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import gradio as gr
import pandas as pd
import io
from huggingface_hub import HfApi, HfFolder, Repository
import os
# Global state
df = pd.DataFrame()
def upload_csv(file):
global df
df = pd.read_csv(file.name)
if "text" not in df.columns or "label" not in df.columns:
return gr.update(visible=False), "CSV must contain 'text' and 'label' columns."
# Fill label column if empty
df["label"] = df["label"].fillna("")
# Return the editable table
return gr.Dataframe(
value=df,
headers=["text", "label"],
interactive=True,
label="Edit labels below"
), "File uploaded successfully."
def save_edits(updated_table):
global df
df = pd.DataFrame(updated_table, columns=["text", "label"])
return "Changes saved."
def download_csv():
# Create a downloadable CSV
csv_bytes = df.to_csv(index=False).encode()
return gr.File.update(value=io.BytesIO(csv_bytes), filename="annotated_data.csv")
def push_to_hub(repo_name, hf_token):
# Authenticate and push to Hugging Face Hub
repo_url = f"https://huggingface.co/datasets/{repo_name}"
local_path = f"./{repo_name}"
if os.path.exists(local_path):
os.system(f"rm -rf {local_path}")
api = HfApi()
api.create_repo(repo_id=repo_name, token=hf_token, repo_type="dataset", exist_ok=True)
repo = Repository(local_dir=local_path, clone_from=repo_url, token=hf_token)
df.to_csv(f"{local_path}/data.csv", index=False)
repo.push_to_hub()
return f"Pushed to Hugging Face: {repo_url}"
with gr.Blocks() as demo:
gr.Markdown("## 🏷️ Label it! Text Labeling Tool")
with gr.Row():
csv_input = gr.File(label="Upload CSV", file_types=[".csv"])
upload_btn = gr.Button("Upload")
df_output = gr.Dataframe(headers=["text", "label"], interactive=True, visible=False)
upload_status = gr.Textbox(visible=True, interactive=False)
with gr.Row():
save_btn = gr.Button("Save Changes")
download_btn = gr.Button("Download CSV")
download_file = gr.File(label="Download", interactive=False)
with gr.Row():
hf_repo = gr.Textbox(label="HF Dataset Repo (e.g. your-username/my-dataset)")
hf_token = gr.Textbox(label="Hugging Face Token", type="password")
push_btn = gr.Button("Push to Hugging Face Hub")
push_status = gr.Textbox(interactive=False)
upload_btn.click(fn=upload_csv, inputs=csv_input, outputs=[df_output, upload_status])
save_btn.click(fn=save_edits, inputs=df_output, outputs=upload_status)
download_btn.click(fn=download_csv, outputs=download_file)
push_btn.click(fn=push_to_hub, inputs=[hf_repo, hf_token], outputs=push_status)
demo.launch()
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