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new 8b4661a14d8 [Enhancement](llm) Support llm_agg function (#2825)
8b4661a14d8 is described below
commit 8b4661a14d83fa4176592073b1d8196c3c93e266
Author: linrrarity <[email protected]>
AuthorDate: Thu Sep 4 15:30:23 2025 +0800
[Enhancement](llm) Support llm_agg function (#2825)
## Versions
- [x] dev
- [ ] 3.0
- [ ] 2.1
- [ ] 2.0
## Languages
- [x] Chinese
- [x] English
## Docs Checklist
- [ ] Checked by AI
- [ ] Test Cases Built
---------
Co-authored-by: linzhenqi <[email protected]>
---
docs/ai/llm-function-overview.md | 3 +
.../sql-functions/aggregate-functions/llm-agg.md | 129 +++++++++++++++++++++
.../ai-functions/llm-functions/llm-function.md | 2 +
.../current/ai/llm-function-overview.md | 3 +
.../sql-functions/aggregate-functions/llm-agg.md | 129 +++++++++++++++++++++
.../ai-functions/llm-functions/llm-function.md | 2 +
sidebars.json | 1 +
7 files changed, 269 insertions(+)
diff --git a/docs/ai/llm-function-overview.md b/docs/ai/llm-function-overview.md
index 8d62b87f309..b7b6ca60155 100644
--- a/docs/ai/llm-function-overview.md
+++ b/docs/ai/llm-function-overview.md
@@ -69,6 +69,9 @@ All large language models must be provided externally to
Doris and support text
-
[LLM_TRANSLATE](https://doris.apache.org/docs/dev/sql-manual/sql-functions/ai-functions/llm-functions/llm-translate):
Translates the text into the specified language.
+-
[LLM_AGG](https://doris.apache.org/docs/dev/sql-manual/sql-functions/aggregate-functions/llm-agg):
+Perform cross-line aggregation analysis on multiple texts
+
## LLM Configuration Parameters
Doris centrally manages LLM API access through the [resource
mechanism](https://doris.apache.org/docs/dev/sql-manual/sql-statements/cluster-management/compute-management/CREATE-RESOURCE),
ensuring key security and permission control.
diff --git a/docs/sql-manual/sql-functions/aggregate-functions/llm-agg.md
b/docs/sql-manual/sql-functions/aggregate-functions/llm-agg.md
new file mode 100644
index 00000000000..d47231868b7
--- /dev/null
+++ b/docs/sql-manual/sql-functions/aggregate-functions/llm-agg.md
@@ -0,0 +1,129 @@
+---
+{
+ "title": "LLM_AGG",
+ "language": "en"
+}
+---
+
+## Description
+
+Aggregates a specific column using a large language model according to
user-provided instructions.
+
+## Syntax
+
+`LLM_AGG([<resource_name>], <expr>, <instruction>)`
+
+## Parameter Description
+
+| Parameter | Description |
+| ----------------- | ------------------------------------------------------- |
+| `<resource_name>` | The specified resource name, optional. |
+| `<expr>` | The text column to aggregate. The number of characters
in a single text must be less than 128K.|
+| `<instruction>` | The instruction to execute, only accepts literals. |
+
+## Return Value
+
+Returns a string containing the aggregation result.
+
+If all input values are NULL, returns NULL.
+
+The result is generated by the language model, so the output is not fixed.
+
+## Example
+
+The following table simulates customer support tickets:
+```sql
+CREATE TABLE support_tickets (
+ ticket_id BIGINT,
+ customer_name VARCHAR(100),
+ subject VARCHAR(200),
+ details TEXT
+)
+DUPLICATE KEY(ticket_id)
+DISTRIBUTED BY HASH(ticket_id) BUCKETS 5
+PROPERTIES (
+ "replication_num" = "1"
+);
+
+INSERT INTO support_tickets VALUES
+(1, 'Alice', 'Login Failure', 'Cannot log in after password reset. Tried
clearing cache and different browsers.'),
+(2, 'Bob', 'Login Failure', 'Same problem as Alice. Also seeing 502 errors on
the SSO page.'),
+(3, 'Carol', 'Payment Declined', 'Credit card charged twice but order still
shows pending.'),
+(4, 'Dave', 'Slow Dashboard', 'Dashboard takes >30 seconds to load since the
last release.'),
+(5, 'Eve', 'Login Failure', 'Getting redirected back to login after entering
2FA code.');
+```
+
+You can use `LLM_AGG` to summarize customer issues by problem subject:
+```sql
+SELECT
+ subject,
+ LLM_AGG(
+ 'llm_resource_name',
+ details,
+ 'Summarize every ticket detail into one short paragraph of 40 words or
less.'
