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Update Neon cookbook README.md (#747)

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examples/vector_databases/neon/README.md
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## Vector search ## Vector search
Neon supports vector search using the [pgvector](https://neon.tech/docs/extensions/pgvector) open-source PostgreSQL extension, which enable Postgres as a vector database for storing and querying embeddings. Neon supports vector search using the [pgvector](https://neon.tech/docs/extensions/pgvector) open-source PostgreSQL extension, which enables Postgres as a vector database for storing and querying embeddings.
## OpenAI cookbook notebook ## OpenAI cookbook notebook
@ -17,7 +17,7 @@ In this notebook you will learn how to:
1. Use embeddings created by OpenAI API 1. Use embeddings created by OpenAI API
2. Store embeddings in a Neon Serverless Postgres database 2. Store embeddings in a Neon Serverless Postgres database
3. Convert a raw text query to an embedding with OpenAI API 3. Convert a raw text query to an embedding with OpenAI API
4. Use Neon with the `pg_vector` extension to perform vector similarity search 4. Use Neon with the `pgvector` extension to perform vector similarity search
## Scaling Support ## Scaling Support