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https://dev.mysql.com/doc/refman/8.4/en/create-table.html
| {FULLTEXT | SPATIAL} [INDEX | KEY] [index_name] (key_part,...) [index_option] ... | [CONSTRAINT [symbol]] UNIQUE [INDEX | KEY] [index_name] [index_type] (key_part,...) [index_option] ... (Some valid select or union statement) CREATE TABLE creates ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-genai-generate-embeddings.html
This section describes how to generate vector embeddings using the ML_EMBED_ROW MySQL HeatWave GenAI routine. Vector embeddings are a numerical representation of the text that capture the semantics of the data and relationships to other data. You ...
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-genai-generate-embeddings.html
This section describes how to generate vector embeddings using the ML_EMBED_ROW routine. Vector embeddings are a numerical representation of the text that capture the semantics of the data and relationships to other data. You can pass the text ...
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-genai-summarize-content.html
The following sections in this topic describe how to summarize exiting content using the GenAI: Before You Begin Summarizing Content Running Batch Queries What's Next Before You Begin Review the GenAI requirements and privileges. For Running Batch ...
https://dev.mysql.com/doc/workbench/en/wb-model-reporting.html
The DBDoc - Model Reporting dialog is found by opening a model, selecting Model from the menu, and then DBDoc - Model Reporting. Note This functionality is only available in the MySQL Workbench Commercial Editions. Use the DBDoc- Model Reporting ...
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-genai-rag.html
The ML_RAG routine runs retrieval-augmented generation which aims to generate more accurate responses for your queries. For context retrieval, the ML_RAG routine uses the name of the embedding model used to embed the input query to find relevant ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-genai-supported-models.html
This topic provides the list of languages that MySQL HeatWave GenAI supports and the embedding models as well as large language models (LLMs) that are available in MySQL HeatWave. This topic contains the following sections: Before You Begin View ...
https://dev.mysql.com/doc/refman/8.4/en/string-type-syntax.html
The string data types are CHAR, VARCHAR, BINARY, VARBINARY, BLOB, TEXT, ENUM, and SET. In some cases, MySQL may change a string column to a type different from that given in a CREATE TABLE or ALTER TABLE statement. For definitions of character ...
https://dev.mysql.com/doc/heatwave/en/mys-hw-genai-rag.html
The ML_RAG routine runs retrieval-augmented generation which aims to generate more accurate responses for your queries. As of MySQL 9.2.1, for context retrieval, the ML_RAG routine uses the name of the embedding model used to embed the input query ...
https://dev.mysql.com/doc/heatwave/en/mys-hwgenai-ml-embed-row.html
The ML_EMBED_ROW routine uses the specified embedding model to encode the specified text or query into a vector embedding. The routine returns a VECTOR that contains a numerical representation of the specified text. This topic contains the ...