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Signed-off-by: Kristen Kelleher <kkelleher@nvidia.com>
- Content, format, and structural changes to the Dynamo docs for 0.3.0. 
- Includes copyediting and the first batch of changes from the DMO review.

This PR modifies the mistralrs engine to ensure that the maximum output token length never exceeds the context length provided.

Signed-off-by: Hongkuan Zhou <tedzhouhk@gmail.com>
Co-authored-by: jothomson <jwillthomson19@gmail.com>
Co-authored-by: Ryan McCormick <rmccormick@nvidia.com>

Do not include by default as it needs libgomp1 at runtime. Add a feature to enable it at build time.

It was confusing to have two names for one type.

This tidy up started in #1064 , is now complete.

Unify them with all our other logs, so we can filter with DYN_LOG, they will eventually go to the log aggregation, etc.

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`.

- Add Granite to our tokenizer
- Fix pre-processor to load context length correctly
- Add strftime_now Jinja function for prompt templates
- Update llama.cpp
- Handle trtllm errors when not using trtllm

Support depends on the engine:

- `mistral.rs`, our default engine, doesn't support Granite yet.

- `llama.cpp` does and works very well:
```
dynamo-run out=llamacpp ~/llms/granite-3.3-2b-instruct-Q4_K_M.gguf --context-length 16384
```

- `vllm` also works very well:
```
dynamo-run in=http out=vllm ~/llms/granite-3.3-2b-instruct --context-length 16384
```

- `sglang` mostly works, but it doesn't catch the stop token, so we do in the HTTP ingress, and log an error. The Text ingress doesn't catch it because I disabled it to make the raw echo engine work. A bit of work to do here.

Closes: #1245 

Signed-off-by: Hongkuan Zhou <tedzhouhk@gmail.com>
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>

Fixes #286

It was removed from the docs in 0.2.1 and replaced with writing a [standalone Python engine](https://github.com/ai-dynamo/dynamo/blob/main/docs/guides/dynamo_run.md#writing-your-own-engine-in-python).

Also remove the associated `dynamo-run` feature `python`.

Releasing this in 0.3.0 will resolve #784 and #1109.

Signed-off-by: Michael Feil <63565275+michaelfeil@users.noreply.github.com>
Co-authored-by: Michael Feil <63565275+michaelfeil@users.noreply.github.com>
Co-authored-by: jthomson04 <jwillthomson19@gmail.com>
Co-authored-by: Ryan Olson <ryanolson@users.noreply.github.com>

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

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.

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.

Co-authored-by: Suman Tatiraju <statiraju@statiraju-mlt.client.nvidia.com>