RAGGENIE: An open-source, low-code platform to build custom Retrieval-Augmented Generation (RAG) Copilets with your own data. Simplify AI development with ease!
Description:
Add a new feature to integrate a VectorDB into the bot configuration, enhancing the bot's ability to store and retrieve vector-based data efficiently.
Tasks:
Implement backend support for MongoDB and ChromaDB as VectorDBs, adding test credentials for both to facilitate testing and development.
Logic will be added to check for vector data in the database; if present, it will load from VectorDB, otherwise, it will proceed with the default configuration.
Integrate the API to add and edit the VectorDB in the bot configuration.
Develop the UI for selecting the database name and displaying relevant fields as required.
Implement and test the database and configuration features.
Description: Add a new feature to integrate a VectorDB into the bot configuration, enhancing the bot's ability to store and retrieve vector-based data efficiently.
Tasks: