AI-Powered Customer Support Chatbot Using RAG

"The project was complete and worked as expected. The RAG concept is implemented properly and the overall application is suitable for both academic submission and learning. It also gave me a good topic to discuss during my viva."

"The chatbot performs really well for product-related questions. I tested price inquiries, recommendations, comparisons and category searches, and the responses were relevant and easy to understand. It feels much more intelligent than a traditional chatbot."

"I was searching for a modern AI project involving RAG and LLMs, and this was a great choice. The project covers FastAPI, LangChain, Hugging Face and Groq integration, so I learned several useful technologies through a single application."

"Working with this project helped me understand embeddings, vector databases and LLM integration much better. I especially liked how ChromaDB is used to retrieve relevant information before sending context to the language model."

"The project is implemented in a very practical way. I was able to understand the complete flow from user query to vector search and finally the AI-generated response. It was also easy to demonstrate different product, price and comparison queries."