Upload app.py

app.py

@@ -85,7 +85,21 @@ def scan_slides(client, image_paths):
                     temperature=0.1
                 )
             )
-            inventory.append(json.loads(response.text))
+            data = json.loads(response.text)
+            
+            # Robustness: Handle case where model returns a list [ { ... } ] instead of { ... }
+            if isinstance(data, list):
+                if len(data) > 0 and isinstance(data[0], dict):
+                    data = data[0]
+                else:
+                    print(f"Warning: Slide {slide_num} returned a list without a dict. Skipping.")
+                    data = None
+
+            if isinstance(data, dict):
+                inventory.append(data)
+            else:
+                 print(f"Warning: Slide {slide_num} did not return a valid JSON dictionary. Data: {data}")
+
         except Exception as e:
             print(f"Error scanning slide {slide_num}: {e}")
             
@@ -95,79 +109,97 @@ def scan_slides(client, image_paths):
 # LOGIC: PASS 2 (COACH CRITIQUE)
 # -----------------------------------------------------------------------------
 def generate_critique(client, inventory):
-    # Filter Appendix
-    def get_title(slide):
-        t = slide.get("title")
-        return t if t else ""
+    try:
+        # Filter Appendix (Robustly)
+        def get_title(slide):
+            if not isinstance(slide, dict): return ""
+            t = slide.get("title")
+            return t if t else ""
+            
+        # Ensure 's' is a dict before accessing
+        active = [s for s in inventory if isinstance(s, dict) and "appendix" not in get_title(s).lower()]
         
-    active = [s for s in inventory if "appendix" not in get_title(s).lower()]
-    
-    # Script
-    script = []
-    for s in active:
-        visuals = s.get("visual_elements", {})
-        busy = "BUSY" if visuals.get("is_busy") else "OK"
-        entry = f"Slide {s['slide_number']}: {s.get('title')}\n- Content: {s.get('key_takeaway')}\n- Visuals: {busy}"
-        script.append(entry)
+        # Script
+        script = []
+        for s in active:
+            visuals = s.get("visual_elements", {})
+            if not isinstance(visuals, dict): visuals = {} # Safety
+            
+            busy = "BUSY" if visuals.get("is_busy") else "OK"
+            title = s.get('title', 'No Title')
+            num = s.get('slide_number', '?')
+            takeaway = s.get('key_takeaway', '')
+            
+            entry = f"Slide {num}: {title}\n- Content: {takeaway}\n- Visuals: {busy}"
+            script.append(entry)
+            
+        full_text = "\n".join(script)
+        
+        # THE MENTOR PROMPT (Synced with run_pass_2_gemini.py)
+        prompt = f"""
+        You are Dr. Jones, an expert Data Science Mentor. 
+        Your goal is to guide a student to professional excellence.
+        
+        SLIDE INVENTORY:
+        {full_text}
+        
+        TASK:
+        Coach this student based on the 8-Step Story Arc.
+        
+        REQUIRED STORY ARC:
+        1. Executive Summary
+        2. Data Description
+        3. Targets & Metrics
+        4. Model Candidates
+        5. HPO Strategy
+        6. Best Model Selection
+        7. Validation
+        8. Business Impact
+        
+        INSTRUCTIONS:
+        1. **Fill the Roadmap**: For each of the 8 steps above, determine status (✅, ⚠️, ❓, ⭕).
+        2. **Slide Refs**: Cite specific slide numbers in the notes.
+        3. **Tone**: Encouraging.
+        4. **Summary**: Write a robust 2-paragraph summary (approx 150 words) explaining the overall impression and main areas for improvement.
+        
+        OUTPUT JSON SCHEMA:
+        {{
+            "overall_summary": "Encouraging feedback (2 paragraphs).",
+            "structure_roadmap": [
+                {{ 
+                    "step_name": "String (e.g. '1. Exec Summary')", 
+                    "status_icon": "String (✅, ⚠️, ❓, ⭕)", 
+                    "coach_notes": "String"
+                }}
+            ]
+        }}
+        """
         
-    full_text = "\n".join(script)
-    
-    # THE MENTOR PROMPT (Synced with run_pass_2_gemini.py)
-    prompt = f"""
-    You are Dr. Jones, an expert Data Science Mentor. 
-    Your goal is to guide a student to professional excellence.
-    
-    SLIDE INVENTORY:
-    {full_text}
-    
-    TASK:
-    Coach this student based on the 8-Step Story Arc.
-    
-    REQUIRED STORY ARC:
-    1. Executive Summary
-    2. Data Description
-    3. Targets & Metrics
-    4. Model Candidates
-    5. HPO Strategy
-    6. Best Model Selection
-    7. Validation
-    8. Business Impact
-    
-    INSTRUCTIONS:
-    1. **Fill the Roadmap**: For each of the 8 steps above, determine status (✅, ⚠️, ❓, ⭕).
-    2. **Slide Refs**: Cite specific slide numbers in the notes.
-    3. **Tone**: Encouraging.
-    4. **Summary**: Write a robust 2-paragraph summary (approx 150 words) explaining the overall impression and main areas for improvement.
-    
-    OUTPUT JSON SCHEMA:
-    {{
-        "overall_summary": "Encouraging feedback (2 paragraphs).",
-        "structure_roadmap": [
-            {{ 
-                "step_name": "String (e.g. '1. Exec Summary')", 
-                "status_icon": "String (✅, ⚠️, ❓, ⭕)", 
-                "coach_notes": "String"
-            }}
-        ]
-    }}
-    """
-    
-    try:
         response = client.models.generate_content(
             model=MODEL_NAME,
             contents=prompt,
             config=types.GenerateContentConfig(response_mime_type="application/json")
         )
         print("DEBUG: Received Pass 2 Response from Gemini.")
-        # print(response.text) # Uncomment to see raw JSON if needed
-        return json.loads(response.text)
+        
+        critique = json.loads(response.text)
+        
+        # Robustness: Handle list return from Coach
+        if isinstance(critique, list):
+            if len(critique) > 0 and isinstance(critique[0], dict):
+                critique = critique[0]
+            else:
+                 # If it's a list but not a list of dicts, or empty, fail gracefully
+                 raise ValueError(f"Coach returned a list, expected a dictionary. Output: {critique}")
+                 
+        return critique
         
     except Exception as e:
         print(f"CRITICAL ERROR in Pass 2: {e}")
         # Return a fallback critique so the UI doesn't hang
         return {
             "overall_summary": f"Error generating critique: {e}",
-            "roadmap": [],
+            "structure_roadmap": [],
             "slide_tips": []
         }