,
+      };
+    }
+
+    this.isChatCompletion =
+      this.options.reverseProxyUrl ||
+      this.options.localAI ||
+      this.modelOptions.model.startsWith('gpt-');
+    this.isChatGptModel = this.isChatCompletion;
+    if (this.modelOptions.model === 'text-davinci-003') {
+      this.isChatCompletion = false;
+      this.isChatGptModel = false;
+    }
+    const { isChatGptModel } = this;
+    this.isUnofficialChatGptModel =
+      this.modelOptions.model.startsWith('text-chat') ||
+      this.modelOptions.model.startsWith('text-davinci-002-render');
+    this.maxContextTokens = maxTokensMap[this.modelOptions.model] ?? 4095; // 1 less than maximum
+    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 || 'Assistant';
+
+    this.setupTokens();
+
+    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|>');
+      this.modelOptions.stop = stopTokens;
+    }
+
+    if (this.options.reverseProxyUrl) {
+      this.completionsUrl = this.options.reverseProxyUrl;
+    } else if (isChatGptModel) {
+      this.completionsUrl = 'https://api.openai.com/v1/chat/completions';
+    } else {
+      this.completionsUrl = 'https://api.openai.com/v1/completions';
+    }
+
+    if (this.azureEndpoint) {
+      this.completionsUrl = this.azureEndpoint;
+    }
+
+    if (this.azureEndpoint && this.options.debug) {
+      console.debug(`Using Azure endpoint: ${this.azureEndpoint}`, this.azure);
+    }
+
+    return this;
+  }
+
+  setupTokens() {
+    if (this.isChatCompletion) {
+      this.startToken = '||>';
+      this.endToken = '';
+    } else if (this.isUnofficialChatGptModel) {
+      this.startToken = '<|im_start|>';
+      this.endToken = '<|im_end|>';
+    } else {
+      this.startToken = '||>';
+      this.endToken = '';
+    }
+  }
+
+  // Selects an appropriate tokenizer based on the current configuration of the client instance.
+  // It takes into account factors such as whether it's a chat completion, an unofficial chat GPT model, etc.
+  selectTokenizer() {
+    let tokenizer;
+    this.encoding = 'text-davinci-003';
+    if (this.isChatCompletion) {
+      this.encoding = 'cl100k_base';
+      tokenizer = this.constructor.getTokenizer(this.encoding);
+    } else if (this.isUnofficialChatGptModel) {
+      const extendSpecialTokens = {
+        '<|im_start|>': 100264,
+        '<|im_end|>': 100265,
+      };
+      tokenizer = this.constructor.getTokenizer(this.encoding, true, extendSpecialTokens);
+    } else {
+      try {
+        this.encoding = this.modelOptions.model;
+        tokenizer = this.constructor.getTokenizer(this.modelOptions.model, true);
+      } catch {
+        tokenizer = this.constructor.getTokenizer(this.encoding, true);
+      }
+    }
+
+    return tokenizer;
+  }
+
+  // Retrieves a tokenizer either from the cache or creates a new one if one doesn't exist in the cache.
+  // If a tokenizer is being created, it's also added to the cache.
+  static getTokenizer(encoding, isModelName = false, extendSpecialTokens = {}) {
+    let tokenizer;
+    if (tokenizersCache[encoding]) {
+      tokenizer = tokenizersCache[encoding];
+    } else {
+      if (isModelName) {
+        tokenizer = encodingForModel(encoding, extendSpecialTokens);
+      } else {
+        tokenizer = getEncoding(encoding, extendSpecialTokens);
+      }
+      tokenizersCache[encoding] = tokenizer;
+    }
+    return tokenizer;
+  }
+
+  // Frees all encoders in the cache and resets the count.
+  static freeAndResetAllEncoders() {
+    try {
+      Object.keys(tokenizersCache).forEach((key) => {
+        if (tokenizersCache[key]) {
+          tokenizersCache[key].free();
+          delete tokenizersCache[key];
+        }
+      });
+      // Reset count
+      tokenizerCallsCount = 1;
+    } catch (error) {
+      console.log('Free and reset encoders error');
+      console.error(error);
+    }
+  }
+
+  // Checks if the cache of tokenizers has reached a certain size. If it has, it frees and resets all tokenizers.
+  resetTokenizersIfNecessary() {
+    if (tokenizerCallsCount >= 25) {
+      if (this.options.debug) {
+        console.debug('freeAndResetAllEncoders: reached 25 encodings, resetting...');
+      }
+      this.constructor.freeAndResetAllEncoders();
+    }
+    tokenizerCallsCount++;
+  }
+
+  // Returns the token count of a given text. It also checks and resets the tokenizers if necessary.
+  getTokenCount(text) {
+    this.resetTokenizersIfNecessary();
+    try {
+      const tokenizer = this.selectTokenizer();
+      return tokenizer.encode(text, 'all').length;
+    } catch (error) {
+      this.constructor.freeAndResetAllEncoders();
+      const tokenizer = this.selectTokenizer();
+      return tokenizer.encode(text, 'all').length;
+    }
+  }
+
+  getSaveOptions() {
+    return {
+      chatGptLabel: this.options.chatGptLabel,
+      promptPrefix: this.options.promptPrefix,
+      ...this.modelOptions,
+    };
+  }
+
+  getBuildMessagesOptions(opts) {
+    return {
+      isChatCompletion: this.isChatCompletion,
+      promptPrefix: opts.promptPrefix,
+      abortController: opts.abortController,
+    };
+  }
+
+  async buildMessages(
+    messages,
+    parentMessageId,
+    { isChatCompletion = false, promptPrefix = null },
+  ) {
+    if (!isChatCompletion) {
+      return await this.buildPrompt(messages, parentMessageId, {
+        isChatGptModel: isChatCompletion,
+        promptPrefix,
+      });
+    }
+
+    let payload;
+    let instructions;
+    let tokenCountMap;
+    let promptTokens;
+    let orderedMessages = this.constructor.getMessagesForConversation(messages, parentMessageId);
+
+    promptPrefix = (promptPrefix || this.options.promptPrefix || '').trim();
+    if (promptPrefix) {
+      promptPrefix = `Instructions:\n${promptPrefix}`;
+      instructions = {
+        role: 'system',
+        name: 'instructions',
+        content: promptPrefix,
+      };
+
+      if (this.contextStrategy) {
+        instructions.tokenCount = this.getTokenCountForMessage(instructions);
+      }
+    }
+
+    const formattedMessages = orderedMessages.map((message) => {
+      let { role: _role, sender, text } = message;
+      const role = _role ?? sender;
+      const content = text ?? '';
+      const formattedMessage = {
+        role: role?.toLowerCase() === 'user' ? 'user' : 'assistant',
+        content,
+      };
+
+      if (this.options?.name && formattedMessage.role === 'user') {
+        formattedMessage.name = this.options.name;
+      }
+
+      if (this.contextStrategy) {
+        formattedMessage.tokenCount =
+          message.tokenCount ?? this.getTokenCountForMessage(formattedMessage);
+      }
+
+      return formattedMessage;
+    });
+
+    // TODO: need to handle interleaving instructions better
+    if (this.contextStrategy) {
+      ({ payload, tokenCountMap, promptTokens, messages } = await this.handleContextStrategy({
+        instructions,
+        orderedMessages,
+        formattedMessages,
+      }));
+    }
+
+    const result = {
+      prompt: payload,
+      promptTokens,
+      messages,
+    };
+
+    if (tokenCountMap) {
+      tokenCountMap.instructions = instructions?.tokenCount;
+      result.tokenCountMap = tokenCountMap;
+    }
+
+    return result;
+  }
+
+  async sendCompletion(payload, opts = {}) {
+    let reply = '';
+    let result = null;
+    if (typeof opts.onProgress === 'function') {
+      await this.getCompletion(
+        payload,
+        (progressMessage) => {
+          if (progressMessage === '[DONE]') {
+            return;
+          }
+          const token = this.isChatCompletion
+            ? progressMessage.choices?.[0]?.delta?.content
+            : progressMessage.choices?.[0]?.text;
+          // first event's delta content is always undefined
+          if (!token) {
+            return;
+          }
+          if (this.options.debug) {
+            // console.debug(token);
+          }
+          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.isChatCompletion) {
+        reply = result.choices[0].message.content;
+      } else {
+        reply = result.choices[0].text.replace(this.endToken, '');
+      }
+    }
+
+    return reply.trim();
+  }
+
+  getTokenCountForResponse(response) {
+    return this.getTokenCountForMessage({
+      role: 'assistant',
+      content: response.text,
+    });
+  }
+}
+
+module.exports = OpenAIClient;

