Remove ~170MB of model files from the repository (LFS + committed).
Models are now downloaded at runtime from Hugging Face on first use
and cached to the OS cache directory with progress reporting and retries.
- Add internal/models/download.go: runtime downloader with retry, progress bar, checksums
- Remove go:embed for ONNX models (keep tokenizers embedded)
- Use file-based ONNX session loading instead of byte-slice
- Add scripts/download-models.sh for dev/CI model setup
- Update Makefile with setup-models target
- Update workflow-prepare.sh to download models in CI
- Set lfs: false in all CI workflows
- SHA256: bge=828e14..., cross-encoder=5d3e70...
Root cause: plugin registered as directory source in known_marketplaces.json,
which gets wiped on CLI updates. Now registers in extraKnownMarketplaces
(settings.json) as a GitHub source — same mechanism caveman/context-mode use.
Binaries install to ~/.claude-mnemonic/bin/ instead of the Claude-managed
plugins directory. Thin wrapper scripts in the repo let the marketplace
clone find them. Nothing gets cleaned up when Claude refreshes its cache.
Also fixed along the way:
- ONNX Runtime 1.24.3 → 1.26.0 (API v25 mismatch broke all embedding tests)
- Vector client leaked on DB reinit, processQueue had a race on sessionManager
- reloadConfig called os.Exit(0) bypassing graceful shutdown
- Removed dead QueryRowWithTimeout that leaked contexts
- Added tests for graph/watcher/maintenance/update (all were at 0%)
* Resolves issue #13
- Switched model to bge-small-en-v1.5
- Added lazy re-embedding
- Added model version tracking per vector
- Added conversion of vectors to the new model
* Add lfs support to the workflow.
* Implements importance scoring with decay + voting #6
* Resolves issue #5 by marking observations as superseeded and scheduled for deletion
* Implement pattern detection #7
* Improve injections and observations accuracy
- Session start: Recent observations for project context (recency-based)
- User prompt: Semantically relevant observations (similarity-based with threshold)
* Added two stage retrieval with bi and cross encoder #8
* Implement query expansion and reformulation #9
* Knowledge graph and relationships ( resolves#4 )
- File Overlap Detection: Detects relationships when observations modify/read the same files
- Concept Overlap Detection: Detects relationships based on shared semantic concepts
- Type Progression Detection: Infers relationships from natural observation type progressions (e.g., discovery → bugfix = "fixes")
- Temporal Proximity Detection: Detects relationships between observations in the same session within 5 minutes
- Narrative Mention Detection: Detects explicit relationship language in narratives (e.g., "fixes", "depends on", "supersedes")
* Add visualisation of the relations to the dashboard.
* fixup! Add visualisation of the relations to the dashboard.
* Update documentation with new settings and screenshots.
lukaszraczylo