fix: large document handling and Cassandra query pagination (#969)

- Paginate heavy Cassandra reads (triples, graph/document embeddings)
  using synchronous session.execute() in run_in_executor with fetch_size
  paging, preventing materialization hang on large result sets
- Fix document stream endpoint to use workspace-scoped librarian queues
- Add decoder error handling for PDF/OCR/unstructured processors
- Add WebSocket mux guards for missing auth fields
- Add null check in librarian document streaming
- Rewrite get_document_content CLI to stream via librarian
- Add Poppler dependency to unstructured container

trustgraph-unstructured/trustgraph/decoding/universal/processor.py

@@ -418,7 +418,14 @@ class Processor(FlowProcessor):
         doc_uri_str = document_uri(source_doc_id)
 
         # Extract elements using unstructured
-        elements = self.extract_elements(blob, mime_type)
+        try:
+            elements = self.extract_elements(blob, mime_type)
+        except Exception as e:
+            logger.error(
+                f"Failed to extract elements from {source_doc_id}: "
+                f"{type(e).__name__}: {e}"
+            )
+            return
 
         if not elements:
             logger.warning("No elements extracted from document")