detect_emotion
Analyze user text to detect emotions (28-class taxonomy) and compute adaptive sampling parameter deltas for personality-driven AI responses using Big Five scores.
Instructions
Classify the emotional tone of user text and compute adaptive sampling parameter adjustments.
Uses SamLowe/roberta-base-go_emotions (28-class taxonomy, ~100MB RAM, runs on Apple Silicon MPS). Returns the top-5 detected emotions and AutoTune parameter deltas that should be ADDED to the soul's base personality parameters before calling Ollama.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The user's message text to analyze. | |
| soul_openness | No | Soul's Big Five Openness score (0-100). | |
| soul_conscientiousness | No | Soul's Big Five Conscientiousness score (0-100). | |
| soul_extraversion | No | Soul's Big Five Extraversion score (0-100). | |
| soul_agreeableness | No | Soul's Big Five Agreeableness score (0-100). | |
| soul_neuroticism | No | Soul's Big Five Neuroticism score (0-100). |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |