Why is my Gem ignoring the provided knowledge base in the attached files?

Understanding Why Your WordPress Plugin Is Ignoring Attached Knowledge Base Files: A Guide for Developers and Enthusiasts

In the rapidly evolving landscape of AI-driven tools and integrations, it’s common to encounter situations where a plugin or feature does not behave as expected. One such scenario involves a WordPress plugin—particularly a custom or third-party “Gem”—that is designed to utilize attached knowledge base files to answer user queries more accurately. However, users often observe that despite providing a well-formatted knowledge file, the plugin seems to ignore it, leading to incorrect or hallucinated responses.

This article aims to elucidate the common causes behind such issues and offer best practices to ensure your plugin correctly reads and utilizes attached knowledge sources.

Understanding the Issue

A typical user scenario involves creating a plugin or extension that references a knowledge base—often a Markdown or plain text file in UTF-8 encoding—to answer questions related to a specific domain, such as personal asset details. Despite meticulous formatting and placement of the file, the plugin may ignore this knowledge and produce hallucinated or inaccurate outputs.

Key Symptoms:
– The plugin responds with fabricated information unrelated to the provided data.
– It acknowledges the knowledge base but does not incorporate its content into responses.
– Persistent ignoring of instructions that designate the knowledge base as an “absolute truth source.”

Common Causes

1. Incorrect File Path or Attachment Method
   Ensure that the file is correctly uploaded and linked within the plugin’s configuration. Relative or absolute paths must be correct, and the plugin must have permission to access the file’s location.

2. Inadequate Parsing or Processing of the File
   The plugin might not be parsing your Markdown or text files properly. Verify that the plugin supports the specific format, encoding, and structure of your knowledge base.

3. Lack of Proper Context Injection
   Many plugins rely on prompts or context injection to incorporate knowledge bases effectively. If the plugin’s prompt design doesn’t explicitly tell it to prioritize this data, it may ignore it or treat it as background noise.

4. Response Formatting and Instruction Clarity
   When instructing the plugin to treat the knowledge base as the sole truth source, clarity in the instructions is paramount. Ambiguous or insufficient instructions may lead the plugin to default to other sources or hallucinate.

5. Limitations of the AI Model or Plugin Configuration
   Some AI models or plugins may have constraints on how they prioritize external data. If the feature is not