Add rerank models to the dynamic model list; Fix integration tests

tests/integration/inference/test_rerank.py

@@ -6,7 +6,7 @@
 
 import pytest
 from llama_stack_client import BadRequestError as LlamaStackBadRequestError
-from llama_stack_client.types import RerankResponse
+from llama_stack_client.types import InferenceRerankResponse
 from llama_stack_client.types.shared.interleaved_content import (
     ImageContentItem,
     ImageContentItemImage,
@@ -30,12 +30,12 @@ SUPPORTED_PROVIDERS = {"remote::nvidia"}
 PROVIDERS_SUPPORTING_MEDIA = {}  # Providers that support media input for rerank models
 
 
-def _validate_rerank_response(response: RerankResponse, items: list) -> None:
+def _validate_rerank_response(response: InferenceRerankResponse, items: list) -> None:
     """
     Validate that a rerank response has the correct structure and ordering.
 
     Args:
-        response: The RerankResponse to validate
+        response: The InferenceRerankResponse to validate
         items: The original items list that was ranked
 
     Raises:
@@ -43,7 +43,7 @@ def _validate_rerank_response(response: RerankResponse, items: list) -> None:
     """
     seen = set()
     last_score = float("inf")
-    for d in response.data:
+    for d in response:
         assert 0 <= d.index < len(items), f"Index {d.index} out of bounds for {len(items)} items"
         assert d.index not in seen, f"Duplicate index {d.index} found"
         seen.add(d.index)
@@ -52,22 +52,22 @@ def _validate_rerank_response(response: RerankResponse, items: list) -> None:
         last_score = d.relevance_score
 
 
-def _validate_semantic_ranking(response: RerankResponse, items: list, expected_first_item: str) -> None:
+def _validate_semantic_ranking(response: InferenceRerankResponse, items: list, expected_first_item: str) -> None:
     """
     Validate that the expected most relevant item ranks first.
 
     Args:
-        response: The RerankResponse to validate
+        response: The InferenceRerankResponse to validate
         items: The original items list that was ranked
         expected_first_item: The expected first item in the ranking
 
     Raises:
         AssertionError: If any validation fails
     """
-    if not response.data:
+    if not response:
         raise AssertionError("No ranking data returned in response")
 
-    actual_first_index = response.data[0].index
+    actual_first_index = response[0].index
     actual_first_item = items[actual_first_index]
     assert actual_first_item == expected_first_item, (
         f"Expected '{expected_first_item}' to rank first, but '{actual_first_item}' ranked first instead."
@@ -94,8 +94,9 @@ def test_rerank_text(client_with_models, rerank_model_id, query, items, inferenc
         pytest.xfail(f"{inference_provider_type} doesn't support rerank models yet. ")
 
     response = client_with_models.inference.rerank(model=rerank_model_id, query=query, items=items)
-    assert isinstance(response, RerankResponse)
-    assert len(response.data) <= len(items)
+    assert isinstance(response, list)
+    # TODO: Add type validation for response items once InferenceRerankResponseItem is exported from llama stack client.
+    assert len(response) <= len(items)
     _validate_rerank_response(response, items)
 
 
@@ -129,8 +130,8 @@ def test_rerank_image(client_with_models, rerank_model_id, query, items, inferen
     else:
         response = client_with_models.inference.rerank(model=rerank_model_id, query=query, items=items)
 
-        assert isinstance(response, RerankResponse)
-        assert len(response.data) <= len(items)
+        assert isinstance(response, list)
+        assert len(response) <= len(items)
         _validate_rerank_response(response, items)
 
 
@@ -148,8 +149,8 @@ def test_rerank_max_results(client_with_models, rerank_model_id, inference_provi
         max_num_results=max_num_results,
     )
 
-    assert isinstance(response, RerankResponse)
-    assert len(response.data) == max_num_results
+    assert isinstance(response, list)
+    assert len(response) == max_num_results
     _validate_rerank_response(response, items)
 
 
@@ -165,8 +166,8 @@ def test_rerank_max_results_larger_than_items(client_with_models, rerank_model_i
         max_num_results=10,  # Larger than items length
     )
 
-    assert isinstance(response, RerankResponse)
-    assert len(response.data) <= len(items)  # Should return at most len(items)
+    assert isinstance(response, list)
+    assert len(response) <= len(items)  # Should return at most len(items)
 
 
 @pytest.mark.parametrize(