GitLab

- 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 

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

. 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.

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

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