DataDialogue

Our project aims to bridge the gap between non-technical users and databases by providing a natural language interface for querying data. Traditionally interacting with databases requires knowledge of query languages and complex syntax, which can be daunting for users unfamiliar with technical concepts. To address this challenge, we have developed a solution that allows users to express their queries in human language.

Our project's data dialogue utilizes DeltaV to power the user interface, bridging users and registered agents within the Agentverse. Users input two fields: the query and the database link they wish to query. This information is then processed by the fetch.ai *uagent, which invokes an API equipped with the logic to extract data from the specified database. The API leverages *Gemini LLM to translate the user's query into the appropriate syntax. Additionally, SQL Alchemy facilitates querying across various database types such as MYSQL, PostgreSQL, etc. The resulting query output is then formatted back into human-readable language using Gemini LLM before being sent back to the user interface via the uagent. This system empowers users to interact with databases without requiring expertise in Query Languages.

Traditional methods of querying databases require users to have knowledge of query languages such as SQL. This can be a barrier for non-technical users who may not be familiar with these languages. Our project aims to provide a user-friendly interface for querying databases using natural language.

Our solution is a web-based interface that allows users to input queries in natural language. The system then processes the query and extracts data from the specified database. The user is presented with the query results in a human-readable format, eliminating the need for users to learn complex query languages.