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The Knowledge Base feature allows you to upload and connect your data sources and ask questions about your documents.

Getting started

Retrieval-Augmented Generation (RAG) is a technique that enhances Large Language Models (LLMs) by allowing them to access and incorporate external knowledge sources, like databases or documents, to generate more accurate and contextually relevant responses.  TypingMind supports a built-in RAG system with the Knowledge Base feature. You can upload files to TypingMind and then allow AI agents to access these files and get more context to answer your questions more accurately during the conversation. Image

Upload your files

  • Open TypingMind, then click the “KB” (Knowledge Base) tab.
  • Click Add Data Source and start uploading your files.
  • Currently supported files are: Text files, PDF, CSV, Excel, Word. We will continue to support more file types.
Xnapper 2025 03 18 07 51 38 You can tag your documents to be used by AI agents later. This helps you split your KB into different topics/categories that can later be used by different AI agents. Xnapper 2025 03 18 08 00 52

Connect External Sources

Beside uploading your internal documents, you can also connect other sources such as Github, Notion, Google Drive or Web Scraping. Click on the source you want to connect and follow the prompts to complete connecting the expected sources.
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Use Knowledge Base in Chat

You will need to toggle the Knowledge Base access button within the message area to enable knowledge base access for your chat. Image 2 1

1. Direct chat

You can access knowledge base by initiating a conversation with any AI models. Just need to ask questions related to your data and the system will help look up relevant information to provide answer.
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2. Access via Agent

Once the data is uploaded, assign the KB access to your AI agents by going to Agents → Edit or create an AI agent → Knowledge Base Access
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By default, AI agents don’t have access to Knowledge Base. You can set the AI agent to be able to:
  • Access all data in the knowledge base
  • Access only documents with specific tags
Note:
  • If you set multiple tags, the agent will have access to documents that have any of the tags assigned (OR condition used for tags matching).
  • Tags are identified by their name. If you later change the tag of the documents from KB, you need to update it again in the AI agent setting.

Connect Your Own Knowledge Base

RAG has been supported by TypingMind for a long time. Knowledge Base is just a built-in integration to make it easier for users. You can connect TypingMind with your own knowledge base by doing the following:
  • Use a plugin (or create a new one): Provide a way for the AI agents to look up additional information when needed
  • Use Dynamic Context: This provides AI agents with context about what kind of data they have access to, so if they need to look up additional information, they can trigger a plugin. This will improve retrieval performance and accuracy. Dynamic Context can also be embedded directly into the plugin with Plugin Context (you will see this section when creating new plugins in TypingMind).
To decide if you want to use TypingMind’s built-in Knowledge Base system or connect your own, here is a quick pros and cons comparison:

Compare with Training Files

Knowledge Base and Training Files are two different ways to add context to an AI agent. We recommend experimenting with both options to achieve the best result. For your reference, here are some key differences: For a full comparison, see this page: Training Files vs Knowledge Base

Limitations

KB is available for free for all licensed users with the following limitations:
  • The supported data source currently is File Upload, Google Drive, Notion, GitHub, Web Scraping. More data sources soon.
  • Supported file types for File Upload: Text files, PDF, CSV, Excel, Word
  • The Knowledge Base limit is based on your TypingMind Cloud plan. This means there’s no restriction on the number of documents you can upload — it depends on the available cloud storage in your account.
Note that these limitations can change in the future.

Frequently Asked Questions

What are the underlying embedding models and techniques? We use the best embedding models and chunking techniques, combined with our own private methods to ensure the best retrieval quality possible. We don’t publish the details on the underlying models, chunk size, embedding dimensions, etc. because it can be outdated very quickly as we upgrade the system continuously. What types of files are supported? Text files, PDF, CSV, Excel, Word, and we are adding more soon. How much can I upload or connect? The Knowledge Base limit is based on your TypingMind Cloud plan. This means there’s no restriction on the number of documents you can upload — it depends solely on the available cloud storage in your account. Is there a plan to add connections to more external sources? Yes! We will add them very soon. Is this the same system used in the TypingMind Team (Custom) version? It is mostly the same, but for the TypingMind Team version we have some other processing logic and optimizations for better use in team contexts.

Connect your own knowledge base

Connect to LlamaIndex