---
title: Additional examples
description: The Modelverse example programs in the release's examples archive, standalone CMake projects against the installed package, from the catalog probe to vision, OCR, reranking and vision-language chat.
---

<!-- CERTIFICATION: the programs below are read off the pinned release's examples archive
     (ClikaRT-<version>-examples.tar.xz, its cpp/modelverse directory and README); the release archive's own
     examples/src carries the runtime's example projects and no Modelverse program. -->

The Modelverse examples are standalone `find_package(Modelverse CONFIG)` projects on the public API only, one shared `README.md` walk-through beside them, and together they cover the library surface the [tutorial](getting-started/first-model/01-pick-a-model.md) meets through the `clikart-cli` executable. They live in the release's examples archive, `ClikaRT-<version>-examples.tar.xz` ([Get ClikaRT](/clikart/getting-started/get-clikart) names the download), under `cpp/modelverse/`; the release archive's own `examples/src` carries the runtime's examples ([the ClikaRT catalog](/clikart/examples)). Building them needs the release archive for your platform, extracted, with `CLIKART_BUNDLE_DIR` naming its directory: the one `cmake/` directory there carries both products' packages.

Read top to bottom; each row assumes a little of the ones above it.

| Example | What it shows |
| --- | --- |
| `init_model` | The registered catalog and identity resolution: list the families, resolve a model's identity from a local directory or a Hugging Face Hub repo id. The snapshot fetches configs and companions only, so identity costs no weight download. |
| `00_generate` | The minimal end-to-end path: explicit snapshot, registry match, generative pipeline, one prompt, text. The program [part 4 of the tutorial](getting-started/first-model/04-use-it-from-code.mdx) builds. |
| `01_serve` | The ServeAPI in process: implement the `ChatEngine` interface, mount it on `ServeApi`, and round-trip one `/v1/chat/completions` request through the built-in HTTP client. Runs with no arguments and no checkpoint, so it is also the fastest server smoke test. |
| `02_custom_node` | Your own `ClikaRT::runtime::Model` node composed with the library's serving nodes in one pipeline: a synthesized two-layer llama generates and a short custom node post-processes the reply, with the request surface unchanged. Offline, runs with no arguments. The worked version against a real model is [Add your own node to a model pipeline](how-to/add-a-pipeline-node.md). |
| `03_conversational_pipeline` | A conversational AI as one pipeline: wav bytes in, the reply waveform out, through speech to text, the chat template, a chat model and text to speech across eight nodes; real models, so it fetches on first run and takes a question wav plus the voice-reference wav the speech model requires. The guide is [A conversational AI as one pipeline](how-to/conversational-ai-pipeline.md). |
| `04_classify_zero_shot` | Zero-shot image classification: the labels you name scored against a picture by cosine in a dual-tower checkpoint's shared space (SigLIP); the picture drawn by the program; no arguments. |
| `05_detect_objects` | Object detection over the checkpoint's own label set (DETR): boxes in the picture's pixels above a confidence; no arguments. |
| `06_detect_by_phrase` | Open-vocabulary detection (OWL-ViT): the prompt's phrases encoded once, a box per thing found, labeled with its phrase; no arguments. |
| `07_estimate_depth` | Monocular depth (Depth Anything V2): one value per pixel at the picture's size, metric or relative; no arguments. |
| `08_read_text` | Text recognition (GLM-OCR): a page of block letters drawn with the operators, read back as text through the registry's text-recognition door; no arguments. |
| `09_rerank` | Reranking (Qwen3-Reranker): one relevance score per document against a query, printed best first; no arguments. |
| `10_describe_a_picture` | Vision-language chat (Qwen3-VL): one question about a picture, the picture riding the user turn; greedy, no arguments. |

A program that runs with no arguments and prints the same text on every run sits beside its recorded output (`<name>.out`), the text the release printed; a program that takes a checkpoint or a clip, or prints a port, is built and not recorded.

## Build and run

From the extracted `examples/` directory:

```bash
cmake -S cpp/modelverse -B build-examples \
      -DModelverse_DIR="$CLIKART_BUNDLE_DIR/cmake"
cmake --build build-examples
```

```bash
build-examples/init_model                                    # catalog only, offline
build-examples/init_model -r openai/whisper-large-v3-turbo    # + identity from Hugging Face
build-examples/00_generate Qwen/Qwen2.5-0.5B-Instruct "Once upon a time, in a port town by a cold sea,"
build-examples/01_serve
build-examples/02_custom_node                                # offline, no arguments
build-examples/05_detect_objects                             # the vision, OCR, reranking and chat programs: no arguments, the checkpoint from the local cache
```

`01_serve` prints its bound port, answers one request against itself, and exits `PASS`, which makes it the one to run first when checking a new machine:

```text
serving on 127.0.0.1:41627
HTTP 200
choice: echo: Say hello.
01_serve: PASS
```

Every program runs compute, so it needs the license credential in `CLIKA_RT_LICENSE` or in the per-user file `clikart-license-init` writes; without one a call is refused with the code name `LICENSE_FAILED`. Where models come from, cache placement and the offline path are the same for the examples as for `clikart-cli`; the examples' shared `README.md` restates them next to the code.