📅 2024-12-02 — Session: Developed Multi-Agent AI Ecosystem with NoSQL Integration
🕒 01:40–02:25
🏷️ Labels: Ai Agents, Nosql, Automation, Workflow, Classification
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal: The session aimed to design and implement a multi-agent AI ecosystem with a focus on automation and NoSQL integration for efficient data processing and classification.
Key Activities:
- Multi-Layered Processing Pipeline: Developed a detailed workflow for a classification agent, outlining each layer’s purpose and integration methods.
- Smart AI Agent Ecosystem Design: Planned a framework for a smart ecosystem of AI agents, emphasizing the classification and routing capabilities of the Smart First Agent and the roles of Specialized Second Agents.
- NoSQL Schema Extraction Layer: Implemented a workflow for a NoSQL-based schema extraction layer using OpenAI API and MongoDB, focusing on data validation and storage.
- Design of Smart Gatekeeper Agent: Outlined the design and functionality of the Smart Gatekeeper Agent, responsible for filtering, classifying, and routing messages using structured schemas and NoSQL parsing.
- Enhanced Gatekeeper Message Schema: Developed an improved schema for the Gatekeeper Agent, detailing structured metadata fields for processing messages.
Achievements:
- Successfully designed a comprehensive AI agent ecosystem with integrated NoSQL schema extraction.
- Established a robust processing pipeline for classification and message routing.
Pending Tasks:
- Further testing and validation of the NoSQL schema extraction layer.
- Optimization of the Smart Gatekeeper Agent’s routing algorithms for improved efficiency.