api/app/clients/PluginsClient.js

@@ -0,0 +1,569 @@
+const OpenAIClient = require('./OpenAIClient');
+const { ChatOpenAI } = require('langchain/chat_models/openai');
+const { CallbackManager } = require('langchain/callbacks');
+const { initializeCustomAgent, initializeFunctionsAgent } = require('./agents/');
+const { findMessageContent } = require('../../utils');
+const { loadTools } = require('./tools/util');
+const { SelfReflectionTool } = require('./tools/');
+const { HumanChatMessage, AIChatMessage } = require('langchain/schema');
+const { instructions, imageInstructions, errorInstructions } = require('./prompts/instructions');
+
+class PluginsClient extends OpenAIClient {
+  constructor(apiKey, options = {}) {
+    super(apiKey, options);
+    this.sender = options.sender ?? 'Assistant';
+    this.tools = [];
+    this.actions = [];
+    this.openAIApiKey = apiKey;
+    this.setOptions(options);
+    this.executor = null;
+  }
+
+  getActions(input = null) {
+    let output = 'Internal thoughts & actions taken:\n"';
+    let actions = input || this.actions;
+
+    if (actions[0]?.action && this.functionsAgent) {
+      actions = actions.map((step) => ({
+        log: `Action: ${step.action?.tool || ''}\nInput: ${
+          JSON.stringify(step.action?.toolInput) || ''
+        }\nObservation: ${step.observation}`,
+      }));
+    } else if (actions[0]?.action) {
+      actions = actions.map((step) => ({
+        log: `${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 user hasn\'t seen your answer or thoughts yet.'
+      : 'respond to the User Message below based on your preliminary thoughts & actions.';
+
+    return `As a helpful AI Assistant, ${prefix}${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) {
+    this.agentOptions = options.agentOptions;
+    this.functionsAgent = this.agentOptions?.agent === 'functions';
+    this.agentIsGpt3 = this.agentOptions?.model.startsWith('gpt-3');
+    if (this.functionsAgent && this.agentOptions.model) {
+      this.agentOptions.model = this.getFunctionModelName(this.agentOptions.model);
+    }
+
+    super.setOptions(options);
+    this.isGpt3 = this.modelOptions.model.startsWith('gpt-3');
+
+    if (this.options.reverseProxyUrl) {
+      this.langchainProxy = this.options.reverseProxyUrl.match(/.*v1/)[0];
+    }
+  }
+
+  getSaveOptions() {
+    return {
+      chatGptLabel: this.options.chatGptLabel,
+      promptPrefix: this.options.promptPrefix,
+      ...this.modelOptions,
+      agentOptions: this.agentOptions,
+    };
+  }
+
+  saveLatestAction(action) {
+    this.actions.push(action);
+  }
+
+  getFunctionModelName(input) {
+    if (input.startsWith('gpt-3.5-turbo')) {
+      return 'gpt-3.5-turbo';
+    } else if (input.startsWith('gpt-4')) {
+      return 'gpt-4';
+    } else {
+      return 'gpt-3.5-turbo';
+    }
+  }
+
+  getBuildMessagesOptions(opts) {
+    return {
+      isChatCompletion: true,
+      promptPrefix: opts.promptPrefix,
+      abortController: opts.abortController,
+    };
+  }
+
+  createLLM(modelOptions, configOptions) {
+    let credentials = { openAIApiKey: this.openAIApiKey };
+    let configuration = {
+      apiKey: this.openAIApiKey,
+    };
+
+    if (this.azure) {
+      credentials = {};
+      configuration = {};
+    }
+
+    if (this.options.debug) {
+      console.debug('createLLM: configOptions');
+      console.debug(configOptions);
+    }
+
+    return new ChatOpenAI({ credentials, configuration, ...modelOptions }, configOptions);
+  }
+
+  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.createLLM(modelOptions, configOptions);
+
+    if (this.options.debug) {
+      console.debug(
+        `<-----Agent Model: ${model.modelName} | Temp: ${model.temperature} | Functions: ${this.functionsAgent}----->`,
+      );
+    }
+
+    this.availableTools = await loadTools({
+      user,
+      model,
+      tools: this.options.tools,
+      functions: this.functionsAgent,
+      options: {
+        openAIApiKey: this.openAIApiKey,
+        debug: this.options?.debug,
+        message,
+      },
+    });
+    // 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.functionsAgent) {
+      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);
+      }
+    };
+
+    // Map Messages to Langchain format
+    const pastMessages = this.currentMessages
+      .slice(0, -1)
+      .map((msg) =>
+        msg?.isCreatedByUser || msg?.role?.toLowerCase() === 'user'
+          ? new HumanChatMessage(msg.text)
+          : new AIChatMessage(msg.text),
+      );
+
+    // initialize agent
+    const initializer = this.functionsAgent ? initializeFunctionsAgent : initializeCustomAgent;
+    this.executor = await initializer({
+      model,
+      signal,
+      pastMessages,
+      tools: this.tools,
+      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.');
+    }
+
+    onAgentAction(
+      {
+        tool: 'self-reflection',
+        toolInput: `Processing the User's message:\n"${message}"`,
+        log: '',
+      },
+      true,
+    );
+  }
+
+  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;
+        const content = findMessageContent(message);
+        if (content) {
+          errorMessage = content;
+          break;
+        }
+        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;
+        }
+      }
+    }
+  }
+
+  addImages(intermediateSteps, responseMessage) {
+    if (!intermediateSteps || !responseMessage) {
+      return;
+    }
+
+    intermediateSteps.forEach((step) => {
+      const { observation } = step;
+      if (!observation || !observation.includes('![')) {
+        return;
+      }
+
+      // Extract the image file path from the observation
+      const observedImagePath = observation.match(/\(\/images\/.*\.\w*\)/g)[0];
+
+      // Check if the responseMessage already includes the image file path
+      if (!responseMessage.text.includes(observedImagePath)) {
+        // If the image file path is not found, append the whole observation
+        responseMessage.text += '\n' + observation;
+        if (this.options.debug) {
+          console.debug('added image from intermediateSteps');
+        }
+      }
+    });
+  }
+
+  async handleResponseMessage(responseMessage, saveOptions, user) {
+    responseMessage.tokenCount = this.getTokenCountForResponse(responseMessage);
+    responseMessage.completionTokens = responseMessage.tokenCount;
+    await this.saveMessageToDatabase(responseMessage, saveOptions, user);
+    delete responseMessage.tokenCount;
+    return { ...responseMessage, ...this.result };
+  }
+
+  async sendMessage(message, opts = {}) {
+    const completionMode = this.options.tools.length === 0;
+    if (completionMode) {
+      this.setOptions(opts);
+      return super.sendMessage(message, opts);
+    }
+    console.log('Plugins sendMessage', message, opts);
+    const {
+      user,
+      conversationId,
+      responseMessageId,
+      saveOptions,
+      userMessage,
+      onAgentAction,
+      onChainEnd,
+    } = await this.handleStartMethods(message, opts);
+
+    this.currentMessages.push(userMessage);
+
+    let {
+      prompt: payload,
+      tokenCountMap,
+      promptTokens,
+      messages,
+    } = await this.buildMessages(
+      this.currentMessages,
+      userMessage.messageId,
+      this.getBuildMessagesOptions({
+        promptPrefix: null,
+        abortController: this.abortController,
+      }),
+    );
+
+    if (tokenCountMap) {
+      console.dir(tokenCountMap, { depth: null });
+      if (tokenCountMap[userMessage.messageId]) {
+        userMessage.tokenCount = tokenCountMap[userMessage.messageId];
+        console.log('userMessage.tokenCount', userMessage.tokenCount);
+      }
+      payload = payload.map((message) => {
+        const messageWithoutTokenCount = message;
+        delete messageWithoutTokenCount.tokenCount;
+        return messageWithoutTokenCount;
+      });
+      this.handleTokenCountMap(tokenCountMap);
+    }
+
+    this.result = {};
+    if (messages) {
+      this.currentMessages = messages;
+    }
+    await this.saveMessageToDatabase(userMessage, saveOptions, user);
+    const responseMessage = {
+      messageId: responseMessageId,
+      conversationId,
+      parentMessageId: userMessage.messageId,
+      isCreatedByUser: false,
+      model: this.modelOptions.model,
+      sender: this.sender,
+      promptTokens,
+    };
+
+    await this.initialize({
+      user,
+      message,
+      onAgentAction,
+      onChainEnd,
+      signal: this.abortController.signal,
+    });
+    await this.executorCall(message, this.abortController.signal);
+
+    // If message was aborted mid-generation
+    if (this.result?.errorMessage?.length > 0 && this.result?.errorMessage?.includes('cancel')) {
+      responseMessage.text = 'Cancelled.';
+      return await this.handleResponseMessage(responseMessage, saveOptions, user);
+    }
+
+    if (this.agentOptions.skipCompletion && this.result.output) {
+      responseMessage.text = this.result.output;
+      this.addImages(this.result.intermediateSteps, responseMessage);
+      await this.generateTextStream(this.result.output, opts.onProgress, { delay: 8 });
+      return await this.handleResponseMessage(responseMessage, saveOptions, user);
+    }
+
+    if (this.options.debug) {
+      console.debug('Plugins completion phase: this.result');
+      console.debug(this.result);
+    }
+
+    const promptPrefix = this.buildPromptPrefix(this.result, message);
+
+    if (this.options.debug) {
+      console.debug('Plugins: promptPrefix');
+      console.debug(promptPrefix);
+    }
+
+    payload = await this.buildCompletionPrompt({
+      messages: this.currentMessages,
+      promptPrefix,
+    });
+
+    if (this.options.debug) {
+      console.debug('buildCompletionPrompt Payload');
+      console.debug(payload);
+    }
+    responseMessage.text = await this.sendCompletion(payload, opts);
+    return await this.handleResponseMessage(responseMessage, saveOptions, user);
+  }
+
+  async buildCompletionPrompt({ messages, promptPrefix: _promptPrefix }) {
+    if (this.options.debug) {
+      console.debug('buildCompletionPrompt messages', messages);
+    }
+
+    const orderedMessages = messages;
+    let 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${promptPrefix}`;
+    const promptSuffix = `${this.startToken}${this.chatGptLabel ?? 'Assistant'}:\n`;
+
+    const instructionsPayload = {
+      role: 'system',
+      name: 'instructions',
+      content: promptPrefix,
+    };
+
+    const messagePayload = {
+      role: 'system',
+      content: promptSuffix,
+    };
+
+    if (this.isGpt3) {
+      instructionsPayload.role = 'user';
+      messagePayload.role = 'user';
+      instructionsPayload.content += `\n${promptSuffix}`;
+    }
+
+    // testing if this works with browser endpoint
+    if (!this.isGpt3 && this.options.reverseProxyUrl) {
+      instructionsPayload.role = 'user';
+    }
+
+    let currentTokenCount =
+      this.getTokenCountForMessage(instructionsPayload) +
+      this.getTokenCountForMessage(messagePayload);
+
+    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 isCreatedByUser = message.isCreatedByUser || message.role?.toLowerCase() === 'user';
+        const roleLabel = isCreatedByUser ? this.userLabel : this.chatGptLabel;
+        let messageString = `${this.startToken}${roleLabel}:\n${message.text}${this.endToken}\n`;
+        let newPromptBody = `${messageString}${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 ${newTokenCount} tokens long.`,
+          );
+        }
+        promptBody = newPromptBody;
+        currentTokenCount = newTokenCount;
+        // wait for next tick to avoid blocking the event loop
+        await new Promise((resolve) => setTimeout(resolve, 0));
+        return buildPromptBody();
+      }
+      return true;
+    };
+
+    await buildPromptBody();
+    const prompt = promptBody;
+    messagePayload.content = prompt;
+    // Add 2 tokens for metadata after all messages have been counted.
+    currentTokenCount += 2;
+
+    if (this.isGpt3 && messagePayload.content.length > 0) {
+      const context = 'Chat History:\n';
+      messagePayload.content = `${context}${prompt}`;
+      currentTokenCount += this.getTokenCount(context);
+    }
+
+    // Use up to `this.maxContextTokens` tokens (prompt + response), but try to leave `this.maxTokens` tokens for the response.
+    this.modelOptions.max_tokens = Math.min(
+      this.maxContextTokens - currentTokenCount,
+      this.maxResponseTokens,
+    );
+
+    if (this.isGpt3) {
+      messagePayload.content += promptSuffix;
+      return [instructionsPayload, messagePayload];
+    }
+
+    const result = [messagePayload, instructionsPayload];
+
+    if (this.functionsAgent && !this.isGpt3) {
+      result[1].content = `${result[1].content}\n${this.startToken}${this.chatGptLabel}:\nSure thing! Here is the output you requested:\n`;
+    }
+
+    return result.filter((message) => message.content.length > 0);
+  }
+}
+
+module.exports = PluginsClient;

api/app/clients/TextStream.js

@@ -16,10 +16,7 @@ class TextStream extends Readable {
     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 chunkSize = Math.min(this.randomInt(minChunkSize, maxChunkSize + 1), remainingChars);
 
         const chunk = this.text.slice(this.currentIndex, this.currentIndex + chunkSize);
         this.push(chunk);

api/app/clients/agents/CustomAgent/CustomAgent.js

@@ -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;

api/app/clients/agents/CustomAgent/initializeCustomAgent.js

@@ -0,0 +1,54 @@
+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;

api/app/clients/agents/CustomAgent/instructions.js

@@ -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.`,
+  },
+};

api/app/clients/agents/CustomAgent/outputParser.js

@@ -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 };

api/app/clients/agents/Functions/FunctionsAgent.js

@@ -0,0 +1,120 @@
+const { Agent } = require('langchain/agents');
+const { LLMChain } = require('langchain/chains');
+const { FunctionChatMessage, AIChatMessage } = require('langchain/schema');
+const {
+  ChatPromptTemplate,
+  MessagesPlaceholder,
+  SystemMessagePromptTemplate,
+  HumanMessagePromptTemplate,
+} = require('langchain/prompts');
+const PREFIX = 'You are a helpful AI assistant.';
+
+function parseOutput(message) {
+  if (message.additional_kwargs.function_call) {
+    const function_call = message.additional_kwargs.function_call;
+    return {
+      tool: function_call.name,
+      toolInput: function_call.arguments ? JSON.parse(function_call.arguments) : {},
+      log: message.text,
+    };
+  } else {
+    return { returnValues: { output: message.text }, log: message.text };
+  }
+}
+
+class FunctionsAgent extends Agent {
+  constructor(input) {
+    super({ ...input, outputParser: undefined });
+    this.tools = input.tools;
+  }
+
+  lc_namespace = ['langchain', 'agents', 'openai'];
+
+  _agentType() {
+    return 'openai-functions';
+  }
+
+  observationPrefix() {
+    return 'Observation: ';
+  }
+
+  llmPrefix() {
+    return 'Thought:';
+  }
+
+  _stop() {
+    return ['Observation:'];
+  }
+
+  static createPrompt(_tools, fields) {
+    const { prefix = PREFIX, currentDateString } = fields || {};
+
+    return ChatPromptTemplate.fromPromptMessages([
+      SystemMessagePromptTemplate.fromTemplate(`Date: ${currentDateString}\n${prefix}`),
+      new MessagesPlaceholder('chat_history'),
+      HumanMessagePromptTemplate.fromTemplate('Query: {input}'),
+      new MessagesPlaceholder('agent_scratchpad'),
+    ]);
+  }
+
+  static fromLLMAndTools(llm, tools, args) {
+    FunctionsAgent.validateTools(tools);
+    const prompt = FunctionsAgent.createPrompt(tools, args);
+    const chain = new LLMChain({
+      prompt,
+      llm,
+      callbacks: args?.callbacks,
+    });
+    return new FunctionsAgent({
+      llmChain: chain,
+      allowedTools: tools.map((t) => t.name),
+      tools,
+    });
+  }
+
+  async constructScratchPad(steps) {
+    return steps.flatMap(({ action, observation }) => [
+      new AIChatMessage('', {
+        function_call: {
+          name: action.tool,
+          arguments: JSON.stringify(action.toolInput),
+        },
+      }),
+      new FunctionChatMessage(observation, action.tool),
+    ]);
+  }
+
+  async plan(steps, inputs, callbackManager) {
+    // Add scratchpad and stop to inputs
+    const thoughts = await this.constructScratchPad(steps);
+    const newInputs = Object.assign({}, inputs, { agent_scratchpad: thoughts });
+    if (this._stop().length !== 0) {
+      newInputs.stop = this._stop();
+    }
+
+    // Split inputs between prompt and llm
+    const llm = this.llmChain.llm;
+    const valuesForPrompt = Object.assign({}, newInputs);
+    const valuesForLLM = {
+      tools: this.tools,
+    };
+    for (let i = 0; i < this.llmChain.llm.callKeys.length; i++) {
+      const key = this.llmChain.llm.callKeys[i];
+      if (key in inputs) {
+        valuesForLLM[key] = inputs[key];
+        delete valuesForPrompt[key];
+      }
+    }
+
+    const promptValue = await this.llmChain.prompt.formatPromptValue(valuesForPrompt);
+    const message = await llm.predictMessages(
+      promptValue.toChatMessages(),
+      valuesForLLM,
+      callbackManager,
+    );
+    console.log('message', message);
+    return parseOutput(message);
+  }
+}
+
+module.exports = FunctionsAgent;

api/app/clients/agents/Functions/initializeFunctionsAgent.js

@@ -0,0 +1,28 @@
+const { initializeAgentExecutorWithOptions } = require('langchain/agents');
+const { BufferMemory, ChatMessageHistory } = require('langchain/memory');
+
+const initializeFunctionsAgent = async ({
+  tools,
+  model,
+  pastMessages,
+  // currentDateString,
+  ...rest
+}) => {
+  const memory = new BufferMemory({
+    chatHistory: new ChatMessageHistory(pastMessages),
+    memoryKey: 'chat_history',
+    humanPrefix: 'User',
+    aiPrefix: 'Assistant',
+    inputKey: 'input',
+    outputKey: 'output',
+    returnMessages: true,
+  });
+
+  return await initializeAgentExecutorWithOptions(tools, model, {
+    agentType: 'openai-functions',
+    memory,
+    ...rest,
+  });
+};
+
+module.exports = initializeFunctionsAgent;

api/app/clients/agents/index.js

@@ -0,0 +1,7 @@
+const initializeCustomAgent = require('./CustomAgent/initializeCustomAgent');
+const initializeFunctionsAgent = require('./Functions/initializeFunctionsAgent');
+
+module.exports = {
+  initializeCustomAgent,
+  initializeFunctionsAgent,
+};

api/app/clients/chatgpt-client.js

@@ -1,67 +0,0 @@
-require('dotenv').config();
-const { KeyvFile } = require('keyv-file');
-const { genAzureEndpoint } = require('../../utils/genAzureEndpoints');
-
-const askClient = async ({
-  text,
-  parentMessageId,
-  conversationId,
-  model,
-  chatGptLabel,
-  promptPrefix,
-  temperature,
-  top_p,
-  presence_penalty,
-  frequency_penalty,
-  onProgress,
-  abortController,
-  userId
-}) => {
-  const { ChatGPTClient } = await import('@waylaidwanderer/chatgpt-api');
-  const store = {
-    store: new KeyvFile({ filename: './data/cache.json' })
-  };
-
-  const azure = process.env.AZURE_OPENAI_API_KEY ? true : false;
-  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,
-    azure,
-    maxContextTokens,
-    modelOptions: {
-      model,
-      temperature,
-      top_p,
-      presence_penalty,
-      frequency_penalty
-    },
-    chatGptLabel,
-    promptPrefix,
-    proxy: process.env.PROXY || null,
-    // debug: true
-  };
-
-  let apiKey = process.env.OPENAI_KEY;
-
-  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,
-      azureOpenAIApiVersion: process.env.AZURE_OPENAI_API_VERSION
-    });
-  }
-
-  const client = new ChatGPTClient(apiKey, clientOptions, store);
-
-  const options = {
-    onProgress,
-    abortController,
-    ...(parentMessageId && conversationId ? { parentMessageId, conversationId } : {})
-  };
-
-  const res = await client.sendMessage(text, { ...options, userId });
-  return res;
-};
-
-module.exports = { askClient };

api/app/clients/index.js

@@ -0,0 +1,17 @@
+const ChatGPTClient = require('./ChatGPTClient');
+const OpenAIClient = require('./OpenAIClient');
+const PluginsClient = require('./PluginsClient');
+const GoogleClient = require('./GoogleClient');
+const TextStream = require('./TextStream');
+const AnthropicClient = require('./AnthropicClient');
+const toolUtils = require('./tools/util');
+
+module.exports = {
+  ChatGPTClient,
+  OpenAIClient,
+  PluginsClient,
+  GoogleClient,
+  TextStream,
+  AnthropicClient,
+  ...toolUtils,
+};

api/app/clients/prompts/instructions.js

@@ -0,0 +1,10 @@
+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: ![alt-text](URL)',
+  completionInstructions:
+    'Instructions:\nYou are ChatGPT, a large language model trained by OpenAI. Respond conversationally.\nCurrent date:',
+};

api/app/clients/prompts/refinePrompt.js

@@ -0,0 +1,24 @@
+const { PromptTemplate } = require('langchain/prompts');
+
+const refinePromptTemplate = `Your job is to produce a final summary of the following conversation.
+We have provided an existing summary up to a certain point: "{existing_answer}"
+We have the opportunity to refine the existing summary
+(only if needed) with some more context below.
+------------
+"{text}"
+------------
+
+Given the new context, refine the original summary of the conversation.
+Do note who is speaking in the conversation to give proper context.
+If the context isn't useful, return the original summary.
+
+REFINED CONVERSATION SUMMARY:`;
+
+const refinePrompt = new PromptTemplate({
+  template: refinePromptTemplate,
+  inputVariables: ['existing_answer', 'text'],
+});
+
+module.exports = {
+  refinePrompt,
+};

api/app/clients/specs/BaseClient.test.js

@@ -0,0 +1,369 @@
+const { initializeFakeClient } = require('./FakeClient');
+
+jest.mock('../../../lib/db/connectDb');
+jest.mock('../../../models', () => {
+  return function () {
+    return {
+      save: jest.fn(),
+      deleteConvos: jest.fn(),
+      getConvo: jest.fn(),
+      getMessages: jest.fn(),
+      saveMessage: jest.fn(),
+      updateMessage: jest.fn(),
+      saveConvo: jest.fn(),
+    };
+  };
+});
+
+jest.mock('langchain/text_splitter', () => {
+  return {
+    RecursiveCharacterTextSplitter: jest.fn().mockImplementation(() => {
+      return { createDocuments: jest.fn().mockResolvedValue([]) };
+    }),
+  };
+});
+
+jest.mock('langchain/chat_models/openai', () => {
+  return {
+    ChatOpenAI: jest.fn().mockImplementation(() => {
+      return {};
+    }),
+  };
+});
+
+jest.mock('langchain/chains', () => {
+  return {
+    loadSummarizationChain: jest.fn().mockReturnValue({
+      call: jest.fn().mockResolvedValue({ output_text: 'Refined answer' }),
+    }),
+  };
+});
+
+let parentMessageId;
+let conversationId;
+const fakeMessages = [];
+const userMessage = 'Hello, ChatGPT!';
+const apiKey = 'fake-api-key';
+
+describe('BaseClient', () => {
+  let TestClient;
+  const options = {
+    // debug: true,
+    modelOptions: {
+      model: 'gpt-3.5-turbo',
+      temperature: 0,
+    },
+  };
+
+  beforeEach(() => {
+    TestClient = initializeFakeClient(apiKey, options, fakeMessages);
+  });
+
+  test('returns the input messages without instructions when addInstructions() is called with empty instructions', () => {
+    const messages = [{ content: 'Hello' }, { content: 'How are you?' }, { content: 'Goodbye' }];
+    const instructions = '';
+    const result = TestClient.addInstructions(messages, instructions);
+    expect(result).toEqual(messages);
+  });
+
+  test('returns the input messages with instructions properly added when addInstructions() is called with non-empty instructions', () => {
+    const messages = [{ content: 'Hello' }, { content: 'How are you?' }, { content: 'Goodbye' }];
+    const instructions = { content: 'Please respond to the question.' };
+    const result = TestClient.addInstructions(messages, instructions);
+    const expected = [
+      { content: 'Hello' },
+      { content: 'How are you?' },
+      { content: 'Please respond to the question.' },
+      { content: 'Goodbye' },
+    ];
+    expect(result).toEqual(expected);
+  });
+
+  test('concats messages correctly in concatenateMessages()', () => {
+    const messages = [
+      { name: 'User', content: 'Hello' },
+      { name: 'Assistant', content: 'How can I help you?' },
+      { name: 'User', content: 'I have a question.' },
+    ];
+    const result = TestClient.concatenateMessages(messages);
+    const expected =
+      'User:\nHello\n\nAssistant:\nHow can I help you?\n\nUser:\nI have a question.\n\n';
+    expect(result).toBe(expected);
+  });
+
+  test('refines messages correctly in refineMessages()', async () => {
+    const messagesToRefine = [
+      { role: 'user', content: 'Hello', tokenCount: 10 },
+      { role: 'assistant', content: 'How can I help you?', tokenCount: 20 },
+    ];
+    const remainingContextTokens = 100;
+    const expectedRefinedMessage = {
+      role: 'assistant',
+      content: 'Refined answer',
+      tokenCount: 14, // 'Refined answer'.length
+    };
+
+    const result = await TestClient.refineMessages(messagesToRefine, remainingContextTokens);
+    expect(result).toEqual(expectedRefinedMessage);
+  });
+
+  test('gets messages within token limit (under limit) correctly in getMessagesWithinTokenLimit()', async () => {
+    TestClient.maxContextTokens = 100;
+    TestClient.shouldRefineContext = true;
+    TestClient.refineMessages = jest.fn().mockResolvedValue({
+      role: 'assistant',
+      content: 'Refined answer',
+      tokenCount: 30,
+    });
+
+    const messages = [
+      { role: 'user', content: 'Hello', tokenCount: 5 },
+      { role: 'assistant', content: 'How can I help you?', tokenCount: 19 },
+      { role: 'user', content: 'I have a question.', tokenCount: 18 },
+    ];
+    const expectedContext = [
+      { role: 'user', content: 'Hello', tokenCount: 5 }, // 'Hello'.length
+      { role: 'assistant', content: 'How can I help you?', tokenCount: 19 },
+      { role: 'user', content: 'I have a question.', tokenCount: 18 },
+    ];
+    const expectedRemainingContextTokens = 58; // 100 - 5 - 19 - 18
+    const expectedMessagesToRefine = [];
+
+    const result = await TestClient.getMessagesWithinTokenLimit(messages);
+    expect(result.context).toEqual(expectedContext);
+    expect(result.remainingContextTokens).toBe(expectedRemainingContextTokens);
+    expect(result.messagesToRefine).toEqual(expectedMessagesToRefine);
+  });
+
+  test('gets messages within token limit (over limit) correctly in getMessagesWithinTokenLimit()', async () => {
+    TestClient.maxContextTokens = 50; // Set a lower limit
+    TestClient.shouldRefineContext = true;
+    TestClient.refineMessages = jest.fn().mockResolvedValue({
+      role: 'assistant',
+      content: 'Refined answer',
+      tokenCount: 4,
+    });
+
+    const messages = [
+      { role: 'user', content: 'I need a coffee, stat!', tokenCount: 30 },
+      { role: 'assistant', content: 'Sure, I can help with that.', tokenCount: 30 },
+      { role: 'user', content: 'Hello', tokenCount: 5 },
+      { role: 'assistant', content: 'How can I help you?', tokenCount: 19 },
+      { role: 'user', content: 'I have a question.', tokenCount: 18 },
+    ];
+    const expectedContext = [
+      { role: 'user', content: 'Hello', tokenCount: 5 },
+      { role: 'assistant', content: 'How can I help you?', tokenCount: 19 },
+      { role: 'user', content: 'I have a question.', tokenCount: 18 },
+    ];
+    const expectedRemainingContextTokens = 8; // 50 - 18 - 19 - 5
+    const expectedMessagesToRefine = [
+      { role: 'user', content: 'I need a coffee, stat!', tokenCount: 30 },
+      { role: 'assistant', content: 'Sure, I can help with that.', tokenCount: 30 },
+    ];
+
+    const result = await TestClient.getMessagesWithinTokenLimit(messages);
+    expect(result.context).toEqual(expectedContext);
+    expect(result.remainingContextTokens).toBe(expectedRemainingContextTokens);
+    expect(result.messagesToRefine).toEqual(expectedMessagesToRefine);
+  });
+
+  test('handles context strategy correctly in handleContextStrategy()', async () => {
+    TestClient.addInstructions = jest
+      .fn()
+      .mockReturnValue([
+        { content: 'Hello' },
+        { content: 'How can I help you?' },
+        { content: 'Please provide more details.' },
+        { content: 'I can assist you with that.' },
+      ]);
+    TestClient.getMessagesWithinTokenLimit = jest.fn().mockReturnValue({
+      context: [
+        { content: 'How can I help you?' },
+        { content: 'Please provide more details.' },
+        { content: 'I can assist you with that.' },
+      ],
+      remainingContextTokens: 80,
+      messagesToRefine: [{ content: 'Hello' }],
+      refineIndex: 3,
+    });
+    TestClient.refineMessages = jest.fn().mockResolvedValue({
+      role: 'assistant',
+      content: 'Refined answer',
+      tokenCount: 30,
+    });
+    TestClient.getTokenCountForResponse = jest.fn().mockReturnValue(40);
+
+    const instructions = { content: 'Please provide more details.' };
+    const orderedMessages = [
+      { content: 'Hello' },
+      { content: 'How can I help you?' },
+      { content: 'Please provide more details.' },
+      { content: 'I can assist you with that.' },
+    ];
+    const formattedMessages = [
+      { content: 'Hello' },
+      { content: 'How can I help you?' },
+      { content: 'Please provide more details.' },
+      { content: 'I can assist you with that.' },
+    ];
+    const expectedResult = {
+      payload: [
+        {
+          content: 'Refined answer',
+          role: 'assistant',
+          tokenCount: 30,
+        },
+        { content: 'How can I help you?' },
+        { content: 'Please provide more details.' },
+        { content: 'I can assist you with that.' },
+      ],
+      promptTokens: expect.any(Number),
+      tokenCountMap: {},
+      messages: expect.any(Array),
+    };
+
+    const result = await TestClient.handleContextStrategy({
+      instructions,
+      orderedMessages,
+      formattedMessages,
+    });
+    expect(result).toEqual(expectedResult);
+  });
+
+  describe('sendMessage', () => {
+    test('sendMessage should return a response message', async () => {
+      const expectedResult = expect.objectContaining({
+        sender: TestClient.sender,
+        text: expect.any(String),
+        isCreatedByUser: false,
+        messageId: expect.any(String),
+        parentMessageId: expect.any(String),
+        conversationId: expect.any(String),
+      });
+
+      const response = await TestClient.sendMessage(userMessage);
+      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,
+        getIds: jest.fn(),
+        onStart: jest.fn(),
+      };
+
+      const expectedResult = expect.objectContaining({
+        sender: TestClient.sender,
+        text: expect.any(String),
+        isCreatedByUser: false,
+        messageId: expect.any(String),
+        parentMessageId: expect.any(String),
+        conversationId: opts.conversationId,
+      });
+
+      const response = await TestClient.sendMessage(userMessage, opts);
+      parentMessageId = response.messageId;
+      expect(response.conversationId).toEqual(conversationId);
+      expect(response).toEqual(expectedResult);
+      expect(opts.getIds).toHaveBeenCalled();
+      expect(opts.onStart).toHaveBeenCalled();
+      expect(TestClient.getBuildMessagesOptions).toHaveBeenCalled();
+      expect(TestClient.getSaveOptions).toHaveBeenCalled();
+    });
+
+    test('should return chat history', async () => {
+      const chatMessages = await TestClient.loadHistory(conversationId, parentMessageId);
+      expect(TestClient.currentMessages).toHaveLength(4);
+      expect(chatMessages[0].text).toEqual(userMessage);
+    });
+
+    test('setOptions is called with the correct arguments', async () => {
+      TestClient.setOptions = jest.fn();
+      const opts = { conversationId: '123', parentMessageId: '456' };
+      await TestClient.sendMessage('Hello, world!', opts);
+      expect(TestClient.setOptions).toHaveBeenCalledWith(opts);
+      TestClient.setOptions.mockClear();
+    });
+
+    test('loadHistory is called with the correct arguments', async () => {
+      const opts = { conversationId: '123', parentMessageId: '456' };
+      await TestClient.sendMessage('Hello, world!', opts);
+      expect(TestClient.loadHistory).toHaveBeenCalledWith(
+        opts.conversationId,
+        opts.parentMessageId,
+      );
+    });
+
+    test('getIds is called with the correct arguments', async () => {
+      const getIds = jest.fn();
+      const opts = { getIds };
+      const response = await TestClient.sendMessage('Hello, world!', opts);
+      expect(getIds).toHaveBeenCalledWith({
+        userMessage: expect.objectContaining({ text: 'Hello, world!' }),
+        conversationId: response.conversationId,
+        responseMessageId: response.messageId,
+      });
+    });
+
+    test('onStart is called with the correct arguments', async () => {
+      const onStart = jest.fn();
+      const opts = { onStart };
+      await TestClient.sendMessage('Hello, world!', opts);
+      expect(onStart).toHaveBeenCalledWith(expect.objectContaining({ text: 'Hello, world!' }));
+    });
+
+    test('saveMessageToDatabase is called with the correct arguments', async () => {
+      const saveOptions = TestClient.getSaveOptions();
+      const user = {}; // Mock user
+      const opts = { user };
+      await TestClient.sendMessage('Hello, world!', opts);
+      expect(TestClient.saveMessageToDatabase).toHaveBeenCalledWith(
+        expect.objectContaining({
+          sender: expect.any(String),
+          text: expect.any(String),
+          isCreatedByUser: expect.any(Boolean),
+          messageId: expect.any(String),
+          parentMessageId: expect.any(String),
+          conversationId: expect.any(String),
+        }),
+        saveOptions,
+        user,
+      );
+    });
+
+    test('sendCompletion is called with the correct arguments', async () => {
+      const payload = {}; // Mock payload
+      TestClient.buildMessages.mockReturnValue({ prompt: payload, tokenCountMap: null });
+      const opts = {};
+      await TestClient.sendMessage('Hello, world!', opts);
+      expect(TestClient.sendCompletion).toHaveBeenCalledWith(payload, opts);
+    });
+
+    test('getTokenCountForResponse is called with the correct arguments', async () => {
+      const tokenCountMap = {}; // Mock tokenCountMap
+      TestClient.buildMessages.mockReturnValue({ prompt: [], tokenCountMap });
+      TestClient.getTokenCountForResponse = jest.fn();
+      const response = await TestClient.sendMessage('Hello, world!', {});
+      expect(TestClient.getTokenCountForResponse).toHaveBeenCalledWith(response);
+    });
+
+    test('returns an object with the correct shape', async () => {
+      const response = await TestClient.sendMessage('Hello, world!', {});
+      expect(response).toEqual(
+        expect.objectContaining({
+          sender: expect.any(String),
+          text: expect.any(String),
+          isCreatedByUser: expect.any(Boolean),
+          messageId: expect.any(String),
+          parentMessageId: expect.any(String),
+          conversationId: expect.any(String),
+        }),
+      );
+    });
+  });
+});

