The struggle to extract specific data points from academic papers just got a new solution. A fresh tutorial published on DEV.to on October 4, 2026, details how to build an Academic & Research Papers AI Agent using the Valyu Search API. This guide, part of the '30 Days of Search' series, addresses the common pain point of finding relevant details buried deep within abstracts or disparate sources.

The Core Integration Stack

The tutorial centers on the valyu-js SDK, specifically version 2.10.1. Developers are instructed to install the package via npm and configure their environment with a VALYU_API_KEY obtained from platform.valyu.ai. The core logic revolves around two primary methods: valyu.search() for locating papers and valyu.contents() for retrieving the actual text needed for analysis. This approach allows the AI agent to move beyond simple title matching to genuine evidence retrieval.

Multi-Source Search Capabilities

A key feature highlighted is the ability to query multiple scholarly databases simultaneously. The guide demonstrates how to configure the includedSources parameter to target specific collections like arXiv, PubMed, bioRxiv, ChemRxiv, and medRxiv. By using dataset IDs such as 'valyu/valyu-arxiv' or 'valyu/valyu-pubmed', developers can unify search results from these traditionally siloed platforms into a single, relevance-ranked stream. The tutorial notes that while includeAbstracts: true broadens discovery, it does not guarantee full-text access for every record.

From Search to Evidence-Based Answers

The agent's workflow is defined as: Question โ†’ Search papers โ†’ Read selected papers โ†’ Return evidence to the model โ†’ Cited answer. The tutorial provides code snippets for a readPaper function that fetches up to 12,000 characters of content, ensuring the model has sufficient context to compare methods and limitations. Crucially, the guide emphasizes that retrieved text is evidence, not instructions, and advises developers to maintain a session list of valid URLs to prevent hallucinated citations.

Key Takeaways

  • The Valyu SDK unifies access to five major preprint and journal archives through a single interface.
  • Developers must manually manage citation integrity by linking findings to original URLs and DOIs.
  • Preprint sources like bioRxiv and arXiv do not imply peer review, requiring agents to label evidence carefully.
  • A real-world implementation example, 'Paraphernalia', showcases the pattern in a public-facing academic interface.

The Bottom Line

This is a pragmatic blueprint for devs tired of fragile scraping. Valyu abstracts the messy API differences between arXiv and PubMed, letting you focus on agent logic instead of XML parsing hell.