Update to Vectara integration (#5950)

This PR updates the Vectara integration (@hwchase17 ):
* Adds reuse of requests.session to imrpove efficiency and speed.
* Utilizes Vectara's low-level API (instead of standard API) to better
match user's specific chunking with LangChain
* Now add_texts puts all the texts into a single Vectara document so
indexing is much faster.
* updated variables names from alpha to lambda_val (to be consistent
with Vectara docs) and added n_context_sentence so it's available to use
if needed.
* Updates to documentation and tests

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>

tests/integration_tests/vectorstores/test_vectara.py

@@ -27,7 +27,9 @@ def test_vectara_add_documents() -> None:
     )
 
     # finally do a similarity search to see if all works okay
-    output = docsearch.similarity_search("large language model", k=2)
+    output = docsearch.similarity_search(
+        "large language model", k=2, n_sentence_context=0
+    )
     assert output[0].page_content == "large language model"
     assert output[0].metadata == {"abbr": "llm"}
     assert output[1].page_content == "information retrieval"