diff --git a/speechserving/speechserving/conf/tts/tts_pd.yaml b/speechserving/speechserving/conf/tts/tts_pd.yaml
index 7a1ca5dc..e34cb5ab 100644
--- a/speechserving/speechserving/conf/tts/tts_pd.yaml
+++ b/speechserving/speechserving/conf/tts/tts_pd.yaml
@@ -12,17 +12,18 @@ port: 8692
 # am choices=['speedyspeech_csmsc', 'fastspeech2_csmsc']
 ##################################################################
 am: 'fastspeech2_csmsc'   
-am_model: 
-am_params:  
-phones_dict: './dict_dir/phone_id_map.txt'
+am_model: # the pdmodel file of am static model
+am_params: # the pdiparams file of am static model
+sample_rate: 24000
+phones_dict: 
 tones_dict: 
 speaker_dict: 
 spk_id: 0
 
 am_predictor_conf:
-  use_gpu: 'true'
-  enable_mkldnn: 'true'
-  switch_ir_optim: 'true'
+  use_gpu: True
+  enable_mkldnn: True
+  switch_ir_optim: True
 
 
 ##################################################################
@@ -30,16 +31,16 @@ am_predictor_conf:
 # voc choices=['pwgan_csmsc', 'mb_melgan_csmsc','hifigan_csmsc']
 ##################################################################
 voc: 'pwgan_csmsc'
-voc_model: 
-voc_params: 
+voc_model: # the pdmodel file of vocoder static model
+voc_params: # the pdiparams file of vocoder static model 
 
 voc_predictor_conf:
-  use_gpu: 'true'
-  enable_mkldnn: 'true'
-  switch_ir_optim: 'true'  
+  use_gpu: True
+  enable_mkldnn: True  
+  switch_ir_optim: True  
 
 ##################################################################
 #                            OTHERS                              #
 ##################################################################
 lang: 'zh'
-device: paddle.get_device()
\ No newline at end of file
+device: paddle.get_device()
diff --git a/speechserving/speechserving/engine/tts/paddleinference/tts_engine.py b/speechserving/speechserving/engine/tts/paddleinference/tts_engine.py
index b394ceaa..40bbcbf4 100644
--- a/speechserving/speechserving/engine/tts/paddleinference/tts_engine.py
+++ b/speechserving/speechserving/engine/tts/paddleinference/tts_engine.py
@@ -36,8 +36,6 @@ from utils.errors import ErrorCode
 from utils.exception import ServerBaseException
 from utils.paddle_predictor import init_predictor
 from utils.paddle_predictor import run_model
-#from paddle.inference import Config
-#from paddle.inference import create_predictor
 
 __all__ = ['TTSEngine']
 
@@ -48,7 +46,7 @@ pretrained_models = {
         'url':
         'https://paddlespeech.bj.bcebos.com/Parakeet/released_models/speedyspeech/speedyspeech_nosil_baker_static_0.5.zip',
         'md5':
-        '9a849a74d1be0c758dd5a1b9c8f77f3d',
+        'f10cbdedf47dc7a9668d2264494e1823',
         'model':
         'speedyspeech_csmsc.pdmodel',
         'params':
@@ -57,19 +55,23 @@ pretrained_models = {
         'phone_id_map.txt',
         'tones_dict':
         'tone_id_map.txt',
+        'sample_rate':
+        24000,
     },
     # fastspeech2
     "fastspeech2_csmsc-zh": {
         'url':
         'https://paddlespeech.bj.bcebos.com/Parakeet/released_models/fastspeech2/fastspeech2_nosil_baker_static_0.4.zip',
         'md5':
-        '8eb01c2e4bc7e8b59beaa9fa046069cf',
+        '9788cd9745e14c7a5d12d32670b2a5a7',
         'model':
         'fastspeech2_csmsc.pdmodel',
         'params':
         'fastspeech2_csmsc.pdiparams',
         'phones_dict':
         'phone_id_map.txt',
+        'sample_rate':
+        24000,
     },
     # pwgan
     "pwgan_csmsc-zh": {
@@ -139,6 +141,7 @@ class TTSServerExecutor(TTSExecutor):
             am: str='fastspeech2_csmsc',
             am_model: Optional[os.PathLike]=None,
             am_params: Optional[os.PathLike]=None,
+            sample_rate: int=24000,
             phones_dict: Optional[os.PathLike]=None,
             tones_dict: Optional[os.PathLike]=None,
             speaker_dict: Optional[os.PathLike]=None,
@@ -156,11 +159,7 @@ class TTSServerExecutor(TTSExecutor):
             return
         # am
         am_tag = am + '-' + lang
-        if phones_dict is None:
-            print("please input phones_dict!")
-            ### 后续下载的模型里加上 phone 和 tone的 dict 就不用这个了
-        #if am_model is None or am_params is None or phones_dict is None:
-        if am_model is None or am_params is None:
+        if am_model is None or am_params is None or phones_dict is None:
             am_res_path = self._get_pretrained_path(am_tag)
             self.am_res_path = am_res_path
             self.am_model = os.path.join(am_res_path,
@@ -168,10 +167,10 @@ class TTSServerExecutor(TTSExecutor):
             self.am_params = os.path.join(am_res_path,
                                           pretrained_models[am_tag]['params'])
             # must have phones_dict in acoustic
-            #self.phones_dict = os.path.join(
-            #am_res_path, pretrained_models[am_tag]['phones_dict'])
+            self.phones_dict = os.path.join(
+                am_res_path, pretrained_models[am_tag]['phones_dict'])
+            self.sample_rate = pretrained_models[am_tag]['sample_rate']
 
