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Signed-off-by: Graham King <grahamk@nvidia.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: Keiven Chang <keivenchang@users.noreply.github.com>

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

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

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

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

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

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

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

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

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

refactor: Split ModelType to ModelInput for request and response type; ModelType for the supported workloads (#2714)
Signed-off-by: Guan Luo <gluo@nvidia.com>
Signed-off-by: GuanLuo <41310872+GuanLuo@users.noreply.github.com>
Co-authored-by: Guan Luo <gluo@nvidia.com>
Co-authored-by: GuanLuo <41310872+GuanLuo@users.noreply.github.com>

Signed-off-by: Krishnan Prashanth <kprashanth@nvidia.com>

Signed-off-by: Biswa Panda <biswa.panda@gmail.com>

Co-authored-by: Yan Ru Pei <yanrpei@gmail.com>

  * Added a default temperature value for text generation requests when no temperature is specified.
  * Improved handling of missing configuration values to prevent errors during model initialization.

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.

Previously `mistral.rs` was the default engine for both safetensors and GGUF models. Now it is only the default for safetensors, `llama.cpp` becomes the default for GGUF.

Why?

- Since #1177 `llama.cpp` is built-in by default, so we can switch.
- `llama.cpp` is very very good at running GGUF (but can't run other types of model), so we should switch.

Dynamo's multi-engine support gives us a secret super-power: we can use the best engine for this specific format or model.

We can still run GGUF with mistralrs by doing `out=mistralrs`.

Example:
```
dynamo-run out=<engine> <model> --kv-cache-block-size 64
```

In a distributed system this goes on the worker node and is propagated to ingress via the model deployment card.

Previously hard coded to 16, which is now the default.

- Load context_length from model. Closes #1172
- Store context length and KV cache block size in Model Deployment Card #1170

Llama 4 has a very large context length (aka n_ctx, model_max_length, max_model_len), and vllm won't start unless it can allocate enough KV cache for the entire context.

Allow passing `--context-length <N>` to `dynamo-run` to limit it so long-context models will fit.

Future todo:
- Restrict every request's `max_tokens` to below the context length. Our pre-processor should do this by setting stop_conditions.max_tokens. mistralrs engine wrapper must do it itself because it does not use the pre-processor.
- mistralrs and llamacpp currently have a hard-coded max context length if one is not provided on the command line. Change those to be the model's built-in max, read from the GGUF or tokenizer_config.json.

- Stop advertising a model when it's last instance stops. Previously was when any instance stops.
- Faster locks on model manager.
- Move discovery code out of http, as it is used by all inputs.