快速开始

以下示例代码中，均需将 <ARK_API_KEY> 替换为实际 API Key，将 <knowledge_resource_id> 替换为授权的知识库 ID。 说明 cURL 示例中的关键字段： thinking.type: "disabled" 关闭模型思考，直接调用知识库搜索； tools.limit 控制最多返回的搜索结果数量； tools.ranking_options.get_attachment_link 是否获取图片临时下载链接； max_tool_calls 限制调用知识库搜索的轮次。 cURL OpenAI SDK Plain 复制 curl --location 'https://ark.cn-beijing.volces.com/api/v3/responses' \ --header 'Content-Type: application/json' \ --header 'Authorization: Bearer <ARK_API_KEY>' \ --header 'ark-beta-knowledge-search: true' \ --data '{ "model": "doubao-seed-2-1-pro-260628", "stream": true, "thinking": { "type": "disabled" }, "tools": [ { "type": "knowledge_search", "knowledge_resource_id": "<knowledge_resource_id>", "limit": 2, "ranking_options": { "get_attachment_link": true } } ], "input": [ { "role": "user", "content": "机票选择页面中，如何选择该航班不同价格的机票？" } ], "max_tool_calls": 1 }' Python 复制 import os from openai import OpenAI # 从环境变量获取API密钥，配置方法见：https://www.volcengine.com/docs/82379/1399008 api_key = os.getenv( 'ARK_API_KEY' ) # 初始化客户端 client = OpenAI( base_url= 'https://ark.cn-beijing.volces.com/api/v3' , api_key=api_key, default_headers={ "ark-beta-knowledge-search" : "true" } # 启用私域知识库搜索 ) # 发起知识库搜索请求 response = client.responses.create( model= "doubao-seed-2-1-pro-260628" , # 替换为支持的模型 input =[ { "role" : "user" , "content" : [ { "type" : "input_text" , "text" : "应用实验室里有类似实时视频理解的agent demo么？" # 用户问题 } ] } ], tools=[ { "type" : "knowledge_search" , "knowledge_resource_id" : "<knowledge_resource_id>" , # 替换为实际知识库ID "limit" : 10 , # 最多返回10条搜索结果 } ], stream= True , # 启用流式响应，实时获取结果 extra_body={ "thinking" : { "type" : "auto" }} # 模型自动判断是否需要搜索 ) # 处理流式响应 for chunk in response: if hasattr (chunk, 'delta' ): print (chunk.delta, end= "" , flush= True ) Plain 复制 curl --location 'https://ark.cn-beijing.volces.com/api/v3/responses' \ --header 'Content-Type: application/json' \ --header 'Authorization: Bearer <ARK_API_KEY>' \ --header 'ark-beta-knowledge-search: true' \ --data '{ "model": "doubao-seed-2-1-pro-260628", "stream": true, "thinking": { "type": "disabled" }, "tools": [ { "type": "knowledge_search", "knowledge_resource_id": "<knowledge_resource_id>", "limit": 2, "ranking_options": { "get_attachment_link": true } } ], "input": [ { "role": "user", "content": "机票选择页面中，如何选择该航班不同价格的机票？" } ], "max_tool_calls": 1 }' curl --location 'https://ark.cn-beijing.volces.com/api/v3/responses' \ --header 'Content-Type: application/json' \ --header 'Authorization: Bearer <ARK_API_KEY>' \ --header 'ark-beta-knowledge-search: true' \ --data '{ "model": "doubao-seed-2-1-pro-260628", "stream": true, "thinking": { "type": "disabled" }, "tools": [ { "type": "knowledge_search", "knowledge_resource_id": "<knowledge_resource_id>", "limit": 2, "ranking_options": { "get_attachment_link": true } } ], "input": [ { "role": "user", "content": "机票选择页面中，如何选择该航班不同价格的机票？" } ], "max_tool_calls": 1 }' Python 复制 import os from openai import OpenAI # 从环境变量获取API密钥，配置方法见：https://www.volcengine.com/docs/82379/1399008 api_key = os.getenv( 'ARK_API_KEY' ) # 初始化客户端 client = OpenAI( base_url= 'https://ark.cn-beijing.volces.com/api/v3' , api_key=api_key, default_headers={ "ark-beta-knowledge-search" : "true" } # 启用私域知识库搜索 ) # 发起知识库搜索请求 response = client.responses.create( model= "doubao-seed-2-1-pro-260628" , # 替换为支持的模型 input =[ { "role" : "user" , "content" : [ { "type" : "input_text" , "text" : "应用实验室里有类似实时视频理解的agent demo么？" # 用户问题 } ] } ], tools=[ { "type" : "knowledge_search" , "knowledge_resource_id" : "<knowledge_resource_id>" , # 替换为实际知识库ID "limit" : 10 , # 最多返回10条搜索结果 } ], stream= True , # 启用流式响应，实时获取结果 extra_body={ "thinking" : { "type" : "auto" }} # 模型自动判断是否需要搜索 ) # 处理流式响应 for chunk in response: if hasattr (chunk, 'delta' ): print (chunk.delta, end= "" , flush= True ) import os from openai import OpenAI # 从环境变量获取API密钥，配置方法见：https://www.volcengine.com/docs/82379/1399008 api_key = os.getenv( 'ARK_API_KEY' ) # 初始化客户端 client = OpenAI( base_url= 'https://ark.cn-beijing.volces.com/api/v3' , api_key=api_key, default_headers={ "ark-beta-knowledge-search" : "true" } # 启用私域知识库搜索 ) # 发起知识库搜索请求 response = client.responses.create( model= "doubao-seed-2-1-pro-260628" , # 替换为支持的模型 input =[ { "role" : "user" , "content" : [ { "type" : "input_text" , "text" : "应用实验室里有类似实时视频理解的agent demo么？" # 用户问题 } ] } ], tools=[ { "type" : "knowledge_search" , "knowledge_resource_id" : "<knowledge_resource_id>" , # 替换为实际知识库ID "limit" : 10 , # 最多返回10条搜索结果 } ], stream= True , # 启用流式响应，实时获取结果 extra_body={ "thinking" : { "type" : "auto" }} # 模型自动判断是否需要搜索 ) # 处理流式响应 for chunk in response: if hasattr (chunk, 'delta' ): print (chunk.delta, end= "" , flush= True )