nr-llm wiring: providers, models, Configurations 

nr_repurpose never talks to an AI provider directly and never picks one itself. It names nr-llm Configuration records (use cases) and lets nr-llm resolve the model, the provider, the API key, the system prompt, and the usage/cost attribution. Set everything up in nr-llm's backend module (Admin Tools > LLM Management):

  1. Create a Provider whose API key references the key identifier nr-llm issued during installation (see Hand the provider key to nr-llm).
  2. Create the Models you want to use (or fetch them via nr-llm's model discovery), including the specialized ones (image, text-to-speech).
  3. Import the Configuration records nr_repurpose declares as presets. nr_repurpose ships the three records below as configuration presets (nr-llm ADR-056): open nr-llm's Configurations module and each appears as a pending preset with its required capabilities — import it with a single click. Each imports as a criteria-mode configuration that resolves against the models you created; no provider, model or key is baked into the preset. Mark the imported nr_repurpose_text record as the instance default. (You may still create the records by hand instead — the identifiers below are what the extension looks up.)
Configuration identifier Used for Model choice
nr_repurpose_text (mark as default) Analysis and copy: the brief, the podcast script, the diagram body, the story copy. The pipeline resolves the instance-default Configuration. Any chat model of any nr-llm provider — OpenAI, Anthropic Claude, Google Gemini, Groq, Mistral, Ollama, OpenRouter.
nr_repurpose_image AI imagery (Schaubild backgrounds and full images, story backgrounds). Any model accepted by nr-llm's image services; falls back to gpt-image-2 when the record is absent. The record's system prompt acts as a style preamble for every image prompt.
nr_repurpose_tts Podcast speech synthesis. Any model of nr-llm's text-to-speech service (currently OpenAI tts-1 / tts-1-hd); falls back to tts-1.

Swapping a model — or, for text, the provider — is a backend-only change: edit the Configuration record, no code or deployment involved. Per-model and per-configuration usage and cost appear in nr-llm's analytics module.

Image and speech calls go through nr-llm's specialized services, which currently cover OpenAI (images, TTS) and fal.ai (images). The extension-side seam for additional backends is the ImageGeneratorInterface / SpeechSynthesizerInterface DI alias in Configuration/Services.yaml.

Keys are always referenced by identifier: both the chat providers and the specialized services let nr-llm resolve and inject the key — no plaintext key is ever set here. See ADR-003: Provider Credentials Delegated to nr-llm.

Prompt snippets 

The New job form's audience, tone of voice, persona, layout and style selectors are populated from nr-llm's prompt-snippet library (snippets tagged audience, tone_of_voice, persona, layout, style). Editors maintain them in nr-llm's backend module; each snippet's description is shown in the form so the choice is informed. A layout snippet may carry an imageSize metadata key ("WIDTHxHEIGHT") that sets the AI-image dimensions for that channel — e.g. skyscraper 768x2160, wide 2160x768.

The starter pack 

A fresh installation has no snippets, so all five selectors read (none). The Content Repurpose Starter use-case pack installs a small library to start from: two audiences, two tones of voice, three podcast personas with their own voice, three layouts with their imageSize, and three visual styles.

Install it in nr-llm's Use Case Packs module, or from a provisioning script:

Install the starter pack unattended 
vendor/bin/typo3 nrllm:usecasepack:install content-repurpose-starter
Copied!

The records it creates are ordinary snippets — rename them, rewrite them, deactivate the ones you do not want. Installing again creates only what is missing and leaves your edits alone.

The pack's snippets are not linked to the nr_repurpose_text configuration by tag, and that is deliberate. This extension resolves the five families per job, from the selection in the form. Linking them would make nr-llm compose every active persona, layout and style into every completion as well — three speakers the job did not choose, and two contradictory image sizes. See nr-llm's ADR-186.