BatchJob.src is always None for Gemini Developer API — inputConfig is not parsed in _BatchJob_from_mldev

# `BatchJob.src` is never populated for Gemini Developer API (mldev), causing input file references to be lost

## Environment

- `google-genai` version: **1.73.1**
- API backend: **Gemini Developer API** (`genai.Client(api_key=...)`, not Vertex AI)
- Python: 3.12
- File: `google/genai/batches.py`

## Summary

`_BatchJob_from_mldev` (the response parser used for the Gemini Developer API) does **not** map `metadata.inputConfig` from the REST response into the `src` field of `types.BatchJob`. Only `metadata.output` is mapped (into `dest`).

As a result, after calling `client.batches.create(...)` or `client.batches.get(name=...)`, **`batch.src` is always `None`** for the Gemini Developer API, even though the underlying REST response contains `metadata.inputConfig.fileName`.

The Vertex AI parser (`_BatchJob_from_vertex`) does not have this issue — it correctly maps `inputConfig` to `src`.

## Reproduction

```python
from google import genai

client = genai.Client(api_key="...")

# 1. Upload an input file
uploaded = client.files.upload(
file=BytesIO(b'{"key":"k1","request":{"contents":[{"parts":[{"text":"hi"}]}]}}\n'),
config={"display_name": "demo", "mime_type": "application/jsonl"},
)
print("uploaded:", uploaded.name) # e.g. "files/vx4mwl208pq9"

# 2. Create a batch from the uploaded file
batch = client.batches.create(
model="gemini-2.5-flash-lite",
src=uploaded.name,
config={"display_name": "demo-batch"},
)

# 3. Retrieve the batch
fetched = client.batches.get(name=batch.name)

print("src:", fetched.src) # ← None (BUG)
print("dest:", fetched.dest) # ← BatchJobDestination(file_name='files/batch-...')
```

The raw REST response (`GET /v1beta/{batch.name}`) contains both:

```json
{
"name": "batches/xhpy2t2ugh8l0obqasnhinyi7aeisy38w6h3",
"metadata": {
"inputConfig": {
"fileName": "files/vx4mwl208pq9"
},
"output": {
"responsesFile": "files/batch-xhpy2t2ugh8l0obqasnhinyi7aeisy38w6h3"
},
...
}
}
```

…but `fetched.src` is `None` because the SDK never parses `metadata.inputConfig`.

## Expected behavior

`fetched.src.file_name` should equal `"files/vx4mwl208pq9"` (consistent with the Vertex AI parser, which sets `src` from `inputConfig`).

## Actual behavior

`fetched.src` is `None` for the Gemini Developer API.

## Root cause

`google/genai/batches.py:256-310` — `_BatchJob_from_mldev` is missing the `inputConfig → src` mapping:

```python
def _BatchJob_from_mldev(
from_object: Union[dict[str, Any], object],
parent_object: Optional[dict[str, Any]] = None,
) -> dict[str, Any]:
to_object: dict[str, Any] = {}
if getv(from_object, ['name']) is not None:
setv(to_object, ['name'], getv(from_object, ['name']))
# ... displayName, state, createTime, endTime, updateTime, model ...

if getv(from_object, ['metadata', 'output']) is not None:
setv(
to_object,
['dest'],
_BatchJobDestination_from_mldev(
t.t_recv_batch_job_destination(
getv(from_object, ['metadata', 'output'])
),
to_object,
),
)

return to_object # ← `src` is never set
```

Compare with `_BatchJob_from_vertex` (`batches.py:313-369`), which **does** map `inputConfig` to `src`:

```python
if getv(from_object, ['inputConfig']) is not None:
setv(
to_object,
['src'],
_BatchJobSource_from_vertex(
getv(from_object, ['inputConfig']), to_object
),
)
```

## Impact

This bug has caused a serious production issue for us. Our code relied on `batch.src.file_name` to identify the input file for cleanup after the batch completes:

```python
src_name = getattr(batch.src, "file_name", None) # always None
if src_name:
client.files.delete(name=src_name) # never executes
```

Because `batch.src` is always `None`, the `client.files.delete(...)` call is silently skipped. Input files (uploaded via `client.files.upload(...)`, default 30-day TTL on the Gemini Developer API) accumulate in the project's Files API quota (20 GB), eventually exhausting it and blocking new batch submissions until the user manually cleans up out-of-band.

Anyone using `BatchJob.src` to track or clean up the input file on the Gemini Developer API path is silently affected.

## Workaround

We are working around this by issuing a raw REST `GET` to retrieve the batch and reading `metadata.inputConfig.fileName` directly:

```python
import urllib.request, json
req = urllib.request.Request(
f"https://generativelanguage.googleapis.com/v1beta/{batch_name}",
headers={"x-goog-api-key": api_key},
)
with urllib.request.urlopen(req) as resp:
meta = json.loads(resp.read())
input_file = meta["metadata"]["inputConfig"]["fileName"]
```

A workaround that stays within the SDK is to persist the file name returned by `client.files.upload(...)` ourselves at submit time and ignore `batch.src` entirely.

## Proposed fix

Add the `inputConfig → src` mapping to `_BatchJob_from_mldev`, mirroring `_BatchJob_from_vertex`:

```python
def _BatchJob_from_mldev(from_object, parent_object=None):
to_object = {}
# ... existing mappings ...

if getv(from_object, ['metadata', 'inputConfig']) is not None:
setv(
to_object,
['src'],
_BatchJobSource_from_mldev(
getv(from_object, ['metadata', 'inputConfig']),
to_object,
),
)

if getv(from_object, ['metadata', 'output']) is not None:
setv(
to_object,
['dest'],
_BatchJobDestination_from_mldev(
t.t_recv_batch_job_destination(
getv(from_object, ['metadata', 'output'])
),
to_object,
),
)

return to_object
```

(`_BatchJobSource_from_mldev` already exists in the file; this just calls it with the right input.)

Thanks for maintaining the SDK!