langchain[minor], community[minor]: add CrossEncoderReranker with HuggingFaceCrossEncoder and SagemakerEndpointCrossEncoder (#13687)

- **Description:** Support reranking based on cross encoder models
available from HuggingFace.
      - Added `CrossEncoder` schema
- Implemented `HuggingFaceCrossEncoder` and
`SagemakerEndpointCrossEncoder`
- Implemented `CrossEncoderReranker` that performs similar functionality
to `CohereRerank`
- Added `cross-encoder-reranker.ipynb` to demonstrate how to use it.
Please let me know if anything else needs to be done to make it visible
on the table-of-contents navigation bar on the left, or on the card list
on [retrievers documentation
page](https://python.langchain.com/docs/integrations/retrievers).
  - **Issue:** N/A
  - **Dependencies:** None other than the existing ones.

---------

Co-authored-by: Kenny Choe <kchoe@amazon.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>

libs/community/langchain_community/cross_encoders/fake.py

@@ -0,0 +1,18 @@
+from difflib import SequenceMatcher
+from typing import List, Tuple
+
+from langchain_core.pydantic_v1 import BaseModel
+
+from langchain_community.cross_encoders.base import BaseCrossEncoder
+
+
+class FakeCrossEncoder(BaseCrossEncoder, BaseModel):
+    """Fake cross encoder model."""
+
+    def score(self, text_pairs: List[Tuple[str, str]]) -> List[float]:
+        scores = list(
+            map(
+                lambda pair: SequenceMatcher(None, pair[0], pair[1]).ratio(), text_pairs
+            )
+        )
+        return scores