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fix(tuto): fix minor typos #3789

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merged 2 commits into from
Oct 4, 2024
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fix(tuto): fix minor typos #3789

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b41002c
fix(tuto): fix minor typos
bene2k1 Oct 4, 2024
824a5de
fix(tuto): fix tuto
bene2k1 Oct 4, 2024
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8 changes: 4 additions & 4 deletions tutorials/how-to-implement-rag/index.mdx
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Expand Up @@ -40,7 +40,7 @@ Run the following command to install the required packages:
```sh
pip install langchain psycopg2 python-dotenv
```
### Step 2: Create a .env file
### Create a .env file

Create a .env file and add the following variables. These will store your API keys, database connection details, and other configuration values.

Expand Down Expand Up @@ -117,9 +117,9 @@ conn = psycopg2.connect(
cur = conn.cursor()
```

## Embeddings and Vector Store Setup
## Embeddings and vector store setup

### Import Required Modules
### Import required modules

```python
# rag.py
Expand All @@ -130,7 +130,7 @@ from langchain_postgres import PGVector

### Configure OpenAI Embeddings

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.
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.

```python
# rag.py
Expand Down