Deep Dive into Retrieval Augmented Generation (RAG) with LangChain / Agents

🚀 Join us for an enlightening Ubuntu TechHive meetup where we'll take a deep dive into Retrieval Augmented Generation (RAG) with LangChain / Agents! Implementing advanced retrieval-augmented generation involves combining techniques from natural language processing (NLP), information retrieval (IR), and machine learning (ML) to generate coherent and contextually relevant responses.

🎯 Topics:

1. Problem Definition
2. Data Collection and Preprocessing
3. Retrieval Model
4. Generation Model
5. Integration and Architecture
6. Fine-tuning and Evaluation
7. Deployment and Monitoring
8. Continuous Improvement
9. Ethical Considerations During Implementation

We will utilize Vector-store, Python, and LangChain modules such as Model I/O, Retrieval, Agents, Chains, and many more. We will explore Naïve RAG and ways of optimizing it for retrieval quality.