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First part of the implementation to support semantic search in tools. Second part: https://github.com/googleapis/genai-toolbox/pull/2151
74 lines
2.5 KiB
Markdown
74 lines
2.5 KiB
Markdown
---
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title: "Gemini Embedding"
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type: docs
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weight: 1
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description: >
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Use Google's Gemini models to generate high-performance text embeddings for vector databases.
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---
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## About
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Google Gemini provides state-of-the-art embedding models that convert text into
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high-dimensional vectors.
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### Authentication
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Toolbox uses your [Application Default Credentials
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(ADC)][adc] to authorize with the
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Gemini API client.
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Optionally, you can use an [API key][api-key] obtain an API
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Key from the [Google AI Studio][ai-studio].
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We recommend using an API key for testing and using application default
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credentials for production.
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[adc]: https://cloud.google.com/docs/authentication#adc
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[api-key]: https://ai.google.dev/gemini-api/docs/api-key#api-keys
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[ai-studio]: https://aistudio.google.com/app/apikey
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## Behavior
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### Automatic Vectorization
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When a tool parameter is configured with `embeddedBy: <your-gemini-model-name>`,
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the Toolbox intercepts the raw text input from the client and sends it to the
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Gemini API. The resulting numerical array is then formatted before being passed
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to your database source.
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### Dimension Matching
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The `dimension` field must match the expected size of your database column
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(e.g., a `vector(768)` column in PostgreSQL). This setting is supported by newer
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models since 2024 only. You cannot set this value if using the earlier model
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(`models/embedding-001`). Check out [available Gemini models][modellist] for more
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information.
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[modellist]:
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https://docs.cloud.google.com/vertex-ai/generative-ai/docs/embeddings/get-text-embeddings#supported-models
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## Example
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```yaml
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embeddingModels:
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gemini-model:
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kind: gemini
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model: gemini-embedding-001
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apiKey: ${GOOGLE_API_KEY}
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dimension: 768
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```
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{{< notice tip >}}
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Use environment variable replacement with the format ${ENV_NAME}
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instead of hardcoding your secrets into the configuration file.
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{{< /notice >}}
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## Reference
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| **field** | **type** | **required** | **description** |
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|-----------|:--------:|:------------:|--------------------------------------------------------------|
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| kind | string | true | Must be `gemini`. |
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| model | string | true | The Gemini model ID to use (e.g., `gemini-embedding-001`). |
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| apiKey | string | false | Your API Key from Google AI Studio. |
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| dimension | integer | false | The number of dimensions in the output vector (e.g., `768`). |
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