Update get_started.mdx (#8744)

- Description: Added a missing word and rearranged a sentence in the
documentation of Self Query Retrievers.,
  - Issue: NA,
  - Dependencies: NA,
  - Tag maintainer: @baskaryan,
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Thanks for your time.
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Snehil Kumar 1 year ago committed by GitHub
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@ -3,7 +3,7 @@ We'll use a Pinecone vector store in this example.
First we'll want to create a `Pinecone` VectorStore and seed it with some data. We've created a small demo set of documents that contain summaries of movies.
To use Pinecone, you to have `pinecone` package installed and you must have an API key and an Environment. Here are the [installation instructions](https://docs.pinecone.io/docs/quickstart).
To use Pinecone, you need to have `pinecone` package installed and you must have an API key and an Environment. Here are the [installation instructions](https://docs.pinecone.io/docs/quickstart).
NOTE: The self-query retriever requires you to have `lark` package installed.
@ -85,7 +85,7 @@ retriever = SelfQueryRetriever.from_llm(llm, vectorstore, document_content_descr
```
## Testing it out
And now we can try actually using our retriever!
And now we can actually try using our retriever!
```python
@ -198,4 +198,4 @@ retriever = SelfQueryRetriever.from_llm(
```python
# This example only specifies a relevant query
retriever.get_relevant_documents("What are two movies about dinosaurs")
```
```

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