chirindaopensource/multi_agent_system_architecture_for_federal_funds_target_rate_prediction

End-to-End Python implementation of "FedSight AI" multi-agent system for Federal Funds Target Rate prediction (NeurIPS 2025 Workshop). Simulates FOMC deliberations using LLMs with Chain-of-Draft reasoning and In-Context Learning. Integrates structured macro indicators with unstructured narratives (Beige Book, Dot Plots).

11
Stars
2
Forks
0.0
Radar Score
Declining
Momentum

Scoring Breakdown

Impact0.0
Velocity0.0
Health0.0

Growth Metrics

7-Day Stars
+0
30-Day Stars
+0
Acceleration
x
Language
Jupyter Notebook

Why it ranks

Momentum is cooling relative to the rest of the index.

AI Agents

🛡️ Enterprise Readiness & Commercial Safety

Organic Growth
95%
High Confidence
Growth pattern looks organic.
License
Permissive (Commercial Friendly)
Safe for commercial use, modification, and distribution.
Health Grade
C
Based on maintenance, issue response, and release cadence.
Radar Score
0.0
Composite of Impact, Velocity, and Health.
Disclaimer: This is an automated heuristic assessment based on public GitHub signals. Always perform your own security audit, dependency review, and legal compliance check before production deployment.

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