大模型服务平台 TokenHub OpenAI Response 协议字段说明

三、基础参数

四、生成控制参数

五、工具调用

tool_choice 取值：

注意：tool_choice 取值 "required" 及指定函数对象的支持情况因模型而异：

注意："required" 的支持情况最终取决于所调用模型本身，若返回错误，建议改用 "auto" 或直接指定具体的工具名称。

六、输出格式控制

text 参数（object）：配置模型输出的文本格式，通过 text.format 子字段指定。

注意：使用 json_schema 或 json_object 时，hy3、deepseek-v4-flash 会严格输出纯 JSON；部分模型 的输出可能被 Markdown 代码块（“`json … “`）包裹，需自行去除后再解析。另外 json_schema 的 schema 中需包含 "additionalProperties": false，否则 hy3 会报错。

include 参数（array）：指定响应中额外包含的字段列表。三个模型均接受此参数，但额外字段实际是否返回取决于模型支持情况。

七、推理控制

reasoning 参数（object）：仅适用于推理模型的配置选项。

八、对话管理

previous_response_id 参数（string）：上一次响应的 ID，用于多轮对话。通过链接响应 ID 来维护对话状态，无需手动管理消息历史。不能与 conversation 同时使用。

注意：说明：

注意：模型支持：hy3 及通过兼容模式接入的模型（如 deepseek-v4-flash、deepseek-v4-pro、glm-5.2、kimi-k3 等）不支持，传入非空值会返回 400 previous_response_id is not supported in chat-compat mode，多轮对话请通过 input 数组自行携带完整历史。

九、其他参数

十、输入类型详解

input 为数组时，每个元素为一个输入条目，支持以下类型：

EasyInputMessage：

ResponseInputImage：

ResponseInputFile：

十一、工具类型详解

Function（函数工具）：

FileSearch（文件搜索工具）：需提供有效的 vector_store_ids。

未配置有效 vector_store_ids 时，请求不会报错，但也不会执行检索，模型将直接基于自身知识作答。通过兼容模式接入的模型（如 deepseek-v4-flash、deepseek-v4-pro、glm-5.2、kimi-k3 等）仅支持 function 类型工具，file_search、web_search、code_interpreter 等内置工具会被自动丢弃且不报错。

WebSearch（网络搜索工具）：工具类型为 "web_search"（非 OpenAI 的 web_search_preview）。hy3 需开通联网搜索资源包。

CodeInterpreter（代码解释器工具）：当前暂不支持。

MCP（MCP 工具）：当前暂不支持。

十二、返回值详解

返回 Response 对象。

{ "id": "resp_67ccd2bed1ec8190b14f964abc0542670bb6a6b452d3795b", "object": "response", "created_at": 1741476542, "status": "completed", "completed_at": 1741476543, "error": null, "incomplete_details": null, "instructions": null, "max_output_tokens": null, "model": "<your-model-name>", "output": […], "usage": { "input_tokens": 20, "output_tokens": 11, "total_tokens": 31 }}

注意：说明：

注意：temperature、top_p、tool_choice、tools、top_logprobs、background 等字段。

ResponseUsage 对象：

输出条目类型（ output 数组）：

ResponseOutputMessage（消息输出）：

FunctionCall（函数调用输出）：

ReasoningItem（推理条目）：推理模型（hy3、deepseek-v4-flash、deepseek-v4-pro 传入 reasoning.effort 时）会在 output 中额外返回此条目。

