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Releases · darks0l/memory-context-pipeline
Memory Context Pipeline v1.2.1
Release Notes - v1.2.1
Added
skill/scripts/orchestrate_memory_cycle.py- One-command chain: trigger -> route -> store
docs/ORCHESTRATOR.mdexamples/orchestrator-example.ps1
Why
Turns individual helpers into a practical single-step operator workflow.
Memory Context Pipeline v1.2.0
Release Notes - v1.2.0
Added
skill/scripts/validate_vision_tasks.pyfor multimodal route validationskill/scripts/enforcement_check.pyfor 10k compaction posture checksdocs/VALIDATION.mdwith tuning guidance and operator runbook
Updated
- Config template now separates text vs vision confidence thresholds
- README includes validation commands and enforcement clarification
Intent
Close the loop on:
- screenshot/vision task validation
- confidence tuning for multimodal extraction
- clear understanding of soft vs practical hard enforcement above 10k
v1.1.3 - Deterministic Multimodal Router
Release Notes v1.1.3
Added
- Deterministic multimodal branch in
context_router.py--has-imageflag for explicit image-bearing turns- vision task routing (
image-caption,screenshot-summary,ocr-extract) - route output now includes
model,fallback_chain,confidence, anddecision_trace
Improved
- Default local fallback behavior now explicit: local (
lfm2) -> premium (opus) for local-routed turns - Router output now includes
needs_premium_reviewsignal for low-confidence paths
Tests
- Added unit tests for routing behavior in
tests/test_context_router.py- premium default path
- local task path
- token threshold trigger
- image/vision routing paths
Memory Context Pipeline v1.1.2
Housekeeping release: ignore runtime .trigger_state.json files from version control.
Memory Context Pipeline v1.1.1
Release Notes - v1.1.1
Added
-
skill/scripts/auto_trigger.py- Auto-trigger decisions for channel-memory writes using:
- context-length threshold
- explicit remember intent
- periodic digest interval
- Per-channel trigger state file for throttling and consistency
- Auto-trigger decisions for channel-memory writes using:
-
docs/AUTO_TRIGGERS.md -
examples/auto-trigger-example.ps1
Improved
- Clarified automation flow from trigger decision -> memory append
- Strengthened practical path toward fully automatic channel organization
Memory Context Pipeline v1.1.0
Release Notes - v1.1.0
Added
skill/scripts/channel_memory_store.pyfor automatic channel-scoped append logsskill/references/channel_layout.mddocumenting the lean folder structureexamples/channel-memory-example.ps1for Windows usage
Channel memory layout
memory/channels/<guild_id>/<channel_id>/YYYY-MM-DD.mdmemory/channels/<guild_id>/<channel_id>/summaries/YYYY-Www.md
Design intent
- Better long-run organization for active Discord environments
- Lower retrieval noise by scoping memory per channel
- Keep writes efficient via append-only + trigger-based events
Memory Context Pipeline v1.0.1
Release Notes - v1.0.1
Changed
- Clarified 10k behavior as a soft compaction threshold (not a hard cap)
- Added practical model guidance for choosing
lfm2vsqwen3.5:35b - Added Windows
ghCLI path note for environments where GitHub CLI is installed but not on PATH
Why this matters
- Prevents confusion about strict token limits
- Helps operators pick the best local model for speed vs quality
- Reduces friction when publishing releases from Windows hosts
Memory Context Pipeline v1.0.0
Release Notes - v1.0.0
Added
- Initial
memory-context-pipelineskill - Router script (
context_router.py) - Output validator (
validate_output.py) - Worker prompt reference
- JSON schema output contract
- Config template for local/premium routing
- Packaged skill artifact support (
.skill)
Operational changes
- Discord thread-bound subagent spawn support configured
- Automatic memory flush compaction policy configured at 10k soft threshold
Recommended model strategy
- Fast path:
lfm2 - High-quality local pass (if hardware allows):
qwen3.5:35b
Known limitations
- 10k behavior is a soft compaction threshold, not a hard token firewall
- Full automation quality depends on local model health/latency