April 2023 Summaries

ChatGPT plugins are a powerful way to expand its functionality by allowing it to leverage third-party resources during conversations. One such plugin is the Weaviate Retrieval Plugin, which connects ChatGPT to an instance of Weaviate and enables it to query relevant documents from the vector database, upsert documents for later use, and delete documents when needed. The process of creating a ChatGPT plugin involves setting up a development environment, implementing specific endpoints, preparing plugin manifest files, testing locally, and deploying remotely to platforms like Fly.io. These plugins can be used to address shortcomings in ChatGPT's current capabilities, such as the lack of contextual understanding or mathematical reasoning.

Authentication is a crucial aspect in ensuring secure access to Weaviate servers. It involves sending a "secret" from a client to verify its identity and determine the level of access allowed. Balancing security with usability can be challenging, as different users have varying needs and systems. Recently, an API key-based authentication method has been introduced for better security and ease of use. Weaviate offers several authentication options such as anonymous, API key, and OIDC (OpenID Connect) authentication. The choice depends on the user's requirements and system setup.

Auto-GPT is an open-source Python project that leverages GPT-4's capabilities by enabling it to run iteratively and complete various tasks autonomously. It chains together "thoughts" and completes tasks or assignments without human intervention, using tools like a code executor, Google search API, calculator, and vector database integration for long-term memory. Auto-GPT can write code, execute Python scripts, conduct market research, and even order pizza. The project is currently in the experimental phase and should be used with caution.

Quality matters in search, and ranking models are a low hanging fruit strategy to improve search quality. These models take the query and each candidate document as input to predict relevance. Cross Encoders, Metadata Rankers, and Score Rankers are three different genres of ranking models that can be used for content-based re-ranking, context-based re-ranking, and scoring or detecting content about candidate documents, respectively. These models offer more personalized and context-aware search experiences by further reasoning about the relevance of results without needing specialized training. Ranking is particularly exciting for retrieval-augmented generation as it can improve the quality of intermediate tasks in complex LLM-driven workflows.

OpenAI has introduced plugins for ChatGPT, allowing it to interact with other apps and perform real-world tasks. These plugins act as the "eyes and ears" of LLMs, enabling them to integrate with various applications such as Zapier, Uber Eats, Duolingo, and more. With plugins, users can now ask ChatGPT to order groceries, book restaurant seats, buy tickets for vacations, and even remember previous conversations by connecting it to a vector database like Weaviate. The retrieval plugin allows ChatGPT to access custom data stored in the connected vector database, providing tailored responses based on user-specific information. This integration of plugins enhances the capabilities of LLMs, making them more versatile and effective in real-world applications.