wehub-resource-sync
e04ed9c211
CF: Deploy Dev Docs / deploy (push) Has been cancelled
Sync Labels / build (push) Has been cancelled
tests / unit tests (macos-latest) (push) Has been cancelled
tests / unit tests (windows-latest) (push) Has been cancelled
tests / unit tests (ubuntu-latest) (push) Has been cancelled
73 lines
4.8 KiB
Markdown
73 lines
4.8 KiB
Markdown
---
|
|
title: "vector-assist-define-spec"
|
|
type: docs
|
|
weight: 1
|
|
description: >
|
|
The "vector-assist-define-spec" tool defines a new vector specification by
|
|
capturing the user's intent and requirements for a vector search workload,
|
|
generating SQL recommendations for setting up database, embeddings, and
|
|
vector indexes.
|
|
---
|
|
|
|
## About
|
|
|
|
The `vector-assist-define-spec` tool defines a new vector specification by capturing the user's intent and requirements for a vector search workload. It generates a complete, ordered set of SQL recommendations required to set up the database, embeddings, and vector indexes.
|
|
|
|
Use this tool at the very beginning of the vector setup process when an agent or user first wants to configure a table for vector search, generate embeddings, or create a new vector index. Under the hood, this tool connects to the target database and executes the `vector_assist.define_spec` function to generate the necessary specifications.
|
|
|
|
## Compatible Sources
|
|
|
|
{{< compatible-sources >}}
|
|
|
|
## Requirements
|
|
|
|
{{< notice tip >}}
|
|
Ensure that your target PostgreSQL database has the required `vector_assist` extension installed, in order for this tool to execute successfully.
|
|
{{< /notice >}}
|
|
|
|
## Parameters
|
|
|
|
The tool takes the following input parameters:
|
|
|
|
| Parameter | Type | Description | Required |
|
|
| :----------------------- | :------ | :--------------------------------------------------------------------- | :------- |
|
|
| `table_name` | string | Target table name for setting up the vector workload. | Yes |
|
|
| `schema_name` | string | Name of the schema containing the target table. | No |
|
|
| `spec_id` | string | Unique ID for the vector specification; auto-generated if omitted. | No |
|
|
| `vector_column_name` | string | Name of the column containing the vector embeddings. | No |
|
|
| `text_column_name` | string | Name of the text column for setting up vector search. | No |
|
|
| `vector_index_type` | string | Type of vector index ('hnsw', 'ivfflat', or 'scann'). | No |
|
|
| `embeddings_available` | boolean | Indicates if vector embeddings already exist in the table. | No |
|
|
| `num_vectors` | integer | Expected total number of vectors in the dataset. | No |
|
|
| `dimensionality` | integer | Dimension of existing vectors or the chosen embedding model. | No |
|
|
| `embedding_model` | string | Model to be used for generating vector embeddings. | No |
|
|
| `prefilter_column_names` | array | List of columns to use for prefiltering vector queries. | No |
|
|
| `distance_func` | string | Distance function for comparing vectors ('cosine', 'ip', 'l2', 'l1'). | No |
|
|
| `quantization` | string | Quantization method for vector indexes ('none', 'halfvec', 'bit'). | No |
|
|
| `memory_budget_kb` | integer | Maximum memory (in KB) the index can use during build. | No |
|
|
| `target_recall` | float | Target recall rate for standard vector queries using this index. | No |
|
|
| `target_top_k` | integer | Number of top results (top-K) to retrieve per query. | No |
|
|
| `tune_vector_index` | boolean | Indicates whether automatic tuning is required for the index. | No |
|
|
|
|
> Note
|
|
> Parameters are marked as required or optional based on the vector assist function definitions.
|
|
> The function may perform further validation on optional parameters to ensure all necessary
|
|
> data is available before returning a response.
|
|
|
|
## Example
|
|
|
|
```yaml
|
|
kind: tool
|
|
name: define_spec
|
|
type: vector-assist-define-spec
|
|
source: my-database-source
|
|
description: "This tool defines a new vector specification by capturing the user's intent and requirements for a vector search workload. This generates a complete, ordered set of SQL recommendations required to set up the database, embeddings, and vector indexes. Use this tool at the very beginning of the vector setup process when a user first wants to configure a table for vector search, generate embeddings, or create a new vector index."
|
|
```
|
|
|
|
## Reference
|
|
|
|
| **field** | **type** | **required** | **description** |
|
|
|-------------|:--------:|:------------:|------------------------------------------------------|
|
|
| type | string | true | Must be "vector-assist-define-spec". |
|
|
| source | string | true | Name of the source the SQL should execute on. |
|
|
| description | string | false | Description of the tool that is passed to the agent. | |