TracyD
Active Member
Introducing the ME/CFS Research Chatbot! It's meant to provide a reliable, accurate, and up-to-date summary of published research for the general public.
While general LLMs like ChatGPT and Claude might provide fine answers to queries about myalgic encephalomyelitis/chronic fatigue syndrome, the sources are often unreported or of unknown quality, and the chatbots are prone to hallucination and to change answers from one moment to the next.
The chatbot that I have designed is a bit different: It relies only on research abstracts from the NIH's PubMed database that address this disease, it can provide a list of the abstracts consulted, and it's designed to provide the same, 'best' answer each time a particular question is asked - including admitting ignorance, if information is lacking.
For the technically inclined: The chatbot is a RAG system using Gemini 2.0 Flash to interpret the 250 abstracts that best match a user's query. The abstracts are embedded in a vector database using Chroma. And the frontend was built with Gradio and resides on Hugging Face. The full dataset of abstracts, with metadata, is here.
If you try it, please let me know how it goes.
While general LLMs like ChatGPT and Claude might provide fine answers to queries about myalgic encephalomyelitis/chronic fatigue syndrome, the sources are often unreported or of unknown quality, and the chatbots are prone to hallucination and to change answers from one moment to the next.
The chatbot that I have designed is a bit different: It relies only on research abstracts from the NIH's PubMed database that address this disease, it can provide a list of the abstracts consulted, and it's designed to provide the same, 'best' answer each time a particular question is asked - including admitting ignorance, if information is lacking.
For the technically inclined: The chatbot is a RAG system using Gemini 2.0 Flash to interpret the 250 abstracts that best match a user's query. The abstracts are embedded in a vector database using Chroma. And the frontend was built with Gradio and resides on Hugging Face. The full dataset of abstracts, with metadata, is here.
If you try it, please let me know how it goes.
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![ME/CFS lecture | Dr Nancy Klimas | 2011 [Chronic Fatigue Syndrome / SEID / New Zealand] - YouTube](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
