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LLM platform

As explained in Software Testing with Generative AI

A software platform that provides access to large language models and related capabilities.

An LLM platform provides access to language models plus surrounding capabilities for integration, customization, deployment, and prompt-based control. Evaluate it by the tasks it supports, not by model size alone. section 2.5.1

Compare platforms across:

  • Integration: determine whether the platform exposes API access or fits existing systems. section 2.5.1
  • Customization: distinguish prompt-based instruction, private fine-tuning, and downloadable models. section 2.5.1
  • Response quality: test usefulness, legibility, hallucination risk, and performance on the intended task. section 2.5.1

Platform trade-off

OpenAI provides paid API access and prompt-based output control, but not private deployment of further fine-tuned GPT models. Meta’s open-source Llama permits further training, while users must build deployment infrastructure. section 2.5.1

How Software Testing with Generative AI covers it

How deep it goes
Compares integration, customization, deployment, and response quality but stops short of detailed platform implementation.
Examples
Uses OpenAI API access, GPT models, Meta Llama, and Google Gemini as comparison examples.
What you can do after
Evaluate platforms by testing outputs against intended tasks and judging quality, cost, customization, and deployment needs.
How it connects
Connects API access, prompt engineering, fine-tuning, deployment, model comparison, and hallucination.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Software Testing with Generative AI. The section links point to the parts of the book it draws on.