import gradio as gr
from transformers import pipeline, AutoTokenizer
import pdfplumber
from docx import Document

# ✅ Load tokenizer and summarization model
MODEL_NAME = "facebook/bart-large-cnn"
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, local_files_only=False, force_download=True)
summarizer = pipeline("summarization", model=MODEL_NAME, tokenizer=MODEL_NAME, device=-1)

# ✅ Function to extract text from different file formats
def extract_text(file):
    if file is None:
        return "No file uploaded."
    
    file_name = file.name.lower()
    try:
        if file_name.endswith(".pdf"):
            with pdfplumber.open(file.name) as pdf:
                text = "\n".join([page.extract_text() for page in pdf.pages if page.extract_text()])
        elif file_name.endswith(".docx"):
            doc = Document(file.name)
            text = "\n".join([para.text for para in doc.paragraphs])
        elif file_name.endswith(".txt"):
            text = file.read().decode("utf-8")
        else:
            return "❌ Unsupported file format. Please upload a PDF, DOCX, or TXT file."
        
        return text if text.strip() else "⚠ No readable text found in the file."
    
    except Exception as e:
        return f"❌ Error reading file: {str(e)}"

# ✅ Function to summarize text
def summarize_text(text, file):
    # If file uploaded, extract text
    if file is not None:
        text = extract_text(file)

    # Ensure valid text and truncate to 1024 tokens
    if text.strip() and "Error" not in text:
        inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=1024)
        summary = summarizer(tokenizer.decode(inputs["input_ids"][0]), max_length=150, min_length=50, do_sample=False)
        return summary[0]["summary_text"]
    else:
        return "⚠ No valid text found to summarize."

# ✅ Gradio Interface with Footer
app = gr.Blocks()

with app:
    gr.Markdown("## 📝 AI-Powered Text Summarization")
    gr.Markdown("📄 Upload a document or enter text to get a concise AI-generated summary.")
    
    with gr.Row():
        text_input = gr.Textbox(lines=10, placeholder="📌 Enter text here or upload a file below ⬇")
        file_input = gr.File(label="📂 Upload File (PDF, DOCX, TXT)")
    
    output_text = gr.Textbox(label="📃 Summarized Text")
    
    summarize_button = gr.Button("✨ Summarize")
    summarize_button.click(summarize_text, inputs=[text_input, file_input], outputs=output_text)
    
    # ✅ Footer
    gr.Markdown("---")
    # ✅ Fixed Footer with Clickable Links
    gr.HTML(
        """
        <div class='footer' style="text-align: center; padding: 10px; font-size: 16px;">
            🌟 Developed by <b>Sheema Masood</b> | Powered By Gradio 🌌 <br>
            🔗 Connect with me: 
            <a href="https://github.com/SheemaMasood381" target="_blank" style="color: #f4d03f; text-decoration: none;">GitHub</a> |
            <a href="https://www.linkedin.com/in/sheema-masood/" target="_blank" style="color: #3498db; text-decoration: none;">LinkedIn</a> |
            <a href="https://www.kaggle.com/sheemamasood" target="_blank" style="color: #e74c3c; text-decoration: none;">Kaggle</a>
        </div>
        """
    )


# ✅ Launch App
if __name__ == "__main__":
    app.launch(debug=True)