> For the complete documentation index, see [llms.txt](https://docs.uptiq.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.uptiq.ai/ai-workbench-qore/console/knowledge/document-processing.md).
# Document processing
Review how Qore extracts, structures, tags, and summarizes each document.
Qore extracts text, identifies sections, applies tags, and creates a summary for each document. Review these results to confirm that agents can retrieve the right information.
Use document processing when an answer is incomplete or inaccurate. Check it before syncing important files.
### Inspect a document
Open a knowledge base and select a document. Then choose an inspection view.
{% hint style="info" %}
**Review before sync.** A warning indicator identifies a document that needs attention, such as a failed sync.
{% endhint %}
* Select **Content** to review sections and chunks.
* Select **Tags**, **Raw extraction**, or **Summary** to investigate a specific issue.
* Open a dataset file with **⋮** → **View extracted content**.
{% columns %}
{% column %}
**Check structure**
Review **Content** and **Tags** when answers miss or confuse a topic.
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**Check source text**
Review **Raw extraction** when the file itself was read incorrectly.
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{% tabs %}
{% tab title="Content" %}
### Content
**Content** lists the sections Qore found in document order. Each section shows its chunk count. Select a section to review its extracted text and tags.
Retrieval uses this structure to locate relevant content. Clear, complete sections produce more accurate answers.
{% hint style="warning" %}
If an expected section is missing, or topics are merged, retrieval cannot recover them. Upload a corrected file, then sync it.
{% endhint %}
{% endtab %}
{% tab title="Tags" %}
### Tags
**Tags** label the document and its sections. They use the format `NAMESPACE:VALUE`. The namespace identifies the type of information.
| Namespace | What it identifies |
| --------------- | ---------------------------------- |
| `DOCUMENT_TYPE` | The whole document |
| `SECTION_TYPE` | A chunk's location in the document |
| `CONTENT_TYPE` | What a chunk contains |
| `FORMAT_TYPE` | How content is organized |
| `TIME_PERIOD` | The time span a chunk references |
Tags apply to individual chunks, not only to the document. A chunk can carry several tags that describe its document, position, meaning, and format.
* `SECTION_TYPE` identifies where a chunk appears in the document.
* `CONTENT_TYPE` identifies what a chunk is about.
Hover over a truncated tag to view its full value. You cannot add or edit tags in these views. Qore regenerates them during sync.
{% hint style="info" %}
The available namespaces vary by document type. The table describes common namespaces, not a fixed set.
{% endhint %}
{% endtab %}
{% tab title="Raw extraction" %}
### Raw extraction
**Raw extraction** contains the plain text Qore read before it created sections. Page breaks appear as `[PAGE 1]`. Select **Download** to save the extracted text.
Use this view when text is garbled, a scanned page has no text, or a table lost its structure. Problems here affect every later stage. Upload a better source file, then sync it. See [Sync & versions](/ai-workbench-qore/console/knowledge/sync-and-versions.md).
{% hint style="info" %}
Use **Raw extraction** for this review. The **Preprocessed Files** view is no longer available.
{% endhint %}
{% endtab %}
{% tab title="Summary" %}
### Summary
**Summary** provides a short description of the whole document. Use it as a quick check that Qore processed the expected content.
If the summary covers the wrong subject or omits part of the file, confirm the source in **Raw extraction**.
{% endtab %}
{% endtabs %}
### When you sync again
Qore regenerates the table of contents, tags, and summary during sync. **Force re-sync everything** replaces existing processing results. It does not merge them.
### Related
| Title | Description | Target |
|---|
| Knowledge | Create knowledge bases, query them, and attach them. | Knowledge |
| Knowledge Datasets | Manage the source files Qore processes. | Datasets |
| Sync & versions | Sync file updates and review knowledge versions. | Sync & versions |
| Try Knowledge | Inspect the chunks and tags behind an answer. | Try Knowledge |
| Knowledge & Context | Why agents search your knowledge instead of reading all of it. | Knowledge & Context |
***
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Maintained by Abhishek Paul
AI-assisted, human-approved
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---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.
Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:
```
GET https://docs.uptiq.ai/ai-workbench-qore/console/knowledge/document-processing.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.
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.
