[Cosmos] [Embedding V0] VectorEmbeddingPolicy: add EmbeddingSource TypedDict and typed policy models

# [Cosmos] [Embedding V0] VectorEmbeddingPolicy: document and add typed support for `embeddingSource`

Parent: [#46729](https://github.com/Azure/azure-sdk-for-python/issues/46729)

## Background

The `vectorEmbeddingPolicy` on a container now supports an optional `embeddingSource` block inside each entry of `vectorEmbeddings`. This block carries the endpoint, deployment name, auth type, and source paths that the new `azure-cosmos-embedding` package reads to construct an `AzureOpenAIEmbeddingGenerator`.

Example container policy JSON:
```json
{
"vectorEmbeddingPolicy": {
"vectorEmbeddings": [
{
"path": "/embedding",
"dataType": "float32",
"dimensions": 1536,
"distanceFunction": "cosine",
"embeddingSource": {
"sourcePaths": ["/title", "/abstract"],
"deploymentName": "text-embedding-3-small",
"modelName": "text-embedding-3-small",
"endpoint": "https://embedding-south-central.cognitiveservices.azure.com/",
"authType": "ApiKey"
}
}
]
}
}
```

## Scope

Python's `vector_embedding_policy` is currently typed as `dict[str, Any]` and passed through transparently. This issue adds typed support for the new `embeddingSource` sub-object without breaking the existing raw-dict path.

### 1. Add `TypedDict` models

In `azure/cosmos/_models.py` (or `documents.py` — confirm preferred location with SDK conventions):

```python
from typing import List, Literal, Optional
from typing_extensions import TypedDict

class EmbeddingSource(TypedDict, total=False):
sourcePaths: List[str]
deploymentName: str
modelName: str
endpoint: str
authType: Literal["ApiKey", "Entra"]

class VectorEmbedding(TypedDict, total=False):
path: str
dataType: Literal["float32", "float16", "uint8", "int8"]
dimensions: int
distanceFunction: Literal["cosine", "dotproduct", "euclidean"]
embeddingSource: EmbeddingSource # NEW

class VectorEmbeddingPolicy(TypedDict, total=False):
vectorEmbeddings: List[VectorEmbedding]
```

### 2. Update `database.py` (sync + async)

Update all `vector_embedding_policy` keyword parameter type annotations from `dict[str, Any]` to `VectorEmbeddingPolicy` — no behavioral change, just stronger typing.

### 3. Update `ContainerProperties` docstring (if applicable)

Update the docstring for `vector_embedding_policy` in `ContainerProperties` / `database.py` to document the new `embeddingSource` schema.

## Acceptance criteria

- `TypedDict` models are exported from `azure.cosmos` (or a supported sub-module).
- `mypy` passes on a usage like:
```python
source: EmbeddingSource = {"endpoint": "...", "deploymentName": "...", "authType": "ApiKey"}
```
- Existing containers without `embeddingSource` continue to work unchanged (round-trip through `dict[str, Any]` still valid).
- Unit test: create a `VectorEmbedding` TypedDict with and without `embeddingSource`, verify `json.dumps` round-trips correctly.

## Files likely touched

- `sdk/cosmos/azure-cosmos/azure/cosmos/_models.py` (or `documents.py`) — new TypedDict classes
- `sdk/cosmos/azure-cosmos/azure/cosmos/__init__.py` — export new types
- `sdk/cosmos/azure-cosmos/azure/cosmos/database.py` — updated type annotations (sync)
- `sdk/cosmos/azure-cosmos/azure/cosmos/aio/_database.py` — updated type annotations (async)

## Dependencies

None — pure model/typing change, no behavioral change.

Inizia controllando azure/cosmos/_models.py o documents.py per le convenzioni SDK TypedDict, quindi esamina azure/cosmos/__init__.py e i file del database sincroni e asincroni alla ricerca delle annotazioni per vector_embedding_policy. Aggiungi i modelli tipizzati e le esportazioni, aggiorna lo schema documentato e verifica l’uso di mypy e i test di round-trip JSON per le policies con e senza embeddingSource.

Scritto dal modello di indicizzazione a partire dal testo della issue.