community: Fix rank-llm import paths for new 0.20.3 version (#29154)

# **PR title**: "community: Fix rank-llm import paths for new 0.20.3
version"
- The "community" package is being modified to handle updated import
paths for the new `rank-llm` version.

---

## Description
This PR updates the import paths for the `rank-llm` package to account
for changes introduced in version `0.20.3`. The changes ensure
compatibility with both pre- and post-revamp versions of `rank-llm`,
specifically version `0.12.8`. Conditional imports are introduced based
on the detected version of `rank-llm` to handle different path
structures for `VicunaReranker`, `ZephyrReranker`, and `SafeOpenai`.

## Issue
RankLLMRerank usage throws an error when used GPT (not only) when
rank-llm version is > 0.12.8 - #29156

## Dependencies
This change relies on the `packaging` and `pkg_resources` libraries to
handle version checks.

## Twitter handle
@tymzar

libs/community/langchain_community/document_compressors/rankllm_rerank.py

@@ -2,12 +2,14 @@
 
 from copy import deepcopy
 from enum import Enum
+from importlib.metadata import version
 from typing import TYPE_CHECKING, Any, Dict, Optional, Sequence
 
 from langchain.retrievers.document_compressors.base import BaseDocumentCompressor
 from langchain_core.callbacks.manager import Callbacks
 from langchain_core.documents import Document
 from langchain_core.utils import get_from_dict_or_env
+from packaging.version import Version
 from pydantic import ConfigDict, Field, PrivateAttr, model_validator
 
 if TYPE_CHECKING:
@@ -49,6 +51,10 @@ def validate_environment(cls, values: Dict) -> Any:
         if not values.get("client"):
             client_name = values.get("model", "zephyr")
 
+            is_pre_rank_llm_revamp = Version(version=version("rank_llm")) <= Version(
+                "0.12.8"
+            )
+
             try:
                 model_enum = ModelType(client_name.lower())
             except ValueError:
@@ -58,15 +64,29 @@ def validate_environment(cls, values: Dict) -> Any:
 
             try:
                 if model_enum == ModelType.VICUNA:
-                    from rank_llm.rerank.vicuna_reranker import VicunaReranker
+                    if is_pre_rank_llm_revamp:
+                        from rank_llm.rerank.vicuna_reranker import VicunaReranker
+                    else:
+                        from rank_llm.rerank.listwise.vicuna_reranker import (
+                            VicunaReranker,
+                        )
 
                     values["client"] = VicunaReranker()
                 elif model_enum == ModelType.ZEPHYR:
-                    from rank_llm.rerank.zephyr_reranker import ZephyrReranker
+                    if is_pre_rank_llm_revamp:
+                        from rank_llm.rerank.zephyr_reranker import ZephyrReranker
+                    else:
+                        from rank_llm.rerank.listwise.zephyr_reranker import (
+                            ZephyrReranker,
+                        )
 
                     values["client"] = ZephyrReranker()
                 elif model_enum == ModelType.GPT:
-                    from rank_llm.rerank.rank_gpt import SafeOpenai
+                    if is_pre_rank_llm_revamp:
+                        from rank_llm.rerank.rank_gpt import SafeOpenai
+                    else:
+                        from rank_llm.rerank.listwise.rank_gpt import SafeOpenai
+
                     from rank_llm.rerank.reranker import Reranker
 
                     openai_api_key = get_from_dict_or_env(