openai_tokenize()

Convert text into tokens for token counting and API cost estimation

Convert text into an array of token IDs using OpenAI’s tokenization algorithm. This is useful for counting tokens to estimate API costs, stay within model limits, and understand how your text is processed.

Samples

Tokenize text

Convert a string into tokens:

SELECT ai.openai_tokenize(
    'text-embedding-ada-002',
    'Timescale is Postgres made Powerful'
);

Returns:

          openai_tokenize
----------------------------------------
 {19422,2296,374,3962,18297,1903,75458}

Count tokens

Determine how many tokens a text will use:

SELECT array_length(
    ai.openai_tokenize(
        'text-embedding-ada-002',
        'Timescale is Postgres made Powerful'
    ),
    1
) AS token_count;

Returns:

 token_count
-------------
           7

Check token count before API call

Ensure your text fits within model limits:

SELECT
    content,
    array_length(ai.openai_tokenize('gpt-4o-mini', content), 1) AS tokens
FROM documents
WHERE array_length(ai.openai_tokenize('gpt-4o-mini', content), 1) > 8000;

Arguments

Name	Type	Default	Required	Description
model	TEXT	-	✔	The OpenAI model to tokenize for (e.g., text-embedding-ada-002, gpt-4o)
text_input	TEXT	-	✔	The text to convert into tokens

Returns

INT[]: An array of token IDs representing the input text.

Related functions

• openai_detokenize(): convert tokens back into text
• openai_embed(): generate embeddings from text or tokens
• openai_chat_complete(): use tokens for completion