qdrant: New sparse embeddings provider interface - PART 1 (#24015)

## Description

This PR introduces a new sparse embedding provider interface to work
with the new Qdrant implementation that will follow this PR.

Additionally, an implementation of this interface is provided with
https://github.com/qdrant/fastembed.

This PR will be followed by
https://github.com/Anush008/langchain/pull/3.

libs/partners/qdrant/langchain_qdrant/sparse_embeddings.py

@@ -0,0 +1,36 @@
+from abc import ABC, abstractmethod
+from typing import List
+
+from langchain_core.runnables.config import run_in_executor
+from pydantic import BaseModel, Field
+
+
+class SparseVector(BaseModel, extra="forbid"):
+    """
+    Sparse vector structure
+    """
+
+    indices: List[int] = Field(..., description="indices must be unique")
+    values: List[float] = Field(
+        ..., description="values and indices must be the same length"
+    )
+
+
+class SparseEmbeddings(ABC):
+    """An interface for sparse embedding models to use with Qdrant."""
+
+    @abstractmethod
+    def embed_documents(self, texts: List[str]) -> List[SparseVector]:
+        """Embed search docs."""
+
+    @abstractmethod
+    def embed_query(self, text: str) -> SparseVector:
+        """Embed query text."""
+
+    async def aembed_documents(self, texts: List[str]) -> List[SparseVector]:
+        """Asynchronous Embed search docs."""
+        return await run_in_executor(None, self.embed_documents, texts)
+
+    async def aembed_query(self, text: str) -> SparseVector:
+        """Asynchronous Embed query text."""
+        return await run_in_executor(None, self.embed_query, text)