替换下线模型

NEW_README.md

@@ -101,7 +101,7 @@ 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-Agent-Speed-8K")
+playground = appbuilder.Playground(prompt_template=template_str, model="DeepSeek-V3.1")
 
 # 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)
@@ -118,7 +118,7 @@ import os
 os.environ["APPBUILDER_TOKEN"] = "your-token-here"
 
 # 创建组件实例
-rag_with_baidu_search_pro = appbuilder.RagWithBaiduSearchPro(model="ERNIE-3.5-8K")
+rag_with_baidu_search_pro = appbuilder.RagWithBaiduSearchPro(model="DeepSeek-V3.1")
 
 # 执行组件
 input = appbuilder.Message("9.11和9.8哪个大")

README.md

@@ -110,7 +110,7 @@ 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-Agent-Speed-8K")
+playground = appbuilder.Playground(prompt_template=template_str, model="DeepSeek-V3.1")
 
 # 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)
@@ -156,7 +156,7 @@ import os
 # 设置环境中的TOKEN，使用请替换为您的个人TOKEN
 os.environ["APPBUILDER_TOKEN"] = "your api key"
 
-rag_with_baidu_search_pro = appbuilder.RagWithBaiduSearchPro(model="ERNIE-3.5-8K")
+rag_with_baidu_search_pro = appbuilder.RagWithBaiduSearchPro(model="DeepSeek-V3.1")
 
 input = appbuilder.Message("9.11和9.8哪个大")
 result = rag_with_baidu_search_pro.run(

cookbooks/components/agent_runtime.ipynb

@@ -429,7 +429,7 @@
     "class PlaygroundWithHistory(Component):\n",
     "    def __init__(self):\n",
     "        super().__init__()\n",
-    "        self.query_rewrite = QueryRewrite(model=\"Qianfan-Agent-Speed-8K\")\n",
+    "        self.query_rewrite = QueryRewrite(model=\"DeepSeek-V3.1\")\n",
     "        self.playground = Playground(\n",
     "            prompt_template=\"{query}\",\n",
     "            model=\"ERNIE-Bot\"\n",

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-Agent-Speed-8K 模型\n",
-    "component = appbuilder.RAGWithBaiduSearch(model=\"Qianfan-Agent-Speed-8K\")\n",
+    "# 使用 DeepSeek-V3.1 模型\n",
+    "component = appbuilder.RAGWithBaiduSearch(model=\"DeepSeek-V3.1\")\n",
     "query = appbuilder.Message(\"海淀区的面积是多少\")\n",
     "\n",
     "answer = component.run(\n",

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-Agent-Speed-8K')\n",
+    "product_information_generation = Playground(prompt_template=prompt_template, model='DeepSeek-V3.1')\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-Agent-Speed-8K')\n",
+    "qa_pair_mining = QAPairMining(model='DeepSeek-V3.1')\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-Agent-Speed-8K')\n",
+    "style_writing = StyleWriting(model='DeepSeek-V3.1')\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-Agent-Speed-8K')\n",
+    "tag_extraction = TagExtraction(model='DeepSeek-V3.1')\n",
     "\n",
     "# 获取标签\n",
     "response = tag_extraction(Message(copywriting), stream=False, temperature=1e-10)\n",

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-Agent-Speed-8K\")\n",
+    "tagger = appbuilder.TagExtraction(model=\"DeepSeek-V3.1\")\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-Agent-Speed-8K\"\n",
+    "    model=\"DeepSeek-V3.1\"\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",