Smart Chatbot UI

This repo is forked from chatbot-ui.

This repository is highly experimental, so please do not expect compatibility when performing updates.

DEMO

• Do not input personal information.
• Conversation, prompts, folders are stored in mongodb.
• Streaming response is not working in vercel environment.
• Plugins are not working for vercel timeout limitation.

Additional Features

• SSO Auth(Google, GitHub)
• ChatGPT compatible plugins
• Python Interpreter Plugin
• Persitent storage(MongoDB)
• IME support

Updates

• Chatbot UI will be updated over time.
• Expect frequent improvements.

Recent updates:

• [x] Python Interpreter (5/8/23)
• [x] Multiple Users with MongoDB Support (4/19/23)
• [x] Plugins(ChatGPT compatible) (4/17/23)
• [x] SSO Auth(email pattern matching only) (4/15/23)
• [x] Prompt templates (3/27/23)
• [x] Regenerate & edit responses (3/25/23)
• [x] Folders (3/24/23)
• [x] Search chat content (3/23/23)
• [x] Stop message generation (3/22/23)
• [x] Import/Export chats (3/22/23)
• [x] Custom system prompt (3/21/23)
• [x] Error handling (3/20/23)
• [x] GPT-4 support (access required) (3/20/23)
• [x] Search conversations (3/19/23)
• [x] Code syntax highlighting (3/18/23)
• [x] Toggle sidebar (3/18/23)
• [x] Conversation naming (3/18/23)
• [x] GitHub flavored markdown (3/18/23)
• [x] Add OpenAI API key in app (3/18/23)
• [x] Markdown support (3/17/23)

Deploy

Docker

Setup enviroment variables:

cp .env.local.example .env.local
# specify OPENAI_API_KEY, MONGODB_URI, MONGO_INITDB_ROOT_USERNAME, MONGO_INITDB_ROOT_PASSWORD
vim .env.local

Run with docker-compose:

docker compose up -d

Running Locally

1. Clone Repo

git clone https://github.com/dotneet/smart-chatbot-ui.git

2. Install Dependencies

npm i

3. Provide OpenAI API Key

Create a .env.local file in the root of the repo with your OpenAI API Key:

cp .env.local.example .env.local
# Specify OPENAI_API_KEY
vim .env.local

You can set OPENAI_API_HOST where access to the official OpenAI host is restricted or unavailable, allowing users to configure an alternative host for their specific needs.

Additionally, if you have multiple OpenAI Organizations, you can set OPENAI_ORGANIZATION to specify one.

4. Run MongoDB

docker compose -f docker-compose.dev.yml up -d

5. Run App

npm run dev

6. Use it

You should be able to start chatting.

Configuration

When deploying the application, the following environment variables can be set:

If you do not provide an OpenAI API key with OPENAI_API_KEY, users will have to provide their own key. If you don't have an OpenAI API key, you can get one here.

API Pricing Configuration

In order to track the consumption of the OpenAI API in USD, it is necessary to configure the current pricing rates for the API. This can be accomplished by updating the llmPriceRate collection in MongoDB and adjusting the values for promptPriceUSDPer1000 and completionPriceUSDPer1000 for each model.

Here is an example document for the gpt-3.5-turbo model:

{
    modelId: "gpt-3.5-turbo",
    promptPriceUSDPer1000: 0.0015,
    completionPriceUSDPer1000: 0.002  
}

To identify the model IDs available, you can refer to the /types/openai.ts file. By updating the pricing rates in this manner, you can ensure accurate tracking of API consumption and associated costs in USD.

Initial Database Configuration

In the process of initializing MongoDB on Docker, it is possible to configure the API rate pricing by utilizing environment variables. These variables should be appropriately named, taking into account the specific model and the corresponding prompt or completion price. The prescribed format for naming these variables is as follows: MODEL_PRICING_1000_${PROMPT || COMPLETION}_${MODEL_ID} = VALUE

For instance, let's consider an example that demonstrates the configuration for the gpt-3.5-turbo model:

MODEL_PRICING_1000_PROMPT_gpt-3.5-turbo=0.002
MODEL_PRICING_1000_COMPLETION_gpt-3.5-turbo=0.002

Monthly consumption limit

To set a monthly consumption limit for users, follow these steps:

• Set a general user monthly limit in USD by configuring the environment variable DEFAULT_USER_LIMIT_USD_MONTHLY.
• Alternatively, you can set a specific limit for individual users by modifying their respective records in the database. Set the value of users.monthlyUSDConsumptionLimit to the desired amount.

Per-user limit takes precedence over the general limit.

Plugin Settings

ChatGPT compatible plugin

You can add a ChatGPT compatible plugin to urls field in plugins.json.

Internal Tools

You can control the tools you want to use with the environment variable PLUGINS_INTERNAL.

Supported Internal Tools

• wikipedia_search
• google_search
• python_interpreter

Python Interpreter

Recommended for use with GPT-4

To enable python interpreter, you need to specify codeapi endpoint to PYTHON_INTERPRETER_BACKEND in .env.local and add python_interpreter to PLUGINS_INTERNAL.

# ex.
PLUGINS_INTERNAL=wikipedia_search,google_search,python_interpreter
PYTHON_INTERPRETER_BACKEND=http://localhost:8080/api/run

Vercel

• streaming response is not supported in vercel.
• plugin executing fails because of the timeout limit is too short in free plan.

Contact

If you have any questions, feel free to reach out to me on Twitter.