GitLab

It's different enough that I made a new engine vllm0_8 and renamed the previous engine to vllm0_7.

`dynamo-run out=vllm` now expects 0.8. This matches the container change in #690.

For older use `dynamo-run out=vllm0_7`.

As a first step towards KV routing:
- introduce a `--router-mode` in dynamo-run that only does random and round-robin right now. Not that interesting yet.
- Make the vllm engine publish the KV events received from our patched vllm.

Now we "just" need to connect the two. Easy right?

Moved all of `lib/llm/src/engines` to their own crates as e.g. `lib/engines/mistralrs`. This will allow publishing of the `dynamo-llm` crate as it won't have any github dependencies.

The only engines in dynamo-llm will be the demo `echo` ones.
Co-authored-by: Graham King <grahamk@nvidia.com>

Put the arguments in a JSON file:
```
{
    "dtype": "half",
    "trust_remote_code": true
}
```

Pass it like this:
```
dynamo-run out=sglang ~/llm_models/Llama-3.2-3B-Instruct --extra-engine-args sglang_extra.json
```

Requested here https://github.com/ai-dynamo/dynamo/issues/290 (`dtype`) and here https://github.com/ai-dynamo/dynamo/issues/360 (`trust_remote_code`).

This lets us do:
```
dynamo-run out=llamacpp <gguf_file>
```

Previously a `--model-config <hf-repo>` was also required, to configure our tokenizer.

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

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

Needs more testing but good enough for now. I get the same results with this as with `vllm serve`.

triton-distributed-llm component and support in tio

- 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
```