feat(api): introduce /rerank (#2940)

# What does this PR do?
Context: https://github.com/meta-llama/llama-stack/issues/2937

The API design is inspired by existing offerings, but not exactly the
same:
* `top_n` as the parameter to control number of results, instead of
`top_k`, since `n` is conventional to control number
* `truncation` bool instead of `max_token_per_doc`, since we should just
handle the truncation automatically depending on model capability,
instead of user setting the context length manually.
* `data` field in the response, to be consistent with other OpenAI APIs
(though they don't have a rerank API). Also, it is one less name to
learn in the API.

## Test Plan

Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>

llama_stack/providers/remote/inference/ollama/ollama.py

@@ -37,11 +37,14 @@ from llama_stack.apis.inference import (
     Message,
     OpenAIChatCompletion,
     OpenAIChatCompletionChunk,
+    OpenAIChatCompletionContentPartImageParam,
+    OpenAIChatCompletionContentPartTextParam,
     OpenAICompletion,
     OpenAIEmbeddingsResponse,
     OpenAIEmbeddingUsage,
     OpenAIMessageParam,
     OpenAIResponseFormatParam,
+    RerankResponse,
     ResponseFormat,
     SamplingParams,
     TextTruncation,
@@ -641,6 +644,15 @@ class OllamaInferenceAdapter(
     ):
         raise NotImplementedError("Batch chat completion is not supported for Ollama")
 
+    async def rerank(
+        self,
+        model: str,
+        query: str | OpenAIChatCompletionContentPartTextParam | OpenAIChatCompletionContentPartImageParam,
+        items: list[str | OpenAIChatCompletionContentPartTextParam | OpenAIChatCompletionContentPartImageParam],
+        max_num_results: int | None = None,
+    ) -> RerankResponse:
+        raise NotImplementedError("Reranking is not supported for Ollama")
+
 
 async def convert_message_to_openai_dict_for_ollama(message: Message) -> list[dict]:
     async def _convert_content(content) -> dict: