make more clear

lightrag/lightrag.py

@@ -509,6 +509,26 @@ class LightRAG:
         await self.doc_status.upsert(new_docs)
         logger.info(f"Stored {len(new_docs)} new unique documents")
 
+    async def _get_pending_documents(self) -> list[str]:
+        """Fetch all pending and failed documents."""
+        to_process_doc_keys: list[str] = []
+        
+        # Fetch failed documents
+        failed_docs = await self.doc_status.get_by_status(status=DocStatus.FAILED)
+        if failed_docs:
+            to_process_doc_keys.extend([doc["id"] for doc in failed_docs])
+        
+        # Fetch pending documents
+        pending_docs = await self.doc_status.get_by_status(status=DocStatus.PENDING)
+        if pending_docs:
+            to_process_doc_keys.extend([doc["id"] for doc in pending_docs])
+        
+        if not to_process_doc_keys:
+            logger.info("All documents have been processed or are duplicates")
+            return []
+        
+        return to_process_doc_keys
+    
     async def apipeline_process_chunks(
         self,
         split_by_character: str | None = None,
@@ -527,52 +547,36 @@ class LightRAG:
                 when split_by_character is None, this parameter is ignored.
         """
         # 1. get all pending and failed documents
-        to_process_doc_keys: list[str] = []
+        pending_doc_ids = await self._get_pending_documents()
         
-        # Process failes
+        if not pending_doc_ids:
-        to_process_docs = await self.doc_status.get_by_status(status=DocStatus.FAILED)
-        if to_process_docs:
-            to_process_doc_keys.extend([doc["id"] for doc in to_process_docs])
-
-        # Process Pending
-        to_process_docs = await self.doc_status.get_by_status(status=DocStatus.PENDING)
-        if to_process_docs:
-            to_process_doc_keys.extend([doc["id"] for doc in to_process_docs])
-
-        if not to_process_doc_keys:
             logger.info("All documents have been processed or are duplicates")
             return
         
-        # If included in text_chunks is all processed, return
+        # Get allready processed documents (text chunks and full docs)
-        new_docs = await self.doc_status.get_by_ids(to_process_doc_keys)
+        text_chunks_processed_doc_ids = await self.text_chunks.filter_keys(pending_doc_ids)
-        text_chunks_new_docs_ids = await self.text_chunks.filter_keys(
+        full_docs_processed_doc_ids = await self.full_docs.filter_keys(pending_doc_ids)
-            to_process_doc_keys
-        )
-        full_docs_new_docs_ids = await self.full_docs.filter_keys(to_process_doc_keys)
-
-        if not new_docs:
-            logger.info("All documents have been processed or are duplicates")
-            return
 
         # 2. split docs into chunks, insert chunks, update doc status
         batch_size = self.addon_params.get("insert_batch_size", 10)
         batch_docs_list = [
-            new_docs[i : i + batch_size] for i in range(0, len(new_docs), batch_size)
+            pending_doc_ids[i : i + batch_size] for i in range(0, len(pending_doc_ids), batch_size)
         ]
-        for i, el in enumerate(batch_docs_list):
+        batch_len = len(batch_docs_list) + 1
-            items = ((k, v) for d in el for k, v in d.items())
+        # 3. iterate over batches
-
         tasks: dict[str, list[Coroutine[Any, Any, None]]] = {}
+        for batch_idx, doc_ids in enumerate(batch_docs_list):
         
             doc_status: dict[str, Any] = {
                 "status": DocStatus.PROCESSING,
                 "updated_at": datetime.now().isoformat(),
             }
 
-            for doc_id, doc in tqdm_async(
+            for doc_id in tqdm_async(
-                items,
+                doc_ids,
-                desc=f"Level 1 - Spliting doc in batch {i // len(batch_docs_list) + 1}",
+                desc=f"Level 1 - Batch {batch_idx} /  {batch_len}",
             ):
+                doc = await self.doc_status.get_by_id(doc_id)
                 doc_status.update(
                     {
                         "content_summary": doc["content_summary"],
@@ -580,7 +584,6 @@ class LightRAG:
                         "created_at": doc["created_at"],
                     }
                 )
-
                 await self.doc_status.upsert({doc_id: doc_status})
 
                 # Generate chunks from document
@@ -614,12 +617,12 @@ class LightRAG:
                     )
                     await self.doc_status.upsert({doc_id: doc_status})
 
-                if doc_id not in full_docs_new_docs_ids:
+                if doc_id not in full_docs_processed_doc_ids:
                     tasks[doc_id].append(
                         self.full_docs.upsert({doc_id: {"content": doc["content"]}})
                     )
 
-                if doc_id not in text_chunks_new_docs_ids:
+                if doc_id not in text_chunks_processed_doc_ids:
                     tasks[doc_id].append(self.text_chunks.upsert(chunks))
 
                 for doc_id, task in tasks.items():