+ ) AS ai_summary
+FROM support_tickets
+GROUP BY subject;
+```
+
+```text
++------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| subject | ai_summary
|
++------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| Slow Dashboard | The dashboard loading time has significantly increased to
over 30 seconds following the latest release, indicating a potential issue with
the recent update. |
+| Login Failure | User experiences login issues, including redirection
post-2FA, inability to log in after password reset despite using different
browsers and clearing cache, and encountering 502 errors on the SSO page. |
+| Payment Declined | The customer's credit card was charged twice, but the
order status remains pending, indicating a potential issue with the transaction
processing or system update. |
++------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
+
+case 2：
+
+The following table simulates the user review table of an e-commerce platform.
+```sql
+CREATE TABLE product_reviews (
+ review_id BIGINT,
+ product_id BIGINT,
+ rating TINYINT,
+ comment STRING
+)
+DUPLICATE KEY(review_id)
+DISTRIBUTED BY HASH(product_id) BUCKETS 10
+PROPERTIES (
+ "replication_num" = "1"
+);
+
+INSERT INTO product_reviews VALUES
+(1, 1001, 5, '鞋子尺码刚好，穿着舒服，颜色也好看，物流很快！'),
+(2, 1001, 4, '质量不错，就是鞋底有点硬，需要磨合几天。'),
+(3, 1001, 3, '外观和图片一样，但收到时有轻微胶味。'),
+(4, 1002, 5, '杯子小巧，出汁快，清洗也方便，上班带着刚好。'),
+(5, 1002, 3, '声音有点大，不过能接受，充满电只能榨 5 杯。'),
+(6, 1002, 2, '用了两周就充不进电，售后换货流程太慢。'),
+(7, 1003, 5, '面料透气不闷热，袖口设计很贴心，UPF50+ 确实晒不黑。'),
+(8, 1003, 4, '颜色好看，但拉链有点卡顿，需要用力。'),
+(9, 1004, 5, '降噪给力，地铁里也能安静听歌，续航一周充一次。');
+```
+
+Using LLM_AGG to summarize and evaluate:
+```sql
+SET default_llm_resoure = 'llm_resource_name';
+SELECT
+ product_id,
+ LLM_AGG(
+ comment,
+ '请把多条用户评价总结成一句话，突出买家最关心的优点和缺点，控制在50字以内。'
+ ) AS 评价摘要
+FROM product_reviews
+GROUP BY product_id;
+```
+
+```text
++------------+--------------------------------------------------------------------------------------------------------------+
+| product_id | 评价摘要
|
++------------+--------------------------------------------------------------------------------------------------------------+
+| 1003 | 该产品面料透气、防晒效果好且颜色美观，但拉链使用不顺畅。
|
+| 1004 | 用户评价该产品降噪效果好，续航能力强，一周充一次电。
|
+| 1001 | 买家普遍认为鞋子穿着舒适、外观好看且物流快，但鞋底偏硬且有轻微胶味。
|
+| 1002 | 买家认为该榨汁杯小巧便携、出汁快且易清洗，但电池续航短且售后换货流程慢。
|
++------------+--------------------------------------------------------------------------------------------------------------+
+```
\ No newline at end of file
diff --git
a/docs/sql-manual/sql-functions/ai-functions/llm-functions/llm-function.md
b/docs/sql-manual/sql-functions/ai-functions/llm-functions/llm-function.md
index 374e5e3c799..ded308e9066 100644
--- a/docs/sql-manual/sql-functions/ai-functions/llm-functions/llm-function.md
+++ b/docs/sql-manual/sql-functions/ai-functions/llm-functions/llm-function.md
@@ -140,6 +140,8 @@ Currently supported LLM Functions in Doris include:
- `LLM_TRANSLATE`: Translation
+- `LLM_AGG`: Perform cross-line aggregation analysis on multiple texts
+
### Examples
1. `LLM_TRANSLATE`
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/ai/llm-function-overview.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/ai/llm-function-overview.md
index d1646687556..f9eced4174e 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/ai/llm-function-overview.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/ai/llm-function-overview.md
@@ -68,6 +68,9 @@ under the License.