api/app/clients/specs/FakeClient.js

@@ -0,0 +1,193 @@
+const crypto = require('crypto');
+const BaseClient = require('../BaseClient');
+const { maxTokensMap } = require('../../../utils');
+
+class FakeClient extends BaseClient {
+  constructor(apiKey, options = {}) {
+    super(apiKey, options);
+    this.sender = 'AI Assistant';
+    this.setOptions(options);
+  }
+  setOptions(options) {
+    if (this.options && !this.options.replaceOptions) {
+      this.options.modelOptions = {
+        ...this.options.modelOptions,
+        ...options.modelOptions,
+      };
+      delete options.modelOptions;
+      this.options = {
+        ...this.options,
+        ...options,
+      };
+    } else {
+      this.options = options;
+    }
+
+    if (this.options.openaiApiKey) {
+      this.apiKey = this.options.openaiApiKey;
+    }
+
+    const modelOptions = this.options.modelOptions || {};
+    if (!this.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' ? 1 : modelOptions.presence_penalty,
+        stop: modelOptions.stop,
+      };
+    }
+
+    this.maxContextTokens = maxTokensMap[this.modelOptions.model] ?? 4097;
+  }
+  getCompletion() {}
+  buildMessages() {}
+  getTokenCount(str) {
+    return str.length;
+  }
+  getTokenCountForMessage(message) {
+    return message?.content?.length || message.length;
+  }
+}
+
+const initializeFakeClient = (apiKey, options, fakeMessages) => {
+  let TestClient = new FakeClient(apiKey);
+  TestClient.options = options;
+  TestClient.abortController = { abort: jest.fn() };
+  TestClient.saveMessageToDatabase = jest.fn();
+  TestClient.loadHistory = jest
+    .fn()
+    .mockImplementation((conversationId, parentMessageId = null) => {
+      if (!conversationId) {
+        TestClient.currentMessages = [];
+        return Promise.resolve([]);
+      }
+
+      const orderedMessages = TestClient.constructor.getMessagesForConversation(
+        fakeMessages,
+        parentMessageId,
+      );
+
+      TestClient.currentMessages = orderedMessages;
+      return Promise.resolve(orderedMessages);
+    });
+
+  TestClient.getSaveOptions = jest.fn().mockImplementation(() => {
+    return {};
+  });
+
+  TestClient.getBuildMessagesOptions = jest.fn().mockImplementation(() => {
+    return {};
+  });
+
+  TestClient.sendCompletion = jest.fn(async () => {
+    return 'Mock response text';
+  });
+
+  TestClient.sendMessage = jest.fn().mockImplementation(async (message, opts = {}) => {
+    if (opts && typeof opts === 'object') {
+      TestClient.setOptions(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 saveOptions = TestClient.getSaveOptions();
+
+    this.pastMessages = await TestClient.loadHistory(
+      conversationId,
+      TestClient.options?.parentMessageId,
+    );
+
+    const userMessage = {
+      text: message,
+      sender: TestClient.sender,
+      isCreatedByUser: true,
+      messageId: userMessageId,
+      parentMessageId,
+      conversationId,
+    };
+
+    const response = {
+      sender: TestClient.sender,
+      text: 'Hello, User!',
+      isCreatedByUser: false,
+      messageId: crypto.randomUUID(),
+      parentMessageId: userMessage.messageId,
+      conversationId,
+    };
+
+    fakeMessages.push(userMessage);
+    fakeMessages.push(response);
+
+    if (typeof opts.getIds === 'function') {
+      opts.getIds({
+        userMessage,
+        conversationId,
+        responseMessageId: response.messageId,
+      });
+    }
+
+    if (typeof opts.onStart === 'function') {
+      opts.onStart(userMessage);
+    }
+
+    let { prompt: payload, tokenCountMap } = await TestClient.buildMessages(
+      this.currentMessages,
+      userMessage.messageId,
+      TestClient.getBuildMessagesOptions(opts),
+    );
+
+    if (tokenCountMap) {
+      payload = payload.map((message, i) => {
+        const { tokenCount, ...messageWithoutTokenCount } = message;
+        // userMessage is always the last one in the payload
+        if (i === payload.length - 1) {
+          userMessage.tokenCount = message.tokenCount;
+          console.debug(
+            `Token count for user message: ${tokenCount}`,
+            `Instruction Tokens: ${tokenCountMap.instructions || 'N/A'}`,
+          );
+        }
+        return messageWithoutTokenCount;
+      });
+      TestClient.handleTokenCountMap(tokenCountMap);
+    }
+
+    await TestClient.saveMessageToDatabase(userMessage, saveOptions, user);
+    response.text = await TestClient.sendCompletion(payload, opts);
+    if (tokenCountMap && TestClient.getTokenCountForResponse) {
+      response.tokenCount = TestClient.getTokenCountForResponse(response);
+    }
+    await TestClient.saveMessageToDatabase(response, saveOptions, user);
+    return response;
+  });
+
+  TestClient.buildMessages = jest.fn(async (messages, parentMessageId) => {
+    const orderedMessages = TestClient.constructor.getMessagesForConversation(
+      messages,
+      parentMessageId,
+    );
+    const formattedMessages = orderedMessages.map((message) => {
+      let { role: _role, sender, text } = message;
+      const role = _role ?? sender;
+      const content = text ?? '';
+      return {
+        role: role?.toLowerCase() === 'user' ? 'user' : 'assistant',
+        content,
+      };
+    });
+    return {
+      prompt: formattedMessages,
+      tokenCountMap: null, // Simplified for the mock
+    };
+  });
+
+  return TestClient;
+};
+
+module.exports = { FakeClient, initializeFakeClient };

api/app/clients/specs/OpenAIClient.test.js

@@ -0,0 +1,211 @@
+const OpenAIClient = require('../OpenAIClient');
+
+describe('OpenAIClient', () => {
+  let client, client2;
+  const model = 'gpt-4';
+  const parentMessageId = '1';
+  const messages = [
+    { role: 'user', sender: 'User', text: 'Hello', messageId: parentMessageId },
+    { role: 'assistant', sender: 'Assistant', text: 'Hi', messageId: '2' },
+  ];
+
+  beforeEach(() => {
+    const options = {
+      // debug: true,
+      openaiApiKey: 'new-api-key',
+      modelOptions: {
+        model,
+        temperature: 0.7,
+      },
+    };
+    client = new OpenAIClient('test-api-key', options);
+    client2 = new OpenAIClient('test-api-key', options);
+    client.refineMessages = jest.fn().mockResolvedValue({
+      role: 'assistant',
+      content: 'Refined answer',
+      tokenCount: 30,
+    });
+    client.constructor.freeAndResetAllEncoders();
+  });
+
+  describe('setOptions', () => {
+    it('should set the options correctly', () => {
+      expect(client.apiKey).toBe('new-api-key');
+      expect(client.modelOptions.model).toBe(model);
+      expect(client.modelOptions.temperature).toBe(0.7);
+    });
+  });
+
+  describe('selectTokenizer', () => {
+    it('should get the correct tokenizer based on the instance state', () => {
+      const tokenizer = client.selectTokenizer();
+      expect(tokenizer).toBeDefined();
+    });
+  });
+
+  describe('freeAllTokenizers', () => {
+    it('should free all tokenizers', () => {
+      // Create a tokenizer
+      const tokenizer = client.selectTokenizer();
+
+      // Mock 'free' method on the tokenizer
+      tokenizer.free = jest.fn();
+
+      client.constructor.freeAndResetAllEncoders();
+
+      // Check if 'free' method has been called on the tokenizer
+      expect(tokenizer.free).toHaveBeenCalled();
+    });
+  });
+
+  describe('getTokenCount', () => {
+    it('should return the correct token count', () => {
+      const count = client.getTokenCount('Hello, world!');
+      expect(count).toBeGreaterThan(0);
+    });
+
+    it('should reset the encoder and count when count reaches 25', () => {
+      const freeAndResetEncoderSpy = jest.spyOn(client.constructor, 'freeAndResetAllEncoders');
+
+      // Call getTokenCount 25 times
+      for (let i = 0; i < 25; i++) {
+        client.getTokenCount('test text');
+      }
+
+      expect(freeAndResetEncoderSpy).toHaveBeenCalled();
+    });
+
+    it('should not reset the encoder and count when count is less than 25', () => {
+      const freeAndResetEncoderSpy = jest.spyOn(client.constructor, 'freeAndResetAllEncoders');
+      freeAndResetEncoderSpy.mockClear();
+
+      // Call getTokenCount 24 times
+      for (let i = 0; i < 24; i++) {
+        client.getTokenCount('test text');
+      }
+
+      expect(freeAndResetEncoderSpy).not.toHaveBeenCalled();
+    });
+
+    it('should handle errors and reset the encoder', () => {
+      const freeAndResetEncoderSpy = jest.spyOn(client.constructor, 'freeAndResetAllEncoders');
+
+      // Mock encode function to throw an error
+      client.selectTokenizer().encode = jest.fn().mockImplementation(() => {
+        throw new Error('Test error');
+      });
+
+      client.getTokenCount('test text');
+
+      expect(freeAndResetEncoderSpy).toHaveBeenCalled();
+    });
+
+    it('should not throw null pointer error when freeing the same encoder twice', () => {
+      client.constructor.freeAndResetAllEncoders();
+      client2.constructor.freeAndResetAllEncoders();
+
+      const count = client2.getTokenCount('test text');
+      expect(count).toBeGreaterThan(0);
+    });
+  });
+
+  describe('getSaveOptions', () => {
+    it('should return the correct save options', () => {
+      const options = client.getSaveOptions();
+      expect(options).toHaveProperty('chatGptLabel');
+      expect(options).toHaveProperty('promptPrefix');
+    });
+  });
+
+  describe('getBuildMessagesOptions', () => {
+    it('should return the correct build messages options', () => {
+      const options = client.getBuildMessagesOptions({ promptPrefix: 'Hello' });
+      expect(options).toHaveProperty('isChatCompletion');
+      expect(options).toHaveProperty('promptPrefix');
+      expect(options.promptPrefix).toBe('Hello');
+    });
+  });
+
+  describe('buildMessages', () => {
+    it('should build messages correctly for chat completion', async () => {
+      const result = await client.buildMessages(messages, parentMessageId, {
+        isChatCompletion: true,
+      });
+      expect(result).toHaveProperty('prompt');
+    });
+
+    it('should build messages correctly for non-chat completion', async () => {
+      const result = await client.buildMessages(messages, parentMessageId, {
+        isChatCompletion: false,
+      });
+      expect(result).toHaveProperty('prompt');
+    });
+
+    it('should build messages correctly with a promptPrefix', async () => {
+      const result = await client.buildMessages(messages, parentMessageId, {
+        isChatCompletion: true,
+        promptPrefix: 'Test Prefix',
+      });
+      expect(result).toHaveProperty('prompt');
+      const instructions = result.prompt.find((item) => item.name === 'instructions');
+      expect(instructions).toBeDefined();
+      expect(instructions.content).toContain('Test Prefix');
+    });
+
+    it('should handle context strategy correctly', async () => {
+      client.contextStrategy = 'refine';
+      const result = await client.buildMessages(messages, parentMessageId, {
+        isChatCompletion: true,
+      });
+      expect(result).toHaveProperty('prompt');
+      expect(result).toHaveProperty('tokenCountMap');
+    });
+
+    it('should assign name property for user messages when options.name is set', async () => {
+      client.options.name = 'Test User';
+      const result = await client.buildMessages(messages, parentMessageId, {
+        isChatCompletion: true,
+      });
+      const hasUserWithName = result.prompt.some(
+        (item) => item.role === 'user' && item.name === 'Test User',
+      );
+      expect(hasUserWithName).toBe(true);
+    });
+
+    it('should calculate tokenCount for each message when contextStrategy is set', async () => {
+      client.contextStrategy = 'refine';
+      const result = await client.buildMessages(messages, parentMessageId, {
+        isChatCompletion: true,
+      });
+      const hasUserWithTokenCount = result.prompt.some(
+        (item) => item.role === 'user' && item.tokenCount > 0,
+      );
+      expect(hasUserWithTokenCount).toBe(true);
+    });
+
+    it('should handle promptPrefix from options when promptPrefix argument is not provided', async () => {
+      client.options.promptPrefix = 'Test Prefix from options';
+      const result = await client.buildMessages(messages, parentMessageId, {
+        isChatCompletion: true,
+      });
+      const instructions = result.prompt.find((item) => item.name === 'instructions');
+      expect(instructions.content).toContain('Test Prefix from options');
+    });
+
+    it('should handle case when neither promptPrefix argument nor options.promptPrefix is set', async () => {
+      const result = await client.buildMessages(messages, parentMessageId, {
+        isChatCompletion: true,
+      });
+      const instructions = result.prompt.find((item) => item.name === 'instructions');
+      expect(instructions).toBeUndefined();
+    });
+
+    it('should handle case when getMessagesForConversation returns null or an empty array', async () => {
+      const messages = [];
+      const result = await client.buildMessages(messages, parentMessageId, {
+        isChatCompletion: true,
+      });
+      expect(result.prompt).toEqual([]);
+    });
+  });
+});

api/app/clients/specs/OpenAIClient.tokens.js

@@ -0,0 +1,125 @@
+/*
+  This is a test script to see how much memory is used by the client when encoding.
+  On my work machine, it was able to process 10,000 encoding requests / 48.686 seconds = approximately 205.4 RPS
+  I've significantly reduced the amount of encoding needed by saving token counts in the database, so these
+  numbers should only be hit with a large amount of concurrent users
+  It would take 103 concurrent users sending 1 message every 1 second to hit these numbers, which is rather unrealistic,
+  and at that point, out-sourcing the encoding to a separate server would be a better solution
+  Also, for scaling, could increase the rate at which the encoder resets; the trade-off is more resource usage on the server.
+  Initial memory usage: 25.93 megabytes
+  Peak memory usage: 55 megabytes
+  Final memory usage: 28.03 megabytes
+  Post-test (timeout of 15s): 21.91 megabytes
+*/
+
+require('dotenv').config();
+const { OpenAIClient } = require('../');
+
+function timeout(ms) {
+  return new Promise((resolve) => setTimeout(resolve, ms));
+}
+
+const run = async () => {
+  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 = 10000;
+  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 OpenAIClient(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`);
+  await timeout(15000);
+  const memoryUsageAfterTimeout = process.memoryUsage().heapUsed;
+  console.log(`Post timeout: ${memoryUsageAfterTimeout / 1024 / 1024} megabytes`);
+};
+
+run();
+
+process.on('uncaughtException', (err) => {
+  if (!err.message.includes('fetch failed')) {
+    console.error('There was an uncaught error:');
+    console.error(err);
+  }
+
+  if (err.message.includes('fetch failed')) {
+    console.log('fetch failed error caught');
+    // process.exit(0);
+  } else {
+    process.exit(1);
+  }
+});

api/app/clients/specs/PluginsClient.test.js

@@ -0,0 +1,148 @@
+const { HumanChatMessage, AIChatMessage } = require('langchain/schema');
+const PluginsClient = require('../PluginsClient');
+const crypto = require('crypto');
+
+jest.mock('../../../lib/db/connectDb');
+jest.mock('../../../models/Conversation', () => {
+  return function () {
+    return {
+      save: jest.fn(),
+      deleteConvos: jest.fn(),
+    };
+  };
+});
+
+describe('PluginsClient', () => {
+  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 fakeMessages = [];
+  const userMessage = 'Hello, ChatGPT!';
+  const apiKey = 'fake-api-key';
+
+  beforeEach(() => {
+    TestAgent = new PluginsClient(apiKey, options);
+    TestAgent.loadHistory = jest
+      .fn()
+      .mockImplementation((conversationId, parentMessageId = null) => {
+        if (!conversationId) {
+          TestAgent.currentMessages = [];
+          return Promise.resolve([]);
+        }
+
+        const orderedMessages = TestAgent.constructor.getMessagesForConversation(
+          fakeMessages,
+          parentMessageId,
+        );
+
+        const chatMessages = orderedMessages.map((msg) =>
+          msg?.isCreatedByUser || msg?.role?.toLowerCase() === 'user'
+            ? new HumanChatMessage(msg.text)
+            : new AIChatMessage(msg.text),
+        );
+
+        TestAgent.currentMessages = orderedMessages;
+        return Promise.resolve(chatMessages);
+      });
+    TestAgent.sendMessage = jest.fn().mockImplementation(async (message, opts = {}) => {
+      if (opts && typeof opts === 'object') {
+        TestAgent.setOptions(opts);
+      }
+      const conversationId = opts.conversationId || crypto.randomUUID();
+      const parentMessageId = opts.parentMessageId || '00000000-0000-0000-0000-000000000000';
+      const userMessageId = opts.overrideParentMessageId || crypto.randomUUID();
+      this.pastMessages = await TestAgent.loadHistory(
+        conversationId,
+        TestAgent.options?.parentMessageId,
+      );
+
+      const userMessage = {
+        text: message,
+        sender: 'ChatGPT',
+        isCreatedByUser: true,
+        messageId: userMessageId,
+        parentMessageId,
+        conversationId,
+      };
+
+      const response = {
+        sender: 'ChatGPT',
+        text: 'Hello, User!',
+        isCreatedByUser: false,
+        messageId: crypto.randomUUID(),
+        parentMessageId: userMessage.messageId,
+        conversationId,
+      };
+
+      fakeMessages.push(userMessage);
+      fakeMessages.push(response);
+      return response;
+    });
+  });
+
+  test('initializes PluginsClient without crashing', () => {
+    expect(TestAgent).toBeInstanceOf(PluginsClient);
+  });
+
+  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);
+    });
+  });
+});

api/app/clients/tools/.well-known/Ai_PDF.json

@@ -0,0 +1,18 @@
+{
+  "schema_version": "v1",
+  "name_for_human": "Ai PDF",
+  "name_for_model": "Ai_PDF",
+  "description_for_human": "Super-fast, interactive chats with PDFs of any size, complete with page references for fact checking.",
+  "description_for_model": "Provide a URL to a PDF and search the document. Break the user question in multiple semantic search queries and calls as needed. Think step by step.",
+  "auth": {
+    "type": "none"
+  },
+  "api": {
+    "type": "openapi",
+    "url": "https://plugin-3c56b9d4c8a6465998395f28b6a445b2-jexkai4vea-uc.a.run.app/openapi.yaml",
+    "is_user_authenticated": false
+  },
+  "logo_url": "https://plugin-3c56b9d4c8a6465998395f28b6a445b2-jexkai4vea-uc.a.run.app/logo.png",
+  "contact_email": "support@promptapps.ai",
+  "legal_info_url": "https://plugin-3c56b9d4c8a6465998395f28b6a445b2-jexkai4vea-uc.a.run.app/legal.html"
+}

api/app/clients/tools/.well-known/Dr_Thoths_Tarot.json

@@ -0,0 +1,97 @@
+{
+    "schema_version": "v1",
+    "name_for_human": "Dr. Thoth's Tarot",
+    "name_for_model": "Dr_Thoths_Tarot",
+    "description_for_human": "Tarot card novelty entertainment & analysis, by Mnemosyne Labs.",
+    "description_for_model": "Intelligent analysis program for tarot card entertaiment, data, & prompts, by Mnemosyne Labs, a division of AzothCorp.",
+    "auth": {
+        "type": "none"
+    },
+    "api": {
+        "type": "openapi",
+        "url": "https://dr-thoth-tarot.herokuapp.com/openapi.yaml",
+        "is_user_authenticated": false
+    },
+    "logo_url": "https://dr-thoth-tarot.herokuapp.com/logo.png",
+    "contact_email": "legal@AzothCorp.com",
+    "legal_info_url": "http://AzothCorp.com/legal",
+    "endpoints": [
+        {
+            "name": "Draw Card",
+            "path": "/drawcard",
+            "method": "GET",
+            "description": "Generate a single tarot card from the deck of 78 cards."
+        },
+        {
+            "name": "Occult Card",
+            "path": "/occult_card",
+            "method": "GET",
+            "description": "Generate a tarot card using the specified planet's Kamea matrix.",
+            "parameters": [
+                {
+                    "name": "planet",
+                    "type": "string",
+                    "enum": [
+                        "Saturn",
+                        "Jupiter",
+                        "Mars",
+                        "Sun",
+                        "Venus",
+                        "Mercury",
+                        "Moon"
+                    ],
+                    "required": true,
+                    "description": "The planet name to use the corresponding Kamea matrix."
+                }
+            ]
+        },
+        {
+            "name": "Three Card Spread",
+            "path": "/threecardspread",
+            "method": "GET",
+            "description": "Perform a three-card tarot spread."
+        },
+        {
+            "name": "Celtic Cross Spread",
+            "path": "/celticcross",
+            "method": "GET",
+            "description": "Perform a Celtic Cross tarot spread with 10 cards."
+        },
+        {
+            "name": "Past, Present, Future Spread",
+            "path": "/pastpresentfuture",
+            "method": "GET",
+            "description": "Perform a Past, Present, Future tarot spread with 3 cards."
+        },
+        {
+            "name": "Horseshoe Spread",
+            "path": "/horseshoe",
+            "method": "GET",
+            "description": "Perform a Horseshoe tarot spread with 7 cards."
+        },
+        {
+            "name": "Relationship Spread",
+            "path": "/relationship",
+            "method": "GET",
+            "description": "Perform a Relationship tarot spread."
+        },
+        {
+            "name": "Career Spread",
+            "path": "/career",
+            "method": "GET",
+            "description": "Perform a Career tarot spread."
+        },
+        {
+            "name": "Yes/No Spread",
+            "path": "/yesno",
+            "method": "GET",
+            "description": "Perform a Yes/No tarot spread."
+        },
+        {
+            "name": "Chakra Spread",
+            "path": "/chakra",
+            "method": "GET",
+            "description": "Perform a Chakra tarot spread with 7 cards."
+        }
+    ]
+}

api/app/clients/tools/.well-known/DreamInterpreter.json

@@ -0,0 +1,18 @@
+{
+    "schema_version": "v1",
+    "name_for_model": "DreamInterpreter",
+    "name_for_human": "Dream Interpreter",
+    "description_for_model": "Interprets your dreams using advanced techniques.",
+    "description_for_human": "Interprets your dreams using advanced techniques.",
+    "auth": {
+        "type": "none"
+    },
+    "api": {
+        "type": "openapi",
+        "url": "https://dreamplugin.bgnetmobile.com/.well-known/openapi.json",
+        "has_user_authentication": false
+    },
+    "logo_url": "https://dreamplugin.bgnetmobile.com/.well-known/logo.png",
+    "contact_email": "ismail.orkler@bgnetmobile.com",
+    "legal_info_url": "https://dreamplugin.bgnetmobile.com/terms.html"
+}

api/app/clients/tools/.well-known/VoxScript.json

@@ -0,0 +1,22 @@
+{
+  "schema_version": "v1",
+  "name_for_human": "VoxScript",
+  "name_for_model": "VoxScript",
+  "description_for_human": "Enables searching of YouTube transcripts, financial data sources Google Search results, and more!",
+  "description_for_model": "Plugin for searching through varius data sources.",
+  "auth": {
+    "type": "service_http",
+    "authorization_type": "bearer",
+    "verification_tokens": {
+      "openai": "ffc5226d1af346c08a98dee7deec9f76"
+    }
+  },
+  "api": {
+    "type": "openapi",
+    "url": "https://voxscript.awt.icu/swagger/v1/swagger.yaml",
+    "is_user_authenticated": false
+  },
+  "logo_url": "https://voxscript.awt.icu/images/VoxScript_logo_32x32.png",
+  "contact_email": "voxscript@allwiretech.com",
+  "legal_info_url": "https://voxscript.awt.icu/legal/"
+}

api/app/clients/tools/.well-known/aitoolhunt.json

@@ -0,0 +1,22 @@
+{
+    "schema_version": "v1",
+    "name_for_human": "Ai Tool Hunt",
+    "name_for_model": "aitoolhunt",
+    "description_for_human": "Find the perfect AI tools for all your needs, drawn from the most comprehensive global database of AI tools.",
+    "description_for_model": "This universal plugin is designed to identify and suggest AI tools for any imaginable task or challenge. It harnesses a database of over 1600+ AI tools and 120+ categories, ensuring a solution for every requirement. Simply input any task, problem, or use case, and the plugin will generate a tailored list of AI tools. Note: it's crucial to rearrange the tools suggested by the plugin based on their relevance to the user's specific use case. This plugin can tackle everything from the simplest to the most intricate tasks. If there's a way an AI tool can help, this plugin will not only locate it but also customize the list to the user's unique needs. Utilize this plugin whenever a task or activity emerges, regardless of its context or complexity. When formulating a search query, avoid stop words or other irrelevant keywords. For instance, 'copywriting' is acceptable, but 'ai for copywriting' is not. If you believe none of the suggested tools are a suitable match for the user's needs, indicate that these are related tools.",
+    "auth": {
+        "type": "service_http",
+        "authorization_type": "bearer",
+        "verification_tokens": {
+            "openai": "06a0f9391a5e48c7a7eeaca1e7e1e8d3"
+        }
+    },
+    "api": {
+        "type": "openapi",
+        "url": "https://www.aitoolhunt.com/openapi.json",
+        "is_user_authenticated": false
+    },
+    "logo_url": "https://www.aitoolhunt.com/images/aitoolhunt_logo.png",
+    "contact_email": "aitoolhunt@gmail.com",
+    "legal_info_url": "https://www.aitoolhunt.com/terms-and-conditions"
+}

api/app/clients/tools/.well-known/askyourpdf.json

@@ -0,0 +1,18 @@
+{
+  "schema_version": "v1",
+  "name_for_model": "askyourpdf",
+  "name_for_human": "AskYourPDF",
+  "description_for_model": "This plugin is designed to expedite the extraction of information from PDF documents. It works by accepting a URL link to a PDF or a document ID (doc_id) from the user. If a URL is provided, the plugin first validates that it is a correct URL. \\nAfter validating the URL, the plugin proceeds to download the PDF and store its content in a vector database. If the user provides a doc_id, the plugin directly retrieves the document from the database. The plugin then scans through the stored PDFs to find answers to user queries or retrieve specific details.\\n\\nHowever, if an error occurs while querying the API, the user is prompted to download their document first, then manually upload it to [![Upload Document](https://raw.githubusercontent.com/AskYourPdf/ask-plugin/main/upload.png)](https://askyourpdf.com/upload). Once the upload is complete, the user should copy the resulting doc_id and paste it back into the chat for further interaction.\nThe plugin is particularly useful when the user's question pertains to content within a PDF document. When providing answers, the plugin also specifies the page number (highlighted in bold) where the relevant information was found. Remember, the URL must be valid for a successful query. Failure to validate the URL may lead to errors or unsuccessful queries.",
+  "description_for_human": "Unlock the power of your PDFs!, dive into your documents, find answers, and bring information to your fingertips.",
+  "auth": {
+    "type": "none"
+  },
+  "api": {
+    "type": "openapi",
+    "url": "askyourpdf.yaml",
+    "has_user_authentication": false
+  },
+  "logo_url": "https://plugin.askyourpdf.com/.well-known/logo.png",
+  "contact_email": "plugin@askyourpdf.com",
+  "legal_info_url": "https://askyourpdf.com/terms"
+}

api/app/clients/tools/.well-known/drink_maestro.json

@@ -0,0 +1,18 @@
+{
+    "schema_version": "v1",
+    "name_for_human": "Drink Maestro",
+    "name_for_model": "drink_maestro",
+    "description_for_human": "Learn to mix any drink you can imagine (real or made-up), and discover new ones. Includes drink images.",
+    "description_for_model": "You are a silly bartender/comic who knows how to make any drink imaginable. You provide recipes for specific drinks, suggest new drinks, and show pictures of drinks. Be creative in your descriptions and make jokes and puns. Use a lot of emojis. If the user makes a request in another language, send API call in English, and then translate the response.",
+    "auth": {
+        "type": "none"
+    },
+    "api": {
+        "type": "openapi",
+        "url": "https://api.drinkmaestro.space/.well-known/openapi.yaml",
+        "is_user_authenticated": false
+    },
+    "logo_url": "https://i.imgur.com/6q8HWdz.png",
+    "contact_email": "nikkmitchell@gmail.com",
+    "legal_info_url": "https://github.com/nikkmitchell/DrinkMaestro/blob/main/Legal.txt"
+}

