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AI assistant plugin for Zotero that integrates multiple AI models to enhance research productivity.
www.bibgenie.com (powered by turbo0)
www.bibgenie.com (powered by turbo0)
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BibGenie is an AI research agent plugin for Zotero that brings AI-powered chat, library search, and paper analysis directly into your reference management workflow.
BibGenie is a Zotero plugin that lets you interact with AI models using your Zotero library as context. It takes inputs such as Zotero items, PDFs, notes, snapshots, tags, collections, selected text, and images, and produces answers with traceable citations that can be saved as Zotero notes. It runs on Windows, Mac, and Linux within the Zotero desktop application and is developed by the BibGenie team.
BibGenie offers credit-based plans. The Free tier gives 50 credits per month with core chat, library search, and BYOK support. Pro ($9.99/month) includes 1000 credits, OpenAlex search, and web access. Max ($30/month) provides 3500 credits for heavy workflows. A Pro Lifetime plan is available at $199 (early bird). Credit boosters (500 credits for $6.99) can be added to any plan.
Yes. The Free plan includes 50 credits per month, core chat, library keyword/semantic search, and the ability to bring your own AI models. It does not include OpenAlex academic search or web search.
Credit consumption depends on paper length and complexity. A typical paper reading might use 10–30 credits, while a synthesis with multiple papers may use more.
Yes. You can use your own API keys for OpenAI, Anthropic, DeepSeek, Gemini, OpenRouter, Groq, Ollama, LM Studio, and other OpenAI-compatible endpoints. Custom model requests go directly from the local plugin to your configured provider.
No. Web search and web extract are available only on Pro and Max plans. The Free plan uses your local library and OpenAlex (if enabled) but not general web content.
Chat records are stored locally on your device. BibGenie does not upload your chat history or library contents to its servers unless you use the official model recommendations, in which case conversation data is processed by the model provider (e.g., OpenAI) but not stored by BibGenie.
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