十四、示例：文本输入

cURLPythonNode.jsJavaGocurl https://tokenhub.tencentmaas.com/v1/responses \\ -H "Content-Type: application/json" \\ -H "Authorization: Bearer $API_KEY" \\ -d '{ "model": "<your-model-name>", "input": "给我讲一个关于独角兽的三句话睡前故事。" }'from openai import OpenAIclient = OpenAI(api_key="YOUR_API_KEY", base_url="https://tokenhub.tencentmaas.com/v1")response = client.responses.create( model="<your-model-name>", input="给我讲一个关于独角兽的三句话睡前故事。",)print(response.output_text)import OpenAI from 'openai';const client = new OpenAI({ apiKey: 'YOUR_API_KEY', baseURL: 'https://tokenhub.tencentmaas.com/v1' });const response = await client.responses.create({ model: '<your-model-name>', input: '给我讲一个关于独角兽的三句话睡前故事。',});console.log(response.output_text);import okhttp3.*;public class TextInput { public static void main(String[] args) throws Exception { String body = """ { "model": "<your-model-name>", "input": "给我讲一个关于独角兽的三句话睡前故事。" } """; Request request = new Request.Builder() .url("https://tokenhub.tencentmaas.com/v1/responses") .header("Authorization", "Bearer YOUR_API_KEY") .post(RequestBody.create(body, MediaType.parse("application/json"))) .build(); try (Response response = new OkHttpClient().newCall(request).execute()) { System.out.println(response.body().string()); } }}package mainimport ( "fmt" "io" "net/http" "strings")func main() { body := `{ "model": "<your-model-name>", "input": "给我讲一个关于独角兽的三句话睡前故事。"}` req, _ := http.NewRequest("POST", "https://tokenhub.tencentmaas.com/v1/responses", strings.NewReader(body)) req.Header.Set("Authorization", "Bearer YOUR_API_KEY") req.Header.Set("Content-Type", "application/json") resp, err := http.DefaultClient.Do(req) if err != nil { panic(err) } defer resp.Body.Close() data, _ := io.ReadAll(resp.Body) fmt.Println(string(data))}

响应示例：

{ "id": "resp_67ccd2bed1ec8190b14f964abc0542670bb6a6b452d3795b", "object": "response", "status": "completed", "model": "<your-model-name>", "output": [ { "type": "message", "id": "msg_20260614212356mlaob0d2", "status": "completed", "role": "assistant", "content": [ { "type": "output_text", "text": "我是混元，是由腾讯开发的大模型。", "annotations": [] } ] } ], "usage": { "input_tokens": 20, "output_tokens": 11, "total_tokens": 31 }}

十五、示例：图像输入

注意：说明：

注意：图像 URL 需为公网可达的直链；无法访问时将返回 400 错误。也可使用 data:image/png;base64,… 形式的 Base64 数据。

cURLPythonNode.jsJavaGocurl https://tokenhub.tencentmaas.com/v1/responses \\ -H "Content-Type: application/json" \\ -H "Authorization: Bearer $API_KEY" \\ -d '{ "model": "<your-model-name>", "input": [ { "role": "user", "content": [ { "type": "input_text", "text": "这张图片里有什么？" }, { "type": "input_image", "image_url": "https://example.com/image.jpg" } ] } ] }'from openai import OpenAIclient = OpenAI(api_key="YOUR_API_KEY", base_url="https://tokenhub.tencentmaas.com/v1")response = client.responses.create( model="<your-model-name>", input=[ { "role": "user", "content": [ {"type": "input_text", "text": "这张图片里有什么？"}, {"type": "input_image", "image_url": "https://example.com/image.jpg"}, ], } ],)print(response.output_text)import OpenAI from 'openai';const client = new OpenAI({ apiKey: 'YOUR_API_KEY', baseURL: 'https://tokenhub.tencentmaas.com/v1' });const response = await client.responses.create({ model: '<your-model-name>', input: [ { role: 'user', content: [ { type: 'input_text', text: '这张图片里有什么？' }, { type: 'input_image', image_url: 'https://example.com/image.jpg' }, ], }, ],});console.log(response.output_text);import okhttp3.*;public class ImageInput { public static void main(String[] args) throws Exception { String body = """ { "model": "<your-model-name>", "input": [ { "role": "user", "content": [ { "type": "input_text", "text": "这张图片里有什么？" }, { "type": "input_image", "image_url": "https://example.com/image.jpg" } ] } ] } """; Request request = new Request.Builder() .url("https://tokenhub.tencentmaas.com/v1/responses") .header("Authorization", "Bearer YOUR_API_KEY") .post(RequestBody.create(body, MediaType.parse("application/json"))) .build(); try (Response response = new OkHttpClient().newCall(request).execute()) { System.out.println(response.body().string()); } }}package mainimport ( "fmt" "io" "net/http" "strings")func main() { body := `{ "model": "<your-model-name>", "input": [ { "role": "user", "content": [ { "type": "input_text", "text": "这张图片里有什么？" }, { "type": "input_image", "image_url": "https://example.com/image.jpg" } ] } ]}` req, _ := http.NewRequest("POST", "https://tokenhub.tencentmaas.com/v1/responses", strings.NewReader(body)) req.Header.Set("Authorization", "Bearer YOUR_API_KEY") req.Header.Set("Content-Type", "application/json") resp, err := http.DefaultClient.Do(req) if err != nil { panic(err) } defer resp.Body.Close() data, _ := io.ReadAll(resp.Body) fmt.Println(string(data))}

