diff --git a/README.md b/README.md index 2c51dcf69..c32e48c08 100644 --- a/README.md +++ b/README.md @@ -111,7 +111,7 @@ template_str = "你扮演{role}, 请回答我的问题。\n\n问题：{question} # 定义输入，调用playground组件 input = appbuilder.Message({"role": "java工程师", "question": "请简要回答java语言的内存回收机制是什么，要求100字以内"}) -playground = appbuilder.Playground(prompt_template=template_str, model="Qianfan-Appbuilder-Speed-8k") +playground = appbuilder.Playground(prompt_template=template_str, model="Qianfan-Agent-Speed-8k") # 以打字机的方式，流式展示大模型回答内容 output = playground(input, stream=True, temperature=1e-10) @@ -157,7 +157,7 @@ import os # 设置环境中的TOKEN，以下TOKEN为访问和QPS受限的试用TOKEN，正式使用请替换为您的个人TOKEN os.environ["APPBUILDER_TOKEN"] = "bce-v3/ALTAK-n5AYUIUJMarF7F7iFXVeK/1bf65eed7c8c7efef9b11388524fa1087f90ea58" -rag_with_baidu_search_pro = appbuilder.RagWithBaiduSearchPro(model="Qianfan-Appbuilder-Speed-8k") +rag_with_baidu_search_pro = appbuilder.RagWithBaiduSearchPro(model="Qianfan-Agent-Speed-8k") input = appbuilder.Message("9.11和9.8哪个大") result = rag_with_baidu_search_pro.run( diff --git a/appbuilder/core/agent.py b/appbuilder/core/agent.py index dd4a2d1d2..4c248d485 100644 --- a/appbuilder/core/agent.py +++ b/appbuilder/core/agent.py @@ -108,7 +108,7 @@ class AgentRuntime(BaseModel): class PlaygroundWithHistory(Component): def __init__(self): super().__init__() - self.query_rewrite = QueryRewrite(model="Qianfan-Appbuilder-Speed-8k") + self.query_rewrite = QueryRewrite(model="Qianfan-Agent-Speed-8k") self.play = Playground( prompt_template="{query}", model="eb-4" diff --git a/appbuilder/core/components/gbi/nl2sql/README.md b/appbuilder/core/components/gbi/nl2sql/README.md index 1ae778a87..050a9fca5 100644 --- 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, ERNIE-Bot-turbo, Qianfan-Appbuilder-Speed-8k +- model_name: 支持的模型名字 ERNIE-Bot 4.0, ERNIE-Bot, ERNIE-Bot-turbo, Qianfan-Agent-Speed-8k - 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 index 2b6f9b7fa..9d3d6c709 100644 --- a/appbuilder/core/components/gbi/nl2sql/component.py +++ b/appbuilder/core/components/gbi/nl2sql/component.py @@ -38,7 +38,7 @@ 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, ERNIE-Bot-turbo, Qianfan-Appbuilder-Speed-8k + model_name: 支持的模型名字 ERNIE-Bot 4.0, ERNIE-Bot, ERNIE-Bot-turbo, Qianfan-Agent-Speed-8k 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 index bc7ce9176..4d173b792 100644 --- 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, ERNIE-Bot-turbo, Qianfan-Appbuilder-Speed-8k +- model_name: 支持的模型名字 ERNIE-Bot 4.0, ERNIE-Bot, ERNIE-Bot-turbo, Qianfan-Agent-Speed-8k - 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 index f0d7511d8..ceb4cdca5 100644 --- a/appbuilder/core/components/gbi/select_table/component.py +++ b/appbuilder/core/components/gbi/select_table/component.py @@ -36,7 +36,7 @@ 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, ERNIE-Bot-turbo, Qianfan-Appbuilder-Speed-8k + model_name: 支持的模型名字 ERNIE-Bot 4.0, ERNIE-Bot, ERNIE-Bot-turbo, Qianfan-Agent-Speed-8k 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 index 05a9eb786..2ef9b0665 100644 --- 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("Qianfan-Appbuilder-Speed-8k") +dialog_summary = appbuilder.DialogSummary("Qianfan-Agent-Speed-8k") 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 index 9da11d2d9..6b5b62d8c 100644 --- a/appbuilder/core/components/llms/dialog_summary/component.py +++ b/appbuilder/core/components/llms/dialog_summary/component.py @@ -32,7 +32,7 @@ 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("Qianfan-Appbuilder-Speed-8k") + dialog_summary = appbuilder.DialogSummary("Qianfan-Agent-Speed-8k") 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/hallucination_detection/README.md b/appbuilder/core/components/llms/hallucination_detection/README.md index 66bf8b206..528cb6812 100644 --- a/appbuilder/core/components/llms/hallucination_detection/README.md +++ b/appbuilder/core/components/llms/hallucination_detection/README.md @@ -37,8 +37,8 @@ context = \ 很多怕胖的女生看到猪皮就怕怕，但其实猪皮含有大量胶原蛋白，营养价值很高呢！这里红通通的猪皮还经过韩国秘制酱汁处理过，会有一点点辣味。烤猪皮的时候也需特别注意火侯，这样吃起来才会有外脆内Q的口感！''' answer = '澳门新麻蒲烤肉店并不是每天开门。' -#! 该组件推荐使用Qianfan-Appbuilder-Speed-8k模型。 -hallucination_detection = appbuilder.HallucinationDetection('Qianfan-Appbuilder-Speed-8k') +#! 该组件推荐使用Qianfan-Agent-Speed-8k模型。 +hallucination_detection = appbuilder.HallucinationDetection('Qianfan-Agent-Speed-8k') inputs = {'query': query, 'context': context, 'answer': answer} msg = appbuilder.Message(inputs) result = hallucination_detection.run(msg) @@ -58,7 +58,7 @@ 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。推荐使用Qianfan-Appbuilder-Speed-8k模型。 | Qianfan-Appbuilder-Speed-8k | +| `model` | str | 是 | 模型名称，用于指定要使用的千帆模型。推荐使用Qianfan-Agent-Speed-8k模型。 | Qianfan-Agent-Speed-8k | | `secret_key` | str | 否 | 用户鉴权token，默认从环境变量中获取: `os.getenv("APPBUILDER_TOKEN", "")` | bce-v3/XXX | | `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", "")` | https://appbuilder.baidu.com | | `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/hallucination_detection/component.py b/appbuilder/core/components/llms/hallucination_detection/component.py index 48fc83dfd..2757a61f6 100644 --- a/appbuilder/core/components/llms/hallucination_detection/component.py +++ b/appbuilder/core/components/llms/hallucination_detection/component.py @@ -26,7 +26,7 @@ class HallucinationDetection(CompletionBaseComponent): """ 幻觉检测。输入，判断answer中是否存在幻觉。 - *注：该组件推荐使用Qianfan-Appbuilder-Speed-8k模型。* + *注：该组件推荐使用Qianfan-Agent-Speed-8k模型。* Examples: @@ -103,7 +103,7 @@ def __init__( """初始化幻觉检测组件。 Args: - model (str|None): 模型名称，用于指定要使用的千帆模型。推荐使用Qianfan-Appbuilder-Speed-8k模型。 + model (str|None): 模型名称，用于指定要使用的千帆模型。推荐使用Qianfan-Agent-Speed-8k模型。 