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For validation purposes, we provide outputs from various components through the terminal. This includes following steps in series in the below figure.
a) Query decomposer
b) Text to SQL conversion of the SQL component
c) Execute query on DDAE
d) SQL results to text conversion
e) Response generated by LLM from relevant context of SQL component from DDAE and non-SQL component from VectorDB
Displays the decomposition of user queries into SQL and non-SQL components. Below image shows the highlights of the RAG flow, suer query, refined query, executable SQL components and non-SQL components.
The transition from natural language queries to executable SQL and back to textual responses is seamless and accurate. This process consists of three main steps: converting text to SQL, executing the SQL on the DDAE, and transforming SQL results into natural language text.
The LLM synthesizes the final response using the context provided by both SQL components from the DDAE and non-SQL components retrieved from the Vector Database. This synthesis ensures that the response is both comprehensive and contextually relevant to the user's query.
By demonstrating these elements, we ensure that the integration of the UI, DDAE, VectorDB, and LLM functions as expected, delivering accurate and contextually relevant information in response to user queries.