Retrieval Augmented Generation (RAG) with Streamlit, LangChain and Pinecone

Watch the full tutorial on my YouTube Channel

 
 
 

Prerequisites

• Python 3.11+

Installation

1. Clone the repository:

git clone https://github.com/ThomasJanssen-tech/LangChain-Pinecone-RAG.git
cd LangChain Pinecone RAG

2. Create a virtual environment

python -m venv venv

3. Activate the virtual environment

venv\Scripts\Activate
(or on Mac): source venv/bin/activate

4. Install libraries

pip install -r requirements.txt

5. Create accounts

• Create a free account on Pinecone: https://www.pinecone.io/
• Create an API key for OpenAI: https://platform.openai.com/api-keys

6. Add API keys to .env file

• Rename .env.example to .env
• Add the API keys for Pinecone and OpenAI to the .env file

Executing the scripts

1. Open a terminal in VS Code

2. Execute the following command:

python sample_ingestion.py
python sample_retrieval.py
python ingestion.py
python retrieval.py
streamlit run chatbot_rag.py