> ## Documentation Index
> Fetch the complete documentation index at: https://futureagi.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Upload a File

> You can import datasets by uploading structured files in **JSON** or **CSV** formats. This method is useful for quickly bringing in external data while ensuring proper schema detection and validation.

## **Steps to Upload a File**

<img src="https://mintcdn.com/futureagi/nAtaiMUdf1A9lM5m/future-agi/get-started/dataset/adding-dataset/upload_csv.png?fit=max&auto=format&n=nAtaiMUdf1A9lM5m&q=85&s=c31d7475af7dc6c9e7bbc4141bbf2234" alt="upload_csv" width="3839" height="2040" data-path="future-agi/get-started/dataset/adding-dataset/upload_csv.png" />

1. **Open the Dataset Panel**
   * Click on **"Add Dataset"** from the **Datasets & Experiments** dashboard.
   * A panel will open on the right side with multiple dataset creation options.
2. **Select the "Upload a File" Option**
   * Scroll down and click on **"Upload a file (JSON/CSV)"**.
   * This opens a file upload modal.
3. **Enter Dataset Name**
   * In the popup, you will see a text field labeled **"Name"**.
   * Enter a clear, descriptive name for your dataset.
4. **Upload the File**
   * Drag and drop your JSON or CSV file into the upload box.
   * Alternatively, click **"Browse"** to select a file from your system.
5. **Confirm and Submit**
   * After selecting your file, click **"Done"** to complete the process.
   * The system will process the file, validate data types, and structure the dataset accordingly.

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### **Best Practice**

* Ensure your **CSV file has headers** for proper column recognition.
* If using JSON, structure your data in a **consistent key-value format**.
* Verify that **all required fields** are present before uploading.
* Keep **file sizes manageable** to prevent long processing times.

By following these steps, you can quickly upload and organise datasets in Future AGI for prompt engineering, evaluation, and experimentation.

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