semantic.ai_dimensions_mismatch: Vector type an embedding is asked for as has a length other than embedding_dimensions:

Vector type an embedding is asked for as has a length other than embedding_dimensions:.

Area 21, AI; not declinable; the next step is usually the agent's.

ai.embed's as: names a vector type with as many dimensions: as embedding_dimensions: says the model makes, so a model change that alters the length is caught before a column holds two kinds of vector.

example

application {    connections: {        local_model: {            driver: Driver.openai_compatible            url: config.model_url        }    }    ai: {        connection: local_model        models: {            default: config.drafting_model            embedding: config.search_model        }        embedding_dimensions: 1536        limits: {            per_day: {                tokens: 2000000            }        }    }}

example

/// A help article's meaning, as the older embedding model made it.type ArticleMeaning = Vector {    dimensions: 768}

example

use support/types { ArticleMeaning }use support/failures { EmbeddingDelayed }/// A help article's meaning, from its text.action meaning_of_article(body: Markdown) fails EmbeddingDelayed -> ArticleMeaning {    return attempt ai.embed(body, as: ArticleMeaning) {        timed_out: EmbeddingDelayed        over_budget: EmbeddingDelayed        too_long: EmbeddingDelayed    }}

text

error: `ArticleMeaning` has 768 dimensions, and the model makes 1,536 --> domains/support/actions/meaning_of_article.jadpo:6:39  |6 |     return attempt ai.embed(body, as: ArticleMeaning) {  |                                       ^^^^^^^^^^^^^^ 768 dimensions, not 1,536  reason: Each embedding the model makes has the 1,536 numbers `ai:`'s `embedding_dimensions:` says, and `ArticleMeaning` holds vectors of 768, so a column of it would hold two kinds of vector.  next: Give `ArticleMeaning` `dimensions: 1536`, or set `embedding_dimensions: 768` in `ai:` if the model makes vectors that long (agent)  rule: semantic.ai_dimensions_mismatch  help: https://jadpo.dev/docs/errors/semantic.ai_dimensions_mismatchcheck failed: 1 error, 5 files