embed_content with gemini-embedding-2* silently returns 1 embedding instead of N

## Description

`client.models.embed_content(model="gemini-embedding-2", contents=[...])` silently returns `len(result.embeddings) == 1` regardless of how many items are passed in `contents`, when using `gemini-embedding-2-preview` or `gemini-embedding-2`.

This causes `ValueError` from `zip(..., strict=True)` in downstream consumers because the number of returned embeddings does not match the number of inputs.

`gemini-embedding-001` does **not** exhibit this behavior — it correctly returns one embedding per input.

## Reproduction

```python
from google import genai
from google.genai import types

client = genai.Client(...)

texts = [
"What is the meaning of life?",
"How does gravity work?",
"What is machine learning?",
]

result = client.models.embed_content(
model="gemini-embedding-2-preview",
contents=texts,
)

print(f"Inputs: {len(texts)}, Embeddings returned: {len(result.embeddings)}")
# Expected: Inputs: 3, Embeddings returned: 3
# Actual: Inputs: 3, Embeddings returned: 1
```

## Root Cause

`gemini-embedding-2*` treats `embed_content(contents=[list_of_strings])` as parts of a single document rather than a batch. The proper batched API for these models is `asyncBatchEmbedContent`, but the SDKs `embed_content` method maps to `embedContent` which does not batch correctly for the `-2*` family.

## Workaround

Wrapping each string in `types.Content(parts=[types.Part(text=s)])` produces correct results:

```python
result = client.models.embed_content(
model="gemini-embedding-2-preview",
contents=[types.Content(parts=[types.Part(text=s)]) for s in texts],
)
```

## Downstream Impact

This has been hit by at least 3 projects:

- **graphiti** (getzep): [#1467](https://github.com/getzep/graphiti/issues/1467) → fixed via [#1474](https://github.com/getzep/graphiti/pull/1474) (`batch_size=1`)
- **pydantic/pydantic-ai**: [#4872](https://github.com/pydantic/pydantic-ai/issues/4872) → fixed via [#4873](https://github.com/pydantic/pydantic-ai/pull/4873) (`Content` wrapper)
- **plastic-labs/honcho**: currently fixing with the same `Content` wrapper workaround

## Expected Behavior

`embed_content(contents=[...])` should either:
1. Return the correct number of embeddings for `gemini-embedding-2*` (one per input), or
2. Raise an error clearly indicating that batching via `contents` list is not supported for this model, pointing users to the correct API.

## Environment

- `google-genai` version: latest (>=1.71.0)
- Models: `gemini-embedding-2-preview`, `gemini-embedding-2`