[Evals API][11/n] huggingface dataset provider + mmlu scoring fn (#392)

* wip

* scoring fn api

* eval api

* eval task

* evaluate api update

* pre commit

* unwrap context -> config

* config field doc

* typo

* naming fix

* separate benchmark / app eval

* api name

* rename

* wip tests

* wip

* datasetio test

* delete unused

* fixture

* scoring resolve

* fix scoring register

* scoring test pass

* score batch

* scoring fix

* fix eval

* test eval works

* huggingface provider

* datasetdef files

* mmlu scoring fn

* test wip

* remove type ignore

* api refactor

* add default task_eval_id for routing

* add eval_id for jobs

* remove type ignore

* huggingface provider

* wip huggingface register

* only keep 1 run_eval

* fix optional

* register task required

* register task required

* delete old tests

* fix

* mmlu loose

* refactor

* msg

* fix tests

* move benchmark task def to file

* msg

* gen openapi

* openapi gen

* move dataset to hf llamastack repo

* remove todo

* refactor

* add register model to unit test

* rename

* register to client

* delete preregistered dataset/eval task

* comments

* huggingface -> remote adapter

* openapi gen

llama_stack/providers/utils/datasetio/url_utils.py

@@ -0,0 +1,45 @@
+# 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 io
+from urllib.parse import unquote
+
+import pandas
+
+from llama_models.llama3.api.datatypes import URL
+
+from llama_stack.providers.utils.memory.vector_store import parse_data_url
+
+
+def get_dataframe_from_url(url: URL):
+    df = None
+    if url.uri.endswith(".csv"):
+        df = pandas.read_csv(url.uri)
+    elif url.uri.endswith(".xlsx"):
+        df = pandas.read_excel(url.uri)
+    elif url.uri.startswith("data:"):
+        parts = parse_data_url(url.uri)
+        data = parts["data"]
+        if parts["is_base64"]:
+            data = base64.b64decode(data)
+        else:
+            data = unquote(data)
+            encoding = parts["encoding"] or "utf-8"
+            data = data.encode(encoding)
+
+        mime_type = parts["mimetype"]
+        mime_category = mime_type.split("/")[0]
+        data_bytes = io.BytesIO(data)
+
+        if mime_category == "text":
+            df = pandas.read_csv(data_bytes)
+        else:
+            df = pandas.read_excel(data_bytes)
+    else:
+        raise ValueError(f"Unsupported file type: {url}")
+
+    return df