Add truncate_headers parameter to Dataframe to improve header text control

[hannahblair]

Description

Adds a truncate_headers param to allow for better control over how the headers behave. Set to default to True for backwards compatibility.

Closes: #11929

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🦄 change detected

This Pull Request includes changes to the following packages.

Package	Version
@gradio/dataframe	patch
gradio	patch

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• Add truncate_headers parameter to Dataframe to improve header text control

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[freddyaboulton]

Looks good to me @hannahblair ! What if this parameter can also take a list of column names to give developers even more control as opposed to all headers are truncated or none are?

[freddyaboulton]

Let's also add to docstring

[abidlabs]

Thanks @hannahblair! This helps for sure, see previous (top) vs. current (bottom):

But it doesn't completely solve the issue, because cell values are still being truncated, see the first column. This leads to ambiguity since all of the values appear to be the same, and there's no way to see the full value in each cell.

I guess my question is why is this truncating happening at all? If we don't specify column widths, I thought the behavior is that the columns should take up as much width as they need to fit the content, especially given that the dataframe already has horizontal scrolling, so there's no need for columns to truncate the inner values to fit some arbitrary width.

Code to repro:

import gradio as gr
import pandas as pd

data = {
    "Name": ["test-run-v1", "test-run-v2", "test-run-v3"],
    "Username": ["abidlabs_user1", "abidlabs_user2", "abidlabs_user3"],
    "Created": ["about 30 minutes ago", "about 30 minutes ago", "about 30 minutes ago"],
    "epoch": [20, 20, 20],
    "learning_rate": [0.001, 0.001, 0.001],
    "batch_size": [32, 32, 32],
    "max_position_embeddings": [32768, 32768, 32768],
    "hidden_size": [896, 896, 896],
    "intermediate_size": [4864, 4864, 4864],
    "optimizer": ["adam with warmup schedule", "adam with warmup schedule", "adam with warmup schedule"],
    "dataset": ["custom-text-dataset-v1", "custom-text-dataset-v1", "custom-text-dataset-v1"],
    "status": ["running (ETA ~2h)", "completed successfully", "failed at step 1200"],
}

df = pd.DataFrame(data)

def show_table():
    return df

with gr.Blocks() as demo:
    gr.Markdown("## Experiment Runs Overview")
    gr.Dataframe(
        value=show_table(),
        interactive=False,
        label="Training Configurations and Status",
        truncate_headers=False
    )

demo.launch()