Spaces:
Running
Running
File size: 5,731 Bytes
aae972d 4078d88 aae972d d9e149b aae972d 54d4f10 aae972d 449442f aae972d 449442f aae972d aefc510 aae972d b3acea8 aae972d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 |
import gradio as gr
from datasets import load_dataset
from huggingface_hub import HfApi, list_repo_refs
import pandas as pd
import os
# Initialize HF API
api = HfApi(token=os.getenv("HF_TOKEN"))
def get_branches(repo_id="lvwerra/fineweb-ultra"):
"""Get all branches from the dataset repository"""
try:
refs = list_repo_refs(repo_id, repo_type="dataset", token=os.getenv("HF_TOKEN"))
branches = [branch.name for branch in refs.branches if branch.name != "main"]
# Sort branches by timestamp (newest first)
branches.sort(reverse=True)
return branches
except Exception as e:
print(f"Error fetching branches: {e}")
return []
def load_branch_data(repo_id, branch_name):
"""Load dataset from a specific branch"""
try:
dataset = load_dataset(repo_id, revision=branch_name, split="train")
return dataset
except Exception as e:
print(f"Error loading branch {branch_name}: {e}")
return None
def update_branch_dropdown():
"""Update the branch dropdown with available branches"""
branches = get_branches()
if branches:
return gr.Dropdown(choices=branches, value=branches[0], label="Select Branch")
else:
return gr.Dropdown(choices=[], value=None, label="No branches found")
def load_dataset_for_branch(branch_name):
"""Load dataset when branch is selected"""
if not branch_name:
return None, gr.Slider(maximum=0, value=0), "", ""
dataset = load_branch_data("lvwerra/fineweb-ultra", branch_name)
if dataset is None:
return None, gr.Slider(maximum=0, value=0), "Error loading dataset", "Error loading dataset"
max_samples = len(dataset) - 1
# Load first sample
sample = dataset[0]
original_text = sample.get("text", sample.get("text", "No original text found")).replace('\n', '<br>')
rephrased_text = sample.get("ultra_text", "No rephrased text found")
return dataset, gr.Slider(maximum=max_samples, value=0, step=1, label=f"Sample Index (0-{max_samples})"), original_text, rephrased_text
def update_sample(dataset, sample_idx):
"""Update the text display when slider changes"""
if dataset is None or sample_idx >= len(dataset):
return "No data available", "No data available"
sample = dataset[int(sample_idx)]
original_text = sample.get("text", sample.get("text", "No original text found")).replace('\n', '<br>')
rephrased_text = sample.get("ultra_text", "No rephrased text found")
return original_text, rephrased_text
def format_text_for_display(text, title):
"""Format text with a title for better display"""
return f"## {title}\n\n{text}"
# Create Gradio interface
with gr.Blocks(title="Dataset Branch Viewer", theme=gr.themes.Soft()) as demo:
gr.Markdown("# Dataset Branch Viewer")
gr.Markdown("Compare original and rephrased text samples from different dataset branches")
# Store dataset in state
dataset_state = gr.State(value=None)
with gr.Row():
with gr.Column(scale=1):
refresh_btn = gr.Button("🔄 Refresh Branches", variant="secondary")
branch_dropdown = gr.Dropdown(
choices=get_branches(),
value=get_branches()[0] if get_branches() else None,
label="Select Branch",
info="Choose a timestamp branch to view"
)
sample_slider = gr.Slider(
minimum=0,
maximum=0,
value=0,
step=1,
label="Sample Index",
info="Navigate through samples"
)
with gr.Row():
gr.Markdown("### Sample Info")
sample_info = gr.Markdown("Select a branch to start")
with gr.Row():
with gr.Column():
original_display = gr.Markdown(
"## Original Text\n\nSelect a branch and sample to view content",
label="Original Text"
)
with gr.Column():
rephrased_display = gr.Markdown(
"## Rephrased Text\n\nSelect a branch and sample to view content",
label="Rephrased Text"
)
# Event handlers
refresh_btn.click(
fn=update_branch_dropdown,
outputs=[branch_dropdown]
)
branch_dropdown.change(
fn=load_dataset_for_branch,
inputs=[branch_dropdown],
outputs=[dataset_state, sample_slider, original_display, rephrased_display]
)
sample_slider.change(
fn=update_sample,
inputs=[dataset_state, sample_slider],
outputs=[original_display, rephrased_display]
)
# Update sample info when slider changes
def update_sample_info(dataset, sample_idx):
if dataset is None:
return "No dataset loaded"
total_samples = len(dataset)
current_sample = int(sample_idx)
sample = dataset[current_sample]
sample_id = sample.get("id", "Unknown")
return f"**Sample {current_sample + 1} of {total_samples}** | ID: `{sample_id}`"
sample_slider.change(
fn=update_sample_info,
inputs=[dataset_state, sample_slider],
outputs=[sample_info]
)
# Load initial data if branches exist
initial_branches = get_branches()
if initial_branches:
demo.load(
fn=load_dataset_for_branch,
inputs=[gr.State(initial_branches[0])],
outputs=[dataset_state, sample_slider, original_display, rephrased_display]
)
# Launch the app
if __name__ == "__main__":
demo.launch() |