Compatible Database
- Japan Search (Under testing)
- NDL (Under testing)
- Utilize external interfaces (APIs) from multiple databases to retrieve metadata in response to user queries to the LLM, and then use RAG (Retrieval-Augmented Generation) to output the results of the database queries in natural language.
- Furthermore, through prompt engineering, it enables optimized output tailored to the each individual, facilitating not only for researchers and experts but also more wide range of people.
- The goal is to utilize multimodal AI (text, images, audio, etc.) for database retrieval and output visualization, allowing AI that has learned multimodal cognition to act as a hub between users and database. This enables multimedia search and output, creating a knowledge base that can process complex multimedia informations.
Coming soon!!!
Coming soon!!!
Coming soon!!!
Coming soon!!!
Core Functionality
- Task 1
- Query generation to SQL database through API.
- Retrieve RDF format information.
- Embedding to vector database.
- Generate responce.
- Expand supported database.
- Development of front end.
For any questions, feel free to reach out to me at [[email protected]].