Gemini Embeddings

This document describes how to use Gemini embedding models with Auto Embedding in TiDB Cloud to perform semantic searches from text queries.

Note

Currently, Auto Embedding is only available on TiDB Cloud Starter clusters in the following AWS regions:

Frankfurt (eu-central-1)
Oregon (us-west-2)
N. Virginia (us-east-1)

Available models

All Gemini models are available for use with the gemini/ prefix if you bring your own Gemini API key (BYOK). For example:

gemini-embedding-001

Name: gemini/gemini-embedding-001
Dimensions: 128–3072 (default: 3072)
Distance metric: Cosine, L2
Maximum input text tokens: 2,048
Price: Charged by Google
Hosted by TiDB Cloud: ❌
Bring Your Own Key: ✅

For a full list of available models, see Gemini documentation.

SQL usage example

To use Gemini models, you must specify a Gemini API key as follows:

Note

Replace 'your-gemini-api-key-here' with your actual Gemini API key.

SET @@GLOBAL.TIDB_EXP_EMBED_GEMINI_API_KEY = 'your-gemini-api-key-here';

CREATE TABLE sample (
  `id`        INT,
  `content`   TEXT,
  `embedding` VECTOR(3072) GENERATED ALWAYS AS (EMBED_TEXT(
                "gemini/gemini-embedding-001",
                `content`
              )) STORED
);

INSERT INTO sample
    (`id`, `content`)
VALUES
    (1, "Java: Object-oriented language for cross-platform development."),
    (2, "Java coffee: Bold Indonesian beans with low acidity."),
    (3, "Java island: Densely populated, home to Jakarta."),
    (4, "Java's syntax is used in Android apps."),
    (5, "Dark roast Java beans enhance espresso blends.");


SELECT `id`, `content` FROM sample
ORDER BY
  VEC_EMBED_COSINE_DISTANCE(
    embedding,
    "How to start learning Java programming?"
  )
LIMIT 2;

Result:

+------+----------------------------------------------------------------+
| id   | content                                                        |
+------+----------------------------------------------------------------+
|    1 | Java: Object-oriented language for cross-platform development. |
|    4 | Java's syntax is used in Android apps.                         |
+------+----------------------------------------------------------------+

Options

All Gemini options are supported via the additional_json_options parameter of the EMBED_TEXT() function.

Example: Specify the task type to improve quality

CREATE TABLE sample (
  `id`        INT,
  `content`   TEXT,
  `embedding` VECTOR(1024) GENERATED ALWAYS AS (EMBED_TEXT(
                "gemini/gemini-embedding-001",
                `content`,
                '{"task_type": "SEMANTIC_SIMILARITY"}'
              )) STORED
);

Example: Use an alternative dimension

CREATE TABLE sample (
  `id`        INT,
  `content`   TEXT,
  `embedding` VECTOR(768) GENERATED ALWAYS AS (EMBED_TEXT(
                "gemini/gemini-embedding-001",
                `content`,
                '{"output_dimensionality": 768}'
              )) STORED
);

For all available options, see Gemini documentation.

Python usage example

See PyTiDB Documentation.