Apply suggestions from code review

Co-authored-by: Michał Olender <[email protected]>

Author: jirispilka

sources/platform/integrations/ai/langchain.md

@@ -15,8 +15,8 @@ slug: /integrations/langchain
 In this example, we'll use the [Website Content Crawler](https://apify.com/apify/website-content-crawler) Actor, which can deeply crawl websites such as documentation, knowledge bases, help centers, or blogs and extract text content from the web pages.
 Then we feed the documents into a vector index and answer questions from it.
 
-This example focuses on how to integrate Apify with LangChain using the Python language,
-but if you prefer to use JavaScript, you can follow the same steps in the [JavaScript LangChain documentation](https://js.langchain.com/docs/integrations/document_loaders/web_loaders/apify_dataset/).
+This example demonstrates how to integrate Apify with LangChain using the Python language.
+If you prefer to use JavaScript, you can follow the  [JavaScript LangChain documentation](https://js.langchain.com/docs/integrations/document_loaders/web_loaders/apify_dataset/).
 
 Before we start with the integration, we need to install all dependencies:
 
@@ -126,7 +126,7 @@ LangChain is a standard interface through which you can interact with a variety
 It provides modules you can use to build language model applications as well as chains and agents with memory capabilities.
 
 You can use all of Apify’s Actors as document loaders in LangChain.
-For example, to incorporate web browsing functionality, you can use the [RAG-Web-Browser](https://apify.com/apify/rag-web-browser) Actor.
+For example, to incorporate web browsing functionality, you can use the [RAG-Web-Browser Actor](https://apify.com/apify/rag-web-browser).
 This allows you to either crawl and scrape top pages from Google Search results or directly scrape text content from a URL and return it as Markdown.
 To set this up, change the `actor_id` to `apify/rag-web-browser` and specify the `run_input`.
 
@@ -139,7 +139,7 @@ loader = apify.call_actor(
 print("Documents:", loader.load())
 ```
 
-In the similar way, you can use other Apify Actors to load data into LangChain and query the vector index.
+Similarly, you can use other Apify Actors to load data into LangChain and query the vector index.
 
 ## Resources