curl --location 'https://geobaseapi.aibase.com/v1/openapi/execute' \
--header 'Content-Type: application/json' \
--header 'AIBase-API-Key: AIBase_xxxxxxxxxxxxxxxx' \
--header 'AIBase-Request-Id: req-20260924-001' \
--data '{
"apiCode": "prompt.analysis.detail",
"data": {
"brandId": "brand-001",
"topicId": "topic-001",
"keyword": "推荐",
"llmName": "deepseek",
"startDate": "2026-09-01",
"endDate": "2026-09-23",
"pageNo": 1,
"pageSize": 50,
"fieldSort": "visibilityCount",
"fieldType": "DESC",
"sentiment": "正面",
"promptId": "prompt-001",
"sentimentType": "positive",
"sentimentKeyword": "好用"
}
}'
import os
import requests
api_key = os.environ["AIBASE_API_KEY"]
headers = {
"AIBase-API-Key": api_key,
"Content-Type": "application/json",
"AIBase-Request-Id": "req-20260924-001",
}
res = requests.post(
"https://geobaseapi.aibase.com/v1/openapi/execute",
headers=headers,
json={"apiCode": "prompt.analysis.detail", "data": {"brandId": "brand-001", "topicId": "topic-001", "keyword": "推荐", "llmName": "deepseek", "startDate": "2026-09-01", "endDate": "2026-09-23", "pageNo": 1, "pageSize": 50, "fieldSort": "visibilityCount", "fieldType": "DESC", "sentiment": "正面", "promptId": "prompt-001", "sentimentType": "positive", "sentimentKeyword": "好用"}},
timeout=60,
)
res.raise_for_status()
payload = res.json()
if payload["code"] == 200:
for item in payload["data"]["records"]:
print(item)
const res = await fetch("https://geobaseapi.aibase.com/v1/openapi/execute", {
method: "POST",
headers: {
"Content-Type": "application/json",
"AIBase-API-Key": process.env.AIBASE_API_KEY,
"AIBase-Request-Id": "req-20260924-001",
},
body: JSON.stringify({"apiCode": "prompt.analysis.detail", "data": {"brandId": "brand-001", "topicId": "topic-001", "keyword": "推荐", "llmName": "deepseek", "startDate": "2026-09-01", "endDate": "2026-09-23", "pageNo": 1, "pageSize": 50, "fieldSort": "visibilityCount", "fieldType": "DESC", "sentiment": "正面", "promptId": "prompt-001", "sentimentType": "positive", "sentimentKeyword": "好用"}}),
});
const payload = await res.json();
if (payload.code === 200) {
for (const item of payload.data.records) {
console.log(item);
}
}
String body = """
{
"apiCode": "prompt.analysis.detail",
"data": {
"brandId": "brand-001",
"topicId": "topic-001",
"keyword": "推荐",
"llmName": "deepseek",
"startDate": "2026-09-01",
"endDate": "2026-09-23",
"pageNo": 1,
"pageSize": 50,
"fieldSort": "visibilityCount",
"fieldType": "DESC",
"sentiment": "正面",
"promptId": "prompt-001",
"sentimentType": "positive",
"sentimentKeyword": "好用"
}
}
""";
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://geobaseapi.aibase.com/v1/openapi/execute"))
.header("Content-Type", "application/json")
.header("AIBase-API-Key", "AIBase_xxxxxxxxxxxxxxxx")
.header("AIBase-Request-Id", "req-20260924-001")
.POST(BodyPublishers.ofString(body))
.build();
HttpResponse<String> response = HttpClient.newHttpClient()
.send(request, BodyHandlers.ofString());
System.out.println(response.body());
{
"code": 200,
"msg": "成功",
"data": {
"records": [
{
"promptId": "prompt-001",
"promptText": "哪个品牌的XX比较好？",
"topicName": "品牌口碑",
"topicId": "topic-001",
"llmName": "deepseek",
"visibilityCount": 12,
"sentiment": "正面",
"sentimentScore": 82.5,
"position": 1,
"competitorsTop3": "竞品A,竞品B,竞品C",
"queryDate": "2026-09-23",
"goodsCount": 3,
"positiveKeywords": ["好用", "推荐"],
"negativeKeywords": null,
"neutralKeywords": null,
"resultContent": "大模型回答原文，可能较长"
}
],
"total": 1,
"size": 50,
"current": 1,
"pages": 1
},
"timeStamp": 1788830174812
