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
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
3. Run the standalone script
# 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:
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
- SDK Documentation: https://docs.aicoevolution.com
License
MIT License - Use freely for research and commercial applications.
Citation
If you use this in research, please cite:
@article{jimenez2026orbital,
title={Semantic Orbital Mechanics: Measuring and Guiding AI Conversation Dynamics},
author={Jimenez Sanchez, Juan Jacobo},
journal={arXiv preprint},
year={2026}
}