GitLab

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

Signed-off-by: alec-flowers <aflowers@nvidia.com>

Signed-off-by: alec-flowers <aflowers@nvidia.com>

Signed-off-by: Jason Zhou <jasonzho@nvidia.com>

feat: pre-deployment profiling automatically generates and deploys optimized DGD with planner (#3441)
Signed-off-by: hongkuanz <hongkuanz@nvidia.com>

Signed-off-by: William Arnold <7565007+Aphoh@users.noreply.github.com>

Signed-off-by: Neal Vaidya <nealv@nvidia.com>

Signed-off-by: ayushag <ayushag@nvidia.com>

Signed-off-by: Hannah Zhang <hannahz@nvidia.com>

Signed-off-by: Ryan Olson <rolson@nvidia.com>

Removed the hard coded sleeps, explained what we're testing.

Closes https://github.com/ai-dynamo/dynamo/issues/1132

The race condition is that `apply_event` sends a message on a channel, it does not directly apply the event. At some later point the tokio runtime schedules the task running the channel receiver, which applies the event. If that had not happened yet the test would fail.

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>

Co-authored-by: Ubuntu <ubuntu@crusoe-prod--inst-2secxwyxeao1mi2dsqk2pl9oaz7.eu-iceland1-a.comp>
Co-authored-by: Hannah Zhang <hannahz@nvidia.com>
Co-authored-by: hongkuanz <hongkuanz@nvidia.com>

Signed-off-by: Jacky <18255193+kthui@users.noreply.github.com>
Signed-off-by: Pavithra Vijayakrishnan <160681768+pvijayakrish@users.noreply.github.com>
Signed-off-by: Chantal D Gama Rose <cdgamarose@nvidia.com>
Signed-off-by: hhzhang16 <54051230+hhzhang16@users.noreply.github.com>
Co-authored-by: Julien Mancuso <jmancuso@nvidia.com>
Co-authored-by: mohammedabdulwahhab <furkhan324@berkeley.edu>
Co-authored-by: mabdulwahhab <mabdulwahhab@nvidia.com>
Co-authored-by: Tushar Sharma <tusharma@nvidia.com>
Co-authored-by: Jacky <18255193+kthui@users.noreply.github.com>
Co-authored-by: Neelay Shah <neelays@nvidia.com>
Co-authored-by: Pavithra Vijayakrishnan <160681768+pvijayakrish@users.noreply.github.com>
Co-authored-by: cdgamarose-nv <cdgamarose@nvidia.com>
Co-authored-by: Anant Sharma <anants@nvidia.com>
Co-authored-by: julienmancuso <161955438+julienmancuso@users.noreply.github.com>
Co-authored-by: Suman Tatiraju <167138127+statiraju@users.noreply.github.com>
Co-authored-by: Piotr Marcinkiewicz <piotrm@nvidia.com>
Co-authored-by: ishandhanani <82981111+ishandhanani@users.noreply.github.com>
Co-authored-by: Tanmay Verma <tanmayv@nvidia.com>

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>

Co-authored-by: Neelay Shah <neelays@nvidia.com>

Co-authored-by: Julien Mancuso <jmancuso@nvidia.com>

You can now run an HF repo directly:
```
tio ~/llm_models/Llama-3.2-1B-Instruct/
```

or a GGUF
```
tio ~/llm_models/Llama-3.2-1B-Instruct-Q4_K_M.gguf
```

Also cleanup kv_router so I can merge.

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

Co-authored-by: Ryan McCormick <rmccormick@nvidia.com>