Fix a few typos and wrapped f-strings (#128)

Fix a few typos and wrapped f-strings

langchain/docstore/wikipedia.py

@@ -32,11 +32,7 @@ class Wikipedia(Docstore):
             page_content = wikipedia.page(search).content
             result: Union[str, Document] = Document(page_content=page_content)
         except wikipedia.PageError:
-            result = (
-                f"Could not find [{search}]. " f"Similar: {wikipedia.search(search)}"
-            )
+            result = f"Could not find [{search}]. Similar: {wikipedia.search(search)}"
         except wikipedia.DisambiguationError:
-            result = (
-                f"Could not find [{search}]. " f"Similar: {wikipedia.search(search)}"
-            )
+            result = f"Could not find [{search}]. Similar: {wikipedia.search(search)}"
         return result

langchain/vectorstores/elastic_vector_search.py

@@ -55,7 +55,7 @@ class ElasticVectorSearch(VectorStore):
             import elasticsearch
         except ImportError:
             raise ValueError(
-                "Could not import elasticsearch python packge. "
+                "Could not import elasticsearch python package. "
                 "Please install it with `pip install elasticearch`."
             )
         self.embedding_function = embedding_function
@@ -64,7 +64,7 @@ class ElasticVectorSearch(VectorStore):
             es_client = elasticsearch.Elasticsearch(elasticsearch_url)  # noqa
         except ValueError as e:
             raise ValueError(
-                "Your elasticsearch client string is misformatted. " f"Got error: {e} "
+                f"Your elasticsearch client string is misformatted. Got error: {e} "
             )
         self.client = es_client
 
@@ -91,7 +91,7 @@ class ElasticVectorSearch(VectorStore):
     ) -> "ElasticVectorSearch":
         """Construct ElasticVectorSearch wrapper from raw documents.
 
-        This is a user friendly interface that:
+        This is a user-friendly interface that:
             1. Embeds documents.
             2. Creates a new index for the embeddings in the Elasticsearch instance.
             3. Adds the documents to the newly created Elasticsearch index.
@@ -125,7 +125,7 @@ class ElasticVectorSearch(VectorStore):
             from elasticsearch.helpers import bulk
         except ImportError:
             raise ValueError(
-                "Could not import elasticsearch python packge. "
+                "Could not import elasticsearch python package. "
                 "Please install it with `pip install elasticearch`."
             )
         try: