# Working with Knowledge and Context

### How to Feed Documents, Data, and Context into a Conversation Effectively

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### Introduction

When a language model produces a response that misses the point, the instinct is to question the model. In many cases, the model is not the problem. The context is.

Context is the information you give a model to work with beyond the task instruction itself. It is the document you want summarised, the data you want analysed, the background you want the model to reason from. The quality of that context, how it is selected, structured, and presented, determines the quality of what the model can produce. A well-engineered prompt with poor context will fail. A modest prompt with precise, well-structured context will often succeed.

This tutorial covers the full spectrum of context management available to users of GLBNXT Workspace, from the simplest file attachment to enterprise-scale retrieval pipelines. That spectrum is wider than most users realise, and the right approach at any point is determined by the size of the dataset you are working with, the frequency of the task, and the level of configuration you are willing to manage.

At one end of the spectrum, a non-technical user can attach a document to a conversation in seconds using the file upload button available in both OpenWebUI and LibreChat within GLBNXT Workspace. No configuration, no setup, no technical knowledge required. That single capability covers a large proportion of everyday knowledge work tasks, and understanding how to use it well is the first priority of this tutorial.

At the other end, an organisation managing thousands of documents across multiple workflows can build an external RAG pipeline using tools such as n8n or Langflow, connecting a large, managed vector database to the model and retrieving precisely the right content for each query automatically. That capability is powerful, but it is not necessary for most users, and it is not where anyone should start.

The goal of this tutorial is to help you identify where on that spectrum your needs sit, and to give you the knowledge to work effectively at whatever tier you occupy.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.glbnxt.com/tutorials/guides/working-with-knowledge-and-context.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.