baidubce · MrChengmo · Mar 12, 2024 · Mar 11, 2024 · Mar 11, 2024 · Mar 11, 2024
diff --git a/README.md b/README.md
@@ -71,7 +71,7 @@ print(", ".join(models))
 
 填写自己的Token，获取模型列表输出如下：
 ``` shell
-ERNIE-Bot 4.0, ERNIE-Bot-8K, ERNIE-Bot, ERNIE-Bot-turbo, EB-turbo-AppBuilder专用版, Qianfan-Chinese-Llama-2-7B, Yi-34B-Chat, Llama-2-7B-Chat, Llama-2-13B-Chat, Llama-2-70B-Chat, ChatGLM2-6B-32K, ChatLaw, BLOOMZ-7B, Qianfan-BLOOMZ-7B-compressed, AquilaChat-7B
+ERNIE-Bot 4.0, ERNIE-Bot-8K, ERNIE-Bot, ERNIE-Bot-turbo, ERNIE Speed-AppBuilder, Qianfan-Chinese-Llama-2-7B, Yi-34B-Chat, Llama-2-7B-Chat, Llama-2-13B-Chat, Llama-2-70B-Chat, ChatGLM2-6B-32K, ChatLaw, BLOOMZ-7B, Qianfan-BLOOMZ-7B-compressed, AquilaChat-7B
 ```
 
 为方便用户更容易使用模型，以下是一些模型的短名称
@@ -81,7 +81,7 @@ ERNIE-Bot 4.0, ERNIE-Bot-8K, ERNIE-Bot, ERNIE-Bot-turbo, EB-turbo-AppBuilder专
 | ERNIE-Bot-8K               |       eb-8k      |
 | ERNIE-Bot                  |       eb         |
 | ERNIE-Bot-turbo            |       eb-turbo   |
-| EB-turbo-AppBuilder专用版   |       eb-turbo-appbuilder           |
+| ERNIE Speed-AppBuilder   |       ernie_speed_appbuilder           |
 
 
 ### 典型示例
@@ -94,7 +94,7 @@ import appbuilder
 
 # 空模版组件
 template_str = "你扮演{role}, 请回答我的问题。\n\n问题：{question}。\n\n回答："
-playground = appbuilder.Playground(prompt_template=template_str, model="eb-turbo-appbuilder")
+playground = appbuilder.Playground(prompt_template=template_str, model="ERNIE Speed-AppBuilder")
 
 # 定义输入，调用空模版组件
 input = appbuilder.Message({"role": "java工程师", "question": "java语言的内存回收机制是什么"})
@@ -107,7 +107,7 @@ print(playground(input, stream=False, temperature=1e-10))
 import appbuilder
 
 # 相似问生成组件
-similar_q = appbuilder.SimilarQuestion(model="eb-turbo-appbuilder")
+similar_q = appbuilder.SimilarQuestion(model="ERNIE Speed-AppBuilder")
 
 # 定义输入，调用相似问生成
 input = appbuilder.Message("我想吃冰淇淋，哪里的冰淇淋比较好吃？")
@@ -149,7 +149,7 @@ import appbuilder
 # 空模版组件
 playground = appbuilder.Playground(
     prompt_template="{query}",
-    model="eb-turbo-appbuilder"
+    model="ERNIE Speed-AppBuilder"
 )
 
 # 使用 AgentRuntime 来服务化playground组件
@@ -196,7 +196,7 @@ class SimilarQuestion(CompletionBaseComponent):
 
             os.environ["APPBUILDER_TOKEN"] = "..."
 
