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New vllm and sglang engines that run in a sub-process. Will hopefully replace the existing embedded python engines.
    
Why?
    
  - Pure Python, does not require knowing Rust to work on it. Much simpler to maintain.
  - No embedded Python interpreter which avoids linking libpython and avoids the MacOS virtualenv issues.
  - Should have better performance as it's "native" vllm / sglang.
  - Works with any version of vllm (including v1!) and sglang. Less upgrade struggle.

Adding this to a Python script makes it register on the network so that `dynamo-run` can discover it and send it requests:
```
from dynamo.llm import register_llm

MODEL = "Qwen/Qwen2.5-0.5B-Instruct"
await register_llm(endpoint, MODEL, 3)
```

Full vllm example, with pre-processing in dynamo:
- `dynamo-run in=text out=dyn://dynamo.backend.generate`
- `cd lib/bindings/python/examples/hello_world`
- `python server_vllm.py`

This builds on top of the work to move pre-processor to ingress side. It means we can decouple Rust and Python using NATS as the bus.

The `register_llm` call does this:

- Download the model from HF if necessary
- Load the model deployment card from the HF folder or extract from GGUF
- Push the tokenizer config etc into NATS object store so ingress can access it from a different machine
- Publish the model deployment card to ETCD

Part of https://github.com/ai-dynamo/dynamo/issues/743

In a distributed system we don't know if the remote workers need pre-processing done ingress-side or not. Previously Client required us to decide this before discovering the remote endpoints, which was fine because pre-processing was worker-side.

As part of moving pre-processing back to ingress-side we need to split this into two steps:
- Client discovers the endpoints, and (later PR) will fetch their Model Deployment Card.
- PushRouter will use the Model Deployment Card to decide if they need pre-processing or not, which affects the types of the generic parameters.

Part of #743

Signed-off-by: Hongkuan Zhou <tedzhouhk@gmail.com>
Co-authored-by: ishandhanani <82981111+ishandhanani@users.noreply.github.com>
Co-authored-by: ishandhanani <ishandhanani@gmail.com>
Co-authored-by: Ubuntu <ubuntu@dev-inst-2w1vokvyuts83rzn4n1k7mnzew9.us-central1-a.c.brevdevprod.internal>
Co-authored-by: Biswa Panda <biswa.panda@gmail.com>
Co-authored-by: Anant Sharma <anants@nvidia.com>

This will allow an ingress-side pre-processor to see it without needing a model checkout.

Currently pre-processing is done in the worker, which has access to the model deployment card ("MDC") files (`config.json`, `tokenizer.json` and `tokenizer_config.json`) locally. We want to move the pre-processor to the ingress side to support KV routing. That requires ingress side (i.e the HTTP server), on a different machine than the worker to be able to see those three files.

To support that this PR makes the worker upload the contents of those files to the NATS object store, and publishes the MDC with those NATS urls to the key-value store. 

The key-value store has an interface so any store (nats, etcd, redis, etc) can be supported. Implementations for memory and NATS are provided.

Fetching the MDC from the store, doing pre-processing ingress side, and publishing a card backed by a GGUF, are all for a later commit.

Part of #743 

Co-authored-by: ishandhanani <82981111+ishandhanani@users.noreply.github.com>

feat: ETCD prefix watcher + python binding + runtime reconfiguration for router and disagg router  (#581)
Signed-off-by: Hongkuan Zhou <tedzhouhk@gmail.com>
Co-authored-by: Neelay Shah <neelays@nvidia.com>

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?

Also upgrade the cargo resolver to v3, the default.

New clippy lints:
- `next_back()` instead of `last()` for a double-ended iterator. That avoids walking the whole list.
- ` repeat_n` instead of `repeat.take`. That avoids cloning.
- Doc indenting

Adds `@dynamo_worker(static = True)` to create a static worker which has a predictable name and hence does not require discovery or `etcd` to be running. There can only be a single static worker per namespace / component / endpoint trio.

This contrasts with the default dynamic `dynamo_worker` endpoints we have now, which get a unique random name (based on namespace/component/endpoint), and are discovered by ingress components using etcd.

Also change the hello_world example to use `dynamo_worker(static = True)` so that it is exercised and demonstrated somewhere.

For NIM.

This makes the Rust parts all use ring / rustls library instead of local install of openssl. It's a step on the journey to being statically linked.

Pieces:
- `tokenizers` and `mistralrs` now support rustls (mistralrs by default, tokenizers with feature flag).
- Move shared dependencies up into workspace
- New `rand` crate has some renames for future rust
- Ensure the dependency doesn't creep back in by enforcing it with cargo deny.

- Any engine can take the name of a Hugging Face repository. It will be downloaded before calling the engine.

- The default engine (previously always mistralrs) depends on what is compiled in.

- Text can be piped in and will result in a single run of the model.

All of those together mean if you build with `--features vllm` you can do this and it will download the model and run it with vllm, answer your question, and exit:
```
echo "What is the capital of Costa Rica?"  | dynamo-run Qwen/Qwen2.5-3B-Instruct
```
Co-authored-by: Ryan McCormick <rmccormick@nvidia.com>

Co-authored-by: Harrison King Saturley-Hall <hsaturleyhal@nvidia.com>

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

There are two etcd keys:
- The service
- The model

The second one is the interesting one for us. Previously we confused the two.

Replaces hard-coded "kv-hit-rate" string in multiple places with KV_HIT_RATE_SUBJECT constant in lib/llm.

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

Co-authored-by: Ryan Olson <rolson@nvidia.com>

This means we don't need to explain the parts to the users until they are ready. We use what they provide and default the rest.

Allows all of this and more:
- `tio out=tdr://test`
- `tio out=tdr://llama_8b_pool`
- `tio in=tdr://corp_ai_research_group/model_next-20250226`
- `tio out=tdr://AIRE.NIM.migrate.mistralrs.1802`

Python, API, etc all untouched.

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

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