GitLab

Signed-off-by: Anna Tchernych <atchernych@nvidia.com>

Signed-off-by: Graham King <grahamk@nvidia.com>

Signed-off-by: PeaBrane <yanrpei@gmail.com>

Signed-off-by: PeaBrane <yanrpei@gmail.com>

Signed-off-by: PeaBrane <yanrpei@gmail.com>

Signed-off-by: PeaBrane <yanrpei@gmail.com>

Signed-off-by: PeaBrane <yanrpei@gmail.com>

Signed-off-by: PeaBrane <yanrpei@gmail.com>

Signed-off-by: Graham King <grahamk@nvidia.com>

Signed-off-by: PeaBrane <yanrpei@gmail.com>

Signed-off-by: Graham King <grahamk@nvidia.com>

Signed-off-by: Anna Tchernych <atchernych@nvidia.com>
Signed-off-by: atchernych <atchernych@nvidia.com>
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>

Signed-off-by: Anna Tchernych <atchernych@nvidia.com>

Signed-off-by: PeaBrane <yanrpei@gmail.com>

Signed-off-by: PeaBrane <yanrpei@gmail.com>

Signed-off-by: Anna Tchernych <atchernych@nvidia.com>

Signed-off-by: Anna Tchernych <atchernych@nvidia.com>

Signed-off-by: Graham King <grahamk@nvidia.com>

Move much of what was in the `dynamo-run` crate into `dynamo-llm` so that everyone can use it.

Example usage:

1. Create a `LocalModel`:

```
    let local_model = LocalModelBuilder::default()
	.model_path("Qwen/Qwen3-0.6B")
	.http_port(8080)
	.build().await?;
```

2. Make an engine:

```
    let engine_config = EngineConfig::StaticFull {
	engine: dynamo_engine_mistralrs::make_engine(&local_model).await?,
	model: Box::new(local_model),
    };
```

3. Connect it to an input and run it

```
    dynamo_llm::entrypoint::input::run_input(Input::Http, runtime, engine_config).await?;
```

For https://github.com/ai-dynamo/dynamo/issues/1647

Code Rabbit summary, thanks:
  * Introduced a flexible builder pattern for local model configuration, allowing advanced customization and easier initialization.
  * Added new input modes and unified input handling, supporting interactive chat, HTTP server, batch file, and distributed endpoint modes.
  * Centralized engine configuration and routing, enabling more extensible and maintainable engine management.
  * Simplified and modularized the codebase by moving input and engine logic into dedicated modules.
  * Replaced direct model construction with an asynchronous builder for improved clarity and extensibility.
  * Streamlined configuration and validation for flags and router settings.
  * Added validation to prevent incompatible input and output combinations in endpoint and dynamic modes.

Co-authored-by: Harrison Saturley-Hall <454891+saturley-hall@users.noreply.github.com>
Co-authored-by: Harrison King Saturley-Hall <hsaturleyhal@nvidia.com>

Co-authored-by: Biswa Panda <biswa.panda@gmail.com>

Co-authored-by: Graham King <grahamk@nvidia.com>

Engine, `tio` support and docs.

Proof of concept / experimental.

Co-authored-by: Graham King <grahamk@nvidia.com>

- Setup venv

```
uv venv
source .venv/bin/activate
uv pip install pip
uv pip install sgl-kernel --force-reinstall --no-deps
uv pip install "sglang[all]==0.4.2" --find-links https://flashinfer.ai/whl/cu124/torch2.4/flashinfer/
```

- Build: `cargo build --release --features sglang`

- Run single node (make sure you're in the venv): `./tio out=sglang ~/llm_models/my_model`

- Run Deepseek multi-gpu / multi-node:

Node 1:
```
tio in=http out=sglang --model-path ~/llm_models/DeepSeek-R1-Distill-Llama-70B/ --tensor-parallel-size 8 --num-nodes 2 --node-rank 0 --dist-init-addr 10.217.98.122:9876
```

Node 2:
```
tio in=none out=sglang --model-path ~/llm_models/DeepSeek-R1-Distill-Llama-70B/ --tensor-parallel-size 8 --num-nodes 2 --node-rank 1 --dist-init-addr 10.217.98.122:9876
```

Co-authored-by: aflowers <aflowers@nvidia.com>

Signed-off-by: Meenakshi Sharma <163925564+nvda-mesharma@users.noreply.github.com>
Signed-off-by: Neelay Shah <neelays@nvidia.com>
Co-authored-by: Neelay Shah <neelays@nvidia.com>
Co-authored-by: Ryan Olson <ryanolson@users.noreply.github.com>
Co-authored-by: Meenakshi Sharma <163925564+nvda-mesharma@users.noreply.github.com>
Co-authored-by: Biswa Panda <biswapanda@users.noreply.github.com>
Co-authored-by: Ryan McCormick <rmccormick@nvidia.com>

Signed-off-by: Ryan McCormick <rmccormick@nvidia.com>

Signed-off-by: Neelay Shah <neelays@nvidia.com>
Co-authored-by: Ryan McCormick <rmccormick@nvidia.com>