-            qa_mining = appbuilder.SimilarQuestion(model="eb-turbo-appbuilder")
+            qa_mining = appbuilder.SimilarQuestion(model="ERNIE Speed-AppBuilder")
 
             msg = "我想吃冰淇淋，哪里的冰淇淋比较好吃？"
             msg = appbuilder.Message(msg)

diff --git a/appbuilder/core/agent.py b/appbuilder/core/agent.py
@@ -104,7 +104,7 @@ class AgentRuntime(BaseModel):
             class PlaygroundWithHistory(Component):
                 def __init__(self):
                     super().__init__()
-                    self.query_rewrite = QueryRewrite(model="eb-turbo-appbuilder")
+                    self.query_rewrite = QueryRewrite(model="ERNIE Speed-AppBuilder")
                     self.play = Playground(
                         prompt_template="{query}",
                         model="eb-4"

diff --git a/appbuilder/core/components/gbi/basic.py b/appbuilder/core/components/gbi/basic.py
@@ -50,5 +50,5 @@ class ColumnItem(BaseModel):
 
 
 SUPPORTED_MODEL_NAME = {
-    "ERNIE-Bot 4.0", "ERNIE-Bot-8K", "ERNIE-Bot", "ERNIE-Bot-turbo", "EB-turbo-AppBuilder"
+    "ERNIE-Bot 4.0", "ERNIE-Bot-8K", "ERNIE-Bot", "ERNIE-Bot-turbo", "ERNIE Speed-AppBuilder"
 }
diff --git a/appbuilder/core/components/gbi/nl2sql/README.md b/appbuilder/core/components/gbi/nl2sql/README.md
@@ -59,7 +59,7 @@ print(f"llm result: {nl2sql_result_message.content.llm_result}")
 ## 参数说明
 
 ### 初始化参数
-- model_name:  支持的模型名字 ERNIE-Bot 4.0, ERNIE-Bot-8K, ERNIE-Bot, ERNIE-Bot-turbo, EB-turbo-AppBuilder"
+- model_name:  支持的模型名字 ERNIE-Bot 4.0, ERNIE-Bot-8K, ERNIE-Bot, ERNIE-Bot-turbo, ERNIE Speed-AppBuilder
 - table_schemas: 表的 schema，例如:
 
 ```

diff --git a/appbuilder/core/components/gbi/nl2sql/component.py b/appbuilder/core/components/gbi/nl2sql/component.py
@@ -45,7 +45,7 @@ def __init__(self, model_name: str, table_schemas: List[str], knowledge: Dict =
         """
         创建 gbi nl2sql 对象
         Args:
-            model_name:  支持的模型名字 ERNIE-Bot 4.0, ERNIE-Bot-8K, ERNIE-Bot, ERNIE-Bot-turbo, EB-turbo-AppBuilder
+            model_name:  支持的模型名字 ERNIE-Bot 4.0, ERNIE-Bot-8K, ERNIE-Bot, ERNIE-Bot-turbo, ERNIE Speed-AppBuilder
             table_schemas: 表的 schema 列表，例如: ```
                             CREATE TABLE `mytable` (
                             `d_year` COMMENT '年度,2019,2020..2022..',

diff --git a/appbuilder/core/components/gbi/select_table/README.md b/appbuilder/core/components/gbi/select_table/README.md
@@ -51,7 +51,7 @@ print(f"选的表是: {select_table_result_message.content}")
 
 ## 参数说明
 ### 初始化参数
-- model_name: 支持的模型名字 ERNIE-Bot 4.0, ERNIE-Bot-8K, ERNIE-Bot, ERNIE-Bot-turbo, EB-turbo-AppBuilder
+- model_name: 支持的模型名字 ERNIE-Bot 4.0, ERNIE-Bot-8K, ERNIE-Bot, ERNIE-Bot-turbo, ERNIE Speed-AppBuilder
 - table_descriptions: 表的描述是个字典，key: 是表的名字, value: 是表的描述，例如:
 
 ```

diff --git a/appbuilder/core/components/gbi/select_table/component.py b/appbuilder/core/components/gbi/select_table/component.py
@@ -41,7 +41,7 @@ def __init__(self, model_name: str, table_descriptions: Dict[str, str],
         """
         创建 GBI 选表对象
         Args:
-            model_name: 支持的模型名字 ERNIE-Bot 4.0, ERNIE-Bot-8K, ERNIE-Bot, ERNIE-Bot-turbo, EB-turbo-AppBuilder
+            model_name: 支持的模型名字 ERNIE-Bot 4.0, ERNIE-Bot-8K, ERNIE-Bot, ERNIE-Bot-turbo, ERNIE Speed-AppBuilder
             table_descriptions: 表的描述是个字典，key: 是表的名字, value: 是表的描述，例如:
                                 {
                                     "超市营收明细表": "超市营收明细表，包含超市各种信息等",