}
AI 对话问题监测明细
查询指定品牌下 AI 对话问题在各 AI 平台的监测明细，包括推荐/曝光情况、情感分析、品牌排名、Top3 竞品、提及商品数量及 AI 平台回答原文等。
POST
/
v1
/
openapi
/
execute
curl --location 'https://geobaseapi.aibase.com/v1/openapi/execute' \
--header 'Content-Type: application/json' \
--header 'AIBase-API-Key: AIBase_xxxxxxxxxxxxxxxx' \
--header 'AIBase-Request-Id: req-20260924-001' \
--data '{
"apiCode": "prompt.analysis.detail",
"data": {
"brandId": "brand-001",
"topicId": "topic-001",
"keyword": "推荐",
"llmName": "deepseek",
"startDate": "2026-09-01",
"endDate": "2026-09-23",
"pageNo": 1,
"pageSize": 50,
"fieldSort": "visibilityCount",
"fieldType": "DESC",
"sentiment": "正面",
"promptId": "prompt-001",
"sentimentType": "positive",
"sentimentKeyword": "好用"
}
}'
import os
import requests
api_key = os.environ["AIBASE_API_KEY"]
headers = {
"AIBase-API-Key": api_key,
"Content-Type": "application/json",
"AIBase-Request-Id": "req-20260924-001",
}
res = requests.post(
"https://geobaseapi.aibase.com/v1/openapi/execute",
headers=headers,
json={"apiCode": "prompt.analysis.detail", "data": {"brandId": "brand-001", "topicId": "topic-001", "keyword": "推荐", "llmName": "deepseek", "startDate": "2026-09-01", "endDate": "2026-09-23", "pageNo": 1, "pageSize": 50, "fieldSort": "visibilityCount", "fieldType": "DESC", "sentiment": "正面", "promptId": "prompt-001", "sentimentType": "positive", "sentimentKeyword": "好用"}},
timeout=60,
)
res.raise_for_status()
payload = res.json()
if payload["code"] == 200:
for item in payload["data"]["records"]:
print(item)
const res = await fetch("https://geobaseapi.aibase.com/v1/openapi/execute", {
method: "POST",
headers: {
"Content-Type": "application/json",
"AIBase-API-Key": process.env.AIBASE_API_KEY,
"AIBase-Request-Id": "req-20260924-001",
},
body: JSON.stringify({"apiCode": "prompt.analysis.detail", "data": {"brandId": "brand-001", "topicId": "topic-001", "keyword": "推荐", "llmName": "deepseek", "startDate": "2026-09-01", "endDate": "2026-09-23", "pageNo": 1, "pageSize": 50, "fieldSort": "visibilityCount", "fieldType": "DESC", "sentiment": "正面", "promptId": "prompt-001", "sentimentType": "positive", "sentimentKeyword": "好用"}}),
});
const payload = await res.json();
if (payload.code === 200) {
for (const item of payload.data.records) {
console.log(item);
}
}
String body = """
{
"apiCode": "prompt.analysis.detail",
"data": {
"brandId": "brand-001",
"topicId": "topic-001",
"keyword": "推荐",
"llmName": "deepseek",
"startDate": "2026-09-01",
"endDate": "2026-09-23",
"pageNo": 1,
"pageSize": 50,
"fieldSort": "visibilityCount",
"fieldType": "DESC",
"sentiment": "正面",
"promptId": "prompt-001",
"sentimentType": "positive",
"sentimentKeyword": "好用"
}
}
""";
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://geobaseapi.aibase.com/v1/openapi/execute"))
.header("Content-Type", "application/json")
.header("AIBase-API-Key", "AIBase_xxxxxxxxxxxxxxxx")
.header("AIBase-Request-Id", "req-20260924-001")
.POST(BodyPublishers.ofString(body))
.build();
HttpResponse<String> response = HttpClient.newHttpClient()
.send(request, BodyHandlers.ofString());
System.out.println(response.body());
{
"code": 200,
"msg": "成功",
"data": {
"records": [
{
"promptId": "prompt-001",
"promptText": "哪个品牌的XX比较好？",
"topicName": "品牌口碑",
"topicId": "topic-001",
"llmName": "deepseek",
"visibilityCount": 12,
"sentiment": "正面",
"sentimentScore": 82.5,
"position": 1,
"competitorsTop3": "竞品A,竞品B,竞品C",
"queryDate": "2026-09-23",
"goodsCount": 3,
"positiveKeywords": ["好用", "推荐"],
"negativeKeywords": null,
