Tag: python

Code examples for Building Effective Agents ported and adapted to use Pydantic AI.

Independent LLM calls are parallelisable.

On the mundane advantages of easy artificial intelligence.

Comparing RAG over a rich and complex text using GraphRag vs traditional embeddings index.

Using Pydantic and Instructor with OpenAI GPT-4o to use the LLM as a software device for implementing different tasks.

Using an LLM to summarise and cluster articles (works better than embeddings and traditional ML clustering).

Take a ToDoList class and chain it to GPT-3.5 by passing the methods for interacting with the list as LangChain tools or OpenAI function calls.

Multiplex between multiple Open AI clients and Azure Open AI deployments + track and attribute the cost of the requests per user and/or endpoint.

We know that we can ask GPT questions. But how about it asking us? In this example GPT-3.5-turbo is working for us as a waiter in a restaurant.