docs: sync docs with current code after refactor

- architecture: remove TaskManager.max_prompt_len (merged into max_seq_len in 53c804e)
- dataflow: fix DatasetFactory.load param name max_position_embeddings -> max_len
- params: add fsdp2 to parallel_mode, add --max_seq_len to server, add 4 missing generate options
- preprocessing: add missing batch_size config field

assets/docs/dataflow.md

@@ -83,9 +83,11 @@ All backends normalise tensors into `Store._data[Dict[str, List[Tensor]]]` + `St
 ## Dataset Architecture
 
 ```
-DatasetFactory.load(train_type, load_path, window_size, stride=None,
-                    storage_type=None, tokenizer_path=None,
-                    max_position_embeddings=2048, store=None)
+DatasetFactory.load(
+    train_type, load_path=None, window_size=0, stride=None,
+    storage_type=None, tokenizer_path=None,
+    max_len=2048, store=None
+)
   → BaseDataset.load(load_path, storage_type=None)
     → detect_format(load_path)
     → StoreFactory.create(storage_type)