LLM-powered PDF academic paper summarizer with LaTeX output
Project description
pysearchlm
LLM-powered library that analyses academic PDF papers via Google Gemini URL Context and produces a comprehensive LaTeX technical summary.
Features
- 🧠 Gemini 2.5-pro integration (URL Context, no downloading)
- 📝 LaTeX output with academic package suggestions
- 🌍 Multi-language summaries (tr, en, fr, de, es, it, nl, pt, ru)
- ⚙️ Modular codebase (
core/,utils/) - 🚀 Minimal usage examples (
examples/)
Installation
pip install -r requirements.txt
Set your API key:
# Windows PowerShell
$env:GEMINI_API_KEY="YOUR_API_KEY"
# macOS / Linux
export GEMINI_API_KEY="YOUR_API_KEY"
# or via .env
echo "GEMINI_API_KEY=YOUR_API_KEY" > .env
Basic Usage
from pysearchlm import PDFAnalyzer
url = "https://arxiv.org/pdf/1706.03762.pdf"
ana = PDFAnalyzer()
res = ana.analyze_pdf(url, language="en")
print(res["latex_file"]["path"]) if res["success"] else print(res["error"])
Batch Analysis
urls = [
"https://arxiv.org/pdf/1706.03762.pdf",
"https://arxiv.org/pdf/1810.04805.pdf"
]
ana = PDFAnalyzer()
results = ana.analyze_multiple_pdfs(urls, language="en")
print("Success", results["successful"], "/", results["total_pdfs"])
Structure
core/ # Gemini client, PDF URL handler, LaTeX generator
utils/ # Config & helpers
examples/ # Minimal demos
pysearchlm.py # Main API class
Notes
- PDF is not downloaded; Gemini reads it directly via URL.
- LaTeX files are stored in
output/. - Make sure
GEMINI_API_KEYis defined, otherwise the analyzer raises an error at startup.
License
MIT. See LICENSE.
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