Update vector_store.py

vector_store.py

@@ -113,30 +113,39 @@ class LegalDocumentVectorStore:
             print(f"❌ Error saving pre-computed embeddings: {e}")
             return False
     
-    def get_retriever(self, clause_tagger, document_id: str = None):
-        """Get retriever for chat functionality"""
-        try:
-            self._initialize_pinecone()
-            
-            legal_embeddings = InLegalBERTEmbeddings(clause_tagger.embedding_model)
-            index = self.pc.Index(self.index_name)
-            
-            vectorstore = PineconeVectorStore(
-                index=index,
-                embedding=legal_embeddings,
-                text_key="text"
-            )
-            
-            # Create retriever with optional document filtering
-            search_kwargs = {'k': 5}
-            if document_id:
-                search_kwargs['filter'] = {'document_id': document_id}
-            
-            return vectorstore.as_retriever(search_kwargs=search_kwargs)
-            
-        except Exception as e:
-            print(f"❌ Error creating retriever: {e}")
-            return None
+ def get_retriever(self, clause_tagger, document_id: str = None):
+    """Get retriever for chat functionality with improved settings"""
+    try:
+        self._initialize_pinecone()
+        
+        legal_embeddings = InLegalBERTEmbeddings(clause_tagger.embedding_model)
+        index = self.pc.Index(self.index_name)
+        
+        vectorstore = PineconeVectorStore(
+            index=index,
+            embedding=legal_embeddings,
+            text_key="text"
+        )
+        
+        # More permissive search settings
+        search_kwargs = {
+            'k': 10,  # Increased from default 5
+            'include_metadata': True
+        }
+        
+        if document_id:
+            search_kwargs['filter'] = {'document_id': document_id}
+        
+        # Use similarity search without threshold initially
+        return vectorstore.as_retriever(
+            search_type="similarity",  # Remove threshold for now
+            search_kwargs=search_kwargs
+        )
+        
+    except Exception as e:
+        print(f"❌ Error creating retriever: {e}")
+        return None
+
 
 # Global instance
 vector_store = LegalDocumentVectorStore()