DeepResearch handles paywalled or restricted content by prioritizing compliance with legal and ethical guidelines while maximizing access to publicly available information. When encountering paywalls or login requirements, the system does not attempt to bypass these restrictions. Instead, it relies on metadata, abstracts, or preview snippets provided by the source, along with any publicly accessible data that doesn’t require authentication. For example, if a research paper is behind a paywall, DeepResearch might extract information from the abstract, keywords, or citation data to provide context without accessing the full text. This approach ensures adherence to terms of service and copyright laws while still delivering useful insights.
To mitigate the limitations of restricted content, DeepResearch leverages alternative sources and caching mechanisms. If a paywalled article is referenced in an open-access repository, a preprint server like arXiv, or a public summary, the system will prioritize those versions. It also uses archived or cached content from services like the Wayback Machine when available. For instance, if a news article is behind a subscription wall, DeepResearch might retrieve an archived snapshot from a prior date when the content was freely accessible. Additionally, the system can integrate with APIs from platforms like PubMed or Crossref that provide structured metadata, helping users identify where to legally acquire the full content.
Developers can extend DeepResearch’s capabilities by configuring custom access rules for authenticated resources. If a user has valid credentials (e.g., institutional library access or API keys), these can be integrated into the system to fetch restricted content programmatically. For example, a university might provide OAuth tokens for accessing subscription-based journals, allowing DeepResearch to retrieve full-text articles through authorized pathways. However, this requires explicit user consent and secure handling of credentials, avoiding storage of sensitive data. The system logs access attempts to ensure transparency and auditability, maintaining a clear boundary between authorized use and unauthorized scraping.