giza-zkml-visualization · git:20260501.87cefc9 · 2026-05-01 · sha256 a899964c43169a5a
giza-zkml-visualization git:20260501.87cefc9A
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--- name: giza-zkml-visualization description: Giza ZKML Agent Visualization — guide covering key concepts, implementation patterns, and best practices. license: MIT metadata: category: development difficulty: advanced author: clawhub tags: [development, giza-zkml-visualization] --- # Giza ZKML Agent Visualization ## Overview Giza is a protocol for deploying verifiable AI agents on-chain using Zero-Knowledge Machine Learning (ZKML). This skill covers how Giza agents work, proof verification, and how to interpret the visualization dashboards in SperaxOS. ## Key Concepts ### Zero-Knowledge Machine Learning (ZKML) ZKML allows AI model inferences to be verified on-chain without revealing the model weights or input data. This creates **trustless AI** — anyone can verify that a model produced a specific output from a specific input, without needing to trust the model operator. ### Giza Agents On-chain AI agents deployed via the Giza protocol. Each agent: - Runs a specific ML model (e.g., price prediction, risk scoring) - Generates ZKML proofs for each inference - Can be deployed on multiple chains (Starknet, Ethereum, Arbitrum, etc.) - Has a verifiable track record of accuracy and performance ### Proof Systems Giza supports multiple proof backends: - **Cairo** — Native to Starknet, fastest proving time for StarkNet deployments - **Noir** — Aztec Labs' DSL for ZK circuits, good for Ethereum L1 - **RISC Zero** — General-purpose zkVM, supports any computation ## SperaxOS Visualization Tool ### Agent Overview Dashboard Shows all deployed Giza agents with: - **Status indicators** — Green (active), Yellow (pending), Red (inactive) - **Summary stats** — Total active agents, inference count, proof count - **Agent rows** — Name, chain, inference count, proof count per agent ### Proof History View Visualizes ZKML proof verification pipeline: - **Verification rate bar** — Color-coded segments showing verified/pending/failed ratios - **Proof rows** — Individual proofs with status badge, proof type (Cairo/Noir/RISC0), chain, duration, and timestamp - Use this to monitor proof verification health and identify failures ### Model Performance Dashboard Detailed metrics for a specific AI model: - **Accuracy gauge** — Green >95%, Yellow 85-95%, Red <85% - **Inference latency** — Average time per inference - **Proof generation time** — Average time to generate ZKML proof - **Inference volume sparkline** — 30-day trend of inference activity - **Chain deployment tags** — Which chains the model is deployed on ### Protocol Analytics Protocol-wide dashboard with: - **Hero stats** — Total agents, active agents, total proofs, 24h proof count - **Chain distribution bars** — Horizontal bars showing agent and proof distribution per chain - **Dual trend chart** — Overlapping proof volume (solid purple) and agent count (dashed green) trends ## Common Use Cases 1. **"Show me Giza AI agents"** → Agent Overview 2. **"What's the proof verification rate?"** → Proof History 3. **"How is model X performing?"** → Model Performance (requires modelId) 4. **"Give me Giza protocol stats"** → Protocol Analytics 5. **"Which chains have the most Giza agents?"** → Protocol Analytics chain breakdown ## Technical Details ### API Integration The tool connects to `api.gizatech.xyz/api/v1` with: - Automatic retry with exponential backoff (2 retries) - 12-second timeout per request - Graceful fallback to curated demo data when API is unavailable ### Data Freshness - Agent and proof data is fetched in real-time from Giza's API - Demo data is deterministically generated for consistent visualization when API is down - Proof timestamps and agent creation dates reflect actual on-chain activity ## Resources - [Giza GitHub](https://github.com/gizatechxyz) - [Giza Documentation](https://docs.gizatech.xyz) - [ZKML Explained](https://docs.gizatech.xyz/concepts/zkml)