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from flask import Flask, request, send_file, jsonify |
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from flask_cors import CORS |
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline |
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import pdfkit |
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import jinja2 |
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import torch |
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import tempfile |
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import os |
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os.environ['TRANSFORMERS_CACHE'] = '/app/.cache' |
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os.environ['HF_DATASETS_CACHE'] = '/app/.cache' |
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os.environ['XDG_CACHE_HOME'] = '/app/.cache' |
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os.environ['HF_HOME'] = '/app/.cache' |
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app = Flask(__name__) |
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CORS(app) |
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try: |
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model = AutoModelForCausalLM.from_pretrained( |
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"gpt2-medium", |
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from_tf=False, |
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use_safetensors=True |
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) |
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tokenizer = AutoTokenizer.from_pretrained("gpt2-medium") |
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generator = pipeline( |
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'text-generation', |
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model=model, |
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tokenizer=tokenizer, |
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device=0 if torch.cuda.is_available() else -1 |
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) |
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except Exception as e: |
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print(f"Model loading failed: {str(e)}") |
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generator = None |
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IEEE_TEMPLATE = """ |
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<!DOCTYPE html> |
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<html> |
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<head> |
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<meta charset="UTF-8"> |
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<title>{{ title }}</title> |
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<style> |
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@page { margin: 0.75in; } |
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body { |
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font-family: 'Times New Roman', Times, serif; |
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font-size: 12pt; |
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line-height: 1.5; |
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} |
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.header { |
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text-align: center; |
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margin-bottom: 24pt; |
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} |
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.two-column { |
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column-count: 2; |
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column-gap: 0.5in; |
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} |
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h1 { font-size: 14pt; margin: 12pt 0; } |
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h2 { font-size: 12pt; margin: 12pt 0 6pt 0; } |
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.abstract { margin-bottom: 24pt; } |
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.keywords { font-weight: bold; margin: 12pt 0; } |
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.references { margin-top: 24pt; } |
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.reference-item { text-indent: -0.5in; padding-left: 0.5in; } |
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</style> |
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</head> |
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<body> |
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<div class="header"> |
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<h1>{{ title }}</h1> |
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<div class="author-info"> |
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{% for author in authors %} |
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{{ author.name }}<br> |
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{% if author.institution %}{{ author.institution }}<br>{% endif %} |
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{% if author.email %}Email: {{ author.email }}{% endif %} |
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{% if not loop.last %}<br>{% endif %} |
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{% endfor %} |
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</div> |
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</div> |
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|
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<div class="abstract"> |
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<h2>Abstract</h2> |
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{{ abstract }} |
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<div class="keywords">Keywords— {{ keywords }}</div> |
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</div> |
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|
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<div class="two-column"> |
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{% for section in sections %} |
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<h2>{{ section.title }}</h2> |
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{{ section.content }} |
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{% endfor %} |
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</div> |
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<div class="references"> |
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<h2>References</h2> |
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{% for ref in references %} |
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<div class="reference-item">[{{ loop.index }}] {{ ref }}</div> |
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{% endfor %} |
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</div> |
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</body> |
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</html> |
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""" |
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|
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def format_content(content): |
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if not generator: |
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return content |
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try: |
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prompt = f"Format this research content to IEEE standards:\n{str(content)}" |
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return generator( |
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prompt, |
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max_length=1024, |
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num_return_sequences=1, |
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clean_up_tokenization_spaces=True |
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)[0]['generated_text'] |
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except Exception as e: |
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print(f"Formatting failed: {str(e)}") |
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return content |
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|
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@app.route('/generate', methods=['POST']) |
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def generate_pdf(): |
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try: |
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data = request.json |
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if not data or 'title' not in data or 'authors' not in data: |
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return jsonify({"error": "Missing required fields"}), 400 |
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formatted = format_content(data.get('content', {})) |
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html = jinja2.Template(IEEE_TEMPLATE).render( |
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title=data['title'], |
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authors=data['authors'], |
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abstract=formatted.get('abstract', ''), |
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keywords=', '.join(formatted.get('keywords', [])), |
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sections=formatted.get('sections', []), |
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references=formatted.get('references', []) |
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) |
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options = { |
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'page-size': 'Letter', |
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'margin-top': '0.75in', |
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'margin-right': '0.75in', |
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'margin-bottom': '0.75in', |
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'margin-left': '0.75in', |
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'encoding': 'UTF-8', |
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'quiet': '' |
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} |
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with tempfile.NamedTemporaryFile(delete=False, suffix='.pdf') as f: |
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pdfkit.from_string(html, f.name, options=options) |
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return send_file(f.name, mimetype='application/pdf') |
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except Exception as e: |
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return jsonify({"error": str(e)}), 500 |
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|
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if __name__ == '__main__': |
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app.run(host='0.0.0.0', port=5000) |
