📅 2024-09-16 — Session: Developed AI-Driven NoSQL Schema Mapping Workflow
🕒 16:55–17:25
🏷️ Labels: AI, Nosql, Openai, Schema Mapping, Automation
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to develop a workflow for mapping natural language texts into structured NoSQL schemas using AI agents, particularly leveraging OpenAI’s tools.
Key Activities
- Explored the use of AI agents constrained by a NoSQL schema to map extracted entities from texts into structured data fields.
- Outlined a dynamic workflow for AI-driven NoSQL schema mapping, enhancing data interaction and flexibility.
- Compared Text-to-SQL tasks with the goal of mapping legal texts into NoSQL schemas, focusing on flexible data extraction.
- Detailed the process of transforming natural language texts into NoSQL schemas, including steps like entity recognition and relationship extraction.
- Utilized OpenAI’s tools to extract entities and convert them into NoSQL schemas, including API usage and model fine-tuning.
- Provided a structured guide for teaching AI agents to generate NoSQL schemas using OpenAI Functions.
- Compiled questions for API documentation to clarify OpenAI Functions usage, focusing on JSON schema and error handling.
- Discussed key points on JSON schema structure and NoSQL management.
- Reflected on fine-tuning models with OpenAI Functions, best practices, and dataset size recommendations.
- Outlined API limitations and cost considerations for using OpenAI Functions.
- Defined tasks for Project Manager and Lead Developer for initial project phases.
- Provided Bash commands for project setup and OpenAI Functions implementation.
Achievements
- Developed a comprehensive workflow for AI-driven NoSQL schema mapping.
- Established guidelines for using OpenAI Functions effectively.
- Identified key considerations for fine-tuning and cost management.
Pending Tasks
- Further refine the workflow based on API documentation clarifications.
- Implement the workflow in a live environment and monitor performance.
- Explore additional fine-tuning techniques to optimize schema generation.