diff --git a/appbuilder/core/components/llms/dialog_summary/README.md b/appbuilder/core/components/llms/dialog_summary/README.md
@@ -23,7 +23,7 @@ import os
 # 请前往千帆AppBuilder官网创建密钥，流程详见：https://cloud.baidu.com/doc/AppBuilder/s/Olq6grrt6#1%E3%80%81%E5%88%9B%E5%BB%BA%E5%AF%86%E9%92%A5
 os.environ["APPBUILDER_TOKEN"] = "bce-YOURTOKEN"
 
-dialog_summary = appbuilder.DialogSummary("eb-turbo-appbuilder")
+dialog_summary = appbuilder.DialogSummary("ERNIE Speed-AppBuilder")
 text = "用户:喂我想查一下我的话费\n坐席:好的女士您话费余的话还有87.49元钱\n用户:好的知道了谢谢\n坐席:嗯不客气祝您生活愉快再见"
 answer = dialog_summary(appbuilder.Message(text))
 print(answer)

diff --git a/appbuilder/core/components/llms/dialog_summary/component.py b/appbuilder/core/components/llms/dialog_summary/component.py
@@ -44,7 +44,7 @@ class DialogSummary(CompletionBaseComponent):
             # 请前往千帆AppBuilder官网创建密钥，流程详见：https://cloud.baidu.com/doc/AppBuilder/s/Olq6grrt6#1%E3%80%81%E5%88%9B%E5%BB%BA%E5%AF%86%E9%92%A5
             os.environ["APPBUILDER_TOKEN"] = '...'
 
-            dialog_summary = appbuilder.DialogSummary("eb-turbo-appbuilder")
+            dialog_summary = appbuilder.DialogSummary("ERNIE Speed-AppBuilder")
             text = "用户:喂我想查一下我的话费\n坐席:好的女士您话费余的话还有87.49元钱\n用户:好的知道了谢谢\n坐席:嗯不客气祝您生活愉快再见"
             answer = dialog_summary(appbuilder.Message(text))
             print(answer)

diff --git a/appbuilder/core/components/llms/is_complex_query/README.md b/appbuilder/core/components/llms/is_complex_query/README.md
@@ -21,7 +21,7 @@ import appbuilder
 # 请前往千帆AppBuilder官网创建密钥，流程详见：https://cloud.baidu.com/doc/AppBuilder/s/Olq6grrt6#1%E3%80%81%E5%88%9B%E5%BB%BA%E5%AF%86%E9%92%A5
 os.environ["APPBUILDER_TOKEN"] = "..."
 
-is_complex_query = appbuilder.IsComplexQuery(model="eb-turbo-appbuilder")
+is_complex_query = appbuilder.IsComplexQuery(model="ERNIE Speed-AppBuilder")
 
 msg = "吸塑包装盒在工业化生产和物流运输中分别有什么重要性？"
 msg = appbuilder.Message(msg)
@@ -42,7 +42,7 @@ os.environ["APPBUILDER_TOKEN"] = "bce-YOURTOKEN"
 ### 初始化参数
 |参数名称 |参数类型 |是否必须 |描述 |示例值|
 |--------|--------|--------|----|------|
-|model |str  |是 |模型名称，用于指定要使用的千帆模型|eb-turbo-appbuilder|
+|model |str  |是 |模型名称，用于指定要使用的千帆模型|ERNIE Speed-AppBuilder|
 
 ### 调用参数
 |参数名称 |参数类型 |是否必须 |描述 |示例值|

diff --git a/appbuilder/core/components/llms/is_complex_query/component.py b/appbuilder/core/components/llms/is_complex_query/component.py
@@ -42,7 +42,7 @@ class IsComplexQuery(CompletionBaseComponent):
             # 请前往千帆AppBuilder官网创建密钥，流程详见：https://cloud.baidu.com/doc/AppBuilder/s/Olq6grrt6#1%E3%80%81%E5%88%9B%E5%BB%BA%E5%AF%86%E9%92%A5
             os.environ["APPBUILDER_TOKEN"] = "..."
 
-            is_complex_query = appbuilder.IsComplexQuery(model="eb-turbo-appbuilder")
+            is_complex_query = appbuilder.IsComplexQuery(model="ERNIE Speed-AppBuilder")
 
             msg = "吸塑包装盒在工业化生产和物流运输中分别有什么重要性？"
             msg = appbuilder.Message(msg)

diff --git a/appbuilder/core/components/llms/mrc/README.md b/appbuilder/core/components/llms/mrc/README.md
@@ -9,7 +9,7 @@ MRC（阅读理解问答模块）是一项先进的自然语言处理功能，
 ### 特色优势
 我们的MRC模块，基于百度自研的先进语言模型文新一言，提供了一系列强大的阅读理解问答功能。在保持文本理解和问题回答的高精度的同时，
 我们特别强调了答案的质量和交互体验。以下是我们MRC模块的几个主要功能特色：
- - 1.多版本模型支持：我们的MRC模块包括不同版本的文新一言大模型，Erniebot 4.0、EB-turbo-AppBuilder等，每个版本都针对特定的应用场景进行了优化。 用户可以根据自己的需求选择最适合的模型版本，以获得最佳的性能。
+ - 1.多版本模型支持：我们的MRC模块包括不同版本的文新一言大模型，Erniebot 4.0、ERNIE Speed-AppBuilder等，每个版本都针对特定的应用场景进行了优化。 用户可以根据自己的需求选择最适合的模型版本，以获得最佳的性能。
  - 2.答案格式的多样性：
    - 拒答功能：当问题超出模型知识范围或不具体时，模型可以选择不回答，避免提供误导性信息。
    - 澄清功能：对于模棱两可或含糊的问题，模型可以请求更多信息或对问题进行澄清，以确保答案的准确性。
@@ -41,7 +41,7 @@ import os
 os.environ["APPBUILDER_TOKEN"] = "..."
 
 # 创建MRC对象
-mrc_component = appbuilder.MRC(model="eb-turbo-appbuilder")
+mrc_component = appbuilder.MRC(model="ERNIE Speed-AppBuilder")
 
 # 初始化参数
 msg = "残疾人怎么办相关证件"
@@ -119,7 +119,7 @@ import os
 os.environ["APPBUILDER_TOKEN"] = '...'
 
 # 创建MRC对象
-mrc_component = appbuilder.MRC(model="eb-turbo-appbuilder")
+mrc_component = appbuilder.MRC(model="ERNIE Speed-AppBuilder")
 
 # 初始化参数
 msg = "残疾人怎么办相关证件"

diff --git a/appbuilder/core/components/llms/nl2pandas/README.md b/appbuilder/core/components/llms/nl2pandas/README.md
@@ -30,7 +30,7 @@ query = "海淀区有哪些学校"
 query = appbuilder.Message(query)
 
