MindsDB enables you to build a chatbot, train it using your data, and integrate it into a chat application. All of this can be achieved through a user-friendly interface that doesn’t require coding.
This guide will walk you through the process of building and training a chatbot using MindsDB’s LLM UI.
To access the LLM UI, click on the robot icon on the left menu. You’ll see a welcome screen.
Click on Create AI Agent to start.
There are three tabs that ask for information to build your chatbot:
Let’s go over all the tabs in detail.
In the Settings tab, you can provide information about engine and model that you want to use.
Currently, we offer OpenAI models that require you to provide an API key.
Optionally you can provide data in form of a URL to be used for training the chatbot.
Click Save to create, train, and deploy the chatbot.
On completion, you’ll see the Model saved
message as below.
In the Prompt tab, you can set up a prompt message to give general directions to the chatbot. You can also define the temperature
and max_tokens
values that affect responses.
Low temperature
values indicate that the model takes fewer risks and completions are more accurate and deterministic. On the other hand, high temperature
values result in more diverse completions. And max_tokens
value should be as close to the expected response size as possible.
Now we are ready to talk with the chatbot.
The right half of the screen is a chat interface where you can submit messages and receive replies.
Now you can tweak the prompt parameters and test the responses.
You can integrate this chatbot into chat applications.
Currently, we support the Slack app.
In the Publish tab, click on the Connect button.
Publishing the chatbot to Slack requires two tokens: Bot User OAuth Token
and App-Level Token
.
Follow the instructions below to set up the Slack app and generate required tokens.
From scratch
or select an existing app.
From scratch
.From an app manifest
, please follow the Slack docs here.socket
and add the connections:write
scope.xapp-...
token - you’ll need it to publish the chatbot.xoxb-...
token - you’ll need it to publish the chatbot.message.im
.Use tokens generated in points 3 and 5 to publish the chatbot to Slack.
Now you can talk with the chatbot on Slack by directly messaging the app you created and configured with the above steps.
MindsDB enables you to build a chatbot, train it using your data, and integrate it into a chat application. All of this can be achieved through a user-friendly interface that doesn’t require coding.
This guide will walk you through the process of building and training a chatbot using MindsDB’s LLM UI.
To access the LLM UI, click on the robot icon on the left menu. You’ll see a welcome screen.
Click on Create AI Agent to start.
There are three tabs that ask for information to build your chatbot:
Let’s go over all the tabs in detail.
In the Settings tab, you can provide information about engine and model that you want to use.
Currently, we offer OpenAI models that require you to provide an API key.
Optionally you can provide data in form of a URL to be used for training the chatbot.
Click Save to create, train, and deploy the chatbot.
On completion, you’ll see the Model saved
message as below.
In the Prompt tab, you can set up a prompt message to give general directions to the chatbot. You can also define the temperature
and max_tokens
values that affect responses.
Low temperature
values indicate that the model takes fewer risks and completions are more accurate and deterministic. On the other hand, high temperature
values result in more diverse completions. And max_tokens
value should be as close to the expected response size as possible.
Now we are ready to talk with the chatbot.
The right half of the screen is a chat interface where you can submit messages and receive replies.
Now you can tweak the prompt parameters and test the responses.
You can integrate this chatbot into chat applications.
Currently, we support the Slack app.
In the Publish tab, click on the Connect button.
Publishing the chatbot to Slack requires two tokens: Bot User OAuth Token
and App-Level Token
.
Follow the instructions below to set up the Slack app and generate required tokens.
From scratch
or select an existing app.
From scratch
.From an app manifest
, please follow the Slack docs here.socket
and add the connections:write
scope.xapp-...
token - you’ll need it to publish the chatbot.xoxb-...
token - you’ll need it to publish the chatbot.message.im
.Use tokens generated in points 3 and 5 to publish the chatbot to Slack.
Now you can talk with the chatbot on Slack by directly messaging the app you created and configured with the above steps.