Fix: Groq API key check both GROQ_API and GROQ_API_KEY, improve fallback with varied poses

modules/art_reels/services/professional_stick_figure.py

@@ -130,12 +130,14 @@ class ProfessionalStickFigure:
     CHARACTER_Y = 1100
     
     def __init__(self, groq_api_key: str = None):
-        self.groq_api_key = groq_api_key or os.environ.get("GROQ_API_KEY")
+        # Try both GROQ_API (config) and GROQ_API_KEY env vars
+        self.groq_api_key = groq_api_key or os.environ.get("GROQ_API") or os.environ.get("GROQ_API_KEY")
         if self.groq_api_key:
             self.groq = Groq(api_key=self.groq_api_key)
+            logger.info("Groq API initialized for AI scene generation")
         else:
             self.groq = None
-            logger.warning("Groq API key not found - AI scene generation disabled")
+            logger.warning("Groq API key not found (GROQ_API or GROQ_API_KEY) - AI scene generation disabled")
         
         # Load fonts
         self._load_fonts()
@@ -203,11 +205,62 @@ Generate exactly {len(chunks)} scenes. Return ONLY valid JSON array."""
             return self._generate_fallback_scenes(chunks)
     
     def _generate_fallback_scenes(self, chunks: List[Dict]) -> List[Dict]:
-        """Fallback scene generation"""
+        """Fallback scene generation with varied poses and emotions"""
         scenes = []
+        
+        # Pose keywords for text detection
+        pose_keywords = {
+            "walking": ["walk", "walked", "forward", "step", "move", "journey"],
+            "running": ["run", "ran", "fast", "quick", "rush", "hurry"],
+            "sitting": ["sit", "sat", "rest", "relax", "seat", "chair"],
+            "sleeping": ["sleep", "slept", "tired", "exhausted", "rest", "night"],
+            "thinking": ["think", "thought", "wonder", "consider", "decide", "choice"],
+            "jumping": ["jump", "leap", "excited", "joy", "success", "win"],
+            "celebrating": ["celebrate", "success", "victory", "won", "achieve", "happy"],
+            "pointing": ["point", "show", "look", "direction", "this", "that"],
+            "talking": ["said", "told", "speak", "talk", "explain", "teach"],
+            "waving": ["hello", "hi", "bye", "goodbye", "wave", "greeting"]
+        }
+        
+        # Emotion keywords
+        emotion_keywords = {
+            "happy": ["happy", "joy", "success", "win", "good", "great", "smile"],
+            "sad": ["sad", "fail", "failed", "lost", "wrong", "bad", "sorry"],
+            "thinking": ["think", "wonder", "decide", "choose", "question"],
+            "excited": ["excited", "wow", "amazing", "incredible", "jump", "celebrate"],
+            "surprised": ["surprise", "shock", "unexpected", "suddenly"],
+            "confused": ["confused", "wonder", "how", "why", "what"]
+        }
+        
+        # Default poses for variety cycling
+        default_poses = ["standing", "walking", "pointing", "thinking", "talking", "waving"]
+        default_emotions = ["happy", "thinking", "excited", "happy"]
+        
         for i, chunk in enumerate(chunks):
             text = chunk.get("text", "").lower()
             
+            # Detect pose from text
+            detected_pose = None
+            for pose, keywords in pose_keywords.items():
+                if any(kw in text for kw in keywords):
+                    detected_pose = pose
+                    break
+            
+            # If no pose detected, cycle through defaults
+            if not detected_pose:
+                detected_pose = default_poses[i % len(default_poses)]
+            
+            # Detect emotion from text
+            detected_emotion = None
+            for emotion, keywords in emotion_keywords.items():
+                if any(kw in text for kw in keywords):
+                    detected_emotion = emotion
+                    break
+            
+            # If no emotion detected, cycle through defaults
+            if not detected_emotion:
+                detected_emotion = default_emotions[i % len(default_emotions)]
+            
             # Detect scene type
             scene_type = "single"
             if any(word in text for word in ["vs", "versus", "compare", "between", "both", "two"]):
@@ -215,16 +268,25 @@ Generate exactly {len(chunks)} scenes. Return ONLY valid JSON array."""
             elif any(word in text for word in ["introduce", "what is", "explained", "definition"]):
                 scene_type = "title"
             
-            scenes.append({
+            # Build scene
+            scene = {
                 "chunk_id": i,
                 "scene_type": scene_type,
                 "background": "white",
                 "title_text": text[:30].upper() if scene_type == "title" else None,
                 "characters": [
-                    {"position": "center", "pose": "standing", "emotion": "happy", "props": []}
+                    {
+                        "position": "center", 
+                        "pose": detected_pose, 
+                        "emotion": detected_emotion, 
+                        "props": []
+                    }
                 ] if scene_type != "title" else [],
                 "caption": text[:50] + "..." if len(text) > 50 else text
-            })
+            }
+            
+            scenes.append(scene)
+            logger.info(f"Fallback scene {i}: pose={detected_pose}, emotion={detected_emotion}")
         
         return scenes