app.py

import os
import random
import re
from string import Template

import gradio as gr
import pandas as pd
from datasets import Dataset
from huggingface_hub import HfApi
from pypdf import PdfReader


to_be_removed = ["ͳ", "•", "→", "□", "▪", "►", "�", "", "", "", ""]
to_be_replaced = {
    "½": "1/2",
    "–": "-",
    "‘": "'",
    "’": "'",
    "…": "...",
    "₋": "-",
    "−": "-",
    "⓫": "11.",
    "⓬": "12.",
    "⓭": "13.",
    "⓮": "14.",
    "◦": "°",
    "❶": "1.",
    "❷": "2.",
    "❸": "3.",
    "❹": "4.",
    "❺": "5.",
    "❻": "6.",
    "❼": "7.",
    "❽": "8.",
    "❾": "9.",
    "❿": "10.",
    "\n": " ",
}


def clean(text):
    # Remove all the unwanted characters
    for char in to_be_removed:
        text = text.replace(char, "")

    # Replace all the characters that need to be replaced
    for char, replacement in to_be_replaced.items():
        text = text.replace(char, replacement)

    # For all \n, if the next line doesn't start with a capital letter, remove the \n
    # text = re.sub(r"\n([^A-ZÀ-ÖØ-Þ])", r" \1", text)

    # Make sure that every "." is followed by a space
    text = re.sub(r"\.([^ ])", r". \1", text)

    # Add a space between a lowercase followed by an uppercase "aA" -> "a A" (include accents)
    text = re.sub(r"([a-zà-öø-ÿ])([A-ZÀ-ÖØ-Þ])", r"\1 \2", text)

    # Make sure that there is no space before a comma, a period, or a hyphen
    text = text.replace(" ,", ",")
    text = text.replace(" .", ".")
    text = text.replace(" -", "-")
    text = text.replace("- ", "-")

    while "  " in text:
        text = text.replace("  ", " ")

    return text


def pdf2dataset(pathes, user_id, dataset_id, token, private, progress=gr.Progress()):
    if any([user_id, dataset_id, token]) and not all([user_id, dataset_id, token]):
        raise gr.Error("Please provide all three: User ID, Dataset ID, and API token.")

    if user_id == "":
        user_id = "pdf2dataset"
        private = False
    if dataset_id == "":
        dataset_id = f"{random.getrandbits(128):x}"
    if token == "":
        token = os.getenv("HF_TOKEN")

    progress(0, desc="Starting...")
    readers = []
    for path in pathes:
        try:
            readers.append(PdfReader(path))
        except Exception as e:
            raise gr.Error(f"Failed to read {path.split('/')[-1]}.")
    num_pages = sum(len(reader.pages) for reader in readers)
    filenames = [path.split("/")[-1] for path in pathes]

    # Convert the PDFs to text
    page_texts = []
    page_filenames = []
    progress(0, desc="Converting pages...")
    for reader, filename in zip(readers, filenames):
        for page in reader.pages:
            page_text = page.extract_text()
            page_text = clean(page_text)
            page_texts.append(page_text)
            page_filenames.append(filename)
            progress(len(page_texts) / num_pages, desc="Converting pages...")

    # Upload the dataset to Hugging Face
    progress(0, desc="Uploading to Hugging Face...")
    dataset = Dataset.from_dict({"text": page_texts, "source": page_filenames})
    dataset.push_to_hub(f"{user_id}/{dataset_id}", token=token, private=private)
    progress(1, desc="Done!")

    instructions = instructions_template.substitute(user_id=user_id, dataset_id=dataset_id)
    preview = pd.DataFrame(dataset[:10])
    print(f"Dataset {dataset_id} uploaded successfully.")
    delete_dataset_id = dataset_id if user_id == "pdf2dataset" else ""
    return instructions, preview, delete_dataset_id


def delete_dataset(repo_id_or_dataset_id):
    # Get the user_id,  dataset_id
    if "/" in repo_id_or_dataset_id:
        user_id, dataset_id = repo_id_or_dataset_id.split("/")
        repo_id = repo_id_or_dataset_id
    else:
        user_id = "pdf2dataset"
        dataset_id = repo_id_or_dataset_id
        repo_id = f"{user_id}/{dataset_id}"

    # Only allow the deletion of datasets in the pdf2dataset namespace
    if not user_id == "pdf2dataset":
        print(f"Deleting datasets in the {user_id} namespace is not allowed.")
        return f"❌ Deleting datasets in the {user_id} namespace is not allowed."

    # Delete the dataset
    api = HfApi()
    try:
        api.delete_repo(repo_id, repo_type="dataset")
        print(f"Dataset {repo_id} deleted successfully.")
        return "✅ Dataset deleted successfully."
    except Exception as e:
        print(f"Error deleting dataset{repo_id}: {e}")
        return f"❌ Error deleting dataset: {e}"


caution_text = """⚠️ Caution:
- This process will upload your data to a public Hugging Face repository. Do not upload sensitive information.
- Anyone (including you) will be able to delete the dataset once it is uploaded.

To avoid this, you can push the dataset to your personal Hugging Face account ⬇️
"""

instructions_template = Template(
    """
🔗: https://huggingface.co/datasets/$user_id/$dataset_id.

```python
from datasets import load_dataset

dataset = load_dataset("$user_id/$dataset_id")
```
    """
)

with gr.Blocks() as demo:
    gr.Markdown("# PDF to 🤗 Dataset")
    gr.Markdown("## 1️⃣ Upload PDFs")
    file = gr.File(file_types=["pdf"], file_count="multiple")
    gr.Markdown(caution_text)
    with gr.Accordion("🔒 Pushing to my personal Hugging Face namespace", open=False):
        gr.Markdown(
            """Recommended for API token
- Go to https://huggingface.co/settings/tokens?new_token=true 
- Choose _Fine-grained_
- Check only _**Repos**/Write access to contents/settings of all repos under your personal namespace_
- Revoke the token after use"""
        )
        user_id = gr.Textbox(label="User ID", placeholder="Enter your Hugging Face user ID")
        dataset_id = gr.Textbox(label="Dataset ID", placeholder="Enter the desired dataset ID")
        token = gr.Textbox(label="API token", placeholder="Enter a Hugging Face API token")
        private = gr.Checkbox(label="Make dataset private")

    gr.Markdown("## 2️⃣ Convert the PDFs and upload")
    convert_button = gr.Button("🔄 Convert and upload")
    preview = gr.Dataframe(
        label="Preview (first 10 rows)", headers=["text", "source"], datatype=["str", "str"], row_count=10, wrap=True, height=200
    )
    gr.Markdown("## 3️⃣ Use the dataset in your code")
    instructions = gr.Markdown(instructions_template.substitute(user_id="pdf2dataset", dataset_id="generated_dataset_id"))
    gr.Markdown("## 4️⃣ Delete the dataset (optional)")
    dataset_id_to_delete = gr.Textbox("", placeholder="Enter dataset name to delete", label="Dataset to delete")
    delete_button = gr.Button("🗑️ Delete dataset")

    # Define the actions
    convert_button.click(
        pdf2dataset, inputs=[file, user_id, dataset_id, token, private], outputs=[instructions, preview, dataset_id_to_delete]
    )
    delete_button.click(delete_dataset, inputs=[dataset_id_to_delete], outputs=[delete_button])
    dataset_id_to_delete.input(lambda: "🗑️ Delete dataset", outputs=[delete_button])

demo.launch()