Update params

Signed-off-by: shiyu22 <shiyu.chen@zilliz.com>

README.md

@@ -49,7 +49,7 @@ collection.create_index(field_name="embedding", index_params=index_params)
 from towhee import AutoPipes, AutoConfig
 
 config = AutoConfig.load_config('eqa-insert')
-config.model = 'all-MiniLM-L6-v2'
+config.embedding_model = 'all-MiniLM-L6-v2'
 config.host = '127.0.0.1'
 config.port = '19530'
 config.collection_name = collection_name
@@ -84,16 +84,16 @@ The kwargs for the splitter, defaults to {}.
 
 #### **Configuration for Sentence Embedding:**
 
-***model***: str
-The model name in the sentence embedding pipeline, defaults to `'all-MiniLM-L6-v2'`.
+***embedding_model***: str
+The model name for sentence embedding, defaults to `'all-MiniLM-L6-v2'`.
 You can refer to the above [Model(s) list ](https://towhee.io/tasks/detail/operator?field_name=Natural-Language-Processing&task_name=Sentence-Embedding)to set the model, some of these models are from [HuggingFace](https://huggingface.co/) (open source), and some are from [OpenAI](https://openai.com/) (not open, required API key).
 
 ***openai_api_key***: str
 The api key of openai, default to `None`.
 This key is required if  the model is from OpenAI, you can check the model provider in the above [Model(s) list](https://towhee.io/sentence-embedding/openai).
 
-***device:*** int
-The number of devices, defaults to `-1`, which means using the CPU. 
+***embedding_device:*** int
+The number of device, defaults to `-1`, which means using the CPU. 
 If the setting is not `-1`, the specified GPU device will be used.
 
 #### **Configuration for [Milvus](https://towhee.io/ann-insert/milvus-client):**

eqa_insert.py

@@ -28,9 +28,9 @@ class EnhancedQAInsertConfig(BaseModel):
     chunk_size: Optional[int] = 300
     splitter_kwargs: Optional[Dict[str, Any]] = {}
     # config for sentence_embedding
-    model: Optional[str] = 'all-MiniLM-L6-v2'
+    embedding_model: Optional[str] = 'all-MiniLM-L6-v2'
     openai_api_key: Optional[str] = None
-    device: Optional[int] = -1
+    embedding_device: Optional[int] = -1
     # config for insert_milvus
     host: Optional[str] = '127.0.0.1'
     port: Optional[str] = '19530'
@@ -47,18 +47,18 @@ _openai_models = ['text-embedding-ada-002', 'text-similarity-davinci-001',
 
 
 def _get_embedding_op(config):
-    if config.device == -1:
+    if config.embedding_device == -1:
         device = 'cpu'
     else:
-        device = config.device
+        device = config.embedding_device
 
-    if config.model in _hf_models:
-        return True, ops.sentence_embedding.transformers(model_name=config.model, device=device)
-    if config.model in _sbert_models:
-        return True, ops.sentence_embedding.sbert(model_name=config.model, device=device)
-    if config.model in _openai_models:
-        return False, ops.sentence_embedding.openai(model_name=config.model, api_key=config.openai_api_key)
-    raise RuntimeError('Unknown model: [%s], only support: %s' % (config.model, _hf_models + _sbert_models + _openai_models))
+    if config.embedding_model in _hf_models:
+        return True, ops.sentence_embedding.transformers(model_name=config.embedding_model, device=device)
+    if config.embedding_model in _sbert_models:
+        return True, ops.sentence_embedding.sbert(model_name=config.embedding_model, device=device)
+    if config.embedding_model in _openai_models:
+        return False, ops.sentence_embedding.openai(model_name=config.embedding_model, api_key=config.openai_api_key)
+    raise RuntimeError('Unknown model: [%s], only support: %s' % (config.embedding_model, _hf_models + _sbert_models + _openai_models))
 
 
 
@@ -72,8 +72,8 @@ def enhanced_qa_insert_pipe(config):
     allow_triton, sentence_embedding_op = _get_embedding_op(config)
     sentence_embedding_config = {}
     if allow_triton:
-        if config.device >= 0:
-            sentence_embedding_config = AutoConfig.TritonGPUConfig(device_ids=[config.device], max_batch_size=128)
+        if config.embedding_device >= 0:
+            sentence_embedding_config = AutoConfig.TritonGPUConfig(device_ids=[config.embedding_device], max_batch_size=128)
         else:
             sentence_embedding_config = AutoConfig.TritonCPUConfig()