Interacting with LLM APIs using Python
With your development environment configured, the next step is enabling communication between your Python code and Large Language Models. This chapter focuses on the mechanics of interacting with LLM Application Programming Interfaces (APIs) using Python.
You will learn the structure of API requests and responses, how to send requests using the standard requests library, and techniques for processing the returned data or handling errors. We will also cover the use of official Python client libraries provided by LLM vendors, different authentication approaches, and practical considerations like managing API rate limits and usage costs. By the end of this chapter, you will be able to programmatically send prompts to LLMs and retrieve their outputs.
Sections
3.1 Understanding LLM APIs
3.2 Making API Requests with the requests Library
3.3 Handling API Responses and Errors
3.4 Using Official Python Client Libraries
3.5 Authentication Methods
3.6 Rate Limiting and Cost Management Considerations
3.7 Practice: Querying an LLM API
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