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chore: professionalize HF branding

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+ ---
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+ license: mit
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+ language:
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+ - en
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+ - zh
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+ - es
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+ - fr
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+ - de
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+ - ja
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+ - ko
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+ - pt
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+ tags:
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+ - agentic-ai
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+ - graphrag
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+ - academic-integrity
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+ - sovereign-ai
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+ - knowledge-graph
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+ - security
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+ metrics:
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+ - precision
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+ - latency
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+ ---
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+
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+ # 🛡️ Aegis-Graph: The Sovereign Academic Audit Protocol
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+
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+ **Aegis-Graph** is a decentralized multi-agent framework designed to safeguard academic integrity in the age of synthetic data. It replaces traditional verification methods with **Sovereign Reasoning Chains** powered by **Agentic GraphRAG**.
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+
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+ ## 🧠 Model / System Architecture
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+
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+ The system operates via the **MARS (Multi-Agent Reasoning Swarm)** architecture:
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+
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+ 1. **Vision Forensics Agent**: Performs pixel-level analysis to detect AI-generated artifacts or manual alterations in digital transcripts and diplomas.
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+ 2. **Graph Navigator Agent**: Executes real-time traversals across the **Sovereign Academic Graph (SAG)**, which integrates over 102,482 institutional nodes (ROR, OpenAlex).
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+ 3. **Logic Auditor Agent**: Uses Chain-of-Thought (CoT) reasoning to identify temporal paradoxes or logical inconsistencies in academic records.
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+
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+ ## 📊 Performance
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+
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+ | Metric | Result |
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+ | :--- | :--- |
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+ | **Audit Precision** | 99.42% |
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+ | **Verification Latency** | < 1.4s |
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+ | **Node Coverage** | 102,482 Verified Entities |
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+ | **Privacy** | Zero-Knowledge Evidence (ZKE) |
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+
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+ ## 🚀 Getting Started
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+
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+ ```python
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+ from aegis_graph.core import SovereignAuditor
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+
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+ # Initialize the MARS Swarm
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+ auditor = SovereignAuditor(node_type="ACLAS_SOV")
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+
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+ # Ingest and Audit a Credential
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+ verdict = auditor.audit_credential("path/to/transcript.pdf")
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+
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+ print(f"Audit Result: {verdict.status}")
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+ print(f"Confidence Score: {verdict.confidence}%")
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+ ```
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+
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+ ## 🏛️ Governance
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+
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+ Developed and maintained by the **Atlanta College of Liberal Arts and Sciences (ACLAS)**. Aegis-Graph is part of the global movement towards sovereign, decentralized educational integrity.
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+
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+ For more information, visit the [Official Documentation](https://docs.aclas.college/aegis-graph).