From Documents to Vectors: Understanding ChatGPT's Technical Architecture with OpenAI Plugins

Learn about the technical intricacies of OpenAI's API and plugins in this 20-minute video that explores real-time data retrieval with ChatGPT. Explore vector databases and their role in storing document representations, comparing open-source options like Weaviate and Milvus with commercial solutions such as Azure's Cognitive Search. Master the fundamentals of OpenAI's retrieval plugin, built using FastAPI, and understand its four main API endpoints: upsert, upsert-file, query, and delete. Dive into the technical architecture where plugins consist of an API, API schema, and manifest JSON file, while learning how ADA-002 embeddings enable sophisticated semantic search capabilities. Discover the integration possibilities with various systems including Google's Search API, YouTube's Data API, and ScholarAI for archive pre-print server access. Grasp the concept of hybrid search, which combines neural and index search methods for enhanced query results on GPT-4, and understand the importance of security through authentication tokens for both OpenAI and vector database providers.