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The Python bindings use the default value for RouterMode. Previously that was Random (good), but now it became None (bad).

Remove the option and clean up the duplicate RouterMode. I was trying to avoid putting the `KV` enum in dynamo-runtime. Turns out adding those two characters gives us a healthy simplification, and restores the old default router value.

Also clean up two noisy log messages when waiting for KV routing metrics to start in worker.

The runtime library already provides a from_current method that creates and returns a Runtime object initialized with the current Tokio runtime handle. Since components do not use the runtime library directly but access it through the worker, the worker needs to be updated to create itself using a Runtime instance derived from the current Tokio runtime.
This PR updates the http component and the worker to use the existing Tokio runtime instead of creating a new one. Other components can be similarly updated to run using the existing runtime.

Router:
```
dynamo-run in=http out=dyn://dynamo.endpoint.generate --router-mode kv
```

Worker (* N):
```
dynamo-run in=dyn://dynamo.endpoint.generate out=vllm /data/llms/Qwen/Qwen3-4B
```

You need patched vllm and the C bindings `.so`. Full docs in the updated guide: `docs/guides/dynamo_run.md`.

This gives us a pure-Rust ingress node: OpenAI compliant HTTP server + Pre-processor + KV-aware router.

Signed-off-by: Harry Kim <harry_kim@live.com>

For #1006

Prints this on startup:
```
2025-05-09T13:06:34.529Z DEBUG dynamo_run::input::http: Supported routes: ["GET /metrics", "GET /dynamo/alpha/list-models", "GET /v1/models", "POST /v1/chat/completions", "POST /v1/completions"]
```

Add max_age to nats stream when create, 10 min should be very enough for prefill workers to consume. this prevent system crash while nats jetstream hits disk limit by endless growing messages.

Co-authored-by: ishandhanani <ishandhananai@gmail.com>

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

Signed-off-by: ishandhanani <82981111+ishandhanani@users.noreply.github.com>
Co-authored-by: Ryan McCormick <rmccormick@nvidia.com>

Example of how to connect a Python sglang engine to the message bus (NATS/etc). I

In this example sglang does the pre/post processing. There is already an example where Dynamo does it.

The examples teach this:

- Be a chat completions engine, do your own pre-processing:

```
await register_llm(ModelType.Chat, endpoint, config.model)
```

- Have Dynamo do pre-processing. It will register us under both Chat and Completions endpoints, because that's handled before a Backend engine gets the request:

```
await register_llm(ModelType.Backend, endpoint, config.model)
```

That avoids passing the `--model-config` param to dynamo-run when using llamacpp.

Allow both password or TLS auth, if none of these is provided fallback to no auth

Closes #657

Co-authored-by: ishandhanani <ishandhananai@gmail.com>

NIXL uses UCX which will have support for EFA since 1.19. Explicitly
use the 1.19 branch for UCX with Dynamo.
Signed-off-by: Adit Ranadive <aranadive@nvidia.com>

Co-authored-by: mohammedabdulwahhab <furkhan324@berkeley.edu>

. New mistralrs and llamacpp version
. mistralrs: Handle Gemma 3 and Llama 4 as vision models
. Update the dynamo-run docs to use Qwen 3
. Our pre-processor now supports Llama 4's newer multi-modal `config.json`
. Upgrade minijinja to handle Qwen 3's prompt template

For Llama 4 we'll need to limit the max seq len. vllm says:
> To serve at least one request with the models's max seq len (10485760), (240.00 GiB KV cache is needed,...

I was able to run Llama 4 with llamacpp and a quantized GGUF, with Dynamo doing the pre-processing.

Signed-off-by: Anthony Casagrande <acasagrande@nvidia.com>