body-emotion-sensor 0.1.1

Body emotion mapper: structured emotion analysis (AnalysisInput) JSON to body-axis states and prompt tags

🫀 Body Emotion Sensor

Give your AI agent a persistent emotional system based on the TCM Five Zang and Five Elements model.

Quick Start · Features · How It Works · 简体中文

Why Body Emotion Sensor? 💖

Do you ever feel that AI agents lack a true sense of "self"? They might simulate emotions in text, but they don't have a persistent internal state that carries over between conversations.

Body Emotion Sensor is here to change that:

• Persistent State: Give your AI a long-term emotional and physical constitution (baseline) that evolves naturally.
• TCM Five Zang Model: Built on the traditional Chinese medicine concepts of the Five Elements (Metal, Wood, Water, Fire, Earth) to map complex emotional states.
• Turn-by-Turn Updates: Converts structured emotional analysis into real-time body state updates, affecting how the agent responds.

Quick Start 🚀

📥 Install:

pip install body-emotion-sensor

The visualization panel is included in the default install. After installation, you can use the CLI:

bes help
body-emotion-sensor help

🔄 Recommended Flow:

1. Print the constitution initialization prompt: bes prompt init
2. Initialize state: bes init-state --workspace /path/to/workspace --agent-id my-agent --name "My Agent" --init-json /path/to/init.json
3. Check readiness: bes check-init --workspace /path/to/workspace --agent-id my-agent --name "My Agent"
4. Bootstrap a new session: bes bootstrap --workspace /path/to/workspace --agent-id my-agent --name "My Agent"
5. Run turn updates: bes run --workspace /path/to/workspace --agent-id my-agent --name "My Agent" --input /path/to/analysis-input.json

Features 🧩

• State Persistence: Stores long-term body-emotion state per workspace and agent identity.
• Session Bootstrap: Generates TURN_CHANGE_TAGS, BODY_TAG, and BASELINE_PERSONA before a new session starts.
• Compact Prompt Payload: Provides a lightweight payload for reply shaping without overwhelming the context window.
• Traceable History: Keeps state/history data for debugging and visualization.
• Visualization Panel: Run bes panel to view the agent's emotional journey visually.

How It Works ✨

body-emotion-sensor distinguishes between two core concepts:

• baseline: The agent's native constitution and long-term personality color.
• current: The body state after the latest turn, influenced by recent interactions.

It converts one turn of structured emotional analysis JSON into persistent body-axis state updates and a compact prompt payload for the reply layer.

Development 🛠️

For local development:

pip install -e .
bes help

Visualization panel:

bes panel --workspace /path/to/workspace --agent-id my-agent

Repository-only docs remain in the source repo, for example:

• docs/五脏情绪映射全表.md
• docs/五脏情绪七阶状态表.md
• prompts/example-openclaw-agents.md
• prompts/example-openclaw-tools.md

License 📄

This project is released under the MIT license in the repository LICENSE.