"neutralKeywords": null,
"resultContent": "大模型回答原文，可能较长"
}
],
"total": 1,
"size": 50,
"current": 1,
"pages": 1
},
"timeStamp": 1788830174812
}
查询指定品牌下 AI 对话问题在各 AI 平台的监测明细，包括推荐/曝光情况、情感分析、品牌排名、Top3 竞品、提及商品数量及 AI 平台回答原文等。支持多条件组合筛选、时间范围限制、排序与分页，是监测能力最完整的实时查询接口。
完整响应类型可表示为
可按以下 TypeScript 类型定义解析响应数据。
执行模式：SYNC · 实时请求。
请求发出后服务端同步执行业务，结果直接在当前响应的
data 中返回，不存在异步任务、无需轮询、无需二次查询。接口速查
| 项目 | 当前接口约定 |
|---|---|
| 接口状态 | 已上线 |
| 请求方式 | POST |
| 请求地址 | https://geobaseapi.aibase.com/v1/openapi/execute |
| 业务标识 | prompt.analysis.detail |
| 执行模式 | SYNC · 实时请求（直接返回，无需轮询） |
| 身份认证 | Header AIBase-API-Key |
| 请求格式 | application/json |
| 返回结构 | 分页结构（含 records） |
请求头
string
required
开发者 API Key，例如
AIBase_xxx。用于身份认证、有效期与调用权限校验，请仅在服务端保存和使用。string
required
固定为
application/json。string
开发者自定义请求 ID，用于请求追踪；不传时系统自动生成 UUID。
请求体
string
required
固定为
prompt.analysis.detailstring
required
所属品牌 ID，为空返回
4001string
按主题筛选
string
按AI对话问题关键词筛选
string
按 AI 平台筛选，如
deepseekstring
格式
yyyy-MM-dd；默认最近 7 天string
格式
yyyy-MM-dd；默认今天，不能晚于今天integer
默认
1integer
默认
50，最大 100，超限自动截断为 100string
见下方排序字段说明；默认按查询日期倒序
string
如
ASC / DESCstring
情感类型筛选，如
正面 / 中性 / 负面string
按具体问题筛选
string
情感词类型，如
positivestring
情感关键词筛选
排序字段说明
| fieldSort 取值 | 含义 |
|---|---|
visibilityCount | 按推荐/曝光次数排序 |
sentimentScore | 按情感得分排序 |
position | 按品牌排名排序 |
goodsCount | 按提及商品数量排序 |
promptText | 按AI对话问题排序 |
llmName | 按AI平台排序 |
createTime | 按创建时间排序 |
时间范围规则：
startDate/endDate 不传时默认查询最近 7 天；endDate 晚于今天会被自动截断为今天；起止时间跨度最大 6 个月，超范围自动截断；开始日期晚于结束日期将直接报错。curl --location 'https://geobaseapi.aibase.com/v1/openapi/execute' \
--header 'Content-Type: application/json' \
--header 'AIBase-API-Key: AIBase_xxxxxxxxxxxxxxxx' \
--header 'AIBase-Request-Id: req-20260924-001' \
--data '{
"apiCode": "prompt.analysis.detail",
"data": {
"brandId": "brand-001",
"topicId": "topic-001",
"keyword": "推荐",
"llmName": "deepseek",
"startDate": "2026-09-01",
"endDate": "2026-09-23",
"pageNo": 1,
"pageSize": 50,
"fieldSort": "visibilityCount",
"fieldType": "DESC",
"sentiment": "正面",
"promptId": "prompt-001",
"sentimentType": "positive",
"sentimentKeyword": "好用"
}
}'
import os
import requests
api_key = os.environ["AIBASE_API_KEY"]
headers = {
"AIBase-API-Key": api_key,
"Content-Type": "application/json",
"AIBase-Request-Id": "req-20260924-001",
}
res = requests.post(
"https://geobaseapi.aibase.com/v1/openapi/execute",
headers=headers,
json={"apiCode": "prompt.analysis.detail", "data": {"brandId": "brand-001", "topicId": "topic-001", "keyword": "推荐", "llmName": "deepseek", "startDate": "2026-09-01", "endDate": "2026-09-23", "pageNo": 1, "pageSize": 50, "fieldSort": "visibilityCount", "fieldType": "DESC", "sentiment": "正面", "promptId": "prompt-001", "sentimentType": "positive", "sentimentKeyword": "好用"}},
timeout=60,
)
res.raise_for_status()
payload = res.json()
if payload["code"] == 200:
for item in payload["data"]["records"]:
print(item)
const res = await fetch("https://geobaseapi.aibase.com/v1/openapi/execute", {
method: "POST",
headers: {
"Content-Type": "application/json",
"AIBase-API-Key": process.env.AIBASE_API_KEY,
"AIBase-Request-Id": "req-20260924-001",
},
body: JSON.stringify({"apiCode": "prompt.analysis.detail", "data": {"brandId": "brand-001", "topicId": "topic-001", "keyword": "推荐", "llmName": "deepseek", "startDate": "2026-09-01", "endDate": "2026-09-23", "pageNo": 1, "pageSize": 50, "fieldSort": "visibilityCount", "fieldType": "DESC", "sentiment": "正面", "promptId": "prompt-001", "sentimentType": "positive", "sentimentKeyword": "好用"}}),
});
