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Adding Knowledge to Custom GPTs

Unlock the potential of Custom GPTs with this comprehensive guide on incorporating expert knowledge, featuring insights from industry professionals.

Discover the transformative power of Custom GPTs by integrating expert knowledge, enhancing their functionality, and relevance. This guide provides essential strategies and insights for AI enthusiasts and developers looking to elevate their Custom GPTs.


In today's rapidly advancing AI landscape, Custom Generative Pre-trained Transformers (GPTs) stand at the forefront, offering bespoke solutions and experiences. The true power of these GPTs lies in their knowledge capacity. Integrating expert knowledge into Custom GPTs is crucial for maximizing their potential. This guide delves into effective methods for enriching Custom GPTs with specialized knowledge, drawing upon industry experiences and best practices. You have the option to upload multiple files to your custom GPT.

Understanding Custom GPTs

Custom GPTs represent a refined iteration of the broader GPT technology, designed for specific roles or sectors. These models differ from standard versions by their ability to be calibrated with unique datasets, directives, and features. The development of Custom GPTs signifies a pivotal shift in AI, championed by OpenAI's CEO, Sam Altman, paving the way for more nuanced and context-aware interactions.

The Art of Adding Knowledge to Custom GPTs

File Types for Knowledge Enrichment

Custom GPTs can be enriched with a wide range of file types, including text, document, spreadsheet, presentation, image, audio, video, compressed, code, and data files. These files can be uploaded to the Custom GPT via the knowledge tab in the configuration menu. The most optimal file formats for knowledge enrichment are .txt, .docx, .csv, .json, and .xml. These formats are well-suited for processing and can be easily converted to other formats if required or processed by the Python sandbox.

Identifying Key Knowledge Domains

Enhancing a Custom GPT begins with pinpointing the knowledge areas most pertinent to its intended function. This requires an in-depth understanding of the target audience, the problems the GPT aims to address, and the nature of content it is expected to produce. It is of great importance that the knowledge domains are well-defined and specific. This ensures that the GPT is not overloaded with excessive information, which can be counterproductive. For instance, a Custom GPT designed to assist in medical diagnosis would benefit from a knowledge base that is focused on the relevant medical fields. This would include areas such as anatomy, physiology, and pathology, as opposed to more general topics like history or geography.

Acquiring Expert Knowledge

Upon identifying the key areas, procuring authoritative and high-caliber content is essential. Sources might include scholarly articles, sector-specific reports, expert blogs, and other reputable forms of information. You can write a simple scraper which will scrape the web for you and then you can upload the data to your custom GPT after cleaning it.

Knowledge Integration Techniques

Incorporating this knowledge into Custom GPTs demands a strategic approach. For instance, constructing a robust knowledge repository, inclusive of diverse resources like articles and talks, ensures a well-rounded and informed GPT.

Expert Strategies for Knowledge Addition

Prioritizing Quality and Relevance

Accuracy and relevance are paramount in the knowledge being added. It's vital to conduct regular reviews and updates to maintain the integrity and currency of the content. This is especially important in rapidly evolving fields, such as technology and medicine.

Balancing Depth and Breadth

A comprehensive knowledge base is advantageous, yet overloading a GPT with excessive data can be counterproductive. Achieving an equilibrium between depth and breadth is crucial.

Continuous GPT Evolution

Regularly updating the GPT with new information is crucial for maintaining its efficacy and relevance in a rapidly evolving landscape.

Practical Applications and Case Studies

Real-life applications, such as those illustrated by AI applications like "Causal Mindset," showcase the successful implementation of these principles. Tailoring the GPT with specific analytical frameworks significantly boosts its capacity to deliver pertinent and insightful responses.

Overcoming Challenges in Knowledge Integration

Addressing Common Obstacles

Issues such as instruction amnesia and conversation starter variations are typical in customizing GPTs, as observed in various applications. Common obstacles include:

  • Instruction Amnesia: The GPT forgets the initial instructions and reverts to generic responses.
  • Conversation Starter Variations: The GPT responds to the same prompt with different conversation starters.
  • Inconsistent Responses: The GPT provides inconsistent responses to the same prompt.

To address these challenges, it is essential to ensure that the GPT is well-informed and calibrated with the appropriate knowledge. Think about whether the information you put into the knowledge files is relevant. On Reddit some people have reported that the limit of the knowledge files is 10. So if you have more than 10 files, you will get an error. Also, if you have more than 50MB of data, you will get an error. So make sure that you have less than 10 files and less than 50MB of data. Altough some found that the single file size limit is 25MB, and others have reported to reach the 10 file limit before reaching the 50MB limit. So it is not 100% clear what the limits are, however these estimations should be a good starting point.

Implementing Effective Solutions

Structured and clear instructional guidelines are key to mitigating these challenges, as seen in successful GPT applications.

Future Directions in Custom GPT Knowledge Augmentation

The realm of AI and Custom GPTs is continuously evolving. Anticipated trends include more sophisticated integration methods, enhanced privacy measures, and user-friendly interfaces.


Enriching Custom GPTs with expert knowledge transforms them from generic AI models to specialized tools capable of detailed tasks and intricate interactions. The experiences and insights from industry professionals offer a valuable framework for those seeking to enhance their Custom GPTs. By adhering to these practices, developers can craft GPTs that are not only well-informed but also finely tuned to the specific requirements of their users.