Docs: typofix (run-llama#7927)

Author: Julien Bouquillon

docs/core_modules/data_modules/documents_and_nodes/usage_documents.md

@@ -70,7 +70,7 @@ documents = SimpleDirectoryReader('./data', file_metadata=filename_fn).load_data
 
 ### Customizing the id
 
-As detailed in the section [Document Management](../index/document_management.md), the `doc_id` is used to enable effecient refreshing of documents in the index. When using the `SimpleDirectoryReader`, you can automatically set the doc `doc_id` to be the full path to each document:
+As detailed in the section [Document Management](../index/document_management.md), the `doc_id` is used to enable efficient refreshing of documents in the index. When using the `SimpleDirectoryReader`, you can automatically set the doc `doc_id` to be the full path to each document:
 
 ```python
 from llama_index import SimpleDirectoryReader
@@ -93,7 +93,7 @@ A key detail mentioned above is that by default, any metadata you set is include
 
 #### Customizing LLM Metadata Text
 
-Typically, a document might have many metadata keys, but you might not want all of them visibile to the LLM during response synthesis. In the above examples, we may not want the LLM to read the `file_name` of our document. However, the `file_name` might include information that will help generate better embeddings. A key advantage of doing this is to bias the embeddings for retrieval without changing what the LLM ends up reading. 
+Typically, a document might have many metadata keys, but you might not want all of them visible to the LLM during response synthesis. In the above examples, we may not want the LLM to read the `file_name` of our document. However, the `file_name` might include information that will help generate better embeddings. A key advantage of doing this is to bias the embeddings for retrieval without changing what the LLM ends up reading. 
 
 We can exclude it like so:
 
@@ -110,7 +110,7 @@ print(document.get_content(metadata_mode=MetadataMode.LLM))
 
 #### Customizing Embedding Metadata Text
 
-Similar to customing the metadata visibile to the LLM, we can also customize the metadata visible to emebddings. In this case, you can specifically exclude metadata visible to the embedding model, in case you DON'T want particular text to bias the embeddings.
+Similar to customing the metadata visible to the LLM, we can also customize the metadata visible to embeddings. In this case, you can specifically exclude metadata visible to the embedding model, in case you DON'T want particular text to bias the embeddings.
 
 ```python
 document.excluded_embed_metadata_keys = ['file_name']
@@ -129,7 +129,7 @@ As you know by now, metadata is injected into the actual text of each document/n
 
 1. `Document.metadata_seperator` -> default = `"\n"`
 
-When concatenating all key/value fields of your metadata, this field controls the seperator bewtween each key/value pair.
+When concatenating all key/value fields of your metadata, this field controls the separator bewtween each key/value pair.
 
 2. `Document.metadata_template` -> default = `"{key}: {value}"`