Add calculate_day_score endpoint for emotion scoring

app.py

@@ -937,3 +937,118 @@ def get_mental_health_details(email: str):
         raise
     except Exception as e:
         raise HTTPException(status_code=500, detail=f"Error fetching mental health details: {str(e)}")
+
+
+# =============================================================================
+# DAILY EMOTION SCORE CALCULATION
+# =============================================================================
+
+# Valence Mapping for emotions
+EMO_VALENCE = {
+    "Angry": -0.80,
+    "Disgust": -0.60,
+    "Fear": -0.70,
+    "Happy": 0.90,
+    "Sad": -0.90,
+    "Surprise": 0.20,
+    "Neutral": 0.0,
+    # text emotions
+    "sadness": -0.90,
+    "joy": 0.90,
+    "love": 0.80,
+    "anger": -0.80,
+    "fear": -0.70,
+    "surprise": 0.20
+}
+
+def valence_from_probabilities(probabilities: Dict[str, float]) -> float:
+    if not probabilities:
+        return 0.0
+    v = 0.0
+    total = sum(probabilities.values()) or 1.0
+    for emo, p in probabilities.items():
+        key = emo if emo in EMO_VALENCE else emo.capitalize()
+        v += p * EMO_VALENCE.get(key, 0.0)
+    return v / total
+
+def valence_to_score(v: float) -> float:
+    return (v + 1) / 2 * 100  # [-1..1] → [0..100]
+
+class EmotionItem(BaseModel):
+    emotion: str
+    probabilities: Optional[Dict[str, float]] = None
+    confidence: Optional[float] = 1.0
+
+class ScoreRequest(BaseModel):
+    face_results: Optional[List[EmotionItem]] = []
+    audio_results: Optional[List[EmotionItem]] = []
+    text_results: Optional[List[EmotionItem]] = []
+
+@app.post("/calculate_day_score")
+def calculate_day_score(payload: ScoreRequest):
+    """Calculate weighted day score from face, audio, and text emotions."""
+    source_weights = {
+        "face": 0.4,
+        "audio": 0.35,
+        "text": 0.25
+    }
+
+    accum_num = 0.0
+    accum_den = 0.0
+    breakdown = {"face": [], "audio": [], "text": []}
+
+    # FACE
+    for item in payload.face_results:
+        v = valence_from_probabilities(item.probabilities) \
+            if item.probabilities else EMO_VALENCE.get(item.emotion, 0.0)
+        score = valence_to_score(v)
+        w = source_weights["face"] * (item.confidence or 1.0)
+        accum_num += score * w
+        accum_den += w
+        breakdown["face"].append({
+            "emotion": item.emotion,
+            "valence": v,
+            "score": score,
+            "weight": w
+        })
+
+    # AUDIO
+    for item in payload.audio_results:
+        v = valence_from_probabilities(item.probabilities) \
+            if item.probabilities else EMO_VALENCE.get(item.emotion, 0.0)
+        score = valence_to_score(v)
+        w = source_weights["audio"] * (item.confidence or 1.0)
+        accum_num += score * w
+        accum_den += w
+        breakdown["audio"].append({
+            "emotion": item.emotion,
+            "confidence": item.confidence,
+            "valence": v,
+            "score": score,
+            "weight": w
+        })
+
+    # TEXT
+    for item in payload.text_results:
+        v = valence_from_probabilities(item.probabilities) \
+            if item.probabilities else EMO_VALENCE.get(item.emotion.lower(), 0.0)
+        score = valence_to_score(v)
+        w = source_weights["text"] * (item.confidence or 1.0)
+        accum_num += score * w
+        accum_den += w
+        breakdown["text"].append({
+            "emotion": item.emotion,
+            "confidence": item.confidence,
+            "valence": v,
+            "score": score,
+            "weight": w
+        })
+
+    final_score = accum_num / accum_den if accum_den > 0 else None
+
+    return {
+        "day_score": final_score,
+        "breakdown": breakdown,
+        "numerator": accum_num,
+        "denominator": accum_den
+    }