# AI Functions ## Install AI Functions To install AI Functions, navigate to **AI > AI & ML Functions**, select the deployment on which to install AI Functions. In the **AI Functions** tab, select **Install**, review the **AI Functions Summary** and then select **Deploy**. Once the AI Functions are installed, query them in the SQL Editor or SingleStore notebooks. SingleStore provides the following AI Functions: | **Category** | **Function** | | --------------------------------------------------------------- | -------------------------- | | Text Processing Functions | `AI_COMPLETE(text, model)` | | `AI_SENTIMENT(text, model)` | | | `AI_TRANSLATE(text, source_languages, target_languages, model)` | | | `AI_SUMMARIZE(text, model, max_lengths)` | | | `AI_CLASSIFY(text, categories, model)` | | | `AI_EXTRACT(text, questions, model)` | | | Embedding Function | | | `EMBED_TEXT(text, model)` | | ## Edit AI Functions To edit AI Functions, navigate to **Settings** in the right navigation of the **AI Functions** tab and select **Edit**. Alternatively, select the ellipsis (vertical three dots) in the right and select **Edit AI Functions**. On the **Edit AI Functions** page, view or select the following: | **WorkspaceGroup** | Theworkspacegroup in which the AI Function is installed and running. | | ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Models** | Default models used by AI Functions for inference and embedding. | | **Settings** | | | **Cost Estimation** | View the cost estimation of LLM Model, Embedding Model, and Compute. In Compute, runtime cost scales with the replica count. | | **Region** | View the region of the following: | Select **Next**, review the changes, and select **Save** to save your settings. ## Uninstall AI Functions To uninstall AI Functions, select the ellipsis (vertical three dots) in the right and then select **Uninstall AI Functions**. Confirm the uninstallation and select **Uninstall**. ## Text Processing Functions ## AI\_COMPLETE Provides batched LLM powered completion of every input text. Used for general purpose text generation, completion, and complex reasoning. ## Syntax ```sql AI_COMPLETE(text, model) ``` ## Arguments * `text`: A prompt. * `model`: An LLM model. ## Return Type `string` ## Usage | Basic usage with the default model | `SELECT cluster.AI_COMPLETE('Life is like a box of') AS completion;` | | ---------------------------------- | ----------------------------------------------------------------------------------------------------------- | | Basic usage with a specific model | `SELECT cluster.AI_COMPLETE('Life is like a box of', model => 'anthropic-claude-3-5-haiku') as completion;` | | Input example on database | `SELECT cluster.AI_COMPLETE(column_1) FROM table;` | ## AI\_SENTIMENT Provides sentiment classification and score for all user-defined inputs. ## Syntax ```sql AI_SENTIMENT(text, model) ``` ## Arguments * `text`: A prompt. * `model`: An LLM model. ## Return Type `string` ## Usage | Basic usage with default model | `SELECT cluster.AI_SENTIMENT('The migration tool saved us hours, but the error messages were completely cryptic and we had to open three support tickets just to get past the setup.') AS sentiment;` | | ------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Basic usage with selected model | `SELECT cluster.AI_SENTIMENT('The migration tool saved us hours, but the error messages were completely cryptic and we had to open three support tickets just to get past the setup.', 'anthropic-claude-3-5-haiku') as sentiment;` | | Input example on database | `SELECT cluster.AI_SENTIMENT(column_1) FROM table;` | ## AI\_TRANSLATE Provides translation of user-provided documents from source language to target language. Supports multi-language translation. ## Syntax ```sql AI_TRANSLATE(text, source_languages, target_languages, model) ``` ## Arguments * `text`: A prompt. * `source_languages`: The language in which the prompt is written. * `target_languages`: The language to which the prompt gets translated. * `model`: An LLM model. ## Return Type `string` ## Usage | Basic usage with default model | `SELECT cluster.AI_TRANSLATE( '平素より大変お世話になっております。株式会社テクノソリューションズの田中と申します。先日よりご利用いただいておりますデータ移行サービスについて、 重大な問題が発生しておりますため、緊急のご連絡を差し上げております。昨日の午後3時頃より、移行ジョブが途中で停止し、エラーログには「接続タイムアウト」 と記録されております。弊社のシステム管理者が調査いたしましたが、原因の特定には至っておりません。本件は弊社の本番環境に影響を及ぼしており、 業務に支障をきたしております。至急、担当エンジニアよりご連絡いただけますようお願い申し上げます。何卒よろしくお願いいたします。','Japanese','English') AS translated_escalation;` | | ------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Basic usage with selected model | `SELECT cluster.AI_TRANSLATE('平素より大変お世話になっております。株式会社テクノソリューションズの田中と申します。 先日よりご利用いただいておりますデータ移行サービスについて、重大な問題が発生しておりますため、緊急のご連絡を差し上げております。 昨日の午後3時頃より、移行ジョブが途中で停止し、エラーログには「接続タイムアウト」と記録されております。弊社のシステム管理者が調査いたしましたが、 原因の特定には至っておりません。本件は弊社の本番環境に影響を及ぼしており、業務に支障をきたしております。至急、 担当エンジニアよりご連絡いただけますようお願い申し上げます。何卒よろしくお願いいたします。','Japanese','English', 'anthropic-claude-3-5-haiku') as translation;` | | Input example on database | `SELECT cluster.AI_TRANSLATE(column_1, "source_language", "target_language") FROM table;` | ## AI\_SUMMARIZE Provides summary of user-provided documents within the specified length. ## Syntax ```sql AI_SUMMARIZE(text, model, max_lengths) ``` ## Arguments * `text`: A prompt. * `model`: An LLM model. * `max_lengths`: Maximum length of the summary. ## Return Type `string` ## Usage | Basic usage with default model and length | `SELECT cluster.AI_SUMMARIZE( 'At 14:32 UTC, our monitoring system detected elevated error rates on the primary ingestion pipeline. The on-call engineer was paged at 14:35. Initial investigation pointed to a misconfigured rate limit introduced during the 14:00 deployment. A rollback was initiated at 14:50 and completed at 15:02. Error rates returned to baseline by 15:05. Total customer-facing impact: approximately 33 minutes of degraded write throughput.') AS incident_one_liner;` | | ----------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Basic usage with selected model | `SELECT cluster.AI_SUMMARIZE( 'At 14:32 UTC, our monitoring system detected elevated error rates on the primary ingestion pipeline. The on-call engineer was paged at 14:35. Initial investigation pointed to a misconfigured rate limit introduced during the 14:00 deployment. A rollback was initiated at 14:50 and completed at 15:02. Error rates returned to baseline by 15:05. Total customer-facing impact: approximately 33 minutes of degraded write throughput.','anthropic-claude-3-5-haiku',15) AS incident_one_liner;` | | Input example on database | `SELECT cluster.AI_SUMMARIZE(column_1) FROM table;` | ## AI\_CLASSIFY Provides classification of each input text into one of the given categories or labels. ## Syntax ```sql AI_CLASSIFY(text, categories, model) ``` ## Arguments * `text`: A prompt. * `categories`: Categories for classification. * `model`: An LLM model. ## Return Type `string` ## Usage | Basic usage with default model | `SELECT cluster.AI_CLASSIFY( 'Hi, I was charged twice for my subscription this month. I have already checked my payment history and both transactions are showing as completed.', '["billing", "technical_issue", "account_access", "feature_request", "abuse_report"]') AS assigned_queue;` | | ------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Basic usage with selected model | `SELECT cluster.AI_CLASSIFY( 'Hi, I was charged twice for my subscription this month. I have already checked my payment history and both transactions are showing as completed.', '["billing", "technical_issue", "account_access", "feature_request", "abuse_report"]','anthropic-claude-3-5-haiku') AS assigned_queue;` | | Input example on database | `SELECT cluster.AI_CLASSIFY(column_1, categories) FROM table;` | ## AI\_EXTRACT Extracts information from a block or text based on the specified natural language question. ## Syntax ```sql AI_EXTRACT(text, questions, model) ``` ## Arguments * `text`: A prompt. * `questions`: Input natural language question on which the LLM model extracts information. * `model`: An LLM model. ## Return Type `string` ## Usage | Basic usage with default model | `SELECT cluster.AI_EXTRACT( 'This Service Agreement is entered into on March 1, 2025 between Acme Corp and DataStream Inc. The total contract value is $240,000 USD, payable in quarterly installments. The agreement expires on February 28, 2027, with a 60-day written notice required for termination.', 'What is the contract expiration date?' ) AS expiration_date, cluster.AI_EXTRACT( 'This Service Agreement is entered into on March 1, 2025 between Acme Corp and DataStream Inc. The total contract value is $240,000 USD, payable in quarterly installments. The agreement expires on February 28, 2027, with a 60-day written notice required for termination.', 'What is the total contract value?' ) AS contract_value, cluster.AI_EXTRACT( 'This Service Agreement is entered into on March 1, 2025 between Acme Corp and DataStream Inc. The total contract value is $240,000 USD, payable in quarterly installments. The agreement expires on February 28, 2027, with a 60-day written notice required for termination.', 'How many days notice is required for termination?' ) AS termination_notice;` | | ------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Basic usage with selected model | `SELECT cluster.AI_EXTRACT( 'This Service Agreement is entered into on March 1, 2025 between Acme Corp and DataStream Inc. The total contract value is $240,000 USD, payable in quarterly installments. The agreement expires on February 28, 2027, with a 60-day written notice required for termination.', 'What is the contract expiration date?' ) AS expiration_date, cluster.AI_EXTRACT( 'This Service Agreement is entered into on March 1, 2025 between Acme Corp and DataStream Inc. The total contract value is $240,000 USD, payable in quarterly installments. The agreement