secret_key (str, 可选): 用户鉴权token, 默认从环境变量中获取: os.getenv("APPBUILDER_TOKEN", ""). gateway (str, 可选): 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, 可选): 延迟认证，为True时在第一次运行时认证. Defaults to False. diff --git a/appbuilder/core/components/llms/is_complex_query/README.md b/appbuilder/core/components/llms/is_complex_query/README.md index b5f70f0f7..a3bab9473 100644 --- 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="Qianfan-Appbuilder-Speed-8k") +is_complex_query = appbuilder.IsComplexQuery(model="Qianfan-Agent-Speed-8k") 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|Qianfan-Appbuilder-Speed-8k| +|model |str |是 |模型名称，用于指定要使用的千帆模型|Qianfan-Agent-Speed-8k| ### 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 index 662d4f01a..f0191b7d8 100644 --- a/appbuilder/core/components/llms/is_complex_query/component.py +++ b/appbuilder/core/components/llms/is_complex_query/component.py @@ -38,7 +38,7 @@ 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="Qianfan-Appbuilder-Speed-8k") + is_complex_query = appbuilder.IsComplexQuery(model="Qianfan-Agent-Speed-8k") 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 index ff1ad9fd0..eaf152beb 100644 --- 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、Qianfan-Appbuilder-Speed-8k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、Qianfan-Agent-Speed-8k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="Qianfan-Appbuilder-Speed-8k") +mrc_component = appbuilder.MRC(model="Qianfan-Agent-Speed-8k") # 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="Qianfan-Appbuilder-Speed-8k") +mrc_component = appbuilder.MRC(model="Qianfan-Agent-Speed-8k") # 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 index 81f1210c8..a6828200f 100644 --- 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="Qianfan-Appbuilder-Speed-8k") +nl2pandas = appbuilder.Nl2pandasComponent(model="Qianfan-Agent-Speed-8k") 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 index eb13e5bcf..95fae2134 100644 --- a/appbuilder/core/components/llms/nl2pandas/component.py +++ b/appbuilder/core/components/llms/nl2pandas/component.py @@ -38,7 +38,7 @@ class Nl2pandasComponent(CompletionBaseComponent): query = "海淀区有哪些学校" query = appbuilder.Message(query) - nl2pandas = appbuilder.Nl2pandasComponent(model="Qianfan-Appbuilder-Speed-8k") + nl2pandas = appbuilder.Nl2pandasComponent(model="Qianfan-Agent-Speed-8k") 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 index 4e700d3e8..4a796b11b 100644 --- a/appbuilder/core/components/llms/oral_query_generation/README.md +++ b/appbuilder/core/components/llms/oral_query_generation/README.md @@ -28,8 +28,8 @@ text = ('文档标题：在OPPO Reno5上使用视频超级防抖\n' '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。') -#! 该组件推荐使用Qianfan-Appbuilder-Speed-8k模型。 -oral_query_generation = appbuilder.OralQueryGeneration(model='Qianfan-Appbuilder-Speed-8k') +#! 该组件推荐使用Qianfan-Agent-Speed-8k模型。 +oral_query_generation = appbuilder.OralQueryGeneration(model='Qianfan-Agent-Speed-8k') result = oral_query_generation(appbuilder.Message(text), query_type='全部', output_format='str') print(result) @@ -47,7 +47,7 @@ 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 | 是 | 模型名称，用于指定要使用的千帆模型。推荐使用Qianfan-Appbuilder-Speed-8k模型。 | Qianfan-Appbuilder-Speed-8k | +| `model` | str | 是 | 模型名称，用于指定要使用的千帆模型。推荐使用Qianfan-Agent-Speed-8k模型。 | Qianfan-Agent-Speed-8k | | `secret_key` | str | 否 | 用户鉴权token，默认从环境变量中获取: `os.getenv("APPBUILDER_TOKEN", "")` | bce-v3/XXX | | `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", "")` | https://appbuilder.baidu.com | | `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 index 5f2a28aa2..bce15e8e5 100644 --- a/appbuilder/core/components/llms/oral_query_generation/component.py +++ b/appbuilder/core/components/llms/oral_query_generation/component.py @@ -27,7 +27,7 @@ class OralQueryGeneration(CompletionBaseComponent): r""" 口语化Query生成，可用于问答场景下对文档增强索引。 - *注：该组件推荐使用Qianfan-Appbuilder-Speed-8k模型。* + *注：该组件推荐使用Qianfan-Agent-Speed-8k模型。* Examples: @@ -43,7 +43,7 @@ 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='Qianfan-Appbuilder-Speed-8k') + oral_query_generation = appbuilder.OralQueryGeneration(model='Qianfan-Agent-Speed-8k') answer = oral_query_generation(appbuilder.Message(text), query_type='全部', output_format='str') print(answer.content) """ @@ -88,7 +88,7 @@ def __init__( """初始化口语化Query生成模型。 Args: - model (str|None): 模型名称，用于指定要使用的千帆模型。推荐使用Qianfan-Appbuilder-Speed-8k模型。 + model (str|None): 模型名称，用于指定要使用的千帆模型。推荐使用Qianfan-Agent-Speed-8k模型。 secret_key (str, 可选): 用户鉴权token, 默认从环境变量中获取: os.getenv("APPBUILDER_TOKEN", ""). gateway (str, 可选): 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, 可选): 延迟认证，为True时在第一次运行时认证. Defaults to False. diff --git a/appbuilder/core/components/llms/playground/README.md b/appbuilder/core/components/llms/playground/README.md index 38ac161c8..73c598591 100644 --- 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="Qianfan-Appbuilder-Speed-8k" + model="Qianfan-Agent-Speed-8k" ) 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 index 28020d2cf..be0344d72 100644 --- a/appbuilder/core/components/llms/playground/component.py +++ b/appbuilder/core/components/llms/playground/component.py @@ -31,7 +31,7 @@ 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="Qianfan-Appbuilder-Speed-8k") + 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="Qianfan-Agent-Speed-8k") 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 index 5dc650605..8fcfa6e5e 100644 --- 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="Qianfan-Appbuilder-Speed-8k") +qa_mining = appbuilder.QAPairMining(model="Qianfan-Agent-Speed-8k") # 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="Qianfan-Appbuilder-Speed-8k") + qa_mining = QAPairMining(model="Qianfan-Agent-Speed-8k") 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 index 495cae874..d8acb07c5 100644 --- a/appbuilder/core/components/llms/qa_pair_mining/component.py +++ b/appbuilder/core/components/llms/qa_pair_mining/component.py @@ -33,7 +33,7 @@ class QAPairMining(CompletionBaseComponent): os.environ["APPBUILDER_TOKEN"] = "..." - qa_mining = appbuilder.QAPairMining(model="Qianfan-Appbuilder-Speed-8k") + qa_mining = appbuilder.QAPairMining(model="Qianfan-Agent-Speed-8k") # 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 index bfd249c49..d1b7f06bc 100644 --- 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="Qianfan-Appbuilder-Speed-8k") +query_decomposition = appbuilder.QueryDecomposition(model="Qianfan-Agent-Speed-8k") 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|Qianfan-Appbuilder-Speed-8k| +|model |str |是 |模型名称，用于指定要使用的千帆模型|Qianfan-Agent-Speed-8k| ### 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 index 