[Bug]: Application crashes with "MemoryError" when processing >1GB CSV files

The application fails to process large CSV datasets. When attempting to upload a file larger than 1GB via the data import tool, the spinner loads for 10 seconds, and then the application crashes entirely, forcing a restart of the local server.

Steps to Reproduce
Launch the application (npm start).

Navigate to the Import Data tab.

Click Upload CSV.

Select a .csv file larger than 1GB (e.g., large_dataset.csv).

Click Process.

Expected Behavior
The file should process in chunks (streaming), or a progress bar should appear. If the file is too large, a user-friendly error message ("File too large") should be displayed instead of a hard crash.

Actual Behavior
The UI freezes, and the backend process terminates with a fatal Python error.

Screenshots/Logs
Console Output:

Plaintext

Processing file...
Traceback (most recent call last):
File "data_loader.py", line 42, in load_data
df = pd.read_csv(file_path)
pandas.errors.ParserError: Error tokenizing data. C error: MemoryError
[Process exited with code 1]
Environment
OS: Windows 11 Pro / macOS Sequoia 15.1

Browser: Chrome 120.0

Version: v2.4.1

Python Version: 3.11

Possible Solution (Optional)
It looks like we are loading the entire dataframe into memory using pandas.read_csv(). We should probably switch to chunksize=1000 to handle large files or stream the data.

Additional Context
This issue does not occur with files smaller than 500MB.

Start in data_loader.py at line 42 and reproduce the failure with npm start using a CSV larger than 1GB. Review how pandas.read_csv() handles the import and determine the project-supported behavior for oversized files. Done means large files no longer terminate the backend, and an appropriate user-facing outcome is verified for the import flow.