-
[LLM_TRANSLATE](https://doris.apache.org/zh-CN/docs/dev/sql-manual/sql-functions/ai-functions/llm-functions/llm-translate)：
将文本翻译为指定语言。
+-
[LLM_AGG](https://doris.apache.org/zh-CN/docs/dev/sql-manual/sql-functions/aggregate-functions/llm-agg):
+对多条文本进行跨行聚合分析。
+
## LLM 配置相关参数
Doris
通过[资源机制](https://doris.apache.org/zh-CN/docs/dev/sql-manual/sql-statements/cluster-management/compute-management/CREATE-RESOURCE)
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/sql-manual/sql-functions/aggregate-functions/llm-agg.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/sql-manual/sql-functions/aggregate-functions/llm-agg.md
new file mode 100644
index 00000000000..c610fcf908f
--- /dev/null
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/sql-manual/sql-functions/aggregate-functions/llm-agg.md
@@ -0,0 +1,129 @@
+---
+{
+ "title": "LLM_AGG",
+ "language": "zh-CN"
+}
+---
+
+## 描述
+
+根据用户提供的指令，通过大语言模型对特定列进行聚合操作
+
+## 语法
+
+`LLM_AGG([<resource_name>], <expr>, <instruction>)`
+
+## 参数说明
+
+| 参数 | 说明 |
+| -- | -- |
+| `<resource_name>` | 指定的资源名称, 可空。 |
+| `<expr>` | 要聚合的文本列。单条文本字符数需小于 128K。 |
+| `<instruction>` | 要执行的指令，仅接受字面量。 |
+
+## 返回值
+
+返回包含聚合结果的字符串。
+
+当输入有值全为 NULL 时返回 NULL。
+
+结果为大模型生成，所以返回内容并不固定。
+
+## 举例
+
+示例 1：
+如下表模拟某个客服工单:
+```sql
+CREATE TABLE support_tickets (
+ ticket_id BIGINT,
+ customer_name VARCHAR(100),
+ subject VARCHAR(200),
+ details TEXT
+)
+DUPLICATE KEY(ticket_id)
+DISTRIBUTED BY HASH(ticket_id) BUCKETS 5
+PROPERTIES (
+ "replication_num" = "1"
+);
+
+INSERT INTO support_tickets VALUES
+(1, 'Alice', 'Login Failure', 'Cannot log in after password reset. Tried
clearing cache and different browsers.'),
+(2, 'Bob', 'Login Failure', 'Same problem as Alice. Also seeing 502 errors on
the SSO page.'),
+(3, 'Carol', 'Payment Declined', 'Credit card charged twice but order still
shows pending.'),
+(4, 'Dave', 'Slow Dashboard', 'Dashboard takes >30 seconds to load since the
last release.'),
+(5, 'Eve', 'Login Failure', 'Getting redirected back to login after entering
2FA code.');
+```
+
+可以通过 `LLM_AGG` 总结不同问题类型下客户遇到的问题
+```sql
+SELECT
+ subject,
+ LLM_AGG(
+ 'llm_resource_name',
+ details,
+ 'Summarize every ticket detail into one short paragraph of 40 words or
less.'
