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fix(tuto): fix minor typos (#3789)
* fix(tuto): fix minor typos * fix(tuto): fix tuto
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tutorials/how-to-implement-rag/index.mdx

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```sh
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pip install langchain psycopg2 python-dotenv
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```
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### Step 2: Create a .env file
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### Create a .env file
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Create a .env file and add the following variables. These will store your API keys, database connection details, and other configuration values.
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cur = conn.cursor()
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```
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## Embeddings and Vector Store Setup
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## Embeddings and vector store setup
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### Import Required Modules
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### Import required modules
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```python
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# rag.py
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### Configure OpenAI Embeddings
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We will utilize the [OpenAIEmbeddings](https://api.python.langchain.com/en/latest/embeddings/langchain_openai.embeddings.base.OpenAIEmbeddings.html) class from LangChain and store the embeddings in PostgreSQL using the PGVector integration.
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We will use the [OpenAIEmbeddings](https://api.python.langchain.com/en/latest/embeddings/langchain_openai.embeddings.base.OpenAIEmbeddings.html) class from LangChain and store the embeddings in PostgreSQL using the PGVector integration.
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```python
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# rag.py

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