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openclaw/extensions/memory-lancedb/package.json

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feat(memory): add lifecycle hooks and vector memory plugin Add plugin lifecycle hooks infrastructure: - before_agent_start: inject context before agent loop - agent_end: analyze conversation after completion - 13 hook types total (message, tool, session, gateway hooks) Memory plugin implementation: - LanceDB vector storage with OpenAI embeddings - kind: "memory" to integrate with upstream slot system - Auto-recall: injects <relevant-memories> when context found - Auto-capture: stores preferences, decisions, entities - Rule-based capture filtering with 0.95 similarity dedup - Tools: memory_recall, memory_store, memory_forget - CLI: clawdbot ltm list|search|stats Plugin infrastructure: - api.on() method for hook registration - Global hook runner singleton for cross-module access - Priority ordering and error catching Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-18 05:40:58 +00:00
{
refactor: rename to openclaw
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"name": "@openclaw/memory-lancedb",
chore: bump version to 2026.1.30
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"version": "2026.1.30",
feat(memory): add lifecycle hooks and vector memory plugin Add plugin lifecycle hooks infrastructure: - before_agent_start: inject context before agent loop - agent_end: analyze conversation after completion - 13 hook types total (message, tool, session, gateway hooks) Memory plugin implementation: - LanceDB vector storage with OpenAI embeddings - kind: "memory" to integrate with upstream slot system - Auto-recall: injects <relevant-memories> when context found - Auto-capture: stores preferences, decisions, entities - Rule-based capture filtering with 0.95 similarity dedup - Tools: memory_recall, memory_store, memory_forget - CLI: clawdbot ltm list|search|stats Plugin infrastructure: - api.on() method for hook registration - Global hook runner singleton for cross-module access - Priority ordering and error catching Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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"type": "module",
refactor: rename to openclaw
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"description": "OpenClaw LanceDB-backed long-term memory plugin with auto-recall/capture",
feat(memory): add lifecycle hooks and vector memory plugin Add plugin lifecycle hooks infrastructure: - before_agent_start: inject context before agent loop - agent_end: analyze conversation after completion - 13 hook types total (message, tool, session, gateway hooks) Memory plugin implementation: - LanceDB vector storage with OpenAI embeddings - kind: "memory" to integrate with upstream slot system - Auto-recall: injects <relevant-memories> when context found - Auto-capture: stores preferences, decisions, entities - Rule-based capture filtering with 0.95 similarity dedup - Tools: memory_recall, memory_store, memory_forget - CLI: clawdbot ltm list|search|stats Plugin infrastructure: - api.on() method for hook registration - Global hook runner singleton for cross-module access - Priority ordering and error catching Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-18 05:40:58 +00:00
"dependencies": {
chore: update deps
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"@lancedb/lancedb": "^0.23.0",
chore: Update deps + `pnpm dedupe`.
2026-01-31 16:25:44 +09:00
"@sinclair/typebox": "0.34.48",
chore: update deps and pi model discovery
2026-01-31 06:40:45 +01:00
"openai": "^6.17.0"
feat(memory): add lifecycle hooks and vector memory plugin Add plugin lifecycle hooks infrastructure: - before_agent_start: inject context before agent loop - agent_end: analyze conversation after completion - 13 hook types total (message, tool, session, gateway hooks) Memory plugin implementation: - LanceDB vector storage with OpenAI embeddings - kind: "memory" to integrate with upstream slot system - Auto-recall: injects <relevant-memories> when context found - Auto-capture: stores preferences, decisions, entities - Rule-based capture filtering with 0.95 similarity dedup - Tools: memory_recall, memory_store, memory_forget - CLI: clawdbot ltm list|search|stats Plugin infrastructure: - api.on() method for hook registration - Global hook runner singleton for cross-module access - Priority ordering and error catching Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-18 05:40:58 +00:00
},
refactor: rename to openclaw
2026-01-30 03:15:10 +01:00
"openclaw": {
chore: update dependencies
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"extensions": [
"./index.ts"
]
feat(memory): add lifecycle hooks and vector memory plugin Add plugin lifecycle hooks infrastructure: - before_agent_start: inject context before agent loop - agent_end: analyze conversation after completion - 13 hook types total (message, tool, session, gateway hooks) Memory plugin implementation: - LanceDB vector storage with OpenAI embeddings - kind: "memory" to integrate with upstream slot system - Auto-recall: injects <relevant-memories> when context found - Auto-capture: stores preferences, decisions, entities - Rule-based capture filtering with 0.95 similarity dedup - Tools: memory_recall, memory_store, memory_forget - CLI: clawdbot ltm list|search|stats Plugin infrastructure: - api.on() method for hook registration - Global hook runner singleton for cross-module access - Priority ordering and error catching Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-18 05:40:58 +00:00
}
}
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