From 45562ac2dbeea57a7e4ec89e226cb09ad2f46423 Mon Sep 17 00:00:00 2001
From: Mason Daugherty <github@mdrxy.com>
Date: Wed, 8 Oct 2025 23:40:35 -0400
Subject: [PATCH] chore(cohere): delete `CohereRerank`

---
 .../document_compressors/cohere_rerank.py     | 125 ------------------
 1 file changed, 125 deletions(-)
 delete mode 100644 libs/langchain/langchain_classic/retrievers/document_compressors/cohere_rerank.py

diff --git a/libs/langchain/langchain_classic/retrievers/document_compressors/cohere_rerank.py b/libs/langchain/langchain_classic/retrievers/document_compressors/cohere_rerank.py
deleted file mode 100644
index 8930f052c1576..0000000000000
--- a/libs/langchain/langchain_classic/retrievers/document_compressors/cohere_rerank.py
+++ /dev/null
@@ -1,125 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import Sequence
-from copy import deepcopy
-from typing import Any
-
-from langchain_core._api.deprecation import deprecated
-from langchain_core.callbacks import Callbacks
-from langchain_core.documents import BaseDocumentCompressor, Document
-from langchain_core.utils import get_from_dict_or_env
-from pydantic import ConfigDict, model_validator
-from typing_extensions import override
-
-
-@deprecated(
-    since="0.0.30",
-    removal="1.0",
-    alternative_import="langchain_cohere.CohereRerank",
-)
-class CohereRerank(BaseDocumentCompressor):
-    """Document compressor that uses `Cohere Rerank API`."""
-
-    client: Any = None
-    """Cohere client to use for compressing documents."""
-    top_n: int | None = 3
-    """Number of documents to return."""
-    model: str = "rerank-english-v2.0"
-    """Model to use for reranking."""
-    cohere_api_key: str | None = None
-    """Cohere API key. Must be specified directly or via environment variable
-        COHERE_API_KEY."""
-    user_agent: str = "langchain"
-    """Identifier for the application making the request."""
-
-    model_config = ConfigDict(
-        arbitrary_types_allowed=True,
-        extra="forbid",
-    )
-
-    @model_validator(mode="before")
-    @classmethod
-    def validate_environment(cls, values: dict) -> Any:
-        """Validate that api key and python package exists in environment."""
-        if not values.get("client"):
-            try:
-                import cohere
-            except ImportError as e:
-                msg = (
-                    "Could not import cohere python package. "
-                    "Please install it with `pip install cohere`."
-                )
-                raise ImportError(msg) from e
-            cohere_api_key = get_from_dict_or_env(
-                values,
-                "cohere_api_key",
-                "COHERE_API_KEY",
-            )
-            client_name = values.get("user_agent", "langchain")
-            values["client"] = cohere.Client(cohere_api_key, client_name=client_name)
-        return values
-
-    def rerank(
-        self,
-        documents: Sequence[str | Document | dict],
-        query: str,
-        *,
-        model: str | None = None,
-        top_n: int | None = -1,
-        max_chunks_per_doc: int | None = None,
-    ) -> list[dict[str, Any]]:
-        """Returns an ordered list of documents ordered by their relevance to the provided query.
-
-        Args:
-            query: The query to use for reranking.
-            documents: A sequence of documents to rerank.
-            model: The model to use for re-ranking. Default to self.model.
-            top_n : The number of results to return. If `None` returns all results.
-                Defaults to self.top_n.
-            max_chunks_per_doc : The maximum number of chunks derived from a document.
-        """  # noqa: E501
-        if len(documents) == 0:  # to avoid empty api call
-            return []
-        docs = [
-            doc.page_content if isinstance(doc, Document) else doc for doc in documents
-        ]
-        model = model or self.model
-        top_n = top_n if (top_n is None or top_n > 0) else self.top_n
-        results = self.client.rerank(
-            query=query,
-            documents=docs,
-            model=model,
-            top_n=top_n,
-            max_chunks_per_doc=max_chunks_per_doc,
-        )
-        if hasattr(results, "results"):
-            results = results.results
-        return [
-            {"index": res.index, "relevance_score": res.relevance_score}
-            for res in results
-        ]
-
-    @override
-    def compress_documents(
-        self,
-        documents: Sequence[Document],
-        query: str,
-        callbacks: Callbacks | None = None,
-    ) -> Sequence[Document]:
-        """Compress documents using Cohere's rerank API.
-
-        Args:
-            documents: A sequence of documents to compress.
-            query: The query to use for compressing the documents.
-            callbacks: Callbacks to run during the compression process.
-
-        Returns:
-            A sequence of compressed documents.
-        """
-        compressed = []
-        for res in self.rerank(documents, query):
-            doc = documents[res["index"]]
-            doc_copy = Document(doc.page_content, metadata=deepcopy(doc.metadata))
-            doc_copy.metadata["relevance_score"] = res["relevance_score"]
-            compressed.append(doc_copy)
-        return compressed