feat(api): (1/n) datasets api clean up (#1573)

## PR Stack
- https://github.com/meta-llama/llama-stack/pull/1573
- https://github.com/meta-llama/llama-stack/pull/1625
- https://github.com/meta-llama/llama-stack/pull/1656
- https://github.com/meta-llama/llama-stack/pull/1657
- https://github.com/meta-llama/llama-stack/pull/1658
- https://github.com/meta-llama/llama-stack/pull/1659
- https://github.com/meta-llama/llama-stack/pull/1660

**Client SDK**
- https://github.com/meta-llama/llama-stack-client-python/pull/203

**CI**
- 1391130488
<img width="1042" alt="image"
src="https://github.com/user-attachments/assets/69636067-376d-436b-9204-896e2dd490ca"
/>
-- the test_rag_agent_with_attachments is flaky and not related to this
PR

## Doc
<img width="789" alt="image"
src="https://github.com/user-attachments/assets/b88390f3-73d6-4483-b09a-a192064e32d9"
/>


## Client Usage
```python
client.datasets.register(
    source={
        "type": "uri",
        "uri": "lsfs://mydata.jsonl",
    },
    schema="jsonl_messages",
    # optional 
    dataset_id="my_first_train_data"
)

# quick prototype debugging
client.datasets.register(
    data_reference={
        "type": "rows",
        "rows": [
                "messages": [...],
        ],
    },
    schema="jsonl_messages",
)
```

## Test Plan
- CI:
1387805545

```
LLAMA_STACK_CONFIG=fireworks pytest -v tests/integration/datasets/test_datasets.py
```

```
LLAMA_STACK_CONFIG=fireworks pytest -v tests/integration/scoring/test_scoring.py
```

```
pytest -v -s --nbval-lax ./docs/notebooks/Llama_Stack_Benchmark_Evals.ipynb
```

tests/integration/datasets/test_datasets.py

@@ -0,0 +1,95 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+
+import base64
+import mimetypes
+import os
+
+import pytest
+
+# How to run this test:
+#
+# LLAMA_STACK_CONFIG="template-name" pytest -v tests/integration/datasets
+
+
+def data_url_from_file(file_path: str) -> str:
+    if not os.path.exists(file_path):
+        raise FileNotFoundError(f"File not found: {file_path}")
+
+    with open(file_path, "rb") as file:
+        file_content = file.read()
+
+    base64_content = base64.b64encode(file_content).decode("utf-8")
+    mime_type, _ = mimetypes.guess_type(file_path)
+
+    data_url = f"data:{mime_type};base64,{base64_content}"
+
+    return data_url
+
+
+@pytest.mark.parametrize(
+    "purpose, source, provider_id, limit",
+    [
+        (
+            "eval/messages-answer",
+            {
+                "type": "uri",
+                "uri": "huggingface://datasets/llamastack/simpleqa?split=train",
+            },
+            "huggingface",
+            10,
+        ),
+        (
+            "eval/messages-answer",
+            {
+                "type": "rows",
+                "rows": [
+                    {
+                        "messages": [{"role": "user", "content": "Hello, world!"}],
+                        "answer": "Hello, world!",
+                    },
+                    {
+                        "messages": [
+                            {
+                                "role": "user",
+                                "content": "What is the capital of France?",
+                            }
+                        ],
+                        "answer": "Paris",
+                    },
+                ],
+            },
+            "localfs",
+            2,
+        ),
+        (
+            "eval/messages-answer",
+            {
+                "type": "uri",
+                "uri": data_url_from_file(os.path.join(os.path.dirname(__file__), "test_dataset.csv")),
+            },
+            "localfs",
+            5,
+        ),
+    ],
+)
+def test_register_and_iterrows(llama_stack_client, purpose, source, provider_id, limit):
+    dataset = llama_stack_client.datasets.register(
+        purpose=purpose,
+        source=source,
+    )
+    assert dataset.identifier is not None
+    assert dataset.provider_id == provider_id
+    iterrow_response = llama_stack_client.datasets.iterrows(dataset.identifier, limit=limit)
+    assert len(iterrow_response.data) == limit
+
+    dataset_list = llama_stack_client.datasets.list()
+    assert dataset.identifier in [d.identifier for d in dataset_list]
+
+    llama_stack_client.datasets.unregister(dataset.identifier)
+    dataset_list = llama_stack_client.datasets.list()
+    assert dataset.identifier not in [d.identifier for d in dataset_list]