EuriBot UI

The Euricom AI chat app for all your Euricom needs.

Usage Info

Assistant

• When chatting, the entire chat history is taken in account, so try not to switch subject to much in a single chat.
• It will sometimes not find the information, even though it has access to it.
  • Try to rewrite the prompt so it can search more specifically.
  • Try starting a new chat so the entire history is not given as context.

Generating Files

• json:
  • Price: cheaper (1960 tokens)
  • The AI writes his own text using the data
  • Speed: normal
  • Quality: Good. Most test questions were answered correctly, but sometimes the data was not found.
• PDF en TXT:
  • Price: more expensive (pdf: 4256 tokens en txt: 4267 tokens)
  • The AI only writes his own text when necessary. Otherwise just answers text from the file
  • Speed: fast
  • Quality: Good. Most test questions were answered correctly, but sometimes the data was not found.

Quick Start

Follow these steps to get your own Euricom Chatbot UI instance running locally.

# install dependencies
npm install

# start the app locally (development)
npm run dev

# db handling
npm run db-reset
npm run db-migrate
npm run db-types,
npm run db-pull
npm run db-push

Chatbot UI - Original version

This is a fork of the original Chatbot UI project. The original project can be found here.

Use Chatbot UI without having to host it yourself!

Find the official hosted version of Chatbot UI here.

Local Quickstart

Follow these steps to get your own Chatbot UI instance running locally.

You can watch the full video tutorial here.

1. Clone the Repo

git clone https://github.com/Euricom/euricom-gpt.git

2. Install Dependencies

Open a terminal in the root directory of your local Chatbot UI repository and run:

npm install

3. Install Supabase & Run Locally

Why Supabase?

Previously, we used local browser storage to store data. However, this was not a good solution for a few reasons:

• Security issues
• Limited storage
• Limits multi-modal use cases

We now use Supabase because it's easy to use, it's open-source, it's Postgres, and it has a free tier for hosted instances.

We will support other providers in the future to give you more options.

1. Install Docker

You will need to install Docker to run Supabase locally. You can download it here for free.

2. Install Supabase CLI

MacOS/Linux

brew install supabase/tap/supabase

Windows

scoop bucket add supabase https://github.com/supabase/scoop-bucket.git
scoop install supabase

3. Start Supabase

In your terminal at the root of your local Chatbot UI repository, run:

supabase start

4. Fill in Secrets

1. Environment Variables

In your terminal at the root of your local Chatbot UI repository, run:

cp .env.local.example .env.local

Get the required values by running:

supabase status

Note: Use API URL from supabase status for NEXT_PUBLIC_SUPABASE_URL

Now go to your .env.local file and fill in the values.

If the environment variable is set, it will disable the input in the user settings.

2. SQL Setup

In the 1st migration file supabase/migrations/20240108234540_setup.sql you will need to replace 2 values with the values you got above:

• project_url (line 53): http://supabase_kong_chatbotui:8000 (default) can remain unchanged if you don't change your project_id in the config.toml file
• service_role_key (line 54): You got this value from running supabase status

This prevents issues with storage files not being deleted properly.

5. Install Ollama (optional for local models)

Follow the instructions here.

6. Run app locally

In your terminal at the root of your local Chatbot UI repository, run:

npm run chat

Your local instance of Chatbot UI should now be running at http://localhost:3000. Be sure to use a compatible node version (i.e. v18).

You can view your backend GUI at http://localhost:54323/project/default/editor.

Hosted Quickstart

Follow these steps to get your own Chatbot UI instance running in the cloud.

Video tutorial coming soon.

1. Follow Local Quickstart

Repeat steps 1-4 in "Local Quickstart" above.

You will want separate repositories for your local and hosted instances.

Create a new repository for your hosted instance of Chatbot UI on GitHub and push your code to it.

2. Setup Backend with Supabase

1. Create a new project

Go to Supabase and create a new project.

2. Get Project Values

Once you are in the project dashboard, click on the "Project Settings" icon tab on the far bottom left.

Here you will get the values for the following environment variables:

• Project Ref: Found in "General settings" as "Reference ID"

• Project ID: Found in the URL of your project dashboard (Ex: https://supabase.com/dashboard/project//settings/general)

While still in "Settings" click on the "API" text tab on the left.

Here you will get the values for the following environment variables:

• Project URL: Found in "API Settings" as "Project URL"

• Anon key: Found in "Project API keys" as "anon public"

• Service role key: Found in "Project API keys" as "service_role" (Reminder: Treat this like a password!)

3. Configure Auth

Next, click on the "Authentication" icon tab on the far left.

In the text tabs, click on "Providers" and make sure "Email" is enabled.

We recommend turning off "Confirm email" for your own personal instance.

4. Connect to Hosted DB

Open up your repository for your hosted instance of Chatbot UI.

In the 1st migration file supabase/migrations/20240108234540_setup.sql you will need to replace 2 values with the values you got above:

• project_url (line 53): Use the Project URL value from above
• service_role_key (line 54): Use the Service role key value from above

Now, open a terminal in the root directory of your local Chatbot UI repository. We will execute a few commands here.

Login to Supabase by running:

supabase login

Next, link your project by running the following command with the "Project ID" you got above:

supabase link --project-ref <project-id>

Your project should now be linked.

Finally, push your database to Supabase by running:

supabase db push

Your hosted database should now be set up!

3. Setup Frontend with Vercel

Go to Vercel and create a new project.

In the setup page, import your GitHub repository for your hosted instance of Chatbot UI. Within the project Settings, in the "Build & Development Settings" section, switch Framework Preset to "Next.js".

In environment variables, add the following from the values you got above:

• NEXT_PUBLIC_SUPABASE_URL
• NEXT_PUBLIC_SUPABASE_ANON_KEY
• SUPABASE_SERVICE_ROLE_KEY
• NEXT_PUBLIC_OLLAMA_URL (only needed when using local Ollama models; default: http://localhost:11434)

You can also add API keys as environment variables.

• OPENAI_API_KEY
• AZURE_OPENAI_API_KEY
• AZURE_OPENAI_ENDPOINT
• AZURE_GPT_45_VISION_NAME

For the full list of environment variables, refer to the '.env.local.example' file. If the environment variables are set for API keys, it will disable the input in the user settings.

Click "Deploy" and wait for your frontend to deploy.

Once deployed, you should be able to use your hosted instance of Chatbot UI via the URL Vercel gives you.