Building an Elastic Plugin for ChatGPT
Context is the backbone of understanding. It’s paramount that conversational AI systems such as ChatGPT are updated with the most recent information to stay relevant in the rapidly changing technological landscape. While a static knowledge base can address a broad array of questions, the precision and relevance of answers can be significantly enhanced when the system understands the present context.
The Dynamic Context Layer (DCL) offers a solution. By continuously updating the model’s knowledge with the latest data, the DCL ensures that the AI’s responses are not just accurate but also timely and context-aware. This chapter focuses on creating such a layer for ChatGPT using Elasticsearch’s vector capabilities combined with Embedchain, a framework designed to effortlessly craft LLM-powered bots over any dataset. Our primary objective is to enable ChatGPT to pull and comprehend the latest domain-specific information...