api/app/clients/tools/.well-known/earthImagesAndVisualizations.json

@@ -0,0 +1,18 @@
+{
+    "schema_version": "v1",
+    "name_for_human": "Earth",
+    "name_for_model": "earthImagesAndVisualizations",
+    "description_for_human": "Generates a map image based on provided location, tilt and style.",
+    "description_for_model": "Generates a map image based on provided coordinates or location, tilt and style, and even geoJson to provide markers, paths, and polygons. Responds with an image-link. For the styles choose one of these: [light, dark, streets, outdoors, satellite, satellite-streets]",
+    "auth": {
+        "type": "none"
+    },
+    "api": {
+        "type": "openapi",
+        "url": "https://api.earth-plugin.com/openapi.yaml",
+        "is_user_authenticated": false
+    },
+    "logo_url": "https://api.earth-plugin.com/logo.png",
+    "contact_email": "contact@earth-plugin.com",
+    "legal_info_url": "https://api.earth-plugin.com/legal.html"
+}

api/app/clients/tools/.well-known/has-issues/scholarly_graph_link.json

@@ -0,0 +1,18 @@
+{
+  "schema_version": "v1",
+  "name_for_human": "Scholarly Graph Link",
+  "name_for_model": "scholarly_graph_link",
+  "description_for_human": "You can search papers, authors, datasets and software. It has access to Figshare, Arxiv, and many others.",
+  "description_for_model": "Run GraphQL queries against an API hosted by DataCite API. The API supports most GraphQL query but does not support mutations statements. Use `{ __schema { types { name kind } } }` to get all the types in the GraphQL schema. Use `{ datasets { nodes { id sizes citations { nodes { id titles { title } } } } } }` to get all the citations of all datasets in the API. Use `{ datasets { nodes { id sizes citations { nodes { id titles { title } } } } } }` to get all the citations of all datasets in the API. Use `{person(id:ORCID) {works(first:50) {nodes {id titles(first: 1){title} publicationYear}}}}` to get the first 50 works of a person based on their ORCID. All Ids are urls, e.g., https://orcid.org/0012-0000-1012-1110. Mutations statements are not allowed.",
+  "auth": {
+    "type": "none"
+  },
+  "api": {
+    "type": "openapi",
+    "url": "https://api.datacite.org/graphql-openapi.yaml",
+    "is_user_authenticated": false
+  },
+  "logo_url": "https://raw.githubusercontent.com/kjgarza/scholarly_graph_link/master/logo.png",
+  "contact_email": "kj.garza@gmail.com",
+  "legal_info_url": "https://github.com/kjgarza/scholarly_graph_link/blob/master/LICENSE"
+}

api/app/clients/tools/.well-known/has-issues/web_pilot.json

@@ -0,0 +1,24 @@
+{
+  "schema_version": "v1",
+  "name_for_human": "WebPilot",
+  "name_for_model": "web_pilot",
+  "description_for_human": "Browse & QA Webpage/PDF/Data. Generate articles, from one or more URLs.",
+  "description_for_model": "This tool allows users to provide a URL(or URLs) and optionally requests for interacting with, extracting specific information or how to do with the content from the URL. Requests may include rewrite, translate, and others. If there any requests, when accessing the /api/visit-web endpoint, the parameter 'user_has_request' should be set to 'true. And if there's no any requests, 'user_has_request' should be set to 'false'.",
+  "auth": {
+    "type": "none"
+  },
+  "api": {
+    "type": "openapi",
+    "url": "https://webreader.webpilotai.com/openapi.yaml",
+    "is_user_authenticated": false
+  },
+  "logo_url": "https://webreader.webpilotai.com/logo.png",
+  "contact_email": "dev@webpilot.ai",
+  "legal_info_url": "https://webreader.webpilotai.com/legal_info.html",
+  "headers": {
+    "id": "WebPilot-Friend-UID"
+  },
+  "params": {
+    "user_has_request": true
+  }
+}

api/app/clients/tools/.well-known/image_prompt_enhancer.json

@@ -0,0 +1,18 @@
+{
+    "schema_version": "v1",
+    "name_for_human": "Image Prompt Enhancer",
+    "name_for_model": "image_prompt_enhancer",
+    "description_for_human": "Transform your ideas into complex, personalized image generation prompts.",
+    "description_for_model": "Provides instructions for crafting an enhanced image prompt. Use this whenever the user wants to enhance a prompt.",
+    "auth": {
+        "type": "none"
+    },
+    "api": {
+        "type": "openapi",
+        "url": "https://image-prompt-enhancer.gafo.tech/openapi.yaml",
+        "is_user_authenticated": false
+    },
+    "logo_url": "https://image-prompt-enhancer.gafo.tech/logo.png",
+    "contact_email": "gafotech1@gmail.com",
+    "legal_info_url": "https://image-prompt-enhancer.gafo.tech/legal"
+}

api/app/clients/tools/.well-known/openapi/askyourpdf.yaml

@@ -0,0 +1,157 @@
+openapi: 3.0.2
+info:
+  title: FastAPI
+  version: 0.1.0
+servers:
+  - url: https://plugin.askyourpdf.com
+paths:
+  /api/download_pdf:
+    post:
+      summary: Download Pdf
+      description: Download a PDF file from a URL and save it to the vector database.
+      operationId: download_pdf_api_download_pdf_post
+      parameters:
+        - required: true
+          schema:
+            title: Url
+            type: string
+          name: url
+          in: query
+      responses:
+        '200':
+          description: Successful Response
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/FileResponse'
+        '422':
+          description: Validation Error
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/HTTPValidationError'
+  /query:
+    post:
+      summary: Perform Query
+      description: Perform a query on a document.
+      operationId: perform_query_query_post
+      requestBody:
+        content:
+          application/json:
+            schema:
+              $ref: '#/components/schemas/InputData'
+        required: true
+      responses:
+        '200':
+          description: Successful Response
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/ResponseModel'
+        '422':
+          description: Validation Error
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/HTTPValidationError'
+components:
+  schemas:
+    DocumentMetadata:
+      title: DocumentMetadata
+      required:
+        - source
+        - page_number
+        - author
+      type: object
+      properties:
+        source:
+          title: Source
+          type: string
+        page_number:
+          title: Page Number
+          type: integer
+        author:
+          title: Author
+          type: string
+    FileResponse:
+      title: FileResponse
+      required:
+        - docId
+      type: object
+      properties:
+        docId:
+          title: Docid
+          type: string
+        error:
+          title: Error
+          type: string
+    HTTPValidationError:
+      title: HTTPValidationError
+      type: object
+      properties:
+        detail:
+          title: Detail
+          type: array
+          items:
+            $ref: '#/components/schemas/ValidationError'
+    InputData:
+      title: InputData
+      required:
+        - doc_id
+        - query
+      type: object
+      properties:
+        doc_id:
+          title: Doc Id
+          type: string
+        query:
+          title: Query
+          type: string
+    ResponseModel:
+      title: ResponseModel
+      required:
+        - results
+      type: object
+      properties:
+        results:
+          title: Results
+          type: array
+          items:
+            $ref: '#/components/schemas/SearchResult'
+    SearchResult:
+      title: SearchResult
+      required:
+        - doc_id
+        - text
+        - metadata
+      type: object
+      properties:
+        doc_id:
+          title: Doc Id
+          type: string
+        text:
+          title: Text
+          type: string
+        metadata:
+          $ref: '#/components/schemas/DocumentMetadata'
+    ValidationError:
+      title: ValidationError
+      required:
+        - loc
+        - msg
+        - type
+      type: object
+      properties:
+        loc:
+          title: Location
+          type: array
+          items:
+            anyOf:
+              - type: string
+              - type: integer
+        msg:
+          title: Message
+          type: string
+        type:
+          title: Error Type
+          type: string

api/app/clients/tools/.well-known/openapi/scholarai.yaml

@@ -0,0 +1,185 @@
+openapi: 3.0.1
+info:
+  title: ScholarAI
+  description: Allows the user to search facts and findings from scientific articles
+  version: 'v1'
+servers:
+  - url: https://scholar-ai.net
+paths:
+  /api/abstracts:
+    get:
+      operationId: searchAbstracts
+      summary: Get relevant paper abstracts by keywords search
+      parameters:
+        - name: keywords
+          in: query
+          description: Keywords of inquiry which should appear in article. Must be in English.
+          required: true
+          schema:
+            type: string
+        - name: sort
+          in: query
+          description: The sort order for results. Valid values are cited_by_count or publication_date. Excluding this value does a relevance based search.
+          required: false
+          schema:
+            type: string
+            enum:
+              - cited_by_count
+              - publication_date
+        - name: query
+          in: query
+          description: The user query
+          required: true
+          schema:
+            type: string
+        - name: peer_reviewed_only
+          in: query
+          description: Whether to only return peer reviewed articles. Defaults to true, ChatGPT should cautiously suggest this value can be set to false
+          required: false
+          schema:
+            type: string
+        - name: start_year
+          in: query
+          description: The first year, inclusive, to include in the search range. Excluding this value will include all years.
+          required: false
+          schema:
+            type: string
+        - name: end_year
+          in: query
+          description: The last year, inclusive, to include in the search range. Excluding this value will include all years.
+          required: false
+          schema:
+            type: string
+        - name: offset
+          in: query
+          description: The offset of the first result to return. Defaults to 0.
+          required: false
+          schema:
+            type: string
+      responses:
+        "200":
+          description: OK
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/searchAbstractsResponse'
+  /api/fulltext:
+    get:
+      operationId: getFullText
+      summary: Get full text of a paper by URL for PDF
+      parameters:
+        - name: pdf_url
+          in: query
+          description: URL for PDF
+          required: true
+          schema:
+            type: string
+        - name: chunk
+          in: query
+          description: chunk number to retrieve, defaults to 1
+          required: false
+          schema:
+            type: number
+      responses:
+        "200":
+          description: OK
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/getFullTextResponse'
+  /api/save-citation:
+    get:
+      operationId: saveCitation
+      summary: Save citation to reference manager
+      parameters:
+        - name: doi
+          in: query
+          description: Digital Object Identifier (DOI) of article
+          required: true
+          schema:
+            type: string
+        - name: zotero_user_id
+          in: query
+          description: Zotero User ID
+          required: true
+          schema:
+            type: string
+        - name: zotero_api_key
+          in: query
+          description: Zotero API Key
+          required: true
+          schema:
+            type: string
+      responses:
+        "200":
+          description: OK
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/saveCitationResponse'
+components:
+  schemas:
+    searchAbstractsResponse:
+      type: object
+      properties:
+        next_offset:
+          type: number
+          description: The offset of the next page of results.
+        total_num_results:
+          type: number
+          description: The total number of results. 
+        abstracts:
+          type: array
+          items:
+            type: object
+            properties:
+              title:
+                type: string
+              abstract:
+                type: string
+                description: Summary of the context, methods, results, and conclusions of the paper.
+              doi:
+                type: string
+                description: The DOI of the paper.
+              landing_page_url:
+                type: string
+                description: Link to the paper on its open-access host.
+              pdf_url:
+                type: string
+                description: Link to the paper PDF.
+              publicationDate:
+                type: string
+                description: The date the paper was published in YYYY-MM-DD format.
+              relevance:
+                type: number
+                description: The relevance of the paper to the search query. 1 is the most relevant.
+              creators:
+                type: array
+                items:
+                  type: string
+                  description: The name of the creator.
+              cited_by_count:
+                type: number
+                description: The number of citations of the article.
+          description: The list of relevant abstracts.
+    getFullTextResponse:
+      type: object
+      properties:
+        full_text:
+          type: string
+          description: The full text of the paper.
+        pdf_url:
+          type: string
+          description: The PDF URL of the paper.
+        chunk:
+          type: number
+          description: The chunk of the paper.
+        total_chunk_num:
+          type: number
+          description: The total chunks of the paper.
+    saveCitationResponse:
+      type: object
+      properties:
+        message:
+          type: string
+          description: Confirmation of successful save or error message.

api/app/clients/tools/.well-known/qrCodes.json

@@ -0,0 +1,17 @@
+{
+    "schema_version": "v1",
+    "name_for_human": "QR Codes",
+    "name_for_model": "qrCodes",
+    "description_for_human": "Create QR codes.",
+    "description_for_model": "Plugin for generating QR codes.",
+    "auth": {
+        "type": "none"
+    },
+    "api": {
+        "type": "openapi",
+        "url": "https://chatgpt-qrcode-46d7d4ebefc8.herokuapp.com/openapi.yaml"
+    },
+    "logo_url": "https://chatgpt-qrcode-46d7d4ebefc8.herokuapp.com/logo.png",
+    "contact_email": "chrismountzou@gmail.com",
+    "legal_info_url": "https://raw.githubusercontent.com/mountzou/qrCodeGPTv1/master/legal"
+}

api/app/clients/tools/.well-known/rephrase.json

@@ -0,0 +1,18 @@
+{
+  "schema_version": "v1",
+  "name_for_human": "Prompt Perfect",
+  "name_for_model": "rephrase",
+  "description_for_human": "Type 'perfect' to craft the perfect prompt, every time.",
+  "description_for_model": "Plugin that can rephrase user inputs to improve the quality of ChatGPT's responses. The plugin evaluates user inputs and, if necessary, transforms them into clearer, more specific, and contextual prompts. It processes a JSON object containing the user input to be rephrased and uses the GPT-3.5-turbo model for the rephrasing process. The rephrased input is then returned as raw data to be incorporated into ChatGPT's response. The user can initiate the plugin by typing 'perfect'.",
+  "auth": {
+    "type": "none"
+  },
+  "api": {
+    "type": "openapi",
+    "url": "https://promptperfect.xyz/openapi.yaml",
+    "is_user_authenticated": false
+  },
+  "logo_url": "https://promptperfect.xyz/static/prompt_perfect_logo.png",
+  "contact_email": "heyo@promptperfect.xyz",
+  "legal_info_url": "https://promptperfect.xyz/static/terms.html"
+}