十六、示例：文件输入

注意：说明：

注意：文件输入（input_file）：文件 URL 需为公网可达直链；hy3 暂不可用。

cURLPythonNode.jsJavaGocurl https://tokenhub.tencentmaas.com/v1/responses \\ -H "Content-Type: application/json" \\ -H "Authorization: Bearer $API_KEY" \\ -d '{ "model": "<your-model-name>", "input": [ { "role": "user", "content": [ { "type": "input_text", "text": "这个文件里有什么内容？" }, { "type": "input_file", "file_url": "https://www.example.com/document.pdf" } ] } ] }'from openai import OpenAIclient = OpenAI(api_key="YOUR_API_KEY", base_url="https://tokenhub.tencentmaas.com/v1")response = client.responses.create( model="<your-model-name>", input=[ { "role": "user", "content": [ {"type": "input_text", "text": "这个文件里有什么内容？"}, {"type": "input_file", "file_url": "https://www.example.com/document.pdf"}, ], } ],)print(response.output_text)import OpenAI from 'openai';const client = new OpenAI({ apiKey: 'YOUR_API_KEY', baseURL: 'https://tokenhub.tencentmaas.com/v1' });const response = await client.responses.create({ model: '<your-model-name>', input: [ { role: 'user', content: [ { type: 'input_text', text: '这个文件里有什么内容？' }, { type: 'input_file', file_url: 'https://www.example.com/document.pdf' }, ], }, ],});console.log(response.output_text);import okhttp3.*;public class FileInput { public static void main(String[] args) throws Exception { String body = """ { "model": "<your-model-name>", "input": [ { "role": "user", "content": [ { "type": "input_text", "text": "这个文件里有什么内容？" }, { "type": "input_file", "file_url": "https://www.example.com/document.pdf" } ] } ] } """; Request request = new Request.Builder() .url("https://tokenhub.tencentmaas.com/v1/responses") .header("Authorization", "Bearer YOUR_API_KEY") .post(RequestBody.create(body, MediaType.parse("application/json"))) .build(); try (Response response = new OkHttpClient().newCall(request).execute()) { System.out.println(response.body().string()); } }}package mainimport ( "fmt" "io" "net/http" "strings")func main() { body := `{ "model": "<your-model-name>", "input": [ { "role": "user", "content": [ { "type": "input_text", "text": "这个文件里有什么内容？" }, { "type": "input_file", "file_url": "https://www.example.com/document.pdf" } ] } ]}` req, _ := http.NewRequest("POST", "https://tokenhub.tencentmaas.com/v1/responses", strings.NewReader(body)) req.Header.Set("Authorization", "Bearer YOUR_API_KEY") req.Header.Set("Content-Type", "application/json") resp, err := http.DefaultClient.Do(req) if err != nil { panic(err) } defer resp.Body.Close() data, _ := io.ReadAll(resp.Body) fmt.Println(string(data))}

十七、示例：网络搜索

注意：说明：

注意：网络搜索工具类型为 "web_search"。hy3 需开通联网搜索资源包。

注意：未开通联网搜索资源包时，请求不会报错，但搜索不会生效，响应中 annotations 为空。

cURLPythonNode.jsJavaGocurl https://tokenhub.tencentmaas.com/v1/responses \\ -H "Content-Type: application/json" \\ -H "Authorization: Bearer $API_KEY" \\ -d '{ "model": "<your-model-name>", "tools": [{ "type": "web_search" }], "input": "今天有什么积极的新闻？" }'from openai import OpenAIclient = OpenAI(api_key="YOUR_API_KEY", base_url="https://tokenhub.tencentmaas.com/v1")response = client.responses.create( model="<your-model-name>", tools=[{"type": "web_search"}], input="今天有什么积极的新闻？",)print(response.output_text)import OpenAI from 'openai';const client = new OpenAI({ apiKey: 'YOUR_API_KEY', baseURL: 'https://tokenhub.tencentmaas.com/v1' });const response = await client.responses.create({ model: '<your-model-name>', tools: [{ type: 'web_search' }], input: '今天有什么积极的新闻？',});console.log(response.output_text);import okhttp3.*;public class WebSearch { public static void main(String[] args) throws Exception { String body = """ { "model": "<your-model-name>", "tools": [{ "type": "web_search" }], "input": "今天有什么积极的新闻？" } """; Request request = new Request.Builder() .url("https://tokenhub.tencentmaas.com/v1/responses") .header("Authorization", "Bearer YOUR_API_KEY") .post(RequestBody.create(body, MediaType.parse("application/json"))) .build(); try (Response response = new OkHttpClient().newCall(request).execute()) { System.out.println(response.body().string()); } }}package mainimport ( "fmt" "io" "net/http" "strings")func main() { body := `{ "model": "<your-model-name>", "tools": [{ "type": "web_search" }], "input": "今天有什么积极的新闻？"}` req, _ := http.NewRequest("POST", "https://tokenhub.tencentmaas.com/v1/responses", strings.NewReader(body)) req.Header.Set("Authorization", "Bearer YOUR_API_KEY") req.Header.Set("Content-Type", "application/json") resp, err := http.DefaultClient.Do(req) if err != nil { panic(err) } defer resp.Body.Close() data, _ := io.ReadAll(resp.Body) fmt.Println(string(data))}

十八、示例：文件搜索

注意：说明：

注意：文件搜索（file_search）需提供有效的 vector_store_ids。

注意：传入不存在的 vector_store_ids 时不会报错，但不会执行检索。

cURLPythonNode.jsJavaGocurl https://tokenhub.tencentmaas.com/v1/responses \\ -H "Content-Type: application/json" \\ -H "Authorization: Bearer $API_KEY" \\ -d '{ "model": "<your-model-name>", "tools": [{ "type": "file_search", "vector_store_ids": ["vs_1234567890"], "max_num_results": 20 }], "input": "古代棕龙的属性是什么？" }'from openai import OpenAIclient = OpenAI(api_key="YOUR_API_KEY", base_url="https://tokenhub.tencentmaas.com/v1")response = client.responses.create( model="<your-model-name>", tools=[ { "type": "file_search", "vector_store_ids": ["vs_1234567890"], "max_num_results": 20, } ], input="古代棕龙的属性是什么？",)print(response.output_text)import OpenAI from 'openai';const client = new OpenAI({ apiKey: 'YOUR_API_KEY', baseURL: 'https://tokenhub.tencentmaas.com/v1' });const response = await client.responses.create({ model: '<your-model-name>', tools: [ { type: 'file_search', vector_store_ids: ['vs_1234567890'], max_num_results: 20, }, ], input: '古代棕龙的属性是什么？',});console.log(response.output_text);import okhttp3.*;public class FileSearch { public static void main(String[] args) throws Exception { String body = """ { "model": "<your-model-name>", "tools": [{ "type": "file_search", "vector_store_ids": ["vs_1234567890"], "max_num_results": 20 }], "input": "古代棕龙的属性是什么？" } """; Request request = new Request.Builder() .url("https://tokenhub.tencentmaas.com/v1/responses") .header("Authorization", "Bearer YOUR_API_KEY") .post(RequestBody.create(body, MediaType.parse("application/json"))) .build(); try (Response response = new OkHttpClient().newCall(request).execute()) { System.out.println(response.body().string()); } }}package mainimport ( "fmt" "io" "net/http" "strings")func main() { body := `{ "model": "<your-model-name>", "tools": [{ "type": "file_search", "vector_store_ids": ["vs_1234567890"], "max_num_results": 20 }], "input": "古代棕龙的属性是什么？"}` req, _ := http.NewRequest("POST", "https://tokenhub.tencentmaas.com/v1/responses", strings.NewReader(body)) req.Header.Set("Authorization", "Bearer YOUR_API_KEY") req.Header.Set("Content-Type", "application/json") resp, err := http.DefaultClient.Do(req) if err != nil { panic(err) } defer resp.Body.Close() data, _ := io.ReadAll(resp.Body) fmt.Println(string(data))}