-            self.phones_dict = os.path.abspath(phones_dict)
             logger.info(am_res_path)
             logger.info(self.am_model)
             logger.info(self.am_params)
@@ -179,6 +178,7 @@ class TTSServerExecutor(TTSExecutor):
             self.am_model = os.path.abspath(am_model)
             self.am_params = os.path.abspath(am_params)
             self.phones_dict = os.path.abspath(phones_dict)
+            self.sample_rate = sample_rate
             self.am_res_path = os.path.dirname(os.path.abspath(self.am_model))
         print("self.phones_dict:", self.phones_dict)
 
@@ -343,6 +343,7 @@ class TTSEngine(BaseEngine):
             am=self.conf_dict["am"],
             am_model=self.conf_dict["am_model"],
             am_params=self.conf_dict["am_params"],
+            sample_rate=self.conf_dict["sample_rate"],
             phones_dict=self.conf_dict["phones_dict"],
             tones_dict=self.conf_dict["tones_dict"],
             speaker_dict=self.conf_dict["speaker_dict"],
@@ -450,8 +451,7 @@ class TTSEngine(BaseEngine):
         try:
             target_sample_rate, wav_base64 = self.postprocess(
                 wav=self.executor._outputs['wav'].numpy(),
-                #original_fs=self.executor.am_config.fs,
-                original_fs=24000,  # TODO get sample rate from model
+                original_fs=self.executor.sample_rate,
                 target_fs=sample_rate,
                 volume=volume,
                 speed=speed,
diff --git a/speechserving/speechserving/utils/paddle_predictor.py b/speechserving/speechserving/utils/paddle_predictor.py
index 608b2b4c..f910161b 100644
--- a/speechserving/speechserving/utils/paddle_predictor.py
+++ b/speechserving/speechserving/utils/paddle_predictor.py
@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import os
+from typing import List
 from typing import Optional
 
 from paddle.inference import Config
@@ -31,21 +32,20 @@ def init_predictor(model_dir: Optional[os.PathLike]=None,
         predictor_conf (dict, optional): The configuration parameters of predictor. Defaults to None.
 
     Returns:
-        [type]: [description]
+        predictor (PaddleInferPredictor): created predictor
     """
+
     if model_dir is not None:
         config = Config(args.model_dir)
     else:
         config = Config(model_file, params_file)
 
     config.enable_memory_optim()
-    if "use_gpu" in predictor_conf and predictor_conf["use_gpu"] == "true":
+    if predictor_conf["use_gpu"]:
         config.enable_use_gpu(1000, 0)
-    if "enable_mkldnn" in predictor_conf and predictor_conf[
-            "enable_mkldnn"] == "true":
+    if predictor_conf["enable_mkldnn"]:
         config.enable_mkldnn()
-    if "switch_ir_optim" in predictor_conf and predictor_conf[
-            "switch_ir_optim"] == "true":
+    if predictor_conf["switch_ir_optim"]:
         config.switch_ir_optim()
 
     predictor = create_predictor(config)
@@ -53,7 +53,7 @@ def init_predictor(model_dir: Optional[os.PathLike]=None,
     return predictor
 
 
-def run_model(predictor, input: list):
+def run_model(predictor, input: List) -> List:
     """ run predictor
 
     Args: