# Learning Packs
**Learning Packs** in ShyftSearch are used to **extract specific directories, files, and fields** from your source cloud storage or raw event logs. They allow you to define patterns and rules for retrieving only the data you need, enabling more efficient log processing and structured analysis.
#### **Key Fields in a Learning Pack**
* **Path Match Patterns**
* Defines **which types of files to extract from the source** using regex patterns. Only files that match these patterns are included in the dataset for processing.
* **Path Extracts**
* In this field, you define **regex patterns to extract files from specific paths along with their filenames**, ensuring accurate identification and organization of log files within the system.
* **Event Types**
* Dropdown to select the type of events present in your logs. Choose **single event type** if all logs are uniform, or **multiple event types** if your raw logs contain different event categories.
* **Event Type Definitions**
* Defines how to **extract fields from log events using regular expressions (regex)**. Multiple regex patterns can be defined if your logs contain multiple event types, allowing precise extraction of all relevant fields.
* **Event Time Field**
* **Timestamp Format**
#### ⚙️ **Steps to create a new Learning Pack**
{% stepper %}
{% step %}
Navigate to the **Configuration** drop-down in the top navigation bar and select **Learning Pack option**.
{% endstep %}
{% step %}
Click on the  button to create a new learning pack.
{% endstep %}
{% step %}
Fill in all the required fields such as *Path Match Patterns*, *Path Extracts*, *Event Types*, and *Event Type Definitions etc*.
{% endstep %}
{% step %}
Once all details are entered, click **Insert Learning Pack button** to create a Learning Pack.
{% endstep %}
{% endstepper %}
---
# 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://supercloudnow.gitbook.io/supercloudnow-docs/undefined/usage-guide/configuration/learning-packs.md?ask=
```
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.