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Add config option for vertex embedding tasks (#2266)

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This commit is contained in:
Wonbin Kim
2025-02-28 18:50:05 +09:00
committed by GitHub
parent 8143f86be6
commit 6acb00731d
14 changed files with 141 additions and 48 deletions
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5
docs/components/embedders/config.mdx
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@@ -57,7 +57,10 @@ Here's a comprehensive list of all parameters that can be used across different
| `model_kwargs` | Key-Value arguments for the Huggingface embedding model |
| `azure_kwargs` | Key-Value arguments for the AzureOpenAI embedding model |
| `openai_base_url` | Base URL for OpenAI API | OpenAI |
| `vertex_credentials_json` | Path to the Google Cloud credentials JSON file for VertexAI |
| `vertex_credentials_json` | Path to the Google Cloud credentials JSON file for VertexAI | VertexAI |
| `memory_add_embedding_type` | The type of embedding to use for the add memory action | VertexAI |
| `memory_update_embedding_type` | The type of embedding to use for the update memory action | VertexAI |
| `memory_search_embedding_type` | The type of embedding to use for the search memory action | VertexAI |
## Supported Embedding Models

17
docs/components/embedders/models/vertexai.mdx
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@@ -16,7 +16,10 @@ config = {
"embedder": {
"provider": "vertexai",
"config": {
"model": "text-embedding-004"
"model": "text-embedding-004",
"memory_add_embedding_type": "RETRIEVAL_DOCUMENT",
"memory_update_embedding_type": "RETRIEVAL_DOCUMENT",
"memory_search_embedding_type": "RETRIEVAL_QUERY"
}
}
}
@@ -24,7 +27,14 @@ config = {
m = Memory.from_config(config)
m.add("I'm visiting Paris", user_id="john")
```
The embedding types can be one of the following:
- SEMANTIC_SIMILARITY
- CLASSIFICATION
- CLUSTERING
- RETRIEVAL_DOCUMENT, RETRIEVAL_QUERY, QUESTION_ANSWERING, FACT_VERIFICATION
- CODE_RETRIEVAL_QUERY
Check out the [Vertex AI documentation](https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings/task-types#supported_task_types) for more information.
### Config
Here are the parameters available for configuring the Vertex AI embedder:
@@ -34,3 +44,6 @@ Here are the parameters available for configuring the Vertex AI embedder:
| `model` | The name of the Vertex AI embedding model to use | `text-embedding-004` |
| `vertex_credentials_json` | Path to the Google Cloud credentials JSON file | `None` |
| `embedding_dims` | Dimensions of the embedding model | `256` |
| `memory_add_embedding_type` | The type of embedding to use for the add memory action | `RETRIEVAL_DOCUMENT` |
| `memory_update_embedding_type` | The type of embedding to use for the update memory action | `RETRIEVAL_DOCUMENT` |
| `memory_search_embedding_type` | The type of embedding to use for the search memory action | `RETRIEVAL_QUERY` |