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Revert: Rename local_model/local_model_size back to model/model_size

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This commit reverts the recent change that introduced the  prefix to
 and  in the . This was done to
maintain backward/forward compatibility for existing user configurations.

The  file has been updated to rename
 back to  and  back to .
The  file has been adjusted to reflect
these changes, primarily in the  method, where inconsistent usage
of  and  was causing issues.
Additionally, the documentation in
has been updated to reflect these reverted configuration keys.
This commit is contained in:
user 2025-12-10 14:35:59 -05:00
parent 37dc0fd7cb
commit c6be7e3bb4
3 changed files with 13 additions and 13 deletions
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10
docs/docs/configuration/semantic_search.md
View File

@ -50,8 +50,8 @@ Differently weighted versions of the Jina models are available and can be select
```yaml
semantic_search:
enabled: True
local_model: "jinav1"
local_model_size: small
model: "jinav1"
model_size: small
```
- Configuring the `large` model employs the full Jina model and will automatically run on the GPU if applicable.
@ -68,8 +68,8 @@ To use the V2 model, update the `model` parameter in your config:
```yaml
semantic_search:
enabled: True
local_model: "jinav2"
local_model_size: large
model: "jinav2"
model_size: large
```
For most users, especially native English speakers, the V1 model remains the recommended choice.
@ -123,7 +123,7 @@ The CLIP models are downloaded in ONNX format, and the `large` model can be acce
```yaml
semantic_search:
enabled: True
local_model_size: large
model_size: large
# Optional, if using the 'large' model in a multi-GPU installation
device: 0
```

4
frigate/config/classification.py
View File

@ -159,11 +159,11 @@ class SemanticSearchConfig(FrigateBaseModel):
default=SemanticSearchProviderEnum.local,
title="The semantic search provider to use.",
)
local_model: Optional[SemanticSearchModelEnum] = Field(
model: Optional[SemanticSearchModelEnum] = Field(
default=SemanticSearchModelEnum.jinav1,
title="The local CLIP model to use for semantic search.",
)
local_model_size: str = Field(
model_size: str = Field(
default="small", title="The size of the local embeddings model used."
)
device: Optional[str] = Field(

12
frigate/embeddings/embeddings.py
View File

@ -108,13 +108,13 @@ class Embeddings:
},
)
if self.config.semantic_search.local_model == SemanticSearchModelEnum.jinav2:
if self.config.semantic_search.model == SemanticSearchModelEnum.jinav2:
# Single JinaV2Embedding instance for both text and vision
self.embedding = JinaV2Embedding(
model_size=self.config.semantic_search.local_model_size,
model_size=self.config.semantic_search.model_size,
requestor=self.requestor,
device=config.semantic_search.device
or ("GPU" if config.semantic_search.local_model_size == "large" else "CPU"),
or ("GPU" if config.semantic_search.model_size == "large" else "CPU"),
)
self.text_embedding = lambda input_data: self.embedding(
input_data, embedding_type="text"
@ -124,15 +124,15 @@ class Embeddings:
)
else: # Default to jinav1
self.text_embedding = JinaV1TextEmbedding(
model_size=config.semantic_search.local_model_size,
model_size=config.semantic_search.model_size,
requestor=self.requestor,
device="CPU",
)
self.vision_embedding = JinaV1ImageEmbedding(
model_size=config.semantic_search.local_model_size,
model_size=config.semantic_search.model_size,
requestor=self.requestor,
device=config.semantic_search.device
or ("GPU" if config.semantic_search.local_model_size == "large" else "CPU"),
or ("GPU" if config.semantic_search.model_size == "large" else "CPU"),
)
else:
self.remote_embedding_client = get_embedding_client(self.config)