LLAMA-RAG-Agent

This project shows my journey in exploring LLAMA and RAG. Here, I create a basic agent with a set of tools: a note writer and a PDF reader. The agent can also analyze CSV data about BTC prices over the last 14 years. Data about all cryptocurrencies was taken from Kaggle.

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Tools

• md_noter: Makes and saves notes.
• pdf_reader: Creates a vector database and provides data from PDFs.

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1. Clone the Repository

Clone this repository to your local machine using:

git clone https://github.com/rifolio/LLAMA-RAG-Agent.git

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2. Set Up Virtual Environment

Navigate to the project directory and set up a virtual environment by running:

python3 -m venv ai

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3. Activate Virtual Environment

Activate the virtual environment using:

source ai/bin/activate

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4. Install Dependencies

Install the project dependencies using pip:

pip3 install -r requirements.txt

The requirements.txt file contains the following packages:

python-dotenv
pandas
llama-index
llama-index-experimental
pypdf

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5. Initialize API KEY from your OPEN AI Account in .env file and Run the Project

.env:
OPENAI_API_KEY=

Once the dependencies are installed, you can run the project using:

python3 main.py