expires on February 28, 2027, with a 60-day written notice required for termination.', 'What is the total contract value?' ) AS contract_value, cluster.AI_EXTRACT( 'This Service Agreement is entered into on March 1, 2025 between Acme Corp and DataStream Inc. The total contract value is $240,000 USD, payable in quarterly installments. The agreement expires on February 28, 2027, with a 60-day written notice required for termination.', 'How many days notice is required for termination?', 'anthropic-claude-3-5-haiku' ) AS termination_notice;` | | Input example on database | `SELECT cluster.AI_EXTRACT(column_1, question) FROM table;` | ## Embedding Function ## EMBED\_TEXT Provides batched embeddings of all input text. Converts text into high-dimensional vector embeddings for semantic search and RAG applications. ## Syntax ```sql EMBED_TEXT(text, model) ``` ## Arguments * `text`: A prompt. * `model`: An embedding model. ## Return Type `bytes` ## Usage | Basic usage with default model | `SELECT cluster.EMBED_TEXT('Lightweight running shoes with breathable mesh fabric, cushioned soles, and flexible support designed for daily workouts and long-distance comfort.') AS embedding;` | | ----------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Basic usage with selected embedding model | `SELECT cluster.EMBED_TEXT('Lightweight running shoes with breathable mesh fabric, cushioned soles, and flexible support designed for daily workouts and long-distance comfort.', 'shared-qwen3-embed-0-6b') as embedding;` | | Input example on database | `SELECT cluster.EMBED_TEXT(column_1) FROM table;` | ## Examples The following examples demonstrate how to use AI functions with the following `customer_reviews` table. ```sql CREATE DATABASE reviews; USE reviews; CREATE TABLE customer_reviews ( review_id INT PRIMARY KEY, product_id VARCHAR(50), product_name VARCHAR(255), customer_name VARCHAR(100), review_text TEXT, rating INT, review_date DATETIME, language VARCHAR(20) DEFAULT 'English', response_text TEXT, review_embedding BLOB ); -- Insert data INSERT INTO customer_reviews ( review_id, product_id, product_name, customer_name, review_text, rating, review_date, language ) VALUES (1, 'PROD-101', 'Wireless Headphones', 'John Smith', 'These headphones are amazing! The sound quality is crystal clear and the battery lasts for days. Highly recommend for anyone looking for quality audio.', 5, '2026-05-01', 'English'), (2, 'PROD-101', 'Wireless Headphones', 'Maria Garcia', 'Disappointed with the build quality. They broke after just two weeks of normal use. Customer service was unhelpful.', 1, '2026-05-02', 'English'), (3, 'PROD-102', 'Smart Watch', 'David Lee', 'Great fitness tracker, but the battery life is shorter than advertised. Overall, good value for the price.', 4, '2026-05-03', 'English'), (4, 'PROD-101', 'Wireless Headphones', 'Sophie Martin', 'Excellente qualité sonore! Je les utilise tous les jours pour le travail et les loisirs.', 5, '2026-05-04', 'French'), (5, 'PROD-103', 'Laptop Stand', 'Ahmed Hassan', 'Perfect ergonomic solution for my home office. Sturdy construction and adjustable height. Worth every penny.', 5, '2026-05-05', 'English'); ``` ## Generate Follow-up Questions for Negative Reviews The following example uses the `AI_COMPLETE` function to generate follow-up questions for negative reviews: ```sql SELECT review_id, customer_name, product_name, review_text, cluster.AI_COMPLETE( CONCAT( 'Based on this negative review: "', review_text, '", generate three specific follow-up questions to better understand the issue.' ) ) AS follow_up_questions FROM customer_reviews WHERE rating <= 2; ``` ```output +-----------+----------------+----------------------+--------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | review_id | customer_name | product_name | review_text | follow_up_questions | +-----------+----------------+----------------------+--------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | 2 | Maria Garcia | Wireless Headphones | Disappointed with the build quality. They broke after just | 1. Can you describe exactly how the product broke and in what specific way? | | | | | two weeks of normal use. Customer service was unhelpful. | 2. Did you contact customer service through phone, email, or another method, and what precisely did they say that made you feel they were unhelpful? | | | | | | 3. What type of normal use were you subjecting the product to when it broke? | +-----------+----------------+----------------------+--------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ ``` ## Compare Customer Ratings with AI Sentiment The following example uses the `AI_SENTIMENT` function to compare customer ratings with AI-generated sentiment analysis: ```sql SELECT review_id, customer_name, product_name, rating AS star_rating, review_text, cluster.AI_SENTIMENT(review_text) AS ai_sentiment FROM customer_reviews ORDER BY review_date DESC; ``` ```output +-----------+----------------+----------------------+-------------+---------------------------------------------------------------------------------------------------------------------+----------------------------------------------+ | review_id | customer_name | product_name | star_rating | review_text | ai_sentiment | +-----------+----------------+----------------------+-------------+---------------------------------------------------------------------------------------------------------------------+----------------------------------------------+ | 3 | David Lee | Smart Watch | 4 | Great fitness tracker, but the battery life is shorter than advertised. Overall, good value for the price. | {'sentiment': 'neutral', 'score': '0.5'} | | 1 | John Smith | Wireless Headphones | 5 | These headphones are amazing! The sound quality is crystal clear and the battery lasts for days. | {'sentiment': 'positive', 'score': '0.9'} | | 5 | Ahmed Hassan | Laptop Stand | 5 | Perfect ergonomic solution for my home office. Sturdy construction and adjustable height. Worth every penny. | {'sentiment': 'positive', 'score': '0.95'} | | 4 | Sophie Martin | Wireless Headphones | 5 | Excellente qualité sonore! Je les utilise tous les jours pour le travail et les loisirs. | {'sentiment': 'positive', 'score': '0.90'} | | 2 | Maria Garcia | Wireless Headphones | 1 | Disappointed with the build quality. They broke after just two weeks of normal use. Customer service was unhelpful. | {'sentiment': 'negative', 'score': '0.85'} | +-----------+----------------+----------------------+-------------+---------------------------------------------------------------------------------------------------------------------+----------------------------------------------+ ``` ## Standardize Reviews in English The following example uses the `AI_TRANSLATE` function to standardize the reviews in English language: ```sql SELECT review_id, customer_name, product_name, language AS original_language, review_text AS original_review, CASE WHEN language = 'English' THEN review_text ELSE cluster.AI_TRANSLATE( review_text, language, 'English' ) END AS standardized_review_english FROM customer_reviews ORDER BY review_date DESC; ``` ```output +-----------+----------------+----------------------+-------------------+---------------------------------------------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------+ | review_id | customer_name | product_name | original_language | original_review | standardized_review_english | +-----------+----------------+----------------------+-------------------+---------------------------------------------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------+ | 3 | David Lee | Smart Watch | English | Great fitness tracker, but the battery life is shorter than advertised. Overall, good value for the price. | Great fitness tracker, but the battery life is shorter than advertised. Overall, good value for the price. | | 1 | John Smith | Wireless Headphones | English | These headphones are amazing! The sound quality is crystal clear and the battery lasts for days. | These headphones are amazing! The sound quality is crystal clear and the battery lasts for days. | | 5 | Ahmed Hassan | Laptop Stand | English | Perfect ergonomic solution for my home office. Sturdy construction and adjustable height. Worth every penny. | Perfect ergonomic solution for my home office. Sturdy construction and adjustable height. Worth every penny. | | 4 | Sophie Martin | Wireless Headphones | French | Excellente qualité sonore! Je les utilise tous les jours pour le travail et les loisirs. | Excellent sound quality! I use them every day for work and leisure. | | 2 | Maria Garcia | Wireless Headphones | English | Disappointed with the build quality. They broke after just two weeks of normal use. Customer service was unhelpful. | Disappointed with the build quality. They broke after just two weeks of normal use. Customer service was unhelpful. | +-----------+----------------+----------------------+-------------------+---------------------------------------------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------+ ``` ## Generate Product-Level Summaries The following example uses the `AI_SUMMARIZE` function to generate product-level summaries from customer reviews: ```sql SELECT product_id, product_name, COUNT(*) AS review_count, AVG(rating) AS avg_rating, cluster.AI_SUMMARIZE( GROUP_CONCAT(review_text SEPARATOR '. ') ) AS product_summary FROM customer_reviews GROUP BY product_id, product_name; ``` ```output +------------+----------------------+--------------+------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | product_id | product_name | review_count | avg_rating | product_summary | +------------+----------------------+--------------+------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | PROD-103 | Laptop Stand | 1 | 5.0000 | Excellent ergonomic home office solution with sturdy construction and adjustable height, providing good value. | | PROD-101 | Wireless Headphones | 3 | 3.6667 | Mixed reviews for headphones: praised for excellent sound quality and long battery life, but criticized for poor durability and potential customer service issues.