docs: Arxiv docs update (#23871)

- [X] **PR title**
- [X] **PR message**: ***Delete this entire checklist*** and replace
with
    - **Description:** Update of docstrings and docpages
- **Issue:**
[22866](https://github.com/langchain-ai/langchain/issues/22866)

- [X] **Add tests and docs**

- [X] **Lint and test**

libs/community/langchain_community/document_loaders/arxiv.py

@@ -8,23 +8,146 @@ from langchain_community.utilities.arxiv import ArxivAPIWrapper
 
 class ArxivLoader(BaseLoader):
     """Load a query result from `Arxiv`.
-
     The loader converts the original PDF format into the text.
 
-    Args:
-        Supports all arguments of `ArxivAPIWrapper`.
-    """
+    Setup:
+        Install ``arxiv`` and ``PyMuPDF`` packages.
+        ``PyMuPDF`` transforms PDF files downloaded from the arxiv.org site
+        into the text format.
+
+        .. code-block:: bash
+
+            pip install -U arxiv pymupdf
+
+
+    Instantiate:
+        .. code-block:: python
+
+            from langchain_community.document_loaders import ArxivLoader
+
+            loader = ArxivLoader(
+                query="reasoning",
+                # load_max_docs=2,
+                # load_all_available_meta=False
+            )
+
+    Load:
+        .. code-block:: python
+
+            docs = loader.load()
+            print(docs[0].page_content[:100])
+            print(docs[0].metadata)
+
+        .. code-block:: python
+            Understanding the Reasoning Ability of Language Models
+            From the Perspective of Reasoning Paths Aggre
+            {
+                'Published': '2024-02-29',
+                'Title': 'Understanding the Reasoning Ability of Language Models From the
+                        Perspective of Reasoning Paths Aggregation',
+                'Authors': 'Xinyi Wang, Alfonso Amayuelas, Kexun Zhang, Liangming Pan,
+                        Wenhu Chen, William Yang Wang',
+                'Summary': 'Pre-trained language models (LMs) are able to perform complex reasoning
+                        without explicit fine-tuning...'
+            }
+
+
+    Lazy load:
+        .. code-block:: python
+
+            docs = []
+            docs_lazy = loader.lazy_load()
+
+            # async variant:
+            # docs_lazy = await loader.alazy_load()
+
+            for doc in docs_lazy:
+                docs.append(doc)
+            print(docs[0].page_content[:100])
+            print(docs[0].metadata)
+
+        .. code-block:: python
+
+            Understanding the Reasoning Ability of Language Models
+            From the Perspective of Reasoning Paths Aggre
+            {
+                'Published': '2024-02-29',
+                'Title': 'Understanding the Reasoning Ability of Language Models From the
+                        Perspective of Reasoning Paths Aggregation',
+                'Authors': 'Xinyi Wang, Alfonso Amayuelas, Kexun Zhang, Liangming Pan,
+                        Wenhu Chen, William Yang Wang',
+                'Summary': 'Pre-trained language models (LMs) are able to perform complex reasoning
+                        without explicit fine-tuning...'
+            }
+
+    Async load:
+        .. code-block:: python
+
+            docs = await loader.aload()
+            print(docs[0].page_content[:100])
+            print(docs[0].metadata)
+
+        .. code-block:: python
+
+            Understanding the Reasoning Ability of Language Models
+            From the Perspective of Reasoning Paths Aggre
+            {
+                'Published': '2024-02-29',
+                'Title': 'Understanding the Reasoning Ability of Language Models From the
+                        Perspective of Reasoning Paths Aggregation',
+                'Authors': 'Xinyi Wang, Alfonso Amayuelas, Kexun Zhang, Liangming Pan,
+                        Wenhu Chen, William Yang Wang',
+                'Summary': 'Pre-trained language models (LMs) are able to perform complex reasoning
+                        without explicit fine-tuning...'
+            }
+
+    Use summaries of articles as docs:
+        .. code-block:: python
+
+            from langchain_community.document_loaders import ArxivLoader
+
+            loader = ArxivLoader(
+                query="reasoning"
+            )
+
+            docs = loader.get_summaries_as_docs()
+            print(docs[0].page_content[:100])
+            print(docs[0].metadata)
+
+        .. code-block:: python
+
+            Pre-trained language models (LMs) are able to perform complex reasoning
+            without explicit fine-tuning
+            {
+                'Entry ID': 'http://arxiv.org/abs/2402.03268v2',
+                'Published': datetime.date(2024, 2, 29),
+                'Title': 'Understanding the Reasoning Ability of Language Models From the
+                        Perspective of Reasoning Paths Aggregation',
+                'Authors': 'Xinyi Wang, Alfonso Amayuelas, Kexun Zhang, Liangming Pan,
+                        Wenhu Chen, William Yang Wang'
+            }
+    """  # noqa: E501
 
     def __init__(
         self, query: str, doc_content_chars_max: Optional[int] = None, **kwargs: Any
     ):
+        """Initialize with search query to find documents in the Arxiv.
+        Supports all arguments of `ArxivAPIWrapper`.
+
+        Args:
+            query: free text which used to find documents in the Arxiv
+            doc_content_chars_max: cut limit for the length of a document's content
+        """  # noqa: E501
+
         self.query = query
         self.client = ArxivAPIWrapper(
             doc_content_chars_max=doc_content_chars_max, **kwargs
         )
 
     def lazy_load(self) -> Iterator[Document]:
+        """Lazy load Arvix documents"""
         yield from self.client.lazy_load(self.query)
 
     def get_summaries_as_docs(self) -> List[Document]:
+        """Uses papers summaries as documents rather than source Arvix papers"""
         return self.client.get_summaries_as_docs(self.query)