const payload = await res.json();
if (payload.code === 200) {
for (const item of payload.data.records) {
console.log(item);
}
}
String body = """
{
"apiCode": "prompt.analysis.detail",
"data": {
"brandId": "brand-001",
"topicId": "topic-001",
"keyword": "推荐",
"llmName": "deepseek",
"startDate": "2026-09-01",
"endDate": "2026-09-23",
"pageNo": 1,
"pageSize": 50,
"fieldSort": "visibilityCount",
"fieldType": "DESC",
"sentiment": "正面",
"promptId": "prompt-001",
"sentimentType": "positive",
"sentimentKeyword": "好用"
}
}
""";
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://geobaseapi.aibase.com/v1/openapi/execute"))
.header("Content-Type", "application/json")
.header("AIBase-API-Key", "AIBase_xxxxxxxxxxxxxxxx")
.header("AIBase-Request-Id", "req-20260924-001")
.POST(BodyPublishers.ofString(body))
.build();
HttpResponse<String> response = HttpClient.newHttpClient()
.send(request, BodyHandlers.ofString());
System.out.println(response.body());
返回参数
业务结果位于data，为分页结构，其中 records 为分析明细列表。
object[]
AI 对话问题分析明细。
string
问题唯一标识。
string
AI 对话问题文本。
string
所属主题名称。
string
所属主题 ID。
string
本次分析对应的 AI 平台。
integer
品牌被推荐/曝光次数。
string
如
正面 / 中性 / 负面。number
情感得分。
integer
品牌在该回答中的排名，未上榜时为 0。
string
回答中出现的前 3 个竞品，逗号分隔，可能为 null。
string
格式
yyyy-MM-dd。integer
该问题提及的商品数量，无商品为 0。
object
正/负/中性情感关键词列表，可能为 null。
object
同上，见上方分页字段说明。
object
同上，见上方分页字段说明。
string
大模型回答原文，可能较长或为 null。
long / integer
总数、每页条数、当前页、总页数。
long / integer
同上，见上方分页字段说明。
long / integer
同上，见上方分页字段说明。
long / integer
同上，见上方分页字段说明。
{
"code": 200,
"msg": "成功",
"data": {
"records": [
{
"promptId": "prompt-001",
"promptText": "哪个品牌的XX比较好？",
"topicName": "品牌口碑",
"topicId": "topic-001",
"llmName": "deepseek",
"visibilityCount": 12,
"sentiment": "正面",
"sentimentScore": 82.5,
"position": 1,
"competitorsTop3": "竞品A,竞品B,竞品C",
"queryDate": "2026-09-23",
"goodsCount": 3,
"positiveKeywords": ["好用", "推荐"],
"negativeKeywords": null,
"neutralKeywords": null,
"resultContent": "大模型回答原文，可能较长"
}
],
"total": 1,
"size": 50,
"current": 1,
"pages": 1
},
"timeStamp": 1788830174812
}
接入注意事项
apiCode必须固定为prompt.analysis.detail。brandId为必填参数，为空返回4001（所需参数不足）。startDate/endDate格式必须为yyyy-MM-dd，默认最近 7 天，最大查询跨度 6 个月。endDate不能晚于今天；开始日期晚于结束日期会报错。pageSize默认 50，最大 100，超限自动截断为 100。fieldSort仅支持文档列出的取值，非法值将回退为默认排序（查询日期倒序）。position = 0表示品牌未上榜，不代表接口失败。competitorsTop3、三个情感关键词字段及resultContent可能为null，解析时做好空值兼容。- 本接口查询数据量较大，建议使用筛选条件缩小范围，控制
pageSize。
Java 返回对象
Java 返回对象
public class PromptAnalysisDetail {
private String promptId;
private String promptText;
private String topicName;
private String topicId;
private String llmName;
private Integer visibilityCount;
private String sentiment;
private BigDecimal sentimentScore;
private Integer position;
private String competitorsTop3;
private LocalDate queryDate;
private Integer goodsCount;
private Object positiveKeywords;
private Object negativeKeywords;
private Object neutralKeywords;
private String resultContent;
}
ReturnResult<PageResult<PromptAnalysisDetail>>（PageResult 定义见 6.2.5）。TypeScript 类型
TypeScript 类型
export interface PromptAnalysisDetail {
promptId: string;
promptText: string;
topicName: string;
topicId: string;
llmName: string;
visibilityCount: number;
sentiment: string | null;
sentimentScore: number | null;
position: number;
competitorsTop3: string | null;
queryDate: string;
goodsCount: number;
positiveKeywords: string[] | null;
negativeKeywords: string[] | null;
neutralKeywords: string[] | null;
resultContent: string | null;
}
本页的 cURL 与 Java 示例来自官方接口文档；Python 与 Node.js 示例为等价转写，未经服务端联调，请以实际返回结果为准。