| | PROD-102 | Smart Watch | 1 | 4.0000 | Fitness tracker offers good value, though battery life is shorter than expected. | +------------+----------------------+--------------+------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------+ ``` ## Classify Review Intent The following example uses the `AI_CLASSIFY` function to classify the review intent: ```sql SELECT review_id, customer_name, product_name, rating, review_text, cluster.AI_CLASSIFY( review_text, '[praise, complaint, suggestion, question, comparison]' ) AS review_intent FROM customer_reviews ORDER BY review_date DESC; ``` ```output +-----------+----------------+----------------------+--------+---------------------------------------------------------------------------------------------------------------------+---------------+ | review_id | customer_name | product_name | rating | review_text | review_intent | +-----------+----------------+----------------------+--------+---------------------------------------------------------------------------------------------------------------------+---------------+ | 3 | David Lee | Smart Watch | 4 | Great fitness tracker, but the battery life is shorter than advertised. Overall, good value for the price. | complaint | | 1 | John Smith | Wireless Headphones | 5 | These headphones are amazing! The sound quality is crystal clear and the battery lasts for days. | praise | | 5 | Ahmed Hassan | Laptop Stand | 5 | Perfect ergonomic solution for my home office. Sturdy construction and adjustable height. Worth every penny. | praise | | 4 | Sophie Martin | Wireless Headphones | 5 | Excellente qualité sonore! Je les utilise tous les jours pour le travail et les loisirs. | praise | | 2 | Maria Garcia | Wireless Headphones | 1 | Disappointed with the build quality. They broke after just two weeks of normal use. Customer service was unhelpful. | complaint | +-----------+----------------+----------------------+--------+---------------------------------------------------------------------------------------------------------------------+---------------+ ``` ## Extract Multiple Insights The following example uses the `AI_EXTRACT` function to extract multiple insights from customer reviews: ```sql SELECT review_id, product_name, review_text, cluster.AI_EXTRACT( review_text, 'What product features are mentioned?' ) AS features_mentioned, cluster.AI_EXTRACT( review_text, 'How long has the customer used this product?' ) AS usage_duration FROM customer_reviews; ``` ```output +-----------+----------------------+--------------------------------------------------------------------------------------------------------------+---------------------------------------------------------------+-----------------------------+ | review_id | product_name | review_text | features_mentioned | usage_duration | +-----------+----------------------+--------------------------------------------------------------------------------------------------------------+---------------------------------------------------------------+-----------------------------+ | 5 | Laptop Stand | Perfect ergonomic solution for my home office. Sturdy construction and adjustable height. Worth every penny. | Sturdy construction, adjustable height | Not specified in the review | | 2 | Wireless Headphones | Disappointed with the build quality. They broke after just two weeks of normal use. Customer service | Build quality issues, broke after two weeks was unhelpful. | Two weeks | | 4 | Wireless Headphones | Excellente qualité sonore! Je les utilise tous les jours pour le travail et les loisirs. | Sound quality | Daily (ongoing) | | 3 | Smart Watch | Great fitness tracker, but the battery life is shorter than advertised. Overall, good value for the price. | Battery life (shorter than advertised), good value for price. | Not specified in the review | | 1 | Wireless Headphones | These headphones are amazing! The sound quality is crystal clear and the battery lasts for days. | Sound quality (crystal clear), long battery life | Not specified in the review | +-----------+----------------------+--------------------------------------------------------------------------------------------------------------+---------------------------------------------------------------+-----------------------------+ ``` ## Perform Semantic Search The following example uses the `EMBED_TEXT` function to perform semantic search on customer reviews. ```sql SET batch_external_functions = AUTO; SELECT review_id, product_name, review_text, cluster.EMBED_TEXT(review_text) AS review_embedding FROM customer_reviews; UPDATE customer_reviews SET review_embedding = cluster.EMBED_TEXT(review_text) WHERE review_embedding IS NULL; WITH search_query AS ( SELECT cluster.EMBED_TEXT( 'battery problems and short lifespan' ) AS query_embedding ) SELECT cr.review_id, cr.product_name, cr.review_text, cr.rating, DOT_PRODUCT( cr.review_embedding, sq.query_embedding ) AS relevance_score FROM customer_reviews cr, search_query sq WHERE cr.review_embedding IS NOT NULL ORDER BY relevance_score DESC; ``` ```output +-----------+---------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------+--------+-----------------+ | review_id | product_name | review_text | rating | relevance_score | +-----------+---------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------+--------+-----------------+ | 3 | Smart Watch | Great fitness tracker, but the battery life is shorter than advertised. Overall, good value for the price. | 4 | NULL | | 1 | Wireless Headphones | These headphones are amazing! The sound quality is crystal clear and the battery lasts for days. Highly recommend for anyone looking for quality audio.| 5 | NULL | | 2 | Wireless Headphones | Disappointed with the build quality. They broke after just two weeks of normal use. Customer service was unhelpful. | 1 | NULL | | 4 | Wireless Headphones | Excellente qualité sonore! Je les utilise tous les jours pour le travail et les loisirs. | 5 | NULL | | 5 | Laptop Stand | Perfect ergonomic solution for my home office. Sturdy construction and adjustable height. Worth every penny. | 5 | NULL | +-----------+---------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------+--------+-----------------+ ``` ## Complete Customer Insights The following example uses the `AI_SUMMARIZE` and `AI_EXTRACT` functions to generate complete customer insights for each product: ```sql SELECT product_id, product_name, COUNT(*) AS total_reviews, AVG(rating) AS avg_rating, cluster.AI_SUMMARIZE( GROUP_CONCAT(review_text SEPARATOR '. ') ) AS overview, cluster.AI_EXTRACT( GROUP_CONCAT(review_text SEPARATOR '. '), 'What are the top three issues customers mention?' ) AS top_issues, cluster.AI_EXTRACT( GROUP_CONCAT(review_text SEPARATOR '. '), 'What do customers love most about this product?' ) AS top_strengths FROM customer_reviews GROUP BY product_id, product_name; ``` ```output +------------+----------------------+---------------+------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------+---------------------------------------------+ | product_id | product_name | total_reviews | avg_rating | overview | top_issues | top_strengths | +------------+----------------------+---------------+------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------+---------------------------------------------+ | PROD-103 | Laptop Stand | 1 | 5.0000 | Excellent ergonomic home office solution with sturdy construction and adjustable height, providing good value. | 1. Sturdy construction 2. Adjustable height 3. Good value for money | Sturdy construction and adjustable height | | PROD-101 | Wireless Headphones | 3 | 3.6667 | Mixed reviews for headphones: praised for excellent sound quality and long battery life, but criticized for poor durability and potential customer service issues. | 1. Sound quality 2. Battery life 3. Build quality (durability) | Sound quality and battery life | | | | PROD-102 | Smart Watch | 1 | 4.0000 | Fitness tracker offers good value, though battery life is shorter than expected. | 1. Battery life 2. Price 3. Functionality | Good value for the price | +------------+----------------------+---------------+------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------+---------------------------------------------+ ``` ## Example Notebook The following notebook demonstrates AI Functions: ## Usage Recommendations for AI Functions To optimize performance and control costs when using AI Functions, SingleStore recommends the following: * Use Common Table Expressions (CTEs) to filter rows before making calls to large language models (LLMs). The query engine currently sends data to the LLM before applying LLM or `WHERE` filters. * LLM calls are expensive. Begin with a small dataset to evaluate response quality and verify the results meet the requirements before scaling up. * Enterprise plans support three model providers; Aura, Amazon Bedrock, and Azure AI Services. Data is processed according to each provider’s policies. If a row violates provider rules, the system fails the batch that includes the row and returns errors for these rows. * Strict usage quotas apply per model and per organization. These quotas are not configurable by end users. For higher usage limits, contact [SingleStore Support](https://support.singlestore.com/). Self-service quota configuration will be available in the future. *** Modified at: May 22, 2026 Source: [/cloud/ai/ai-ml-functions/ai-functions/](https://docs.singlestore.com/cloud/ai/ai-ml-functions/ai-functions/) (An index of the documentation is available at /llms.txt)