adaptive local RAG agent with LLaMA3.2 🦙🔗

this project was me learning how retrieval augmented generation works by building a local RAG agent using llama 3.2 🚀 huge acknowledgements to LangChain and LangGraph tutorials and documentation

about 🌟

the adaptive local RAG agent uses LLaMA3.2 to enhance the generation of responses by incorporating relevant information retrieved from a local knowledge base 📚

features ✨

the RAG agent uses llama 3.2 has 3 components:

• Routing: Adaptive RAG to route questions to different retrieval approaches
• Fallback: Corrective RAG to fallback to general knowledge if docs are not relevant to the query
• Self Correction: Self-RAG to fix irrelevant answers or ones with hallucinations

installation 🛠️

installation steps:

1. clone the repository:

git clone https://github.com/yourusername/RAG-bot.git
cd RAG-bot

2. install dependencies:

pip install -r requirements.txt

usage 🚀

to run the adaptive local RAG agent, use the following command:

python main.py