Rust Arxiv Summarizer (RAS) is a Rust application that fetches research papers from arXiv, extracts their content, and generates concise summaries using OpenAI's language models. The summaries are saved in markdown format for easy reading and sharing. The application try to fetch the latest 100 papers in the Artificial Intelligence (cs.AI) category.
- Build int Rust 1.90+
- Fetches papers about AI from arXiv
https://arxiv.org/list/cs.AI/recent - Make a prompt to call OpenAI API with the PDF content and the summary prompt.
- OpenAI model used:
gpt-4o-mini - Saves is in a markdown file.
- Uses the markdown files as cache to avoid reprocessing papers.
cargo buildOPEN_AI_API_KEY="sk-proj-..."
cargo runResult:
❯ cargo run
Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.09s
Running `target/debug/arxiv-summarizer`
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by Diego Pacheco
Found 99 existing summaries
Fetching papers from arXiv...
Found 100 papers
1 papers need processing
Processing: Topology Matters: Measuring Memory Leakage in Multi-Agent LLMs
PDF already exists: Topology Matters_ Measuring Memory Leakage in Multi-Agent LLMs.pdf
Extracting text from PDF: Topology Matters: Measuring Memory Leakage in Multi-Agent LLMs
Generating summary: Topology Matters: Measuring Memory Leakage in Multi-Agent LLMs
Summary saved: Topology Matters_ Measuring Memory Leakage in Multi-Agent LLMs-summary.md
Progress: 1/1
Done!