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Year
2024
Tech & Technique
Python, Google Gemini API, Multi-Agent Systems, Pandas, Scikit-learn
Description
Multi-Agent AI Competition Assistant.
Key Features:
Technical Highlights:
Key Features:
- 🤖 Specialized Agents: Model Improvement, Feature Engineering, Debugging, Strategy, and Insights agents.
- 🧠 Memory System: Maintains rolling conversation context and summarized memory snapshots.
- 🛠️ Custom Tools: Function calling for ML workflows (e.g., suggest_model_improvements, debug_code_issue).
- 📊 Observability: Comprehensive logging of agent routing, execution time, and error traces.
Technical Highlights:
- Architected a multi-agent system using Google Gemini API for reasoning and tool routing.
- Implemented a central Coordinator Agent to intelligently route queries to specialized experts.
- Built a production-style orchestration with stateful/stateless agent mix and error-resistant execution.
My Role
Lead Developer
- Designed the multi-agent architecture and coordinator logic.
- Integrated Google Gemini API and custom ML tools.