46f15196e..067215b2b 100644 --- a/appbuilder/core/components/llms/query_decomposition/component.py +++ b/appbuilder/core/components/llms/query_decomposition/component.py @@ -33,7 +33,7 @@ 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="Qianfan-Appbuilder-Speed-8k") + query_decomposition = appbuilder.QueryDecomposition(model="Qianfan-Agent-Speed-8k") 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 index 608e44514..ca568cf03 100644 --- 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="Qianfan-Appbuilder-Speed-8k") +query_rewrite = appbuilder.QueryRewrite(model="Qianfan-Agent-Speed-8k") 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 index 48e727936..964a269bb 100644 --- a/appbuilder/core/components/llms/query_rewrite/component.py +++ b/appbuilder/core/components/llms/query_rewrite/component.py @@ -31,7 +31,7 @@ class QueryRewrite(CompletionBaseComponent): import appbuilder os.environ["APPBUILDER_TOKEN"] = '...' - query_rewrite = appbuilder.QueryRewrite(model="Qianfan-Appbuilder-Speed-8k") + query_rewrite = appbuilder.QueryRewrite(model="Qianfan-Agent-Speed-8k") 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 index 4cd75df4d..ca5b11297 100644 --- 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="Qianfan-Appbuilder-Speed-8k") +similar_question = appbuilder.SimilarQuestion(model="Qianfan-Agent-Speed-8k") 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 index e95dbe3f0..39f79262f 100644 --- a/appbuilder/core/components/llms/similar_question/component.py +++ b/appbuilder/core/components/llms/similar_question/component.py @@ -35,7 +35,7 @@ class SimilarQuestion(CompletionBaseComponent): os.environ["APPBUILDER_TOKEN"] = "..." - qa_mining = appbuilder.SimilarQuestion(model="Qianfan-Appbuilder-Speed-8k") + qa_mining = appbuilder.SimilarQuestion(model="Qianfan-Agent-Speed-8k") 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/style_rewrite/README.md b/appbuilder/core/components/llms/style_rewrite/README.md index f79650110..f694e3762 100644 --- a/appbuilder/core/components/llms/style_rewrite/README.md +++ b/appbuilder/core/components/llms/style_rewrite/README.md @@ -33,7 +33,7 @@ import appbuilder os.environ["APPBUILDER_TOKEN"] = "..." # 初始化并使用 StyleRewrite 组件 -style_rewrite = appbuilder.StyleRewrite(model="Qianfan-Appbuilder-Speed-8k") +style_rewrite = appbuilder.StyleRewrite(model="Qianfan-Agent-Speed-8k") answer = style_rewrite(appbuilder.Message("文心大模型发布新版"), style="激励话术") ``` diff --git a/appbuilder/core/components/llms/style_rewrite/component.py b/appbuilder/core/components/llms/style_rewrite/component.py index c37dd6557..dd7bc60da 100644 --- a/appbuilder/core/components/llms/style_rewrite/component.py +++ b/appbuilder/core/components/llms/style_rewrite/component.py @@ -31,7 +31,7 @@ class StyleRewrite(CompletionBaseComponent): import appbuilder os.environ["APPBUILDER_TOKEN"] = '...' - style_rewrite = appbuilder.StyleRewrite(model="Qianfan-Appbuilder-Speed-8k") + style_rewrite = appbuilder.StyleRewrite(model="Qianfan-Agent-Speed-8k") answer = style_rewrite(appbuilder.Message("文心大模型发布新版本"), style="激励话术") """ diff --git a/appbuilder/core/components/llms/style_writing/README.md b/appbuilder/core/components/llms/style_writing/README.md index 40d8f140f..9ae429339 100644 --- a/appbuilder/core/components/llms/style_writing/README.md +++ b/appbuilder/core/components/llms/style_writing/README.md @@ -26,7 +26,7 @@ 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"] = "..." -model = "Qianfan-Appbuilder-Speed-8k" +model = "Qianfan-Agent-Speed-8k" style_writing = appbuilder.StyleWriting(model) query = "帮我写一篇关于人体工学椅的文案" diff --git a/appbuilder/core/components/llms/style_writing/component.py b/appbuilder/core/components/llms/style_writing/component.py index 7379899dd..499946172 100644 --- a/appbuilder/core/components/llms/style_writing/component.py +++ b/appbuilder/core/components/llms/style_writing/component.py @@ -55,7 +55,7 @@ class StyleWriting(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"] = '...' - style_writing = appbuilder.StyleWriting(model="Qianfan-Appbuilder-Speed-8k") + style_writing = appbuilder.StyleWriting(model="Qianfan-Agent-Speed-8k") answer = style_writing(appbuilder.Message("帮我写一篇关于人体工学椅的文案"), style_query="小红书", length=100) """ diff --git a/appbuilder/core/components/llms/tag_extraction/README.md b/appbuilder/core/components/llms/tag_extraction/README.md index e5ea6410a..313541a7f 100644 --- a/appbuilder/core/components/llms/tag_extraction/README.md +++ b/appbuilder/core/components/llms/tag_extraction/README.md @@ -31,7 +31,7 @@ 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"] = '...' -tag_extraction = appbuilder.TagExtraction(model="Qianfan-Appbuilder-Speed-8k") +tag_extraction = appbuilder.TagExtraction(model="Qianfan-Agent-Speed-8k") result = tag_extraction(appbuilder.Message("从这段文本中抽取关键标签")) ``` diff --git a/appbuilder/core/components/llms/tag_extraction/component.py b/appbuilder/core/components/llms/tag_extraction/component.py index fd6d5c56f..69b7eca57 100644 --- a/appbuilder/core/components/llms/tag_extraction/component.py +++ b/appbuilder/core/components/llms/tag_extraction/component.py @@ -29,7 +29,7 @@ class TagExtraction(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"] = '...' - tag_extraction = appbuilder.TagExtraction(model="Qianfan-Appbuilder-Speed-8k") + tag_extraction = appbuilder.TagExtraction(model="Qianfan-Agent-Speed-8k") answer = tag_extraction(appbuilder.Message("从这段文本中抽取关键标签")) """ diff --git a/appbuilder/core/components/rag_with_baidu_search/README.md b/appbuilder/core/components/rag_with_baidu_search/README.md index fc44a554b..8196d8886 100644 --- a/appbuilder/core/components/rag_with_baidu_search/README.md +++ b/appbuilder/core/components/rag_with_baidu_search/README.md @@ -38,7 +38,7 @@ import os os.environ["APPBUILDER_TOKEN"] = '...' # 创建rag_with_baidusearch对象 -rag_with_baidusearch_component = appbuilder.RAGWithBaiduSearch(model="Qianfan-Appbuilder-Speed-8k") +rag_with_baidusearch_component = appbuilder.RAGWithBaiduSearch(model="Qianfan-Agent-Speed-8k") # 运行rag_with_baidusearch基本组件 msg = appbuilder.Message("残疾人怎么办相关证件") @@ -111,7 +111,7 @@ os.environ["APPBUILDER_TOKEN"] = '...' # 创建rag_with_baidusearch对象, 