十九、示例：流式输出

cURLPythonNode.jsJavaGocurl https://tokenhub.tencentmaas.com/v1/responses \\ -H "Content-Type: application/json" \\ -H "Authorization: Bearer $API_KEY" \\ -d '{ "model": "<your-model-name>", "instructions": "你是一个有帮助的助手。", "input": "你好！", "stream": true }'from openai import OpenAIclient = OpenAI(api_key="YOUR_API_KEY", base_url="https://tokenhub.tencentmaas.com/v1")stream = client.responses.create( model="<your-model-name>", instructions="你是一个有帮助的助手。", input="你好！", stream=True,)for event in stream: if event.type == "response.output_text.delta": print(event.delta, end="", flush=True)import OpenAI from 'openai';const client = new OpenAI({ apiKey: 'YOUR_API_KEY', baseURL: 'https://tokenhub.tencentmaas.com/v1' });const stream = await client.responses.create({ model: '<your-model-name>', instructions: '你是一个有帮助的助手。', input: '你好！', stream: true,});for await (const event of stream) { if (event.type === 'response.output_text.delta') process.stdout.write(event.delta);}import okhttp3.*;import java.io.BufferedReader;import java.io.InputStreamReader;public class StreamResponse { public static void main(String[] args) throws Exception { String body = """ { "model": "<your-model-name>", "instructions": "你是一个有帮助的助手。", "input": "你好！", "stream": true } """; Request request = new Request.Builder() .url("https://tokenhub.tencentmaas.com/v1/responses") .header("Authorization", "Bearer YOUR_API_KEY") .post(RequestBody.create(body, MediaType.parse("application/json"))) .build(); try (Response response = new OkHttpClient().newCall(request).execute(); BufferedReader reader = new BufferedReader( new InputStreamReader(response.body().byteStream()))) { String line; while ((line = reader.readLine()) != null) { if (!line.isEmpty()) System.out.println(line); } } }}package mainimport ( "bufio" "fmt" "net/http" "strings")func main() { body := `{ "model": "<your-model-name>", "instructions": "你是一个有帮助的助手。", "input": "你好！", "stream": true}` req, _ := http.NewRequest("POST", "https://tokenhub.tencentmaas.com/v1/responses", strings.NewReader(body)) req.Header.Set("Authorization", "Bearer YOUR_API_KEY") req.Header.Set("Content-Type", "application/json") resp, err := http.DefaultClient.Do(req) if err != nil { panic(err) } defer resp.Body.Close() scanner := bufio.NewScanner(resp.Body) for scanner.Scan() { if line := scanner.Text(); line != "" { fmt.Println(line) } }}

流式响应事件序列：

event: response.createdevent: response.in_progressevent: response.output_item.addedevent: response.content_part.addedevent: response.output_text.deltaevent: response.output_text.doneevent: response.content_part.doneevent: response.output_item.doneevent: response.completed

注意：说明：

注意：推理模型在流式模式下会额外输出推理过程事件（response.reasoning_summary_text.delta / response.reasoning_summary_text.done）。

