Update app.py

app.py

@@ -169,7 +169,7 @@ class ExtendedQuantumDocumentManager(QuantumDocumentManager):
                     emb = clip_model.get_image_features(**inputs)
                 embeddings.append(emb.numpy())
                 valid_images.append(img_path)
-            except FileNotFoundError as fe:
+            except FileNotFoundError:
                 logger.warning(f"Image file not found: {img_path}. Skipping this file.")
             except Exception as e:
                 logger.exception(f"Error processing image {img_path}: {str(e)}")
@@ -430,7 +430,7 @@ class MultiModalRetriever:
     def _retrieve_images(self, query: str) -> List[str]:
         inputs = self.clip_processor(text=query, return_tensors="pt")
         with torch.no_grad():
-            text_emb = self.clip_model.get_text_features(**inputs)
+            _ = self.clip_model.get_text_features(**inputs)
         return ["image_result_1.png", "image_result_2.png"]
     
     def _retrieve_code(self, query: str) -> List[str]:
@@ -628,6 +628,33 @@ class ResearchWorkflow:
             "context": {"error": True},
             "metadata": {"status": "error"}
         }
+    
+    def enhance_analysis(self, state: AgentState) -> Dict:
+        """
+        Augments the analysis with multi-modal insights.
+        If images or code snippets are available in the context, they are appended to the analysis.
+        """
+        try:
+            analysis = state["messages"][-1].content
+            enhanced = f"{analysis}\n\n## Multi-Modal Insights\n"
+            # Append image captions if available
+            if "images" in state["context"]:
+                enhanced += "### Visual Evidence\n"
+                for img in state["context"]["images"]:
+                    enhanced += f"![Relevant visual]({img})\n"
+            # Append code snippets if available
+            if "code" in state["context"]:
+                enhanced += "### Code Artifacts\n```python\n"
+                for code in state["context"]["code"]:
+                    enhanced += f"{code}\n"
+                enhanced += "```"
+            return {
+                "messages": [AIMessage(content=enhanced)],
+                "context": state["context"]
+            }
+        except Exception as e:
+            logger.exception("Error during multi-modal enhancement.")
+            return self._error_state(f"Enhancement Error: {str(e)}")
 
 # ------------------------------
 # Enhanced Research Interface