flask-files

Dockerfile

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+# 1. Use an official Python image
+FROM python:3.9-slim
+
+# 2. Set the working directory inside the container
+WORKDIR /app
+
+# 3. Copy only the requirements first (better for speed)
+COPY requirements.txt .
+
+# 4. Install the libraries
+RUN pip install --no-cache-dir -r requirements.txt
+
+# 5. Copy the rest of your code (app.py and templates folder)
+COPY . .
+
+# 6. Tell Hugging Face to use port 7860
+ENV PORT=7860
+EXPOSE 7860
+
+# 7. Start the Flask app
+CMD ["python", "app.py"]

README.md

@@ -1,11 +1,25 @@
----
-title: Text Summarizer AI
-emoji: 🐠
-colorFrom: yellow
-colorTo: yellow
-sdk: docker
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: AI Text Summarizer
+emoji: 📝
+colorFrom: blue
+colorTo: purple
+sdk: docker
+app_port: 7860
+pinned: false
+---
+# AI Text Summarizer (Bart-Large)
+An intelligent, web-based application that leverages Transformer-based Deep Learning to transform long, complex articles into concise, meaningful summaries. This project uses the facebook/bart-large-cnn model to provide high-quality, abstractive summarization.
+
+### Overview :-
+Reading through massive blocks of text is time-consuming. This tool aims to solve the "Information Overload" problem by providing a user-friendly interface where users can paste up to 1024 words and receive a human-like summary in seconds.
+
+Unlike basic extractive summarizers that just copy sentences, this app uses Abstractive Summarization, meaning the AI understands the context and "rewrites" the summary in its own words.
+
+### Key Features :-
+Deep Learning Backend: Powered by the 1.6GB BART-Large model for superior accuracy.
+
+Intelligent Post-Processing: Custom Python logic to handle sentence capitalization and proper noun preservation (e.g., keeping "James Webb" capitalized).
+
+Dynamic Summary Length: Forced minimum word counts to ensure summaries are detailed and informative rather than just one-liners.
+
+Modern Web UI: A clean, responsive interface built with Flask and CSS.

app.py

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+import os
+from flask import Flask, render_template, request, jsonify
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+app = Flask(__name__)
+
+MODEL_NAME = "facebook/bart-large-cnn"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME)
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+@app.route('/summarize', methods=['POST'])
+def summarize():
+    try:
+        data = request.get_json()
+        text = data.get('text', '').strip()
+
+        if not text or len(text.split()) < 15:
+            return jsonify({'error': 'Text too short.'}), 400
+
+        inputs = tokenizer(text, return_tensors="pt", max_length=1024, truncation=True)
+
+        summary_ids = model.generate(
+            inputs["input_ids"], 
+            max_length=300,        
+            min_length=150,        
+            length_penalty=2.5,    
+            num_beams=5,           
+            no_repeat_ngram_size=3,
+            early_stopping=False   
+        )
+
+        summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+
+        # --- SAFE CLEANING LOGIC ---
+        # 1. Fix punctuation spacing
+        summary = summary.replace(" .", ".").replace(" ,", ",").replace(" !", "!").replace(" ?", "?")
+        
+        # 2. Capitalize ONLY the first letter of each sentence
+        # This prevents "James Webb" from becoming "James webb"
+        parts = summary.split(". ")
+        cleaned_sentences = []
+        for p in parts:
+            p = p.strip()
+            if p:
+                # Upcase only index 0, keep everything else exactly as the AI wrote it
+                sentence = p[0].upper() + p[1:]
+                cleaned_sentences.append(sentence)
+        
+        summary = ". ".join(cleaned_sentences)
+        
+        if summary and not summary.endswith('.'): 
+            summary += '.'
+
+        return jsonify({'summary': summary})
+
+    except Exception as e:
+        return jsonify({'error': str(e)}), 500
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=7860)

requirements.txt

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+flask
+transformers
+torch --index-url https://download.pytorch.org/whl/cpu

