Multi Agent System Architecture For Federal Funds Target Rate Prediction
by chirindaopensourceLearning Resourcesagent based modelingchain of draft reasoningcomputational financecrewaifed sight ai
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).
Multi Agent System Architecture For Federal Funds Target Rate Prediction is an open-source ai agent by chirindaopensource, written mainly in Jupyter Notebook, with 12 GitHub stars and the MIT license. Its code was last updated Jan 3, 2026.
Scan summary: scanned Nov 5, 2026 at commit 2817f0f. No capabilities flagged by our checks. Scan policy
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2817f0f · Nov 5, 2026 ScannedStatic, secrets and dependency checks completed with no critical findings.
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Findings (16)
- highHigh. Something risky that needs a close look before you install.dependencies issueDetails are available to the maintainer after claiming this listing.
- highHigh. Something risky that needs a close look before you install.dependencies issueDetails are available to the maintainer after claiming this listing.
- mediumMedium. Worth checking, often a vulnerable dependency or a setup problem.crewai-tools@0.17.0: 1 known vulnerabilityPYSEC-2026-3819
requirements.txt - mediumMedium. Worth checking, often a vulnerable dependency or a setup problem.cryptography@43.0.3: 6 known vulnerabilitiesPYSEC-2026-1284, PYSEC-2026-2141, PYSEC-2026-35, PYSEC-2026-3553, PYSEC-2026-3554 +1 more
requirements.txt - mediumMedium. Worth checking, often a vulnerable dependency or a setup problem.langchain@0.3.7: 2 known vulnerabilitiesPYSEC-2026-2192, PYSEC-2026-2555
requirements.txt - mediumMedium. Worth checking, often a vulnerable dependency or a setup problem.langchain-community@0.3.7: 1 known vulnerabilityPYSEC-2026-1515
requirements.txt - mediumMedium. Worth checking, often a vulnerable dependency or a setup problem.langchain-text-splitters@0.3.2: 2 known vulnerabilitiesPYSEC-2026-1520, PYSEC-2026-77
requirements.txt - mediumMedium. Worth checking, often a vulnerable dependency or a setup problem.lxml@5.3.0: 1 known vulnerabilityPYSEC-2026-87
requirements.txt - mediumMedium. Worth checking, often a vulnerable dependency or a setup problem.pypdf@5.1.0: 67 known vulnerabilitiesPYSEC-2026-1827, PYSEC-2026-1828, PYSEC-2026-1829, PYSEC-2026-1830, PYSEC-2026-1831 +62 more
requirements.txt - mediumMedium. Worth checking, often a vulnerable dependency or a setup problem.urllib3@2.2.3: 8 known vulnerabilitiesPYSEC-2026-141, PYSEC-2026-1994, PYSEC-2026-1996, PYSEC-2026-1997, PYSEC-2026-1998 +3 more
requirements.txt - mediumMedium. Worth checking, often a vulnerable dependency or a setup problem.Install or build failed in a clean environment: Because langchain-community==0.3.7 depends on langchain-core>=0.3.17,<0.4.0 and you require langchain-community==0.3.7, we can conclude that you require langchain-core>=0.3.17,<0.4.0. And because you require langchain-core==0.3.15, we can conclude that your requirements are unsatisfiable.
- lowLow. Minor, or common in normal tools. Shown for information.h2@4.1.0: 2 known vulnerabilitiesPYSEC-2026-1435, PYSEC-2026-3628
requirements.txt - lowLow. Minor, or common in normal tools. Shown for information.langchain-openai@0.2.8: 1 known vulnerabilityPYSEC-2026-76
requirements.txt - lowLow. Minor, or common in normal tools. Shown for information.python-dotenv@1.0.1: 1 known vulnerabilityPYSEC-2026-2270
requirements.txt - lowLow. Minor, or common in normal tools. Shown for information.requests@2.32.3: 2 known vulnerabilitiesPYSEC-2026-1872, PYSEC-2026-2275
requirements.txt - lowLow. Minor, or common in normal tools. Shown for information.No manifest declaring network access and environment variables (agent.json)
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