docs: integrations reference updates 13 (#25711)

Added missed provider pages and links. Fixed inconsistent formatting.
Added arxiv references to docstirngs.

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>

libs/community/langchain_community/embeddings/fastembed.py

@@ -12,6 +12,7 @@ MIN_VERSION = "0.2.0"
 
 class FastEmbedEmbeddings(BaseModel, Embeddings):
     """Qdrant FastEmbedding models.
+
     FastEmbed is a lightweight, fast, Python library built for embedding generation.
     See more documentation at:
     * https://github.com/qdrant/fastembed/

libs/community/langchain_community/vectorstores/faiss.py

@@ -74,6 +74,8 @@ def _len_check_if_sized(x: Any, y: Any, x_name: str, y_name: str) -> None:
 class FAISS(VectorStore):
     """FAISS vector store integration.
 
+    See [The FAISS Library](https://arxiv.org/pdf/2401.08281) paper.
+
     Setup:
         Install ``langchain_community`` and ``faiss-cpu`` python packages.
 

libs/langchain/langchain/chains/flare/base.py

@@ -73,7 +73,10 @@ def _low_confidence_spans(
 
 class FlareChain(Chain):
     """Chain that combines a retriever, a question generator,
-    and a response generator."""
+    and a response generator.
+
+    See [Active Retrieval Augmented Generation](https://arxiv.org/abs/2305.06983) paper.
+    """
 
     question_generator_chain: Runnable
     """Chain that generates questions from uncertain spans."""