This post explores using GPT-4o's structured output feature for web scraping, highlighting its strengths, limitations, and cost considerations.
High-performance deployment of the vLLM serving engine, optimized for serving large language models at scale.
A study investigating whether format restrictions like JSON or XML impact the performance of large language models (LLMs) in tasks like reasoning and domain knowledge comprehension.
Explore the capabilities of GPT-4, our latest large language model, offering improved understanding, generation, and problem-solving abilities. Discover its applications and learn how to integrate it into your projects.
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OpenAI's official website featuring news, blog posts, and information about their work on artificial intelligence.
This page provides information about LLooM, a tool that uses raw LLM logits to weave threads in a probabilistic way. It includes instructions on how to use LLooM with various environments, such as vLLM, llama.cpp, and OpenAI. The README also explains the parameters and configurations for LLooM.
Mariya Mansurova explores using CrewAI's multi-agent framework to create a solution for writing documentation based on tables and answering related questions.
pgai brings AI workflows to your PostgreSQL database. It simplifies the process of building search and Retrieval Augmented Generation (RAG) AI applications with PostgreSQL by bringing embedding and generation AI models closer to the database.
This article discusses how to overcome limitations of retrieval-augmented generation (RAG) models by creating an AI assistant using advanced SQL vector queries. The author uses tools such as MyScaleDB, OpenAI, LangChain, Hugging Face and the HackerNews API to develop an application that enhances the accuracy and efficiency of data retrieval process.
