LLM for Retail Business – AI-powered assistant project
OtherTextPrompt Response Writing SFT
Developed an AI-powered retail assistant using language models to translate natural language queries into SQL for real-time business insights. Designed workflows that leveraged LLMs for handling and interpreting retail data to optimize inventory levels and sales trends. Used prompt engineering and SQL generation to facilitate decision-making and automate business queries for retail management.
• Created prompt templates to train the LLM on domain-specific retail questions.
• Generated labeled prompt-response pairs for natural language to SQL conversion.
• Evaluated and refined language model outputs to ensure accuracy of business insights.
• Deployed LLM solutions using Streamlit and MySQL for end-user interaction.
Developed an AI-powered retail assistant using language models to translate natural language queries into SQL for real-time business insights. Designed workflows that leveraged LLMs for handling and interpreting retail data to optimize inventory levels and sales trends. Used prompt engineering and SQL generation to facilitate decision-making and automate business queries for retail management. • Created prompt templates to train the LLM on domain-specific retail questions. • Generated labeled prompt-response pairs for natural language to SQL conversion. • Evaluated and refined language model outputs to ensure accuracy of business insights. • Deployed LLM solutions using Streamlit and MySQL for end-user interaction.
Not specified