[HN Gopher] Knowledge retrieval architectures for LLMs (2023) ___________________________________________________________________ Knowledge retrieval architectures for LLMs (2023) Author : burakemir Score : 36 points Date : 2023-04-27 21:13 UTC (1 hours ago) (HTM) web link (mattboegner.com) (TXT) w3m dump (mattboegner.com) | triyambakam wrote: | This is super helpful. I'm building a document question-answering | service over a custom data corpus (related to Saivism, a sect of | Hinduism). So far the first pass has been to manually chunk the | text (based on headings, chapters etc.) and then I've used | OpenAI's embedding service and storing the embeddings in | Pinecone. All stiched together using LangChain. To ask a | question, the question is again embedded, then searched against | the vector store, then the related documents are provided as | context to the LLM along with the question. | | So far it was really easy to set up the prototype, but the | results weren't as great as I had hoped, so I'm excited to see | how I could improve it. | | Edit: wow, I didn't see this before. LangChain implements one of | the featured article's suggestions (HyDE) - | https://python.langchain.com/en/latest/modules/chains/index_... | vectoral wrote: | This is one of the areas of LLMs that I find most interesting. So | far, I've found simple question-answering over vectorstores to be | a lackluster experience. In particular, the more information you | embed and stick into the vectorstore, the less useful the system | becomes as you are less likely to get the information you're | looking for (especially if the users don't understand their | queries need to look like the docs the want to ask about. | | I haven't had a chance to try out hypothetical embedded docs yet, | but I expect they only provide a marginal improvement (especially | if QAing over proprietary data or information). | | I'd love to see any other interesting, more up-to-date resources | anyone has found on this topic. I found this recent paper | interesting: https://arxiv.org/abs/2304.11062 ___________________________________________________________________ (page generated 2023-04-27 23:00 UTC)