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This PR introduces a significant update to the Toolbox configuration file format, which is one of the primary **breaking changes** required for the implementation of the Advanced Control Plane. # Summary of Changes The configuration schema has been updated to enforce resource isolation and facilitate atomic, incremental updates. * Resource Isolation: Resource definitions are now separated into individual blocks, using a distinct structure for each resource type (Source, Tool, Toolset, etc.). This improves readability, management, and auditing of configuration files. * Field Name Modification: Internal field names have been modified to align with declarative methodologies. Specifically, the configuration now separates kind (general resource type, e.g., Source) from type (specific implementation, e.g., Postgres). # User Impact Existing tools.yaml configuration files are now in an outdated format. Users must eventually update their files to the new YAML format. # Mitigation & Compatibility Backward compatibility is maintained during this transition to ensure no immediate user action is required for existing files. * Immediate Backward Compatibility: The source code includes a pre-processing layer that automatically detects outdated configuration files (v1 format) and converts them to the new v2 format under the hood. * [COMING SOON] Migration Support: The new toolbox migrate subcommand will be introduced to allow users to automatically convert their old configuration files to the latest format. # Example Example for config file v2: ``` kind: sources name: my-pg-instance type: cloud-sql-postgres project: my-project region: my-region instance: my-instance database: my_db user: my_user password: my_pass --- kind: authServices name: my-google-auth type: google clientId: testing-id --- kind: tools name: example_tool type: postgres-sql source: my-pg-instance description: some description statement: SELECT * FROM SQL_STATEMENT; parameters: - name: country type: string description: some description --- kind: tools name: example_tool_2 type: postgres-sql source: my-pg-instance description: returning the number one statement: SELECT 1; --- kind: toolsets name: example_toolset tools: - example_tool ``` --------- Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> Co-authored-by: Averi Kitsch <akitsch@google.com>
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title, type, weight, description
| title | type | weight | description |
|---|---|---|---|
| Gemini Embedding | docs | 1 | Use Google's Gemini models to generate high-performance text embeddings for vector databases. |
About
Google Gemini provides state-of-the-art embedding models that convert text into high-dimensional vectors.
Authentication
Toolbox uses your Application Default Credentials (ADC) to authorize with the Gemini API client.
Optionally, you can use an API key obtain an API Key from the Google AI Studio.
We recommend using an API key for testing and using application default credentials for production.
Behavior
Automatic Vectorization
When a tool parameter is configured with embeddedBy: <your-gemini-model-name>,
the Toolbox intercepts the raw text input from the client and sends it to the
Gemini API. The resulting numerical array is then formatted before being passed
to your database source.
Dimension Matching
The dimension field must match the expected size of your database column
(e.g., a vector(768) column in PostgreSQL). This setting is supported by newer
models since 2024 only. You cannot set this value if using the earlier model
(models/embedding-001). Check out available Gemini models for more
information.
Example
kind: embeddingModels
name: gemini-model
type: gemini
model: gemini-embedding-001
apiKey: ${GOOGLE_API_KEY}
dimension: 768
{{< notice tip >}} Use environment variable replacement with the format ${ENV_NAME} instead of hardcoding your secrets into the configuration file. {{< /notice >}}
Reference
| field | type | required | description |
|---|---|---|---|
| type | string | true | Must be gemini. |
| model | string | true | The Gemini model ID to use (e.g., gemini-embedding-001). |
| apiKey | string | false | Your API Key from Google AI Studio. |
| dimension | integer | false | The number of dimensions in the output vector (e.g., 768). |