[Enhancement](llm) Support some LLM functions

docs/sql-manual/sql-functions/scalar-functions/llm-functions/llm-classify.md

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+---
+{
+    "title": "LLM_CLASSIFY",
+    "language": "en"
+}
+---
+
+<!-- 
+Licensed to the Apache Software Foundation (ASF) under one
+or more contributor license agreements.  See the NOTICE file
+distributed with this work for additional information
+regarding copyright ownership.  The ASF licenses this file
+to you under the Apache License, Version 2.0 (the
+"License"); you may not use this file except in compliance
+with the License.  You may obtain a copy of the License at
+
+  http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing,
+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied.  See the License for the
+specific language governing permissions and limitations
+under the License.
+-->
+
+## Description
+
+Used to classify text into a specified set of labels.
+
+## Syntax
+
+```sql
+LLM_CLASSIFY([<resource_name>], <text>, <labels>)
+```
+
+## Parameters
+
+|    Parameter      | Description                                 |
+| ----------------- | ------------------------------------------- |
+| `<resource_name>` | The specified resource name, optional       |
+| `<text>`          | The text to be classified                   |
+| `<labels>`        | Array of classification labels              |
+
+## Return Value
+
+Returns the single label that best matches the text.
+
+If any input is NULL, returns NULL.
+
+The result is generated by a large language model, so the output may vary.
+
+## Examples
+
+```sql
+SET default_llm_resource = 'resource_name';
+SELECT LLM_CLASSIFY('Apache Doris is a databases system.', ['useage', 'introduce']) AS Result;
+```
+```text
++-----------+
+| Result    |
++-----------+
+| introduce |
++-----------+
+```
+
+```sql
+SELECT LLM_CLASSIFY('resource_name', 'Apache Doris is developing rapidly.', ['science', 'sport']) AS Result;
+```
+```text
++---------+
+| Result  |
++---------+
+| science |
++---------+
+```

docs/sql-manual/sql-functions/scalar-functions/llm-functions/llm-extract.md

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+---
+{
+    "title": "LLM_EXTRACT",
+    "language": "en"
+}
+---
+
+<!-- 
+Licensed to the Apache Software Foundation (ASF) under one
+or more contributor license agreements.  See the NOTICE file
+distributed with this work for additional information
+regarding copyright ownership.  The ASF licenses this file
+to you under the Apache License, Version 2.0 (the
+"License"); you may not use this file except in compliance
+with the License.  You may obtain a copy of the License at
+
+  http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing,
+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied.  See the License for the
+specific language governing permissions and limitations
+under the License.
+-->
+
+## Description
+
+Used to extract information corresponding to specific labels from text.
+
+## Syntax
+
+```sql
+LLM_EXTRACT([<resource_name>], <text>, <labels>)
+```
+
+## Parameters
+
+|    Parameter      | Description                                  |
+| ----------------- | -------------------------------------------- |
+| `<resource_name>` | The specified resource name, optional        |
+| `<text>`          | The text from which to extract information   |
+| `<labels>`        | Array of labels to extract                   |
+
+## Return Value
+
+Returns a string containing all extracted labels and their corresponding values.
+
+If any input is NULL, returns NULL.
+
+The result is generated by a large language model, so the output may vary.
+
+## Examples
+
+```sql
+SET default_llm_resource = 'resource_name';
+SELECT LLM_EXTRACT('Apache Doris is an MPP-based real-time data warehouse known for its high query speed.', 
+                  ['product_name', 'architecture', 'key_feature']) AS Result;
+```
+```text
++---------------------------------------------------------------------------------------+
+| Result                                                                                |
++---------------------------------------------------------------------------------------+
+| product_name="Apache Doris", architecture="MPP-based", key_feature="high query speed" |
++---------------------------------------------------------------------------------------+
+```
+
+```sql
+SELECT LLM_EXTRACT('resource_name', 'Apache Doris began in 2008 as an internal project named Palo.',
+                  ['original name', 'founding time']) AS Result;
+```
+```text
++----------------------------------------+
+| Result                                 |
++----------------------------------------+
+| original name=Palo, founding time=2008 |
++----------------------------------------+
+```

docs/sql-manual/sql-functions/scalar-functions/llm-functions/llm-fixgrammar.md

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+---
+{
+    "title": "LLM_FIXGRAMMAR",
+    "language": "en"
+}
+---
+
+<!-- 
+Licensed to the Apache Software Foundation (ASF) under one
+or more contributor license agreements.  See the NOTICE file
+distributed with this work for additional information
+regarding copyright ownership.  The ASF licenses this file
+to you under the Apache License, Version 2.0 (the
+"License"); you may not use this file except in compliance
+with the License.  You may obtain a copy of the License at
+
+  http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing,
+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied.  See the License for the
+specific language governing permissions and limitations
+under the License.
+-->
+
+## Description
+
+Used to correct grammatical errors in text.
+
+## Syntax
+
+```sql
+LLM_FIXGRAMMAR([<resource_name>], <text>)
+```
+
+## Parameters
+
+|    Parameter      | Description                                 |
+| ----------------- | ------------------------------------------- |
+| `<resource_name>` | The specified resource name, optional       |
+| `<text>`          | The text to be grammar-corrected            |
+
+## Return Value
+
+Returns the text string after grammar correction.
+
+If any input is NULL, returns NULL.
+
+The result is generated by a large language model, so the output may vary.
+
+## Examples
+
+```sql
+SET default_llm_resource = 'resource_name';
+SELECT LLM_FIXGRAMMAR('Apache Doris a great system DB') AS Result;
+```
+```text
++------------------------------------------+
+| Result                                   |
++------------------------------------------+
+| Apache Doris is a great database system. |
++------------------------------------------+
+```
+
+```sql
+SELECT LLM_FIXGRAMMAR('resource_name', 'I am like to using Doris') AS Result;
+```
+```text
++--------------------+
+| Result             |
++--------------------+
+| I like using Doris |
++--------------------+
+```

docs/sql-manual/sql-functions/scalar-functions/llm-functions/llm-function.md

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+---
+{
+    "title": "LLM_Function",
+    "language": "en"
+}
+---
+
+<!-- 
+Licensed to the Apache Software Foundation (ASF) under one
+or more contributor license agreements.  See the NOTICE file
+distributed with this work for additional information
+regarding copyright ownership.  The ASF licenses this file
+to you under the Apache License, Version 2.0 (the
+"License"); you may not use this file except in compliance
+with the License.  You may obtain a copy of the License at
+
+  http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing,
+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied.  See the License for the
+specific language governing permissions and limitations
+under the License.
+-->
+
+## Description
+
+LLM Function is a built-in function provided by Doris based on large language model (LLM) capabilities. Users can directly call LLM in SQL queries to perform various intelligent text tasks. LLM Function connects to multiple mainstream LLM providers (such as OpenAI, Anthropic, DeepSeek, Gemini, Ollama, MoonShot, etc.) through Doris's resource mechanism.
+
+The LLM used must be provided externally by Doris and support text analysis.
+
+---
+
+## Configure LLM Resource
+
+Before using LLM Function, you need to create a Resource of type LLM to centrally manage access information for the LLM API.
+
+### Example: Create LLM Resource
+
+```sql
+CREATE RESOURCE "llm_resource_name"
+PROPERTIES (
+    'type' = 'llm',
+    'llm.provider_type' = 'openai',
+    'llm.endpoint' = 'https://endpoint_example',
+    'llm.model_name' = 'model_example',
+    'llm.api_key' = 'sk-xxx',
+    'llm.temperature' = '0.7',
+    'llm.max_token' = '1024',
+    'llm.max_retries' = '3',
+    'llm.retry_delay_second' = '1'
+);
+ ```
+
+##### Parameter Description
+
+`type`: Required, must be `llm`, used as the type identifier for llm.
+
+`llm.provider_type`: Required, external LLM provider type. Currently supported providers include: OpenAI, Anthropic, Gemini, DeepSeek, Local, MoonShot, MiniMax, Zhipu, QWen, Baichuan. If there are providers not listed above but their API format is the same as [OpenAI](https://platform.openai.com/docs/overview)/[Anthropic](https://docs.anthropic.com/en/api/messages-examples)/[Gemini](https://ai.google.dev/gemini-api/docs/quickstart#rest_1), you can directly fill in the corresponding provider.
+
+`llm.endpoint`: Required, LLM API endpoint.
+
+`llm.model_name`: Required, model name.
+
+`llm_api_key`: Required except when `llm.provider_type = local`, API key.
+
+`llm.temperature`: Optional. Controls the randomness of generated content. Accepts a float value between 0 and 1. 
+The default value is -1, which means this parameter is not set.
+
+`llm.max_tokens`: Optional. Limits the maximum number of tokens for generated content. 
+The default value is -1, which means this parameter is not set. The default value for Anthropic is 2048.
+
+`llm.max_retries`: Optional. The maximum number of retries for a single request. The default value is 3.
+
+`llm.retry_delay_second`: Optional. The delay time (in seconds) before retrying. The default value is 0.
+
+---
+
+## Resource Selection and Session Variables
+
+When users call LLM-related functions, resources can be specified in the following two ways:
+
+- Explicitly specify the resource: directly pass the resource name when calling the function.
+- Implicitly specify the resource: set the Session variable in advance, and the function will automatically use the corresponding resource.
+
+Set Session variable format:
+```sql
+SET default_llm_resource='resource_name';
+```
+
+Function call format:
+```sql
+SELECT LLM_FUNCTION([<resource_name>], <args...>);
+```
+
+### Resource Selection Priority
+
+When calling an LLM_Function, it determines which resource to use in the following order:
+
+1. The resource explicitly specified by the user in the call
+2. The global default resource (`default_llm_resource`)
+
+Example:
+
+```sql
+SET default_llm_resource='global_default_resource';
+SELECT LLM_SENTIMENT('this is a test'); -- Uses resource named 'global_default_resource'
+SELECT LLM_SENTIMENT('invoke_resource', 'this is a test') --Uses resource named 'invoke_resource'
+```
+
+---
+
+## LLM Functions
+
+Currently supported LLM Functions in Doris include:
+
+- `LLM_CLASSIFY`: Information classification
+
+- `LLM_EXTRACT`: Information extraction
+
+- `LLM_FIXGRAMMAR`: Grammar correction
+
+- `LLM_GENERATE`: Text generation
+
+- `LLM_MASK`: Masking sensitive information
+
+- `LLM_SENTIMENT`: Sentiment analysis
+
+- `LLM_SUMMARIZE`: Text summarization
+
+- `LLM_TRANSLATE`: Translation
+
+### Examples
+
+1. `LLM_TRANSLATE`
+```sql
+SELECT LLM_TRANSLATE('resource_name', 'this is a test', 'Chinese');
+-- 这是一个测试
+```
+
+2. `LLM_SENTIMENT`
+```sql
+SET default_llm_resource = 'resource_name';
+SELECT LLM_SENTIMENT('Apache Doris is a great DBMS.');
+```
+
+For detailed function and usage, please refer to the documentation of each specific function.