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nbs/02_learning_interface.ipynb

@@ -539,12 +539,11 @@
     "        specialty: str,\n",
     "        setting: str,\n",
     "        state: Dict[str, Any]\n",
-    "    ) -> List:\n",
+    "    ) -> Tuple[List, List, List, str]:  # Explicitly return all outputs\n",
     "        \"\"\"Update rotation context with session tracking.\"\"\"\n",
     "        if specialty and setting:\n",
     "            self.tutor.learning_context.update_rotation(specialty, setting)\n",
     "            \n",
-    "            # Start new session\n",
     "            if self.auth.start_session(specialty, setting):\n",
     "                self.auth.log_interaction(\n",
     "                    \"context_update\",\n",
@@ -555,15 +554,17 @@
     "                goals = await self.tutor.generate_smart_goals(specialty, setting)\n",
     "                state[\"suggested_goals\"] = goals\n",
     "                \n",
-    "                # Log goal generation\n",
     "                if self.auth.token:\n",
     "                    self.auth.log_interaction(\n",
     "                        \"goals_generated\",\n",
     "                        f\"Generated {len(goals)} goals\"\n",
     "                    )\n",
     "            \n",
-    "            return self._update_displays(state)\n",
-    "        return [[], [], [], \"No active learning goal\"]\n",
+    "            update_results = self._update_displays(state)\n",
+    "            return tuple(update_results)  # Return as tuple to match output structure\n",
+    "            \n",
+    "        empty_results = [[], [], [], \"No active learning goal\"]\n",
+    "        return tuple(empty_results)  # Return as tuple here too\n",
     "\n",
     "    # Chat Processing\n",
     "    async def process_chat(\n",
@@ -863,10 +864,11 @@
     "                        with gr.Row():\n",
     "                            # Left: Chat Interface\n",
     "                            with gr.Column(scale=3):\n",
-    "                                # Active goal display with improved styling\n",
+    "                                # Update the Markdown component to handle string input\n",
     "                                goal_display = gr.Markdown(\n",
     "                                    value=\"No active learning goal\",\n",
-    "                                    elem_classes=[\"active-goal\"]\n",
+    "                                    elem_classes=[\"active-goal\"],\n",
+    "                                    sanitize=False  # Allow raw HTML if needed\n",
     "                                )\n",
     "                                \n",
     "                                # Chat interface with proper sizing\n",
@@ -960,6 +962,13 @@
     "                                label=\"Identified Knowledge Gaps\",\n",
     "                                row_count=8\n",
     "                            )\n",
+    "                            gr.Markdown(\"### Recent Goals\")\n",
+    "                            recent_goals = gr.DataFrame(\n",
+    "                                headers=[\"Goal\", \"Category\", \"Completed\"],\n",
+    "                                value=[],\n",
+    "                                label=\"Recently Completed Goals\",\n",
+    "                                row_count=5\n",
+    "                            )\n",
     "            \n",
     "            # Helper Functions\n",
     "            def clear_discussion() -> Tuple[List, str, Dict]:\n",
@@ -1005,15 +1014,25 @@
     "            specialty.change(\n",
     "                fn=self.update_context,\n",
     "                inputs=[specialty, setting, state],\n",
-    "                outputs=[goals_list, goal_display]\n",
+    "                outputs=[\n",
+    "                    goals_list,         # DataFrame\n",
+    "                    progress_display,   # DataFrame\n",
+    "                    recent_goals,       # DataFrame\n",
+    "                    goal_display       # Markdown\n",
+    "                ]\n",
     "            )\n",
     "            \n",
     "            setting.change(\n",
     "                fn=self.update_context,\n",
     "                inputs=[specialty, setting, state],\n",
-    "                outputs=[goals_list, goal_display]\n",
+    "                outputs=[\n",
+    "                    goals_list,         # DataFrame\n",
+    "                    progress_display,   # DataFrame\n",
+    "                    recent_goals,       # DataFrame\n",
+    "                    goal_display       # Markdown\n",
+    "                ]\n",
     "            )\n",
-    "            \n",
+    "                        \n",
     "            # Chat events with streaming\n",
     "            msg.submit(\n",
     "                self.process_chat,\n",

wardbuddy/learning_interface.py

@@ -440,12 +440,11 @@ class LearningInterface:
         specialty: str,
         setting: str,
         state: Dict[str, Any]
-    ) -> List:
+    ) -> Tuple[List, List, List, str]:  # Explicitly return all outputs
         """Update rotation context with session tracking."""
         if specialty and setting:
             self.tutor.learning_context.update_rotation(specialty, setting)
             
-            # Start new session
             if self.auth.start_session(specialty, setting):
                 self.auth.log_interaction(
                     "context_update",
@@ -456,15 +455,17 @@ class LearningInterface:
                 goals = await self.tutor.generate_smart_goals(specialty, setting)
                 state["suggested_goals"] = goals
                 
-                # Log goal generation
                 if self.auth.token:
                     self.auth.log_interaction(
                         "goals_generated",
                         f"Generated {len(goals)} goals"
                     )
             
-            return self._update_displays(state)
-        return [[], [], [], "No active learning goal"]
+            update_results = self._update_displays(state)
+            return tuple(update_results)  # Return as tuple to match output structure
+            
+        empty_results = [[], [], [], "No active learning goal"]
+        return tuple(empty_results)  # Return as tuple here too
 
     # Chat Processing
     async def process_chat(
@@ -764,10 +765,11 @@ class LearningInterface:
                         with gr.Row():
                             # Left: Chat Interface
                             with gr.Column(scale=3):
-                                # Active goal display with improved styling
+                                # Update the Markdown component to handle string input
                                 goal_display = gr.Markdown(
                                     value="No active learning goal",
-                                    elem_classes=["active-goal"]
+                                    elem_classes=["active-goal"],
+                                    sanitize=False  # Allow raw HTML if needed
                                 )
                                 
                                 # Chat interface with proper sizing
@@ -861,6 +863,13 @@ class LearningInterface:
                                 label="Identified Knowledge Gaps",
                                 row_count=8
                             )
+                            gr.Markdown("### Recent Goals")
+                            recent_goals = gr.DataFrame(
+                                headers=["Goal", "Category", "Completed"],
+                                value=[],
+                                label="Recently Completed Goals",
+                                row_count=5
+                            )
             
             # Helper Functions
             def clear_discussion() -> Tuple[List, str, Dict]:
@@ -906,15 +915,25 @@ class LearningInterface:
             specialty.change(
                 fn=self.update_context,
                 inputs=[specialty, setting, state],
-                outputs=[goals_list, goal_display]
+                outputs=[
+                    goals_list,         # DataFrame
+                    progress_display,   # DataFrame
+                    recent_goals,       # DataFrame
+                    goal_display       # Markdown
+                ]
             )
             
             setting.change(
                 fn=self.update_context,
                 inputs=[specialty, setting, state],
-                outputs=[goals_list, goal_display]
+                outputs=[
+                    goals_list,         # DataFrame
+                    progress_display,   # DataFrame
+                    recent_goals,       # DataFrame
+                    goal_display       # Markdown
+                ]
             )
-            
+                        
             # Chat events with streaming
             msg.submit(
                 self.process_chat,