templates/index.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>SummAI | Professional Text Summarizer</title>
+    <script src="https://cdn.tailwindcss.com"></script>
+    <link href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css" rel="stylesheet">
+</head>
+<body class="bg-gray-50 text-gray-900 font-sans leading-normal tracking-normal">
+
+    <nav class="bg-white shadow-sm border-b border-gray-200 py-4 px-6">
+        <div class="max-w-7xl mx-auto flex justify-between items-center">
+            <div class="flex items-center space-x-2">
+                <i class="fa-solid font-bold text-indigo-600 text-2xl"></i>
+                <span class="text-xl font-extrabold tracking-tight text-gray-800">Summ<span class="text-indigo-600">AI</span></span>
+            </div>
+            <div class="hidden md:flex space-x-6 text-sm font-medium text-gray-500">
+                <span class="hover:text-indigo-600 cursor-pointer">Abstractive AI</span>
+                <span class="hover:text-indigo-600 cursor-pointer">BART Model</span>
+            </div>
+        </div>
+    </nav>
+
+    <main class="max-w-6xl mx-auto py-12 px-4 sm:px-6 lg:px-8">
+        <div class="text-center mb-12">
+            <h1 class="text-4xl font-extrabold text-gray-900 sm:text-5xl">
+                Summarize content in <span class="text-indigo-600">seconds.</span>
+            </h1>
+            <p class="mt-4 text-lg text-gray-600 max-w-2xl mx-auto">
+                Paste long articles, research papers, or reports and let our AI provide a professional-grade summary instantly.
+            </p>
+        </div>
+
+        <div class="grid grid-cols-1 lg:grid-cols-2 gap-8">
+            
+            <div class="bg-white rounded-2xl shadow-xl p-6 border border-gray-100">
+                <div class="flex items-center justify-between mb-4">
+                    <h3 class="text-lg font-bold text-gray-800">Original Text</h3>
+                    <span id="charCount" class="text-xs text-gray-400 font-medium">0 words</span>
+                </div>
+                <textarea id="inputText" 
+                    class="w-full h-80 p-4 bg-gray-50 border border-gray-200 rounded-xl focus:ring-2 focus:ring-indigo-500 focus:border-transparent transition resize-none placeholder-gray-400"
+                    placeholder="Paste your text here (minimum 20 words for best results)..."></textarea>
+                
+                <button id="sumBtn" onclick="summarize()" 
+                    class="mt-6 w-full bg-indigo-600 hover:bg-indigo-700 text-white font-bold py-4 rounded-xl transition-all duration-200 flex items-center justify-center space-x-2 shadow-lg shadow-indigo-200">
+                    <i class="fa-solid fa-wand-sparkles"></i>
+                    <span>Generate Summary</span>
+                </button>
+            </div>
+
+            <div class="bg-white rounded-2xl shadow-xl p-6 border border-gray-100 flex flex-col">
+                <div class="flex items-center justify-between mb-4">
+                    <h3 class="text-lg font-bold text-gray-800">AI Summary</h3>
+                    <button onclick="copyToClipboard()" class="text-indigo-600 hover:text-indigo-800 text-sm font-semibold flex items-center space-x-1">
+                        <i class="fa-regular fa-copy"></i>
+                        <span>Copy</span>
+                    </button>
+                </div>
+                
+                <div id="outputBox" class="flex-grow w-full h-80 p-4 bg-indigo-50/30 border-2 border-dashed border-indigo-100 rounded-xl overflow-y-auto">
+                    <p id="outputPlaceholder" class="text-gray-400 italic">Your summary will appear here after processing...</p>
+                    <p id="outputText" class="text-gray-700 hidden leading-relaxed"></p>
+                </div>
+
+                <div id="statusMessage" class="mt-4 text-sm text-gray-500 flex items-center space-x-2 opacity-0 transition-opacity">
+                    <i class="fa-solid fa-circle-notch fa-spin text-indigo-600"></i>
+                    <span>AI is thinking...</span>
+                </div>
+            </div>
+        </div>
+    </main>
+
+    <footer class="mt-12 py-8 text-center text-gray-400 text-sm border-t border-gray-100">
+        &copy; 2026 SummAI. Powered by Hugging Face Transformers.
+    </footer>
+
+    <script>
+        // Word counter logic
+        document.getElementById('inputText').addEventListener('input', function() {
+            const words = this.value.trim().split(/\s+/).filter(x => x.length > 0).length;
+            document.getElementById('charCount').innerText = `${words} words`;
+        });
+
+        async function summarize() {
+            const inputText = document.getElementById('inputText').value;
+            const outputText = document.getElementById('outputText');
+            const outputPlaceholder = document.getElementById('outputPlaceholder');
+            const statusMessage = document.getElementById('statusMessage');
+            const btn = document.getElementById('sumBtn');
+
+            if (inputText.split(/\s+/).length < 20) {
+                alert("Please enter at least 20 words for a meaningful summary.");
+                return;
+            }
+
+            // Start Loading State
+            btn.disabled = true;
+            btn.classList.add('opacity-50', 'cursor-not-allowed');
+            statusMessage.classList.add('opacity-100');
+            outputPlaceholder.innerText = "Analyzing text and generating summary...";
+            outputText.classList.add('hidden');
+
+            try {
+                const response = await fetch('/summarize', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({ text: inputText })
+                });
+
+                const data = await response.json();
+
+                if (response.ok) {
+                    outputText.innerText = data.summary;
+                    outputText.classList.remove('hidden');
+                    outputPlaceholder.classList.add('hidden');
+                } else {
+                    alert(data.error || "An error occurred");
+                    outputPlaceholder.innerText = "Summary failed. Please try again.";
+                }
+            } catch (error) {
+                console.error("Error:", error);
+                alert("Failed to connect to the server.");
+            } finally {
+                // End Loading State
+                btn.disabled = false;
+                btn.classList.remove('opacity-50', 'cursor-not-allowed');
+                statusMessage.classList.remove('opacity-100');
+            }
+        }
+
+        function copyToClipboard() {
+            const text = document.getElementById('outputText').innerText;
+            if (!text) return;
+            navigator.clipboard.writeText(text).then(() => {
+                alert("Summary copied to clipboard!");
+            });
+        }
+    </script>
+</body>
+</html>