From 0da88990e64f89f922ea26db43ace2cc59e83bf6 Mon Sep 17 00:00:00 2001 From: Michele Pangrazzi Date: Tue, 3 Dec 2024 09:49:54 +0100 Subject: [PATCH] fix lint --- integrations/mongodb_atlas/examples/embedding_retrieval.py | 5 +++-- integrations/mongodb_atlas/examples/hybrid_retrieval.py | 5 +++-- 2 files changed, 6 insertions(+), 4 deletions(-) diff --git a/integrations/mongodb_atlas/examples/embedding_retrieval.py b/integrations/mongodb_atlas/examples/embedding_retrieval.py index 79d6ee4b3..d8a71c343 100644 --- a/integrations/mongodb_atlas/examples/embedding_retrieval.py +++ b/integrations/mongodb_atlas/examples/embedding_retrieval.py @@ -19,7 +19,8 @@ # To use the MongoDBAtlasDocumentStore, you must have a running MongoDB Atlas database. # For details, see https://www.mongodb.com/docs/atlas/getting-started/ -# NOTE: you need to create manually the vector search index and the full text search index in your MongoDB Atlas database. +# NOTE: you need to create manually the vector search index and the full text search +# index in your MongoDB Atlas database. # Once your database is set, set the environment variable `MONGO_CONNECTION_STRING` # with the connection string to your MongoDB Atlas database. @@ -40,7 +41,7 @@ # Create the indexing Pipeline and index some documents file_paths = glob.glob("neural-search-pills/pills/*.md") -print(f"Creating indexing pipeline") +print("Creating indexing pipeline") indexing = Pipeline() indexing.add_component("converter", MarkdownToDocument()) indexing.add_component("splitter", DocumentSplitter(split_by="sentence", split_length=2)) diff --git a/integrations/mongodb_atlas/examples/hybrid_retrieval.py b/integrations/mongodb_atlas/examples/hybrid_retrieval.py index b5f637d58..a165edf12 100644 --- a/integrations/mongodb_atlas/examples/hybrid_retrieval.py +++ b/integrations/mongodb_atlas/examples/hybrid_retrieval.py @@ -23,7 +23,8 @@ # To use the MongoDBAtlasDocumentStore, you must have a running MongoDB Atlas database. # For details, see https://www.mongodb.com/docs/atlas/getting-started/ -# NOTE: you need to create manually the vector search index and the full text search index in your MongoDB Atlas database. +# NOTE: you need to create manually the vector search index and the full text search +# index in your MongoDB Atlas database. # Once your database is set, set the environment variable `MONGO_CONNECTION_STRING` # with the connection string to your MongoDB Atlas database. @@ -43,7 +44,7 @@ print(f"Cleaning up collection {document_store.collection_name}") document_store.collection.delete_many({}) -print(f"Creating indexing pipeline with") +print("Creating indexing pipeline") indexing = Pipeline() indexing.add_component("converter", MarkdownToDocument()) indexing.add_component("splitter", DocumentSplitter(split_by="sentence", split_length=2))