First Author-Level Intelligence for Every Research Paper
Experience the future of research with first-author-level intelligence.
Instead of making your AI agent read entire papers, let it talk directly to Paper Agents — like having a conversation with the first author themselves. Each paper becomes an intelligent agent that understands its content deeply and can answer questions with author-level expertise.
# Install from PyPI
pip install py1stauthor[all]
# Get your free API token (1000 requests/day)
# Visit: https://data.rag.ac.cn/register
# Quickstart - 3 lines to talk to papers
from py1stauthor import Reader, Agent
agent = Agent(api_key=OPENAI_KEY, reader=Reader(token=ARXIV_TOKEN))
agent.query("What are the latest papers about LLM agents?")
Each paper is transformed into an intelligent agent that deeply understands its methodology, results, and implications.
Your research agent queries paper agents directly, getting precise answers without reading full texts.
Get first-author-level understanding and contextual knowledge that goes beyond surface reading.
Ask your agent to survey hundreds of papers by talking to them, saving days of reading time.
Build agents that consult paper experts for accurate, contextual information instead of hallucinating.
Ask papers questions directly, get methodology details, and understand nuances like talking to authors.
Compare methods, trace idea evolution, and synthesize knowledge across papers through agent collaboration.