app.py

import gradio as gr
import pandas as pd
import matplotlib.pyplot as plt
from pathlib import Path
from huggingface_hub import HfApi, Repository

plt.rcParams.update({
    "font.family": "sans-serif",
    "font.size": 10,
})

# Global DataFrame
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 (
            None,  # table
            "❌ CSV must contain 'text' and 'label' columns.",
            gr.update(visible=False),  # save
            gr.update(visible=False),  # download CSV
            gr.update(visible=False),  # visualize
            gr.update(visible=False),  # push accordion
        )
    df["label"] = df["label"].fillna("")
    return (
        df[["text","label"]],
        "✅ File uploaded — you can now annotate and use the buttons below.",
        gr.update(visible=True),
        gr.update(visible=True),
        gr.update(visible=True),
        gr.update(visible=True),
    )

def save_changes(table):
    global df
    df = pd.DataFrame(table, columns=["text","label"])
    return "💾 Changes saved."

def download_csv():
    global df
    path = "annotated_data.csv"
    df.to_csv(path, index=False)
    return path

def create_distribution_figure():
    global df
    counts = df["label"].value_counts().sort_values(ascending=False)
    labels, values = counts.index.tolist(), counts.values.tolist()
    
    fig, (ax_table, ax_bar) = plt.subplots(
        ncols=2,
        gridspec_kw={"width_ratios": [1,2]},
        figsize=(8, max(2, len(labels)*0.4)),
        tight_layout=True
    )
    # Table
    ax_table.axis("off")
    data = [[l,v] for l,v in zip(labels, values)]
    tbl = ax_table.table(cellText=data, colLabels=["Label","Count"], loc="center")
    tbl.auto_set_font_size(False); tbl.set_fontsize(10); tbl.scale(1,1.2)
    # Bar chart
    ax_bar.barh(labels, values, color="#222")
    ax_bar.invert_yaxis(); ax_bar.set_xlabel("Count")
    return fig

def visualize_and_download_chart():
    fig = create_distribution_figure()
    out_path = "label_distribution.png"
    fig.savefig(out_path, dpi=150, bbox_inches="tight")
    return fig, out_path

def push_to_hub(repo_name, hf_token):
    global df
    try:
        api = HfApi()
        api.create_repo(repo_id=repo_name, token=hf_token,
                        repo_type="dataset", exist_ok=True)
        local_dir = Path(f"./{repo_name.replace('/','_')}")
        if local_dir.exists():
            for f in local_dir.iterdir(): f.unlink()
            local_dir.rmdir()
        repo = Repository(
            local_dir=str(local_dir),
            clone_from=repo_name,
            repo_type="dataset",
            use_auth_token=hf_token
        )
        df.to_csv(local_dir/"data.csv", index=False)
        repo.push_to_hub(commit_message="📑 Update annotated data")
        return f"🚀 Pushed to https://huggingface.co/datasets/{repo_name}"
    except Exception as e:
        return f"❌ Push failed: {e}"

with gr.Blocks(theme=gr.themes.Default()) as app:
    gr.Markdown("## 🏷️ Label It! Text Annotation Tool\n"
                "Upload a `.csv` (with **text** + **label** columns), "
                "then annotate, export, visualize, or publish.")
    
    # Step 1: Upload
    with gr.Row():
        file_input = gr.File(label="📁 Upload CSV", file_types=[".csv"])
        upload_btn = gr.Button("Upload")
    
    # Editable table
    table = gr.Dataframe(headers=["text","label"], interactive=True, visible=False)
    status = gr.Textbox(label="Status", interactive=False)
    
    # Step 2 buttons (hidden initially)
    with gr.Row(visible=False) as action_row:
        save_btn     = gr.Button("💾 Save")
        download_btn = gr.Button("⬇️ Download CSV")
        visualize_btn= gr.Button("📊 Visualize Distribution")
        download_csv_out   = gr.File(label="📥 Download CSV")
        chart_plot         = gr.Plot(label="Label Distribution")
        download_chart_out = gr.File(label="📥 Download Chart")
    
    # Push accordion
    push_acc = gr.Accordion("📦 Push to Hugging Face Hub", open=False, visible=False)
    with push_acc:
        repo_in   = gr.Textbox(label="Repo (username/dataset-name)")
        token_in  = gr.Textbox(label="🔑 HF Token", type="password")
        push_btn  = gr.Button("🚀 Push")
        push_status = gr.Textbox(label="Push Status", interactive=False)
    
    # Event bindings
    upload_btn.click(
        upload_csv,
        inputs=file_input,
        outputs=[table, status,
                 save_btn, download_btn, visualize_btn, push_acc]
    )
    save_btn.click(save_changes, inputs=table, outputs=status)
    download_btn.click(download_csv, outputs=download_csv_out)
    visualize_btn.click(visualize_and_download_chart,
                        outputs=[chart_plot, download_chart_out])
    push_btn.click(push_to_hub, inputs=[repo_in, token_in], outputs=push_status)

app.launch()