**Chatbot applications with LanceDB π€**
====================================================================
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¨ | [][databricks_github]
[][databricks_python] |
| **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€ | [][clisdk_github]
[][clisdk_python] |
| **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¬ | [][youtube_github]
[][youtube_colab]
[][youtube_python] |
| **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 | [][docs_github]
[][docs_colab]
[][docs_python] |
| **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¬ | [][aware_github]
[][aware_colab]
[][aware_ghost] |
| **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 | [][csv_github]
[][csv_colab]
[][csv_ghost] |
[databricks_github]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/databricks_DBRX_website_bot
[databricks_python]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/databricks_DBRX_website_bot/main.py
[clisdk_github]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/CLI-SDK-Manual-Chatbot-Locally
[clisdk_python]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/CLI-SDK-Manual-Chatbot-Locally/assistant.py
[youtube_github]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/Youtube-Search-QA-Bot
[youtube_colab]: https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Youtube-Search-QA-Bot/main.ipynb
[youtube_python]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/Youtube-Search-QA-Bot/main.py
[docs_github]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/Code-Documentation-QA-Bot
[docs_colab]: https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/Code-Documentation-QA-Bot/main.ipynb
[docs_python]: https://github.com/lancedb/vectordb-recipes/blob/main/examples/Code-Documentation-QA-Bot/main.py
[aware_github]: https://github.com/lancedb/vectordb-recipes/blob/main/tutorials/chatbot_using_Llama2_&_lanceDB
[aware_colab]: https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/chatbot_using_Llama2_&_lanceDB/main.ipynb
[aware_ghost]: https://blog.lancedb.com/context-aware-chatbot-using-llama-2-lancedb-as-vector-database-4d771d95c755
[csv_github]: https://github.com/lancedb/vectordb-recipes/tree/main/examples/archived_examples/Chat_with_csv_file
[csv_colab]: https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/examples/archived_examples/Chat_with_csv_file/main.ipynb
[csv_ghost]: https://blog.lancedb.com/p/d8c71df4-e55f-479a-819e-cde13354a6a3/