In my previous post using tools, I discussed how a Retrieval-Augmented Generation (RAG) system can be enhanced with plugins that handle specific queries using predefined functions. While this approach works well for a limited set of query types, it becomes difficult to scale as user queries become more diverse and complex. In this post, I’ll explore how we can use a plugin to generate dynamic SQL queries from natural language, enabling the AI assistant to answer a much broader range of questions.
Sql
All Posts
- llm (8)
- openai (7)
- ai-agent (5)
- rag (4)
- azure (4)
- tools (3)
- ai (2)
- mcp (2)
- vscode (2)
- microsoft-agent-framework (2)
- testing (1)
sql (1)
- multiagent (1)
- ai-foundry (1)
- agents (1)
- github-copilot (1)
- agent-framework (1)
- ag-ui (1)
- context-engineering (1)
- memory (1)
- apiops (1)
- devops (1)
- apim (1)
- azure-functions (1)
- aks (1)
- kubernetes (1)
- container (1)