* Increase requirements for face to be set
* Manage faces properly
* Add basic docs
* Simplify
* Separate out face recognition frome semantic search
* Update docs
* Formatting
* Add basic config and face recognition table
* Reconfigure updates processing to handle face
* Crop frame to face box
* Implement face embedding calculation
* Get matching face embeddings
* Add support face recognition based on existing faces
* Use arcface face embeddings instead of generic embeddings model
* Add apis for managing faces
* Implement face uploading API
* Build out more APIs
* Add min area config
* Handle larger images
* Add more debug logs
* fix calculation
* Reduce timeout
* Small tweaks
* Use webp images
* Use facenet model
* Handle Frigate+ submitted case
* Add search settings and rename general to ui settings
* Add platform aware sheet component
* use two columns on mobile view
* Add cameras page to more filters
* clean up search settings view
* Add time range to side filter
* better match with ui settings
* fix icon size
* use two columns on mobile view
* clean up search settings view
* Add zones and saving logic
* Add all filters to side panel
* better match with ui settings
* fix icon size
* Fix mobile fitler page
* Fix embeddings access
* Cleanup
* Fix scroll
* fix double scrollbars and add separators on mobile too
* two columns on mobile
* italics for emphasis
---------
Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
* Remove device config and use model size to configure device used
* Don't show Frigate+ submission when in progress
* Add docs link for bounding box colors
* Add config option to select fp16 or quantized jina vision model
* requires_fp16 for text and large models only
* fix model type check
* fix cpu
* pass model size
* refactor dispatcher
* add reindex to dictionary
* add circular progress bar component
* Add progress to UI when embeddings are reindexing
* readd comments to dispatcher for clarity
* Only report progress every 10 events so we don't spam the logs and websocket
* clean up
* add generic onnx model class and use jina ai clip models for all embeddings
* fix merge confligt
* add generic onnx model class and use jina ai clip models for all embeddings
* fix merge confligt
* preferred providers
* fix paths
* disable download progress bar
* remove logging of path
* drop and recreate tables on reindex
* use cache paths
* fix model name
* use trust remote code per transformers docs
* ensure tokenizer and feature extractor are correctly loaded
* revert
* manually download and cache feature extractor config
* remove unneeded
* remove old clip and minilm code
* docs update
* swap sqlite_vec for chroma in requirements
* load sqlite_vec in embeddings manager
* remove chroma and revamp Embeddings class for sqlite_vec
* manual minilm onnx inference
* remove chroma in clip model
* migrate api from chroma to sqlite_vec
* migrate event cleanup from chroma to sqlite_vec
* migrate embedding maintainer from chroma to sqlite_vec
* genai description for sqlite_vec
* load sqlite_vec in main thread db
* extend the SqliteQueueDatabase class and use peewee db.execute_sql
* search with Event type for similarity
* fix similarity search
* install and add comment about transformers
* fix normalization
* add id filter
* clean up
* clean up
* fully remove chroma and add transformers env var
* readd uvicorn for fastapi
* readd tokenizer parallelism env var
* remove chroma from docs
* remove chroma from UI
* try removing custom pysqlite3 build
* hard code limit
* optimize queries
* revert explore query
* fix query
* keep building pysqlite3
* single pass fetch and process
* remove unnecessary re-embed
* update deps
* move SqliteVecQueueDatabase to db directory
* make search thumbnail take up full size of results box
* improve typing
* improve model downloading and add status screen
* daemon downloading thread
* catch case when semantic search is disabled
* fix typing
* build sqlite_vec from source
* resolve conflict
* file permissions
* try build deps
* remove sources
* sources
* fix thread start
* include git in build
* reorder embeddings after detectors are started
* build with sqlite amalgamation
* non-platform specific
* use wget instead of curl
* remove unzip -d
* remove sqlite_vec from requirements and load the compiled version
* fix build
* avoid race in db connection
* add scale_factor and bias to description zscore normalization
* Portal tooltips
* Add ability to time_range filter chroma searches
* centering and padding consistency
* add event id back to chroma metadata
* query sqlite first and pass those ids to chroma for embeddings search
* ensure we pass timezone to the api call
* remove object lifecycle from search details for non-object events
* simplify hour calculation
* fix query without filters
* bump chroma version
* chroma 0.5.7
* fix selecting camera group in cameras filter button
* Set caching options for hardware providers
* Always use CPU for searching
* Use new install strategy to remove onnxruntime and then install post wheels
* Initial re-implementation of semantic search
* put docker-compose back and make reindex match docs
* remove debug code and fix import
* fix docs
* manually build pysqlite3 as binaries are only available for x86-64
* update comment in build_pysqlite3.sh
* only embed objects
* better error handling when genai fails
* ask ollama to pull requested model at startup
* update ollama docs
* address some PR review comments
* fix lint
* use IPC to write description, update docs for reindex
* remove gemini-pro-vision from docs as it will be unavailable soon
* fix OpenAI doc available models
* fix api error in gemini and metadata for embeddings