 #定义并运行Nl2pandas实例，得到结果
-nl2pandas = appbuilder.Nl2pandasComponent(model="eb-turbo-appbuilder")
+nl2pandas = appbuilder.Nl2pandasComponent(model="ERNIE Speed-AppBuilder")
 answer = nl2pandas(query, table_info = table_info)
 ```
 

diff --git a/appbuilder/core/components/llms/nl2pandas/component.py b/appbuilder/core/components/llms/nl2pandas/component.py
@@ -55,7 +55,7 @@ class Nl2pandasComponent(CompletionBaseComponent):
             query = "海淀区有哪些学校"
             query = appbuilder.Message(query)
 
-            nl2pandas = appbuilder.Nl2pandasComponent(model="eb-turbo-appbuilder")
+            nl2pandas = appbuilder.Nl2pandasComponent(model="ERNIE Speed-AppBuilder")
             answer = nl2pandas(query, table_info = table_info)
     """
     name = "nl2pandas"

diff --git a/appbuilder/core/components/llms/oral_query_generation/README.md b/appbuilder/core/components/llms/oral_query_generation/README.md
@@ -26,7 +26,7 @@ text = ('文档标题：在OPPO Reno5上使用视频超级防抖\n'
         '防抖 开启路径：打开「相机 > 视频 > 点击屏幕上方的“超级防抖”标识」 后置视频同时支持超级防抖和超级防抖Pro功能，开启超级'
         '防抖后手机屏幕将出现超级防抖Pro开关，点击即可开启或关闭。 除此之外，前置视频同样加持防抖算法，边走边拍也能稳定聚焦脸部'
         '，实时视频分享您的生活。')
-oral_query_generation = appbuilder.OralQueryGeneration(model='eb-turbo-appbuilder')
+oral_query_generation = appbuilder.OralQueryGeneration(model='ERNIE Speed-AppBuilder')
 result = oral_query_generation(appbuilder.Message(text))
 print(result)
 ```
@@ -43,7 +43,7 @@ os.environ["APPBUILDER_TOKEN"] = "bce-YOURTOKEN"
 
 | 参数名称 | 参数类型 | 是否必须 | 描述 | 示例值 |
 | ------- | ------- | -------- | -------- | -------- |
-| `model` | str | 否 | 模型名称，用于指定要使用的千帆模型。 | eb-turbo-appbuilder |
+| `model` | str | 否 | 模型名称，用于指定要使用的千帆模型。 | ERNIE Speed-AppBuilder |
 | `secret_key` | str | 否 | 用户鉴权token，默认从环境变量中获取: `os.getenv("APPBUILDER_TOKEN", "")` |  |
 | `gateway` | str | 否 | 后端网关服务地址，默认从环境变量中获取: `os.getenv("GATEWAY_URL", "")` |  |
 | `lazy_certification` | bool | 否 | 延迟认证，为True时在第一次运行时认证。默认为False。 | False |

diff --git a/appbuilder/core/components/llms/oral_query_generation/component.py b/appbuilder/core/components/llms/oral_query_generation/component.py
@@ -54,7 +54,7 @@ class OralQueryGeneration(CompletionBaseComponent):
                     '防抖 开启路径：打开「相机 > 视频 > 点击屏幕上方的“超级防抖”标识」 后置视频同时支持超级防抖和超级防抖Pro功能，开启超级'
                     '防抖后手机屏幕将出现超级防抖Pro开关，点击即可开启或关闭。 除此之外，前置视频同样加持防抖算法，边走边拍也能稳定聚焦脸部'
                     '，实时视频分享您的生活。')
-            oral_query_generation = appbuilder.OralQueryGeneration(model='eb-turbo-appbuilder')
+            oral_query_generation = appbuilder.OralQueryGeneration(model='ERNIE Speed-AppBuilder')
             answer = oral_query_generation(appbuilder.Message(text))
             print(answer.content)
     """

diff --git a/appbuilder/core/components/llms/playground/README.md b/appbuilder/core/components/llms/playground/README.md
@@ -26,7 +26,7 @@ os.environ["APPBUILDER_TOKEN"] = "..."
 
