ebfeb7a6bf
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>
15 lines
354 B
JSON
15 lines
354 B
JSON
{
|
|
"name": "@clawdbot/memory",
|
|
"version": "0.0.1",
|
|
"type": "module",
|
|
"description": "Clawdbot long-term memory plugin with vector search and seamless auto-recall/capture",
|
|
"dependencies": {
|
|
"@sinclair/typebox": "0.34.47",
|
|
"@lancedb/lancedb": "^0.15.0",
|
|
"openai": "^4.77.0"
|
|
},
|
|
"clawdbot": {
|
|
"extensions": ["./index.ts"]
|
|
}
|
|
}
|