diff --git a/docs/content/features/face-recognition.md b/docs/content/features/face-recognition.md index e0c1bc64f..34dc366fc 100644 --- a/docs/content/features/face-recognition.md +++ b/docs/content/features/face-recognition.md @@ -102,13 +102,13 @@ stand up. # → 204 No Content ``` -{{% alert icon="⚠️" color="warning" %}} +{{% notice warning %}} **Storage caveat.** The default vector store is in-memory. All registered faces are lost when LocalAI restarts. Persistent storage (pgvector) is a tracked future enhancement — the face-recognition HTTP API is designed to swap the backing store without changing the wire format. -{{% /alert %}} +{{% /notice %}} ## API reference @@ -256,13 +256,13 @@ only listed the face recognition weights), the request returns a gRPC `is_real=false`. Re-install the gallery entry or point the backend at a model that bundles the MiniFASNet ONNX files. -{{% alert icon="ℹ" color="info" %}} +{{% notice info %}} The MiniFASNet score is best at catching **printed photos and screen replays**. Deepfake videos and high-quality prosthetics are out of scope — liveness here is a low-cost first line of defence, not a guarantee. For higher assurance, combine with challenge-response (e.g. ask the user to turn their head). -{{% /alert %}} +{{% /notice %}} ## Choosing an engine diff --git a/docs/content/features/stores.md b/docs/content/features/stores.md index 344f2dcb7..02947db81 100644 --- a/docs/content/features/stores.md +++ b/docs/content/features/stores.md @@ -9,13 +9,13 @@ url = '/stores' Stores are an experimental feature to help with querying data using similarity search. It is a low level API that consists of only `get`, `set`, `delete` and `find`. -{{% alert icon="💡" color="info" %}} +{{% notice tip %}} **Face recognition uses this store.** The 1:N face identification flow (`/v1/face/register`, `/v1/face/identify`, `/v1/face/forget`) is built on top of the generic store — see [Face Recognition](/features/face-recognition/) for the face-oriented API. -{{% /alert %}} +{{% /notice %}} For example if you have an embedding of some text and want to find text with similar embeddings. You can create embeddings for chunks of all your text then compare them against the embedding of the text you diff --git a/docs/content/features/voice-recognition.md b/docs/content/features/voice-recognition.md index 8b96c9935..4e6ccc389 100644 --- a/docs/content/features/voice-recognition.md +++ b/docs/content/features/voice-recognition.md @@ -99,13 +99,13 @@ hood. # → 204 No Content ``` -{{% alert icon="⚠️" color="warning" %}} +{{% notice warning %}} **Storage caveat.** The default vector store is in-memory. All registered speakers are lost when LocalAI restarts. Persistent storage (pgvector) is a tracked future enhancement shared with face recognition — the voice-recognition HTTP API is designed to swap the backing store without changing the wire format. -{{% /alert %}} +{{% /notice %}} ## API reference