Llama.embed() calls LlamaBatch.add_sequence with old 3-arg signature; missing logits_array

# Prerequisites

- [x] I am running the latest code. Development is very rapid so there are no tagged versions as of now.
- [x] I carefully followed the README.md.
- [x] I searched using keywords relevant to my issue to make sure that I am creating a new issue that is not already open (or closed).
- [x] I reviewed the Discussions, and have a new bug or useful enhancement to share.

# Expected Behavior

`Llama.embed()` should successfully compute embeddings when called on a model constructed with `embeddings=True`.

# Current Behavior

`Llama.embed()` raises a `TypeError` immediately, before any embedding is computed:

```
TypeError: LlamaBatch.add_sequence() missing 1 required positional argument: 'logits_array'
```

The cause: `Llama.embed()` in `llama_cpp/llama.py` (around line 1678) calls `add_sequence` with three positional arguments:

```python
self._batch.add_sequence(tokens, p_batch, logits_all)
```

But `LlamaBatch.add_sequence` in `llama_cpp/_internals.py` (around line 1013) requires four:

```python
def add_sequence(
self,
token_array: Sequence[int],
pos_array: Sequence[int],
seq_ids: Sequence[Sequence[int]],
logits_array: Sequence[bool]
)
```

`llama_cpp/llama_embedding.py` (around line 262) already calls `add_sequence` correctly with the four-arg shape — the call site in `Llama.embed()` was apparently missed during the `LlamaBatch.add_sequence` refactor.

# Environment and Context

- Hardware: x86_64, NVIDIA GeForce RTX 4090
- OS: Windows 10 22H2
- Python 3.12.9
- llama-cpp-python 0.3.36 (CUDA 12.8 prebuilt wheel)

```
$ python --version
Python 3.12.9

$ pip show llama-cpp-python | findstr Version
Version: 0.3.36
```

# Failure Information (for bugs)

This is a clean regression — `LlamaBatch.add_sequence` was refactored from a 3-arg signature to a 4-arg one, and the call sites were updated everywhere except in `Llama.embed()`. `llama_embedding.py` shows what the new shape should look like for the embedding code path.

# Steps to Reproduce

```python
from llama_cpp import Llama

m = Llama(model_path="path/to/model.gguf", embeddings=True)
m.embed("hello")
```

Result:
```
TypeError: LlamaBatch.add_sequence() missing 1 required positional argument: 'logits_array'
```

# Failure Logs

```
Traceback (most recent call last):
File "...\Lib\site-packages\llama_cpp\llama.py", line 1678, in embed
self._batch.add_sequence(tokens, p_batch, logits_all)
TypeError: LlamaBatch.add_sequence() missing 1 required positional argument: 'logits_array'
```

# Suggested fix

Mirror the call shape already used in `llama_cpp/llama_embedding.py`:

```python
# In llama.py Llama.embed(), replace:
self._batch.add_sequence(tokens, p_batch, logits_all)

# With something like:
self._batch.add_sequence(
token_array=tokens,
pos_array=list(range(len(tokens))),
seq_ids=[p_batch],
logits_array=[True] * len(tokens) if logits_all else [False] * (len(tokens) - 1) + [True],
)
```

# Workaround

Monkey-patching `LlamaBatch.add_sequence` to detect 3-arg legacy calls and synthesize the missing `pos_array` works as a stopgap. Hit while running Tencent's HY-Motion text-to-motion model, whose text encoder uses `Llama.embed()` against GGUF Qwen3 weights.