并初始化人设指令 rag_with_baidusearch_component = appbuilder.RAGWithBaiduSearch( - model="Qianfan-Appbuilder-Speed-8k", + model="Qianfan-Agent-Speed-8k", instruction=appbuilder.Message("你是问答助手，在回答问题前需要加上: 很高兴为您解答")) diff --git a/appbuilder/core/components/rag_with_baidu_search_pro/README.md b/appbuilder/core/components/rag_with_baidu_search_pro/README.md index 58d74dd42..816a26c8b 100644 --- a/appbuilder/core/components/rag_with_baidu_search_pro/README.md +++ b/appbuilder/core/components/rag_with_baidu_search_pro/README.md @@ -26,7 +26,7 @@ import os os.environ["APPBUILDER_TOKEN"] = '...' # 创建rag_with_baidusearch_pro对象 -rag_with_baidu_search_pro = appbuilder.RagWithBaiduSearchPro(model="Qianfan-Appbuilder-Speed-8k") +rag_with_baidu_search_pro = appbuilder.RagWithBaiduSearchPro(model="Qianfan-Agent-Speed-8k") # 运行rag_with_baidusearch基本组件 msg = appbuilder.Message("残疾人怎么办相关证件") @@ -88,7 +88,7 @@ os.environ["APPBUILDER_TOKEN"] = '...' # 创建rag_with_baidusearch对象, 并初始化人设指令 rag_with_baidusearch_pro = appbuilder.RagWithBaiduSearchPro( - model="Qianfan-Appbuilder-Speed-8k", + model="Qianfan-Agent-Speed-8k", instruction=appbuilder.Message("你是问答助手，在回答问题前需要加上: 很高兴为您解答")) diff --git a/appbuilder/tests/test_appbuilder_components_trace.py b/appbuilder/tests/test_appbuilder_components_trace.py index 009a1eb8c..a33b4ef7a 100644 --- a/appbuilder/tests/test_appbuilder_components_trace.py +++ b/appbuilder/tests/test_appbuilder_components_trace.py @@ -55,7 +55,7 @@ def setUp(self): "%2Fa6c4d2ca8a3f0259f4cae8ae3fa98a9f75afde1a063eaec04847c99ab7d1e411" self.asr = appbuilder.ASR() self.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-4') - model_name = 'Qianfan-Appbuilder-Speed-8k' + model_name = 'Qianfan-Agent-Speed-8k' secret_key = os.getenv('SECRET_KEY', None) self.hallucination_detection = appbuilder.HallucinationDetection(model=model_name, secret_key=secret_key) diff --git a/appbuilder/tests/test_dialog_summary.py b/appbuilder/tests/test_dialog_summary.py index 40aa2cc98..2c5edfbf6 100644 --- a/appbuilder/tests/test_dialog_summary.py +++ b/appbuilder/tests/test_dialog_summary.py @@ -28,7 +28,7 @@ def setUp(self): Returns: 无返回值，方法中执行了环境变量的赋值操作。 """ - self.model_name = "Qianfan-Appbuilder-Speed-8k" + self.model_name = "Qianfan-Agent-Speed-8k" self.node = appbuilder.DialogSummary(model=self.model_name) def test_run_with_default_params(self): diff --git a/appbuilder/tests/test_hallucination_detection.py b/appbuilder/tests/test_hallucination_detection.py index 6a4e29565..a0a429f7e 100644 --- a/appbuilder/tests/test_hallucination_detection.py +++ b/appbuilder/tests/test_hallucination_detection.py @@ -51,7 +51,7 @@ def setUp(self): 无返回值，方法中执行了环境变量的赋值操作。 """ - self.model_name = 'Qianfan-Appbuilder-Speed-8k' + self.model_name = 'Qianfan-Agent-Speed-8k' secret_key = os.getenv('SECRET_KEY', None) self.hallucination_detection = appbuilder.HallucinationDetection(model=self.model_name, secret_key=secret_key) diff --git a/appbuilder/tests/test_is_complex_query.py b/appbuilder/tests/test_is_complex_query.py index 54c28f1ab..7ae9ee73f 100644 --- a/appbuilder/tests/test_is_complex_query.py +++ b/appbuilder/tests/test_is_complex_query.py @@ -29,7 +29,7 @@ def setUp(self): Returns: 无返回值，方法中执行了环境变量的赋值操作。 """ - self.model_name = "Qianfan-Appbuilder-Speed-8k" + self.model_name = "Qianfan-Agent-Speed-8k" self.node = appbuilder.IsComplexQuery(model=self.model_name) def test_run_with_default_params(self): diff --git a/appbuilder/tests/test_mrc.py b/appbuilder/tests/test_mrc.py index 2794d95f1..b156b642f 100644 --- a/appbuilder/tests/test_mrc.py +++ b/appbuilder/tests/test_mrc.py @@ -23,7 +23,7 @@ def setUp(self): return mrc class ''' # 设置环境变量和初始化TestMRCComponent实例 - self.model_name = "Qianfan-Appbuilder-Speed-8k" + self.model_name = "Qianfan-Agent-Speed-8k" self.mrc = appbuilder.MRC(model=self.model_name) def test_mrc_with_custom_context_list(self): diff --git a/appbuilder/tests/test_nl2pandas.py b/appbuilder/tests/test_nl2pandas.py index 2e4c293e2..814755c4a 100644 --- a/appbuilder/tests/test_nl2pandas.py +++ b/appbuilder/tests/test_nl2pandas.py @@ -25,7 +25,7 @@ def setUp(self): """ 设置环境变量及必要数据。 """ - self.model_name = "Qianfan-Appbuilder-Speed-8k" + self.model_name = "Qianfan-Agent-Speed-8k" self.node = appbuilder.Nl2pandasComponent(model=self.model_name) self.table_info = '''表格列信息如下： 学校名 : 清华附小 , 字符串类型，代表小学学校的名称 diff --git a/appbuilder/tests/test_oral_query_generation.py b/appbuilder/tests/test_oral_query_generation.py index 82deafe14..8d1ffefea 100644 --- a/appbuilder/tests/test_oral_query_generation.py +++ b/appbuilder/tests/test_oral_query_generation.py @@ -36,7 +36,7 @@ def setUp(self): 无返回值，方法中执行了环境变量的赋值操作。 """ - self.model_name = 'Qianfan-Appbuilder-Speed-8k' + self.model_name = 'Qianfan-Agent-Speed-8k' secret_key = os.getenv('SECRET_KEY', None) self.query_generation = appbuilder.OralQueryGeneration(model=self.model_name, secret_key=secret_key) diff --git a/appbuilder/tests/test_qa_pair_mining.py b/appbuilder/tests/test_qa_pair_mining.py index e3c54e926..1fb098cb8 100644 --- a/appbuilder/tests/test_qa_pair_mining.py +++ b/appbuilder/tests/test_qa_pair_mining.py @@ -31,7 +31,7 @@ def setUp(self): Returns: 无返回值，方法中执行了环境变量的赋值操作。 """ - self.model_name = "Qianfan-Appbuilder-Speed-8k" + self.model_name = "Qianfan-Agent-Speed-8k" self.node = appbuilder.QAPairMining(model=self.model_name) def test_run_with_default_params(self): diff --git a/appbuilder/tests/test_query_decomposition.py b/appbuilder/tests/test_query_decomposition.py index b83b41996..64c16f013 100644 --- a/appbuilder/tests/test_query_decomposition.py +++ b/appbuilder/tests/test_query_decomposition.py @@ -29,7 +29,7 @@ def setUp(self): Returns: 无返回值，方法中执行了环境变量的赋值操作。 """ - self.model_name = "Qianfan-Appbuilder-Speed-8k" + self.model_name = "Qianfan-Agent-Speed-8k" self.node = appbuilder.QueryDecomposition(model=self.model_name) def test_run_with_default_params(self): diff --git a/appbuilder/tests/test_query_rewrite.py b/appbuilder/tests/test_query_rewrite.py index c6e9165c9..a2fe94b32 100644 --- a/appbuilder/tests/test_query_rewrite.py +++ b/appbuilder/tests/test_query_rewrite.py @@ -32,7 +32,7 @@ def setUp(self): 无返回值。 """ # 设置环境变量和初始化TranslateComponent实例 - self.model_name = "Qianfan-Appbuilder-Speed-8k" + self.model_name = "Qianfan-Agent-Speed-8k" self.node = appbuilder.QueryRewrite(model=self.model_name) def test_run_with_default_params(self): @@ -54,7 +54,7 @@ def test_run_with_custom_params(self): def test_run_with_stream_and_temperature(self): """测试不同的 stream 和 temperature 参数值""" - node = appbuilder.QueryRewrite("Qianfan-Appbuilder-Speed-8k") + node = appbuilder.QueryRewrite("Qianfan-Agent-Speed-8k") query = ['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'] msg = appbuilder.Message(query) answer = node(msg, rewrite_type="带机器人回复", stream=False, temperature=0.5) diff --git a/appbuilder/tests/test_rag_baidu_search.py b/appbuilder/tests/test_rag_baidu_search.py index a8ffe00eb..144cacb0e 100644 --- a/appbuilder/tests/test_rag_baidu_search.py +++ b/appbuilder/tests/test_rag_baidu_search.py @@ -11,7 +11,7 @@ def setUp(self): return rag_with_baidu_search class """ # 设置环境变量和初始化TestMRCComponent实例 - self.model_name = "Qianfan-Appbuilder-Speed-8k" + self.model_name = "Qianfan-Agent-Speed-8k" self.rag_with_baidu_search = appbuilder.RAGWithBaiduSearch(model=self.model_name) def test_rag_with_baidu_search(self): diff --git a/appbuilder/tests/test_rag_baidu_search_pro.py b/appbuilder/tests/test_rag_baidu_search_pro.py index b5cea10c8..804736743 100644 --- a/appbuilder/tests/test_rag_baidu_search_pro.py +++ b/appbuilder/tests/test_rag_baidu_search_pro.py @@ -9,6 +9,8 @@ import unittest import appbuilder +from appbuilder.core._exception import AppBuilderServerException + @unittest.skipUnless(os.getenv("TEST_CASE", "UNKNOWN") == "CPU_PARALLEL", "") class TestRagBaiduSearch(unittest.TestCase): @@ -71,5 +73,25 @@ def test_rag_with_baidu_search_pro_stream(self): self.assertTrue(flag_content and flag_ref_content) + def test_rag_with_baidu_search_component_RAGWithBaiduSearch(self): + rwbs=appbuilder.RAGWithBaiduSearch(model='ERNIE-Bot 4.0') + + # test_get_search_input + text='text' + res_text=rwbs._get_search_input(text) + self.assertEqual(res_text, 'text') + text='UTF-8是一种变长字节表示的Unicode字符集编码方式，它可以使用1到4个字节来表示一个字符。' + res_text=rwbs._get_search_input(text) + self.assertEqual(res_text, 'UTF-8是一种变长字节表示的Unicode字符集编码方式，它可') + + # test run + message=appbuilder.Message() + message.content=""" + appbuilderappbuilderappbuilderappbuilderappbuilderappbuilderappbuilderappbuilder + appbuilderappbuilderappbuilderappbuilderappbuilderappbuilderappbuilderappbuilder + """ + with self.assertRaises(AppBuilderServerException): + rwbs.run(message=message) + if __name__ == '__main__': unittest.main() diff --git a/appbuilder/tests/test_rag_with_baidu_search_component.py b/appbuilder/tests/test_rag_with_baidu_search_component.py deleted file mode 100644 index d9bc7c17e..000000000 --- a/appbuilder/tests/test_rag_with_baidu_search_component.py +++ /dev/null @@ -1,48 +0,0 @@ -# Copyright (c) 2023 Baidu, Inc. All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import unittest -import os - -from appbuilder.core.components.rag_with_baidu_search.component import RAGWithBaiduSearch -from appbuilder.core.message import Message -from appbuilder.core._exception import * - -@unittest.skipUnless(os.getenv("TEST_CASE", "UNKNOWN") == "CPU_SERIAL", "") -class TestRagWithBaiduSearchComponent(unittest.TestCase): - def test_rag_with_baidu_search_component_RAGWithBaiduSearch(self): - rwbs=RAGWithBaiduSearch(model='ERNIE-Bot 4.0') - - # test_get_search_input - text='text' - res_text=rwbs._get_search_input(text) - self.assertEqual(res_text, 'text') - text='UTF-8是一种变长字节表示的Unicode字符集编码方式，它可以使用1到4个字节来表示一个字符。' - res_text=rwbs._get_search_input(text) - self.assertEqual(res_text, 'UTF-8是一种变长字节表示的Unicode字符集编码方式，它可') - - # test run - message=Message() - message.content='message' - res_response=rwbs.run(message=message) - assert message.content.startswith('message') - - message.content=""" - appbuilderappbuilderappbuilderappbuilderappbuilderappbuilderappbuilderappbuilder - appbuilderappbuilderappbuilderappbuilderappbuilderappbuilderappbuilderappbuilder - """ - with self.assertRaises(AppBuilderServerException): - rwbs.run(message=message) - -if __name__ == '__main__': - unittest.main() \ No newline at end of file diff --git a/appbuilder/tests/test_similar_question.py b/appbuilder/tests/test_similar_question.py index b47f877ec..c021f00ca 100644 --- a/appbuilder/tests/test_similar_question.py +++ b/appbuilder/tests/test_similar_question.py @@ -28,7 +28,7 @@ def setUp(self): Returns: 无返回值，方法中执行了环境变量的赋值操作。 """ - self.model_name = "Qianfan-Appbuilder-Speed-8k" + self.model_name = "Qianfan-Agent-Speed-8k" self.node = appbuilder.SimilarQuestion(model=self.model_name) def test_run_with_default_params(self): diff --git a/appbuilder/tests/test_style_rewrite.py b/appbuilder/tests/test_style_rewrite.py index 3087fe43c..33d1ad8a5 100644 --- a/appbuilder/tests/test_style_rewrite.py +++ b/appbuilder/tests/test_style_rewrite.py @@ -31,7 +31,7 @@ def setUp(self): Returns: 无返回值，方法中执行了环境变量的赋值操作。 """ - self.model_name = "Qianfan-Appbuilder-Speed-8k" + self.model_name = "Qianfan-Agent-Speed-8k" self.node = appbuilder.StyleRewrite(model=self.model_name) self.sc=StyleChoices.YINGXIAO diff --git a/appbuilder/tests/test_style_writing.py b/appbuilder/tests/test_style_writing.py index 836f15104..98e5b8417 100644 --- a/appbuilder/tests/test_style_writing.py +++ b/appbuilder/tests/test_style_writing.py @@ -32,7 +32,7 @@ def setUp(self): Returns: 无返回值，方法中执行了环境变量的赋值操作。 """ - self.model_name = "Qianfan-Appbuilder-Speed-8k" + self.model_name = "Qianfan-Agent-Speed-8k" self.node = appbuilder.StyleWriting(model=self.model_name) self.sqc=StyleQueryChoices.BILIBILI self.lc=LengthChoices.SHORT diff --git a/appbuilder/tests/test_tag_extraction.py b/appbuilder/tests/test_tag_extraction.py index 85fb24d41..0c6146d87 100644 --- a/appbuilder/tests/test_tag_extraction.py +++ b/appbuilder/tests/test_tag_extraction.py @@ -25,7 +25,7 @@ def setUp(self): Returns: 无返回值，方法中执行了环境变量的赋值操作。 """ - self.model_name = "Qianfan-Appbuilder-Speed-8k" + self.model_name = "Qianfan-Agent-Speed-8k" self.tag_extraction = appbuilder.TagExtraction(model=self.model_name) def test_run_with_default_params(self): diff --git a/appbuilder/utils/model_util.py b/appbuilder/utils/model_util.py index c77c27221..c2116e963 100644 --- a/appbuilder/utils/model_util.py +++ b/appbuilder/utils/model_util.py @@ -30,7 +30,7 @@ ("ERNIE-Bot-turbo", "eb-turbo"), ("EB-turbo-AppBuilder专用版", "eb-turbo-appbuilder"), ("EB-turbo-AppBuilder专用版", "ernie_speed_appbuilder"), - ("EB-turbo-AppBuilder专用版", "Qianfan-Appbuilder-Speed-8k"), + ("EB-turbo-AppBuilder专用版", "Qianfan-Agent-Speed-8k"), ] class RemoteModel(object): @@ -62,7 +62,7 @@ def get_remote_name_by_short_name(self, short_name: str) -> Optional[str]: """ # TODO(chengmo): 使用logging 替换 print，解决print多次的问题 if short_name == "eb-turbo-appbuilder": - print("Deprecate warning: model [eb-turbo-appbuilder] is deprecated, please use [Qianfan-Appbuilder-Speed-8k]") + print("Deprecate warning: model [eb-turbo-appbuilder] is deprecated, please use [Qianfan-Agent-Speed-8k]") if short_name in self.short_names: return self.remote_name diff --git a/cookbooks/components/agent_runtime.ipynb b/cookbooks/components/agent_runtime.ipynb index 6fb095f17..63ee56d78 100644 --- a/cookbooks/components/agent_runtime.ipynb +++ b/cookbooks/components/agent_runtime.ipynb @@ -426,7 +426,7 @@ "class PlaygroundWithHistory(Component):\n", " def __init__(self):\n", " super().__init__()\n", - " self.query_rewrite = QueryRewrite(model=\"Qianfan-Appbuilder-Speed-8k\")\n", + " self.query_rewrite = QueryRewrite(model=\"Qianfan-Agent-Speed-8k\")\n", " self.playground = Playground(\n", " prompt_template=\"{query}\",\n", " model=\"ERNIE-Bot\"\n", diff --git a/cookbooks/components/rag_with_baidusearch.ipynb b/cookbooks/components/rag_with_baidusearch.ipynb index 677ff07bf..477729bc1 100644 --- a/cookbooks/components/rag_with_baidusearch.ipynb +++ b/cookbooks/components/rag_with_baidusearch.ipynb @@ -82,8 +82,8 @@ "friendly = False # 友好度提升\n", "cite = True # 溯源\n", "\n", - "# 使用 Qianfan-Appbuilder-Speed-8kder 模型\n", - "component = appbuilder.RAGWithBaiduSearch(model=\"Qianfan-Appbuilder-Speed-8k\")\n", + "# 使用 Qianfan-Agent-Speed-8k 模型\n", + "component = appbuilder.RAGWithBaiduSearch(model=\"Qianfan-Agent-Speed-8k\")\n", "query = appbuilder.Message(\"海淀区的面积是多少\")\n", "\n", "answer = component.run(\n", diff --git a/cookbooks/components/text_generation.ipynb b/cookbooks/components/text_generation.ipynb index 65683fbc9..17b2319c5 100644 --- a/cookbooks/components/text_generation.ipynb +++ b/cookbooks/components/text_generation.ipynb @@ -101,7 +101,7 @@ "商品信息：\n", "'''\n", "# 创建商品信息生成组件\n", - "product_information_generation = Playground(prompt_template=prompt_template, model='Qianfan-Appbuilder-Speed-8k')\n", + "product_information_generation = Playground(prompt_template=prompt_template, model='Qianfan-Agent-Speed-8k')\n", "\n", "# 获取商品信息\n", "# 填充prompt_template参数的参数映射表，需要与prompt_template对应\n", @@ -152,7 +152,7 @@ "from appbuilder import QAPairMining\n", "\n", "# 初始化问答对生成组件\n", - "qa_pair_mining = QAPairMining(model='Qianfan-Appbuilder-Speed-8k')\n", + "qa_pair_mining = QAPairMining(model='Qianfan-Agent-Speed-8k')\n", "\n", "# 获取问答对\n", "response = qa_pair_mining(Message(product_information), stream=False, temperature=1e-10)\n", @@ -210,7 +210,7 @@ "'''\n", "\n", "# 初始化风格写作组件\n", - "style_writing = StyleWriting(model='Qianfan-Appbuilder-Speed-8k')\n", + "style_writing = StyleWriting(model='Qianfan-Agent-Speed-8k')\n", "\n", "# 获取小红书文案\n", "response = style_writing(Message(query), style_query='小红书', length=300)\n", @@ -260,7 +260,7 @@ "from appbuilder import TagExtraction\n", "\n", "# 初始化标签抽取组件\n", - "tag_extraction = TagExtraction(model='Qianfan-Appbuilder-Speed-8k')\n", + "tag_extraction = TagExtraction(model='Qianfan-Agent-Speed-8k')\n", "\n", "# 获取标签\n", "response = tag_extraction(Message(copywriting), stream=False, temperature=1e-10)\n", diff --git a/cookbooks/end2end_application/rag/rag.ipynb b/cookbooks/end2end_application/rag/rag.ipynb index 5a1d39c27..3eef0c479 100644 --- a/cookbooks/end2end_application/rag/rag.ipynb +++ b/cookbooks/end2end_application/rag/rag.ipynb @@ -171,7 +171,7 @@ "具备团队协作精神，能够与团队成员有效沟通，共同推进项目进展。'''\n", "\n", "# 标签抽取的组件\n", - "tagger = appbuilder.TagExtraction(model=\"Qianfan-Appbuilder-Speed-8k\")\n", + "tagger = appbuilder.TagExtraction(model=\"Qianfan-Agent-Speed-8k\")\n", "\n", "# 从JD抽取标签并打印\n", "tags = tagger(appbuilder.Message(job_desc))\n", @@ -234,7 +234,7 @@ "\n", "play = appbuilder.Playground(\n", " prompt_template=\"基于候选人姓名、职责描述和简历内容，概括一下{name}的推荐理由。\\n候选人姓名: {name}\\n职责描述: {JD}\\n简历内容: {resume}\\n推荐理由: \",\n", - " model=\"Qianfan-Appbuilder-Speed-8k\"\n", + " model=\"Qianfan-Agent-Speed-8k\"\n", ")\n", "\n", "resume_summary = play(appbuilder.Message({\"JD\": job_desc, \"name\": sorted_resumes[0][0], \"resume\": \"\\n\".join(list(resume_content[sorted_resumes[0][0]]))}))\n", diff --git a/docs/README_en.md b/docs/README_en.md index fc3b076e4..f423f800c 100644 --- a/docs/README_en.md +++ b/docs/README_en.md @@ -82,7 +82,7 @@ template_str = "你扮演{role}, 请回答我的问题。\n\n问题：{question} # 定义输入，调用playground组件 input = appbuilder.Message({"role": "java工程师", "question": "请简要回答java语言的内存回收机制是什么，要求100字以内"}) -playground = appbuilder.Playground(prompt_template=template_str, model="Qianfan-Appbuilder-Speed-8k") +playground = appbuilder.Playground(prompt_template=template_str, model="Qianfan-Agent-Speed-8k") # 以打字机的方式，流式展示大模型回答内容 output = playground(input, stream=True, temperature=1e-10) @@ -128,7 +128,7 @@ import os # 设置环境中的TOKEN，以下TOKEN为访问和QPS受限的试用TOKEN，正式使用请替换为您的个人TOKEN os.environ["APPBUILDER_TOKEN"] = "bce-v3/ALTAK-n5AYUIUJMarF7F7iFXVeK/1bf65eed7c8c7efef9b11388524fa1087f90ea58" -rag_with_baidu_search_pro = appbuilder.RagWithBaiduSearchPro(model="Qianfan-Appbuilder-Speed-8k") +rag_with_baidu_search_pro = appbuilder.RagWithBaiduSearchPro(model="Qianfan-Agent-Speed-8k") input = appbuilder.Message("9.11和9.8哪个大") result = rag_with_baidu_search_pro.run( diff --git a/docs/README_ja.md b/docs/README_ja.md index e8aa39aa4..23bc623a2 100644 --- a/docs/README_ja.md +++ b/docs/README_ja.md @@ -79,7 +79,7 @@ template_str = "あなたは{role}の役割を果たします。私の質問に # 入力を定義し、playgroundコンポーネントを呼び出します。 input = appbuilder.Message({"role": "Javaエンジニア", "question": "Java言語のメモリ回収メカニズムについて簡単に説明してください。100文字以内でお願いします。"