# AICoevolution Semantic Telemetry **Measure conversational dynamics in real-time.** This open-source script demonstrates the core capabilities of the AICoevolution SDK for measuring semantic dynamics in human-AI conversations. ## What It Measures | Metric | Description | Range | |--------|-------------|-------| | **SGI (Orbital Radius)** | How balanced between query responsiveness and context grounding | ~0.5-1.5 | | **Velocity** | Rate of semantic movement per turn | 0-180° | | **Context Phase** | Topic coherence state | stable / protostar / split | | **Context Mass** | Accumulated turns in current topic | 0-N | | **Attractor Count** | Number of competing topic centers | 1+ | ## Quick Start ### 1. Install Dependencies ```bash pip install requests ``` ### 2. Get an API Key Get a free API key by loging in and generate it from the User settings/API Keys [https://aicoevolution.com](https://aicoevolution.com) ### 3. Run the standalone script ```bash # With cloud API python semantic_telemetry.py --api-key YOUR_API_KEY # Optional: custom SDK URL (e.g. local self-hosted) python semantic_telemetry.py --api-key YOUR_API_KEY --url http://localhost:8001 # Custom turns python semantic_telemetry.py --api-key YOUR_API_KEY --turns 20 ``` ## Minimal thin-client example (PyPI) If you prefer integrating the SDK via a Python dependency: ```bash pip install aicoevolution set AIC_SDK_API_KEY=aic_..... python hello_aicoevolution.py ``` ## Example Output ``` ╔═══════════════════════════════════════════════════════════════════════════════╗ ║ SEMANTIC TELEMETRY - AICoevolution SDK ║ ╚═══════════════════════════════════════════════════════════════════════════════╝ ────────────────────────────────────────────────── Turn 5/10 ────────────────────────────────────────────────── [YOU]: I'm trying to understand how meaning emerges in conversation [SDK] <- OK | SGI=0.952, Velocity=34.2° [AI]: Meaning emerges through the dynamic interplay between what's said and the accumulated context... [SDK] <- OK | SGI=0.891, Velocity=28.7° ────────────────────────────── SEMANTIC METRICS ────────────────────────────── SGI (Orbital Radius): 0.891 Velocity (degrees): 28.7° Context ID: ctx_1 Context State: stable Attractor Count: 1 Active Context Mass: 5 turns ────────────────────────────────────────────────────────────────────── ``` ## Understanding the Metrics ### Coherence Region Productive conversations tend to occupy: - **SGI**: 0.7 - 1.3 (balanced orbit) - **Velocity**: 15° - 60° (productive movement) ### Context Phases - **stable** (🟢): Conversation anchored to current topic - **protostar** (🟠): New topic forming, may switch soon - **split** (🔴): Topic changed, new context promoted ### Orbital Energy `E_orb = SGI × Velocity` - Higher = more dynamic, potentially unstable - Lower = more grounded, potentially stagnant ## Under Development The following metrics are planned for future releases: - **Domain Distribution**: Cognitive / Somatic / Emotional / Volitional balance - **Symbolic Depth (S64)**: Transformation path detection - **Mass Contribution**: Who is steering the conversation? - **Grammatical Hierarchy**: Geometric grammar detection ## Learn More - **Paper**: "Semantic Orbital Mechanics" (Jimenez Sanchez, 2026) - **Website**: [https://aicoevolution.com](https://aicoevolution.com) - **SDK Documentation**: [https://docs.aicoevolution.com](https://docs.aicoevolution.com) ## License MIT License - Use freely for research and commercial applications. ## Citation If you use this in research, please cite: ```bibtex @article{jimenez2026orbital, title={Semantic Orbital Mechanics: Measuring and Guiding AI Conversation Dynamics}, author={Jimenez Sanchez, Juan Jacobo}, journal={arXiv preprint}, year={2026} } ```