 play = appbuilder.Playground(
     prompt_template="你好，{name}，我是{bot_name}，{bot_name}是一个{bot_type}，我可以{bot_function}，你可以问我{bot_question}。",
-    model="eb-turbo-appbuilder"
+    model="ERNIE Speed-AppBuilder"
 )
 play(appbuilder.Message({"name": "小明", "bot_name": "小红", "bot_type": "聊天机器人", "bot_function": "聊天", "bot_question": "你好吗？"}), stream=False)
 ```

diff --git a/appbuilder/core/components/llms/playground/component.py b/appbuilder/core/components/llms/playground/component.py
@@ -41,7 +41,7 @@ class Playground(CompletionBaseComponent):
             import appbuilder
             os.environ["APPBUILDER_TOKEN"] = "..."
 
-            play = appbuilder.Playground(prompt_template="你好，{name}，我是{bot_name}，{bot_name}是一个{bot_type}，我可以{bot_function}，你可以问我{bot_question}。", model="eb-turbo-appbuilder")
+            play = appbuilder.Playground(prompt_template="你好，{name}，我是{bot_name}，{bot_name}是一个{bot_type}，我可以{bot_function}，你可以问我{bot_question}。", model="ERNIE Speed-AppBuilder")
             play(appbuilder.Message({"name": "小明", "bot_name": "小红", "bot_type": "聊天机器人", "bot_function": "聊天", "bot_question": "你好吗？"}), stream=False)
 
     """

diff --git a/appbuilder/core/components/llms/qa_pair_mining/README.md b/appbuilder/core/components/llms/qa_pair_mining/README.md
@@ -23,7 +23,7 @@ import appbuilder
 # 请前往千帆AppBuilder官网创建密钥，流程详见：https://cloud.baidu.com/doc/AppBuilder/s/Olq6grrt6#1%E3%80%81%E5%88%9B%E5%BB%BA%E5%AF%86%E9%92%A5
 os.environ["APPBUILDER_TOKEN"] = "..."
 
-qa_mining = appbuilder.QAPairMining(model="eb-turbo-appbuilder")
+qa_mining = appbuilder.QAPairMining(model="ERNIE Speed-AppBuilder")
 # 输入文本（对此文本挖掘问答对）
 msg = '2017年，工商银行根据外部宏观环境变化，及时调整业务策略，优化资产负债结构，' + \
     '保持存贷款业务协调发展，提升资产负债配置效率。' + \
@@ -110,7 +110,7 @@ split_result = splitter(parse_result)
 
 # 每个段落抽取问答对，并返回结果
 for doc_segment in split_result.content["paragraphs"]:
-    qa_mining = QAPairMining(model="eb-turbo-appbuilder")
+    qa_mining = QAPairMining(model="ERNIE Speed-AppBuilder")
     text = doc_segment.get("text", "")
     if text == "":
         logger.error("Text is null. break")

diff --git a/appbuilder/core/components/llms/qa_pair_mining/component.py b/appbuilder/core/components/llms/qa_pair_mining/component.py
@@ -41,7 +41,7 @@ class QAPairMining(CompletionBaseComponent):
 
             os.environ["APPBUILDER_TOKEN"] = "..."
 
-            qa_mining = appbuilder.QAPairMining(model="eb-turbo-appbuilder")
+            qa_mining = appbuilder.QAPairMining(model="ERNIE Speed-AppBuilder")
             # 输入文本（对此文本挖掘问答对）
             msg =  '2017年，工商银行根据外部宏观环境变化，及时调整业务策略，优化资产负债结构，' + \
                 '保持存贷款业务协调发展，提升资产负债配置效率。' + \

diff --git a/appbuilder/core/components/llms/query_decomposition/README.md b/appbuilder/core/components/llms/query_decomposition/README.md
@@ -21,7 +21,7 @@ import appbuilder
 # 请前往千帆AppBuilder官网创建密钥，流程详见：https://cloud.baidu.com/doc/AppBuilder/s/Olq6grrt6#1%E3%80%81%E5%88%9B%E5%BB%BA%E5%AF%86%E9%92%A5
 os.environ["APPBUILDER_TOKEN"] = "..."
 
-query_decomposition = appbuilder.QueryDecomposition(model="eb-turbo-appbuilder")
+query_decomposition = appbuilder.QueryDecomposition(model="ERNIE Speed-AppBuilder")
 
 msg = "吸塑包装盒在工业化生产和物流运输中分别有什么重要性？"
 msg = appbuilder.Message(msg)
@@ -42,7 +42,7 @@ os.environ["APPBUILDER_TOKEN"] = "bce-YOURTOKEN"
 ### 初始化参数
 |参数名称 |参数类型 |是否必须 |描述 |示例值|
 |--------|--------|--------|----|------|
-|model |str  |是 |模型名称，用于指定要使用的千帆模型|eb-turbo-appbuilder|
+|model |str  |是 |模型名称，用于指定要使用的千帆模型|ERNIE Speed-AppBuilder|
 
 ### 调用参数
 |参数名称 |参数类型 |是否必须 |描述 |示例值|

diff --git a/appbuilder/core/components/llms/query_decomposition/component.py b/appbuilder/core/components/llms/query_decomposition/component.py
@@ -42,7 +42,7 @@ class QueryDecomposition(CompletionBaseComponent):
             # 请前往千帆AppBuilder官网创建密钥，流程详见：https://cloud.baidu.com/doc/AppBuilder/s/Olq6grrt6#1%E3%80%81%E5%88%9B%E5%BB%BA%E5%AF%86%E9%92%A5
             os.environ["APPBUILDER_TOKEN"] = "..."
 
-            query_decomposition = appbuilder.QueryDecomposition(model="eb-turbo-appbuilder")
+            query_decomposition = appbuilder.QueryDecomposition(model="ERNIE Speed-AppBuilder")
 
             msg = "吸塑包装盒在工业化生产和物流运输中分别有什么重要性？"
             msg = appbuilder.Message(msg)

diff --git a/appbuilder/core/components/llms/query_rewrite/README.md b/appbuilder/core/components/llms/query_rewrite/README.md
@@ -24,7 +24,7 @@ import appbuilder
 os.environ["APPBUILDER_TOKEN"] = '...'
 
 # 初始化并使用 QueryRewrite 组件
-query_rewrite = appbuilder.QueryRewrite(model="eb-turbo-appbuilder")
+query_rewrite = appbuilder.QueryRewrite(model="ERNIE Speed-AppBuilder")
 answer = query_rewrite(appbuilder.Message(['我应该怎么办理护照？', '您可以查询官网或人工咨询', '我需要准备哪些材料？', '身份证、免冠照片一张以及填写完整的《中国公民因私出国（境）申请表》', '在哪里办']), rewrite_type="带机器人回复")
 print(answer)
 ```