}) -playground = appbuilder.Playground(prompt_template=template_str, model="Qianfan-Appbuilder-Speed-8k") +playground = appbuilder.Playground(prompt_template=template_str, model="Qianfan-Agent-Speed-8k") # タイプライターのように、ストリーム形式で大規模モデルの回答内容を表示します。 output = playground(input, stream=True, temperature=1e-10) @@ -124,7 +124,7 @@ import os # 環境変数にTOKENを設定します。以下のTOKENはアクセスとQPSが制限された試用TOKENです。正式な使用には個人のTOKENに置き換えてください。 os.environ["APPBUILDER_TOKEN"] = "bce-v3/ALTAK-n5AYUIUJMarF7F7iFXVeK/1bf65eed7c8c7efef9b11388524fa1087f90ea58" -rag_with_baidu_search_pro = appbuilder.RagWithBaiduSearchPro(model="Qianfan-Appbuilder-Speed-8k") +rag_with_baidu_search_pro = appbuilder.RagWithBaiduSearchPro(model="Qianfan-Agent-Speed-8k") input = appbuilder.Message("9.11と9.8のどちらが大きいですか？") result = rag_with_baidu_search_pro.run( diff --git a/docs/basic_module/README.md b/docs/basic_module/README.md index 0724d56f3..0c0cd811e 100644 --- a/docs/basic_module/README.md +++ b/docs/basic_module/README.md @@ -52,7 +52,7 @@ ERNIE-Bot 4.0, ERNIE-Bot, ERNIE-3.5-4K-0205, ERNIE-3.5-8K-0205, ERNIE-3.5-8K-122 | ERNIE-Bot | eb | | ERNIE-Bot-turbo | eb-turbo | | EB-turbo-AppBuilder专用版 | ernie_speed_appbuilder | -| Qianfan-Appbuilder-Speed-8k | ernie_speed_appbuilder | +| Qianfan-Agent-Speed-8k | ernie_speed_appbuilder | @@ -66,7 +66,7 @@ os.environ["APPBUILDER_TOKEN"] = "bce-v3/ALTAK-n5AYUIUJMarF7F7iFXVeK/1bf65eed7c8 # 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="Qianfan-Appbuilder-Speed-8k") +playground = appbuilder.Playground(prompt_template=template_str, model="Qianfan-Agent-Speed-8k") # 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"}) @@ -83,7 +83,7 @@ import os os.environ["APPBUILDER_TOKEN"] = "bce-v3/ALTAK-n5AYUIUJMarF7F7iFXVeK/1bf65eed7c8c7efef9b11388524fa1087f90ea58" # 相似问生成组件 -similar_q = appbuilder.SimilarQuestion(model="Qianfan-Appbuilder-Speed-8k") +similar_q = appbuilder.SimilarQuestion(model="Qianfan-Agent-Speed-8k") # 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？") @@ -128,7 +128,7 @@ import appbuilder # 空模版组件 playground = appbuilder.Playground( prompt_template="{query}", - model="Qianfan-Appbuilder-Speed-8k" + model="Qianfan-Agent-Speed-8k" ) # 使用 AgentRuntime 来服务化playground组件 diff --git a/docs/basic_module/agentruntime.md b/docs/basic_module/agentruntime.md index d4a4e080c..fc18c4de8 100644 --- a/docs/basic_module/agentruntime.md +++ b/docs/basic_module/agentruntime.md @@ -120,7 +120,7 @@ os.environ["APPBUILDER_TOKEN"] = 'YOUR_APPBUILDER_TOKEN' class PlaygroundWithHistory(Component): def __init__(self): super().__init__() - self.query_rewrite = QueryRewrite(model="Qianfan-Appbuilder-Speed-8k") + self.query_rewrite = QueryRewrite(model="Qianfan-Agent-Speed-8k") self.play = Playground( prompt_template="{query}", model="eb-4" diff --git a/docs/develop_guide/README.md b/docs/develop_guide/README.md index 560f5596d..921d17c59 100644 --- a/docs/develop_guide/README.md +++ b/docs/develop_guide/README.md @@ -43,7 +43,7 @@ class SimilarQuestion(CompletionBaseComponent): os.environ["APPBUILDER_TOKEN"] = "..." - qa_mining = appbuilder.SimilarQuestion(model="Qianfan-Appbuilder-Speed-8k") + qa_mining = appbuilder.SimilarQuestion(model="Qianfan-Agent-Speed-8k") msg = "我想吃冰淇淋，哪里的冰淇淋比较好吃？" msg = appbuilder.Message(msg) diff --git a/docs/quick_start/README.md b/docs/quick_start/README.md index 8f56fde9b..f1a5f2ff5 100644 --- a/docs/quick_start/README.md +++ b/docs/quick_start/README.md @@ -42,7 +42,7 @@ ERNIE-Bot 4.0, ERNIE-Bot, ERNIE-3.5-4K-0205, ERNIE-3.5-8K-0205, ERNIE-3.5-8K-122 | ERNIE-Bot | eb | | ERNIE-Bot-turbo | eb-turbo | | EB-turbo-AppBuilder专用版 | ernie_speed_appbuilder | -| Qianfan-Appbuilder-Speed-8k | ernie_speed_appbuilder | +| Qianfan-Agent-Speed-8k | ernie_speed_appbuilder | @@ -56,7 +56,7 @@ os.environ["APPBUILDER_TOKEN"] = "bce-v3/ALTAK-n5AYUIUJMarF7F7iFXVeK/1bf65eed7c8 # 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="Qianfan-Appbuilder-Speed-8k") +playground = appbuilder.Playground(prompt_template=template_str, model="Qianfan-Agent-Speed-8k") # 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"}) @@ -73,7 +73,7 @@ import os os.environ["APPBUILDER_TOKEN"] = "bce-v3/ALTAK-n5AYUIUJMarF7F7iFXVeK/1bf65eed7c8c7efef9b11388524fa1087f90ea58" # 相似问生成组件 -similar_q = appbuilder.SimilarQuestion(model="Qianfan-Appbuilder-Speed-8k") +similar_q = appbuilder.SimilarQuestion(model="Qianfan-Agent-Speed-8k") # 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？") @@ -118,7 +118,7 @@ import appbuilder # 空模版组件 playground = appbuilder.Playground( prompt_template="{query}", - model="Qianfan-Appbuilder-Speed-8k" + model="Qianfan-Agent-Speed-8k" ) # 使用 AgentRuntime 来服务化playground组件 diff --git a/docs/sphinx_md/appbuilder.core.components.llms.dialog_summary.md b/docs/sphinx_md/appbuilder.core.components.llms.dialog_summary.md index 79fc5f997..88c6b8db3 100644 --- a/docs/sphinx_md/appbuilder.core.components.llms.dialog_summary.md +++ b/docs/sphinx_md/appbuilder.core.components.llms.dialog_summary.md @@ -19,7 +19,7 @@ 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"] = '...' -dialog_summary = appbuilder.DialogSummary("Qianfan-Appbuilder-Speed-8k") +dialog_summary = appbuilder.DialogSummary("Qianfan-Agent-Speed-8k") 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/docs/sphinx_md/appbuilder.core.components.llms.hallucination_detection.md b/docs/sphinx_md/appbuilder.core.components.llms.hallucination_detection.md index 712456eb7..d5400d62d 100644 --- a/docs/sphinx_md/appbuilder.core.components.llms.hallucination_detection.md +++ b/docs/sphinx_md/appbuilder.core.components.llms.hallucination_detection.md @@ -9,7 +9,7 @@ 基类：`CompletionBaseComponent` 幻觉检测。输入，判断answer中是否存在幻觉。 - *注：该组件推荐使用Qianfan-Appbuilder-Speed-8k模型。* + *注：该组件推荐使用Qianfan-Agent-Speed-8k模型。* Examples: diff --git a/docs/sphinx_md/appbuilder.core.components.llms.is_complex_query.md b/docs/sphinx_md/appbuilder.core.components.llms.is_complex_query.md index ed83b24b5..ede4feb93 100644 --- a/docs/sphinx_md/appbuilder.core.components.llms.is_complex_query.md +++ b/docs/sphinx_md/appbuilder.core.components.llms.is_complex_query.