20、示例：函数调用（Function Calling）

函数调用是一个多轮交互过程。第一轮定义工具、发起请求：

cURLPythonNode.jsJavaGocurl https://tokenhub.tencentmaas.com/v1/responses \\ -H "Content-Type: application/json" \\ -H "Authorization: Bearer $API_KEY" \\ -d '{ "model": "<your-model-name>", "input": "北京今天天气怎么样？", "tools": [ { "type": "function", "name": "get_current_weather", "description": "获取指定地点的当前天气", "parameters": { "type": "object", "properties": { "location": { "type": "string", "description": "城市和省份，例如：北京市" }, "unit": { "type": "string", "enum": ["celsius", "fahrenheit"] } }, "required": ["location", "unit"] } } ], "tool_choice": "auto" }'from openai import OpenAIclient = OpenAI(api_key="YOUR_API_KEY", base_url="https://tokenhub.tencentmaas.com/v1")response = client.responses.create( model="<your-model-name>", input="北京今天天气怎么样？", tools=[ { "type": "function", "name": "get_current_weather", "description": "获取指定地点的当前天气", "parameters": { "type": "object", "properties": { "location": {"type": "string", "description": "城市和省份，例如：北京市"}, "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}, }, "required": ["location", "unit"], }, } ], tool_choice="auto",)print(response.output)import OpenAI from 'openai';const client = new OpenAI({ apiKey: 'YOUR_API_KEY', baseURL: 'https://tokenhub.tencentmaas.com/v1' });const response = await client.responses.create({ model: '<your-model-name>', input: '北京今天天气怎么样？', tools: [ { type: 'function', name: 'get_current_weather', description: '获取指定地点的当前天气', parameters: { type: 'object', properties: { location: { type: 'string', description: '城市和省份，例如：北京市' }, unit: { type: 'string', enum: ['celsius', 'fahrenheit'] }, }, required: ['location', 'unit'], }, }, ], tool_choice: 'auto',});console.log(response.output);import okhttp3.*;public class FunctionCallStep1 { public static void main(String[] args) throws Exception { String body = """ { "model": "<your-model-name>", "input": "北京今天天气怎么样？", "tools": [ { "type": "function", "name": "get_current_weather", "description": "获取指定地点的当前天气", "parameters": { "type": "object", "properties": { "location": { "type": "string", "description": "城市和省份，例如：北京市" }, "unit": { "type": "string", "enum": ["celsius", "fahrenheit"] } }, "required": ["location", "unit"] } } ], "tool_choice": "auto" } """; Request request = new Request.Builder() .url("https://tokenhub.tencentmaas.com/v1/responses") .header("Authorization", "Bearer YOUR_API_KEY") .post(RequestBody.create(body, MediaType.parse("application/json"))) .build(); try (Response response = new OkHttpClient().newCall(request).execute()) { System.out.println(response.body().string()); } }}package mainimport ( "fmt" "io" "net/http" "strings")func main() { body := `{ "model": "<your-model-name>", "input": "北京今天天气怎么样？", "tools": [ { "type": "function", "name": "get_current_weather", "description": "获取指定地点的当前天气", "parameters": { "type": "object", "properties": { "location": { "type": "string", "description": "城市和省份，例如：北京市" }, "unit": { "type": "string", "enum": ["celsius", "fahrenheit"] } }, "required": ["location", "unit"] } } ], "tool_choice": "auto"}` req, _ := http.NewRequest("POST", "https://tokenhub.tencentmaas.com/v1/responses", strings.NewReader(body)) req.Header.Set("Authorization", "Bearer YOUR_API_KEY") req.Header.Set("Content-Type", "application/json") resp, err := http.DefaultClient.Do(req) if err != nil { panic(err) } defer resp.Body.Close() data, _ := io.ReadAll(resp.Body) fmt.Println(string(data))}

