Buckets

Buckets are simple data container. Think of them as simple folders that can contain files. They are the basic unit of storage in Knowledgio and are used to store data and read data.

You can create Chatbots trained on your data, which can be stored in buckets. You can also use the data in buckets to enrich your data with AI.

Every file in a bucket will be indexed and can be searched by the chatbot or query.

Besides the actual content of the file, the following metadata can be stored for each file.

Metadata

• author
• title
• date
• tags
• source
• geo
• contentType

Buckets and AI

Because documents in buckets are mostly used with AI, you do not have to structure your data in a specific way. You can just upload your data and start using it with AI.

Of course, the more information you provide in your document, the better.

Create a bucket

To create a bucket, you can navigate to the buckets page and click on the "Add bucket" button.

Delete a bucket

To delete a bucket, you can navigate to the buckets page and click on the "Delete" button.

Upload a file

To upload a file, you can navigate to the buckets page, select the bucket you want to upload the file to and click on the "New File" button.

Delete a file

To delete a file, you can navigate to the buckets page, select the bucket you want to delete the file from and click on the "Delete" button.

Delete all files

To delete all files, you can navigate to the buckets page, select the bucket you want to delete the files from and click on the "Reset all" button.

Note that this will delete all files in the bucket, but will not delete the bucket itself. Also it might take a while to complete, but you can leave the page and come back later.

API Reference

You can integrate Knowledgio into your own application by using the API. To add documents to your bucket, you can navigate to your bucket and click on the "API" button.

Authentication

To authenticate with the API, you need to provide your API key in the Authorization header.

To get an API key go to your workspace settings and generate an API Key.

Instructions

Navigate to the bucket you want to send documents to, click on the "API" button.

You will see instructions for JavaScript.

The endpoint currently supports adding documents to a bucket. You can specify the title and the content of the document.

Example

const { data } = await fetch(
  "https://europe-west3-knowledgio-prod.cloudfunctions.net/api/v1/buckets/[bucket id]/docs",
  {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      Authorization: "Bearer [API_KEY]",
    },
    body: JSON.stringify({
      title: "Hello World",
      text: "This is a sample text",
    }),
  }
);