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="Qianfan-Appbuilder-Speed-8k") +is_complex_query = appbuilder.IsComplexQuery(model="Qianfan-Agent-Speed-8k") 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/docs/sphinx_md/appbuilder.core.components.llms.nl2pandas.md b/docs/sphinx_md/appbuilder.core.components.llms.nl2pandas.md index 10972ad85..d9bf1d518 100644 --- a/docs/sphinx_md/appbuilder.core.components.llms.nl2pandas.md +++ b/docs/sphinx_md/appbuilder.core.components.llms.nl2pandas.md @@ -27,7 +27,7 @@ table_info = '''表格列信息如下： query = "海淀区有哪些学校" query = appbuilder.Message(query) -nl2pandas = appbuilder.Nl2pandasComponent(model="Qianfan-Appbuilder-Speed-8k") +nl2pandas = appbuilder.Nl2pandasComponent(model="Qianfan-Agent-Speed-8k") answer = nl2pandas(query, table_info = table_info) ``` diff --git a/docs/sphinx_md/appbuilder.core.components.llms.oral_query_generation.md b/docs/sphinx_md/appbuilder.core.components.llms.oral_query_generation.md index b9a13d412..02a51f76b 100644 --- a/docs/sphinx_md/appbuilder.core.components.llms.oral_query_generation.md +++ b/docs/sphinx_md/appbuilder.core.components.llms.oral_query_generation.md @@ -9,7 +9,7 @@ 基类：`CompletionBaseComponent` 口语化Query生成，可用于问答场景下对文档增强索引。 - *注：该组件推荐使用Qianfan-Appbuilder-Speed-8k模型。* + *注：该组件推荐使用Qianfan-Agent-Speed-8k模型。* Examples: @@ -24,7 +24,7 @@ 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='Qianfan-Appbuilder-Speed-8k') +oral_query_generation = appbuilder.OralQueryGeneration(model='Qianfan-Agent-Speed-8k') answer = oral_query_generation(appbuilder.Message(text), query_type='全部', output_format='str') print(answer.content) ``` diff --git a/docs/sphinx_md/appbuilder.core.components.llms.playground.md b/docs/sphinx_md/appbuilder.core.components.llms.playground.md index 233718b3a..11f92c75b 100644 --- a/docs/sphinx_md/appbuilder.core.components.llms.playground.md +++ b/docs/sphinx_md/appbuilder.core.components.llms.playground.md @@ -17,7 +17,7 @@ import os 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="Qianfan-Appbuilder-Speed-8k") +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="Qianfan-Agent-Speed-8k") 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/docs/sphinx_md/appbuilder.core.components.llms.query_decomposition.md b/docs/sphinx_md/appbuilder.core.components.llms.query_decomposition.md index 089db8d46..fe98c5896 100644 --- a/docs/sphinx_md/appbuilder.core.components.llms.query_decomposition.md +++ b/docs/sphinx_md/appbuilder.core.components.llms.query_decomposition.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="Qianfan-Appbuilder-Speed-8k") +query_decomposition = appbuilder.QueryDecomposition(model="Qianfan-Agent-Speed-8k") 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/docs/sphinx_md/appbuilder.core.components.llms.query_rewrite.md b/docs/sphinx_md/appbuilder.core.components.llms.query_rewrite.md index b706e12f5..43fd6aa1b 100644 --- a/docs/sphinx_md/appbuilder.core.components.llms.query_rewrite.md +++ b/docs/sphinx_md/appbuilder.core.components.llms.query_rewrite.md @@ -18,7 +18,7 @@ Examples: import appbuilder os.environ["APPBUILDER_TOKEN"] = '...' -query_rewrite = appbuilder.QueryRewrite(model="Qianfan-Appbuilder-Speed-8k") +query_rewrite = appbuilder.QueryRewrite(model="Qianfan-Agent-Speed-8k") 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/docs/sphinx_md/appbuilder.core.components.llms.similar_question.md b/docs/sphinx_md/appbuilder.core.components.llms.similar_question.md index 393311eeb..06fa9b57a 100644 --- a/docs/sphinx_md/appbuilder.core.components.llms.similar_question.md +++ b/docs/sphinx_md/appbuilder.core.components.llms.similar_question.md @@ -20,7 +20,7 @@ import appbuilder os.environ["APPBUILDER_TOKEN"] = "..." -qa_mining = appbuilder.SimilarQuestion(model="Qianfan-Appbuilder-Speed-8k") +qa_mining = appbuilder.SimilarQuestion(model="Qianfan-Agent-Speed-8k") msg = "我想吃冰淇淋，哪里的冰淇淋比较好吃？" msg = appbuilder.Message(msg) diff --git a/docs/sphinx_md/appbuilder.core.components.llms.style_rewrite.md b/docs/sphinx_md/appbuilder.core.components.llms.style_rewrite.md index 6f8239ba6..10567fb42 100644 --- a/docs/sphinx_md/appbuilder.core.components.llms.style_rewrite.md +++ b/docs/sphinx_md/appbuilder.core.components.llms.style_rewrite.md @@ -17,7 +17,7 @@ import os import appbuilder os.environ["APPBUILDER_TOKEN"] = '...' -style_rewrite = appbuilder.StyleRewrite(model="Qianfan-Appbuilder-Speed-8k") +style_rewrite = appbuilder.StyleRewrite(model="Qianfan-Agent-Speed-8k") answer = style_rewrite(appbuilder.Message("文心大模型发布新版本"), style="激励话术") ``` diff --git a/docs/sphinx_md/appbuilder.core.components.llms.style_writing.md b/docs/sphinx_md/appbuilder.core.components.llms.style_writing.md index e525936a3..d33f64173 100644 --- a/docs/sphinx_md/appbuilder.core.components.llms.style_writing.md +++ b/docs/sphinx_md/appbuilder.core.components.llms.style_writing.md @@ -18,7 +18,7 @@ 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"] = '...' -style_writing = appbuilder.StyleWriting(model="Qianfan-Appbuilder-Speed-8k") +style_writing = appbuilder.StyleWriting(model="Qianfan-Agent-Speed-8k") answer = style_writing(appbuilder.Message("帮我写一篇关于人体工学椅的文案"), style_query="小红书", length=100) ``` diff --git a/docs/sphinx_md/appbuilder.core.components.llms.tag_extraction.md b/docs/sphinx_md/appbuilder.core.components.llms.tag_extraction.md index 79fa7c357..1fbb62f50 100644 --- a/docs/sphinx_md/appbuilder.core.components.llms.tag_extraction.md +++ b/docs/sphinx_md/appbuilder.core.components.llms.tag_extraction.md @@ -17,7 +17,7 @@ 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"] = '...' -tag_extraction = appbuilder.TagExtraction(model="Qianfan-Appbuilder-Speed-8k") +tag_extraction = appbuilder.TagExtraction(model="Qianfan-Agent-Speed-8k") answer = tag_extraction(appbuilder.Message("从这段文本中抽取关键标签")) ``` diff --git a/docs/sphinx_md/appbuilder.core.md b/docs/sphinx_md/appbuilder.core.md index c53ac75cd..acd1d9004 100644 --- a/docs/sphinx_md/appbuilder.core.md +++ b/docs/sphinx_md/appbuilder.core.md @@ -91,7 +91,7 @@ os.environ["APPBUILDER_TOKEN"] = '...' class PlaygroundWithHistory(Component): def __init__(self): super().__init__() - self.query_rewrite = QueryRewrite(model="Qianfan-Appbuilder-Speed-8k") + self.query_rewrite = QueryRewrite(model="Qianfan-Agent-Speed-8k") self.play = Playground( prompt_template="{query}", model="eb-4"