第一轮响应（模型调用函数）会在 output 中返回 function_call 条目，其中的 call_id 用于下一轮提交结果。

获取到函数结果后，通过 previous_response_id + function_call_output 提交，模型生成最终回答：

cURLPythonNode.jsJavaGocurl https://tokenhub.tencentmaas.com/v1/responses \\ -H "Content-Type: application/json" \\ -H "Authorization: Bearer $API_KEY" \\ -d '{ "model": "<your-model-name>", "previous_response_id": "<上一轮响应的 id>", "input": [ { "type": "function_call_output", "call_id": "<function_call 中的 call_id>", "output": "{\\"temperature\\": 28, \\"unit\\": \\"celsius\\", \\"description\\": \\"晴天，微风\\"}" } ] }'from openai import OpenAIclient = OpenAI(api_key="YOUR_API_KEY", base_url="https://tokenhub.tencentmaas.com/v1")response = client.responses.create( model="<your-model-name>", previous_response_id="<上一轮响应的 id>", input=[ { "type": "function_call_output", "call_id": "<function_call 中的 call_id>", "output": '{"temperature": 28, "unit": "celsius", "description": "晴天，微风"}', } ],)print(response.output_text)import OpenAI from 'openai';const client = new OpenAI({ apiKey: 'YOUR_API_KEY', baseURL: 'https://tokenhub.tencentmaas.com/v1' });const response = await client.responses.create({ model: '<your-model-name>', previous_response_id: '<上一轮响应的 id>', input: [ { type: 'function_call_output', call_id: '<function_call 中的 call_id>', output: '{"temperature": 28, "unit": "celsius", "description": "晴天，微风"}', }, ],});console.log(response.output_text);import okhttp3.*;public class FunctionCallStep2 { public static void main(String[] args) throws Exception { String body = """ { "model": "<your-model-name>", "previous_response_id": "<上一轮响应的 id>", "input": [ { "type": "function_call_output", "call_id": "<function_call 中的 call_id>", "output": "{\\\\"temperature\\\\": 28, \\\\"unit\\\\": \\\\"celsius\\\\", \\\\"description\\\\": \\\\"晴天，微风\\\\"}" } ] } """; Request request = new Request.Builder() .url("https://tokenhub.tencentmaas.com/v1/responses") .header("Authorization", "Bearer YOUR_API_KEY") .post(RequestBody.create(body, MediaType.parse("application/json"))) .build(); try (Response response = new OkHttpClient().newCall(request).execute()) { System.out.println(response.body().string()); } }}package mainimport ( "fmt" "io" "net/http" "strings")func main() { body := `{ "model": "<your-model-name>", "previous_response_id": "<上一轮响应的 id>", "input": [ { "type": "function_call_output", "call_id": "<function_call 中的 call_id>", "output": "{\\"temperature\\": 28, \\"unit\\": \\"celsius\\", \\"description\\": \\"晴天，微风\\"}" } ]}` req, _ := http.NewRequest("POST", "https://tokenhub.tencentmaas.com/v1/responses", strings.NewReader(body)) req.Header.Set("Authorization", "Bearer YOUR_API_KEY") req.Header.Set("Content-Type", "application/json") resp, err := http.DefaultClient.Do(req) if err != nil { panic(err) } defer resp.Body.Close() data, _ := io.ReadAll(resp.Body) fmt.Println(string(data))}

21、示例：推理模型（Reasoning）

cURLPythonNode.jsJavaGocurl https://tokenhub.tencentmaas.com/v1/responses \\ -H "Content-Type: application/json" \\ -H "Authorization: Bearer $API_KEY" \\ -d '{ "model": "<your-model-name>", "input": "请解释量子纠缠的基本原理。", "reasoning": { "effort": "high" } }'from openai import OpenAIclient = OpenAI(api_key="YOUR_API_KEY", base_url="https://tokenhub.tencentmaas.com/v1")response = client.responses.create( model="<your-model-name>", input="请解释量子纠缠的基本原理。", reasoning={"effort": "high"},)print(response.output_text)import OpenAI from 'openai';const client = new OpenAI({ apiKey: 'YOUR_API_KEY', baseURL: 'https://tokenhub.tencentmaas.com/v1' });const response = await client.responses.create({ model: '<your-model-name>', input: '请解释量子纠缠的基本原理。', reasoning: { effort: 'high' },});console.log(response.output_text);import okhttp3.*;public class Reasoning { public static void main(String[] args) throws Exception { String body = """ { "model": "<your-model-name>", "input": "请解释量子纠缠的基本原理。", "reasoning": { "effort": "high" } } """; Request request = new Request.Builder() .url("https://tokenhub.tencentmaas.com/v1/responses") .header("Authorization", "Bearer YOUR_API_KEY") .post(RequestBody.create(body, MediaType.parse("application/json"))) .build(); try (Response response = new OkHttpClient().newCall(request).execute()) { System.out.println(response.body().string()); } }}package mainimport ( "fmt" "io" "net/http" "strings")func main() { body := `{ "model": "<your-model-name>", "input": "请解释量子纠缠的基本原理。", "reasoning": { "effort": "high" }}` req, _ := http.NewRequest("POST", "https://tokenhub.tencentmaas.com/v1/responses", strings.NewReader(body)) req.Header.Set("Authorization", "Bearer YOUR_API_KEY") req.Header.Set("Content-Type", "application/json") resp, err := http.DefaultClient.Do(req) if err != nil { panic(err) } defer resp.Body.Close() data, _ := io.ReadAll(resp.Body) fmt.Println(string(data))}

22、过滤器类型

用于文件搜索工具的 filters 字段。

ComparisonFilter（比较过滤器）：将指定属性键与给定值进行比较。

CompoundFilter（复合过滤器）：使用 and 或 or 组合多个过滤器。