---
title: "nr-llm wiring: providers, models, Configurations"
manual: "nr_repurpose"
version: "main"
permalink: "https://docs.typo3.org/permalink/netresearch/nr-repurpose:configuration-nr-llm@main"
source: "Configuration/NrLlm.rst"
rendered: "2026-09-30T16:39:51+00:00"
---

# nr-llm wiring: providers, models, Configurations {#configuration-nr-llm}

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](https://docs.typo3.org/permalink/netresearch/nr-repurpose:installation-openai-key@main)).
1.  Create the **Models** you want to use (or fetch them via nr-llm's model
    discovery), including the specialized ones (image, text-to-speech).
1.  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](https://docs.typo3.org/permalink/netresearch/nr-repurpose:adr-003@main).

## Prompt snippets {#configuration-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 {#configuration-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**

```bash
vendor/bin/typo3 nrllm:usecasepack:install content-repurpose-starter
```

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.