Create innovative chatbot applications that utilizes LanceDB for efficient vector-based response generation! πβ¨
Introduction πβ¨
Users can input their queries, allowing the chatbot to retrieve relevant context seamlessly. ππ This enables the generation of coherent and context-aware replies that enhance user experience. ππ€ Dive into the world of advanced conversational AI and streamline interactions with powerful data management! ππ‘
Chatbot
Description
Links
Databricks DBRX Website Bot β‘οΈ
Engage with the Hogwarts chatbot, that uses Open-source RAG with DBRX, LanceDB and LLama-index with Hugging Face Embeddings, to provide interactive and engaging user experiences. β¨
CLI SDK Manual Chatbot Locally π»
CLI chatbot for SDK/hardware documents using Local RAG with LLama3, Ollama, LanceDB, and Openhermes Embeddings, built with Phidata Assistant and Knowledge Base π€
Youtube Transcript Search QA Bot πΉ
Search through youtube transcripts using natural language with a Q&A bot, leveraging LanceDB for effortless data storage and management π¬
Code Documentation Q&A Bot with LangChain π€
Query your own documentation easily using questions in natural language with a Q&A bot, powered by LangChain and LanceDB, demonstrated with Numpy 1.26 docs π
Context-aware Chatbot using Llama 2 & LanceDB π€
Build conversational AI with a context-aware chatbot, powered by Llama 2, LanceDB, and LangChain, that enables intuitive and meaningful conversations with your data ππ¬
Chat with csv using Hybrid Search π
Chat application that interacts with CSV and Excel files using LanceDBβs hybrid search capabilities, performing direct operations on large-scale columnar data efficiently π