diff --git a/modelscope/pipelines/builder.py b/modelscope/pipelines/builder.py
index 18d934da..b45cd663 100644
--- a/modelscope/pipelines/builder.py
+++ b/modelscope/pipelines/builder.py
@@ -7,7 +7,7 @@ from modelscope.hub.snapshot_download import snapshot_download
 from modelscope.metainfo import DEFAULT_MODEL_FOR_PIPELINE
 from modelscope.models.base import Model
 from modelscope.utils.config import ConfigDict, check_config
-from modelscope.utils.constant import (DEFAULT_MODEL_REVISION, Invoke,
+from modelscope.utils.constant import (DEFAULT_MODEL_REVISION, Invoke, Tasks,
                                        ThirdParty)
 from modelscope.utils.hub import read_config
 from modelscope.utils.plugins import (register_modelhub_repo,
@@ -108,11 +108,21 @@ def pipeline(task: str = None,
     """
     if task is None and pipeline_name is None:
         raise ValueError('task or pipeline_name is required')
-
+    prefer_llm_pipeline = kwargs.get('llm_first')
+    if task is not None and task.lower() in [
+            Tasks.text_generation, Tasks.text2text_generation, Tasks.chat
+    ]:
+        # if not specified, prefer llm pipeline for aforementioned tasks
+        if prefer_llm_pipeline is None:
+            prefer_llm_pipeline = True
+    # for llm pipeline, if llm_framework is not specified, default to swift instead
+    # TODO: port the swift infer based on transformer into ModelScope
+    if prefer_llm_pipeline and kwargs.get('llm_framework') is None:
+        kwargs['llm_framework'] = 'swift'
     third_party = kwargs.get(ThirdParty.KEY)
     if third_party is not None:
         kwargs.pop(ThirdParty.KEY)
-    if pipeline_name is None and kwargs.get('llm_first'):
+    if pipeline_name is None and prefer_llm_pipeline:
         pipeline_name = llm_first_checker(model, model_revision, kwargs)
     else:
         model = normalize_model_input(
@@ -135,7 +145,7 @@ def pipeline(task: str = None,
                 register_modelhub_repo(model, cfg.get('allow_remote', False))
                 pipeline_name = llm_first_checker(
                     model, model_revision,
-                    kwargs) if kwargs.get('llm_first') else None
+                    kwargs) if prefer_llm_pipeline else None
                 if pipeline_name is not None:
                     pipeline_props = {'type': pipeline_name}
                 else:
diff --git a/modelscope/pipelines/nlp/llm_pipeline.py b/modelscope/pipelines/nlp/llm_pipeline.py
index cb801bd4..1bc36cc7 100644
--- a/modelscope/pipelines/nlp/llm_pipeline.py
+++ b/modelscope/pipelines/nlp/llm_pipeline.py
@@ -90,7 +90,7 @@ class LLMPipeline(Pipeline, PipelineStreamingOutputMixin):
         if self._is_swift_model(model):
             if self.llm_framework is not None:
                 logger.warning(
-                    f'Cannot using swift with llm_framework, ignoring {self.llm_framework}.'
+                    f'Cannot swift with llm_framework, ignoring {self.llm_framework}.'
                 )
 
             base_model = self.cfg.safe_get('adapter_cfg.model_id_or_path')
@@ -223,9 +223,13 @@ class LLMPipeline(Pipeline, PipelineStreamingOutputMixin):
                 for k, v in MODEL_MAPPING.items()
             }
 
-        def format_messages(messages: Dict[str, List[Dict[str, str]]],
+        def format_messages(messages: Union[List, Dict[str, List[Dict[str,
+                                                                      str]]]],
                             tokenizer: PreTrainedTokenizer,
                             **kwargs) -> Dict[str, torch.Tensor]:
+            # for compatibility, also support input list, but we shall wrap it into Dict
+            if isinstance(messages, list):
+                messages = {'messages': messages}
             inputs, _ = self.template.encode(get_example(messages))
             inputs.pop('labels', None)
             if 'input_ids' in inputs:
@@ -256,7 +260,8 @@ class LLMPipeline(Pipeline, PipelineStreamingOutputMixin):
             history = list(zip(contents[::2], contents[1::2]))
             return dict(system=system, prompt=prompt, history=history)
 
-        assert model_id in SWIFT_MODEL_ID_MAPPING, 'Swift framework does not support current model!'
+        assert model_id in SWIFT_MODEL_ID_MAPPING,\
+            f'Invalid model id {model_id} or Swift framework does not this model.'
         args = InferArguments(model_type=SWIFT_MODEL_ID_MAPPING[model_id])
         model, template = prepare_model_template(
             args, device_map=self.device_map)