+ ) AS ai_summary
+FROM support_tickets
+GROUP BY subject;
+```
+
+```text
++------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| subject | ai_summary
|
++------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| Slow Dashboard | The dashboard loading time has significantly increased to
over 30 seconds following the latest release, indicating a potential issue with
the recent update. |
+| Login Failure | User experiences login issues, including redirection
post-2FA, inability to log in after password reset despite using different
browsers and clearing cache, and encountering 502 errors on the SSO page. |
+| Payment Declined | The customer's credit card was charged twice, but the
order status remains pending, indicating a potential issue with the transaction
processing or system update. |
++------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+```
+
+示例 2：
+下表模拟了电商平台的用户评价表
+```sql
+CREATE TABLE product_reviews (
+ review_id BIGINT,
+ product_id BIGINT,
+ rating TINYINT,
+ comment STRING
+)
+DUPLICATE KEY(review_id)
+DISTRIBUTED BY HASH(product_id) BUCKETS 10
+PROPERTIES (
+ "replication_num" = "1"
+);
+
+INSERT INTO product_reviews VALUES
+(1, 1001, 5, '鞋子尺码刚好，穿着舒服，颜色也好看，物流很快！'),
+(2, 1001, 4, '质量不错，就是鞋底有点硬，需要磨合几天。'),
+(3, 1001, 3, '外观和图片一样，但收到时有轻微胶味。'),
+(4, 1002, 5, '杯子小巧，出汁快，清洗也方便，上班带着刚好。'),
+(5, 1002, 3, '声音有点大，不过能接受，充满电只能榨 5 杯。'),
+(6, 1002, 2, '用了两周就充不进电，售后换货流程太慢。'),
+(7, 1003, 5, '面料透气不闷热，袖口设计很贴心，UPF50+ 确实晒不黑。'),
+(8, 1003, 4, '颜色好看，但拉链有点卡顿，需要用力。'),
+(9, 1004, 5, '降噪给力，地铁里也能安静听歌，续航一周充一次。');
+```
+
+使用 LLM_AGG 总结聚合评价：
+```sql
+SET default_llm_resource = 'llm_resource_name';
+SELECT
+ product_id,
+ LLM_AGG(
+ comment,
+ '请把多条用户评价总结成一句话，突出买家最关心的优点和缺点，控制在50字以内。'
+ ) AS 评价摘要
+FROM product_reviews
+GROUP BY product_id;
+```
+
+```text
++------------+--------------------------------------------------------------------------------------------------------------+
+| product_id | 评价摘要
|
++------------+--------------------------------------------------------------------------------------------------------------+
+| 1003 | 该产品面料透气、防晒效果好且颜色美观，但拉链使用不顺畅。
|
+| 1004 | 用户评价该产品降噪效果好，续航能力强，一周充一次电。
|
+| 1001 | 买家普遍认为鞋子穿着舒适、外观好看且物流快，但鞋底偏硬且有轻微胶味。
|
+| 1002 | 买家认为该榨汁杯小巧便携、出汁快且易清洗，但电池续航短且售后换货流程慢。
|
++------------+--------------------------------------------------------------------------------------------------------------+
+```
\ No newline at end of file
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/sql-manual/sql-functions/ai-functions/llm-functions/llm-function.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/sql-manual/sql-functions/ai-functions/llm-functions/llm-function.md
index 20285c2e6d2..fda00ebe58d 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/sql-manual/sql-functions/ai-functions/llm-functions/llm-function.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/sql-manual/sql-functions/ai-functions/llm-functions/llm-function.md
@@ -134,6 +134,8 @@ Doris当前支持的 LLM Function包括:
- `LLM_TRANSLATE`： 翻译
+- `LLM_AGG`：对多条文本进行跨行聚合分析
+
### 示例
1. `LLM_TRANSLATE`
diff --git a/sidebars.json b/sidebars.json
index 8221db02f7e..9e760881b5c 100644
--- a/sidebars.json
+++ b/sidebars.json
@@ -1751,6 +1751,7 @@
"sql-manual/sql-functions/aggregate-functions/intersect-count",
"sql-manual/sql-functions/aggregate-functions/kurt",
"sql-manual/sql-functions/aggregate-functions/linear-histogram",
+
"sql-manual/sql-functions/aggregate-functions/llm-agg",
"sql-manual/sql-functions/aggregate-functions/map-agg",
"sql-manual/sql-functions/aggregate-functions/max",
"sql-manual/sql-functions/aggregate-functions/max-by",
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