A naukri.com initiative
Hackernoon
4d
20
Image Credit: Hackernoon
Leveraging RAG With Reddit URLs on Diabetes: Open Source LLMs for Enhanced Knowledge Retrieval
- Pre-trained LLMs, being open source, offer valuable assistance in knowledge retrieval, using RAG to leverage generative power while incorporating external knowledge.
- Utilizing LLMs like Ollama for sourcing experiential data on diabetes is illustrated in a step-by-step experiment using Reddit URLs.
- The process involves fetching and processing content from multiple URLs, splitting text into chunks, initializing Ollama embeddings, and creating a FAISS vector store.
- Ollama LLM is then used to generate responses based on stored knowledge, allowing RAG to retrieve context and answer user queries effectively.
- The ask_question_with_fallback function is designed to query and respond to user questions using stored knowledge, falling back on general knowledge if needed.
- In the absence of relevant documents, the fallback function utilizes the LLM's general knowledge to address user inquiries, promoting efficient knowledge retrieval.
- The methodology showcases the powerful application of RAG with URLs for improved knowledge access in diabetes inquiries, combining real-world insights from platforms like Reddit with LLMs.
- By merging community insights with open-source LLM capabilities, this cost-effective approach enhances personalized information on diabetes management, understanding the importance of lived experiences.
- The evolving potential of AI in healthcare, exemplified through knowledge-enhanced retrieval systems, signifies a collaborative and supportive future for individuals navigating diabetes.
Read Full Article
1 Like
For uninterrupted reading, download the app