diff --git a/appbuilder/core/components/llms/query_rewrite/component.py b/appbuilder/core/components/llms/query_rewrite/component.py
@@ -71,7 +71,7 @@ class QueryRewrite(CompletionBaseComponent):
             import appbuilder
             os.environ["APPBUILDER_TOKEN"] = '...'
 
-            query_rewrite = appbuilder.QueryRewrite(model="eb-turbo-appbuilder")
+            query_rewrite = appbuilder.QueryRewrite(model="ERNIE Speed-AppBuilder")
             answer = query_rewrite(appbuilder.Message(['我应该怎么办理护照？', 
                                                      '您可以查询官网或人工咨询', 
                                                      '我需要准备哪些材料？', 

diff --git a/appbuilder/core/components/llms/similar_question/README.md b/appbuilder/core/components/llms/similar_question/README.md
@@ -23,7 +23,7 @@ import appbuilder
 # 请前往千帆AppBuilder官网创建密钥，流程详见：https://cloud.baidu.com/doc/AppBuilder/s/Olq6grrt6#1%E3%80%81%E5%88%9B%E5%BB%BA%E5%AF%86%E9%92%A5
 os.environ["APPBUILDER_TOKEN"] = "..."
 
-similar_question = appbuilder.SimilarQuestion(model="eb-turbo-appbuilder")
+similar_question = appbuilder.SimilarQuestion(model="ERNIE Speed-AppBuilder")
 
 msg = "我想吃冰淇淋，哪里的冰淇淋比较好吃？"
 msg = appbuilder.Message(msg)

diff --git a/appbuilder/core/components/llms/similar_question/component.py b/appbuilder/core/components/llms/similar_question/component.py
@@ -40,7 +40,7 @@ class SimilarQuestion(CompletionBaseComponent):
 
             os.environ["APPBUILDER_TOKEN"] = "..."
 
-            qa_mining = appbuilder.SimilarQuestion(model="eb-turbo-appbuilder")
+            qa_mining = appbuilder.SimilarQuestion(model="ERNIE Speed-AppBuilder")
 
             msg = "我想吃冰淇淋，哪里的冰淇淋比较好吃？"
             msg = appbuilder.Message(msg)