Upload app.py

app.py

@@ -325,13 +325,36 @@ Now return a NEW JSON different from the example.
 
 
 def try_parse_json(text: str) -> Optional[Dict[str, Any]]:
+    """
+    Try to extract a JSON object from the model output.
+    Handles cases where the model wraps JSON in ``` or ```json fences.
+    """
     if not text:
         return None
-    match = re.search(r"\{[\s\S]*\}\s*$", text.strip())
+
+    stripped = text.strip()
+
+    # If the model wrapped the JSON in ``` or ```json fences, strip them.
+    if stripped.startswith("```"):
+        lines = stripped.splitlines()
+
+        # Drop the first line (``` or ```json)
+        lines = lines[1:]
+
+        # Drop final line if it's a closing fence
+        if lines and lines[-1].strip().startswith("```"):
+            lines = lines[:-1]
+
+        stripped = "\n".join(lines).strip()
+
+    # Now look for the first {...} block
+    match = re.search(r"\{[\s\S]*\}", stripped)
     if not match:
         return None
+
+    candidate = match.group(0)
     try:
-        return json.loads(match.group(0))
+        return json.loads(candidate)
     except Exception:
         return None
 
@@ -403,26 +426,66 @@ def model_call(prompt: str) -> str:
 
 
 def normalize_output(
-    data: Dict[str, Any], lang: str, category_key: str, variant: str
+    data: Dict[str, Any],
+    lang: str,
+    category_key: str,
+    variant: str
 ) -> Dict[str, Any]:
-    q = [str(x).strip() for x in data.get("questions", []) if str(x).strip()]
-    m = [str(x).strip() for x in data.get("micro_actions", []) if str(x).strip()]
+    """
+    Make model output always valid, even if the model returns emojis, wrong category labels,
+    capitalized names, or unexpected keys.
+    """
+
+    # --- FIX CATEGORY ---
+    raw_cat = str(data.get("category", "")).strip()
+
+    # Strip emojis
+    raw_cat = re.sub(r"[^\w\- ]+", "", raw_cat)
 
+    # Lowercase
+    raw_cat = raw_cat.lower()
+
+    # Map likely variants to internal keys
+    mapping = {
+        "alimentation": "alimentation",
+        "nutrition": "alimentation",
+        "mouvement": "mouvement",
+        "movement": "mouvement",
+        "cerveau": "cerveau",
+        "brain": "cerveau",
+        "liens": "liens",
+        "links": "liens",
+        "bienetre": "bien-etre",
+        "bien-etre": "bien-etre",
+        "wellbeing": "bien-etre",
+        "well being": "bien-etre",
+    }
+
+    # Choose corrected category
+    clean_cat = mapping.get(raw_cat, category_key)
+
+    # --- FIX QUESTIONS ---
+    q = [str(x).strip() for x in data.get("questions", []) if str(x).strip()]
     q = (q + [""] * 4)[:4]
+
+    # --- FIX MICRO-ACTIONS ---
+    m = [str(x).strip() for x in data.get("micro_actions", []) if str(x).strip()]
     m = (m + [""] * 2)[:2]
 
+    # --- FIX TONE ---
     if not data.get("tone"):
         if lang == "fr":
             tone = "ludique" if variant == "best" else "sincère"
         else:
             tone = "playful" if variant == "best" else "sincere"
     else:
-        tone = str(data["tone"])
+        tone = str(data.get("tone")).strip().lower()
 
+    # --- SAFETY NOTES ---
     safety_notes = str(data.get("safety_notes", ""))
 
     return {
-        "category": category_key,
+        "category": clean_cat,
         "language": lang,
         "questions": q,
         "micro_actions": m,