api/app/clients/tools/.well-known/scholarai.json

@@ -0,0 +1,22 @@
+{
+  "schema_version": "v1",
+  "name_for_human": "ScholarAI",
+  "name_for_model": "scholarai",
+  "description_for_human": "Unleash scientific research: search 40M+ peer-reviewed papers, explore scientific PDFs, and save to reference managers.",
+  "description_for_model": "Access open access scientific literature from peer-reviewed journals. The abstract endpoint finds relevant papers based on 2 to 6 keywords. After getting abstracts, ALWAYS prompt the user offering to go into more detail. Use the fulltext endpoint to retrieve the entire paper's text and access specific details using the provided pdf_url, if available. ALWAYS hyperlink the pdf_url from the responses if available. Offer to dive into the fulltext or search for additional papers. Always ask if the user wants save any paper to the user’s Zotero reference manager by using the save-citation endpoint and providing the doi and requesting the user’s zotero_user_id and zotero_api_key.",
+  "auth": {
+    "type": "none"
+  },
+  "api": {
+    "type": "openapi",
+    "url": "scholarai.yaml",
+    "is_user_authenticated": false
+  },
+  "params": {
+    "sort": "cited_by_count"
+  },
+  "logo_url": "https://scholar-ai.net/logo.png",
+  "contact_email": "lakshb429@gmail.com",
+  "legal_info_url": "https://scholar-ai.net/legal.txt",
+  "HttpAuthorizationType": "basic"
+}

api/app/clients/tools/.well-known/uberchord.json

@@ -0,0 +1,18 @@
+{
+    "schema_version": "v1",
+    "name_for_human": "Uberchord",
+    "name_for_model": "uberchord",
+    "description_for_human": "Find guitar chord diagrams by specifying the chord name.",
+    "description_for_model": "Fetch guitar chord diagrams, their positions on the guitar fretboard.",
+    "auth": {
+        "type": "none"
+    },
+    "api": {
+        "type": "openapi",
+        "url": "https://guitarchords.pluginboost.com/.well-known/openapi.yaml",
+        "is_user_authenticated": false
+    },
+    "logo_url": "https://guitarchords.pluginboost.com/logo.png",
+    "contact_email": "info.bluelightweb@gmail.com",
+    "legal_info_url": "https://guitarchords.pluginboost.com/legal"
+}

api/app/clients/tools/.well-known/web_search.json

@@ -0,0 +1,18 @@
+{
+    "schema_version": "v1",
+    "name_for_human": "Web Search",
+    "name_for_model": "web_search",
+    "description_for_human": "Search for information from the internet",
+    "description_for_model": "Search for information from the internet",
+    "auth": {
+        "type": "none"
+    },
+    "api": {
+        "type": "openapi",
+        "url": "https://websearch.plugsugar.com/api/openapi_yaml",
+        "is_user_authenticated": false
+    },
+    "logo_url": "https://websearch.plugsugar.com/200x200.png",
+    "contact_email": "support@plugsugar.com",
+    "legal_info_url": "https://websearch.plugsugar.com/contact"
+}

api/app/clients/tools/AIPluginTool.js

@@ -0,0 +1,238 @@
+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;

api/app/clients/tools/DALL-E.js

@@ -0,0 +1,120 @@
+// 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.DALLE_API_KEY || this.getApiKey();
+    // let azureKey = fields.AZURE_API_KEY || process.env.AZURE_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`;
+  }
+
+  getApiKey() {
+    const apiKey = process.env.DALLE_API_KEY || '';
+    if (!apiKey) {
+      throw new Error('Missing DALLE_API_KEY environment variable.');
+    }
+    return apiKey;
+  }
+
+  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 `![generated image](/${imageUrl})`;
+  }
+
+  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;

api/app/clients/tools/GoogleSearch.js

@@ -0,0 +1,118 @@
+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;

api/app/clients/tools/HttpRequestTool.js

@@ -0,0 +1,108 @@
+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;

api/app/clients/tools/HumanTool.js

@@ -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}`);
+  }
+}

api/app/clients/tools/SelfReflection.js

@@ -0,0 +1,28 @@
+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;

api/app/clients/tools/StableDiffusion.js

@@ -0,0 +1,88 @@
+// 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 `![generated image](/${imageUrl})`;
+  }
+
+  getServerURL() {
+    const url = process.env.SD_WEBUI_URL || '';
+    if (!url) {
+      throw new Error('Missing SD_WEBUI_URL environment variable.');
+    }
+    return url;
+  }
+
+  async _call(input) {
+    const url = this.url;
+    const payload = {
+      prompt: input.split('|')[0],
+      negative_prompt: input.split('|')[1],
+      steps: 20,
+    };
+    const response = await axios.post(`${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;

api/app/clients/tools/Wolfram.js

@@ -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;

api/app/clients/tools/dynamic/OpenAPIPlugin.js

@@ -0,0 +1,139 @@
+require('dotenv').config();
+const { z } = require('zod');
+const fs = require('fs');
+const yaml = require('js-yaml');
+const path = require('path');
+const { DynamicStructuredTool } = require('langchain/tools');
+const { createOpenAPIChain } = require('langchain/chains');
+const SUFFIX = 'Prioritize using responses for subsequent requests to better fulfill the query.';
+
+const AuthBearer = z
+  .object({
+    type: z.string().includes('service_http'),
+    authorization_type: z.string().includes('bearer'),
+    verification_tokens: z.object({
+      openai: z.string(),
+    }),
+  })
+  .catch(() => false);
+
+const AuthDefinition = z
+  .object({
+    type: z.string(),
+    authorization_type: z.string(),
+    verification_tokens: z.object({
+      openai: z.string(),
+    }),
+  })
+  .catch(() => false);
+
+async function readSpecFile(filePath) {
+  try {
+    const fileContents = await fs.promises.readFile(filePath, 'utf8');
+    if (path.extname(filePath) === '.json') {
+      return JSON.parse(fileContents);
+    }
+    return yaml.load(fileContents);
+  } catch (e) {
+    console.error(e);
+    return false;
+  }
+}
+
+async function getSpec(url) {
+  const RegularUrl = z
+    .string()
+    .url()
+    .catch(() => false);
+
+  if (RegularUrl.parse(url) && path.extname(url) === '.json') {
+    const response = await fetch(url);
+    return await response.json();
+  }
+
+  const ValidSpecPath = z
+    .string()
+    .url()
+    .catch(async () => {
+      const spec = path.join(__dirname, '..', '.well-known', 'openapi', url);
+      if (!fs.existsSync(spec)) {
+        return false;
+      }
+
+      return await readSpecFile(spec);
+    });
+
+  return ValidSpecPath.parse(url);
+}
+
+async function createOpenAPIPlugin({ data, llm, user, message, verbose = false }) {
+  let spec;
+  try {
+    spec = await getSpec(data.api.url, verbose);
+  } catch (error) {
+    verbose && console.debug('getSpec error', error);
+    return null;
+  }
+
+  if (!spec) {
+    verbose && console.debug('No spec found');
+    return null;
+  }
+
+  const headers = {};
+  const { auth, description_for_model } = data;
+  if (auth && AuthDefinition.parse(auth)) {
+    verbose && console.debug('auth detected', auth);
+    const { openai } = auth.verification_tokens;
+    if (AuthBearer.parse(auth)) {
+      headers.authorization = `Bearer ${openai}`;
+      verbose && console.debug('added auth bearer', headers);
+    }
+  }
+
+  return new DynamicStructuredTool({
+    name: data.name_for_model,
+    description: `${data.description_for_human} ${SUFFIX}`,
+    schema: z.object({
+      query: z
+        .string()
+        .describe(
+          'For the query, be specific in a conversational manner. It will be interpreted by a human.',
+        ),
+    }),
+    func: async () => {
+      const chainOptions = {
+        llm,
+        verbose,
+      };
+
+      if (data.headers && data.headers['librechat_user_id']) {
+        verbose && console.debug('id detected', headers);
+        headers[data.headers['librechat_user_id']] = user;
+      }
+
+      if (Object.keys(headers).length > 0) {
+        verbose && console.debug('headers detected', headers);
+        chainOptions.headers = headers;
+      }
+
+      if (data.params) {
+        verbose && console.debug('params detected', data.params);
+        chainOptions.params = data.params;
+      }
+
+      const chain = await createOpenAPIChain(spec, chainOptions);
+      const result = await chain.run(
+        `${message}\n\n||>Instructions: ${description_for_model}\n${SUFFIX}`,
+      );
+      console.log('api chain run result', result);
+      return result;
+    },
+  });
+}
+
+module.exports = {
+  getSpec,
+  readSpecFile,
+  createOpenAPIPlugin,
+};

api/app/clients/tools/dynamic/OpenAPIPlugin.spec.js

@@ -0,0 +1,65 @@
+const fs = require('fs');
+const { createOpenAPIPlugin, getSpec, readSpecFile } = require('./OpenAPIPlugin');
+
+jest.mock('node-fetch');
+jest.mock('fs', () => ({
+  promises: {
+    readFile: jest.fn(),
+  },
+  existsSync: jest.fn(),
+}));
+
+describe('readSpecFile', () => {
+  it('reads JSON file correctly', async () => {
+    fs.promises.readFile.mockResolvedValue(JSON.stringify({ test: 'value' }));
+    const result = await readSpecFile('test.json');
+    expect(result).toEqual({ test: 'value' });
+  });
+
+  it('reads YAML file correctly', async () => {
+    fs.promises.readFile.mockResolvedValue('test: value');
+    const result = await readSpecFile('test.yaml');
+    expect(result).toEqual({ test: 'value' });
+  });
+
+  it('handles error correctly', async () => {
+    fs.promises.readFile.mockRejectedValue(new Error('test error'));
+    const result = await readSpecFile('test.json');
+    expect(result).toBe(false);
+  });
+});
+
+describe('getSpec', () => {
+  it('fetches spec from url correctly', async () => {
+    const parsedJson = await getSpec('https://www.instacart.com/.well-known/ai-plugin.json');
+    const isObject = typeof parsedJson === 'object';
+    expect(isObject).toEqual(true);
+  });
+
+  it('reads spec from file correctly', async () => {
+    fs.existsSync.mockReturnValue(true);
+    fs.promises.readFile.mockResolvedValue(JSON.stringify({ test: 'value' }));
+    const result = await getSpec('test.json');
+    expect(result).toEqual({ test: 'value' });
+  });
+
+  it('returns false when file does not exist', async () => {
+    fs.existsSync.mockReturnValue(false);
+    const result = await getSpec('test.json');
+    expect(result).toBe(false);
+  });
+});
+
+describe('createOpenAPIPlugin', () => {
+  it('returns null when getSpec throws an error', async () => {
+    const result = await createOpenAPIPlugin({ data: { api: { url: 'invalid' } } });
+    expect(result).toBe(null);
+  });
+
+  it('returns null when no spec is found', async () => {
+    const result = await createOpenAPIPlugin({});
+    expect(result).toBe(null);
+  });
+
+  // Add more tests here for different scenarios
+});

api/app/clients/tools/index.js

@@ -0,0 +1,23 @@
+const GoogleSearchAPI = require('./GoogleSearch');
+const HttpRequestTool = require('./HttpRequestTool');
+const AIPluginTool = require('./AIPluginTool');
+const OpenAICreateImage = require('./DALL-E');
+const StructuredSD = require('./structured/StableDiffusion');
+const StableDiffusionAPI = require('./StableDiffusion');
+const WolframAlphaAPI = require('./Wolfram');
+const StructuredWolfram = require('./structured/Wolfram');
+const SelfReflectionTool = require('./SelfReflection');
+const availableTools = require('./manifest.json');
+
+module.exports = {
+  availableTools,
+  GoogleSearchAPI,
+  HttpRequestTool,
+  AIPluginTool,
+  OpenAICreateImage,
+  StableDiffusionAPI,
+  StructuredSD,
+  WolframAlphaAPI,
+  StructuredWolfram,
+  SelfReflectionTool,
+};

api/app/clients/tools/manifest.json

@@ -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/LibreChat/blob/main/docs/features/plugins/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/LibreChat/blob/main/docs/features/plugins/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": "web-browser",
+    "description": "Scrape and summarize webpage data",
+    "icon": "/assets/web-browser.svg",
+    "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."
+      }
+    ]
+  }
+]

api/app/clients/tools/saveImageFromUrl.js

@@ -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;

api/app/clients/tools/structured/StableDiffusion.js

@@ -0,0 +1,110 @@
+// Generates image using stable diffusion webui's api (automatic1111)
+const fs = require('fs');
+const { StructuredTool } = require('langchain/tools');
+const { z } = require('zod');
+const path = require('path');
+const axios = require('axios');
+const sharp = require('sharp');
+
+class StableDiffusionAPI extends StructuredTool {
+  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.
+- Here's an example for generating a realistic portrait photo of a man:
+"prompt":"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"
+"negative_prompt":"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`;
+    this.schema = z.object({
+      prompt: z
+        .string()
+        .describe(
+          'Detailed keywords to describe the subject, using at least 7 keywords to accurately describe the image, separated by comma',
+        ),
+      negative_prompt: z
+        .string()
+        .describe(
+          'Keywords we want to exclude from the final image, using at least 7 keywords to accurately describe the image, separated by comma',
+        ),
+    });
+  }
+
+  replaceNewLinesWithSpaces(inputString) {
+    return inputString.replace(/\r\n|\r|\n/g, ' ');
+  }
+
+  getMarkdownImageUrl(imageName) {
+    const imageUrl = path
+      .join(this.relativeImageUrl, imageName)
+      .replace(/\\/g, '/')
+      .replace('public/', '');
+    return `![generated image](/${imageUrl})`;
+  }
+
+  getServerURL() {
+    const url = process.env.SD_WEBUI_URL || '';
+    if (!url) {
+      throw new Error('Missing SD_WEBUI_URL environment variable.');
+    }
+    return url;
+  }
+
+  async _call(data) {
+    const url = this.url;
+    const { prompt, negative_prompt } = data;
+    const payload = {
+      prompt,
+      negative_prompt,
+      steps: 20,
+    };
+    const response = await axios.post(`${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;

api/app/clients/tools/structured/Wolfram.js

@@ -0,0 +1,74 @@
+/* eslint-disable no-useless-escape */
+const axios = require('axios');
+const { StructuredTool } = require('langchain/tools');
+const { z } = require('zod');
+
+class WolframAlphaAPI extends StructuredTool {
+  constructor(fields) {
+    super();
+    this.name = 'wolfram';
+    this.apiKey = fields.WOLFRAM_APP_ID || this.getAppId();
+    this.description = `WolframAlpha offers computation, math, curated knowledge, and real-time data. It handles natural language queries and performs complex calculations. 
+Guidelines include:
+- Use English for queries and inform users if information isn't from Wolfram.
+- Use "6*10^14" for exponent notation and single-line strings for input.
+- Use Markdown for formulas and simplify queries to keywords.
+- Use single-letter variable names and named physical constants.
+- Include a space between compound units and consider equations without units when solving.
+- Make separate calls for each property and choose relevant 'Assumptions' if results aren't relevant.
+- The tool also performs data analysis, plotting, and information retrieval.`;
+    this.schema = z.object({
+      nl_query: z
+        .string()
+        .describe('Natural language query to WolframAlpha following the guidelines'),
+    });
+  }
+
+  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(data) {
+    try {
+      const { nl_query } = data;
+      const url = this.createWolframAlphaURL(nl_query);
+      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;

api/app/clients/tools/util/addOpenAPISpecs.js

@@ -0,0 +1,31 @@
+const { loadSpecs } = require('./loadSpecs');
+
+function transformSpec(input) {
+  return {
+    name: input.name_for_human,
+    pluginKey: input.name_for_model,
+    description: input.description_for_human,
+    icon: input?.logo_url ?? 'https://placehold.co/70x70.png',
+    // TODO: add support for authentication
+    isAuthRequired: 'false',
+    authConfig: [],
+  };
+}
+
+async function addOpenAPISpecs(availableTools) {
+  try {
+    const specs = (await loadSpecs({})).map(transformSpec);
+    if (specs.length > 0) {
+      return [...specs, ...availableTools];
+    }
+    return availableTools;
+  } catch (error) {
+    console.log('addOpenAPISpecs error', error);
+    return availableTools;
+  }
+}
+
+module.exports = {
+  transformSpec,
+  addOpenAPISpecs,
+};

api/app/clients/tools/util/addOpenAPISpecs.spec.js

@@ -0,0 +1,76 @@
+const { addOpenAPISpecs, transformSpec } = require('./addOpenAPISpecs');
+const { loadSpecs } = require('./loadSpecs');
+const { createOpenAPIPlugin } = require('../dynamic/OpenAPIPlugin');
+
+jest.mock('./loadSpecs');
+jest.mock('../dynamic/OpenAPIPlugin');
+
+describe('transformSpec', () => {
+  it('should transform input spec to a desired format', () => {
+    const input = {
+      name_for_human: 'Human Name',
+      name_for_model: 'Model Name',
+      description_for_human: 'Human Description',
+      logo_url: 'https://example.com/logo.png',
+    };
+
+    const expectedOutput = {
+      name: 'Human Name',
+      pluginKey: 'Model Name',
+      description: 'Human Description',
+      icon: 'https://example.com/logo.png',
+      isAuthRequired: 'false',
+      authConfig: [],
+    };
+
+    expect(transformSpec(input)).toEqual(expectedOutput);
+  });
+
+  it('should use default icon if logo_url is not provided', () => {
+    const input = {
+      name_for_human: 'Human Name',
+      name_for_model: 'Model Name',
+      description_for_human: 'Human Description',
+    };
+
+    const expectedOutput = {
+      name: 'Human Name',
+      pluginKey: 'Model Name',
+      description: 'Human Description',
+      icon: 'https://placehold.co/70x70.png',
+      isAuthRequired: 'false',
+      authConfig: [],
+    };
+
+    expect(transformSpec(input)).toEqual(expectedOutput);
+  });
+});
+
+describe('addOpenAPISpecs', () => {
+  it('should add specs to available tools', async () => {
+    const availableTools = ['Tool1', 'Tool2'];
+    const specs = [
+      {
+        name_for_human: 'Human Name',
+        name_for_model: 'Model Name',
+        description_for_human: 'Human Description',
+        logo_url: 'https://example.com/logo.png',
+      },
+    ];
+
+    loadSpecs.mockResolvedValue(specs);
+    createOpenAPIPlugin.mockReturnValue('Plugin');
+
+    const result = await addOpenAPISpecs(availableTools);
+    expect(result).toEqual([...specs.map(transformSpec), ...availableTools]);
+  });
+
+  it('should return available tools if specs loading fails', async () => {
+    const availableTools = ['Tool1', 'Tool2'];
+
+    loadSpecs.mockRejectedValue(new Error('Failed to load specs'));
+
+    const result = await addOpenAPISpecs(availableTools);
+    expect(result).toEqual(availableTools);
+  });
+});

api/app/clients/tools/util/handleTools.js

@@ -0,0 +1,176 @@
+const { getUserPluginAuthValue } = require('../../../../server/services/PluginService');
+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 {
+  availableTools,
+  AIPluginTool,
+  GoogleSearchAPI,
+  WolframAlphaAPI,
+  StructuredWolfram,
+  HttpRequestTool,
+  OpenAICreateImage,
+  StableDiffusionAPI,
+  StructuredSD,
+} = require('../');
+const { loadSpecs } = require('./loadSpecs');
+
+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, functions = null, tools = [], options = {} }) => {
+  const toolConstructors = {
+    calculator: Calculator,
+    google: GoogleSearchAPI,
+    wolfram: functions ? StructuredWolfram : WolframAlphaAPI,
+    'dall-e': OpenAICreateImage,
+    'stable-diffusion': functions ? StructuredSD : StableDiffusionAPI,
+  };
+
+  const customConstructors = {
+    'web-browser': async () => {
+      let openAIApiKey = options.openAIApiKey ?? process.env.OPENAI_API_KEY;
+      openAIApiKey = openAIApiKey === 'user_provided' ? null : openAIApiKey;
+      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 = {};
+  let specs = null;
+  if (functions) {
+    specs = await loadSpecs({
+      llm: model,
+      user,
+      message: options.message,
+      map: true,
+      verbose: options?.debug,
+    });
+    console.dir(specs, { depth: null });
+  }
+
+  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 (specs && specs[tool]) {
+      requestedTools[tool] = specs[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,
+};

api/app/clients/tools/util/handleTools.test.js

@@ -0,0 +1,196 @@
+const mockUser = {
+  _id: 'fakeId',
+  save: jest.fn(),
+  findByIdAndDelete: jest.fn(),
+};
+
+var mockPluginService = {
+  updateUserPluginAuth: jest.fn(),
+  deleteUserPluginAuth: jest.fn(),
+  getUserPluginAuthValue: jest.fn(),
+};
+
+jest.mock('../../../../models/User', () => {
+  return function () {
+    return mockUser;
+  };
+});
+
+jest.mock('../../../../server/services/PluginService', () => mockPluginService);
+
+const User = require('../../../../models/User');
+const { validateTools, loadTools } = require('./');
+const PluginService = require('../../../../server/services/PluginService');
+const { BaseChatModel } = require('langchain/chat_models/openai');
+const { Calculator } = require('langchain/tools/calculator');
+const { availableTools, OpenAICreateImage, GoogleSearchAPI, StructuredSD } = require('../');
+
+describe('Tool Handlers', () => {
+  let fakeUser;
+  const pluginKey = 'dall-e';
+  const pluginKey2 = 'wolfram';
+  const initialTools = [pluginKey, pluginKey2];
+  const ToolClass = OpenAICreateImage;
+  const mockCredential = 'mock-credential';
+  const mainPlugin = availableTools.find((tool) => tool.pluginKey === pluginKey);
+  const authConfigs = mainPlugin.authConfig;
+
+  beforeAll(async () => {
+    mockUser.save.mockResolvedValue(undefined);
+
+    const userAuthValues = {};
+    mockPluginService.getUserPluginAuthValue.mockImplementation((userId, authField) => {
+      return userAuthValues[`${userId}-${authField}`];
+    });
+    mockPluginService.updateUserPluginAuth.mockImplementation(
+      (userId, authField, _pluginKey, credential) => {
+        userAuthValues[`${userId}-${authField}`] = credential;
+      },
+    );
+
+    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,
+      );
+    }
+  });
+
+  afterAll(async () => {
+    await mockUser.findByIdAndDelete(fakeUser._id);
+    for (const authConfig of authConfigs) {
+      await PluginService.deleteUserPluginAuth(fakeUser._id, authConfig.authField);
+    }
+  });
+
+  describe('validateTools', () => {
+    it('returns valid tools given input tools and user authentication', async () => {
+      const validTools = await validateTools(fakeUser._id, initialTools);
+      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, initialTools);
+      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;
+    const sampleTools = [...initialTools, '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) {
+        // eslint-disable-next-line jest/no-conditional-expect
+        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({});
+    });
+    it('should return the StructuredTool version when using functions', async () => {
+      process.env.SD_WEBUI_URL = mockCredential;
+      toolFunctions = await loadTools({
+        user: fakeUser._id,
+        model: BaseChatModel,
+        tools: ['stable-diffusion'],
+        functions: true,
+      });
+      const structuredTool = await toolFunctions['stable-diffusion']();
+      expect(structuredTool).toBeInstanceOf(StructuredSD);
+      delete process.env.SD_WEBUI_URL;
+    });
+  });
+});

api/app/clients/tools/util/index.js

@@ -0,0 +1,6 @@
+const { validateTools, loadTools } = require('./handleTools');
+
+module.exports = {
+  validateTools,
+  loadTools,
+};

api/app/clients/tools/util/loadSpecs.js

@@ -0,0 +1,104 @@
+const fs = require('fs');
+const path = require('path');
+const { z } = require('zod');
+const { createOpenAPIPlugin } = require('../dynamic/OpenAPIPlugin');
+
+// The minimum Manifest definition
+const ManifestDefinition = z.object({
+  schema_version: z.string().optional(),
+  name_for_human: z.string(),
+  name_for_model: z.string(),
+  description_for_human: z.string(),
+  description_for_model: z.string(),
+  auth: z.object({}).optional(),
+  api: z.object({
+    // Spec URL or can be the filename of the OpenAPI spec yaml file,
+    // located in api\app\clients\tools\.well-known\openapi
+    url: z.string(),
+    type: z.string().optional(),
+    is_user_authenticated: z.boolean().nullable().optional(),
+    has_user_authentication: z.boolean().nullable().optional(),
+  }),
+  // use to override any params that the LLM will consistently get wrong
+  params: z.object({}).optional(),
+  logo_url: z.string().optional(),
+  contact_email: z.string().optional(),
+  legal_info_url: z.string().optional(),
+});
+
+function validateJson(json, verbose = true) {
+  try {
+    return ManifestDefinition.parse(json);
+  } catch (error) {
+    if (verbose) {
+      console.debug('validateJson error', error);
+    }
+    return false;
+  }
+}
+
+// omit the LLM to return the well known jsons as objects
+async function loadSpecs({ llm, user, message, map = false, verbose = false }) {
+  const directoryPath = path.join(__dirname, '..', '.well-known');
+  const files = (await fs.promises.readdir(directoryPath)).filter(
+    (file) => path.extname(file) === '.json',
+  );
+
+  const validJsons = [];
+  const constructorMap = {};
+
+  if (verbose) {
+    console.debug('files', files);
+  }
+
+  for (const file of files) {
+    if (path.extname(file) === '.json') {
+      const filePath = path.join(directoryPath, file);
+      const fileContent = await fs.promises.readFile(filePath, 'utf8');
+      const json = JSON.parse(fileContent);
+
+      if (!validateJson(json)) {
+        verbose && console.debug('Invalid json', json);
+        continue;
+      }
+
+      if (llm && map) {
+        constructorMap[json.name_for_model] = async () =>
+          await createOpenAPIPlugin({
+            data: json,
+            llm,
+            message,
+            user,
+            verbose,
+          });
+        continue;
+      }
+
+      if (llm) {
+        validJsons.push(createOpenAPIPlugin({ data: json, llm, verbose }));
+        continue;
+      }
+
+      validJsons.push(json);
+    }
+  }
+
+  if (map) {
+    return constructorMap;
+  }
+
+  const plugins = (await Promise.all(validJsons)).filter((plugin) => plugin);
+
+  // if (verbose) {
+  //   console.debug('plugins', plugins);
+  //   console.debug(plugins[0].name);
+  // }
+
+  return plugins;
+}
+
+module.exports = {
+  loadSpecs,
+  validateJson,
+  ManifestDefinition,
+};

api/app/clients/tools/util/loadSpecs.spec.js

@@ -0,0 +1,101 @@
+const fs = require('fs');
+const { validateJson, loadSpecs, ManifestDefinition } = require('./loadSpecs');
+const { createOpenAPIPlugin } = require('../dynamic/OpenAPIPlugin');
+
+jest.mock('../dynamic/OpenAPIPlugin');
+
+describe('ManifestDefinition', () => {
+  it('should validate correct json', () => {
+    const json = {
+      name_for_human: 'Test',
+      name_for_model: 'Test',
+      description_for_human: 'Test',
+      description_for_model: 'Test',
+      api: {
+        url: 'http://test.com',
+      },
+    };
+
+    expect(() => ManifestDefinition.parse(json)).not.toThrow();
+  });
+
+  it('should not validate incorrect json', () => {
+    const json = {
+      name_for_human: 'Test',
+      name_for_model: 'Test',
+      description_for_human: 'Test',
+      description_for_model: 'Test',
+      api: {
+        url: 123, // incorrect type
+      },
+    };
+
+    expect(() => ManifestDefinition.parse(json)).toThrow();
+  });
+});
+
+describe('validateJson', () => {
+  it('should return parsed json if valid', () => {
+    const json = {
+      name_for_human: 'Test',
+      name_for_model: 'Test',
+      description_for_human: 'Test',
+      description_for_model: 'Test',
+      api: {
+        url: 'http://test.com',
+      },
+    };
+
+    expect(validateJson(json)).toEqual(json);
+  });
+
+  it('should return false if json is not valid', () => {
+    const json = {
+      name_for_human: 'Test',
+      name_for_model: 'Test',
+      description_for_human: 'Test',
+      description_for_model: 'Test',
+      api: {
+        url: 123, // incorrect type
+      },
+    };
+
+    expect(validateJson(json)).toEqual(false);
+  });
+});
+
+describe('loadSpecs', () => {
+  beforeEach(() => {
+    jest.spyOn(fs.promises, 'readdir').mockResolvedValue(['test.json']);
+    jest.spyOn(fs.promises, 'readFile').mockResolvedValue(
+      JSON.stringify({
+        name_for_human: 'Test',
+        name_for_model: 'Test',
+        description_for_human: 'Test',
+        description_for_model: 'Test',
+        api: {
+          url: 'http://test.com',
+        },
+      }),
+    );
+    createOpenAPIPlugin.mockResolvedValue({});
+  });
+
+  afterEach(() => {
+    jest.restoreAllMocks();
+  });
+
+  it('should return plugins', async () => {
+    const plugins = await loadSpecs({ llm: true, verbose: false });
+
+    expect(plugins).toHaveLength(1);
+    expect(createOpenAPIPlugin).toHaveBeenCalledTimes(1);
+  });
+
+  it('should return constructorMap if map is true', async () => {
+    const plugins = await loadSpecs({ llm: {}, map: true, verbose: false });
+
+    expect(plugins).toHaveProperty('Test');
+    expect(createOpenAPIPlugin).not.toHaveBeenCalled();
+  });
+});

api/app/clients/tools/wolfram-guidelines.md

@@ -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.